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Review

Climate-Driven Pest and Disease Dynamics in Greenhouse Vegetables: A Review

by
Dimitrios Fanourakis
1,*,
Theodora Makraki
1,
Theodora Ntanasi
2,
Evangelos Giannothanasis
2,
Georgios Tsaniklidis
3,
Dimitrios I. Tsitsigiannis
4 and
Georgia Ntatsi
2,*
1
Laboratory of Quality and Safety of Agricultural Products, Landscape and Environment, Department of Agriculture, School of Agricultural Sciences, Hellenic Mediterranean University, Estavromenos, 71004 Heraklion, Greece
2
Laboratory of Vegetable Production, Department of Crop Science, Agricultural University of Athens, Iera Odos 75, 11855 Athens, Greece
3
Institute of Olive Tree, Subtropical Plants and Viticulture, Hellenic Agricultural Organization ‘ELGO-Dimitra’, Kastorias 32A, 71307 Heraklion, Greece
4
Laboratory of Plant Pathology, Department of Crop Science, Agricultural University of Athens, 11855 Athens, Greece
*
Authors to whom correspondence should be addressed.
Horticulturae 2026, 12(4), 415; https://doi.org/10.3390/horticulturae12040415
Submission received: 11 February 2026 / Revised: 21 March 2026 / Accepted: 25 March 2026 / Published: 27 March 2026
(This article belongs to the Section Protected Culture)

Abstract

Greenhouse cultivation enables year-round vegetable production and high yields through precise environmental regulation. Yet, the same stable microclimate that promotes crop growth also favors the proliferation of pests and diseases. This review synthesizes current knowledge on how greenhouse climate variables govern pest and disease epidemiology in tomato, cucumber, and sweet pepper. Only greenhouse-based studies were included to ensure direct relevance to protected horticulture. Microclimatic stability determines infection probability, vector behavior, and host susceptibility. Warm, humid conditions promote fungal and bacterial pathogens, whereas dry, high vapor pressure deficit (VPD) environments favor mites and thrips and enhance virus transmission. Species-specific traits further modulate vulnerability. Tomato is dominated by virus–bacterium complexes and foliar/stem fungal diseases, cucumber by phytopathogenic fungi favored by high relative humidity (RH) and soilborne pathogens, and sweet pepper by virus–vector systems and long-cycle fungal infections. Temperature exerts the strongest influence, while RH and VPD jointly regulate surface moisture and vector activity. Light intensity and spectral composition also affect pest orientation and fungal sporulation. Integrating environmental sensing, biological control, and adaptive climate regulation offers a pathway toward preventive, climate-smart Integrated Pest Management (IPM). The review highlights the emerging role of climate-informed decision-support systems (DSSs) and the need for greenhouse-specific datasets to improve pest and disease forecasting.

1. Introduction

Greenhouse vegetable production represents one of the most intensive and high-value forms of horticulture, enabling year-round supply of fresh produce through the manipulation of temperature, relative air humidity (RH), light, and carbon dioxide [1,2]. By providing controlled environmental conditions, greenhouse cultivation increases yield stability and product quality while minimizing exposure to external climatic fluctuations [3]. However, the same microclimatic stability that favors plant growth also creates highly favorable conditions for the proliferation of pests [4,5]. According to EU plant health legislation (Regulation (EU) 2016/2031), the term ‘pests’ formally encompasses insects, mites, pathogens (including fungi, bacteria and viruses), nematodes and weeds, a definition that underpins the integrated climate-driven framework adopted in this review [6]. Constant temperatures, elevated RH, dense canopies, and limited air exchange provide ideal niches for numerous fungal, bacterial, viral, and arthropod species, many of which exhibit accelerated life cycles and increased virulence under protected conditions [2,4,5]. As a result, pest and disease management remains one of the most critical challenges in sustainable greenhouse horticulture.
Even under advanced climate control systems, pests are responsible for approximately 15–30% of potential yield losses in protected vegetable production, posing a major economic constraint to sustainable greenhouse horticulture [7,8]. These losses not only reduce profitability but also increase reliance on chemical interventions, counteracting the goals of climate-smart Integrated Pest Management (IPM) [9].
The present review focuses exclusively on studies conducted under greenhouse conditions, where the interactive effects of environmental variables and biological factors can be isolated and quantitatively assessed. While open-field research provides valuable epidemiological insights, microclimate–pest relationships in greenhouses are inherently different due to the regulated environment, high planting density, and continuous cropping cycles. In protected cultivation, diverse pest groups coexist in an artificial ecosystem where climatic regulation directly determines their survival, reproduction, and dispersal [2,4,5]. Understanding these complex interactions is therefore essential for optimizing climate management strategies and for integrating pest suppression into modern greenhouse design [2,4]. These relationships are conceptually summarized in Figure 1, which illustrates the interconnections between microclimatic factors, crop physiological responses, and pest dynamics within the greenhouse ecosystem.
Tomato (Solanum lycopersicum L.), cucumber (Cucumis sativus L.), and sweet pepper (Capsicum annuum L.) were selected as model species for this review because they dominate greenhouse vegetable production globally. These species display contrasting physiological and microclimatic requirements, which in turn shape their susceptibility to different pest and disease complexes [2,10,11]. Their combined analysis offers a representative framework for understanding how greenhouse climate modulates the biology and epidemiology of diverse biotic stress agents. To our knowledge, this is the first review that systematically synthesizes species-specific sensitivities of major pest groups, including fungi, bacteria, viruses, insects, mites, and nematodes, in relation to the controlled greenhouse environment.
This article critically synthesizes available research on how the major environmental parameters of greenhouse cultivation [i.e., air and root-zone temperature, RH, vapor pressure deficit (VPD), light intensity and spectrum, as well as CO2 concentration] affect the development, survival, and spread of key pests. Emphasis is placed on six principal biological groups (fungi, bacteria, viruses, insects, mites, and nematodes), as well as on their interactions and feedbacks with the controlled environment. Only greenhouse-based experimental and observational evidence is considered when analyzing microclimate effects on outbreaks across these biotic groups, ensuring that the conclusions are specific to protected cultivation.
The review further explores inter-group interactions (e.g., vector–virus, nematode–fungus, and secondary bacterial infections) and the reciprocal influences between microclimate regulation and pest dynamics. By integrating these aspects, it aims to provide a comprehensive understanding of how greenhouse environmental management can function not only as a driver of crop productivity but also as a tool for mitigating pest risk and reducing pesticide dependence. The synthesis presented here establishes the scientific foundation for climate-adaptive IPM and supports the transition toward resilient, sustainable and smart greenhouse production systems aligned with the objectives of the European Green Deal and Farm-to-Fork strategies. These relationships vary across greenhouse technological levels, from passive Mediterranean structures to semi-closed, high-tech systems, affecting both microclimate uniformity and pest population dynamics.

2. Species Differences in Pest Susceptibility

Tomato, cucumber, and sweet pepper are physiologically and anatomically distinct crops that respond differently to greenhouse environmental conditions [3] and, consequently, to pests [12,13,14]. These interspecific differences stem from variations in canopy structure, leaf surface characteristics, cuticular properties, stomatal behavior, phenology, and nutrient physiology, all of which influence the microclimatic boundary layer around plant organs and determine host–pest or host–vector interactions (Table 1) [15,16,17]. A synthesis of these species-specific susceptibilities to major pest groups is illustrated in Figure 2, which highlights the contrasting vulnerability of tomato, cucumber, and sweet pepper under greenhouse climatic conditions.
Tomato is a climacteric species that performs optimally at moderate air temperatures [18] and relatively dry atmospheric conditions (Table 1) [19]. Its dense canopy, hairy leaf surface, and high transpiration capacity produce heterogeneous microzones with elevated RH around internal leaves, favoring fungal pathogens (such as Botrytis cinerea, Phytophthora infestans, and Cladosporium fulvum) [10]. Tomato is particularly sensitive to viral and bacterial diseases [e.g., tomato yellow leaf curl virus (TYLCV), tomato spotted wilt virus (TSWV), Clavibacter michiganensis, Pseudomonas syringae] because these pathogens exploit wounds caused by pruning or handling, and are efficiently transmitted by common greenhouse vectors, especially whiteflies and thrips [10,13,20]. In addition to vector-borne viruses, tomato is highly susceptible to mechanically transmitted tobamoviruses, with tomato brown rugose fruit virus (ToBRFV) representing the most damaging emergent pathogen due to its exceptional surface stability and ability to overcome Tm-22 resistance [21,22], as well as pepino mosaic virus (PepMV), which is highly transmissible through mechanical means (hands, tools, etc.) and can spread rapidly once introduced into a greenhouse setting. The high nitrogen (N) demand and succulent tissues of modern cultivars also support rapid bacterial multiplication under suboptimal RH control [10,13,20]. Excess N fertilization can further increase susceptibility to bacterial diseases, including bacterial speck (Pseudomonas syringae pv. tomato) and bacterial spot (Xanthomonas spp.), by promoting lush, succulent tissues and elevated leaf surface moisture that favor bacterial colonization and infection.
Table 1. Comparative physiological and pathological traits across species under greenhouse conditions. Environmental parameters represent typical ranges considered optimal for plant growth and physiological performance in greenhouse cultivation.
Table 1. Comparative physiological and pathological traits across species under greenhouse conditions. Environmental parameters represent typical ranges considered optimal for plant growth and physiological performance in greenhouse cultivation.
ParameterTomatoCucumberSweet PepperKey References
Optimal T (°C)22–2624–2824–28[17,19,23]
Optimal RH (%)60–7070–8560–75[18,23,24]
Optimal VPD (kPa)0.7–1.00.5–0.80.6–0.9[19,25,26]
Canopy structureDense, compact, self-shadingOpen canopy, fast-growing vinesSemi-open, bushy[10,27,28]
Leaf surface traitsPubescent, moderate wax layerSmooth surface, low wax, high stomatal densityWaxy, thick cuticle[10,16,29]
Water relation sensitivityModerate; prone to condensation in dense canopyVery high; sensitive to drought and excess RHModerate; tolerates transient dryness[30,31,32]
Dominant pathogen groupsViruses: TYLCV, TSWV, ToBRFV; Bacteria: Clavibacter, Pseudomonas; Fungi: Botrytis, Phytophthora, CladosporiumFungi: Pseudoperonospora, Oidium; Bacteria: Pseudomonas; Nematodes: MeloidogyneViruses: TSWV, ToMV, PMMoV; Fungi: Leveillula taurica; Bacteria: Pectobacterium, Dickeya[13,14,20,33,34]
Key insect/mite pests and vectorsWhiteflies, thrips, aphidsWhiteflies, aphids, mitesThrips, whiteflies, aphids, mites[13,14,34]
Primary infection routesWounds and pruning injuries; high canopy RHLeaf wetness, soil saturationMechanical contact; prolonged exposure[12,13,20]
Typical microclimatic challengeInternal canopy condensationProlonged surface wetnessT fluctuations during long cycles[19,20,26,28]
Overall pest sensitivityHigh susceptibility to viral, bacterial infections and foliar/stem fungal pathogensHigh susceptibility to phytopathogenic fungal and nematode pestsModerate but long-term accumulation of pest pressure[14,33,34]
PMMoV, pepper mild mottle virus; RH, relative air humidity; T, temperature, ToBRFV, tomato brown rugose fruit virus; ToMV, tobacco mosaic virus; TSWV, tomato spotted wilt virus; TYLCV, tomato yellow leaf curl virus; VPD, vapor pressure deficit.
Cucumber differs markedly in its ecophysiological requirements and stress responses. As a fast-growing, non-climacteric species with thin, wax-poor cuticles and high stomatal density, cucumber is more prone to water-related stress and surface moisture accumulation [14,20,27,29]. It thrives under relatively humid greenhouse conditions and moderate temperatures (Table 1) [23] but becomes highly susceptible to foliar and stem pathogens (e.g., Pseudoperonospora cubensis, Oidium spp., Botrytis cinerea and Sclerotinia sclerotiorum) and to angular leaf spot (Pseudomonas syringae pv. lachrymans) under prolonged leaf wetness [14,20]. Root-zone pathogens such as Fusarium oxysporum f. sp. cucumerinum, Phytophthora spp. and root-knot nematodes (Meloidogyne spp.) are also prevalent, particularly in soil-based systems [14,35]. The rapid growth rate and high transpiration demand make cucumber highly responsive to even small microclimatic deviations, especially in poorly ventilated or over-irrigated environments [32].
Sweet pepper represents an intermediate case in terms of physiological sensitivity and pest and disease spectrum. It exhibits optimal performance under moderate greenhouse temperatures and RH (Table 1) [17,24], showing greater tolerance to transient water stress compared with cucumber [30,32]. However, its thick cuticle and waxy leaf surface are offset by long cropping cycles and continuous flowering, which extend the exposure period to thrips, whiteflies, and viruses such as TSWV, pepper yellows disease (PYD), and cucumber mosaic virus (CMV) [16,36]. Unlike tomato, pepper is less prone to severe bacterial canker but is frequently affected by fungal and bacterial diseases such as powdery mildew, soft rot, and tobamoviruses [tobacco mosaic virus (ToMV; sometimes historically referred to as TMV in older literature) and pepper mild mottle virus (PMMoV)], particularly when sanitation lapses or RH increases [20,33]. The extended harvest period and canopy longevity make pest management in pepper more dependent on sustained microclimate stability and hygiene than on short-term interventions [37].
These physiological contrasts illustrate that the same greenhouse environment can exert distinct epidemiological pressures depending on the crop species and species variety or hybrid. Consequently, designing climate control strategies requires species-specific optimization of temperature, RH, and VPD targets to maintain both plant productivity and phytosanitary safety.
The three crops under consideration exhibit divergent physiological behaviors that define their relative vulnerability to specific biotic stresses. Tomato is dominated by virus- and bacteria-associated complexes, cucumber by fungal and soilborne pathogens, and sweet pepper by virus–vector systems and long-cycle fungal infections. These differences underscore the need for species-tailored climate management and adaptive IPM protocols that integrate crop-specific temperature, RH, and ventilation regimes into pest control strategies.

3. Major Fungal Pathogens

Fungal pathogens represent the most pervasive and damaging biotic agents in greenhouse vegetable cultivation [2,5]. Species-specific susceptibilities to major pest groups are summarized in Section 2 and Table 1 and are therefore not repeated here. Their development is highly sensitive to the greenhouse microclimate, particularly to the interaction of temperature, RH, and VPD, which collectively regulate spore germination, infection processes, and secondary dispersal (Table 2) [4,5,37]. Additional secondary or regionally restricted fungal pathogens of these crops are listed in Supplementary Table S1, which indicates that most of these pathogens become problematic under warm conditions (22–30 °C) combined with high RH (>85%) and low VPD (<0.6 kPa). These thresholds highlight that dense canopies, limited ventilation, and prolonged leaf wetness create favorable microhabitats for secondary fungal infections. Accordingly, improving air circulation and maintaining a moderate VPD (≈0.6–1.0 kPa) are common preventive strategies across crops. Even brief periods of leaf wetness under such conditions can trigger epidemics, making environmental control the cornerstone of sustainable disease management [2,4,5].
Gray mold caused by B. cinerea is among the most destructive fungal pathogens in greenhouse systems, particularly in crops with dense canopies and high internal humidity (see Section 2; Table 1) [5,38]. It affects all three crops, infecting flowers, stems, and fruits under cool, humid conditions typical of poorly ventilated greenhouse environments (Table 2) [39,40]. Pathogen outbreaks coincide with condensation events on plant surfaces or with senescent tissue accumulation [5,39,40]. The pathogen produces abundant airborne conidia that infect through wounds or decaying petals [5,39]. Control relies on maintaining a moderate VPD and preventing leaf wetness through nighttime ventilation–heating cycles, together with the regular removal of senescent or infected tissues to minimize inoculum sources and fungicide applications [5,40].
Powdery mildew, primarily caused by Leveillula taurica in tomato and pepper [41,42], and by Podosphaera xanthii or Golovinomyces cichoracearum (Oidium spp., the anamorph of the fungus) in cucumber [43], develops under warm conditions and fluctuating RH typical of greenhouse environments (Table 2) [42]. Unlike most foliar fungi, it does not require free water for infection and can progress rapidly in shaded or poorly ventilated canopies [42,44]. Strong RH variation, low ultraviolet (UV) radiation, and dense foliage enhance disease severity. Preventive measures include maintaining stable RH, ensuring sufficient light intensity or controlled UV-B exposure, and avoiding excessive canopy density, complemented when necessary, by preventive fungicide treatments [41,42,44].
In cucumber, downy mildew caused by P. cubensis thrives in cool, humid environments with prolonged leaf wetness (Table 2) [45,46]. This oomycete is particularly problematic during late-winter and early-spring cycles when night condensation and limited ventilation persist [46,47]. Pathogen development is minimized by maintaining slightly warmer night temperatures, ventilating before sunrise, and irrigating early in the day to promote rapid leaf drying [44,46]. In tomato, downy mildew is caused by Phytophthora infestans, a devastating oomycete that causes late blight, characterized by dark leaf lesions with white sporulation on the abaxial surface under humid conditions and firm, brown fruit lesions, leading to rapid plant death and significant yield loss [13,20]. High RH and the presence of free water are essential for infection and spore dispersal, while sporulation is favored under cool, moist conditions and lesion expansion occurs more rapidly at moderately warm temperatures. Integrated management relies on strict sanitation, climate control (low RH, good airflow, heating), resistant varieties, pathogen-free transplants, proper watering, and primarily preventive fungicide applications [20,34]
In tomato, leaf mold caused by Cladosporium fulvum (syn. Passalora fulva) occurs in greenhouses under warm and humid conditions typical of poorly ventilated canopies (Table 2) [20,48]. The fungus infects mainly the lower canopy, producing yellow patches and gray sporulation on the abaxial leaf surface [13,20,48]. Preventive strategies focus on reducing canopy RH through improved ventilation, removing lower leaves to improve air exchange, and applying preventive fungicide treatments [20,48].
Fusarium wilt, incited mainly by F. oxysporum f.sp. lycopersici in tomato [49] and F. oxysporum f.sp. capsici in pepper [50], is a soilborne vascular fungal pathogen favored by warm root-zone conditions, excessive substrate moisture, and elevated electrical conductivity (EC) (Table 2) [20,51]. Infected plants show progressive wilting and vascular browning caused by xylem blockage [49,51]. Control depends on maintaining well-drained substrates, moderating irrigation frequency, and employing resistant rootstocks or grafted plants [49,51].
Root and stem rots caused by Pythium spp. and Phytophthora spp. are widespread in all three crops, particularly during seedling and early vegetative stages [52,53,54]. These oomycetes thrive in cool, waterlogged substrates with limited oxygen diffusion (Table 2) [52,54]. Symptoms include damping-off, stunted growth, and basal stem necrosis [52,55]. Preventive measures involve substrate heating, improved drainage, and avoidance of over-irrigation or excessive fertigation volumes [52,53,54].
Finally, white mold caused by Sclerotinia sclerotiorum affects stems and fruits of all three crops [56,57]. White mold is a devastating fungal pathogen appearing as soft, watery lesions with white, cottony growth on stems (especially near the soil), leading to plant wilting, girdling, and eventual death. It is promoted by cool, humid microclimates and dense canopies with poor air movement [57]. The fungus forms persistent survival structures (sclerotia) that can remain viable in the soil for years and thus complicate eradication once the pathogen becomes established [57,58]. Greenhouse management should include sanitation of plant residues, maintaining low canopy RH through ventilation, the use of preventive chemical or biological fungicides, soil solarization and periodic heating–ventilation cycles to limit mycelial spread and the formation of sexual fruiting bodies (apothecia) [56,57,58].
Overall, the incidence and severity of fungal diseases in greenhouse vegetables are dictated by the microclimatic moisture regime, principally the interaction of temperature and RH that determines VPD. Airborne fungi (e.g., Botrytis, Phytophthora infestans, Cladosporium, and Leveillula) prevail under cool, humid conditions with prolonged leaf wetness, whereas soilborne pathogens (e.g., Fusarium, Pythium, Phytophthora) thrive in saturated substrates with warm root zones. Maintaining a moderate VPD, ensuring uniform air circulation, and avoiding late-day irrigation remain the most effective preventive strategies. Supplementary measures, including sanitation, balanced fertigation, resistant cultivars and chemical/biological fungicide treatments, complete an integrated approach to fungal pathogen management in greenhouse vegetable cultivation.

4. Major Bacterial Pathogens

Bacterial pathogens constitute major constraints in intensive greenhouse vegetable production, where warm and humid microclimates, frequent plant contact, and high plant densities enhance pathogen survival and spread (Table 3) [20,62]. Species-specific susceptibilities to major pest groups are summarized in Section 2 and Table 1 and are therefore not repeated here. Secondary or sporadically reported bacterial pathogens, along with their microclimatic thresholds, are summarized in Supplementary Table S2, which indicates that most bacterial infections are favored by moderate to warm temperatures (≈18–30 °C) combined with high RH (>85–90%) and very low VPD (<0.5–0.6 kPa). These conditions promote the formation and persistence of surface water films that facilitate bacterial multiplication and dispersal. Consequently, preventing condensation and maintaining adequate air circulation are key preventive measures across greenhouse vegetable crops. Bacterial proliferation is strongly promoted by surface moisture, condensation, and aerosols generated by irrigation or handling [31]. Unlike fungi, bacteria lack airborne spores. Consequently, epidemics depend on free water films, splash droplets, and mechanical transmission [20,62]. Greenhouse practices that minimize leaf wetness, enhance air circulation, and maintain an optimal VPD are therefore central to prevention [2,20].
Bacterial speck, caused by P. syringae pv. tomato, occurs mainly under cool, humid conditions (Table 3) [13,63]. Infections develop when free water persists on leaf surfaces or when small wounds arise from handling or abrasion [13,20,63]. Outbreaks are most severe during nocturnal condensation [13,20]. Effective suppression requires reducing canopy wetness through timely ventilation and heating cycles, avoiding overhead irrigation, ensuring leaf surfaces dry completely before nightfall, using resistant varieties, and applying preventive copper-based products or other biological plant protection products (e.g., Bacillus amyloliquefaciens) [13,20,63].
Bacterial spot, caused by Xanthomonas euvesicatoria, X. vesicatoria, and X. gardneri, affects both tomato and sweet pepper [13,64,66]. The pathogen proliferates under warm, moist conditions (Table 3) and spreads rapidly by water splash or mechanical contact in dense canopies [64,66]. Extended fog or mist irrigation markedly increases disease incidence [64,66]. Management focuses on maintaining low canopy RH, enhancing canopy air movement to prevent humid stagnation, using resistant varieties, and applying preventive copper-based products or plant resistance inducers (e.g., laminarin) [64,65,66].
Bacterial canker, caused by C. michiganensis subsp. michiganensis, is a systemic vascular disease of tomato introduced primarily through contaminated seed, transplants, or pruning tools [67,68]. The pathogen spreads mechanically, especially when foliage is moist, and symptoms intensify under warm conditions (Table 3) [20,67,68,69]. Since curative options are limited, prevention relies on strict sanitation and disinfection of tools, prompt removal and destruction of infected plants once symptoms appear, and maintaining low canopy RH through adequate ventilation to minimize bacterial proliferation [20,67,68,69].
In cucumber, angular leaf spot caused by P. syringae pv. lachrymans develops under cool, humid environments with extended leaf wetness (Table 3) [71,72]. Outbreaks are rare when air movement is sufficient and leaf wetness duration remains below 8 h [70,71]. Preventive measures include morning irrigation, adequate ventilation, avoidance of nocturnal condensation, use of resistant varieties and application of preventive copper-based products or plant defense inducers (e.g., acibenzolar-S-methyl) [33,70].
The soft rot and pith necrosis complexes, primarily involving Pectobacterium carotovorum, Dickeya chrysanthemi, and several Pseudomonas spp., affect stems and fruits of all three crops [74,75]. These bacteria proliferate rapidly when free water persists on tissues under warm greenhouse conditions (Table 3), consistent with the microclimatic susceptibilities described in Section 2 [74,75]. The coexistence of high RH and wounding creates ideal infection conditions [70,74]. Control emphasizes minimizing tissue damage, using clean planting material, strict sanitation and disinfection of tools, prompt removal and destruction of infected plants once symptoms appear, maintaining stable greenhouse temperatures, and ensuring rapid drying of plant surfaces through continuous air exchange [74,75].
The greenhouse microclimate exerts a decisive influence on bacterial epidemiology. RH and leaf wetness duration are the principal factors governing infection probability. Maintaining RH below 85% and preventing condensation events are key to outbreak prevention. Temperature interacts with RH by influencing bacterial multiplication and host susceptibility. Pseudomonas and Clavibacter species favor mild to warm conditions, whereas Xanthomonas and Pectobacterium thrive at higher temperatures coupled with surface moisture. Air movement remains a simple yet powerful mitigation tool, as active convection prevents the formation of water films on foliage. Drip irrigation is therefore preferred over overhead systems to minimize splash dissemination. Because high RH amplifies cross-contamination risks, climatic regulation must always be complemented by rigorous sanitation, including tool disinfection and waterline cleaning.
In summary, bacterial diseases in greenhouse vegetables are primarily linked to persistent surface moisture, which facilitates entry and spread of pathogens through stomata or wounds. The cornerstone of management is minimizing leaf wetness and maintaining moderate RH through coordinated ventilation, heating, and drip irrigation. Complementary hygiene measures such as seed disinfection, tool sterilization, and removal of infected plants further restrict inoculum sources. The integration of microclimate control with strict sanitation enables effective suppression of bacterial diseases in all three crops without reliance on intensive chemical protection.

