Apple Cultivar Responses to Fungal Diseases and Insect Pests Under Variable Orchard Conditions: A Multisite Study

Abstract

Evaluating cultivar susceptibility to biotic stressors in apple orchards is essential for selecting genotypes adapted to local conditions and for designing effective plant protection strategies. This study conducted a comparative assessment of five apple cultivars (‘Florina’, ‘Jonathan’, ‘Golden Delicious’, ‘Pinova’, and ‘Idared’) in response to major fungal diseases (Venturia inaequalis, Podosphaera leucotricha, and Monilinia spp.) and insect pests (Eriosoma lanigerum, Quadraspidiotus perniciosus, Anthonomus pomorum, Aphis spp., and Cydia pomonella). The cultivars were monitored over a five-year period in six orchards located in Central Transylvania, Romania. Significant differences in phytosanitary behavior were recorded among cultivars and locations. ‘Florina’ consistently showed the highest tolerance to pathogens and pests across all sites and years, while ‘Jonathan’ and ‘Golden Delicious’ proved highly susceptible, particularly to apple scab, powdery mildew, aphids, and codling moth. Pest incidence was strongly influenced by temperature, while disease occurrence was more closely linked to precipitation patterns. Heritability analysis indicated that genetic factors played a substantial role in shaping cultivar responses to most biotic stressors. The integrated approach to cultivar–location–pathogen and pest interactions offers practical insights for optimizing orchard protection strategies under variable ecological conditions.

1. Introduction

The apple (Malus × domestica Borkh.) is one of the most widely cultivated temperate fruit trees, playing a central role in global horticulture due to its nutritional, ecological, and economic importance [1,2]. With global production in 2023 exceeding 97.3 million tons [3], the apple has become a strategic fruit crop across temperate regions, appreciated for its storability, diversity of use, and broad consumer appeal [4,5,6]. Despite the existence of over 10,000 to 15,000 cultivars globally [7,8] and, according to some opinions, even more than 30,000 apple varieties in the world [9,10], commercial production relies on fewer than 40, including dominant cultivars such as ‘Golden Delicious’, ‘Fuji’, ‘Gala’, and ‘Granny Smith’ [11,12,13]. The over-representation of a small number of elite cultivars has led to a progressive erosion of the apple gene pool, raising concerns regarding long-term sustainability and resilience [14,15,16]. This reduction in genetic diversity stems from the intense selection pressure applied over the last century, which has focused primarily on fruit quality and uniformity [10,17,18]. Such narrowing compromises adaptive potential in the face of increasing biotic and abiotic stresses [19], including the emergence of new pest biotypes and virulent pathogen strains [20,21].

To counteract these challenges, breeding programs have explored the use of wild Malus species, such as M. floribunda, M. sieversii, M. baccata, and M. fusca, which harbor valuable traits including scab and powdery mildew resistance, cold hardiness, and drought tolerance [22,23,24,25,26,27,28]. Interspecific hybridization with these species has enabled the introgression of resistance loci into elite backgrounds, exemplified by the incorporation of the Rvi6 (Vf) gene from M. floribunda 821 into several scab-resistant cultivars [29,30,31,32].

However, introgression breeding carries inherent limitations, notably the transmission of undesirable traits (e.g., small or poorly flavored fruit), requiring long-term backcrossing and selection to recover agronomic quality [33,34]. This process is time-consuming and labor-intensive, often extending breeding cycles to over 20 years [35,36,37,38]. To accelerate selection and reduce uncertainty, modern programs have incorporated molecular tools such as marker-assisted selection (MAS) and, more recently, genomic selection (GS) [39,40,41,42,43,44]. Numerous resistance genes have been mapped and tagged with molecular markers, including Rvi1–Rvi15 for scab, Pl1–Pl2 for powdery mildew, and loci linked to woolly aphid resistance [25,45,46]. The use of molecular markers enables early-generation selection, even in seedling stages, improving breeding efficiency and enabling pyramiding of resistance genes [47,48,49].

Despite these advances, G × E × M (genotype × environment × management) interactions remain a key challenge. Phenotypic expression of resistance traits can be influenced by local microclimate, orchard design, and treatment regime. For instance, scab severity is known to be heavily influenced by spring rainfall and leaf wetness duration [21], while pest outbreaks such as Cydia pomonella or Aphis spp. are modulated by temperature and host phenology [50,51,52]. Therefore, the evaluation of cultivar response under real-world orchard conditions remains essential for validating breeding outcomes. Field trials help elucidate how environmental variability and orchard practices shape plant–pathogen and plant–insect dynamics, allowing more precise cultivar recommendations and risk mitigation strategies.

The present study was conducted over five consecutive years (2020–2024) across six apple orchards located in Central Transylvania, Romania. The research focused on the field response of five cultivars (‘Florina’, ‘Jonathan’, ‘Golden Delicious’, ‘Pinova’, and ‘Idared’) to the major diseases (scab, powdery mildew, and brown rot) and pests (woolly aphid, San Jose scale, apple blossom weevil, aphids, and codling moth). The goal was to explore how cultivar genotype, environmental conditions, and management factors interact to determine phytosanitary outcomes. By combining multi-year observations with statistical and heritability analysis, this study contributes to a better understanding of the cultivar’s response to biotic stressors. It also supports the development of breeding and management strategies aimed at increasing orchard resilience, reducing pesticide use, and enabling climate-smart apple production systems.

2. Materials and Methods

2.1. Description of the Study Area and Local Climatic Conditions

The analysis of the behavior of several apple cultivars in response to the main pests and diseases was conducted over a five-year period (2020–2024) in six family-owned orchards located in various localities of Alba County, Romania: Aiud, Boz, Cergău Mare, Doștat, Galda de Jos, and Izvoru Ampoiului (Figure 1). The study area is situated in the central part of Transylvania, Romania—a region with a moderately continental climate characterized by relatively warm summers and moderate precipitation, though with considerable interannual variability.

Meteorological data were obtained from the National Meteorological Administration and the weather stations of the Transylvania-South Regional Meteorological Center, Romania.

Table 1. Meteorological data on the annual temperature and precipitation for the four weather stations that cover the six locations where the apple orchards are situated (MSL * are included in parentheses).

	Average Annual Temperature (°C)	Annual Amount of Precipitation (mm)	Average Annual Temperature (°C)	Annual Amount of Precipitation (mm)
Year	Blaj (Aiud—347 m, and Cergău Mare—303 m)		Alba Iulia (Galda de Jos—236 m)
2020	10.6	709.2	11.3	746.4
2021	9.9	708.0	10.7	558.0
2022	10.7	475.2	11.5	464.4
2023	11.5	602.4	12.2	589.2
2024	12.1	555.6	12.9	496.8
Year	Sebeș-Alba (Boz—335 m, and Doștat—455 m)		Câmpeni (Izvoru Ampoiului—503 m)
2020	11.1	681.6	8.7	855.6
2021	10.4	573.6	8.1	920.4
2022	11.2	446.4	8.8	832.8
2023	12.0	481.2	9.4	964.8
2024	12.5	510.0	10.0	658.8

* MSL—mean sea level, data expressing altitude or elevation, in meters (m).

presents the annual average temperature and total annual precipitation recorded at four meteorological stations covering the six localities where the studied orchards are located. The primary focus was on climatic conditions during key periods relevant to apple phenology and major biotic stressors: spring (March–May), when diseases affecting the vegetative phase of trees and early pests begin to appear; the summer months (June–August), when fruit-related diseases and the main pest populations develop; and the early autumn period.

During the study period, the year 2020 was characterized by a drier spring and several hot summer days. In contrast, the spring of 2021 was cool and very rainy. In 2023, heavy rainfall was recorded during May and June, while 2024 was an exceptionally warm year, particularly during the summer months, when precipitation levels were relatively low.

2.2. Biological Material and Experimental Conditions

The biological material consisted of five apple cultivars: ‘Idared’, ‘Florina’, ‘Jonathan’, ‘Golden Delicious’, and ‘Pinova’, all of which are well known and relatively widely cultivated in Romania. These cultivars were present in all six studied orchards. The family orchards analyzed were of small size: 1.3 ha (Izvoru Ampoiului), 1.5 ha (Galda de Jos), and 2 ha (Cergău Mare and Doștat), except for the Boz orchard, which was significantly larger (80 ha).

