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A special issue of Agronomy (ISSN 2073-4395). This special issue belongs to the section "Pest and Disease Management".

Deadline for manuscript submissions: 1 August 2025 | Viewed by 11084

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Special Issue Editors

Dr. Antonios E. Tsagkarakis

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Guest Editor

Department of Crop Science, Agricultural University of Athens, 1155 Athens, Greece
Interests: integrated pest management; biological control; auchenorrhyncha; sustainable plant protection; pollinators; remote sensing; precision plant protection; productive entomology; apiculture; insects as proteins

Prof. Dr. Georgios Papadoulis

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Guest Editor

Department of Crop Science, Agricultural University of Athens, 1155 Athens, Greece
Interests: agricultural zoology and entomology

Dr. Argyro Kalaitzaki

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Guest Editor

Institute for Olive Tree, Subtropical Crops & Viticulture, Hellenic Agricultural Organization “DEMETER", 73100 Chania, Greece
Interests: insect pest; insect parasitoids; population dynamics; vectors of xylella fastidiosa; mass trapping; monitoring; biological control; integrated pest management; smart tools in agriculture

Special Issue Information

Dear Colleagues,

Crop pests can cause significant yield losses and threaten food supply and security. Relying solely on synthetic pesticides for pest control has proven ineffective and induces adverse effects on pollinators, biodiversity, environmental sustainability, and human health. Moreover, the overreliance on pesticides can foster resistance in pests, trigger outbreaks of other pest species, and adversely affect non-target organisms. To ensure improved control and ecological sustainability, it is essential to reduce synthetic pesticide usage. This can be achieved via the adoption of alternative and effective strategies that keep pest populations below the economic injury threshold, aligning with the objectives of the European Green Deal.

In this Special Issue, we aim to share knowledge on all aspects related to sustainable plant pest management systems that are also compatible with pollination services, adopting a "from farm to fork" approach.

Based on the above, we welcome original research articles and reviews, which will focus on:

Integrated and biological pest management systems of crops;
Use of pollinators for sustainable farming;
Smart plant protection systems (remote sensing, artificial intelligence, decision support systems);
Innovative pollinator-friendly pest control;
Biopesticides.

Dr. Antonios E. Tsagkarakis
Prof. Dr. Georgios Papadoulis
Dr. Argyro Kalaitzaki
Guest Editors

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Agronomy is an international peer-reviewed open access monthly journal published by MDPI.

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Keywords

integrated pest management
biological control
precision plant protection
pollinators
remote sensing
biopesticides
sustainable pest management

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Published Papers (9 papers)

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Research

16 pages, 1873 KiB

Open AccessArticle

Satureja kitaibelii Essential Oil and Extracts: Bioactive Compounds and Pesticide Properties

by Milena Nikolova, Aneta Lyubenova, Elina Yankova-Tsvetkova, Borislav Georgiev, Genadi Gavrilov and Anna Gavrilova

Agronomy 2025, 15(2), 357; https://doi.org/10.3390/agronomy15020357 - 30 Jan 2025

Cited by 1 | Viewed by 798

Abstract

In recent years, the essential oil of Satureja species has been studied as a source of biocidal activity with potential applications in organic farming such as bio-pesticides. The present study aims to determine the potential of essential oil (EO), exudate fraction (EF) and methanolic extract (ME) of Satureja kitaibelii Wierzb. ex Heuff. to inhibit the mycelial growth of phytopathogenic fungi and acetylcholinesterase (AChE). Additionally, ME was tested for inhibitory activity on seed germination and root elongation. Phytochemical analysis was conducted using gas chromatography–mass spectrometry (GC–MS) and thin-layer chromatography (TLC). Biological activities were studied using in vitro methods. p-Cymene, limonene, geraniol, carvacrol and borneol were identified as the main components of EO. Oleanolic and ursolic acid, carvacrol and flavonoid aglycones were determined as the most abundant bioactive compounds of EF, whereas rosmarinic acid and flavonoid glycosides were found in ME. EO reduced the growth of all tested plant pathogens, indicated by 40% to 84% inhibition of mycelial growth (IMG). The growth rates of oomycetes Phytophthora cryptogea Pethybr. & Laff. and Phytophthora nicotianae Breda de Haan were affected to the greatest extent with 84% and 68% IMG. EF showed the most potent AChE inhibitory activity with IC₅₀ value of 0.18 mg/mL. Aqueous solutions of the ME with a concentration above 5 mg/mL were found to inhibit seed germination by more than 90%, whereas a reduction in root elongation was observed at 3 mg/mL. The present study provides for the first time data for the pesticidal properties of EO, EF and ME of S. kitaibelii. Full article