5. Major Viral Diseases

Viral diseases represent one of the most serious challenges in protected vegetable cultivation due to their capacity for rapid spread through insect vectors (e.g., whiteflies, thrips, and aphids) [76,77]. Species-specific susceptibilities to major pest groups are summarized in Section 2 and Table 1 and are therefore not repeated here. Most greenhouse viruses depend on living vectors for transmission, although several economically important viruses (e.g., PepMV, PMMoV, ToMV, ToBRFV) are efficiently transmitted mechanically and remain strongly influenced by host physiological status for replication and symptom expression (Table 4) [76,77]. Secondary or sporadically reported viral pathogens, together with their microclimatic thresholds, are summarized in Supplementary Table S3, which indicates that most viral outbreaks are indirectly governed by climatic conditions that regulate vector activity and plant physiological status. In general, moderate to warm temperatures (≈18–28 °C) combined with moderate RH (≈60–85%) favor vector survival, feeding activity, and virus transmission, whereas abrupt fluctuations in temperature or RH may reduce vector efficiency and viral spread. Consequently, stabilizing greenhouse microclimate and limiting vector access are key preventive strategies across crops. The greenhouse environment itself, characterized by stable temperature, high planting density, and limited air exchange, often provides favorable conditions for vector proliferation and movement [78,79]. However, the magnitude and pattern of these interactions vary across greenhouse technological levels: passive or naturally ventilated structures typical of Mediterranean regions exhibit greater temperature and RH fluctuations than high-tech, semi-closed systems with active climate control, resulting in distinct vector and virus dynamics [4,80]. Environmental factors including temperature, light intensity, and RH influence both vector activity and viral replication [77,78]. Because no curative measures exist once infection occurs, the prevention of viral diseases in greenhouses relies on strict hygiene, effective vector exclusion, resistant cultivars, and microclimate management that suppresses vector abundance and infection efficiency [76,77,78]. As the biology and climate responses of the major insect vectors (whiteflies, thrips, and aphids) are discussed in detail in Section 6, the present section focuses primarily on viral epidemiology and host–virus interactions.
TYLCV, transmitted persistently by the silverleaf whitefly Bemisia tabaci, is the most destructive viral pathogen of tomato, causing leaf curling and yellowing, interveinal and marginal leaf yellowing (chlorosis), stunting, leaf distortion, and reduced yield [81,83]. Epidemics typically occur during warm greenhouse conditions favorable to whitefly activity (Table 4) [81,83]. The climatic drivers of whitefly population dynamics are discussed in detail in Section 6. Dense canopies, weak air movement, and UV-blocking films enhance vector retention and virus spread [81,84]. Control measures include maintaining moderate greenhouse temperatures, improving air circulation, using UV-transmitting cover materials that disrupt vector orientation, deploying yellow sticky insect traps, installing insect-proof screens to prevent whitefly entry, and introducing natural enemies of B. tabaci as part of an IPM strategy [83,115].
TSWV, transmitted by the western flower thrips Frankliniella occidentalis, affects both tomato and sweet pepper [85,86]. TSWV-infected fruits can be deformed, stunted, and develop raised bumps, necrotic spots, or yellow/brown ring patterns that make them unmarketable. Stunting of the entire plant is common, especially if infected at a young stage. TSWV predominates during spring and summer cycles (Table 4) [85,87]. Conditions that favor thrips activity, such as relatively dry air and high light intensity, can enhance virus transmission (see Section 6 for details on thrips ecology and climate responses) [86,88,89]. The virus is incurable in infected plants, making prevention and vector control the primary management strategies. Maintaining moderate RH and avoiding excessive canopy dryness can significantly suppress thrips mobility [87,89]. Fine-mesh insect screens, colored sticky traps, resistant varieties, and removal of alternative hosts such as weeds further decrease disease pressure [85,87,88].
Pepino mosaic virus (PepMV) is a highly infectious virus and has emerged as one of the most economically significant viruses of greenhouse tomato production [90,92]. It causes mosaic and distortion symptoms and spreads mechanically via tools, clothing, and pollinators (e.g., bumblebees) [20,90]. Its genetic complexity and multiple strains make control challenging [91,92]. The virus persists readily in greenhouse environments and remains stable in contaminated plant debris or on surfaces for prolonged periods [20,90]. The high temperatures and light intensity characteristic of the Mediterranean summer can suppress or mask leaf symptoms, making disease detection more difficult during warmer months [90]. This means that PepMV-infected plants may appear asymptomatic in summer conditions despite harboring viable virus, creating a hidden epidemiological reservoir.
In a greenhouse environment, the virus is highly sensitive to the balance between plant stress and environmental stability. Symptom expression is strongly influenced by plant physiological status and environmental conditions (Table 4). PepMV symptoms are most severe when the host plant is under physiological stress. Under cooler, low-light conditions typical of autumn and winter, the most visible leaf symptoms appear, such as distorted, thin top leaves and yellow mosaic patterns [90,92]. When the plant is heavily laden with fruit and faces high heat and high RH, the virus often re-emerges, leading to severe fruit marbling, blotchy ripening, and flame-like discoloration patterns that make the fruit unmarketable [91,92].
The rate of spread is largely driven by mechanical activity rather than climate alone. To minimize the impact of PepMV, maintaining stable greenhouse conditions that reduce plant stress is recommended. Essential management measures include strict hygiene practices, sanitation of tools and working surfaces (e.g., skim milk or bleach solutions used for disinfection), the use of virus-free transplants, and the adoption of tolerant or resistant cultivars where available [91,92].
Tomato infectious chlorosis virus (TICV) and tomato chlorosis virus (ToCV) are also significant threats to greenhouse tomato production worldwide, both transmitted exclusively by whiteflies in a semi-persistent manner [96,116,117]. The diseases they cause are often indistinguishable based on visual symptoms alone and can result in substantial yield losses [98,117]. TICV is transmitted exclusively by the greenhouse whitefly Trialeurodes vaporariorum [96,116]. ToCV has a broader range of vectors, including the greenhouse whitefly, the silverleaf whitefly (Bemisia tabaci), and the banded-wing whitefly (Trialeurodes abutilonea) [117,118]. Neither virus is mechanically transmitted through handling of plants or tools, nor are they known to be seed-borne [95,116]. Spread within and between greenhouses occurs through the movement of infected whiteflies and the transport of infected plants [98,117]. Both viruses also infect a wide range of common weeds, which can act as reservoirs of infection outside the greenhouse environment [97,118].
Vector control is therefore the key management strategy and should include the use of physical barriers (such as high-quality greenhouse screens), biological control agents (e.g., the parasitic wasp Encarsia formosa), and insecticides. Cultural practices include the use of certified healthy seedlings for transplanting, the prompt removal and destruction of infected plants, suppression of whitefly populations, and limitation of alternative host plants (weeds) around the greenhouse. Both viruses (TICV and ToCV) are considered as quarantine pathogens in certain regions [e.g., the EPPO (European and Mediterranean Plant Protection Organization) region], and suspected outbreaks must be reported to local plant health authorities [97,116,117,118].
In cucumber, CMV is one of the most widespread pathogens, transmitted non-persistently by aphids (e.g., Myzus persicae) [99,101]. CMV has an exceptionally broad host range (over 1200 species) and can cause substantial yield losses and unmarketable produce in greenhouses. Transmission occurs within seconds during brief probing of plant tissues, and the virus spreads most rapidly under moderate greenhouse conditions favorable to aphid activity (Table 4; see Section 6 for details on aphid ecology and its climatic drivers) when aphid populations are abundant [99,102]. Preventive measures emphasize physical exclusion through insect-proof vents, maintenance of insect-free entry zones, resistant cultivars, and prompt removal of symptomatic plants to eliminate local inoculum sources [99,100]. Because transmission is non-persistent, chemical aphid control is largely ineffective [103].
A second important cucurbit virus, cucumber vein yellowing virus (CVYV), is transmitted semi-persistently by B. tabaci [76,106]. The disease predominates under warm greenhouse conditions favorable to whitefly activity (Table 4) [105], when whitefly densities peak during spring and summer [106,107]. Temperature moderation through adequate ventilation, the use of reflective mulches that reduce vector landing, and deployment of UV-transmitting or photo-selective films can effectively lower transmission rates and crop losses [76,104,106]. Further details on whitefly ecology and climate responses are provided in Section 6.
In sweet pepper, PMMoV and ToMV remain major threats due to their extreme stability and ease of mechanical transmission [109,110]. Unlike vector-borne viruses, these tobamoviruses spread through direct contact with contaminated tools, hands, or substrates [109,110]. Their persistence is enhanced under warm and humid conditions (Table 4), which prolong virus survival on contaminated surfaces [108,109]. Management is entirely preventive and relies on strict sanitation, including the disinfection of tools and gloves, the avoidance of handling wet plants, the immediate removal of infected material to prevent mechanical spread, and the use of resistant cultivars [109,110].
Mixed viral infections, such as TSWV combined with PMMoV in pepper or TYLCV co-occurring with CMV in tomato, are increasingly reported under fluctuating greenhouse climates [119]. Transient temperature and RH shifts can alter vector feeding behavior and host physiology, thereby facilitating co-infection and synergistic symptom expression [108,120]. Such combinations often exacerbate yield and quality losses beyond those caused by single infections, while complicating diagnosis and control [107]. Therefore, maintaining stable microclimatic conditions and ensuring rigorous vector exclusion are essential to minimize the likelihood and impact of mixed viral epidemics.
ToBRFV has recently emerged as one of the most damaging viral pathogens in greenhouse tomato [111,113]. As a tobamovirus, it is transmitted exclusively through mechanical means (i.e., contaminated tools, hands, gloves, stakes, substrates, or plant-to-plant contact) and displays exceptional stability on greenhouse surfaces, remaining infectious for weeks to months [113]. Warm and humid conditions (Table 4) prolong virus persistence on tools and benches, while dense canopies and intensive crop handling during pruning or harvesting accelerate local spread [111]. ToBRFV breaks the classical Tm-22 resistance gene, leading to severe fruit rugosity, discoloration, deformation, and market rejection [17,111,114]. Because no curative measures exist, management relies entirely on strict sanitation, including the avoidance of handling wet plants, the use of disposable or disinfected gloves, regular tool sterilization, and the immediate removal of infected plants to prevent further mechanical transmission [112,114].
The dynamics of viral diseases in greenhouse vegetables are strongly determined by the interaction between environmental factors and vector biology. Temperature is the dominant climatic driver, regulating both vector population growth and viral replication within host tissues. The detailed climatic responses of whiteflies, thrips, aphids, and other arthropod vectors are discussed in Section 6, while the present section emphasizes their implications for virus epidemiology. Generally, warm conditions favorable to vector development (Table 4) accelerate virus accumulation and increase feeding and reproductive activity of whiteflies and thrips, whereas extreme heat may reduce vector fecundity but often intensifies symptom expression. RH and VPD further modulate vector behavior. Low RH and high VPD enhance thrips and whitefly flight, while moderate RH promotes aphid activity. Maintaining RH within moderate ranges provides an effective balance between suppressing vectors and avoiding conditions conducive to fungal disease. The RH range required to suppress vectors partially overlaps with the thresholds associated with fungal disease development, underscoring the need for dynamic VPD control rather than fixed RH targets.
Light intensity and spectral composition also influence vector behavior and virus transmission [107,112]. UV-blocking films can reduce virus spread by altering insect navigation cues but may inadvertently increase powdery mildew incidence [80,121]. Conversely, UV-transmitting or photo-selective films maintain adequate radiation while disrupting vector orientation, offering an environmentally benign strategy for disease suppression [112,121]. Recent studies further indicate that LED-based spectral management can modulate vector activity [109,117]. Targeted UV-A radiation (365–400 nm) disrupts orientation and feeding of whiteflies and thrips [121,122], whereas far-red enrichment (>700 nm) alters host-seeking and oviposition behavior [123]. Although evidence remains limited, the controlled application of UV-A or far-red wavelengths represents a promising non-chemical complement to vector exclusion and biological control, particularly under low natural radiation conditions in multilayer greenhouse systems. Adequate air movement and ventilation further prevent vector aggregation by dissipating localized heat and excess CO2 accumulation [107].
In summary, viral diseases in greenhouse vegetables are governed by the interplay between climate and vector ecology. Warm and moderately dry conditions favorable to vector development (Table 4) promote the proliferation of thrips, whiteflies, and aphids, thereby enhancing transmission efficiency. Dense canopies with limited air circulation exacerbate infection risk by providing favorable microhabitats for vectors. Because post-infection control is impossible, prevention must focus on vector exclusion, sanitation, and climate regulation. Maintaining RH within moderate ranges and moderating temperature within ranges unfavorable to excessive vector proliferation (Table 4), together with ensuring continuous air circulation, reduce both vector activity and viral pressure. The combined implementation of UV-transmitting or photo-selective covers, fine-mesh screens, reflective mulches, and rigorous hygiene protocols constitutes the most effective and sustainable framework of cultural management strategies for minimizing viral disease outbreaks in greenhouse vegetable cultivation.

6. Insects, Mites and Nematodes

Insects, mites and nematode pests remain persistent and economically significant threats in greenhouse vegetable production [8,124]. Species-specific susceptibilities to major pest groups are summarized in Section 2 and Table 1 and are therefore not repeated here. The stable environmental conditions of protected cultivation, characterized by moderate to high temperature, abundant host biomass, and limited natural enemy activity, provide an ideal refuge for polyphagous species such as whiteflies, thrips, aphids, mites, and root-knot nematodes (Table 5) [8,124]. Several of these arthropods, particularly whiteflies, thrips, and aphids, also act as vectors of economically important plant viruses. The epidemiology and management of the corresponding viral diseases are discussed in Section 5. Secondary or sporadically observed insects, mites, and nematodes, together with their microclimatic thresholds, are summarized in Supplementary Table S4, which indicates that most secondary arthropod pests proliferate under warm temperatures (≈20–30 °C) combined with moderate to low RH (≈40–70%) and elevated VPD (>0.8–1.2 kPa), conditions that accelerate development, reproduction, and dispersal. In contrast, slightly higher RH and moderated temperature can suppress population growth of several pests, particularly thrips and spider mites. These patterns highlight that maintaining moderate RH, avoiding excessive heat accumulation, and ensuring adequate air circulation represent important preventive strategies for limiting arthropod pest outbreaks in greenhouse systems. Unlike open-field systems, where seasonal extremes suppress populations, the greenhouse microclimate supports continuous reproduction and overlapping generations [8,124]. Temperature, RH, light intensity, and air movement jointly determine the developmental rate, fecundity, and dispersal behavior of arthropods and nematodes [8,125,126]. Effective management therefore requires maintaining an environment that is optimal for crop growth but suboptimal for pest proliferation, integrating climate regulation with biological, chemical, and cultural control strategies [8].
Whiteflies, principally B. tabaci and Trialeurodes vaporariorum, are among the most destructive pests in all three crops [127,129]. Populations expand rapidly under warm greenhouse conditions favorable to whitefly development (Table 5) and low to moderate RH [131,166]. In addition to direct feeding damage and honeydew deposition, whiteflies serve as vectors of several viruses, including TYLCV, TICV, ToCV and CVYV [118,128]. Outbreaks are most frequent during summer and under UV-blocking films that reduce natural deterrence [104,127,131,132]. Preventive management includes temperature moderation, enhancing air movement to disturb flight activity, employing UV-transmitting or photo-selective covers, and integrating biological control agents (e.g., Encarsia formosa or Eretmocerus eremicus) with sticky traps and insect-proof screens [129,130,131].
Another key pest specific to tomato is the tomato leaf miner (Tuta absoluta), which thrives under warm greenhouse conditions favorable to rapid development (Table 5) and moderately dry environments [134,135]. Its development accelerates with temperature, completing up to 10–12 generations annually in Mediterranean regions [167]. Poor ventilation and dense canopies promote adult activity and oviposition on leaf undersides [167]. Infestation risk is highest in summer and under low RH and high VPD conditions (Table 5) [135,137]. Climate-based management includes maintaining moderate RH (60–70%), lowering temperature peaks through ventilation, and using light traps or pheromone mass-trapping systems in combination with biological control agents (e.g., Nesidiocoris tenuis, Trichogramma achaeae) [136,137,138].
Thrips, mainly F. occidentalis, are equally problematic, particularly in pepper and tomato [140]. Their reproduction accelerates under moderate to warm greenhouse conditions favorable to thrips development (Table 5) and low RH conditions typical of spring and summer [89,140,143]. Feeding causes flower and fruit scarring and facilitates transmission of TSWV [159]. Infestations intensify under high irradiance and elevated VPD conditions (Table 5) [87,89,141]. Management emphasizes maintaining RH within moderate ranges, increasing canopy moisture without condensation, and using fine-mesh insect screens and colored sticky traps to intercept incoming adults [89,142].
Aphids, including M. persicae and Aphis gossypii, colonize all three crops and reproduce rapidly under mild greenhouse conditions favorable to aphid development (Table 5) and moderate RH [144,145,150]. Infestations lead to sap loss, honeydew accumulation, and transmission of viruses such as CMV [168]. Rapid population buildup occurs in poorly ventilated structures [144,146,150]. Prevention relies on excluding winged aphids via screened vents, avoiding excessive N fertilization, and promoting biological control through releases of parasitoids (e.g., Aphidius colemani) or predators (e.g., Chrysoperla carnea) [147,148].
The two-spotted spider mite (Tetranychus urticae) is one of the few arthropods that thrives under hot and dry conditions (Table 5) [151,152]. Populations often surge in tomato and cucumber during summer when high VPD and strong irradiance desiccate foliage [151,153]. Under such conditions, populations can expand rapidly and complete a generation in 1–2 weeks. Mite feeding causes fine chlorotic speckling, bronzing, leaf drying, and webbing, reducing photosynthetic activity and inducing chlorotic stippling. Maintaining moderate RH, reducing plant water stress, and fostering predatory mites (e.g., Phytoseiulus persimilis, Amblyseius swirskii) are the most effective climate-compatible approaches [154,155]. Excessive dehumidification, although useful against fungal diseases, can inadvertently favor mite outbreaks, highlighting the need for balanced VPD control.
Other sporadic but significant pests include leafminers (Liriomyza trifolii, L. huidobrensis) and fungus gnats (Bradysia spp.), which exploit warm, humid microclimates and organic substrates [156,158,169]. Their populations can be reduced by maintaining substrate aeration, avoiding prolonged wetness, and the use of entomopathogenic nematodes (Steinernema feltiae) as biological control agents [157,159,160,161].
Belowground, root-knot nematodes (Meloidogyne incognita, M. javanica) represent a major constraint in all three crops cultivated in soil or unsterilized substrates [162,163]. Nematode activity and reproduction intensify under warm root-zone temperatures (25–30 °C) and adequate moisture, conditions typical of greenhouse systems [162,163]. Infested plants exhibit root galls, stunted growth, and increased susceptibility to Fusarium and Ralstonia infections [127,163]. Because chemical nematicides are limited, management focuses on crop rotation with non-host species, soil solarization, biological antagonists (e.g., Paecilomyces lilacinus), and resistant or grafted rootstocks to sustain yield under infestation pressure [162,164,165].
The abundance and distribution of insect pests and nematodes in greenhouses are closely regulated by microclimatic conditions. Temperature exerts the greatest influence, directly determining development rates and reproductive potential. For instance, the generation time of B. tabaci shortens from 30 days at 20 °C to less than 15 days at 30 °C [170,171]. Detailed thermal thresholds and degree-day (DD) requirements for the major arthropod pests are summarized in Supplementary Table S5, which shows that most greenhouse arthropods develop optimally between 24 and 32 °C and require approximately 120–400 DD per generation depending on species, thereby providing a quantitative basis for predictive, climate-based IPM scheduling and early-warning models. RH interacts with temperature via its impact on water balance and activity patterns. Low RH and high VPD favor mites and thrips but suppress entomopathogenic fungi used in biological control, whereas excessive RH restricts insect flight yet promotes fungal pathogens [141]. Thus, maintaining a moderate VPD range (0.6–1.0 kPa) is essential to balance pest suppression with crop health.
Light intensity and spectral composition further influence pest orientation. Whiteflies and aphids are attracted to yellow–green wavelengths, while thrips respond to blue and UV radiation cues [172,173]. The use of UV-absorbing or photo-selective films can disrupt visual orientation and reduce vector activity [174]. Air movement, achieved through horizontal airflow fans or ventilation, reduces localized heat and RH stratification, diminishing microhabitats favorable to pests.
For nematodes, soil temperature and moisture are decisive [163]. Sustained root-zone temperatures above 25 °C accelerate reproduction, while periodic drying or controlled substrate heating can suppress nematode populations [162,163,165]. Soil solarization and maintaining slightly drier conditions between irrigations can effectively reduce egg hatch and juvenile survival [163,164].
Overall, environmental regulation combined with biological control offers a sustainable approach for pest and nematode management. Integrating climate management with natural enemies, selective physical barriers, and resistant rootstocks enables durable suppression without compromising crop physiology. Insect pests and nematodes in greenhouse vegetables are primarily governed by temperature, RH, and light regime, which together determine their development and distribution. Whiteflies, thrips, aphids, and mites thrive under warm, dry conditions, whereas nematodes favor warm, moist substrates. Because these parameters are inherent to protected cultivation, microclimate regulation is a cornerstone of IPM. Maintaining moderate temperatures, balanced RH, and sufficient air movement reduces pest fecundity and mobility. Complementary strategies such as biological control, physical exclusion, and sanitation further enhance resilience against infestations. Collectively, these measures establish a climate-responsive IPM framework capable of suppressing arthropod and nematode populations while minimizing chemical inputs in greenhouse vegetable cultivation.

7. Interactions Among Pest Groups

The pest groups described in the previous sections rarely occur in isolation in greenhouse systems. Their interactions, often mediated by plant physiological responses and microclimatic conditions, can significantly influence outbreak dynamics and management outcomes. The coexistence of multiple pest groups within the greenhouse ecosystem generates complex interaction networks, where the activity of one group often facilitates or suppresses another (Table 6) [160,161,162]. A detailed overview of cross-group interaction types is provided in Supplementary Table S6, which indicates that many pest outbreaks arise from synergistic or sequential interactions among pathogens, insects, and nematodes that are strongly influenced by greenhouse microclimatic conditions. Warm temperatures (≈25–30 °C), high RH, and stable canopy environments often promote facilitative interactions, such as vector-mediated virus transmission or fungal–bacterial disease complexes, whereas hot and dry conditions may suppress certain pathogens while favoring arthropod pests. These patterns highlight that microclimate regulation not only affects individual pest groups but can also modify interaction dynamics among them, thereby influencing the overall epidemiological pressure within greenhouse cropping systems. Such interactions are regulated primarily by the greenhouse microclimate, including temperature, RH, VPD, light regime, and CO2 concentration, each of which influences both host plant physiology and the biological performance of pathogens, arthropods, and nematodes [4,89,175].
One of the most prominent examples involves the synergistic relationship between soilborne fungi and root-knot nematodes. Nematodes of the genus Meloidogyne cause extensive root galling and wounding, providing entry sites for soilborne fungal pathogens such as F. oxysporum and Verticillium dahliae [176,177]. Pre-existing nematode infestation enhances root permeability, disrupts calcium uptake, and accelerates the onset of vascular wilts [178,179]. Conversely, fungal infections that cause root and stem rots (Pythium spp., Phytophthora spp., Rhizoctonia solani) soften root tissues and facilitate nematode penetration [178]. The outcome is a self-reinforcing cycle of root deterioration and physiological stress, particularly under warm and moist conditions that favor both nematodes and fungi [178,179].
Equally important are interactions between insect vectors and viral pathogens. Viruses such as TYLCV and TSWV rely entirely on their insect vectors (i.e., whiteflies and thrips, respectively) for transmission [152,157]. Greenhouse conditions that combine elevated temperatures (25–30 °C) with moderate to low RH (<60%) enhance vector activity, feeding, and longevity, thereby accelerating viral spread [161,169]. Infected plants frequently emit volatile compounds that increase vector attraction, creating a positive feedback loop that reinforces epidemic development [180,181]. Elevated CO2 levels, which stimulate canopy biomass and modify tissue N content, can further improve vector performance and feeding efficiency, indirectly amplifying virus transmission [182,183].
Interactions also occur between fungal and bacterial pathogens. Many bacterial infections exploit wounds or necrotic tissue caused by fungal colonization as entry points into plant tissues [184,185]. For instance, secondary infections by P. syringae or Xanthomonas species commonly follow lesions produced by B. cinerea or Alternaria alternata [184,186]. The prolonged surface wetness (RH > 90%) required for fungal spore germination simultaneously promotes bacterial dispersal through water films and splash droplets [184,187]. Consequently, under persistently humid greenhouse conditions, the boundaries between fungal and bacterial epidemics are often blurred, resulting in complex mixed infections [184,185].
Another important category includes mutualistic or facilitative interactions between insects and fungi or bacteria. Certain insect vectors serve as mobile carriers of fungal spores [20,88], transporting them from plant to plant via their mouthparts or body surfaces. Thrips, for example, can disseminate B. cinerea spores from flowers to leaves, while whiteflies often promote the proliferation of saprophytic fungi (e.g., Capnodium spp.) through their sugary honeydew secretions [79,170,188]. These sooty molds reduce light interception, hinder photosynthesis, and create localized humid microenvironments that further support fungal growth and pathogen persistence [20,188].
Antagonistic interactions may also occur when one group suppresses another. For example, heavy infestations by spider mites (T. urticae) in hot and dry conditions (VPD > 1.2 kPa) can reduce the RH around leaf surfaces, thereby decreasing the likelihood of Botrytis or Cladosporium infections, which require surface moisture [189,190,191]. However, excessive dehumidification practices implemented to control fungal diseases may unintentionally favor mites and thrips, leading to pest outbreaks [20]. Achieving an appropriate climatic balance that minimizes risks for all organism groups is therefore a fundamental aspect of integrated greenhouse management.
Ultimately, the greenhouse microclimate acts as a common regulator of all these biotic interactions. Temperature, RH, light, and CO2 do not affect individual species in isolation but rather shape entire microecosystems of interacting pests. Even minor deviations, such as a 2–3 °C rise in temperature or a 5–10% change in RH, can shift the equilibrium among organisms, triggering new epidemic dynamics. For this reason, pest management in greenhouse cultivation must move beyond single-target interventions and adopt an ecologically integrated approach that accounts for the cross-effects among fungi, bacteria, viruses, insects, nematodes, and host physiology.
Table 6. Representative interactions among pest groups across species and their climatic determinants. The main types of cross-group interactions are summarized in Supplementary Table S6.
Table 6. Representative interactions among pest groups across species and their climatic determinants. The main types of cross-group interactions are summarized in Supplementary Table S6.
Interaction TypeInvolved OrganismsMechanistic BasisFavorable Climatic ConditionsAgronomic OutcomeIndicative Management ApproachKey References
Synergistic (soilborne)Meloidogyne spp. (root-knot nematodes) × Fusarium oxysporum, Verticillium dahliaeNematode-induced root wounding facilitates fungal penetration and vascular colonizationWarm (25–30 °C), moist root zoneAccelerated wilt development, reduced water and nutrient uptakeCrop rotation, soil solarization, grafted resistant rootstocks, moderate soil moisture[176,177,178,179]
Sequential (fungus → bacterium)Botrytis cinerea, Alternaria alternata × Pseudomonas syringae, Xanthomonas spp.Fungal lesions create entry points for bacterial colonization; high RH enhances bothRH > 90%, low air movementMixed infections, extended tissue necrosisReduce leaf wetness, improve ventilation, stagger fungicide/bactericide timing[20,184,185,187]
Vector-mediated (insect–virus)Bemisia tabaci, Frankliniella occidentalis × TYLCV, TSWVInsect feeding transmits viruses; infected plants emit volatiles that attract more vectors25–30 °C, RH < 60%, high lightRapid virus spread, epidemic outbreaksMaintain RH 60–75%, use insect-proof screens, UV-transmitting films, vector control[81,85,87,89,95,115]
Facilitative (insect–fungus)Whiteflies × Capnodium spp. (sooty molds); thrips × Botrytis cinereaHoneydew supports fungal growth; insect movement disperses sporesWarm, humid, high canopy densityReduced photosynthesis, secondary fungal growthManage vector populations; wash foliage; enhance airflow[20,79,88,170,188,192]
Antagonistic (pest–pathogen)Tetranychus urticae (spider mite) × Botrytis spp.Mite feeding increases transpiration and local dryness, reducing fungal infection probabilityHot, dry, VPD > 1.2 kPaDecrease in foliar pathogens but pest proliferationMaintain RH 60–70%, balance VPD; promote predatory mites[20,40,189,190,191]
Climate-mediated (competition–facilitation shift)Multiple pest–pathogen groupsMicroclimate shifts (ΔT ± 2–3 °C, ΔRH ± 5–10%) alter dominance between organismsTransitional seasons, variable ventilationSudden epidemic or pest outbreak following climatic fluctuationDynamic climate control (RH, T, VPD); continuous monitoring and adaptive IPM[73,193,194,195]
Mechanical–Biotic synergyToMV/PMMoV × handling tools or workers × Pseudomonas spp.Human-mediated spread of stable viruses combined with secondary bacterial invasion of damaged tissueWarm (25–28 °C), high RHRapid within-crop spread, compounded damageDisinfect tools and gloves, avoid handling wet plants, sanitation of benches and lines[92,196,197,198,199]
Δ, change (difference between two values); IPM, integrated pest management; PMMoV, pepper mild mottle virus; RH, relative air humidity; T, temperature; ToMV, tobacco mosaic virus; TSWV, tomato spotted wilt virus; TYLCV, tomato yellow leaf curl virus; UV, ultraviolet; VPD, vapor pressure deficit.