The orchards were located on hilly terrain with chernozem soils, except for the orchard in Izvoru Ampoiului, where the soil was clay-loam, alluvial in nature, due to the proximity of the Ampoi River. All cultivars were grown in intensive orchard systems on MM 106 rootstock, except for ‘Pinova’ in the Boz orchard, which was cultivated in a super-intensive system on M9 rootstock (Figure A1). In the intensive orchards, the planting distance was 3 × 4 m, corresponding to a density of 833 trees/ha. In Galda de Jos, the planting distance was 3 × 3.5 m, resulting in a density of 925 trees/ha. For the super-intensive orchard (Boz, ‘Pinova’ cultivar), the planting distance was 1 × 4 m, with a density of 2500 trees/ha.

The tree training systems also varied: symmetrical palmette in Aiud, Doștat, and Galda de Jos; improved open vase in Boz and Izvoru Ampoiului; open vase in Cergău Mare; and slender spindle in the super-intensive system in Boz. Soil management practices included inter-row grass strips (Aiud and Boz) and fully grass-covered ground (Cergău Mare, Doștat, Galda de Jos, and Izvoru Ampoiului), relying on natural vegetation. Foliar fertilization was applied at different intensities across sites, with an average of three applications per year in Aiud, nine in Boz, five in Doștat, and only one in each of the orchards in Cergău Mare, Galda de Jos, and Izvoru Ampoiului. Phytosanitary treatments also varied depending on the preferences of individual orchard owners and the recommendations provided by the Alba County Phytosanitary Office, part of the National Phytosanitary Authority under the Romanian Ministry of Agriculture and Rural Development. In general, the treatments followed a similar pattern across the five years of investigation. Additional information regarding the main agrotechnical characteristics of the six orchards, including planting system, rootstock type, and soil management, is provided in Table S1. Details on phytosanitary and foliar fertilizer treatments, with examples from the final year of study (2024), are presented in Table S2, which is representative of the practices applied throughout the study period.

2.3. Assessment of Major Diseases and Pests

During the study period (2020–2024), the analysis focused on the most significant apple diseases: apple scab (Venturia inaequalis), powdery mildew (Podosphaera leucotricha), and brown rot (Monilinia spp.). Other diseases with sporadic incidence were not included in the study, and no outbreaks of fire blight (Erwinia amylovora) were recorded. Among the pests, only those that cause substantial damage to apple crops or are subject to special regulatory status (including quarantine pests) were monitored: woolly apple aphid (Eriosoma lanigerum), San Jose scale (Quadraspidiotus perniciosus), apple blossom weevil (Anthonomus pomorum), aphids (Aphis spp.), and codling moth (Cydia pomonella). Spiders or other insect pests reported sporadically were not considered in the study. The variable hydrothermal conditions across the five years of the study provided a suitable framework for examining the relationships between climatic variability and the incidence of major apple diseases and pests. Visual examples of damage caused by some of the diseases and pests analyzed in the study are illustrated in Figure A2 and Figure A3.

The response of apple cultivars to pathogens and pests was evaluated under field conditions through natural infection and infestation, assessed at key phenological stages according to the biology of the biotic stressors. For each pathogen, three parameters were recorded: frequency (F%), intensity (I%), and infection rate (IR%), the latter also referred to as the ‘degree of attack’ [53,54]. Frequency, or incidence (F%), was calculated as the proportion of affected plants or plant organs (n) relative to the total number observed (N), using the formula F% = (n/N) × 100. Intensity, or severity (I%), was determined based on the extent of symptomatic manifestation and expressed as a weighted average using the formula I% = Σ(i × f)/n, where i represents the severity class, f is the number of cases in that class, and n is the total number of infected cases. A six-point severity scale was applied, with classes defined as follows: 0 (0%), 1 (1–3%), 2 (4–10%), 3 (11–25%), 4 (26–50%), 5 (51–75%), and 6 (76–100%). The infection rate (IR%) was then calculated as IR% = (F% × I%)/100. Assessments of apple scab, powdery mildew, and brown rot were conducted monthly during the growing season. For each cultivar, evaluations were performed on 10 randomly selected trees. Scab infection was assessed on 100 leaves per tree, powdery mildew on 10–20 shoots per tree, and brown rot on flowers, leaves, and fruits from flowering until harvest, with 10–20 flowers, 40–60 leaves, and all harvested apples examined per tree.

Pest monitoring was conducted through a combination of visual inspections and pheromone traps. The infestation level (IL%) was calculated for each pest species using the following formula: IL% = (Number of infested organs/Total number of organs inspected) × 100. This assessment was performed on ten randomly selected trees per cultivar throughout the growing season, with evaluations targeting specific plant organs depending on the pest’s biology. For woolly aphids, colonies on branches and the root collar area were visually assessed. San Jose scale populations were monitored using pheromone traps and observations (especially on shoots and stem bark), with periodic visual inspections beginning in spring to assess first-generation activity. Codling moth flight patterns were tracked using pheromone traps installed in April, followed by generation-specific monitoring and fruit damage assessments (based on total picked fruits) on ten trees per cultivar. The apple blossom weevil was evaluated during the pink bud stage through visual examination of floral bud damage. General aphid populations were observed monthly from spring to autumn. In all cases, the infestation level calculation considered either larvae, adults, or both life stages, depending on the target pest’s biology and damage symptoms.

2.4. Statistical Analysis

The recorded data on the degree of attack were processed as mean values and presented in summary tables together with the standard error of the mean (SEM). To determine whether the differences among cultivars were statistically significant, a one-way analysis of variance (ANOVA) was applied. When the null hypothesis was rejected, Duncan’s multiple range test (Duncan MRT, p < 0.05) was used as a post hoc test to assess pairwise differences. Before performing ANOVA, percentage data were adjusted using the arcsine transformation. Multivariate analyses were carried out using the PAST software (Past4.09) [55]. The data were normalized prior to analysis and then processed using UPGMA hierarchical clustering (unweighted pair group method with arithmetic mean).

Broad-sense heritability (H²) was estimated as the ratio of genotypic variance (σ²₉) to total phenotypic variance (σ²_p). Variance components were partitioned according to the model proposed by Boss and Caligari for clonal analysis [56], which we previously validated across multiple Rosaceae species with clonal propagation [57,58]. Thus, apple varieties were propagated vegetatively through grafting; in orchard settings, inter-clone variation was attributed to genetic variance, whereas intra-clone variation (i.e., among grafted trees of the same genotype) reflected environmental effects. The response of the varieties to each disease and pest was considered a quantitative (polygenic) trait, except for ‘Florina’, which possesses monogenic resistance to apple scab and was, therefore, excluded from the heritability analysis for this pathogen.

3. Results

3.1. Occurrence of Pathogens and Pests on Trees During the Growing Season

Figure 2 presents the infection rate (IR%) of powdery mildew (P. leucotricha) on five apple cultivars (‘Idared’, ‘Florina’, ‘Jonathan’, ‘Golden Delicious’, and ‘Pinova’), assessed across six orchards in Alba County and averaged over the 2020–2024 period. Infection dynamics followed a consistent seasonal pattern across all locations, with initial symptoms observed in March–April, peaking during May–June, and gradually declining toward the end of the vegetation period in August–September. Among the cultivars, ‘Jonathan’ and ‘Idared’ recorded the highest infection rates in most orchards, with peak values exceeding 12–14% in Boz and Izvoru Ampoiului. In contrast, ‘Florina’ consistently exhibited the lowest infection levels, with negligible values in Aiud and Cergău Mare. Differences among locations were also evident: the highest average infection rates were registered in Izvoru Ampoiului and Cergău Mare, while Aiud and Galda de Jos displayed substantially lower levels throughout the growing season. These findings reflect marked differences in cultivar susceptibility and spatial variability across the study area.