(This article belongs to the Special Issue Pests, Pesticides, Pollinators and Sustainable Farming)

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20 pages, 4651 KiB

Open AccessArticle

Faunistic Study of Auchenorrhyncha in Olive Orchards in Greece, Including First Records of Species

by Zoi Thanou, Myrto Stamouli, Anastasia Magklara, David Theodorou, Georgia Stamatakou, Georgios Konidis, Panagiota Koufopoulou, Christos Lyberopoulos, Sofia Tribonia, Petros Vetsos, Andreas Katribouzas, Argyro Kalaitzaki, Georgios Papadoulis and Antonios Tsagkarakis

Agronomy 2024, 14(12), 2792; https://doi.org/10.3390/agronomy14122792 - 25 Nov 2024

Viewed by 752

Abstract

The study of Auchenorrhyncha species composition in Greek olive orchards is crucial due to the potential threat of Xylella fastidiosa invading the region. Recent studies have begun exploring agricultural landscapes, particularly olive and citrus orchards. From 2016 to 2022, biodiversity surveys were conducted in thirteen olive orchards across three regions of Greece: Peloponnese, Sterea Ellada, and the Northeast Aegean. Malaise traps were installed in each orchard and monitored monthly, supplemented by sweep net sampling in two orchards to capture less mobile species and assess their association with host plants. A total of 14,771 specimens were collected, representing 125 species predominantly feeding on weeds. The dominant species were the Typhlocybinae Hebata decipiens and Zyginidia pullula, while Euscelis lineolata was the most common Deltocephalinae. Aphrophoridae, including Philaenus spumarius and Neophilaenus campestris, were more effectively collected with sweep nets, primarily from Avena sterilis L. This study offers a detailed overview of the Auchenorrhyncha fauna in Greek olive orchards, providing essential insights for developing strategies to prevent the invasion of Xylella fastidiosa. Full article

(This article belongs to the Special Issue Pests, Pesticides, Pollinators and Sustainable Farming)

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24 pages, 4358 KiB

Open AccessArticle

Longitudinal Analysis of Honey Bee Colony Health as a Function of Pesticide Exposure

by Susan E. Kegley, Rosemarie Radford, Timothy J. Brown, Jeff Anderson, Darren Cox, Steve Ellis and Geoffrey W. Marcy

Agronomy 2024, 14(11), 2505; https://doi.org/10.3390/agronomy14112505 - 25 Oct 2024

Viewed by 1238

Abstract

Sixty commercial honey bee colonies were monitored over the course of one year with the goal of assessing potential correlations between measured colony strength and environmental stressors, including exposures to pesticides and pathogens. We developed a new method for assessing colony health by determining the fractional change in population of the four colonies on each pallet between peak population on 1 June and the last population assessment prior to winter on 1 October. This fractional change in population was evaluated as a function of pesticide load per pallet for each of the 37 pesticide chemicals detected, grouping pallets by beekeeper. The analysis of individual chemicals showed that both imidacloprid and cyprodinil were negatively correlated with colony health, while tau-fluvalinate and dinotefuran (at very low concentrations) were positively correlated, possibly because of effects on Varroa control. Exposure to groups of chemicals was also evaluated. Normalization of each chemical concentration to the maximum observed for that chemical provided an equal weighting for each chemical, even though their relative occurrence in the environment and their effective toxicities might differ. A total of 24 chemical groups whose members share a structural commonality, a functional commonality, or suspected synergistic actions were considered, demonstrating negative correlations between colony health and exposures to neonicotinoids as a group and neonicotinoids in combination with (1) methoxyfenozide (2) organophosphates, and (3) diflubenzuron. Analysis of several groups of fungicides applied to almonds during pollination also showed negative correlations with colony health. Full article

(This article belongs to the Special Issue Pests, Pesticides, Pollinators and Sustainable Farming)

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14 pages, 2348 KiB

Open AccessEditor’s ChoiceArticle

Use of Beauveria bassiana and Bacillus amyloliquefaciens Strains as Gossypium hirsutum Seed Coatings: Evaluation of the Bioinsecticidal and Biostimulant Effects in Semi-Field Conditions

by Vasileios Papantzikos, Spiridon Mantzoukas, Alexandra Koutsompina, Evangelia M. Karali, Panagiotis A. Eliopoulos, Dimitrios Servis, Stergios Bitivanos and George Patakioutas