8. Microclimatic Regulation of Pest–Pathogen Dynamics

All previous sections converge on a common conclusion. Despite the taxonomic and ecological diversity of greenhouse pests, their outbreaks are governed by a shared set of climatic drivers (i.e., temperature, RH, VPD, and light). These factors jointly regulate the biological processes underlying infection, reproduction, and dispersal across fungi, bacteria, viruses, arthropods, and nematodes. This section, therefore, synthesizes these patterns to highlight how the same microclimatic variables, when unbalanced, can simultaneously promote one group while suppressing another, emphasizing the need for integrated environmental management rather than pathogen-specific control. While the same climatic drivers regulate all pest groups, their impact intensity varies by crop. The crop-specific susceptibilities summarized in Section 2 and Table 1 provide the physiological framework for these responses. Tomato is more responsive to RH and temperature fluctuations [10,11], cucumber to condensation and substrate moisture [45,200] and pepper to VPD extremes and high light conditions [201,202]. These species-specific sensitivities determine the dominant pest and disease complexes observed in each crop under identical greenhouse environments.
The greenhouse microclimate defines the environmental boundary conditions under which pests interact with their hosts. The major climatic variables (i.e., temperature, RH, VPD, light, and CO2 concentration) act as simultaneous and interdependent regulators of biological activity. Their combined influence determines infection probability, vector behavior, reproductive rate, and host susceptibility. Because environmental control is central to greenhouse production, understanding how these parameters interact with biotic stress agents is fundamental to sustainable pest and disease management.
Temperature exerts the most direct control over pathogen growth and pest development. Fungal and bacterial pathogens generally thrive within 20–28 °C, whereas insects and nematodes show accelerated life cycles above 25 °C [20,192,203]. Even modest temperature shifts can modify the balance between plant defense and pathogen aggressiveness [192,204]. Sustained warmth increases the replication of viruses and the feeding rate of vectors (e.g., whiteflies and thrips), while excessive heat may limit their survival or reduce fungal sporulation [84,205]. Maintaining moderate day–night temperature amplitudes stabilizes crop physiology and prevents both stress-induced vulnerability and pest and disease outbreaks [192,204,206].
RH and VPD jointly regulate moisture availability on plant surfaces, thereby influencing spore germination, bacterial dissemination, and vector performance [207,208]. High RH and prolonged leaf wetness favor foliar pathogens, whereas dry conditions promote mite and thrips proliferation [87,207]. The duration of condensation following night cooling often defines the critical infection window for Botrytis, Phytophthora infestans, Cladosporium, and Pseudomonas species [63,207,209,210]. Conversely, persistently low RH enhances desiccation stress, stimulating feeding and oviposition in arthropods [87,207,208]. Optimal greenhouse management maintains RH between 60 and 75% (VPD ≈ 0.6–1.0 kPa), minimizing both fungal infection risk and insect activity [87,207,208,211].
Light intensity and spectral quality further influence the microclimate and the behavior of pests. High irradiance elevates canopy temperature and VPD, indirectly reducing RH-dependent diseases but stimulating the activity of thermophilic pests [212,213,214,215,216]. Spectral composition, particularly UV and blue light, affects vector orientation and fungal spore viability [213,214,215]. UV-blocking films reduce whitefly and aphid attraction but may simultaneously enhance powdery mildew severity by suppressing natural UV sterilization [121,217]. Thus, spectral manipulation should balance crop physiology with pest control outcomes.
CO2 enrichment, widely applied to stimulate photosynthesis, indirectly modifies microclimatic conditions by increasing canopy density and altering gas exchange [218,219,220]. Denser foliage restricts air circulation, raising local RH and temperature near the leaf surface, conditions favorable for foliar pathogens [221,222,223]. Elevated CO2 can also change the carbon–nitrogen balance of tissues, sometimes reducing resistance to necrotrophic fungi or bacterial invasion [221,224]. The interaction between CO2 supply and ventilation efficiency therefore represents a critical consideration in climate–health optimization.
Microclimatic variables seldom operate in isolation. Instead, they interact as an integrated regulatory network that concurrently influences plant and pest physiology. The same environmental settings that maximize productivity may also create favorable niches for pathogen infection or vector proliferation. Consequently, effective pest and disease management in controlled environments relies not only on chemical or biological interventions but also on continuous, adaptive regulation of temperature, RH, and air circulation. Advances in sensor networks and automated climate control technologies now enable real-time adjustment of environmental parameters to maintain conditions that suppress biotic stress while sustaining optimal crop growth. This convergence of microclimate monitoring and biological regulation constitutes the foundation of climate-adaptive IPM in modern greenhouse horticulture.
Table 7 highlights the biological sensitivity of major pest groups to individual climatic factors. Greenhouse management must also balance these sensitivities against the environmental conditions required for optimal yield. Accordingly, Table 8 presents typical climatic trade-offs and IPM priorities across the main greenhouse vegetable species. Although the interactions among temperature, RH, light, and CO2 define the fundamental ecology of pests, these relationships do not remain static throughout the year. Gradual seasonal changes in external climate alter the internal greenhouse balance, shifting the relative dominance of microbial and arthropod groups. The following section examines how these seasonal transitions reshape pest dynamics and how adaptive, climate-based management strategies can maintain crop health across contrasting cultivation periods.

9. Seasonal Variability and Integrated Climate–Pest Management Framework

Although greenhouse environments buffer external fluctuations, seasonal trends in light, temperature, and RH still determine the relative dominance of different pest groups (Table 9). During winter, low radiation and restricted ventilation maintain high RH and condensation, favoring foliar fungi and bacterial diseases such as B. cinerea and P. syringae [211,234]. In contrast, the warmer and drier conditions of late spring and summer accelerate the development of insects, mites, powdery mildews, and virus transmission cycles [89,139]. Transitional autumn periods, characterized by large diurnal temperature amplitudes, often produce mixed infections as fluctuating RH alternately benefits pathogens and vectors [20,194,235]. These seasonal shifts in dominant pest groups are synthesized in Figure 3, which illustrates the progression of biotic threats across winter, spring, summer, and autumn as shaped by temperature, RH, VPD, and ventilation patterns.
These seasonal patterns highlight the need for adaptive IPM that integrates climate control with biological and cultural regulation. Winter IPM should focus on RH management, namely through timed ventilation, heating cycles, and dehumidification, while summer strategies emphasize vector exclusion, shading, and biological control of insect pests [13,221,236]. Continuous environmental monitoring enables growers to shift priorities dynamically as conditions change, preventing the establishment of favorable niches for pest populations.
The integration of climate regulation, pest surveillance, and predictive modeling forms the basis of climate-smart IPM. Automated systems that adjust temperature, RH, and VPD in real time according to biological risk indicators can suppress pest pressure without negatively impacting crop growth or yield. Seasonal adaptability, rather than fixed set-points, thus represents the key principle of climate-smart and resilient pest and disease management in protected horticulture.
Under projected Mediterranean climate scenarios, extended warm periods and reduced nocturnal cooling are expected to prolong pest activity windows and enable additional generations per year [3]. Consequently, key arthropod pests such as B. tabaci, F. occidentalis, and T. absoluta may persist or re-emerge during transitional seasons, thereby increasing the need for timely biological or chemical control interventions and complicating existing IPM schedules.

10. Decision Support Systems (DSSs) for Climate-Informed Pest and Disease Management

Modern greenhouse production increasingly relies on Decision Support Systems (DSSs) that integrate environmental monitoring, pest prediction models, and climate-adaptive management recommendations [238,239]. Because pests in protected cultivation are strongly regulated by temperature, RH, VPD, and short-term leaf-wetness events, DSSs provide an opportunity to transform the mechanistic relationships summarized in this review into actionable, real-time guidance for growers [19,240].
DSSs in high-technology greenhouses typically operate by combining continuous sensor data (air temperature, RH, VPD, CO2, solar radiation, and sometimes canopy temperature or leaf-wetness surrogates) with biological models describing infection windows, sporulation thresholds, and developmental rates [19,240]. For fungal pathogens such as B. cinerea, powdery mildew, and downy mildew, DSSs often identify high-risk periods based on temperature, nighttime RH, dew-point depression, or drops in VPD that indicate likely condensation. In insect pests, including whiteflies, thrips, and Tetranychus mites, DD (thermal-time) accumulation is used to forecast generation turnover, population peaks, and the optimal timing of biological control releases. These forecasting tools are especially accurate in greenhouses, where environmental variation is lower and climatic inputs can be directly manipulated [239,241]. The overall decision pathway linking climate monitoring, risk identification, environmental steering, biological control integration, and DSS feedback is summarized in Figure 4, providing a conceptual framework for climate-adaptive IPM in protected vegetable cultivation.
Crop-specific DSSs have been developed for all three crops under evaluation, although most platforms remain proprietary and are limited in their consideration of species- or cultivar-specific sensitivities [242,243]. Tomato DSSs commonly integrate models for whitefly–TYLCV risk, T. absoluta phenology, and Botrytis infection windows, while cucumber platforms emphasize powdery mildew, downy mildew, and mite risk driven by high VPD and summer temperature peaks [244,245]. Sweet pepper tools increasingly incorporate PMMoV contamination risk linked to worker contact and microclimate-related surface persistence, together with thermal-time models for thrips and mite outbreaks [246,247]. Some advanced systems propose climate-based recommendations (e.g., increasing VPD overnight to limit sporulation, or adjusting ventilation/CO2 supply to reduce vector activity), supporting a more climate-adaptive form of IPM [246,247].
Despite their promise, current DSSs face several limitations. Many models have been calibrated under Northern European greenhouse conditions and may not account for the extreme temperature–radiation regimes common in Mediterranean greenhouses. Few systems incorporate cross-group interactions, such as vector-mediated virus transmission or fungal–insect facilitation under specific RH regimes. Moreover, cultivar differences in susceptibility or canopy structure are rarely integrated. As a result, DSSs often provide generic alerts rather than crop- and climate-specific recommendations.
In addition to these scientific limitations, several practical barriers still limit the widespread adoption of DSSs, particularly in Mediterranean and low-technology greenhouse systems. One major constraint is the limited availability of high-resolution environmental monitoring and sensor infrastructure, which many small-scale growers lack [3]. In addition, DSS platforms often require reliable internet connectivity, technical training, and continuous data input, which may not be readily available in traditional greenhouse operations [3,248]. Economic considerations and perceived complexity can further discourage adoption among growers accustomed to experience-based decision making [3]. Nevertheless, several successful validation trials have demonstrated the value of climate-based DSSs in predicting disease outbreaks such as powdery mildew, Botrytis, and downy mildew, as well as in forecasting insect population dynamics using DD models [249,250]. When properly calibrated and integrated with greenhouse climate control, these systems can significantly improve the timing of preventive interventions and reduce unnecessary pesticide applications. Continued development of simplified, user-friendly DSS platforms tailored to Mediterranean greenhouse conditions will therefore be essential to bridge the gap between experimental research and practical adoption.
Overall, DSSs represent an essential bridge between microclimate knowledge and operational management of pests and diseases in protected cultivation. Their integration with real-time climate control, biological control scheduling, and automated environmental interventions is likely to become central to climate-smart greenhouse horticulture.

11. Methodological Notes: Experimental Design, Confounders, and Reporting Standards

Experimental studies on pest dynamics under greenhouse conditions require precise environmental control and transparent reporting. A visual summary of these methodological considerations is provided in Figure 5. Because even small variations in temperature, RH, or light can alter infection or infestation outcomes, both biological replication and environmental standardization are essential. Randomized block or split-plot designs are preferred to account for spatial microclimate heterogeneity within the greenhouse, with continuous monitoring of air temperature, RH, VPD, CO2, and light intensity at canopy level. Non-inoculated controls under identical conditions are necessary to separate environmental from biological effects, and when multiple species are compared, both plant developmental stage and inoculum load must be standardized.
Spatial microclimate variability within the greenhouse represents a major yet often overlooked factor influencing pest dynamics. Temperature, RH, and air movement differ markedly between canopy strata, with upper leaves experiencing greater irradiance and VPD, while lower zones remain cooler and more humid. These gradients create distinct microhabitats that affect sporulation, condensation, and vector behavior. Consequently, pest incidence and severity may vary even within a single crop row. Experimental designs and monitoring systems should therefore account for vertical and horizontal microclimate heterogeneity, using distributed sensors or canopy-level stratification, to improve the accuracy of epidemiological assessments and the reliability of climate-based management models.
Several confounding factors can obscure climate–pest/disease relationships. Interactions among environmental variables often make it difficult to isolate single-factor effects. For example, temperature changes modify VPD and leaf wetness simultaneously. Nutrient status, irrigation frequency, and plant density also influence pest susceptibility, while differences in greenhouse technology level affect the uniformity of microclimate regulation. The inoculation or infestation method, pathogen strain, pest biotype and crop cultivar or hybrid must be explicitly described, as they strongly influence disease progression and vector behavior.
To ensure comparability across studies, greenhouse experiments should report complete environmental metadata, including mean and range values of temperature, RH, and VPD during the infection or infestation period, together with information on host species, cultivar, age, and canopy characteristics. Quantitative outcomes such as pest incidence, vector density, and severity indices should be expressed relative to plant area or biomass to enable cross-study analysis. Transparent reporting of environmental stability is as important as biological outcomes, since microclimatic fluctuation itself often determines pest dynamics.
Reproducibility remains a major limitation in greenhouse pest research due to structural and technological variability among facilities. Detailed documentation of climate control systems, data logging methods, and microclimate variability allows for better inter-laboratory comparison. When possible, results should include empirical relationships between environmental parameters and infection or infestation rates, providing a foundation for predictive epidemiological and IPM modeling. Such standardized environmental monitoring and metadata reporting are particularly critical because these datasets form the foundation for developing, calibrating, and validating climate-informed DSSs.

12. Knowledge Gaps and Research Priorities

Despite extensive advances in understanding how greenhouse climate influences pest dynamics, significant gaps remain in both mechanistic knowledge and methodological consistency. Most available studies address single environmental factors under simplified conditions, often without quantifying the interactions among temperature, RH, light, and CO2 [2,5]. This reductionist approach limits the predictive value of results, as real greenhouse environments are characterized by continuous and interdependent fluctuations [2,28,251]. Future research must therefore focus on multi-factorial experiments that integrate the full spectrum of climatic variables to describe their synergistic or antagonistic effects on disease epidemiology and pest population dynamics [4,156]. In addition, the increasing integration of climate-informed DSSs (Section 10) underscores the need for greenhouse-specific datasets linking environmental variation with biological responses.
A major limitation concerns the scarcity of quantitative response models linking microclimate to infection or infestation parameters. Although threshold data exist for specific pests or vectors, few studies provide continuous functions describing how changes in temperature or VPD influence reproduction rates, spore germination, or virus transmission efficiency [250,252]. Developing such models requires high-resolution monitoring of both environmental conditions and biological responses, supported by standardized experimental design and metadata reporting. The integration of these datasets into mechanistic and machine-learning (ML) models will enable the construction of predictive tools for real-time pest risk forecasting. However, most existing modeling attempts have not yet been incorporated into operational DSS platforms, reflecting a persistent gap between experimental findings and decision-support applications [242,243].
Another critical gap lies in the species-specific characterization of microclimatic sensitivity. The three crops under study differ substantially in canopy structure, transpiration, and physiological plasticity (Table 1) [10,11,23,28,253], yet comparative studies under identical greenhouse conditions remain scarce [37]. Detailed cross-species analyses are needed to identify microclimatic thresholds that define vulnerability to each pest group and to establish species-tailored IPM setpoints for temperature, RH, and VPD [5,252]. In addition, cultivar-specific resistance traits may substantially modify these climate–pest relationships. Differences in canopy architecture, stomatal behavior, leaf morphology, and biochemical defenses can alter microclimatic conditions within the canopy and influence pathogen infection efficiency or arthropod colonization [20,222,230]. Incorporating cultivar-dependent traits into future epidemiological models and DSSs will therefore improve the accuracy of climate-based pest risk predictions.
Equally important is the limited understanding of how microclimate affects the efficacy of biological control agents. Temperature, RH, and light intensity strongly influence the performance of entomopathogenic fungi, parasitoids, microbial biopesticides, and predatory mites [254,255,256]. High RH favors fungal infection, whereas excessive VPD or heat reduces spore viability and predator activity [254]. Quantifying these relationships is essential for integrating biocontrol measures into climate-responsive IPM frameworks that maintain efficacy across diverse greenhouse environments. To date, few DSSs incorporate biological control performance modules, representing a major obstacle to climate-adaptive IPM [242,243,257].
Optimal climate management for yield versus pest suppression represents another major research frontier [2,258]. The environmental conditions that maximize photosynthesis and fruit growth often differ from those that minimize pest pressure [10,11]. High RH and moderate temperature enhance physiological efficiency and nutrient uptake but also favor fungal sporulation and bacterial proliferation [5,20,250]. Conversely, low RH suppresses fungal infection yet promotes thrips and mite outbreaks [37,254,255], while elevated temperature accelerates fruit development but increases whitefly reproduction [94,104,254]. Balancing productivity with biosecurity requires defining dynamic climate setpoints that simultaneously sustain crop performance and restrict pest populations. Quantitative frameworks to describe these trade-offs are still lacking [242,257], especially under Mediterranean semi-controlled conditions where environmental variability is high [2,28]. Integrating such trade-off models into DSSs would substantially improve their predictive and prescriptive capacity.
Emerging challenges also relate to climate change and technology transitions. Rising external temperatures, variable radiation patterns, and the use of semi-closed or energy-saving greenhouses are altering traditional microclimatic regimes [3]. These shifts will likely modify pest community equilibria and may favor previously minor species [194,254]. Long-term monitoring programs integrating climate data, pest surveys, and diagnostic monitoring are necessary to detect and model these transitions [242,243,257]. Yet, current DSSs rarely incorporate long-term climate change projections or adaptive risk modules, limiting their future relevance [242,250,257]. Furthermore, the deployment of digital sensing networks and artificial intelligence (AI)-based DSSs remains underexploited [240,251]. The integration of optical, thermal, and multispectral sensors with automated climate control could enable adaptive pest management strategies that pre-empt epidemic onset rather than respond to it [240,245,251]. Developing greenhouse-specific datasets to train these AI systems represents a critical research need. Future DSS frameworks may further benefit from the integration of remote sensing and digital twin technologies [19,259]. Multispectral and thermal imaging systems can enable early detection of plant stress or disease symptoms [260,261], while digital twin models (virtual representations of greenhouse cropping systems) can simulate climate–plant–pest interactions in real time and evaluate alternative climate management strategies before implementation [262,263].
Finally, there is a need to strengthen interdisciplinary collaboration among plant pathologists, entomologists, agronomists, and engineers to harmonize terminology, measurement protocols, and data-sharing frameworks. A unified methodological and modeling approach would accelerate progress toward climate-responsive pest management. Addressing these research priorities will transform greenhouse pest management from a reactive, empirically driven practice into a predictive and ecologically optimized system, aligning with the broader objectives of sustainable and resilient horticultural production.

13. Conclusions

Greenhouse horticulture provides a uniquely controllable environment that can simultaneously enhance crop productivity and intensify biotic pressures. The balance between these outcomes depends on how effectively the microclimate, defined by temperature, RH, light, and CO2, is managed in relation to the biology of pests. The synthesis presented in this review demonstrates that most major pest outbreaks in greenhouse-grown tomato, cucumber, and sweet pepper arise not from individual pathogens, but from microclimatic conditions that favor their reproduction, survival, or transmission. The dynamic interactions among fungi, bacteria, viruses, insects, mites and nematodes are largely governed by environmental stability, canopy architecture, and the persistence of favorable microhabitats within the greenhouse.
A central insight is that the same environmental parameters that promote photosynthesis and yield can also create optimal conditions for pest proliferation. Small deviations in temperature or RH may shift the balance between host resistance and pathogen aggressiveness. Integrating microclimate management with biological control, resistant cultivars, and precise irrigation or fertigation regimes represents the most sustainable route to pest suppression. Continuous monitoring of temperature, RH, and VPD, combined with adaptive control systems, enables growers to anticipate rather than react to epidemic conditions. Integrating these mechanistic insights into climate-informed decision-support systems (DSSs) will be essential for transitioning greenhouse pest management from reactive suppression to predictive, data-driven control.
Looking ahead, the development of predictive, data-driven frameworks that merge environmental sensing, epidemiological modeling, and DSSs will further enhance preventive management. Aligning pest management with microclimate regulation can drive greenhouse production toward resilient, low-input systems that meet the objectives of sustainable intensification and the European Green Deal.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/horticulturae12040415/s1, Table S1: Secondary fungal pathogens (pests), their critical microclimatic thresholds, and indicative climate-based control measures. RH, relative air humidity; T, temperature; VPD, vapor pressure deficit; Table S2: Secondary bacterial pathogens (pests), their critical microclimatic thresholds, and indicative climate-based control measures. N, nitrogen; RH, relative air humidity; T, temperature; VPD, vapor pressure deficit; Table S3: Secondary viral pathogens (pests), their critical microclimatic thresholds, and indicative climate-based control measures. AMV, alfalfa mosaic virus; CMV, cucumber mosaic virus; PepMV, pepino mosaic virus; PMMoV, pepper mild mottle virus; PRSV-W, papaya ringspot virus–W; PVY, potato virus Y; RH, relative air humidity; T, temperature; TICV, tomato infectious chlorosis virus; ToCV, tomato chlorosis virus; ToMV, tomato mosaic virus; TRSV, tobacco ringspot virus; TSWV, tomato spotted wilt virus; TYLCV, tomato yellow leaf curl virus; VPD, vapor pressure deficit; ZYMV, zucchini yellow mosaic virus. * Mild or non-aggressive isolates of viruses that also occur in more severe epidemic forms; Table S4: Secondary insect pests and nematodes, their critical microclimatic thresholds, and indicative climate-based control measures. RH, relative air humidity; T, temperature; UV, ultraviolet; VPD, vapor pressure deficit; Table S5: Climatic thresholds and degree-day (DD) requirements of major arthropod pests in greenhouse vegetables. Corresponding species and their indicative climate-based control measures are shown in Table 5. RH, relative air humidity; T, temperature; Table S6: Types of interactions among major pest and pathogen groups in greenhouse vegetables and their climatic determinants. Representative examples of these cross-group interactions are shown in Table 6. Δ, change (difference between two values); PMMoV, pepper mild mottle virus; RH, relative air humidity; T, temperature; ToMV, tobacco mosaic virus; TSWV, tomato spotted wilt virus; TYLCV, tomato yellow leaf curl virus; UV, ultraviolet; VPD, vapor pressure deficit. References [264,265,266,267,268,269,270,271,272,273,274,275,276,277,278,279,280,281,282,283,284,285,286,287,288,289,290,291,292,293,294,295,296,297,298,299,300,301,302,303,304,305,306,307,308,309,310,311,312,313,314,315,316,317,318,319,320,321,322,323,324,325,326,327,328,329,330,331,332,333,334,335,336,337,338,339,340,341,342,343,344,345,346,347,348,349,350,351,352,353,354,355,356,357,358,359,360,361,362,363,364,365,366,367] are cited in the Supplementary Materials.

Author Contributions

Conceptualization, D.F.; methodology, D.F.; validation, D.F., T.M., T.N., E.G., G.T., D.I.T. and G.N.; investigation, D.F., T.M., T.N., E.G., G.T., D.I.T. and G.N.; writing—original draft preparation, D.F., T.M., T.N., E.G., G.T., D.I.T. and G.N.; writing—review and editing, D.F., T.M., T.N., E.G., G.T., D.I.T. and G.N.; visualization, D.F., T.N. and E.G.; supervision, D.F.; project administration, D.F.; funding acquisition, G.N. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Data Availability Statement

No new data were created in this study. Data sharing is not applicable to this review article.