The infection rate (IR%) of apple scab (V. inaequalis) varied significantly across the five cultivars and six study locations, based on five-year average values (2020–2024). The disease showed a seasonal progression similar to other foliar pathogens, with infection onset in early spring (March–April), peaking in May–June, and gradually declining by August–September (Figure 3). ‘Golden Delicious’ exhibited the highest susceptibility in all orchards, with peak infection rates exceeding 12% in Boz and Cergău Mare. ‘Idared’, ‘Jonathan’, and ‘Pinova’ displayed moderate susceptibility, while ‘Florina’ consistently showed strong resistance, with near-zero infection rates throughout the growing season in all sites. Among the locations, Cergău Mare, Izvoru Ampoiului, and Boz recorded the highest levels of infection, whereas Aiud and Galda de Jos reported the lowest. These results emphasize the distinct cultivar responses to scab infection and the influence of local environmental and management conditions.

The infection rate of brown rot (Monilinia spp.) typically began in late spring (May–June), peaked in July, and declined toward the end of the growing season (Figure 4). ‘Idared’ was the most affected cultivar, with peak infection rates exceeding 14–16% in multiple orchards, particularly in Boz, Doștat, and Galda de Jos. ‘Jonathan’ and ‘Golden Delicious’ showed moderate levels of susceptibility, while ‘Pinova’ exhibited lower infection values. ‘Florina’ again demonstrated strong resistance, maintaining near-zero infection rates across all six locations. Spatial variability was notable: Boz, Doștat, and Izvoru Ampoiului recorded the highest infection levels, while Aiud and Cergău Mare remained at the lower end of the spectrum. These results indicate significant differences in cultivar sensitivity and environmental influence on disease development.

The infestation level (IL%) of E. lanigerum varied across apple cultivars and locations. Infestation typically began in May, peaked between June and July, and decreased gradually through September (Figure 5). ‘Golden Delicious’ exhibited the highest susceptibility across all orchards, with peak infestation levels surpassing 3.5% in Boz and Cergău Mare. ‘Jonathan’ and ‘Idared’ showed moderate infestation levels, while ‘Pinova’ maintained low values. ‘Florina’ again demonstrated the lowest susceptibility, with negligible infestation across the growing season. Among the six locations, the most affected were Aiud, Boz, and Cergău Mare, whereas Galda de Jos and Doștat recorded the lowest infestation levels. These results highlight differences in cultivar tolerance and spatial patterns of aphid pressure.

Q. perniciosus infestation displayed notable temporal and spatial variation across cultivars and localities during the 2020–2024 growing seasons (Figure 6). The pest pressure was concentrated in a narrow seasonal period, with maximum activity recorded in June–July. ‘Golden Delicious’ consistently showed the highest infestation rates, particularly in Doștat and Cergău Mare, where values reached up to 11–12%. ‘Idared’ and ‘Jonathan’ followed with moderate infestation, while ‘Pinova’ recorded slightly lower levels. ‘Florina’ once again proved the least susceptible, with minimal to absent presence in most orchards. Spatial patterns revealed significant contrasts: Boz remained virtually unaffected throughout the study period, while Doștat, Cergău Mare, and Izvoru Ampoiului registered elevated infestation levels, especially during early summer. The distinct cultivar response and clear spatial heterogeneity suggest that localized pest dynamics are potentially influenced by environmental and agrotechnical conditions.

Across the six study orchards, A. pomorum infestations followed an early-season trend, with peak levels occurring in April–May and declining sharply by the end of June (Figure 7). This pattern reflects the biology of the species, which targets floral buds before and during blossoming. The most affected cultivars were ‘Golden Delicious’ and ‘Jonathan’, particularly in Doștat and Cergău Mare, where infestation levels approached or exceeded 10%. ‘Idared’ and ‘Pinova’ experienced moderate pressure, while ‘Florina’ remained the least affected, confirming a recurring trend of reduced susceptibility. Notably, infestation was either minimal or absent in Boz and Galda de Jos throughout the entire study period, suggesting unfavorable local conditions for the pest’s development in those sites. In contrast, Aiud, Cergău Mare, and Izvoru Ampoiului exhibited consistent pressure across multiple cultivars, underscoring the combined effect of site-specific factors and cultivar vulnerability.

Infestation levels of Aphis spp. showed a clear temporal pattern, with populations building up from April and peaking in May–June, followed by a steady decline through July and minimal presence from August onward (Figure 8). This trend was consistent across most locations. Among cultivars, ‘Idared’ registered the highest infestation rates, particularly in Boz and Doștat, where values surpassed 10–12%. ‘Pinova’ also showed notable susceptibility, especially in Boz and Aiud. By contrast, ‘Florina’ consistently recorded the lowest levels of aphid infestation across all orchards, with values remaining near zero. Differences between orchards were also evident. Boz and Cergău Mare exhibited the highest aphid pressure overall, while Galda de Jos and Izvoru Ampoiului experienced relatively low infestation levels. These observations underscore the role of both cultivar choice and site-specific conditions in shaping aphid population dynamics during the growing season.

The seasonal dynamics of C. pomonella infestation revealed a distinct pattern, with populations building up gradually in June, reaching their peak in July–August, and tapering off toward September (Figure 9). This trend was consistent across most orchards, though the magnitude of infestation varied significantly by location and cultivar. ‘Golden Delicious’ and ‘Jonathan’ were the most heavily infested cultivars, particularly in Cergău Mare, Doștat, and Aiud, where peak infestation levels surpassed 12–14%. ‘Idared’ followed closely in several sites, while ‘Pinova’ recorded moderate values. ‘Florina’ once again showed relatively low susceptibility, maintaining the lowest infestation levels across all environments. From a spatial perspective, orchards in Boz remained virtually unaffected, while Cergău Mare and Doștat emerged as hotspots for codling moth activity. Infestation pressure was also elevated in Aiud and Izvoru Ampoiului, albeit with cultivar-dependent variability. Galda de Jos exhibited intermediate levels, with moderate peaks in July.

3.2. Infection Rate and Infestation Level Depending on Orchards and Cultivars

Table 2. Infection rate (IR%) of major apple diseases affecting five cultivars in six orchards over the 2020–2024 period.

No	Orchard	Cultivar	Podosphaera leucotricha	Venturia inaequalis	Monilinia ssp.
1	Aiud	‘Idared’	1.93 ± 0.32 a	1.53 ± 0.29 b	2.25 ± 0.96 a
2		‘Florina’	0.00 ± 0.00 d	0.00 ± 0.00 d	0.98 ± 0.46 c
3		‘Jonathan’	1.73 ± 0.42 a	1.55 ± 0.25 b	0.70 ± 0.34 d
4		Golden D.	0.48 ± 0.12 b	3.25 ± 0.45 a	1.28 ± 0.62 b
5		‘Pinova’	0.13 ± 0.04 c	0.55 ± 0.08 c	0.45 ± 0.23 e
1	Boz	‘Idared’	4.23 ± 0.32 c	1.18 ± 0.11 c	4.53 ± 1.31 a
2		‘Florina’	0.23 ± 0.03 d	0.00 ± 0.00 e	2.83 ± 0.74 b
3		‘Jonathan’	5.35 ± 0.42 a	1.33 ± 0.16 b	2.88 ± 0.77 b
4		Golden D.	4.28 ± 0.56 bc	3.48 ± 0.11 a	4.48 ± 1.13 a
5		‘Pinova’	4.70 ± 0.69 b	0.95 ± 0.08 d	4.08 ± 1.07 a
1	Cergău Mare	‘Idared’	4.45 ± 0.41 b	3.38 ± 0.46 b	2.55 ± 0.82 c
2		‘Florina’	0.00 ± 0.00 e	0.00 ± 0.00 e	1.65 ± 0.56 d
3		‘Jonathan’	5.25 ± 0.63 a	2.80 ± 0.44 c	2.68 ± 0.99 bc
4		Golden D.	1.93 ± 0.39 d	5.23 ± 0.71 a	2.83 ± 0.93 b
5		‘Pinova’	2.43 ± 0.44 c	1.75 ± 0.30 d	3.65 ± 1.11 a
1	Doștat	‘Idared’	3.00 ± 0.59 b	1.58 ± 0.36 c	4.08 ± 1.07 c
2		‘Florina’	0.20 ± 0.12 d	0.00 ± 0.00 e	3.68 ± 0.95 c
3		‘Jonathan’	3.85 ± 0.73 a	2.08 ± 0.41 b	3.28 ± 0.86 d
4		Golden D.	3.23 ± 0.70 b	4.25 ± 0.92 a	4.85 ± 1.28 b
5		‘Pinova’	1.73 ± 0.36 c	1.18 ± 0.27 d	5.88 ± 1.49 a
1	Galda de Jos	‘Idared’	1.00 ± 0.23 b	2.20 ± 0.59 b	1.10 ± 0.57 a
2		‘Florina’	0.33 ± 0.09 e	0.00 ± 0.00 e	0.63 ± 0.36 c
3		‘Jonathan’	1.15 ± 0.27 a	1.68 ± 0.45 c	0.50 ± 0.31 d
4		Golden D.	0.38 ± 0.06 d	2.80 ± 0.88 a	0.95 ± 0.68 b
5		‘Pinova’	0.43 ± 0.10 c	1.00 ± 0.22 d	0.28 ± 0.21 e
1	Izvoru Ampoiului	‘Idared’	6.10 ± 0.97 a	5.98 ± 0.91 a	1.23 ± 0.74 c
2		‘Florina’	0.43 ± 0.13 e	0.00 ± 0.00 e	1.53 ± 0.86 b
3		‘Jonathan’	5.05 ± 0.85 b	5.20 ± 0.83 b	1.08 ± 0.57 d
4		Golden D.	3.85 ± 0.65 c	4.70 ± 0.70 c	2.08 ± 1.13 a
5		‘Pinova’	2.98 ± 0.53 d	3.58 ± 0.58 d	0.88 ± 0.46 e