Acknowledgments

Insightful discussions with Roland Pieruschka and Fabio Fiorani are greatly acknowledged. We are also grateful to the Academic Editor and the three anonymous reviewers for their careful evaluation and valuable suggestions, which substantially strengthened the manuscript.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

The following abbreviations are used in this manuscript:
ΔChange (difference between two values)
AIArtificial Intelligence
CMVcucumber mosaic virus
CO2Carbon dioxide
CVYVCucumber vein yellowing virus
DDDegree-days
DSSsDecision Support Systems
ECElectrical conductivity
FCField capacity
IPMIntegrated Pest Management
NNitrogen
PARPhotosynthetically active radiation
PMMoVPepper mild mottle virus
RHRelative air humidity
TTemperature
ToBRFVTomato brown rugose fruit virus
ToMVTobacco mosaic virus
TSWVTomato spotted wilt virus
TYLCVTomato yellow leaf curl virus
UVUltraviolet
VPDVapor Pressure Deficit

References

  1. Fernández, J.A.; Orsini, F.; Baeza, E.; Oztekin, G.B.; Muñoz, P.; Contreras, J.; Montero, J.I. Current Trends in Protected Cultivation in Mediterranean Climates. Eur. J. Hortic. Sci. 2018, 83, 294–305. [Google Scholar] [CrossRef]
  2. Stanghellini, C.; van’t Ooster, B.; Heuvelink, E. Greenhouse Horticulture; Brill Wageningen Academic: Wageningen, The Netherlands, 2024. [Google Scholar]
  3. Fanourakis, D.; Tsaniklidis, G.; Makraki, T.; Nikoloudakis, N.; Bartzanas, T.; Sabatino, L.; Fatnassi, H.; Ntatsi, G. Climate Change Impacts on Greenhouse Horticulture in the Mediterranean Basin: Challenges and Adaptation Strategies. Plants 2025, 14, 3390. [Google Scholar] [CrossRef] [PubMed]
  4. Yusuf, A.G.; Al-Yahya, F.A.; Saleh, A.A.; Abdel-Ghany, A.M. Optimizing Greenhouse Microclimate for Plant Pathology: Challenges and Cooling Solutions for Pathogen Control in Arid Regions. Front. Plant Sci. 2025, 16, 1492760. [Google Scholar] [CrossRef] [PubMed]
  5. Jarvis, W.R. Managing Diseases in Greenhouse Crops; APS Press: Philadelphia, PA, USA, 1992. [Google Scholar]
  6. European Parliament and Council of the European Union. Regulation (EU) 2016/2031 on protective measures against pests of plants. Off. J. Eur. Union 2016, L317, 4–104. [Google Scholar]
  7. Oerke, E.-C. Crop Losses to Pests. J. Agric. Sci. 2006, 144, 31–43. [Google Scholar] [CrossRef]
  8. van Lenteren, J.C. A Greenhouse without Pesticides: Fact or Fantasy? Crop Prot. 2000, 19, 375–384. [Google Scholar] [CrossRef]
  9. Heeb, A.; Lundegårdh, B.; Ericsson, T.; Savage, G.P. Effects of Nitrate-, Ammonium-, and Organic-nitrogen-based Fertilizers on Growth and Yield of Tomatoes. Z. Pflanzenernähr. Bodenk. 2005, 168, 123–129. [Google Scholar] [CrossRef]
  10. Heuvelink, E. Tomatoes; CABI Publishing: Wallingford, UK, 2005. [Google Scholar]
  11. Dorais, M. Advances in greenhouses and other protected structures used for cultivation of vegetables. In Achieving Sustainable Greenhouse Cultivation; Heuvelink, E., Ed.; Burleigh Dodds Science Publishing: Cambridge, UK, 2019; pp. 167–210. [Google Scholar]
  12. Black, L.L.; Green, S.K.; Hartman, G.L.; Poulos, J.M. Pepper Diseases: A Field Guide; Asian Vegetable Research and Development Center: Tainan City, Taiwan, 1991. [Google Scholar]
  13. Jones, J.B. Compendium of Tomato Diseases and Pests, 2nd ed.; APS Press/The American Phytopathological Society: St. Paul, MN, USA, 2016. [Google Scholar]
  14. Keinath, A.P.; Wintermantel, W.M.; Zitter, T.A. Compendium of Cucurbit Diseases and Pests; APS Press: St. Paul, MN, USA, 2017. [Google Scholar]
  15. Gullino, M.L.; Albajes, R.; Nicot, P.C. Integrated Pest and Disease Management in Greenhouse Crops; Springer: Cham, Switzerland, 2020. [Google Scholar]
  16. Weryszko-Chmielewska, E.; Michałojć, Z. Anatomical features of leaves of sweet pepper (Capsicum annuum L.) fed with calcium using foliar nutrition. Acta Agrobot. 2009, 62, 155–164. [Google Scholar] [CrossRef][Green Version]
  17. Zhang, Y.; Henke, M.; Li, Y.; Xu, D.; Liu, A.; Liu, X.; Li, T. Analyzing the Impact of Greenhouse Planting Strategy and Plant Architecture on Tomato Plant Physiology and Estimated Dry Matter. Front. Plant Sci. 2022, 13, 828252. [Google Scholar] [CrossRef]
  18. Harel, D.; Fadida, H.; Slepoy, A.; Gantz, S.; Shilo, K. The Effect of Mean Daily Temperature and Relative Humidity on Pollen, Fruit Set and Yield of Tomato Grown in Commercial Protected Cultivation. Agronomy 2014, 4, 167–177. [Google Scholar] [CrossRef]
  19. Shamshiri, R.R.; Jones, J.W.; Thorp, K.R.; Ahmad, D.; Man, H.C.; Taheri, S. Review of Optimum Temperature, Humidity, and Vapour Pressure Deficit for Microclimate Evaluation and Control in Greenhouse Cultivation of Tomato: A Review. Int. Agrophys. 2018, 32, 287–302. [Google Scholar] [CrossRef]
  20. Oliver, R. Agrios’ Plant Pathology, 6th ed.; Elsevier Academic Press: Amsterdam, The Netherlands, 2024. [Google Scholar]
  21. Salem, N.M.; Jewehan, A.; Aranda, M.A.; Fox, A. Tomato Brown Rugose Fruit Virus Pandemic. Annu. Rev. Phytopathol. 2023, 61, 137–164. [Google Scholar] [CrossRef] [PubMed]
  22. Luria, N.; Smith, E.; Reingold, V.; Bekelman, I.; Lapidot, M.; Levin, I.; Elad, N.; Tam, Y.; Sela, N.; Abu-Ras, A.; et al. A New Israeli Tobamovirus Isolate Infects Tomato Plants Harboring Tm-22 Resistance Genes. PLoS ONE 2017, 12, e0170429. [Google Scholar] [CrossRef]
  23. Pal, A. Cultivation of cucumber in greenhouse. In Protected Cultivation and Smart Agriculture; New Delhi Publishers: New Delhi, India, 2020. [Google Scholar] [CrossRef]
  24. Abd-El-Baky, H.; Ali, S.; Haddad, Z.E.; Ansary, Z.E. Some Environmental Parameters Affecting Sweet Pepper Growth and Productivity under Different Greenhouse Forms in Hot and Humid Climatic Conditions. J. Soil Sci. Agric. Eng. 2010, 1, 225–247. [Google Scholar] [CrossRef][Green Version]
  25. Aladenola, O.; Madramootoo, C. Response of Greenhouse-Grown Bell Pepper (Capsicum annuum L.) to Variable Irrigation. Can. J. Plant Sci. 2014, 94, 303–310. [Google Scholar] [CrossRef]
  26. Al-Mulla, Y.A.; Al-Balushi, M.I.; Al-Busaidi, H.A.; Al-Mahdouri, A.A.; Kittas, C.; Katsoulas, N. Analysis of Microclimate and Cucumber Fruit Yield in a Screenhouse and an Evaporatively Cooled Greenhouse in a Semi-Arid Location. Trans. ASABE 2018, 61, 619–629. [Google Scholar] [CrossRef]
  27. Kumar, P.; Khapte, P.S.; Singh, A.; Saxena, A. Optimization of Low-Tech Protected Structure and Irrigation Regime for Cucumber Production under Hot Arid Regions of India. Plants 2024, 13, 146. [Google Scholar] [CrossRef]
  28. Katsoulas, N.; Kittas, C. Impact of greenhouse microclimate on plant growth and development with special reference to the Solanaceae. Eur. J. Plant Sci. Biotechnol. 2008, 2, 31–44. [Google Scholar]
  29. Sun, W.; Ma, N.; Huang, H.; Wei, J.; Ma, S.; Liu, H.; Zhang, S.; Zhang, Z.; Sui, X.; Li, X. Photosynthetic Contribution and Characteristics of Cucumber Stems and Petioles. BMC Plant Biol. 2021, 21, 454. [Google Scholar] [CrossRef]
  30. Jaimez, R.; Rada, F. Gas Exchange in Sweet Pepper (Capsicum chinense Jacq) under Different Light Conditions. J. Agric. Sci. 2011, 3, 134. [Google Scholar] [CrossRef]
  31. Patanè, C. Leaf Area Index, Leaf Transpiration and Stomatal Conductance as Affected by Soil Water Deficit and VPD in Processing Tomato in Semi Arid Mediterranean Climate. J. Agron. Crop Sci. 2011, 197, 165–176. [Google Scholar] [CrossRef]
  32. Zhang, D.; Liu, Y.; Li, Y.; Qin, L.; Li, J.; Xu, F. Reducing the Excessive Evaporative Demand Improved the Water-Use Efficiency of Greenhouse Cucumber by Regulating the Trade-off between Irrigation Demand and Plant Productivity. HortScience 2018, 53, 1784–1790. [Google Scholar] [CrossRef]
  33. Hanssen, I.M.; Lapidot, M.; Thomma, B.P.H.J. Emerging Viral Diseases of Tomato Crops. Mol. Plant-Microbe Interact. 2010, 23, 539–548. [Google Scholar] [CrossRef] [PubMed]
  34. Tsitsigiannis, D.I.; Antoniou, P.P.; Tjamos, S.E.; Paplomatas, E.J. Major Diseases of Tomato, Pepper and Egg Plant in Green Houses. Eur. J. Plant Sci. Biotechnol. 2008, 2, 106–124. [Google Scholar]
  35. Patil, J.A.; Yadav, S.; Kumar, A. Management of Root-Knot Nematode, Meloidogyne Incognita and Soil Borne Fungus, Fusarium oxysporum in Cucumber Using Three Bioagents under Polyhouse Conditions. Saudi J. Biol. Sci. 2021, 28, 7006–7011. [Google Scholar] [CrossRef] [PubMed]
  36. Calvo, F.J.; Bolckmans, K.; Belda, J.E. Biological Control-Based IPM in Sweet Pepper Greenhouses Using Amblyseius swirskii (Acari: Phytoseiidae). Biocontrol Sci. Technol. 2012, 22, 1398–1416. [Google Scholar] [CrossRef]
  37. Weintraub, P.G.; Recht, E.; Mondaca, L.L.; Harari, A.R.; Diaz, B.M.; Bennison, J. Arthropod Pest Management in Organic Vegetable Greenhouses. J. Integr. Pest Manag. 2017, 8, 29. [Google Scholar] [CrossRef]
  38. Elad, Y.; Shtienberg, D. Botrytis cinerea in Greenhouse Vegetables: Chemical, Cultural, Physiological and Biological Controls and Their Integration. Integr. Pest Manag. Rev. 1995, 1, 15–29. [Google Scholar] [CrossRef]
  39. Dik, A.J.; Elad, Y. Comparison of Antagonists of Botrytis cinerea in Greenhouse-Grown Cucumber and Tomato under Different Climatic Conditions. Eur. J. Plant Pathol. 1999, 105, 123–137. [Google Scholar] [CrossRef]
  40. Dik, A.J.; Wubben, J.P. Epidemiology of Botrytis cinerea diseases in greenhouses. In Botrytis: Biology, Pathology and Control; Elad, Y., Williamson, B., Tudzynski, P., Delen, N., Eds.; Springer: Dordrecht, The Netherlands, 2007; pp. 319–333. [Google Scholar]
  41. Cerkauskas, R.F.; Ferguson, G.; Banik, M. Powdery Mildew (Leveillula taurica) on Greenhouse and Field Peppers in Ontario–Host Range, Cultivar Response and Disease Management Strategies. Can. J. Plant Pathol. 2011, 33, 485–498. [Google Scholar] [CrossRef]
  42. Guzman-Plazola, R.A.; Davis, R.M.; Marois, J.J. Effects of Relative Humidity and High Temperature on Spore Germination and Development of Tomato Powdery Mildew (Leveillula taurica). Crop Prot. 2003, 22, 1157–1168. [Google Scholar] [CrossRef]
  43. Sletova, M.E.; Korottseva, I.B.; Kameneva, A.V.; Engalycheva, I.A.; Belov, S.N. Study of Morphobiological Characteristics of the Pathogen Causing True Powdery Mildew in the Family cucurbitaceae L. Crops. Russ. Agric. Sci. 2024, 50, 694–701. [Google Scholar] [CrossRef]
  44. Bélanger, R.R. The Powdery Mildews: A Comprehensive Treatise; APS Press: St. Paul, MN, USA, 2002. [Google Scholar]
  45. Lebeda, A.; Cohen, Y. Cucurbit Downy Mildew (Pseudoperonospora cubensis)—Biology, Ecology, Epidemiology, Host-Pathogen Interaction and Control. Eur. J. Plant Pathol. 2011, 129, 157–192. [Google Scholar] [CrossRef]
  46. Savory, E.A.; Granke, L.L.; Quesada-Ocampo, L.M.; Varbavova, M.; Hausbeck, M.K.; Day, B. The Cucurbit Downy Mildew Pathogen Pseudoperonospora cubensis. Mol. Plant Pathol. 2011, 12, 217–226. [Google Scholar] [CrossRef]
  47. Babadoost, M. Oomycete diseases of cucurbits: History, significance, and management. In Horticultural Reviews; John Wiley & Sons: Hoboken, NJ, USA, 2016; pp. 279–314. [Google Scholar] [CrossRef]
  48. Rivas, S.; Thomas, C.M. Molecular Interactions Between Tomato and the Leaf Mold Pathogen Cladosporium fulvum. Annu. Rev. Phytopathol. 2005, 43, 395–436. [Google Scholar] [CrossRef] [PubMed]
  49. Srinivas, C.; Devi, D.N.; Murthy, K.N.; Mohan, C.D.; Lakshmeesha, T.R.; Singh, B.; Kalagatur, N.K.; Niranjana, S.R.; Hashem, A.; Alqarawi, A.A.; et al. Fusarium oxysporum F. sp. lycopersici Causal Agent of Vascular Wilt Disease of Tomato: Biology to Diversity—A Review. Saudi J. Biol. Sci. 2019, 26, 1315–1324. [Google Scholar] [CrossRef]
  50. Velarde-Félix, S.; Garzón-Tiznado, J.A.; Hernández-Verdugo, S.; López-Orona, C.A.; Retes-Manjarrez, J.E. Occurrence of Fusarium oxysporum Causing Wilt on Pepper in Mexico. Can. J. Plant Pathol. 2018, 40, 238–247. [Google Scholar] [CrossRef]
  51. Gordon, T.R. Fusarium oxysporum and the Fusarium Wilt Syndrome. Annu. Rev. Phytopathol. 2017, 55, 23–39. [Google Scholar] [CrossRef] [PubMed]
  52. Arora, H.; Sharma, A.; Sharma, S.; Haron, F.F.; Gafur, A.; Sayyed, R.Z.; Datta, R. Pythium Damping-Off and Root Rot of Capsicum annuum L.: Impacts, Diagnosis, and Management. Microorganisms 2021, 9, 823. [Google Scholar] [CrossRef]
  53. Herrero, M.L.; Hermansen, A.; Elen, O.N. Occurrence of Pythium spp. and Phytophthora spp. in Norwegian Greenhouses and Their Pathogenicity on Cucumber Seedlings. J. Phytopathol. 2003, 151, 36–41. [Google Scholar] [CrossRef]
  54. Saltos, L.A.; Monteros-Altamirano, Á.; Reis, A.; Garcés-Fiallos, F.R. Phytophthora capsici: The Diseases It Causes and Management Strategies to Produce Healthier Vegetable Crops. Hortic. Bras. 2022, 40, 5–17. [Google Scholar] [CrossRef]
  55. Rai, M.; Abd-Elsalam, K.A.; Ingle, A.P. Pythium: Diagnosis, Diseases and Management; CRC Press: Boca Raton, FL, USA, 2020. [Google Scholar]
  56. Al-Masri, M.I.; Ali-Shtayeh, M.S.; Elad, Y.; Sharon, A.; Tudzynski, P.; Barakat, R. Effect of Plant Growth Regulators on White Mould (Sclerotinia sclerotiorum) on Bean and Cucumber. J. Phytopathol. 2002, 150, 481–487. [Google Scholar] [CrossRef]
  57. Mazumdar, P. Sclerotinia Stem Rot in Tomato: A Review on Biology, Pathogenicity, Disease Management and Future Research Priorities. J. Plant Dis. Prot. 2021, 128, 1403–1431. [Google Scholar] [CrossRef]
  58. Bolton, M.D.; Thomma, B.P.H.J.; Nelson, B.D. Sclerotinia sclerotiorum (Lib.) de Bary: Biology and Molecular Traits of a Cosmopolitan Pathogen. Mol. Plant Pathol. 2006, 7, 1–16. [Google Scholar] [CrossRef]
  59. Massimi, M.; Kabashi, B. Integrated Management of Alternaria alternata in Tomato and Pepper: Leaf-Environment, and Cultivar Interactions. Jordan J. Appl. Sci.-Nat. Sci. Ser. 2025, 19, 34–38. [Google Scholar] [CrossRef]
  60. Maurya, S.; Regar, R.; Kumar, S.; Dubey, S. Management Tactics for Early Blight of Tomato Caused by Alternaria solani: A Review. J. Plant Biol. Crop Res. 2022, 5, 1062. [Google Scholar]
  61. Schmey, T.; Tominello-Ramirez, C.S.; Brune, C.; Stam, R. Alternaria Diseases on Potato and Tomato. Mol. Plant Pathol. 2024, 25, e13435. [Google Scholar] [CrossRef] [PubMed]
  62. Mansfield, J.; Genin, S.; Magori, S.; Citovsky, V.; Sriariyanum, M.; Ronald, P.; Dow, M.; Verdier, V.; Beer, S.V.; Machado, M.A.; et al. Top 10 Plant Pathogenic Bacteria in Molecular Plant Pathology. Mol. Plant Pathol. 2012, 13, 614–629. [Google Scholar] [CrossRef]
  63. Preston, G.M. Pseudomonas syringae pv. tomato: The Right Pathogen, of the Right Plant, at the Right Time. Mol. Plant Pathol. 2000, 1, 263–275. [Google Scholar] [CrossRef]
  64. Potnis, N.; Timilsina, S.; Strayer, A.; Shantharaj, D.; Barak, J.D.; Paret, M.L.; Vallad, G.E.; Jones, J.B. Bacterial spot of tomato and pepper: Diverse Xanthomonas species with a wide variety of virulence factors posing a worldwide challenge. Mol. Plant Pathol. 2015, 16, 907–920. [Google Scholar] [CrossRef] [PubMed]
  65. Stall, R.E.; Jones, J.B.; Minsavage, G.V. Durability of Resistance in Tomato and Pepper to Xanthomonads Causing Bacterial Spot. Annu. Rev. Phytopathol. 2009, 47, 265–284. [Google Scholar] [CrossRef]
  66. Osdaghi, E.; Jones, J.B.; Sharma, A.; Goss, E.M.; Abrahamian, P.; Newberry, E.A.; Potnis, N.; Carvalho, R.; Choudhary, M.; Paret, M.L.; et al. A Centenary for Bacterial Spot of Tomato and Pepper. Mol. Plant Pathol. 2021, 22, 1500–1519. [Google Scholar] [CrossRef] [PubMed]
  67. Gartemann, K.-H.; Kirchner, O.; Engemann, J.; Gräfen, I.; Eichenlaub, R.; Burger, A. Clavibacter michiganensis subsp. michiganensis: First Steps in the Understanding of Virulence of a Gram-Positive Phytopathogenic Bacterium. J. Biotechnol. 2003, 106, 179–191. [Google Scholar] [CrossRef]
  68. Milijašević, S.; Todorović, B.; Rekanović, E.; Potočnik, I.; Balaž, J. Clavibacter michiganensis subsp. michiganensis, bacterial canker of tomato: 2. Comparison of the effectiveness of extraction procedures and sensitivity of methods for detection in tomato seeds. Pestic. Fitomed. 2007, 22, 121–130. [Google Scholar]
  69. Peritore-Galve, F.C.; Tancos, M.A.; Smart, C.D. Bacterial Canker of Tomato: Revisiting a Global and Economically Damaging Seedborne Pathogen. Plant Dis. 2021, 105, 1581–1595. [Google Scholar] [CrossRef]
  70. Charkowski, A.O. The Changing Face of Bacterial Soft-Rot Diseases. Annu. Rev. Phytopathol. 2018, 56, 269–288. [Google Scholar] [CrossRef] [PubMed]
  71. Newberry, E.A.; Jardini, T.M.; Rubio, I.; Roberts, P.D.; Babu, B.; Koike, S.T.; Bouzar, H.; Goss, E.M.; Jones, J.B.; Bull, C.T.; et al. Angular Leaf Spot of Cucurbits Is Associated With Genetically Diverse Pseudomonas syringae Strains. Plant Dis. 2016, 100, 1397–1404. [Google Scholar] [CrossRef] [PubMed]
  72. Olczak-Woltman, H.; Schollenberger, M.; Mądry, W.; Niemirowicz-Szczytt, K. Evaluation of Cucumber (Cucumis sativus) Cultivars Grown in Eastern Europe and Progress in Breeding for Resistance to Angular Leaf Spot (Pseudomonas syringae pv. lachrymans). Eur. J. Plant Pathol. 2008, 122, 385–393. [Google Scholar] [CrossRef]
  73. Hossain, M.F.; Hasan, S.Z.; Zaoti, Z.F.; Hasan, M.F.; Acharjee, U.K.; Islam, M.A.; Khalekuzzaman, M.; Sikdar, B. Isolation and characterization of Pseudomonas syringae pv. lachrymans from angular leaf spot disease of cucumber (Cucumis sativus L.) and evaluation of its antibiotic sensitivity. J. Pharmacogn. Phytochem. 2017, 6, 233–238. [Google Scholar]
  74. van der Wolf, J.M.; Acuña, I.; De Boer, S.H.; Brurberg, M.B.; Cahill, G.; Charkowski, A.O.; Coutinho, T.; Davey, T.; Dees, M.W.; Degefu, Y.; et al. Diseases caused by Pectobacterium and Dickeya species around the world. In Plant Diseases Caused by Dickeya and Pectobacterium Species; Van der Wolf, J.M., De Boer, S.H., Czajkowski, R., Eds.; Springer: Cham, Switzerland, 2021; pp. 215–261. [Google Scholar] [CrossRef]
  75. Czajkowski, R.; Grabe, G.J.; van der Wolf, J.M. Distribution of Dickeya spp. and Pectobacterium carotovorum subsp. carotovorum in Naturally Infected Seed Potatoes. Eur. J. Plant Pathol. 2009, 125, 263–275. [Google Scholar] [CrossRef]
  76. Navas-Castillo, J.; Fiallo-Olivé, E.; Sánchez-Campos, S. Emerging Virus Diseases Transmitted by Whiteflies. Annu. Rev. Phytopathol. 2011, 49, 219–248. [Google Scholar] [CrossRef] [PubMed]
  77. Sastry, K.S.; Mandal, B.; Hammond, J.; Scott, S.W.; Briddon, R.W. Encyclopedia of Plant Viruses and Viroids; Springer: New Delhi, India, 2019. [Google Scholar]
  78. Bonsignore, C.P. Effect of Environmental Factors on the Flight Activity Trialeurodes vaporariorum (Westwood) under Greenhouse Conditions. Entomol. Sci. 2015, 18, 207–216. [Google Scholar] [CrossRef]
  79. Jones, D.R. Plant Viruses Transmitted by Whiteflies. Eur. J. Plant Pathol. 2003, 109, 195–219. [Google Scholar] [CrossRef]
  80. Kumar, P.; Poehling, H.-M. Uv-Blocking Plastic Films and Nets Influence Vectors and Virus Transmission on Greenhouse Tomatoes in the Humid Tropics. Environ. Entomol. 2006, 35, 1069–1082. [Google Scholar] [CrossRef]
  81. Moriones, E.; Navas-Castillo, J. Tomato Yellow Leaf Curl Virus, an Emerging Virus Complex Causing Epidemics Worldwide. Virus Res. 2000, 71, 123–134. [Google Scholar] [CrossRef]
  82. Lapidot, M.; Friedmann, M. Breeding for Resistance to Whitefly-transmitted Geminiviruses. Ann. Appl. Biol. 2002, 140, 109–127. [Google Scholar] [CrossRef]
  83. Prasad, A.; Sharma, N.; Hari-Gowthem, G.; Muthamilarasan, M.; Prasad, M. Tomato Yellow Leaf Curl Virus: Impact, Challenges, and Management. Trends Plant Sci. 2020, 25, 897–911. [Google Scholar] [CrossRef]
  84. Aregbesola, O.Z.; Legg, J.P.; Sigsgaard, L.; Lund, O.S.; Rapisarda, C. Potential Impact of Climate Change on Whiteflies and Implications for the Spread of Vectored Viruses. J. Pest Sci. 2019, 92, 381–392. [Google Scholar] [CrossRef]
  85. Pappu, H.R.; Jones, R.A.C.; Jain, R.K. Global Status of Tospovirus Epidemics in Diverse Cropping Systems: Successes Achieved and Challenges Ahead. Virus Res. 2009, 141, 219–236. [Google Scholar] [CrossRef]
  86. Rotenberg, D.; Jacobson, A.L.; Schneweis, D.J.; Whitfield, A.E. Thrips Transmission of Tospoviruses. Curr. Opin. Virol. 2015, 15, 80–89. [Google Scholar] [CrossRef]
  87. Reitz, S.R. Biology and Ecology of the Western Flower Thrips (Thysanoptera: Thripidae): The Making of a Pest. Fla. Entomol. 2009, 92, 7–13. [Google Scholar] [CrossRef]
  88. Lewis, T. Thrips as Crop Pests; CABI Publishing: Wallingford, UK, 1998. [Google Scholar]
  89. Shipp, J.L.; Gillespie, T.J. Influence of Temperature and Water Vapor Pressure Deficit on Survival of Frankliniella occidentalis (Thysanoptera: Thripidae). Environ. Entomol. 1993, 22, 726–732. [Google Scholar] [CrossRef]
  90. Hanssen, I.M.; Thomma, B.P.H.J. Pepino Mosaic Virus: A Successful Pathogen That Rapidly Evolved from Emerging to Endemic in Tomato Crops. Mol. Plant Pathol. 2010, 11, 179–189. [Google Scholar] [CrossRef]
  91. Hanssen, I.M.; Paeleman, A.; Vandewoestijne, E.; Bergen, L.V.; Bragard, C.; Lievens, B.; Vanachter, A.C.R.C.; Thomma, B.P.H.J. Pepino Mosaic Virus Isolates and Differential Symptomatology in Tomato. Plant Pathol. 2009, 58, 450–460. [Google Scholar] [CrossRef]
  92. Nowakowska, M.; Minicka, J.; Nowicki, M.; Szczechura, W.; Hasiów-Jaroszewska, B. Pepino Mosaic Virus in Tomato: Challenges, Control Strategies, and Future Prospects for Resistance Breeding. Int. J. Mol. Sci. 2025, 26, 11749. [Google Scholar] [CrossRef]
  93. Ontiveros, I.; López-Moya, J.J.; Díaz-Pendón, J.A. Coinfection of Tomato Plants with Tomato Yellow Leaf Curl Virus and Tomato Chlorosis Virus Affects the Interaction with Host and Whiteflies. Phytopathology 2022, 112, 944–952. [Google Scholar] [CrossRef]
  94. Liu, S.; Yu, H.; Vlasenko, V.A. Effect of Different Temperature and Humidity on Bemisia tabaci. J. Bot. Res. 2020, 2, 21–24. [Google Scholar] [CrossRef]