Data are presented as mean values ± standard error of the mean (SEM). Within each orchard and pathogen, differences between cultivars, followed by different letters, indicate statistically significant differences according to Duncan’s test (p < 0.05).

presents the infection rates (IR%) of P. leucotricha (powdery mildew), V. inaequalis (apple scab), and Monilinia spp. (brown rot) in five apple cultivars cultivated across six orchards during 2020–2024. The highest infection rates for powdery mildew were generally recorded in Izvoru Ampoiului, Cergău Mare, and Boz, with values exceeding 5% in ‘Jonathan’ and ‘Idared’. ‘Florina’ exhibited exceptional resistance, showing null or near-zero values across all sites. Conversely, ‘Golden Delicious’ and ‘Pinova’ presented intermediate levels, depending on location. In terms of apple scab, ‘Golden Delicious’ consistently showed the highest susceptibility, particularly in Cergău Mare, Doștat, and Izvoru Ampoiului, with IR% values surpassing 4–5%. ‘Jonathan’ and ‘Idared’ displayed moderate infection rates, while ‘Florina’ again remained highly resistant, with zero infection in all locations. For brown rot, infestation varied more widely. Peak values were found in ‘Pinova’ and ‘Golden Delicious’ in Doștat (5.88% and 4.85%, respectively), and in multiple cultivars in Boz. ‘Florina’ showed the lowest susceptibility overall, though a slightly higher IR% was observed in Boz and Izvoru Ampoiului. Overall, the results demonstrate cultivar-dependent susceptibility patterns and significant spatial variation across orchards, with ‘Florina’ consistently performing as the least affected cultivar across all three diseases.

Table 3. Infestation level (IL%) of key apple pests recorded on five cultivars in six orchards over the 2020–2024 period.

No	Orchard	Cultivar	E. lanigerum	Q. perniciosus	A. pomorum	Aphis spp.	C. pomonella
1	Aiud	‘Idared’	1.15 ± 0.24 a	1.13 ± 0.18 b	2.60 ± 0.46 a	2.13 ± 0.41 a	2.23 ± 0.46 d
2		‘Florina’	0.00 ± 0.00 e	0.05 ± 0.03 d	1.93 ± 0.35 b	0.15 ± 0.03 e	1.55 ± 0.36 e
3		‘Jonathan’	0.78 ± 0.16 b	1.23 ± 0.22 b	1.78 ± 0.28 b	1.60 ± 0.29 c	2.63 ± 0.66 c
4		Golden D.	0.60 ± 0.21 c	1.65 ± 0.26 a	1.28 ± 0.20 c	1.75 ± 0.31 b	3.50 ± 0.63 b
5		‘Pinova’	0.05 ± 0.03 d	0.23 ± 0.12 c	1.13 ± 0.21 d	0.23 ± 0.14 d	3.93 ± 0.60 a
1	Boz	‘Idared’	0.60 ± 0.14 c	-	-	3.30 ± 0.44 a	-
2		‘Florina’	0.00 ± 0.00 d	-	-	0.85 ± 0.16 c	-
3		‘Jonathan’	1.45 ± 0.19 b	-	-	0.30 ± 0.03 d	-
4		Golden D.	2.43 ± 0.25 a	-	-	2.58 ± 0.45 b	-
5		‘Pinova’	1.40 ± 0.25 b	-	-	2.48 ± 0.26 b	-
1	Cergău Mare	‘Idared’	0.70 ± 0.12 c	2.08 ± 0.29 b	2.40 ± 0.35 c	3.00 ± 0.43 c	3.08 ± 0.22 c
2		‘Florina’	0.00 ± 0.00 d	0.00 ± 0.00 d	1.70 ± 0.26 d	0.00 ± 0.00 e	2.38 ± 0.19 d
3		‘Jonathan’	2.20 ± 0.32 b	2.50 ± 0.41 b	3.18 ± 0.52 b	4.20 ± 0.57 a	4.70 ± 0.42 b
4		Golden D.	3.48 ± 0.52 a	2.93 ± 0.47 a	3.45 ± 0.42 b	3.60 ± 0.48 b	5.75 ± 0.42 a
5		‘Pinova’	0.58 ± 0.15 c	1.25 ± 0.25 c	4.15 ± 0.53 a	2.20 ± 0.30 d	6.05 ± 0.52 a
1	Doștat	‘Idared’	0.50 ± 0.12 d	1.43 ± 0.21 b	2.05 ± 0.32 c	1.23 ± 0.19 b	1.35 ± 0.21 c
2		‘Florina’	0.00 ± 0.00 e	0.15 ± 0.09 d	1.73 ± 0.30 d	0.00 ± 0.00 e	1.45 ± 0.25 c
3		‘Jonathan’	2.15 ± 0.42 b	1.95 ± 0.25 a	2.30 ± 0.33 b	0.88 ± 0.13 d	3.48 ± 0.58 a
4		Golden D.	2.90 ± 0.49 a	1.88 ± 0.42 a	2.93 ± 0.45 a	2.80 ± 0.43 a	2.65 ± 0.54 b
5		‘Pinova’	0.63 ± 0.21 c	0.73 ± 0.21 c	1.15 ± 0.20 e	1.05 ± 0.23 c	3.88 ± 0.55 a
1	Galda de Jos	‘Idared’	0.53 ± 0.11 a	1.15 ± 0.29 a	-	1.50 ± 0.32 b	0.80 ± 0.17 d
2		‘Florina’	0.00 ± 0.00 d	0.00 ± 0.00 d	-	0.00 ± 0.00 d	0.70 ± 0.23 e
3		‘Jonathan’	0.40 ± 0.06 b	1.28 ± 0.35 a	-	1.18 ± 0.25 c	1.10 ± 0.43 c
4		Golden D.	0.18 ± 0.03 c	0.85 ± 0.28 b	-	1.80 ± 0.28 a	1.35 ± 0.35 b
5		‘Pinova’	0.00 ± 0.00 d	0.45 ± 0.14 c	-	0.00 ± 0.00 d	1.70 ± 0.50 a
1	Izvoru Ampoiului	‘Idared’	0.45 ± 0.14 b	1.28 ± 0.21 a	-	0.35 ± 0.10 a	0.20 ± 0.17 d
2		‘Florina’	0.00 ± 0.00 c	0.00 ± 0.00 d	-	0.00 ± 0.00 d	0.13 ± 0.10 e
3		‘Jonathan’	0.70 ± 0.18 a	0.80 ± 0.14 b	-	0.20 ± 0.08 b	0.30 ± 0.24 c
4		Golden D.	0.00 ± 0.00 c	0.40 ± 0.11 c	-	0.03 ± 0.03 c	0.35 ± 0.26 b
5		‘Pinova’	0.00 ± 0.00 c	0.00 ± 0.00 d	-	0.00 ± 0.00 d	0.48 ± 0.33 a

Data are presented as mean values ± standard error of the mean (SEM). Within each orchard and pest species, differences between cultivars, followed by different letters, indicate statistically significant differences according to Duncan’s test (p < 0.05). Note: ‘-’ indicates that the pest was not detected despite monitoring during the study period.

presents the infestation levels (IL%) of five key apple pests—E. lanigerum, Q. perniciosus, A. pomorum, Aphis spp., and C. pomonella—recorded on five cultivars across six orchards over the 2020–2024 period. E. lanigerum showed moderate to high infestation in several locations, with the highest IL% values recorded in ‘Golden Delicious’ and ‘Jonathan’, especially in Cergău Mare and Doștat, where values exceeded 3.0%. ‘Florina’ exhibited complete resistance in all orchards, while ‘Pinova’ generally showed low to intermediate susceptibility. Q. perniciosus was most prevalent in Cergău Mare, Aiud, and Doștat, where ‘Golden Delicious’ and ‘Jonathan’ recorded the highest IL% values (up to 2.9%). ‘Pinova’ and ‘Florina’ displayed the lowest infestation levels, with multiple orchards showing near-zero values. Infestation by A. pomorum followed a similar pattern, with elevated levels in ‘Pinova’, ‘Golden Delicious’, and ‘Jonathan’, particularly in Cergău Mare and Doștat, where IL% values surpassed 3.0–4.0%. ‘Florina’ consistently maintained the lowest infestation across all sites. Aphis spp. exhibited high pressure in Cergău Mare and Boz, especially on ‘Jonathan’, ‘Golden Delicious’, and ‘Idared’, with IL% values above 3.0–4.0%. ‘Florina’ remained largely unaffected, showing minimal to no infestation across the entire study. Lastly, C. pomonella recorded the highest infestation in ‘Pinova’ and ‘Golden Delicious’, particularly in Cergău Mare and Doștat, where IL% values exceeded 5.5–6.0%. ‘Jonathan’ and ‘Idared’ showed moderate infestation levels, while ‘Florina’ again had the lowest values, typically below 1.5%. Overall, the results reveal distinct differences in pest susceptibility among cultivars and substantial variability across orchards. ‘Golden Delicious’ and ‘Jonathan’ were most frequently affected across all pest species, while ‘Florina’ consistently demonstrated the highest resistance under field conditions.

3.3. Relationships Between Biotic Stressors and Environmental and Management Conditions

Table 4. Pearson correlation coefficients (r) between infection rate (IR%) by pathogens, infestation level (IL%) by pests, and mean annual temperature, calculated over the 2020–2024 period for each orchard and cultivar.

Cultivar	Orchard	Diseases			Pests
		P.l.	V.i.	M.s.	E.l.	Q.p.	A.p.	A.s.	C.p.
‘Idared’	Aiud	0.828	0.042	−0.348	0.951 *	0.892 *	0.942 *	0.917 *	0.985 **
	Boz	0.973 **	−0.169	0.890 *	0.240	−	−	0.541	−
	Cergău Mare	0.402	−0.656	0.936 *	0.921 *	0.980 **	0.946 *	0.889 *	0.993 ***
	Doștat	0.419	−0.497	0.926 *	0.532	0.679	0.529	0.102	0.685
	Galda de Jos	0.094	−0.232	−0.191	0.364	0.832	−	0.975 **	0.864
	Izvoru Ampoiului	0.972 **	−0.422	−0.156	0.880 *	0.963 **	−	0.810	0.963 **
‘Florina’	Aiud	−	−	−	−	0.899 *	0.927 *	0.747	0.977 **
	Boz	0.709	−	−	−	−	−	0.696	−
	Cergău Mare	−	−	−	−	−	0.904 *	−	0.934 *
	Doștat	0.144	−	−	−	0.122	0.605	−	0.793
	Galda de Jos	0.394	−	−	−	−	−	−	0.562
	Izvoru Ampoiului	0.749	−	−	−	−	−	−	−
‘Jonathan’	Aiud	0.901 *	0.239	−0.352	0.812	0.907 *	0.963 **	0.955 *	0.879 *
	Boz	0.900 *	−0.245	0.762	0.134	−	−	0.401	−
	Cergău Mare	0.418	−0.684	0.890 *	0.981 **	0.976 **	0.932 *	0.835	0.899 *
	Doștat	0.569	−0.527	0.812	0.749	0.640	0.432	−0.039	0.741
	Galda de Jos	−0.106	−0.186	−0.496	0.344	0.760	−	0.814	0.884 *
	Izvoru Ampoiului	0.969 **	−0.356	−0.545	0.763	0.976 **	−	0.772	0.900 *
‘Golden Delicious’	Aiud	0.454	0.265	−0.289	0.883 *	0.883 *	0.973 **	0.838	0.974 **
	Boz	0.507	−0.009	0.521	0.320	−	−	0.610	−
	Cergău Mare	−0.357	−0.312	0.950 *	0.930 *	0.978 **	0.954 *	0.842	0.922 *
	Doștat	0.614	−0.567	0.848	0.841	0.581	0.589	0.597	0.719
	Galda de Jos	−0.382	−0.036	−0.306	−0.344	0.854	−	0.990 **	0.924 *
	Izvoru Ampoiului	0.994 ***	−0.382	0.445	−	0.987 **	−	0.772	0.756
‘Pinova’	Aiud	0.622	−0.719	−0.481	0.417	0.954 *	0.985 **	0.901 *	0.960 **
	Boz	0.840	−0.104	0.253	0.183	−	−	0.598	−
	Cergău Mare	−0.358	−0.151	0.722	0.991 ***	0.945 *	0.990 **	0.880 *	0.956 *
	Doștat	−0.017	−0.477	0.830	0.408	0.560	0.081	0.485	0.586
	Galda de Jos	0.787	−0.120	−0.774	−	0.896 *	−	−	0.771
	Izvoru Ampoiului	0.989 **	−0.311	−0.441	−	−	−	−	−

Diseases: P.l.—P. leucotricha; V.i.—V. inaequalis; M.s.—Monilinia spp. Pests: E.l.—E. lanigerum; Q.p.—Q. perniciosus; A.p.—A. pomorum; A.s.—Aphis spp.; C.p.—C. pomonella. Statistical significance: * = p ≤ 0.05; ** = p ≤ 0.01; *** = p ≤ 0.001 (critical r values: r₅% = 0.878; r₁% = 0.959; r_0.1% = 0.991). Note: ‘−’ indicates that the pest or disease was not detected despite monitoring during the study period.

displays the Pearson correlation coefficients (r) between average annual temperature and the infection rates (IR%) of three major pathogens (P. leucotricha, V. inaequalis, Monilinia spp.), as well as the infestation levels (IL%) of five key pests, for each cultivar and orchard over the study period. Highly significant and strong positive correlations were frequently observed between temperature and pest infestation levels. For example, C. pomonella in ‘Idared’ from Aiud, A. pomorum in ‘Golden Delicious’ from Aiud, and E. lanigerum in ‘Jonathan’ from Cergău Mare all showed very strong relationships with temperature. These results suggest that temperature plays a critical role in promoting pest development. The infection rate of P. leucotricha also displayed significant positive correlations with temperature, particularly in cultivars like ‘Idared’ and ‘Jonathan’. Notably, in Boz (‘Idared’), the correlation reached r = 0.973 **, and in Izvoru Ampoiului (‘Pinova’), r = 0.989 **. These patterns point to temperature as a contributing factor in the epidemiology of powdery mildew. In contrast, V. inaequalis exhibited weak or negative correlations with temperature in most sites and cultivars, none of which reached statistical significance. For instance, in Cergău Mare (‘Jonathan’), r = −0.684, and in Doștat (‘Golden Delicious’), r = −0.567, suggesting a possible preference for cooler or wetter conditions. Monilinia spp. correlations varied widely. Some high positive and significant correlations were observed, such as in Cergău Mare (‘Golden Delicious’: r = 0.950 *), but also negative or weak values in other locations (e.g., Galda de Jos—‘Pinova’: r = −0.774). ‘Florina’ consistently presented few significant correlations, reinforcing its stable performance across environmental variability and its low susceptibility to biotic stressors. Only a few pest-temperature correlations in ‘Florina’ approached significance, such as C. pomonella in Aiud (r = 0.977 **). Overall, these results emphasize that pest infestation levels are more consistently and significantly influenced by temperature than pathogen infection rates, with the strongest correlations observed for C. pomonella, A. pomorum, and E. lanigerum in multiple orchards and cultivars.