  95. Wang, F.; Liu, J.; Dong, Y.; Chen, P.; Zhu, X.; Liu, Y.; Ma, J. Insect-Proof Netting Technique: Effective Control of Bemisia tabaci and Tomato Chlorosis Virus (ToCV) in Protected Cultivations in China. Chil. J. Agric. Res. 2018, 78, 48–58. [Google Scholar] [CrossRef]
  96. Duffus, J.E.; Liu, H.-Y.; Wisler, G.C. Tomato Infectious Chlorosis Virus—A New Clostero-like Virus Transmitted by Trialeurodes vaporariorum. Eur. J. Plant Pathol. 1996, 102, 219–226. [Google Scholar] [CrossRef]
  97. Fiallo-Olivé, E.; Navas-Castillo, J. Tomato Chlorosis Virus, an Emergent Plant Virus Still Expanding Its Geographical and Host Ranges. Mol. Plant Pathol. 2019, 20, 1307–1320. [Google Scholar] [CrossRef] [PubMed]
  98. Hartono, S.; Natsuaki, T.; Sayama, H.; Atarashi, H.; Okuda, S. Yellowing Disease of Tomatoes Caused by Tomato Infectious Chlorosis Virus Newly Recognized in Japan. J. Gen. Plant Pathol. 2003, 69, 61–64. [Google Scholar] [CrossRef]
  99. Akhtar, K.P.; Saleem, M.Y.; Asghar, M.; Ahmad, M.; Sarwar, N. Resistance of Solanum Species to Cucumber Mosaic Virus Subgroup IA and Its Vector Myzus persicae. Eur. J. Plant Pathol. 2010, 128, 435–450. [Google Scholar] [CrossRef]
  100. Jones, R.A.C. Global plant virus disease pandemics and epidemics. Plants 2021, 10, 233. [Google Scholar] [CrossRef] [PubMed]
  101. Moya-Ruiz, C.D.; Gómez, P.; Juárez, M. Occurrence, Distribution, and Management of Aphid-Transmitted Viruses in Cucurbits in Spain. Pathogens 2023, 12, 422. [Google Scholar] [CrossRef] [PubMed]
  102. Khaled-Gasmi, W.; Souissi, R.; Boukhris-Bouhachem, S. Cucumber Mosaic Virus Epidemiology in Pepper: Aphid Dispersal, Transmission Efficiency and Vector Pressure. Ann. Appl. Biol. 2023, 182, 101–111. [Google Scholar] [CrossRef]
  103. Rathee, M.; Singh, N.V.; Dalal, P.K.; Mehra, S. Integrated Pest Management under Protected Cultivation: A Review. J. Entomol. Zool. Stud. 2018, 6, 1201–1208. [Google Scholar]
  104. Curnutte, L.B.; Simmons, A.M.; Abd-Rabou, S. Climate Change and Bemisia tabaci (Hemiptera: Aleyrodidae): Impacts of Temperature and Carbon Dioxide on Life History. Ann. Entomol. Soc. Am. 2014, 107, 933–943. [Google Scholar] [CrossRef]
  105. Horowitz, A.R.; Antignus, Y.; Gerling, D. Management of Bemisia tabaci whiteflies. In The Whitefly, Bemisia tabaci (Homoptera: Aleyrodidae) Interaction with Geminivirus-Infected Host Plants; Thompson, W.M.O., Ed.; Springer: Dordrecht, The Netherlands, 2011; pp. 293–322. [Google Scholar]
  106. Ruiz, L.; Janssen, D.; Martín, G.; Velasco, L.; Segundo, E.; Cuadrado, I.M. Analysis of the Temporal and Spatial Disease Progress of Bemisia tabaci-transmitted Cucurbit Yellow Stunting Disorder Virus and Cucumber Vein Yellowing Virus in Cucumber. Plant Pathol. 2006, 55, 264–275. [Google Scholar] [CrossRef]
  107. Yin, Z.; Zieniuk, B.; Pawełkowicz, M. Climate Change Effects on Cucumber Viruses and Their Management. Agriculture 2024, 14, 1999. [Google Scholar] [CrossRef]
  108. Ahamedemujtaba, V.; Atheena, P.V.; Bhat, A.I.; Krishnamurthy, K.S.; Srinivasan, V. Symptoms of Piper Yellow Mottle Virus in Black Pepper as Influenced by Temperature and Relative Humidity. VirusDisease 2021, 32, 305–313. [Google Scholar] [CrossRef]
  109. Kumari, N.; Sharma, V.; Patel, P.; Sharma, P.N. Pepper Mild Mottle Virus: A Formidable Foe of Capsicum Production—A Review. Front. Virol. 2023, 3, 1208853. [Google Scholar] [CrossRef]
  110. Kumar, S.; Shankar, A.C.U.; Nayaka, S.C.; Lund, O.S.; Prakash, H.S. Detection of Tobacco Mosaic Virus and Tomato Mosaic Virus in Pepper and Tomato by Multiplex RT-PCR. Lett. Appl. Microbiol. 2011, 53, 359–363. [Google Scholar] [CrossRef] [PubMed]
  111. Caruso, A.G.; Bertacca, S.; Parrella, G.; Rizzo, R.; Davino, S.; Panno, S. Tomato Brown Rugose Fruit Virus: A Pathogen That Is Changing the Tomato Production Worldwide. Ann. Appl. Biol. 2022, 181, 258–274. [Google Scholar] [CrossRef]
  112. Parrella, G.; Elbeaino, T.; Guy, P.L. Emerging and Reemerging Plant Viruses in a Context of Global Change. Front. Plant Sci. 2022, 13, 1108211. [Google Scholar] [CrossRef]
  113. Zhang, S.; Griffiths, J.S.; Marchand, G.; Bernards, M.A.; Wang, A. Tomato brown rugose fruit virus: An emerging and rapidly spreading plant RNA virus that threatens tomato production worldwide. Mol. Plant Pathol. 2022, 23, 1262–1277. [Google Scholar] [CrossRef]
  114. Fidan, H.; Ulusoy, D.; Albezirgan, H.N. Exploring Effective Strategies for ToBRFV Management in Tomato Production: Insights into Seed Transmission Dynamics and Innovative Control Approaches. Agriculture 2024, 14, 108. [Google Scholar] [CrossRef]
  115. Polston, J.E.; Lapidot, M. Management of tomato yellow leaf curl virus: U.S. and Israel perspectives. In Tomato Yellow Leaf Curl Virus Disease; Czosnek, H., Ed.; Springer: Dordrecht, The Netherlands, 2007; pp. 251–262. [Google Scholar] [CrossRef]
  116. European and Mediterranean Plant Protection Organization (EPPO). Tomato chlorosis virus and tomato infectious chlorosis virus. EPPO Bull. 2013, 43, 462–470. [Google Scholar] [CrossRef]
  117. Wintermantel, W.M.; Wisler, G.C. Vector Specificity, Host Range, and Genetic Diversity of Tomato Chlorosis Virus. Plant Dis. 2006, 90, 814–819. [Google Scholar] [CrossRef]
  118. Orfanidou, C.G.; Pappi, P.G.; Efthimiou, K.E.; Katis, N.I.; Maliogka, V.I. Transmission of Tomato Chlorosis Virus (ToCV) by Bemisia tabaci Biotype Q and Evaluation of Four Weed Species as Viral Sources. Plant Dis. 2016, 100, 2043–2049. [Google Scholar] [CrossRef]
  119. Sánchez-Tovar, M.R.; Rivera-Bustamante, R.F.; Saavedra-Trejo, D.L.; Guevara-González, R.G.; Torres-Pacheco, I. Mixed Plant Viral Infections: Complementation, Interference and Their Effects, a Review. Agronomy 2025, 15, 620. [Google Scholar] [CrossRef]
  120. Syller, J. Facilitative and Antagonistic Interactions between Plant Viruses in Mixed Infections. Mol. Plant Pathol. 2012, 13, 204–216. [Google Scholar] [CrossRef]
  121. Mutwiwa, U.N.; Borgemeister, C.; Von Elsner, B.; Tantau, H. Effects of UV-Absorbing Plastic Films on Greenhouse Whitefly (Homoptera: Aleyrodidae). J. Econ. Entomol. 2005, 98, 1221–1228. [Google Scholar] [CrossRef]
  122. Dáder, B.; Gwynn-Jones, D.; Moreno, A.; Winters, A.; Fereres, A. Impact of UV-A Radiation on the Performance of Aphids and Whiteflies and on the Leaf Chemistry of Their Host Plants. J. Photochem. Photobiol. B Biol. 2014, 138, 307–316. [Google Scholar] [CrossRef] [PubMed]
  123. Meijer, D. The Effects of Far-Red Light on Plant–Arthropod Interactions and the Implications for Greenhouse Tomato Cultivation. Ph.D. Thesis, Wageningen University, Wageningen, The Netherlands, 2023. [Google Scholar]
  124. Tileubayeva, Z.; Avdeenko, A.; Avdeenko, S.; Stroiteleva, N.; Kondrashev, S. Plant-Parasitic Nematodes Affecting Vegetable Crops in Greenhouses. Saudi J. Biol. Sci. 2021, 28, 5428–5433. [Google Scholar] [CrossRef] [PubMed]
  125. Klowden, M.J.; Palli, S.R. Physiological Systems in Insects; Academic Press: Cambridge, MA, USA, 2023. [Google Scholar]
  126. Pan, H.; Liang, G.; Lu, Y. Response of Different Insect Groups to Various Wavelengths of Light under Field Conditions. Insects 2021, 12, 427. [Google Scholar] [CrossRef]
  127. Khan, M.M.H. Effect of temperature and relative humidity on the population dynamics of brinjal- and tomato-infested whitefly, Bemisia tabaci. Bangladesh J. Agric. Res. 2019, 44, 83–86. [Google Scholar]
  128. Li, Y.; Mbata, G.N.; Punnuri, S.; Simmons, A.M.; Shapiro-Ilan, D.I. Bemisia tabaci on Vegetables in the Southern United States: Incidence, Impact, and Management. Insects 2021, 12, 198. [Google Scholar] [CrossRef]
  129. Stansly, P.A.; Sánchez, P.A.; Rodríguez, J.M.; Cañizares, F.; Nieto, A.; Leyva, M.J.L.; Fajardo, M.; Suárez, V.; Urbaneja, A. Prospects for Biological Control of Bemisia tabaci (Homoptera, Aleyrodidae) in Greenhouse Tomatoes of Southern Spain. Crop Prot. 2004, 23, 701–712. [Google Scholar] [CrossRef]
  130. Teitel, M.; Tanny, J.; Ben-Yakir, D.; Barak, M. Airflow Patterns through Roof Openings of a Naturally Ventilated Greenhouse and Their Effect on Insect Penetration. Biosyst. Eng. 2005, 92, 341–353. [Google Scholar] [CrossRef]
  131. Xie, M.; Wan, F.-H.; Chen, Y.-H.; Wu, G. Effects of Temperature on the Growth and Reproduction Characteristics of Bemisia tabaci B-Biotype and Trialeurodes vaporariorum. J. Appl. Entomol. 2011, 135, 252–257. [Google Scholar] [CrossRef]
  132. Simmons, A.M.; Mahroof, R.M. Response of Bemisia tabaci (Hemiptera: Aleyrodidae) to Vapor Pressure Deficit: Oviposition, Immature Survival, and Body Size. Ann. Entomol. Soc. Am. 2011, 104, 928–934. [Google Scholar] [CrossRef]
  133. White, P.J. The Ecophysiology of Plant-Phosphorus Interactions; Springer: Dordrecht, The Netherlands, 2008. [Google Scholar]
  134. Krechemer, F.D.S.; Foerster, L.A. Tuta absoluta (Lepidoptera: Gelechiidae): Thermal Requirements and Effect of Temperature on Development, Survival, Reproduction and Longevity. Eur. J. Entomol. 2015, 112, 658–663. [Google Scholar] [CrossRef]
  135. Shiberu, T.; Getu, E. Biology of Tuta absoluta (Meyrick) (Lepidoptera: Gelechiidae) under Different Temperature and Relative Humidity. J. Hortic. For. 2017, 9, 66–73. [Google Scholar] [CrossRef][Green Version]
  136. Roditakis, E.; Papachristos, D.; Roditakis, N.E. Current Status of the Tomato Leafminer Tuta absoluta in Greece. EPPO Bull. 2010, 40, 163–166. [Google Scholar] [CrossRef]
  137. Terzidis, A.N.; Wilcockson, S.; Leifert, C. The Tomato Leaf Miner (Tuta absoluta): Conventional Pest Problem, Organic Management Solutions? Org. Agric. 2014, 4, 43–61. [Google Scholar] [CrossRef]
  138. Arnó, J.; Gabarra, R. Side Effects of Selected Insecticides on the Tuta absoluta (Lepidoptera: Gelechiidae) Predators Macrolophus pygmaeus and Nesidiocoris tenuis (Hemiptera: Miridae). J. Pest Sci. 2011, 84, 513–520. [Google Scholar] [CrossRef]
  139. Park, Y.; Lee, J.-H. Life History Characteristics of the Western Flower Thrips, Frankliniella occidentalis (Pergande) (Thysanoptera: Thripidae), under Fluctuating Conditions of Temperature or Relative Humidity. J. Asia-Pac. Entomol. 2020, 23, 606–611. [Google Scholar] [CrossRef]
  140. Healey, M.A.; Senior, L.J.; Brown, P.H.; Duff, J. Relative Abundance and Temporal Distribution of Adult Frankliniella occidentalis (Pergande) and Frankliniella schultzei (Trybom) on French Bean, Lettuce, Tomato and Zucchini Crops in Relation to Crop Age. J. Asia-Pac. Entomol. 2017, 20, 859–865. [Google Scholar] [CrossRef]
  141. Mcdonald, J.R.; Bale, J.S.; Walters, K.F.A. Effect of Temperature on Development of the Western Flower Thrips, Frankliniella occidentalis (Thysanoptera: Thripidae). Eur. J. Entomol. 1998, 95, 301–306. [Google Scholar]
  142. Jung, C.-R.; Yoon, J.-B.; Kim, K.-H.; Lee, G.-J.; Heo, J.-W.; Kim, H.-H. Colors and Sizes of Insect Screen Net Influence Physical Control of Bemisia tabaci and Frankliniella occidentalis under Controlled Environments. Korean J. Environ. Agric. 2016, 35, 46–54. [Google Scholar] [CrossRef]
  143. Steiner, M.Y.; Spohr, L.J.; Goodwin, S. Relative Humidity Controls Pupation Success and Dropping Behaviour of Western Flower Thrips, Frankliniella occidentalis (Pergande) (Thysanoptera: Thripidae). Aust. J. Entomol. 2011, 50, 179–186. [Google Scholar] [CrossRef]
  144. Ebert, T.A.; Cartwright, B. Biology and ecology of Aphis gossypii Glover (Homoptera: Aphididae). Southwest. Entomol. 1997, 22, 116–153. [Google Scholar]
  145. Zamani, A.A.; Talebi, A.A.; Fathipour, Y.; Baniameri, V. Effect of Temperature on Biology and Population Growth Parameters of Aphis gossypii Glover (Hom., Aphididae) on Greenhouse Cucumber. J. Appl. Entomol. 2006, 130, 453–460. [Google Scholar] [CrossRef]
  146. Katsoulas, N.; Bartzanas, T.; Boulard, T.; Mermier, M.; Kittas, C. Effect of Vent Openings and Insect Screens on Greenhouse Ventilation. Biosyst. Eng. 2006, 93, 427–436. [Google Scholar] [CrossRef]
  147. Asasi, R.; Hassanpour, M.; Golizadeh, A.; Dastjerdi, H.R.; Kalkhoran, M.G. Effect of Some Cucumber Cultivars on Biological and Population Growth Parameters of Aphis gossypii (Glover) and Functional Response of Chrysoperla carnea (Stephens). J. Veg. Sci. 2022, 6, 17–32. [Google Scholar] [CrossRef]
  148. Prado, S.; Jandricic, S.; Frank, S. Ecological Interactions Affecting the Efficacy of Aphidius colemani in Greenhouse Crops. Insects 2015, 6, 538–575. [Google Scholar] [CrossRef]
  149. Ali, J.; Bayram, A.; Mukarram, M.; Zhou, F.; Karim, M.F.; Hafez, M.M.A.; Mahamood, M.; Yusuf, A.A.; King, P.J.H.; Adil, M.F.; et al. Peach–Potato Aphid Myzus persicae: Current Management Strategies, Challenges, and Proposed Solutions. Sustainability 2023, 15, 11150. [Google Scholar] [CrossRef]
  150. Vuong, P.T.; Kim, J.; Song, Y. The Seasonal Occurrence of the Two Aphid Species, Myzus persicae and Aphis gossypii, and Their Natural Enemies on Vegetable Crops in Chinju, Korea. J. Asia-Pac. Entomol. 2001, 4, 41–44. [Google Scholar] [CrossRef]
  151. Holtzer, T.O.; Norman, J.M.; Perring, T.M.; Berry, J.S.; Heintz, J.C. Effects of Microenvironment on the Dynamics of Spider-Mite Populations. Exp. Appl. Acarol. 1988, 4, 247–264. [Google Scholar] [CrossRef]
  152. Riahi, E.; Shishehbor, P.; Nemati, A.R.; Saeidi, Z. Temperature effects on development and life table parameters of Tetranychus urticae (Acari: Tetranychidae). Acarologia 2013, 53, 661–672. [Google Scholar]
  153. Gotoh, T.; Bruin, J.; Sabelis, M.W.; Menken, S.B.J. Host Race Formation in Tetranychus urticae: Genetic Differentiation, Host Plant Preference, and Mate Choice in a Tomato and a Cucumber Strain. Entomol. Exp. Appl. 1993, 68, 171–178. [Google Scholar] [CrossRef]
  154. Attia, S.; Grissa, K.L.; Lognay, G.; Bitume, E.; Hance, T.; Mailleux, A.C. A Review of the Major Biological Approaches to Control the Worldwide Pest Tetranychus urticae (Acari: Tetranychidae) with Special Reference to Natural Pesticides. J. Pest Sci. 2013, 86, 361–386. [Google Scholar] [CrossRef]
  155. Shibuya, T.; Itagaki, K.; Ueyama, S.; Hirai, N.; Endo, R. Atmospheric Humidity Influences Oviposition Rate of Tetranychus urticae (Acari: Tetranychidae) Through Morphological Responses of Host Cucumis sativus Leaves. J. Econ. Entomol. 2016, 109, 255–258. [Google Scholar] [CrossRef]
  156. Weintraub, P.G.; Scheffer, S.J.; Visser, D.; Valladares, G.; Correa, A.S.; Shepard, B.M.; Rauf, A.; Murphy, S.T.; Mujica, N.; MacVean, C.; et al. The Invasive Liriomyza huidobrensis (Diptera: Agromyzidae): Understanding Its Pest Status and Management Globally. J. Insect Sci. 2017, 17, 28. [Google Scholar] [CrossRef]
  157. Keularts, J.L.W.; Lindquist, R.K. Increase in Mortality of Prepupae and Pupae of Liriomyza trifolii (Diptera: Agromyzidae) by Manipulation of Relative Humidity and Substrate. Environ. Entomol. 1989, 18, 499–503. [Google Scholar] [CrossRef]
  158. Lanzoni, A.; Bazzocchi, G.G.; Burgio, G.; Fiacconi, M.R. Comparative Life History of Liriomyza trifolii and Liriomyza huidobrensis (Diptera: Agromyzidae) on Beans: Effect of Temperature on Development. Environ. Entomol. 2002, 31, 797–803. [Google Scholar] [CrossRef]
  159. Elkhouly, A.R. Effect of mean temperature and relative humidity on the population abundance of the serpentine leaf miner Liriomyza trifolii (Diptera: Agromyzidae) and its parasitoids Diglyphus isaea (Hymenoptera: Eulophidae) and Opius pallipes (Hymenoptera: Braconidae). Egypt. J. Plant Prot. Res. Inst. 2024, 7, 31–42. [Google Scholar]
  160. Ridland, P.M.; Umina, P.A.; Pirtle, E.I.; Hoffmann, A.A. Potential for Biological Control of the Vegetable Leafminer, Liriomyza sativae (Diptera: Agromyzidae), in Australia with Parasitoid Wasps. Austral Entomol. 2020, 59, 16–36. [Google Scholar] [CrossRef]
  161. Williams, E.C.; Walters, K.F.A. Foliar Application of the Entomopathogenic Nematode Steinernema feltiae Against Leafminers on Vegetables. Biocontrol Sci. Technol. 2000, 10, 61–70. [Google Scholar] [CrossRef]
  162. Collange, B.; Navarrete, M.; Peyre, G.; Mateille, T.; Tchamitchian, M. Root-Knot Nematode (Meloidogyne) Management in Vegetable Crop Production: The Challenge of an Agronomic System Analysis. Crop Prot. 2011, 30, 1251–1262. [Google Scholar] [CrossRef]
  163. Walia, R.K.; Khan, M.R. Root-knot nematodes (Meloidogyne spp.). In Root-Galling Disease of Vegetable Plants; Khan, M.R., Walia, R.K., Eds.; Springer: Singapore, 2023; pp. 1–60. [Google Scholar] [CrossRef]
  164. Expósito, A.; Pujolà, M.; Achaerandio, I.; Giné, A.; Escudero, N.; Fullana, A.M.; Cunquero, M.; Loza-Alvarez, P.; Sorribas, F.J. Tomato and Melon Meloidogyne Resistant Rootstocks Improve Crop Yield but Melon Fruit Quality Is Influenced by the Cropping Season. Front. Plant Sci. 2020, 11, 560024. [Google Scholar] [CrossRef] [PubMed]
  165. Sasanelli, N.; Konrat, A.; Migunova, V.; Toderas, I.; Iurcu-Straistaru, E.; Rusu, S.; Bivol, A.; Andoni, C.; Veronico, P. Review on Control Methods against Plant Parasitic Nematodes Applied in Southern Member States (C Zone) of the European Union. Agriculture 2021, 11, 602. [Google Scholar] [CrossRef]
  166. Masoodi, K.Z.; Khan, A.A.; Hussain, Z.; Wani, W.M.; Rashid, H.; Naik, A.; Nazir, N. Population dynamics of whitefly (Bemisia tabaci) on tomato (Solanum esculentum Mill.) under protected conditions. J. Entomol. Zool. Stud. 2019, 7, 804–807. [Google Scholar]
  167. Birhan, A. Tomato Leafminer [(Tuta absoluta Meyrick) (Lepidoptera: Gelechiidae)] and Its Current Ecofriendly Management Strategies: A Review. J. Agric. Biotechnol. Sustain. Dev. 2018, 10, 11–24. [Google Scholar] [CrossRef]
  168. Monnot, S.; Ravineau, A.; Coindre, E.; Mistral, P.; Leyre, K.; Chadœuf, J.; Cantet, M.; Boissot, N. Genome-Wide Association Studies to Assess Genetic Factors Controlling Cucumber Resistance to CABYV and CMV in Crop Fields and the Attractiveness for Their Aphis gossypii Vector. Hortic. Res. 2025, 12, uhaf016. [Google Scholar] [CrossRef]
  169. Cloyd, R. Ecology of Fungus Gnats (Bradysia spp.) in Greenhouse Production Systems Associated with Disease-Interactions and Alternative Management Strategies. Insects 2015, 6, 325–332. [Google Scholar] [CrossRef]
  170. Sani, I.; Ismail, S.I.; Abdullah, S.; Jalinas, J.; Jamian, S.; Saad, N. A Review of the Biology and Control of Whitefly, Bemisia tabaci (Hemiptera: Aleyrodidae), with Special Reference to Biological Control Using Entomopathogenic Fungi. Insects 2020, 11, 619. [Google Scholar] [CrossRef] [PubMed]
  171. Soha, N.Z.; Shishehbor, P.; Kocheili, F. Thermal Effect on the Biology and Life Tables of Bemisia tabaci Gennadius (Homoptera: Aleyrodidae). Pak. J. Biol. Sci. 2007, 10, 4057–4062. [Google Scholar] [CrossRef] [PubMed]
  172. Döring, T.F. How Aphids Find Their Host Plants, and How They Don’t. Ann. Appl. Biol. 2014, 165, 3–26. [Google Scholar] [CrossRef]
  173. Lopez-Reyes, K.; Armstrong, K.F.; van Tol, R.W.H.M.; Teulon, D.A.J.; Bok, M.J. Colour Vision in Thrips (Thysanoptera). Philos. Trans. R. Soc. B Biol. Sci. 2022, 377, 20210282. [Google Scholar] [CrossRef]
  174. Gomez, M.L.; Montoya, J.A.; García-Jaramillo, D.J.; Cardenas, I. Photo-Selective Covers and Light Quality: Impact on Crop Physiology and Integrated Pest Management. Rev. Colomb. Cienc. Hortícolas 2024, 18, e18075. [Google Scholar] [CrossRef]
  175. Messelink, G.J.; Lambion, J.; Janssen, A.; van Rijn, P.C.J. Biodiversity in and around greenhouses: Benefits and potential risks for pest management. Insects 2021, 12, 933. [Google Scholar] [CrossRef]
  176. Geboloğlu, N.; Yanar, Y.; Yanar, D.; Akyazı, F.; Çakmak, P. Role of Different Rootstocks on Yield and Resistance for Fusarium oxysporium, Verticillium dahliae and Meloidogyne incognita in Grafted Peppers. Eur. J. Hortic. Sci. 2011, 76, 41–44. [Google Scholar] [CrossRef]
  177. Sikandar, A.; Mo, Y.; Chen, B.; Nishat, Y.; Wu, H. Influence of Meloidogyne incognita and Fusarium oxysporum on Growth, Physiological, Biochemical, and Root Morphology in Tomato Hybrids Cultivars. Agronomy 2025, 15, 890. [Google Scholar] [CrossRef]
  178. Jain, V.; Pal, M.; Raj, A.; Khetarpal, S. Photosynthesis and nutrient composition of spinach and fenugreek grown under elevated carbon dioxide concentration. Indian J. Plant Physiol. 2007, 12, 559–562. [Google Scholar] [CrossRef]
  179. Siddique, W.; Hasan, M.U.; Shah, M.S.; Ali, M.M.; Hayat, F.; Mehmood, A. Impact of Blanching and Packaging Materials on Postharvest Quality and Storability of Fresh Spinach. J. Hortic. Sci. Technol. 2021, 4, 7–12. [Google Scholar] [CrossRef]
  180. Eigenbrode, S.D.; Bosque-Pérez, N.A.; Davis, T.S. Insect-Borne Plant Pathogens and Their Vectors: Ecology, Evolution, and Complex Interactions. Annu. Rev. Entomol. 2018, 63, 169–191. [Google Scholar] [CrossRef]
  181. Mauck, K.; Bosque-Pérez, N.A.; Eigenbrode, S.D.; De Moraes, C.M.; Mescher, M.C. Transmission Mechanisms Shape Pathogen Effects on Host–Vector Interactions: Evidence from Plant Viruses. Funct. Ecol. 2012, 26, 1162–1175. [Google Scholar] [CrossRef]
  182. Stiling, P.; Cornelissen, T. How Does Elevated Carbon Dioxide (CO2) Affect Plant–Herbivore Interactions? A Field Experiment and Meta-analysis of CO2-mediated Changes on Plant Chemistry and Herbivore Performance. Glob. Change Biol. 2007, 13, 1823–1842. [Google Scholar] [CrossRef]
  183. Johnson, S.N.; Waterman, J.M.; Hall, C.R. Increased Insect Herbivore Performance under Elevated CO2 Is Associated with Lower Plant Defence Signalling and Minimal Declines in Nutritional Quality. Sci. Rep. 2020, 10, 14553. [Google Scholar] [CrossRef]
  184. Lamichhane, J.R.; Venturi, V. Synergisms between Microbial Pathogens in Plant Disease Complexes: A Growing Trend. Front. Plant Sci. 2015, 6, 385. [Google Scholar] [CrossRef]
  185. Prusky, D.; Alkan, N.; Mengiste, T.; Fluhr, R. Quiescent and Necrotrophic Lifestyle Choice During Postharvest Disease Development. Annu. Rev. Phytopathol. 2013, 51, 155–176. [Google Scholar] [CrossRef]
  186. Lindow, S.E.; Brandl, M.T. Microbiology of the Phyllosphere. Appl. Environ. Microbiol. 2003, 69, 1875–1883. [Google Scholar] [CrossRef] [PubMed]
  187. Romero, F.; Cazzato, S.; Walder, F.; Vogelgsang, S.; Bender, S.F.; van der Heijden, M.G.A. Humidity and high temperature are important for predicting fungal disease outbreaks worldwide. New Phytol. 2022, 234, 1553–1556. [Google Scholar] [CrossRef] [PubMed]
  188. Chomnunti, P.; Hongsanan, S.; Aguirre-Hudson, B.; Tian, Q.; Peršoh, D.; Dhami, M.K.; Alias, A.S.; Xu, J.; Liu, X.; Stadler, M.; et al. The Sooty Moulds. Fungal Divers. 2014, 66, 1–36. [Google Scholar] [CrossRef]
  189. Ferree, D.C.; Hall, F.R. Effects of Soil Water Stress and Two-spotted Spider Mites on Net Photosynthesis and Transpiration of Apple Leaves. Photosynth Res. 1980, 1, 189–197. [Google Scholar] [CrossRef] [PubMed]
  190. Glazebrook, J. Contrasting Mechanisms of Defense against Biotrophic and Necrotrophic Pathogens. Annu. Rev. Phytopathol. 2005, 43, 205–227. [Google Scholar] [CrossRef]
  191. Sances, F.V.; Wyman, J.A.; Ting, I.P.; Steenwyk, R.A.V.; Oatman, E.R. Spider Mite Interactions with Photosynthesis, Transpiration and Productivity of Strawberry 2. Environ. Entomol. 1981, 10, 442–448. [Google Scholar] [CrossRef]
  192. Elad, Y.; Pertot, I. Climate Change Impacts on Plant Pathogens and Plant Diseases. J. Crop Improv. 2014, 28, 99–139. [Google Scholar] [CrossRef]
  193. Boulard, T.; Fatnassi, H.; Roy, J.C.; Lagier, J.; Fargues, J.; Smits, N.; Rougier, M.; Jeannequin, B. Effect of Greenhouse Ventilation on Humidity of inside Air and in Leaf Boundary-Layer. Agric. For. Meteorol. 2004, 125, 225–239. [Google Scholar] [CrossRef]
  194. Garrett, K.A.; Dendy, S.P.; Frank, E.E.; Rouse, M.N.; Travers, S.E. Climate Change Effects on Plant Disease: Genomes to Ecosystems. Annu. Rev. Phytopathol. 2006, 44, 489–509. [Google Scholar] [CrossRef]
  195. Legein, M.; Smets, W.; Vandenheuvel, D.; Eilers, T.; Muyshondt, B.; Prinsen, E.; Samson, R.; Lebeer, S. Modes of Action of Microbial Biocontrol in the Phyllosphere. Front. Microbiol. 2020, 11, 1619. [Google Scholar] [CrossRef]
  196. Broadbent, L. Epidemiology and Control of Tomato Mosaic Virus. Annu. Rev. Phytopathol. 1976, 14, 75–96. [Google Scholar] [CrossRef]
  197. Dombrovsky, A.; Mor, N.; Gantz, S.; Lachman, O.; Smith, E. Disinfection Efficacy of Tobamovirus-Contaminated Soil in Greenhouse-Grown Crops. Horticulturae 2022, 8, 563. [Google Scholar] [CrossRef]
  198. Losenge, T.; Faust, J.E.; Scott, S.W. The Transmission and Management of Tobacco Mosaic Virus in a Greenhouse Environment. Acta Hortic. 2012, 937, 85–90. [Google Scholar] [CrossRef]
  199. Pfeufer, E.; Gauthier, N. Managing Tobamoviruses in Greenhouse Production; University of Kentucky College of Agriculture, Food and Environment: Lexington, KY, USA, 2020. [Google Scholar]
  200. Wang, H.; Li, J.; Cheng, M.; Zhang, F.; Wang, X.; Fan, J.; Wu, L.; Fang, D.; Zou, H.; Xiang, Y. Optimal Drip Fertigation Management Improves Yield, Quality, Water and Nitrogen Use Efficiency of Greenhouse Cucumber. Sci. Hortic. 2019, 243, 357–366. [Google Scholar] [CrossRef]
  201. Aloni, B.; Karni, L.; Rylski, I.; Cohen, Y.; Lee, Y.; Fuchs, M.; Moreshet, S.; Yao, C. Cuticular Cracking in Pepper Fruit. I. Effects of Night Temperature and Humidity. J. Hortic. Sci. Biotechnol. 1998, 73, 743–749. [Google Scholar] [CrossRef]
  202. Rylski, I.; Spigelman, M. Effect of Shading on Plant Development, Yield and Fruit Quality of Sweet Pepper Grown under Conditions of High Temperature and Radlation. Sci. Hortic. 1986, 29, 31–35. [Google Scholar] [CrossRef]
  203. Devaney, E. Thermoregulation in the Life Cycle of Nematodes. Int. J. Parasitol. 2006, 36, 641–649. [Google Scholar] [CrossRef]
  204. Hua, J. Modulation of Plant Immunity by Light, Circadian Rhythm, and Temperature. Curr. Opin. Plant Biol. 2013, 16, 406–413. [Google Scholar] [CrossRef]
  205. Amari, K.; Huang, C.; Heinlein, M. Potential Impact of Global Warming on Virus Propagation in Infected Plants and Agricultural Productivity. Front. Plant Sci. 2021, 12, 649768. [Google Scholar] [CrossRef]
  206. de Koning, A.N.M. Long-Term Temperature Integration of Tomato. Growth and Development under Alternating Temperature Regimes. Sci. Hortic. 1990, 45, 117–127. [Google Scholar] [CrossRef]
  207. Thomidis, T.; Prodromou, I.; Paresidou, M.; Damos, P. Effects of Temperature and Leaf Wetness Duration on Pathogens Causing Preharvest Fruit Rots on Tomato. J. Plant Pathol. 2023, 105, 1431–1448. [Google Scholar] [CrossRef]
  208. Seo, T.C.; Kim, J.H.; Kim, S.Y.; Cho, M.W.; Choi, M.K.; Ryu, H.R.; Shin, H.H.; Lee, C.K. Ventilation at Supra-Optimal Temperature Leading High Relative Humidity Controls Powdery Mildew, Silverleaf Whitefly, Mite and Inhibits the Flowering of Korean Melon in a Greenhouse Cultivation. J. Bio-Environ. Control 2022, 31, 43–51. [Google Scholar] [CrossRef]
  209. O’Neill, T.M.; Shtienberg, D.; Elad, Y. Effect of some host and microclimate factors on infection of tomato stems by Botrytis cinerea. Plant Dis. 1997, 81, 36–40. [Google Scholar] [CrossRef]
  210. Şen, B.; Asan, A. Airborne Fungi in Vegetable Growing Areas of Edirne, Turkey. Aerobiologia 2001, 17, 69–75. [Google Scholar] [CrossRef]
  211. Mieslerová, B.; Cook, R.T.A.; Wheater, C.P.; Lebeda, A. Ecology of Powdery Mildews–Influence of Abiotic Factors on Their Development and Epidemiology. Crit. Rev. Plant Sci. 2022, 41, 365–390. [Google Scholar] [CrossRef]
  212. Choab, N.; Allouhi, A.; Maakoul, A.E.; Kousksou, T.; Saadeddine, S.; Jamil, A. Review on Greenhouse Microclimate and Application: Design Parameters, Thermal Modeling and Simulation, Climate Controlling Technologies. Sol. Energy 2019, 191, 109–137. [Google Scholar] [CrossRef]
  213. Fourtouni, A.; Manetas, Y.; Christias, C. Effects of UV-B Radiation on Growth, Pigmentation, and Spore Production in the Phytopathogenic Fungus Alternaria solani. Can. J. Bot. 1998, 76, 2093–2099. [Google Scholar] [CrossRef]
  214. Raviv, M.; Antigus, Y. UV Radiation Effects on Pathogens and Insect Pests of Greenhouse-Grown Crops. Photochem. Photobiol. 2004, 79, 219–226. [Google Scholar] [CrossRef]
  215. Ulevičius, V.; Pečiulytė, D.; Lugauskas, A.; Andriejauskienė, J. Field Study on Changes in Viability of Airborne Fungal Propagules Exposed to UV Radiation. Environ. Toxicol. 2004, 19, 437–441. [Google Scholar] [CrossRef]
  216. Jeon, Y.; Cho, L.; Park, S.; Kim, S.; Lee, C.; Kim, D. Canopy Temperature and Heat Flux Prediction by Leaf Area Index of Bell Pepper in a Greenhouse Environment: Experimental Verification and Application. Agronomy 2022, 12, 1807. [Google Scholar] [CrossRef]
  217. Kobayashi, M.; Kanto, T.; Fujikawa, T.; Yamada, M.; Ishiwata, M.; Satou, M.; Hisamatu, T. Supplemental UV Radiation Controls Rose Powdery Mildew Disease under the Greenhouse Conditions. Environ. Control Biol. 2014, 51, 157–163. [Google Scholar] [CrossRef]
  218. Ainsworth, E.A.; Long, S.P. What Have We Learned from 15 Years of Free-air CO2 Enrichment (FACE)? A Meta-analytic Review of the Responses of Photosynthesis, Canopy Properties and Plant Production to Rising CO2. New Phytol. 2005, 165, 351–372. [Google Scholar] [CrossRef] [PubMed]
  219. Kirschbaum, M.U.F. Does Enhanced Photosynthesis Enhance Growth? Lessons Learned from CO2 Enrichment Studies. Plant Physiol. 2011, 155, 117–124. [Google Scholar] [CrossRef]
  220. Leakey, A.D.B.; Ainsworth, E.A.; Bernacchi, C.J.; Rogers, A.; Long, S.P.; Ort, D.R. Elevated CO2 Effects on Plant Carbon, Nitrogen, and Water Relations: Six Important Lessons from FACE. J. Exp. Bot. 2009, 60, 2859–2876. [Google Scholar] [CrossRef]
  221. Berlinger, M.J.; Jarvis, W.R.; Jewett, T.J.; Lebiush-Mordechi, S. Managing the greenhouse crop and crop environment. In Greenhouse Ecosystems; Stanhill, G., Enoch, H.Z., Eds.; Elsevier: Amsterdam, The Netherlands, 1999; pp. 97–123. [Google Scholar] [CrossRef]
  222. Pangga, I.B.; Hanan, J.; Chakraborty, S. Climate Change Impacts on Plant Canopy Architecture: Implications for Pest and Pathogen Management. Eur. J. Plant Pathol. 2013, 135, 595–610. [Google Scholar] [CrossRef]
  223. Majdoubi, H.; Boulard, T.; Fatnassi, H.; Bouirden, L. Airflow and Microclimate Patterns in a One-Hectare Canary Type Greenhouse: An Experimental and CFD Assisted Study. Agric. For. Meteorol. 2009, 149, 1050–1062. [Google Scholar] [CrossRef]
  224. Lake, J.A.; Wade, R.N. Plant-Pathogen Interactions and Elevated CO2: Morphological Changes in Favour of Pathogens. J. Exp. Bot. 2009, 60, 3123–3131. [Google Scholar] [CrossRef] [PubMed]
  225. Panchal, S.; Chitrakar, R.; Thompson, B.K.; Obulareddy, N.; Roy, D.; Hambright, W.S.; Melotto, M. Regulation of Stomatal Defense by Air Relative Humidity. Plant Physiol. 2016, 172, 2021–2032. [Google Scholar] [CrossRef] [PubMed]
  226. Abawi, G.S.; Widmer, T.L. Impact of Soil Health Management Practices on Soilborne Pathogens, Nematodes and Root Diseases of Vegetable Crops. Appl. Soil Ecol. 2000, 15, 37–47. [Google Scholar] [CrossRef]
  227. Dixon, G.R. Water, Irrigation and Plant Diseases. CABI Rev. 2015, 1–18. [Google Scholar] [CrossRef]
  228. Jones, H.G. Plants and Microclimate: A Quantitative Approach to Environmental Plant Physiology; Cambridge University Press: Cambridge, UK, 1992. [Google Scholar]
  229. Bonato, O.; Lurette, A.; Vidal, C.; Fargues, J. Modelling Temperature-dependent Bionomics of Bemisia tabaci (Q-biotype). Physiol. Entomol. 2007, 32, 50–55. [Google Scholar] [CrossRef]
  230. Yunis, H.; Elad, Y.; Mahrer, Y. Effects of Air Temperature, Relative Humidity and Canopy Wetness on Gray Mold of Cucumbers in Unheated Greenhouses. Phytoparasitica 1990, 18, 203–215. [Google Scholar] [CrossRef]
  231. Suthaparan, A.; Solhaug, K.A.; Stensvand, A.; Gislerød, H.R. Determination of UV Action Spectra Affecting the Infection Process of Oidium neolycopersici, the Cause of Tomato Powdery Mildew. J. Photochem. Photobiol. B Biol. 2016, 156, 41–49. [Google Scholar] [CrossRef] [PubMed]
  232. Eastburn, D.M.; McElrone, A.J.; Bilgin, D.D. Influence of Atmospheric and Climatic Change on Plant–Pathogen Interactions. Plant Pathol. 2011, 60, 54–69. [Google Scholar] [CrossRef]
  233. Morris, K.A.; Langston, D.B.; Dutta, B.; Davis, R.F.; Timper, P.; Noe, J.P.; Dickson, D.W. Evidence for a Disease Complex Between Pythium aphanidermatum and Root-Knot Nematodes in Cucumber. Plant Health Prog. 2016, 17, 200–201. [Google Scholar] [CrossRef]
  234. Körner, O.; Holst, N. Model-based humidity control of Botrytis in greenhouse cultivation. Acta Hortic. 2005, 691, 141–148. [Google Scholar] [CrossRef]
  235. Czosnek, H.; Ghanim, M.; Ghanim, M. The Circulative Pathway of Begomoviruses in the Whitefly Vector Bemisia tabaci—Insights from Studies with Tomato Yellow Leaf Curl Virus. Ann. Appl. Biol. 2002, 140, 215–231. [Google Scholar] [CrossRef]
  236. Yıldız, İ. Greenhouse Engineering; CRC Press: Boca Raton, FL, USA, 2021. [Google Scholar]
  237. Sharma, R.; Verma, S. Environment-Pathogen Interaction in Plant Diseases. Agric. Rev. 2019, 40, 192. [Google Scholar] [CrossRef]
  238. Ahmed, Z.; Gui, D.; Qi, Z.; Liu, Y.; Liu, Y.; Azmat, M. Agricultural System Modeling: Current Achievements, Innovations, and Future Roadmap. Arab. J. Geosci. 2022, 15, 363. [Google Scholar] [CrossRef]
  239. Kaur, J.; Bala, R.; Singh, P. Forecasting of wheat diseases: Insights, methods and challenges. In New Horizons in Wheat and Barley Research; Gupta, O.P., Pandey, G.C., Singh, G.P., Eds.; Springer: Singapore, 2022; pp. 21–75. [Google Scholar] [CrossRef]
  240. Fountas, S.; Carli, G.; Sørensen, C.G.; Tsiropoulos, Z.; Cavalaris, C.; Vatsanidou, A.; Liakos, B.; Canavari, M.; Wiebensohn, J.; Tisserye, B. Farm Management Information Systems: Current Situation and Future Perspectives. Comput. Electron. Agric. 2015, 115, 40–50. [Google Scholar] [CrossRef]
  241. Messelink, G.; Leman, A. Are low humidity levels a limiting factor for spider mite control by phytoseiid predators under fluctuating climatic conditions? Acta Hortic. 2020, 1271, 101–102. [Google Scholar]
  242. Shtienberg, D. Will Decision-Support Systems Be Widely Used for the Management of Plant Diseases? Annu. Rev. Phytopathol. 2013, 51, 1–16. [Google Scholar] [CrossRef]
  243. Small, I.M.; Joseph, L.; Fry, W.E. Development and Implementation of the BlightPro Decision Support System for Potato and Tomato Late Blight Management. Comput. Electron. Agric. 2015, 115, 57–65. [Google Scholar] [CrossRef]
  244. Basit, A.; Ullah, F.; Akhtar, M.R.; Humza, M.; Ghafar, M.A.; Hyder, M.; Haq, I.U.; Hou, Y. Transforming Tuta absoluta Management: A Synergistic Approach Integrating Sustainability, Biological Control, and Biotechnological Innovations. Insects 2025, 16, 1173. [Google Scholar] [CrossRef]
  245. Giakoumoglou, N.; Pechlivani, E.-M.; Frangakis, N.; Tzovaras, D. Enhancing Tuta absoluta Detection on Tomato Plants: Ensemble Techniques and Deep Learning. AI 2023, 4, 996–1009. [Google Scholar] [CrossRef]
  246. Chan, K.H.; Moerkens, R.; Brenard, N.; Huysmans, M.; Leirs, H.; Sluydts, V. Data-driven Approach to Weekly Forecast of the Western Flower Thrips Frankliniella occidentalis (Pergande) Population in a Pepper Greenhouse with an Ensemble Model. Pest Manag. Sci. 2025, 81, 3378–3390. [Google Scholar] [CrossRef]
  247. Körner, O.; Jakobsen, L. A Thrips Pest Pressure Model for Greenhouse Climate Control. Acta Hortic. 2006, 407–414. [Google Scholar] [CrossRef]
  248. Rose, D.C.; Sutherland, W.J.; Parker, C.; Lobley, M.; Winter, M.; Morris, C.; Twining, S.; Ffoulkes, C.; Amano, T.; Dicks, L.V. Decision Support Tools for Agriculture: Towards Effective Design and Delivery. Agric. Syst. 2016, 149, 165–174. [Google Scholar] [CrossRef]
  249. Magarey, R.D.; Sutton, T.B.; Thayer, C.L. A Simple Generic Infection Model for Foliar Fungal Plant Pathogens. Phytopathology 2005, 95, 92–100. [Google Scholar] [CrossRef]
  250. Rossi, V.; Caffi, T.; Salinari, F. Helping Farmers Face the Increasing Complexity of Decision-Making for Crop Protection. Phytopathol. Mediterr. 2012, 51, 457–479. [Google Scholar]
  251. Ferentinos, K.P. Deep Learning Models for Plant Disease Detection and Diagnosis. Comput. Electron. Agric. 2018, 145, 311–318. [Google Scholar] [CrossRef]
  252. Jeger, M.J.; Pautasso, M. Plant Disease and Global Change–the Importance of Long-term Data Sets. New Phytol. 2008, 177, 8–11. [Google Scholar] [CrossRef]
  253. Fanourakis, D.; Makraki, T.; Spyrou, G.P.; Karavidas, I.; Tsaniklidis, G.; Ntatsi, G. Environmental Drivers of Fruit Quality and Shelf Life in Greenhouse Vegetables: Species-Specific Insights. Agronomy 2026, 16, 48. [Google Scholar]
  254. Bale, J.S.; Van Lenteren, J.C.; Bigler, F. Biological Control and Sustainable Food Production. Phil. Trans. R. Soc. B 2008, 363, 761–776. [Google Scholar] [CrossRef] [PubMed]
  255. Van Lenteren, J.C. The State of Commercial Augmentative Biological Control: Plenty of Natural Enemies, but a Frustrating Lack of Uptake. BioControl 2012, 57, 1–20. [Google Scholar] [CrossRef]
  256. Wraight, S.P.; Ugine, T.A.; Ramos, M.E.; Sanderson, J.P. Efficacy of Spray Applications of Entomopathogenic Fungi against Western Flower Thrips Infesting Greenhouse Impatiens under Variable Moisture Conditions. Biol. Control 2016, 97, 31–47. [Google Scholar] [CrossRef]
  257. Lobell, D.B.; Asseng, S. Comparing Estimates of Climate Change Impacts from Process-Based and Statistical Crop Models. Environ. Res. Lett. 2017, 12, 015001. [Google Scholar] [CrossRef]
  258. Bardin, M.; Gullino, M.L. Fungal diseases. In Integrated Pest and Disease Management in Greenhouse Crops; Gullino, M.L., Albajes, R., Nicot, P.C., Eds.; Springer: Cham, Switzerland, 2020; pp. 55–100. [Google Scholar] [CrossRef]
  259. Liakos, K.; Busato, P.; Moshou, D.; Pearson, S.; Bochtis, D. Machine Learning in Agriculture: A Review. Sensors 2018, 18, 2674. [Google Scholar] [CrossRef]
  260. Mahlein, A.-K. Plant Disease Detection by Imaging Sensors–Parallels and Specific Demands for Precision Agriculture and Plant Phenotyping. Plant Dis. 2016, 100, 241–251. [Google Scholar] [CrossRef]
  261. Zhang, N.; Yang, G.; Pan, Y.; Yang, X.; Chen, L.; Zhao, C. A Review of Advanced Technologies and Development for Hyperspectral-Based Plant Disease Detection in the Past Three Decades. Remote Sens. 2020, 12, 3188. [Google Scholar] [CrossRef]
  262. Ariesen-Verschuur, N.; Verdouw, C.; Tekinerdogan, B. Digital Twins in Greenhouse Horticulture: A Review. Comput. Electron. Agric. 2022, 199, 107183. [Google Scholar] [CrossRef]
  263. Jones, J.W.; Antle, J.M.; Basso, B.; Boote, K.J.; Conant, R.T.; Foster, I.; Godfray, H.C.J.; Herrero, M.; Howitt, R.E.; Janssen, S.; et al. Toward a New Generation of Agricultural System Data, Models, and Knowledge Products: State of Agricultural Systems Science. Agric. Syst. 2017, 155, 269–288. [Google Scholar] [CrossRef] [PubMed]
  264. Kim, B.S.; Cho, H.J.; Hwang, H.S.; Cha, Y.S. Gray Leaf Spot of Tomato Caused by Stemphylium solani. Plant Pathol. J. 1999, 6, 348–350. [Google Scholar]
  265. Lin, S.; Fan, H. The Occurrence and Mechanism of Field Resistance to Boscalid and Pyraclostrobin in Stemphylium solani, the Causal Agent of Tomato Gray Leaf Spot in China. Pestic. Biochem. Physiol. 2024, 204, 106028. [Google Scholar] [CrossRef]
  266. Su, X.; Zhu, G.; Huang, Z.; Wang, X.; Guo, Y.; Li, B.; Du, Y.; Yang, W.; Gao, J. Fine Mapping and Molecular Marker Development of the Sm Gene Conferring Resistance to Gray Leaf Spot (Stemphylium spp.) in Tomato. Theor. Appl. Genet. 2019, 132, 871–882. [Google Scholar] [CrossRef] [PubMed]
  267. Oliver, R.P.; Henricot, B.; Segers, G. Cladosporium fulvum, cause of leaf mould of tomato. In Fungal Pathology; Kronstad, J.W., Ed.; Springer: Dordrecht, The Netherlands, 2000; pp. 65–91. [Google Scholar] [CrossRef]
  268. Colmán, A.A.; Alves, J.L.; da Silva, M.; Barreto, R.W. Phoma destructiva Causing Blight of Tomato Plants: A New Fungal Threat for Tomato Plantations in Brazil? Trop. Plant Pathol. 2018, 43, 257–262. [Google Scholar] [CrossRef]
  269. Deb, D.; Khan, A.; Dey, N. Phoma Diseases: Epidemiology and Control. Plant Pathol. 2020, 69, 1203–1217. [Google Scholar] [CrossRef]
  270. Rashid, T.S.; Sijam, K.; Nasehi, A.; Kadir, J.; Saud, H.M.; Awla, H.K. Occurrence of Phoma Blight Caused by Phoma destructiva on Tomato (Solanum lycopersicum) in Malaysia. Plant Dis. 2016, 100, 1241. [Google Scholar] [CrossRef]
  271. Beltran, M.; Delgado, J.C.; Valdivia, A.G.; Hernandez, A.; Garcia, A.M. First Report of Fusarium equiseti Causing Root and Crown Rot in Tomato in Mexico. Plant Dis. 2023, 107, 2542. [Google Scholar] [CrossRef]
  272. Horinouchi, H.; Watanabe, H.; Taguchi, Y.; Muslim, A.; Hyakumachi, M. Biological Control of Fusarium Wilt of Tomato with Fusarium equiseti GF191 in Both Rock Wool and Soil Systems. BioControl 2011, 56, 915–923. [Google Scholar] [CrossRef]
  273. Olsen, M.W. Mycosphaerella melonis on Greenhouse Cucumber. Plant Dis. 1981, 65, 157. [Google Scholar] [CrossRef]
  274. Pharis, V.L.; Kemp, T.R.; Knavel, D.E. Host Plant-Emitted Volatiles as a Factor in Susceptibility in Vitro of Cucumis and Cucurbita spp. to the Fungus Mycosphaerella melonis. Sci. Hortic. 1982, 17, 311–317. [Google Scholar] [CrossRef]
  275. Fu, J.; Wu, Y.; Yan, X.; Wang, L.; Zhang, S.; Luo, Y. Isolation and Identification of the Endophytic Fungus J2-3 and Its Disease-Preventive and Growth-Promoting Effects on Cucumber. Braz. J. Microbiol. 2023, 54, 1115–1125. [Google Scholar] [CrossRef]
  276. Imran, M.; Khalifa, H.A.; Sun, Z.; Bilal, M.S.; El-Wahed, M.H.A.; Abo-Elyousr, K.A.M.; Ali, E.F.; Li, C. Insights into the Dynamics of Biochemical Profile and Relative Gene Expression of Cucumber Fruits Associated with Fusarium Spoilage. J. Plant Dis. Prot. 2025, 132, 36. [Google Scholar] [CrossRef]
  277. Braun, U.; Ale-Agha, N.; Bolay, A.; Boyle, H.; Brielmaier-Liebetanz, U.; Emgenbroich, D.; Kruse, J.; Kummer, V. New records of powdery mildew fungi (Erysiphaceae). Schlechtendalia 2009, 19, 39–46. [Google Scholar] [CrossRef]
  278. Hossain, M.M.; Sultana, F.; Mostafa, M.; Ferdus, H.; Rahman, M.; Rana, J.A.; Islam, S.S.; Adhikary, S.; Sannal, A.; Al Emran Hosen, M.; et al. Plant Disease Dynamics in a Changing Climate: Impacts, Molecular Mechanisms, and Climate-Informed Strategies for Sustainable Management. Discov. Agric. 2024, 2, 132. [Google Scholar] [CrossRef]
  279. Kim, M.-J.; Kim, Y.-K.; Park, S.-H.; Park, J.-H.; Hong, S.-J.; Shim, C.-K. Control of Cucumber Powdery Mildew Using Resistant Cultivars and Organic Agricultural Materials. J. Microbiol. Biotechnol. 2024, 35, e2409030. [Google Scholar] [CrossRef] [PubMed]
  280. Peng, X.; Zhang, H.; Bai, Z.; Li, B. Induced resistance to Cladosporium cucumerinum in cucumber by pectinases extracted from Penicillium oxalicum. Phytoparasitica 2004, 32, 377–387. [Google Scholar] [CrossRef]
  281. Zhao, H.; Wang, B.-C.; Zhao, H.-C.; Wang, J.-B. Stress stimulus-induced resistance to Cladosporium cucumerinum in cucumber seedlings. Colloids Surf. B Biointerfaces 2005, 44, 36–40. [Google Scholar] [CrossRef]
  282. Kazerooni, E.A.; Maharachchikumbura, S.S.N.; Al-Sadi, A.M.; Kang, S.-M.; Yun, B.-W.; Lee, I.-J. Biocontrol Potential of Bacillus amyloliquefaciens against Botrytis pelargonii and Alternaria alternata on Capsicum annuum. J. Fungi 2021, 7, 472. [Google Scholar] [CrossRef]
  283. Sid, A.; Ezziyyani, M.; Egea-Gilabert, C.; Candela, M.E. Selecting Bacterial Strains for Use in the Biocontrol of Diseases Caused by Phytophthora capsici and Alternaria alternata in Sweet Pepper Plants. Biol. Plant. 2003, 46, 569–574. [Google Scholar] [CrossRef]
  284. Harp, T.; Kuhn, P.; Roberts, P.D.; Pernezny, K.L. Management and cross-infectivity potential of Colletotrichum acutatum causing anthracnose on bell pepper in Florida. Phytoparasitica 2014, 42, 31–39. [Google Scholar] [CrossRef]