Pearson correlation coefficients (r) between annual precipitation and infection rates (IR%) of major pathogens, as well as infestation levels (IL%) of key pests, are presented in

Table 5. Pearson correlation coefficients (r) between infection rate (IR%) by pathogens, infestation level (IL%) by pests, and sum of annual precipitation, calculated over the 2020–2024 period for each orchard and cultivar.

Cultivar	Orchard	Diseases			Pests
		P.l.	V.i.	M.s.	E.l.	Q.p.	A.p.	A.s.	C.p.
‘Idared’	Aiud	−0.685	0.687	0.709	−0.725	−0.382	−0.692	−0.769	−0.627
	Boz	−0.462	0.938 *	−0.247	0.766	−	−	0.488	−
	Cergău Mare	−0.915 *	0.979 **	−0.628	−0.506	−0.514	−0.746	−0.554	−0.774
	Doștat	−0.957 *	0.982 **	−0.140	−0.898 *	−0.922 *	0.749	−0.775	−0.870
	Galda de Jos	−0.718	0.946 *	0.753	−0.941 *	−0.658	−	−0.335	−0.636
	Izvoru Ampoiului	−0.464	0.945 *	0.865	−0.332	−0.501	−	−0.676	−0.617
‘Florina’	Aiud	−	−	−	−	0.282	−0.700	0.302	−0.353
	Boz	−0.212	−	−	−	−	−	0.362	−
	Cergău Mare	−	−	−	−	−	−0.806	−	−0.677
	Doștat	−0.786	−	−	−	−0.747	−0.880 *	−	−0.633
	Galda de Jos	−0.730	−	−	−	−	−	−	0.557
	Izvoru Ampoiului	−0.478	−	−	−	−	−	−	−
‘Jonathan’	Aiud	−0.634	0.576	0.663	−0.848	−0.557	−0.683	−0.342	−0.721
	Boz	−0.748	0.957 *	−0.064	0.764	−	−	0.564	−
	Cergău Mare	−0.891 *	0.970 **	−0.683	−0.601	−0.591	−0.763	−0.726	−0.744
	Doștat	−0.965 **	0.970 **	−0.105	−0.802	−0.920 *	−0.910 *	−0.453	−0.841
	Galda de Jos	−0.724	0.914 *	0.762	−0.287	−0.625	−	0.250	−0.560
	Izvoru Ampoiului	−0.520	0.921 *	0.988 **	−0.347	−0.542	−	−0.880 *	−0.709
‘Golden Delicious’	Aiud	−0.877	0.506	0.615	−0.452	−0.632	−0.577	−0.417	−0.639
	Boz	−0.724	0.624	0.472	0.625	−	−	0.405	−
	Cergău Mare	−0.544	0.953 *	−0.707	−0.564	−0.533	−0.729	−0.727	−0.722
	Doștat	−0.940 *	0.980 **	−0.150	−0.736	−0.945 *	−0.965 **	−0.924 *	−0.867
	Galda de Jos	−0.714	0.852	0.988 **	−0.287	−0.666	−	−0.367	−0.619
	Izvoru Ampoiului	−0.611	0.925 *	0.355	−	−0.662	−	−0.880 *	−0.341
‘Pinova’	Aiud	−0.539	0.954 *	0.752	0.202	−0.492	−0.401	−0.475	−0.348
	Boz	−0.605	0.815	0.520	0.758	−	−	0.429	−
	Cergău Mare	−0.561	0.840	0.088	−0.501	−0.651	−0.416	−0.785	−0.601
	Doștat	−0.793	0.935 *	0.015	−0.387	−0.898 *	−0.862	−0.827	−0.510
	Galda de Jos	−0.696	0.905 *	0.676	−	−0.544	−	−	0.346
	Izvoru Ampoiului	−0.695	0.913 *	0.674	−	−	−	−	−

Diseases: P.l.—P. leucotricha; V.i.—V. inaequalis; M.s.—Monilinia spp. Pests: E.l.—E. lanigerum; Q.p.—Q. perniciosus; A.p.—A. pomorum; A.s.—Aphis spp.; C.p.—C. pomonella. Statistical significance: * = p ≤ 0.05; ** = p ≤ 0.01 (critical r values: r₅% = 0.878; r₁% = 0.959). Note: ‘−’ indicates that the pest or disease was not detected despite monitoring during the study period.

. The strongest and most consistent positive correlations were observed between precipitation and the infection rate of V. inaequalis. For instance, highly significant correlations were recorded in ‘Idared’ (Doștat: r = 0.982 **), ‘Jonathan’ (Boz: r = 0.957 *), and ‘Golden Delicious’ (Doștat: r = 0.980 **), suggesting that scab development is strongly promoted by increased moisture availability. In contrast, P. leucotricha was consistently and significantly negatively correlated with precipitation, with the strongest inverse relationships in ‘Jonathan’ (Doștat: r = –0.965 **), ‘Golden Delicious’ (Doștat: r = –0.940 *), and ‘Idared’ (Cergău Mare: r = –0.915 *). This pattern reinforces the pathogen’s preference for dry and warm conditions. Monilinia spp. correlations were more variable but included a few notable positive relationships, such as in Izvoru Ampoiului (‘Jonathan’: r = 0.988 **) and Galda de Jos (‘Golden Delicious’: r = 0.988 **). However, several orchards showed negative or non-significant values, indicating site- and cultivar-specific sensitivity.

Regarding pests, most insect infestation levels were negatively correlated with precipitation, particularly in ‘Idared’, ‘Jonathan’, and ‘Golden Delicious’. For example, Aphis spp. in ‘Idared’ from Doștat (r = –0.775) and C. pomonella in ‘Golden Delicious’ from Doștat (r = –0.867) showed inverse correlations. However, exceptions were found in Boz, where some pests (e.g., E. lanigerum in ‘Jonathan’: r = 0.764) had moderate positive associations with rainfall. ‘Florina’ again displayed fewer significant correlations overall, confirming its lower sensitivity to climatic variation and biotic stressors.

In summary, precipitation appears to favor fungal diseases such as apple scab while generally limiting the development of powdery mildew and insect pests. These trends contrast with those observed for temperature and highlight the differential ecological responses of stressors to climatic drivers.

Figure 10 illustrates the UPGMA cluster analyses and heat maps for biotic stressors and climatic variables recorded in six apple orchards during the 2020–2024 period. The dendrograms grouped variables by similarity in their annual patterns, while the heat maps show the relative intensity of each variable in each year. Across all orchards, several consistent pairwise associations were identified. V. inaequalis and precipitation clustered together in Cergău Mare, Doștat, and Izvoru Ampoiului, indicating that scab severity followed a similar annual pattern to rainfall. Another frequent grouping involved C. pomonella and temperature, which formed tight clusters in Izvoru Ampoiului, Boz, and Doștat, suggesting similar interannual variation. Additionally, Aphis spp. and E. lanigerum appeared repeatedly in proximity, particularly in Aiud, Galda de Jos, and Boz, reflecting parallel dynamics in aphid populations. Pathogens such as P. leucotricha and M. spp. often clustered together or near V. inaequalis, especially in Aiud and Galda de Jos, indicating overlapping annual profiles. Pest clusters including Q. perniciosus, A. pomorum, and C. pomonella were evident in Cergău Mare and Doștat.

In terms of annual grouping, some orchards displayed partial consistency. In Boz and Cergău Mare, the years 2021 and 2022 tended to cluster together across multiple variables, suggesting similar environmental or biotic conditions. In contrast, in Aiud and Izvoru Ampoiului, the years were more dispersed, indicating greater temporal variability. Overall, the analyses revealed strong and recurrent associations between specific pairs of variables, such as V. inaequalis with precipitation and C. pomonella with temperature, as well as co-variation among certain years within individual orchards.