  285. Dunn, A.R.; Lange, H.W.; Smart, C.D. Evaluation of Commercial Bell Pepper Cultivars for Resistance to Phytophthora Blight (Phytophthora capsici). Plant Health Prog. 2014, 15, 19–24. [Google Scholar] [CrossRef]
  286. Mohammadbagheri, L.; Nasr-Esfahani, M.; Abdossi, V.; Naderi, D. Genetic Diversity and Biochemical Analysis of Capsicum annuum (Bell Pepper) in Response to Root and Basal Rot Disease, Phytophthora capsici. Phytochemistry 2021, 190, 112884. [Google Scholar] [CrossRef]
  287. Parra, G.; Ristaino, J.B. Resistance to Mefenoxam and Metalaxyl Among Field Isolates of Phytophthora capsici Causing Phytophthora Blight of Bell Pepper. Plant Dis. 2001, 85, 1069–1075. [Google Scholar] [CrossRef]
  288. Massire, A.; Cussonneau, F.; Elbelt, S.; Constant, C.; Bardin, M.; Moury, B.; Lefebvre, V. Powdery mildew caused by Leveillula taurica (synonym: Phyllactinia taurica): A global challenge for pepper production. Mol. Plant Pathol. 2025, 26, e70128. [Google Scholar] [CrossRef]
  289. Catara, V. Pseudomonas corrugata: Plant Pathogen and/or Biological Resource? Mol. Plant Pathol. 2007, 8, 233–244. [Google Scholar] [CrossRef]
  290. Lai, M. Occurrence of Pseudomonas corrugata on Tomato in California. Plant Dis. 1983, 67, 110. [Google Scholar] [CrossRef]
  291. Powell, M.; Gundersen, B.; Miles, C.A.; Humann, J.L.; Schroeder, B.K.; Inglis, D.A. First Report of Tomato Pith Necrosis (Pseudomonas corrugata) on Tomato (Solanum lycopersicum) in Washington. Plant Dis. 2013, 97, 1381. [Google Scholar] [CrossRef]
  292. Alippi, A.M.; Bo, E.D.; Ronco, L.B.; López, M.V.; López, A.C.; Aguilar, O.M. Pseudomonas Populations Causing Pith Necrosis of Tomato and Pepper in Argentina Are Highly Diverse. Plant Pathol. 2003, 52, 287–302. [Google Scholar] [CrossRef]
  293. Lee, Y.J.; Luo, H.; Kim, W.G.; Yu, J.M. First report of tomato pith necrosis caused by Pseudomonas mediterranea in South Korea. Plant Dis. 2022, 106, 2985. [Google Scholar] [CrossRef]
  294. Xu, H.-L.; Xu, L.; Qin, F.; Ma, G.; Yu, Y.; Shah, S.K. Biological Pest and Disease Control in Greenhouse Vegetable Production. Acta Hortic. 2008, 767, 229–238. [Google Scholar] [CrossRef]
  295. Trantas, E.A.; Sarris, P.F.; Pentari, M.G.; Mpalantinaki, E.E.; Ververidis, F.N.; Goumas, D.E. Diversity among Pseudomonas corrugata and Pseudomonas mediterranea isolated from tomato and pepper showing symptoms of pith necrosis in Greece. Plant Pathol. 2015, 64, 307–318. [Google Scholar] [CrossRef]
  296. Chang, R.J. Dissemination of Clavibacter michiganensis subsp. michiganensis by Practices Used to Produce Tomato Transplants. Phytopathology 1991, 81, 1276. [Google Scholar] [CrossRef]
  297. Nandi, M.; Macdonald, J.; Liu, P.; Weselowski, B.; Yuan, Z.-C. Clavibacter michiganensis ssp. michiganensis: Bacterial Canker of Tomato, Molecular Interactions and Disease Management. Mol. Plant Pathol. 2018, 19, 2036–2050. [Google Scholar] [CrossRef]
  298. Tancos, M.A.; Chalupowicz, L.; Barash, I.; Manulis-Sasson, S.; Smart, C.D. Tomato Fruit and Seed Colonization by Clavibacter michiganensis subsp. michiganensis through External and Internal Routes. Appl. Environ. Microbiol. 2013, 79, 6948–6957. [Google Scholar] [CrossRef] [PubMed]
  299. Kolomiiets, Y.; Grygoryuk, I.; Butsenko, L.; Bohoslavets, V.; Blume, Y.; Yemets, A. Identification and Biological Properties of the Pathogen of Soft Rot of Tomatoes in the Greenhouse. Open Agric. J. 2020, 14, 290–298. [Google Scholar] [CrossRef]
  300. Perfileva, A.I.; Strekalovskaya, E.I.; Klushina, N.V.; Gorbenko, I.V.; Krutovsky, K.V. The Causative Agent of Soft Rot in Plants, the Phytopathogenic Bacterium Pectobacterium carotovorum subsp. carotovorum: A Brief Description and an Overview of Methods to Control It. Agronomy 2025, 15, 1578. [Google Scholar] [CrossRef]
  301. Hernandez, M.N.; Lindow, S.E. Pseudomonas syringae Increases Water Availability in Leaf Microenvironments via Production of Hygroscopic Syringafactin. Appl. Environ. Microbiol. 2019, 85, e01014-19. [Google Scholar] [CrossRef]
  302. Burdman, S.; Walcott, R.O.N. Acidovorax citrulli: Generating Basic and Applied Knowledge to Tackle a Global Threat to the Cucurbit Industry. Mol. Plant Pathol. 2012, 13, 805–815. [Google Scholar] [CrossRef]
  303. Elhalag, K.M.; Ahmad, A.A.; Elsharkawy, M.M.; Huang, Q.; Nasr-Eldin, M.A. A novel Pectobacterium brasiliense-infecting phage from Egypt with biocontrol potential against soft rot in vegetables. Front. Microbiol. 2025, 16, 1621267. [Google Scholar] [CrossRef]
  304. Hong, S.-M.; Park, K.-T.; Ten, L.N.; Back, C.-G.; Kang, I.-K.; Lee, S.-Y.; Jung, H.-Y. First Report of Soft Rot Caused by Pectobacterium brasiliense on Cucumber in Korea. Res. Plant Dis. 2023, 29, 304–309. [Google Scholar] [CrossRef]
  305. Meng, X.; Chai, A.; Shi, Y.; Xie, X.; Ma, Z.; Li, B. Emergence of Bacterial Soft Rot in Cucumber Caused by Pectobacterium carotovorum subsp. brasiliense in China. Plant Dis. 2017, 101, 279–287. [Google Scholar] [CrossRef]
  306. Dhakal, U.; Dobhal, S.; Alvarez, A.M.; Arif, M. Phylogenetic analyses of xanthomonads causing bacterial leaf spot of tomato and pepper: Xanthomonas euvesicatoria revealed homologous populations despite distant geographical distribution. Microorganisms 2019, 7, 462. [Google Scholar] [CrossRef] [PubMed]
  307. Utami, D.; Meale, S.J.; Young, A.J. A Pan-Global Study of Bacterial Leaf Spot of Chilli Caused by Xanthomonas spp. Plants 2022, 11, 2291. [Google Scholar] [CrossRef]
  308. Liao, C.-H. Control of Foodborne Pathogens and Soft-Rot Bacteria on Bell Pepper by Three Strains of Bacterial Antagonists. J. Food Prot. 2009, 72, 85–92. [Google Scholar] [CrossRef] [PubMed]
  309. Perombelon, M.C.M.; Kelman, A. Ecology of the Soft Rot Erwinias. Annu. Rev. Phytopathol. 1980, 18, 361–387. [Google Scholar] [CrossRef]
  310. Kaplan, I.B.; Zhang, L.; Palukaitis, P. Characterization of Cucumber Mosaic Virus. Virology 1998, 246, 221–231. [Google Scholar] [CrossRef] [PubMed]
  311. Kobori, T.; Ryang, B.-S.; Natsuaki, T.; Kosaka, Y. A New Technique to Select Mild Strains of Cucumber Mosaic Virus. Plant Dis. 2005, 89, 879–882. [Google Scholar] [CrossRef] [PubMed]
  312. Ahsan, M.; Ashfaq, M.; Amer, M.A.; Shakeel, M.T.; Mehmood, M.A.; Umar, M.; Al-Saleh, M.A. Zucchini Yellow Mosaic Virus (ZYMV) as a Serious Biotic Stress to Cucurbits: Prevalence, Diversity, and Its Implications for Crop Sustainability. Plants 2023, 12, 3503. [Google Scholar] [CrossRef]
  313. Desbiez, C.; Lecoq, H. Zucchini Yellow Mosaic Virus. Plant Pathol. 1997, 46, 809–829. [Google Scholar] [CrossRef]
  314. Wong, S.M.; Chng, C.G.; Chng, C.Y.; Chong, P.L. Characterization of an Isolate of Zucchini Yellow Mosaic Virus Form Cucumber in Singapore. J. Phytopathol. 1994, 141, 355–368. [Google Scholar] [CrossRef]
  315. Grumet, R.; Kabelka, E.; McQueen, S.; Wai, T.; Humphrey, R. Characterization of Sources of Resistance to the Watermelon Strain of Papaya Ringspot Virus in Cucumber: Allelism and Co-Segregation with Other Potyvirus Resistances. Theor. Appl. Genet. 2000, 101, 463–472. [Google Scholar] [CrossRef]
  316. Kramer, L.D. Complexity of Virus–Vector Interactions. Curr. Opin. Virol. 2016, 21, 81–86. [Google Scholar] [CrossRef]
  317. Širca, S.; Stare, B.G.; Pleško, I.M.; Marn, M.V.; Urek, G.; Javornik, B. Xiphinema rivesi from Slovania Transmit Tobacco Ringspot Virus and Tomato Ringspot Virus to Cucumber Bait Plants. Plant Dis. 2007, 91, 770. [Google Scholar] [CrossRef]
  318. Douthit, L.B. Some Effects of Temperature on Xiphinema americanum and Infection of Cucumber by Tobacco Ringspot Virus. Phytopathology 1975, 65, 134. [Google Scholar] [CrossRef]
  319. Wang, X.; Zhou, C.; Gao, X.; Luo, J.; He, Y.; Wang, L.; Xu, Z.; Zhu, Z.; Xu, Y. A Real-Time Visualized TRSV-Based Gene Silencing Method Using Trichome as a Selected Marker in Cucumber. Plant Sci. 2025, 360, 112728. [Google Scholar] [CrossRef] [PubMed]
  320. Li, N.; Yu, C.; Yin, Y.; Gao, S.; Wang, F.; Jiao, C.; Yao, M. Pepper Crop Improvement Against Cucumber Mosaic Virus (CMV): A Review. Front. Plant Sci. 2020, 11, 598798. [Google Scholar] [CrossRef] [PubMed]
  321. Ormeño, J.; Sepúlveda, P.; Rojas, R.; Araya, J.E. Datura genus weeds as an epidemiological factor of Alfalfa Mosaic Virus (AMV), Cucumber Mosaic Virus (CMV), and Potato Virus Y (PVY) on Solanaceous crops. Agric. Téc. 2006, 66, 3–13. [Google Scholar] [CrossRef]
  322. de Moraes Echer, M.; da Costa, C.P. Reaction of Sweet Pepper to the Potato Virus Y (PVYm). Sci. Agric. 2002, 59, 309–314. [Google Scholar] [CrossRef]
  323. Moodley, V.; Naidoo, R.; Gubba, A. Screening of Pepper (Capsicum annuum L.) Lines for Resistance to an Isolate of Potato Virus Y (PVY) Occurring in KwaZulu-Natal (KZN), Republic of South Africa. Crop Prot. 2015, 68, 36–40. [Google Scholar] [CrossRef]
  324. Radcliffe, E.B.; Ragsdale, D.W. Aphid-Transmitted Potato Viruses: The Importance of Understanding Vector Biology. Am. J. Potato Res. 2002, 79, 353–386. [Google Scholar] [CrossRef]
  325. Abdalla, O.A.; Ali, A. First Report of Alfalfa Mosaic Virus Associated with Severe Mosaic and Mottling of Pepper (Capsicum annuum) and White Clover (Trifolium repens) in Oklahoma. Plant Dis. 2012, 96, 1705. [Google Scholar] [CrossRef]
  326. Amiri-Kazaz, L.M.; Nachappa, P.; Szczepaniec, A. Evaluation of Host Plant Resistance to Alfalfa Mosaic Virus in Peppers in Greenhouse and Field. Front. Agron. 2025, 7, 1679604. [Google Scholar] [CrossRef]
  327. Elbeshehy, E.K.F.; Hassan, W.M.; Baeshen, A.A. Controlling Pepper Mild Mottle Virus (PMMoV) Infection in Pepper Seedlings by Use of Chemically Synthetic Silver Nanoparticles. Molecules 2022, 28, 139. [Google Scholar] [CrossRef]
  328. Ochar, K.; Ko, H.-C.; Woo, H.-J.; Hahn, B.-S.; Hur, O. Pepper Mild Mottle Virus: An Infectious Pathogen in Pepper Production and a Potential Indicator of Domestic Water Quality. Viruses 2023, 15, 282. [Google Scholar] [CrossRef]
  329. van Houten, Y.M.; van Rijn, P.C.J.; Tanigoshi, L.K.; van Stratum, P.; Bruin, J. Preselection of Predatory Mites to Improve Year-round Biological Control of Western Flower Thrips in Greenhouse Crops. Entomol. Exp. Appl. 1995, 74, 225–234. [Google Scholar] [CrossRef]
  330. Reitz, S.R. Biology and ecology of flower thrips in relation to Tomato Spotted Wilt Virus. Acta Hortic. 2004, 659, 129–137. [Google Scholar] [CrossRef]
  331. Reitz, S.R.; Gao, Y.; Kirk, W.D.J.; Hoddle, M.S.; Leiss, K.A.; Funderburk, J.E. Invasion Biology, Ecology, and Management of Western Flower Thrips. Annu. Rev. Entomol. 2020, 65, 17–37. [Google Scholar] [CrossRef]
  332. Ullah, M.S.; Lim, U.T. Life History Characteristics of Frankliniella occidentalis and Frankliniella intonsa (Thysanoptera: Thripidae) in Constant and Fluctuating Temperatures. J. Econ. Entomol. 2015, 108, 1000–1009. [Google Scholar] [CrossRef]
  333. Boughton, A.J.; Hoover, K.; Felton, G.W. Impact of Chemical Elicitor Applications on Greenhouse Tomato Plants and Population Growth of the Green Peach Aphid, Myzus persicae. Entomol. Exp. Appl. 2006, 120, 175–188. [Google Scholar] [CrossRef]
  334. Dedryver, C.-A.; Le Ralec, A.; Fabre, F. The Conflicting Relationships between Aphids and Men: A Review of Aphid Damage and Control Strategies. Comptes Rendus. Biol. 2010, 333, 539–553. [Google Scholar] [CrossRef]
  335. Bhagyasree, S.N.; Baradevanal, G.; Hussain, Z.; Singh, P.K.; Suroshe, S. Weather-Based Forewarning Model for the Incidence of Mite, Tetranychus urticae Koch (Acari: Tetranychidae) in Tomato. J. Hortic. Sci. 2024, 19, 146–152. [Google Scholar] [CrossRef]
  336. Pokle, P.P.; Shukla, A. Population dynamics of two-spotted spider mite, Tetranychus urticae (Koch) (Acari: Tetranychidae) on tomato under polyhouse condition. Ecoscan 2015, 9, 859–862. [Google Scholar]
  337. Schnitzler, W.H. Pest and Disease Management of Soilless Culture. Acta Hortic. 2004, 648, 191–203. [Google Scholar] [CrossRef]
  338. Seid, A.; Fininsa, C.; Mekete, T.; Decraemer, W.; Wesemael, W.M.L. Tomato (Solanum lycopersicum) and Root-Knot Nematodes (Meloidogyne spp.)—A Century-Old Battle. Nematology 2015, 17, 995–1009. [Google Scholar] [CrossRef]
  339. Perry, K.L.; Zhang, L.; Shintaku, M.H.; Palukaitis, P. Mapping Determinants in Cucumber Mosaic Virus for Transmission by Aphis gossypii. Virology 1994, 205, 591–595. [Google Scholar] [CrossRef]
  340. Rodríguez, D.; Coy-Barrera, E. Overview of Updated Control Tactics for Western Flower Thrips. Insects 2023, 14, 649. [Google Scholar] [CrossRef]
  341. Ehara, S. Revision of the Spider Mite Family Tetranychidae of Japan (Acari, Prostigmata). Species Divers. 1999, 4, 63–141. [Google Scholar] [CrossRef]
  342. Reddy, G.V.P.; Baskaran, P. Damage Potential of the Spider Mite Tetranychus ludeni (Acari: Tetranychidae) on Four Varieties of Eggplant. Int. J. Trop. Insect Sci. 2006, 26, 48–56. [Google Scholar] [CrossRef]
  343. Stephan, Z.A.; Trudgill, D.L. Development of four populations of Meloidogyne hapla on two cultivars of cucumber at different temperatures. Nematologica 1982, 28, 144–152. [Google Scholar]
  344. Satar, S.; Kersting, U.; Uygun, N. Effect of Temperature on Population Parameters of Aphis gossypii Glover and Myzus persicae (Sulzer) (Homoptera: Aphididae) on Pepper. J. Plant Dis. Prot. 2008, 115, 69–74. [Google Scholar] [CrossRef]
  345. Fadaei, E.; Mehrabadi, M.; Bagheri, A.; Rashed, A.; Fathipour, Y. Unraveling the Impact of Greenhouse Pepper Resistance on Biological Performance of the Broad Mite Polyphagotarsonemus latus (Acari: Tarsonemidae). Crop Prot. 2024, 186, 106899. [Google Scholar] [CrossRef]
  346. Jovicich, E.; Cantliffe, D.J.; Osborne, L.S.; Stoffella, P.J. Mite Population and Damage Caused by Broad Mites (Polyphagotarsonemus latus [Banks]) Infesting Bell Pepper (Capsicum annuum L.) at Different Seedling Developmental Stages. Acta Hortic. 2004, 659, 339–344. [Google Scholar] [CrossRef]
  347. Weintraub, P.G.; Kleitman, S.; Mori, R.; Shapira, N.; Palevsky, E. Control of the Broad Mite (Polyphagotarsonemus latus (Banks)) on Organic Greenhouse Sweet Peppers (Capsicum annuum L.) with the Predatory Mite, Neoseiulus cucumeris (Oudemans). Biol. Control 2003, 27, 300–309. [Google Scholar] [CrossRef]
  348. Bergant, K.; Trdan, S.; Žnidarčič, D.; Črepinšek, Z.; Kajfež-Bogataj, L. Impact of Climate Change on Developmental Dynamics of Thrips tabaci (Thysanoptera: Thripidae): Can It Be Quantified? Environ. Entomol. 2005, 34, 755–766. [Google Scholar] [CrossRef]
  349. van Lenteren, J.C.; Alomar, O.; Ravensberg, W.J.; Urbaneja, A. Biological control agents for control of pests in greenhouses. In Integrated Pest and Disease Management in Greenhouse Crops; Gullino, M.L., Albajes, R., Nicot, P.C., Eds.; Springer: Cham, Switzerland, 2020; pp. 409–439. [Google Scholar] [CrossRef]
  350. Bhatt, B.D.; Rohde, R.A. The influence of environmental factors on the respiration of plant-parasitic nematodes. J. Nematol. 1970, 2, 204–212. [Google Scholar]
  351. Thies, J.A.; Fery, R.L. Characterization of resistance conferred by the N gene to Meloidogyne arenaria races 1 and 2, M. hapla, and M. javanica in two sets of isogenic lines of Capsicum annuum L. J. Am. Soc. Hortic. Sci. 2000, 125, 71–75. [Google Scholar] [CrossRef]
  352. Gamarra, H.; Carhuapoma, P.; Cumapa, L.; González, G.; Muñoz, J.; Sporleder, M.; Kreuze, J. A temperature-driven model for potato yellow vein virus transmission efficacy by Trialeurodes vaporariorum (Hemiptera: Aleyrodidae). Virus Res. 2016, 289, 198109. [Google Scholar] [CrossRef]
  353. Kapil, J.; Tomar, M. Fertility Lifetables of Glasshouse Whitefly Trialeurodes vaporariorum (Westwood) on French Bean Cv. Contender at Different Temperatures. Int. J. Econ. Plants 2020, 7, 001–005. [Google Scholar] [CrossRef]
  354. Nielsen, M.-C.; Teulon, D.A.J.; Chapman, R.B.; Butler, R.C.; Drayton, G.M.; Phillipsen, H. Effects of Temperature on Survival, Oviposition, and Development Rate of ‘Greenhouse’ and ‘Lupin’ Strains of Western Flower Thrips, Frankliniella occidentalis. Entomol. Exp. Appl. 2021, 169, 480–490. [Google Scholar] [CrossRef]
  355. Edde, P.A. Arthropod pests of cotton (Gossypium hirsutum L.). In Field Crop Arthropod Pests of Economic Importance; Elsevier: Amsterdam, The Netherlands, 2022; pp. 208–274. [Google Scholar]
  356. Parajulee, M.N. Influence of constant temperatures on life history parameters of the cotton aphid, Aphis gossypii, infesting cotton. Environ. Entomol. 2007, 36, 666–672. [Google Scholar] [CrossRef]
  357. Ali, A.H.; Abo-El-Maged, T.M.; Abdel-Rahman, M.A.A.; Ali, A.M. Temperature Effects on Some Life Table Parameters of Tetranychus urticae Koch (Acari: Tetranychidae). Assiut J. Agric. Sci. 2017, 48, 163–172. [Google Scholar] [CrossRef][Green Version]
  358. Ganjisaffar, F.; Fathipour, Y.; Kamali, K. Temperature-Dependent Development and Life Table Parameters of Typhlodromus bagdasarjani (Phytoseiidae) Fed on Two-Spotted Spider Mite. Exp. Appl. Acarol. 2011, 55, 259–272. [Google Scholar] [CrossRef]
  359. Parrella, M.P. Effect of Temperature on Oviposition, Feeding, and Longevity of Liriomyza trifolii (Diptera: Agromyzidae). Can. Entomol. 1984, 116, 85–92. [Google Scholar] [CrossRef]
  360. Chang, Y.-W.; Zhao, J.-Y.; Wang, Y.-C.; Du, Y.-Z. Thermal Adaptation in Liriomyza trifolii (Diptera: Agromyzidae): From Interspecific Competition to Mechanisms. Insects 2025, 16, 957. [Google Scholar] [CrossRef]
  361. Soares, M.A.; Campos, M.R. Phthorimaea absoluta (tomato leafminer). In Invasive Species—Introduction Pathways, Economic Impact, and Possible Management Options; IntechOpen: London, UK, 2020. [Google Scholar] [CrossRef]
  362. Bavithra, C.M.M.L.; Murugan, M.; Balasubramani, V.; Harish, S.; Prakash, K. Baseline Susceptibility of an A1 Quarantine Pest-the South American Tomato Pinworm Tuta absoluta (Lepidoptera: Gelechiidae) to Insecticides: Past Incidents and Future Probabilities in Line to Implementing Successful Pest Management. Front. Plant Sci. 2024, 15, 1404250. [Google Scholar] [CrossRef]
  363. Ferracini, C.; Bueno, V.H.P.; Dindo, M.L.; Ingegno, B.L.; Luna, M.G.; Gervassio, N.G.S.; Sánchez, N.E.; Siscaro, G.; van Lenteren, J.C.; Zappalà, L.; et al. Natural Enemies of Tuta absoluta in the Mediterranean Basin, Europe and South America. Biocontrol Sci. Technol. 2019, 29, 578–609. [Google Scholar] [CrossRef]
  364. Tarusikirwa, V.L.; Machekano, H.; Mutamiswa, R.; Chidawanyika, F.; Nyamukondiwa, C. Tuta absoluta (Meyrick) (Lepidoptera: Gelechiidae) on the “Offensive” in Africa: Prospects for Integrated Management Initiatives. Insects 2020, 11, 764. [Google Scholar] [CrossRef]
  365. Louws, F.J.; Rivard, C.L.; Kubota, C. Grafting Fruiting Vegetables to Manage Soilborne Pathogens, Foliar Pathogens, Arthropods and Weeds. Sci. Hortic. 2010, 127, 127–146. [Google Scholar] [CrossRef]
  366. Mai, W.F.; Abawi, G.S. Interactions Among Root-Knot Nematodes and Fusarium Wilt Fungi on Host Plants. Annu. Rev. Phytopathol. 1987, 2, 317–338. [Google Scholar] [CrossRef]
  367. Manjunatha, L.; Chowdappa, A.; Madhu, G.S.; Venkataravanappa, V.; Ravikumara, B.M.; Ambika, D.S.; Keerthi, M.C.; Mahadevaiah, C.; Dhanushree, H.K. Tomato spotted wilt virus. In Compendium of Phytopathogenic Microbes in Agro-Ecology; Singh, B.P., Gupta, V.K., Upadhyay, R.S., Eds.; Springer: Cham, Switzerland, 2025; pp. 349–378. [Google Scholar] [CrossRef]
Figure 1. Climate–pest–crop interactions in greenhouse vegetables. The greenhouse microclimate regulates crop physiology and the activity of four major biological groups: fungi, bacteria, viruses, and arthropods/nematodes. Most greenhouse viruses are vector-borne, although some key viruses are also transmitted mechanically. Biological groups interact through synergistic or facilitative relationships. Crop physiology links environmental control with pest dynamics. Arrows indicate relationships among components: unidirectional arrows represent directional (cause–effect) influences, whereas bidirectional arrows denote reciprocal interactions or feedback processes. RH, relative air humidity; T, temperature; VPD, vapor pressure deficit.
Figure 1. Climate–pest–crop interactions in greenhouse vegetables. The greenhouse microclimate regulates crop physiology and the activity of four major biological groups: fungi, bacteria, viruses, and arthropods/nematodes. Most greenhouse viruses are vector-borne, although some key viruses are also transmitted mechanically. Biological groups interact through synergistic or facilitative relationships. Crop physiology links environmental control with pest dynamics. Arrows indicate relationships among components: unidirectional arrows represent directional (cause–effect) influences, whereas bidirectional arrows denote reciprocal interactions or feedback processes. RH, relative air humidity; T, temperature; VPD, vapor pressure deficit.
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Figure 2. Species–pest sensitivity matrix. Heatmap showing the relative sensitivity of tomato, cucumber, and sweet pepper to major pest groups under greenhouse conditions. Colors indicate pest pressure intensity, integrating crop physiology, greenhouse microclimate sensitivity, and known epidemiological patterns. Color scale (sensitivity): green, Moderate; orange, High; red, Very High. CMV, cucumber mosaic virus; ToBRFV, tomato brown rugose fruit virus; TSWV, tomato spotted wilt virus; TYLCV, tomato yellow leaf curl virus.
Figure 2. Species–pest sensitivity matrix. Heatmap showing the relative sensitivity of tomato, cucumber, and sweet pepper to major pest groups under greenhouse conditions. Colors indicate pest pressure intensity, integrating crop physiology, greenhouse microclimate sensitivity, and known epidemiological patterns. Color scale (sensitivity): green, Moderate; orange, High; red, Very High. CMV, cucumber mosaic virus; ToBRFV, tomato brown rugose fruit virus; TSWV, tomato spotted wilt virus; TYLCV, tomato yellow leaf curl virus.