According to

Table 6. Pearson correlation coefficients (r) between infection rates (IR%) by pathogens and infestation levels (IL%) by pests across six orchards and five apple cultivars (2020–2024).

	V.i.	M.s.	E.l.	Q.p.	A.p.	A.s.	C.p.
P.l.	0.598 ***	0.375 *	0.467 **	0.512 **	0.552 **	0.361 *	0.018
V.i.		0.008	0.452 **	0.546 **	0.519 **	0.302	0.003
M.s.			0.485 **	0.365 *	0.256	0.463 **	0.439 *
E.l.				0.839 ***	0.591 ***	0.690 ***	0.573 ***
Q.p.					0.592 ***	0.877 ***	0.585 ***
A.p.						0.693 ***	0.549 **
A.s.							0.662 ***

Diseases: P.l.—P. leucotricha; V.i.—V. inaequalis; M.s.—Monilinia spp. Pests: E.l.—E. lanigerum; Q.p.—Q. perniciosus; A.p.—A. pomorum; A.s.—Aphis spp.; C.p.—C. pomonella. Statistical significance: * = p ≤ 0.05; ** = p ≤ 0.01; *** = p ≤ 0.001 (critical r values: r₅% = 0.349; r₁% = 0.449; r_0.1% = 0.554).

, significant positive correlations were found between P. leucotricha and several pests, including E. lanigerum, Q. perniciosus, and A. pomorum. V. inaequalis was also positively associated with Q. perniciosus and A. pomorum. The strongest correlations were observed among pests themselves. For example, E. lanigerum showed strong positive associations with Q. perniciosus, A. pomorum, Aphis spp., and C. pomonella, suggesting a consistent pattern of pest co-occurrence. By contrast, C. pomonella showed weaker and generally non-significant correlations with disease incidence. These results provide a comprehensive overview of the statistical relationships among key stressors and external factors in the studied apple orchards.

Table 7. Pearson correlation coefficients (r) between biotic stressors (IR% and IL%) and orchard altitude (MSL) and the number of phytosanitary treatments (NPT) across six localities (2020–2024).

	P.l.	V.i.	M.s.	E.l.	Q.p.	A.p.	A.s.	C.p.
MSL	0.545	0.604	0.292	−0.030	−0.108	−0.032	−0.515	−0.212
NPT	0.140	−0.688	0.712	0.501	−0.383	−0.050	0.271	−0.215
P.l.		0.547	0.548	0.409	−0.263	−0.138	0.129	−0.320
V.i.			−0.181	−0.214	0.133	−0.047	−0.356	−0.070
M.s.				0.863 *	0.080	0.313	0.475	0.099
E.l.					0.398	0.631	0.832 *	0.482
Q.p.						0.892 *	0.420	0.940 **
A.p.							0.602	0.966 **
A.s.								0.575

MSL—mean sea level; NPT—number of phytosanitary treatments. Diseases: P.l.—P. leucotricha; V.i.—V. inaequalis; M.s.—Monilinia spp. Pests: E.l.—E. lanigerum; Q.p.—Q. perniciosus; A.p.—A. pomorum; A.s.—Aphis spp.; C.p.—C. pomonella. Statistical significance: * = p ≤ 0.05; ** = p ≤ 0.01 (critical r values: r₅% = 0.811; r₁% = 0.917).

includes correlation coefficients between biotic stressors and two external factors: orchard altitude (MSL) and the number of phytosanitary treatments (NPT). Although the correlations between altitude and infection rates of V. inaequalis and P. leucotricha (positive) and Aphis spp. (negative) were statistically insignificant, the moderately high absolute values of the correlation coefficient (r) and their directional trends may suggest potential differences in environmental preferences among these biotic stressors. Regarding NPT, an insignificant negative correlation was observed with V. inaequalis, but its value could suggest effective disease control. Similarly, positive links between NPT and Monilinia spp. and E. lanigerum could indicate reactive treatments after infestation. Significant correlations were noted between Q. perniciosus and C. pomonella, and between A. pomorum and C. pomonella, reinforcing the pattern of pest interaction observed in Table 6.

Figure 11 illustrates the regression relationships between two pairs of biotic stressors that showed consistent and meaningful associations across the study orchards during the 2020–2024 period. The relationship between P. leucotricha and V. inaequalis is positive (Figure 11a), with the regression model indicating only modest explanatory power. The coefficient of determination (R²) shows that while an increase in powdery mildew infection is generally associated with higher scab severity, this pattern is only partially predictive, suggesting that additional independent factors are involved in disease development. In contrast, a strong linear association between E. lanigerum and Aphis spp. is revealed in Figure 11b, with a high R² value supporting the observation of frequent co-occurrence. This finding suggests that these two pests respond similarly to environmental conditions or orchard management practices, and their population dynamics may overlap in time and space. These regression models support the correlation-based findings and highlight the potential for integrated monitoring strategies in cases where biotic stressors exhibit convergent ecological patterns.

Figure 12 presents the Pearson correlation coefficients between the main biotic stressors, expressed as infection rates (IR%) and infestation levels (IL%), and two external factors: orchard altitude (mean sea level, MSL) and the number of phytosanitary treatments (NPT) applied during the 2020–2024 period. Positive correlations were observed between altitude and the infection rates of V. inaequalis and P. leucotricha, suggesting that disease incidence tended to be higher in orchards located at greater elevations, likely due to more favorable microclimatic conditions for fungal development. In contrast, pest infestation levels, particularly those of Aphis spp. and E. lanigerum, were generally negatively correlated with altitude, indicating greater pest pressure at lower elevations. Correlations with the number of phytosanitary treatments varied in both strength and direction. Notably, two correlations were statistically significant (r > 0.707). A positive correlation was found between NPT and the infection rate of Monilinia spp., suggesting that treatments were more frequent in orchards where brown rot severity was higher, possibly reflecting reactive interventions. In contrast, a significant negative correlation was observed between NPT and Aphis spp., indicating effective aphid control in orchards receiving more frequent treatments. These results highlight how both environmental conditions and management practices influenced the distribution and severity of biotic stressors across the studied orchards.

Table 8. Broad-sense heritability (H²) of disease and pest response in apple cultivars across six orchards (2020–2024).

Orchard	Diseases			Pests
	P.l.	V.i.	M.s.	A.s.	E.l.	Q.p.	A.p.	C.p.
Aiud	0.933	0.956	0.591	0.919	0.904	0.935	0.774	0.751
Boz	0.951	0.933	0.404	0.943	0.960	-	-	-
Cergău Mare	0.960	0.949	0.385	0.941	0.961	0.925	0.830	0.949
Doștat	0.875	0.910	0.446	0.946	0.940	0.897	0.799	0.863
Galda de Jos	0.839	0.810	0.345	0.937	0.945	0.819	-	0.566
Izvoru Ampoiului	0.908	0.921	0.260	0.882	0.912	0.951	-	0.251

Diseases: P.l.—P. leucotricha; V.i.—V. inaequalis; M.s.—Monilinia spp. Pests: A.s.—Aphis spp.; E.l.—E. lanigerum; Q.p.—Q. perniciosus; A.p.—A. pomorum; C.p.—C. pomonella. Note: The response of the varieties to each disease and pest was considered a quantitative (polygenic) trait. ‘Florina’, with monogenic resistance to apple scab, was excluded from the heritability analysis for this pathogen.

presents broad-sense heritability (H²) values for the response of five apple cultivars to major biotic stressors, including both diseases and pests, recorded across six orchards during the study period. The heritability values for infection caused by P. leucotricha and V. inaequalis were consistently high across all sites, ranging from H² = 0.839 to 0.960. This suggests that genetic factors play a dominant role in determining the susceptibility or resistance of the cultivars to these fungal pathogens. Similarly, high H² values were observed for pest-related traits, particularly in the case of E. lanigerum (ranging from 0.904 to 0.961), Aphis spp. (0.882 to 0.946), and Q. perniciosus (up to 0.951), indicating a strong genetic control over plant response to these insects. By contrast, the heritability estimates for Monilinia spp. were notably lower and more variable, with values ranging from 0.260 (Izvoru Ampoiului) to 0.591 (Aiud), suggesting a greater influence of environmental conditions on brown rot expression in these orchards. Similarly, C. pomonella exhibited moderate to low H² values, ranging from 0.251 to 0.949 depending on the orchard, with the lowest value recorded in Izvoru Ampoiului, suggesting high site-specific environmental variability in codling moth pressure. Overall, most H² values exceeded the threshold of 0.5, which indicates that, for the majority of biotic stressors analyzed, phenotypic response in apple was more strongly influenced by genotype than by environmental factors. This is especially evident for scab, powdery mildew, woolly aphid, and San José scale, for which genetic control appears to be stable and consistent across different locations.

4. Discussion

In the context of increasing biotic pressure and environmental instability, the choice of apple cultivars with stable resistance traits has become a cornerstone of sustainable fruit production. Numerous studies have emphasized that scab and powdery mildew continue to be the most economically important fungal diseases in temperate orchards [20,34], while a complex of insect pests, including woolly apple aphid, codling moth, and aphids, poses persistent challenges, especially under climate-driven phenological shifts [50,51]. Our five-year multisite assessment of five apple cultivars revealed consistent differences in their response to these biotic stressors, shaped both by genetic background and environmental conditions. A summary of our study’s findings regarding the overall response of apple cultivars to biotic stress caused by pathogens and pests, as well as the influence of environmental and management conditions across the studied orchards on cultivar performance, is provided in Supplementary Tables S3 and S4.

Apple scab (V. inaequalis) displayed significant variability across cultivars and locations, with infection levels closely correlated with rainfall during spring and early summer. This supports previous findings that leaf wetness duration and relative humidity are critical for scab development [21]. ‘Golden Delicious’ was the most susceptible cultivar across all sites, consistent with earlier observations [19,59,60]. ‘Florina’ appears to have maintained the resistance conferred by the Rvi6 gene (formerly Vf) [31] and showed no symptoms in the studied orchards. However, isolated infections have been reported in nearby areas, particularly in poorly maintained orchards. So far, no cases of apple scab have been identified on ‘Florina’ or other cultivars derived from Malus floribunda 821 in Romania, but such cases have been documented in other countries [32]. Our results reinforce the idea that resistant cultivars such as ‘Florina’ can drastically reduce the need for fungicides, contributing both to economic efficiency and ecological sustainability. Ultimately, it is important to note that the response to apple scab infection can vary significantly for the same genotype (cultivar), depending on environmental and management conditions. In our study, for example, the cultivar ‘Pinova’ exhibited considerable variability in susceptibility across orchards and years. This helps explain why ‘Pinova’ has been classified as resistant in some studies [61], while others have described it as low susceptible [62], moderately susceptible [63], or even highly susceptible [64], reflecting differences in site conditions, pathogen pressure, and cultivation practices.

Fungal disease management, especially for apple scab, remains one of the most resource-intensive aspects of apple production, with nearly three-quarters of phytosanitary inputs directed toward fungal control and over half specifically targeting scab [65]. Scab management involves considerable costs, and inadequate control can result in substantial yield losses, potentially exceeding 70% [66,67,68]. The high susceptibility of commercial cultivars, combined with favorable climatic conditions and pathogen virulence, makes apple scab a persistent threat [34,69]. Although resistant varieties like ‘Florina’ offer promising results, their adoption is limited by less-favorable tree architecture, external fruit quality, and sensory traits. Most are confined to organic systems [46]. This underlines the importance of breeding new cultivars that combine robust, multi-stressor resistance with commercial-grade fruit quality, enabling broader integration into intensive orchard systems.

Powdery mildew (P. leucotricha) showed a markedly different epidemiological pattern, peaking under warm and dry conditions, particularly in Boz and Izvoru Ampoiului. Susceptibility was greatest in ‘Jonathan’ and ‘Idared’, which aligns with findings from Sestras et al. [24], and suggests a lack of durable resistance in these widely cultivated genotypes. Interestingly, ‘Florina’ again exhibited strong field resistance, with near-zero infection across all years and locations. Climatic correlations confirmed temperature as a key factor, with mildew incidence rising significantly in warmer years, consistent with projections of increased pathogen activity under climate change [35]. The combination of low rainfall and high temperature, typical for recent summers in Central Transylvania, appears to enhance the risk of mildew outbreaks, especially in genotypes lacking resistance loci such as Pl1 or Pl2 [48]. In addition, recent studies have shown that climate change may contribute to increased aggressiveness and adaptive potential of plant pathogens, including those affecting apple orchards, through mechanisms such as accelerated reproduction, extended infection periods, and the emergence of virulent strains. These trends may further challenge the effectiveness of genetic resistance and necessitate dynamic management strategies [70,71,72,73,74].

Regarding pest dynamics, codling moth (C. pomonella), woolly apple aphid (E. lanigerum), and aphids (Aphis spp.) were the most impactful. The infestation levels of C. pomonella and A. pomorum correlated strongly with high temperatures, consistent with their accelerated phenology under warm conditions [50]. Our results align with Frechette et al. [51], who showed that aphid populations expand rapidly in dry, warm springs, especially in cultivars like ‘Idared’ and ‘Jonathan’. Conversely, ‘Florina’ again demonstrated low susceptibility, suggesting a potential role for morphological or biochemical traits contributing to its pest tolerance [34]. The significant linear relationship identified between E. lanigerum and Aphis spp. indicates overlapping ecological niches and reinforces the need for integrated monitoring. These co-occurrence patterns also suggest the feasibility of predictive pest models that incorporate both biotic and abiotic factors.

Heritability values further clarified the genetic contribution to stressor response. High H² values for scab, mildew, and woolly aphid reinforce the efficacy of resistance breeding, as previously emphasized by Khan and Korban [35]. In contrast, the moderate to low heritability estimates for codling moth and brown rot highlight the importance of local environmental conditions and the limitations of genetic resistance alone in managing these stressors. This suggests that control strategies for C. pomonella and Monilinia spp. must remain flexible and adaptive, incorporating weather-based risk assessments. Interestingly, our data also revealed site-specific interactions between stressors and orchard characteristics. For example, apple scab incidence was significantly higher at higher altitudes, where humidity was more persistent, whereas aphid infestation tended to be greater in lowland orchards. The frequency of phytosanitary treatments was negatively correlated with scab and aphid levels, indicating that preventive spraying in spring was effective for these targets. However, the positive correlation between brown rot and treatment frequency implies that fungicides were often applied reactively, after infection had already taken place; this finding suggests the need for earlier detection or more effective timing.

From a broader perspective, this study brings forward original insights by integrating disease and pest monitoring with multivariate climate data and heritability analysis. In doing so, it contributes to a better understanding of cultivar-specific resilience and supports the development of precision orchard systems that are more responsive to climatic variability and less reliant on chemical inputs. The consistent superior performance of ‘Florina’ underscores the potential of genetically resistant cultivars to meet the dual goals of productivity and environmental stewardship. In the context of modern pomology, where consumer health, ecological sustainability, and climate adaptation intersect, such cultivars play a vital role in ensuring the long-term viability of apple production. This integrated approach, combining empirical field observations with ecological and genetic interpretation, advances current knowledge on the adaptive performance of apple genotypes in real-world conditions. The findings not only validate previous hypotheses regarding G × E × M interactions but also provide a robust foundation for decision-making in breeding, orchard design, and integrated pest and disease management strategies.

5. Conclusions

This study highlights the complex interactions between genetic, ecological, and cultural factors that determine the apple tree’s response to major diseases and pests. Among the five cultivars studied, ‘Florina’ exhibited the most consistent response to both pathogens and insect pests, while ‘Jonathan’ and ‘Golden Delicious’ were generally more susceptible. Disease incidence was strongly associated with precipitation, whereas pest infestation showed significant dependence on temperature. Multivariate and regression analyses revealed consistent co-occurrence patterns between several biotic stressors, particularly between E. lanigerum and Aphis spp., as well as between powdery mildew and apple scab. The calculated heritability coefficients confirmed that genetic factors contribute substantially to stressor response in most cases, suggesting that breeding for resistance remains a viable and important objective. The integration of these findings supports the need for tailored, location-specific management approaches that consider both cultivar-specific resistance profiles and local environmental conditions. These insights are relevant for improving pest and disease forecasting, optimizing treatment schedules, and selecting cultivars best adapted to changing climate scenarios.