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Figure 3. Seasonal dynamics of major pest groups in greenhouse vegetable crops. Within each season, information is organized from top to bottom as dominant threats, environmental drivers, consequences, and key features, linking microclimate conditions to pest and disease dynamics. Arrows indicate direction of projected change (↑ increase, ↓ decrease). CMV, cucumber mosaic virus; CVYV, cucumber vein yellowing virus; RH, relative air humidity; T, temperature; ToBRFV, tomato brown rugose fruit virus; TSWV, tomato spotted wilt virus; TYLCV, tomato yellow leaf curl virus; VPD, vapor pressure deficit.
Figure 3. Seasonal dynamics of major pest groups in greenhouse vegetable crops. Within each season, information is organized from top to bottom as dominant threats, environmental drivers, consequences, and key features, linking microclimate conditions to pest and disease dynamics. Arrows indicate direction of projected change (↑ increase, ↓ decrease). CMV, cucumber mosaic virus; CVYV, cucumber vein yellowing virus; RH, relative air humidity; T, temperature; ToBRFV, tomato brown rugose fruit virus; TSWV, tomato spotted wilt virus; TYLCV, tomato yellow leaf curl virus; VPD, vapor pressure deficit.
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Figure 4. Climate-adaptive integrated pest management (IPM) framework for greenhouse vegetable production. Sequential decision pathway linking climate monitoring, risk-zone identification (fungi, bacteria, insects, mites), targeted environmental steering, biological control integration, seasonal adaptation, and linkage with decision-support systems (DSSs). Symbols (↑ increase, ↓ decrease) indicate the direction of change in climatic variables. RH, relative air humidity; T, temperature; VPD, vapor pressure deficit.
Figure 4. Climate-adaptive integrated pest management (IPM) framework for greenhouse vegetable production. Sequential decision pathway linking climate monitoring, risk-zone identification (fungi, bacteria, insects, mites), targeted environmental steering, biological control integration, seasonal adaptation, and linkage with decision-support systems (DSSs). Symbols (↑ increase, ↓ decrease) indicate the direction of change in climatic variables. RH, relative air humidity; T, temperature; VPD, vapor pressure deficit.
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Figure 5. Visual summary of methodological considerations in greenhouse pest experiments. Schematic overview of key elements affecting reproducibility: (i) experimental design requirements, (ii) major environmental confounders, and (iii) essential reporting standards. Arrows indicate relationships or flow among components: unidirectional arrows represent directional (cause–effect) influences or process flow, whereas bidirectional arrows denote reciprocal interactions or feedback processes. CO2, carbon dioxide; EC, electrical conductivity; N, nitrogen; PAR, photosynthetically active radiation; RH, relative air humidity; T, temperature; VPD, vapor pressure deficit.
Figure 5. Visual summary of methodological considerations in greenhouse pest experiments. Schematic overview of key elements affecting reproducibility: (i) experimental design requirements, (ii) major environmental confounders, and (iii) essential reporting standards. Arrows indicate relationships or flow among components: unidirectional arrows represent directional (cause–effect) influences or process flow, whereas bidirectional arrows denote reciprocal interactions or feedback processes. CO2, carbon dioxide; EC, electrical conductivity; N, nitrogen; PAR, photosynthetically active radiation; RH, relative air humidity; T, temperature; VPD, vapor pressure deficit.
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Table 2. Major fungal/oomycete pathogens across species and indicative climate-oriented control measures. Secondary or sporadically observed fungal pathogens are presented in Supplementary Table S1.
Table 2. Major fungal/oomycete pathogens across species and indicative climate-oriented control measures. Secondary or sporadically observed fungal pathogens are presented in Supplementary Table S1.
PathogenCrops AffectedOccurrenceControl DifficultyCritical Microclimatic Threshold (T °C/RH %/VPD kPa)Indicative Climate-Based Control MeasuresKey References
Botrytis cinerea (gray mold)Tomato, cucumber, pepperVery frequent (winter–spring)HighOptimum 15–22 °C; RH > 90%; VPD < 0.5Maintain RH < 85%; VPD 0.6–0.8; night ventilation; remove infected tissues[5,38,39,40]
Leveillula taurica, Podosphaera xanthii (powdery mildew)Tomato, cucumber, pepperFrequent (spring–autumn)Moderate–high20–28 °C; RH 60–80%; VPD 0.6–1.0Avoid abrupt RH fluctuations; increase light or UV-B; prevent excessive shading[12,13,41,42,43,44]
Pseudoperonospora cubensis (downy mildew)CucumberFrequent in cool–humid seasonsHigh15–20 °C; RH > 95%; VPD < 0.4Maintain T > 22 °C; RH < 90%; irrigate early; promote rapid leaf drying[29,45,46,47]
Phytophthora infestansTomatoFrequent in cool–humid seasons (spring–autumn)Moderate–high18–24 °C; RH > 90%; VPD < 0.4Maintain T > 25 °C; RH < 90%; irrigate early; promote rapid leaf drying[13,20,34]
Cladosporium fulvum (leaf mold)TomatoPeriodic (warm–humid)Moderate25–30 °C; RH > 90%; VPD < 0.5Enhance ventilation; reduce canopy density; maintain RH < 85%[13,20,48]
Fusarium oxysporum (fusarium wilt)Tomato, pepperCommon (warm months)High24–28 °C (root zone); RH 70–80%Keep root-zone < 25 °C; improve drainage; maintain moderate EC; use resistant rootstocks[20,49,50,51]
Pythium spp., Phytophthora spp. (root and stem rots)Cucumber, tomato, pepper (seedlings)Frequent under waterloggingHigh15–20 °C (root zone); RH > 90%; substrate saturationEnsure drainage; heat substrate to 20–24 °C; avoid over-irrigation; disinfect between crops[52,53,54,55]
Sclerotinia sclerotiorum (white mold)Tomato, cucumber, pepperFrequentHigh18–22 °C; RH > 90%; VPD < 0.5Maintain RH < 85%; remove plant debris; ventilate to dry lower canopy[56,57,58]
Alternaria alternata, A. solani (Alternaria leaf spots)Tomato, pepperModerateModerate24–28 °C; RH > 85%; VPD < 0.6Improve air circulation; avoid leaf wetness; prune lower leaves timely[59,60,61]
EC, electrical conductivity; RH, relative air humidity; T, temperature; UV, ultraviolet; VPD, vapor pressure deficit.
Table 3. Major bacterial pathogens across species and indicative climate-based control measures. Secondary or sporadically reported bacterial pathogens are presented in Supplementary Table S2.
Table 3. Major bacterial pathogens across species and indicative climate-based control measures. Secondary or sporadically reported bacterial pathogens are presented in Supplementary Table S2.
PathogenCrops AffectedOccurrenceControl DifficultyCritical Microclimatic Threshold (T °C/RH %/VPD kPa)Indicative Climate-Based Control MeasuresKey References
Pseudomonas syringae pv. tomato (bacterial speck)TomatoModerate–frequent (cool–humid periods)Medium18–24 °C; RH > 85%; VPD < 0.6Maintain RH < 85%; improve air circulation; avoid leaf wetness; ventilate at dusk[13,20,63]
Xanthomonas spp. (bacterial spot)Tomato, pepperFrequent (warm–humid periods)High25–30 °C; RH > 85%; VPD < 0.6Maintain RH < 85%; keep T < 26 °C; enhance airflow; avoid overhead irrigation[13,64,65,66]
Clavibacter michiganensis subsp. michiganensis (bacterial canker)Tomato, pepperOccasional but severeVery high24–28 °C; RH > 80%; VPD < 0.7Keep RH < 80%; avoid handling wet plants; disinfect tools; remove symptomatic plants[33,67,68,69]
Pseudomonas syringae pv. lachrymans (angular leaf spot)CucumberCommon in cool–humid conditionsMedium18–22 °C; RH > 90%; VPD < 0.5Irrigate early in the day; ensure air movement; avoid condensation; RH < 85%[33,70,71,72,73]
Pectobacterium carotovorum, Dickeya chrysanthemi, Pseudomonas spp. (soft rot and pith necrosis)Tomato, cucumber, pepperOccasionalMedium>25 °C; RH > 90%; free surface waterPrevent free water on tissues; avoid wounding; maintain T < 28 °C; promote rapid drying[70,74,75]
RH, relative air humidity; T, temperature.
Table 4. Major viral diseases across species and indicative climate-based control measures. Secondary or sporadically reported viral pathogens are presented in Supplementary Table S3.
Table 4. Major viral diseases across species and indicative climate-based control measures. Secondary or sporadically reported viral pathogens are presented in Supplementary Table S3.
VirusPrimary Vector (s)Crops AffectedOccurrenceControl DifficultyCritical Microclimatic Threshold (T °C/RH %/VPD kPa)Indicative Climate-Based Control MeasuresKey References
TYLCVBemisia tabaci (whitefly)Tomato
Pepper
Frequent (warm seasons)Very high25–30 °C; RH 50–70%; VPD 0.8–1.2Maintain T < 28 °C; improve air circulation; use UV-transmitting films; install insect-proof screens.[81,82,83,84]
TSWVFrankliniella occidentalis (thrips)Tomato, PepperFrequent (spring–summer)High20–26 °C; RH < 60% favors vector flight; VPD > 1.0Maintain RH 60–75%; reduce VPD; fine-mesh screens; remove weed hosts.[85,86,87,88,89]
PepMVMechanical (tools, hands)Tomato
Pepper
Frequent (autumn–winter)Very highVector-/spread-favouring climate (18–26 °C, RH 60–75%); Symptom-exacerbating stress climate (leaf: 15–20 °C + low light; fruit: >30 °C + RH > 75%)Maintain stable moderate climate (20–26 °C; RH 60–70%); avoid prolonged cold–low light stress in winter and heat–high RH stress in summer[20,90,91,92]
ToCVBemisia tabaci,
Trialeurodes abutilonea
(whiteflies)
Tomato
Pepper
ModerateVery high22–28 °C; RH 60–80%; VPD 0.8–1.2 (vector activity)Maintain VPD 0.7–0.9; limit whitefly hotspots; reduce lower-canopy RH[93,94,95]
TICVT. vaporariorum (whitefly)TomatoModerate (cool–humid periods)Very high15–22 °C; RH 65–85%; VPD 0.6–1.0Increase T slightly to reduce vector efficiency; canopy airflow[96,97,98]
CMVAphids (Myzus persicae)Cucumber, tomato, pepperModerateMedium18–24 °C; RH 60–80%; VPD 0.6–0.9Use insect-proof vents; remove infected plants; ventilate during periods of low aphid activity.[99,100,101,102,103]
CVYVBemisia tabaci (whitefly)CucumberIncreasing in warm cyclesHigh>25 °C; RH 55–75%; VPD 0.8–1.1Keep T < 30 °C; enhance ventilation; apply reflective or photo-selective films.[76,104,105,106,107]
PMMoV, ToMVMechanical (tools, hands)Pepper, tomatoFrequent in reused substratesMedium25–28 °C; RH > 80%; stable on moist surfacesDisinfect tools and gloves; avoid handling wet plants; maintain hygiene in irrigation/substrate systems.[108,109,110]
ToBRFVMechanical (tools, hands, gloves, surfaces); seed transmission possibleTomato (main), occasionally pepperIncreasing rapidly in greenhouse systemsVery high20–30 °C; RH > 70% prolongs survival; stable at high RHStrict sanitation; tool/glove disinfection; avoid handling wet plants; remove infected plants immediately; use certified seed lots.[111,112,113,114]
CMV, cucumber mosaic virus; CVYV, cucumber vein yellowing virus; PMMoV, pepper mild mottle virus; RH, relative air humidity; T, temperature; TICV, tomato infectious chlorosis virus; ToBRFV, tomato brown rugose fruit virus; ToCV, tomato chlorosis virus; ToMV, tobacco mosaic virus; TSWV, tomato spotted wilt virus; TYLCV, tomato yellow leaf curl virus; UV, ultraviolet; VPD, vapor pressure deficit.
Table 5. Major insect pests and nematodes across species and indicative climate-based sustainable control measures. Climatic thresholds and degree-day requirements of major arthropods are provided in Supplementary Table S5, while secondary or sporadically observed insect pests and nematodes are presented in Supplementary Table S4.
Table 5. Major insect pests and nematodes across species and indicative climate-based sustainable control measures. Climatic thresholds and degree-day requirements of major arthropods are provided in Supplementary Table S5, while secondary or sporadically observed insect pests and nematodes are presented in Supplementary Table S4.
Insect/Mite
/Nematode
Crops AffectedOccurrenceControl DifficultyCritical Microclimatic Threshold (T °C/RH %/VPD kPa)Indicative Climate-Based Control MeasuresKey References
Bemisia tabaci, Trialeurodes vaporariorum (whiteflies)Tomato, cucumber, pepperVery frequent (warm periods)High25–32 °C; RH 50–70%; VPD 0.8–1.2Maintain T < 28 °C; ensure continuous airflow; use UV-transmitting films and insect-proof screens; integrate biological control (Encarsia formosa, Eretmocerus eremicus).[104,127,128,129,130,131,132,133]
Tuta absoluta (tomato leaf miner)TomatoFrequent (warm, dry conditions)Very high24–30 °C; RH < 60%; VPD > 1.0Maintain moderate RH (60–70%); ventilate to reduce heat peaks; employ pheromone and light traps; integrate biological control (Nesidiocoris tenuis, Trichogramma achaeae).[134,135,136,137,138]
Frankliniella occidentalis (western flower thrips)Tomato, pepperFrequent (spring–summer)High22–30 °C; RH < 60%; VPD > 1.0Maintain RH > 60%; avoid excessive dryness; use fine-mesh screens and blue/yellow sticky traps; regulate VPD to 0.6–1.0.[89,139,140,141,142,143]
Myzus persicae, Aphis gossypii (aphids)Tomato, cucumber, pepperCommon (mild–humid conditions)Moderate18–24 °C; RH 60–80%; VPD 0.6–0.9Maintain good ventilation; exclude winged aphids using screened vents; avoid excessive N; promote biological control (Aphidius colemani, Chrysoperla carnea).[144,145,146,147,148,149,150]
Tetranychus urticae (two-spotted spider mite)Tomato, cucumberFrequent (hot–dry periods)High28–35 °C; RH < 50%; VPD > 1.2Maintain moderate RH (60–70%); reduce leaf T; encourage predatory mites (Phytoseiulus persimilis, Amblyseius swirskii).[151,152,153,154,155]
Liriomyza trifolii, L. huidobrensis (leafminers)Tomato, cucumber, pepperOccasionalModerate22–28 °C; RH 65–80%; VPD 0.6–1.0Maintain balanced RH; avoid waterlogging; introduce parasitoids (Diglyphus isaea) or entomopathogenic nematodes (Steinernema feltiae).[156,157,158,159,160,161]
Meloidogyne incognita, M. javanica
(root-knot nematodes)
Tomato, cucumber, pepperFrequent in soil-grown cropsHigh25–30 °C (root zone); soil moisture near FCMaintain root-zone T < 25 °C; improve drainage; apply solarization; use resistant or grafted rootstocks.[162,163,164,165]
FC, field capacity; N, nitrogen; RH, relative air humidity; T, temperature; UV, ultraviolet; VPD, vapor pressure deficit.
Table 7. Interactions between greenhouse microclimate parameters and pest dynamics across species.
Table 7. Interactions between greenhouse microclimate parameters and pest dynamics across species.
Microclimate FactorBiological Group Most AffectedTypical Response to ChangeOptimal Range for Crop Growth (Minimized Pest Pressure)Key Management ImplicationsKey References
T (°C)Fungi, oomycetes, bacteria, viruses, insects, nematodes+3–5 °C accelerates pest development; >33 °C reduces insect longevity22–28 °CMaintain thermal stability via ventilation and shading; avoid high night T that favors bacterial and viral multiplication.[20,192,203,204]
RH (%)Fungi, oomycetes, bacteria, mites, thripsRH > 85% favors fungal, oomycete and bacterial diseases; RH < 55% favors mites and thrips60–75%Balance RH to suppress both fungal sporulation and arthropod mobility; use dehumidification cycles at dawn.[207,208,209,211,225]
VPD (kPa)Insects, mites, fungiHigh VPD (>1.2 kPa) promotes mite and thrips activity; low VPD (<0.4 kPa) promotes Botrytis, Phytophthora and Cladosporium infection0.6–1.0 kPaControl air circulation and irrigation timing to maintain stable VPD within moderate range.[87,207,208,210]
Light intensity (µmol m−2 s−1)Insects, powdery mildewsHigh light raises leaf T and VPD; UV deficiency favors mildew; strong UV deters vectors300–600 µmol m−2 s−1 (PAR)Use photo-selective or UV-transmitting covers to balance pathogen and vector control.[121,213,214,215,217]
Spectral composition (UV range)Whiteflies, aphids, powdery and downy mildewsUV-blocking films reduce insect attraction but increase powdery and downy mildew incidenceModerate UV transmissionSelect covering materials according to dominant pest/pathogen pressure.[212,213,214,216,217]
CO2 concentration (µmol mol−1)Virus vectors, foliar pathogensElevated CO2 (≥800 µmol mol−1) increases canopy density, RH, and leaf turgor700–900 µmol mol−1Couple CO2 enrichment with ventilation to prevent excessive RH and vector proliferation.[218,219,220,221,222,224]
Air circulation/ventilationAll groupsEnhances T and RH uniformity; reduces condensation and insect aggregation, reduces foliar fungal and oomycete pathogensModerate, continuous airflow (0.2–0.5 m s−1)Continuous fan operation prevents microhabitats conducive to disease and pest buildup.[193,211,221,223]
Irrigation timing and methodFungi, oomycetes, bacteria, nematodesNight irrigation increases leaf wetness and pathogen risk; over-irrigation promotes root diseasesMorning drip irrigation; controlled moistureAvoid nocturnal wetting; optimize irrigation frequency for substrate aeration.[226,227,228]
PAR, photosynthetically active radiation; RH, relative air humidity; T, temperature; UV, ultraviolet; VPD, vapor pressure deficit.
Table 8. Typical climatic trade-offs between optimum yield conditions and pest/disease suppression targets across species and associated Integrated Pest Management (IPM) priorities.
Table 8. Typical climatic trade-offs between optimum yield conditions and pest/disease suppression targets across species and associated Integrated Pest Management (IPM) priorities.
Environmental FactorOptimal Range for YieldOptimal Range for Pest/Disease SuppressionTypical Trade-Off/ConflictExample Crop or PathogenKey References
T (°C)24–28<25 for fungal suppressionHigher T accelerates growth but increases whitefly and mite activityTomato—Bemisia tabaci[94,211,229]
RH (%)70–85<80 for Botrytis controlHigh RH improves transpiration but favors condensation and fungal sporulationCucumber—Botrytis cinerea[5,40,230]
VPD (kPa)0.4–0.80.8–1.2Low VPD supports gas exchange but promotes leaf wetnessTomato—Cladosporium fulvum[19,33,210]
Light intensity (µmol m−2 s−1)400–600>500 suppresses powdery mildew via UVHigher PAR boosts yield but increases canopy TPepper—Leveillula taurica[42,211,217,231]
CO2 concentration (µmol mol−1)800–1000NeutralElevated CO2 enhances photosynthesis but may thicken canopy, trapping RHTomato—mixed fungal flora[15,218,232]
Air CirculationModerateHighIncreased airflow reduces RH but can cool canopy and increase evapotranspirationAll crops[146,193,221,223]
Root-zone MoistureNear FCSlight deficitExcess moisture favors growth but promotes Pythium and nematodesCucumber—Pythium spp.[53,55,233]
FC, field capacity; PAR, photosynthetically active radiation; RH, relative air humidity; T, temperature; UV, ultraviolet radiation; VPD, vapor pressure deficit.
Table 9. Seasonal trends in greenhouse pest dominance and corresponding Integrated Pest Management (IPM) priorities.
Table 9. Seasonal trends in greenhouse pest dominance and corresponding Integrated Pest Management (IPM) priorities.
Season/CycleDominant Climatic CharacteristicsMajor Pest GroupsTypical Disease/Pest ExamplesPrimary IPM PrioritiesKey references
Winter—Early SpringLow T, high RH, frequent condensation, low lightFungal, oomycete and bacterial pathogensBotrytis cinerea, downy mildews, Cladosporium fulvum, Pseudomonas syringaeDehumidification, heating/ventilation cycles, morning irrigation, RH sensors, biological control and preventive fungicides[5,20,221,236]
Late Spring—SummerHigh T, low RH, high VPD, intense lightInsect vectors, mites, nematodes, powdery mildewsBemisia tabaci, Frankliniella occidentalis, Tetranychus urticae, Meloidogyne spp., powdery mildewsVector exclusion, biological control, shading, airflow management, avoid over-dehumidification[8,18,103,139,171,184]
AutumnModerate T, variable RH, day–night fluctuationsMixed infections (fungi–oomycetes–bacteria–viruses)BotrytisXanthomonas complexes, TYLCV–Bemisia complexes,
downy mildews
Adaptive climate control, alternating RH and vector management, continuous monitoring[221,229,234]
All seasons (constant greenhouse cycles)Controlled environment with human interventionOpportunistic or cross-group interactionsRoot–wilt complexes, sooty molds, viral co-infectionsContinuous monitoring, data-driven IPM, integration of climate and biological models[93,119,237]
RH, relative air humidity; T, temperature; TYLCV, tomato yellow leaf curl virus; VPD, vapor pressure deficit.
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Fanourakis, D.; Makraki, T.; Ntanasi, T.; Giannothanasis, E.; Tsaniklidis, G.; Tsitsigiannis, D.I.; Ntatsi, G. Climate-Driven Pest and Disease Dynamics in Greenhouse Vegetables: A Review. Horticulturae 2026, 12, 415. https://doi.org/10.3390/horticulturae12040415

AMA Style

Fanourakis D, Makraki T, Ntanasi T, Giannothanasis E, Tsaniklidis G, Tsitsigiannis DI, Ntatsi G. Climate-Driven Pest and Disease Dynamics in Greenhouse Vegetables: A Review. Horticulturae. 2026; 12(4):415. https://doi.org/10.3390/horticulturae12040415

Chicago/Turabian Style

Fanourakis, Dimitrios, Theodora Makraki, Theodora Ntanasi, Evangelos Giannothanasis, Georgios Tsaniklidis, Dimitrios I. Tsitsigiannis, and Georgia Ntatsi. 2026. "Climate-Driven Pest and Disease Dynamics in Greenhouse Vegetables: A Review" Horticulturae 12, no. 4: 415. https://doi.org/10.3390/horticulturae12040415

APA Style

Fanourakis, D., Makraki, T., Ntanasi, T., Giannothanasis, E., Tsaniklidis, G., Tsitsigiannis, D. I., & Ntatsi, G. (2026). Climate-Driven Pest and Disease Dynamics in Greenhouse Vegetables: A Review. Horticulturae, 12(4), 415. https://doi.org/10.3390/horticulturae12040415

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