Agronomy 2024, 14(10), 2335; https://doi.org/10.3390/agronomy14102335 - 10 Oct 2024

Viewed by 1332

Abstract

There are many challenges in cotton cultivation, which are mainly linked to management practices and market demands. The textile commerce requirements are increasing but the effects of climate change on cotton cultivation are becoming an issue, as its commercial development depends significantly on the availability of favorable climatic parameters and the absence of insect pests. In this research, it was studied whether the use of two commercial strains as cotton seed coatings could effectively contribute to the previous obstacles. The experiment was carried out in semi-field conditions at the University of Ioannina. It used a completely randomized design and lasted for 150 days. The following treatments were tested: (a) coated seeds with a commercial strain of Beauveria bassiana (Velifer^®); (b) coated seeds with a combination of Velifer^® and a commercial strain of Beauveria bassiana (Selifer^®); and (c) uncoated cotton seeds (control). The biostimulant effect of the two seed coatings was assessed against the growth characteristics of cotton, and the total chlorophyll and proline content. The bioinsecticidal effect was evaluated by measuring the population of Aphis gossypii on the cotton leaves. The proline effect increased by 15% in the treated plants, whereas the total chlorophyll was higher in the use of both Velifer^® and Velifer^®–Selifer^® treatments by 32% and 19%, respectively. Aphid populations also decreased in the treated plants compared to the control plants (29.9% in Velifer^® and 22.4% in Velifer^®–Selifer^®). Based on an assessment of the above parameters, it follows that the two seed coatings can significantly enhance the growth performance of cotton and reduce the abundance of A. gossypii. Full article

(This article belongs to the Special Issue Pests, Pesticides, Pollinators and Sustainable Farming)

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17 pages, 8025 KiB

Open AccessArticle

Using Multispectral Data from UAS in Machine Learning to Detect Infestation by Xylotrechus chinensis (Chevrolat) (Coleoptera: Cerambycidae) in Mulberries

by Christina Panopoulou, Athanasios Antonopoulos, Evaggelia Arapostathi, Myrto Stamouli, Anastasios Katsileros and Antonios Tsagkarakis

Agronomy 2024, 14(9), 2061; https://doi.org/10.3390/agronomy14092061 - 9 Sep 2024

Viewed by 949

Abstract

The tiger longicorn beetle, Xylotrechus chinensis Chevrolat (Coleoptera: Cerambycidae), has posed a significant threat to mulberry trees in Greece since its invasion in 2017, which may be associated with global warming. Detection typically relies on observing adult emergence holes on the bark or dried branches, indicating severe damage. Addressing pest threats linked to global warming requires efficient, targeted solutions. Remote sensing provides valuable, swift information on vegetation health, and combining these data with machine learning techniques enables early detection of pest infestations. This study utilized airborne multispectral data to detect infestations by X. chinensis in mulberry trees. Variables such as mean NDVI, mean NDRE, mean EVI, and tree crown area were calculated and used in machine learning models, alongside data on adult emergence holes and temperature. Trees were classified into two categories, infested and healthy, based on X. chinensis infestation. Evaluated models included Random Forest, Decision Tree, Gradient Boosting, Multi-Layer Perceptron, K-Nearest Neighbors, and Naïve Bayes. Random Forest proved to be the most effective predictive model, achieving the highest scores in accuracy (0.86), precision (0.84), recall (0.81), and F-score (0.82), with Gradient Boosting performing slightly lower. This study highlights the potential of combining remote sensing and machine learning for early pest detection, promoting timely interventions, and reducing environmental impacts. Full article

(This article belongs to the Special Issue Pests, Pesticides, Pollinators and Sustainable Farming)

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14 pages, 19599 KiB

Open AccessArticle

Stress Response of Citrus Leaves under Mechanical Damage and Huanglongbing Disease Infection Using Plasmonic TiO₂ Nanotube Substrate-Based Imprinting Mass Spectrometry Imaging

by Yaming Sun, Dong Chen, Xiran Chen and Xinzhou Wu

Agronomy 2024, 14(8), 1797; https://doi.org/10.3390/agronomy14081797 - 15 Aug 2024

Cited by 1 | Viewed by 1187

Abstract

Mapping the molecular signatures and metabolic regulation of plant tissues under biotic/abiotic stresses and defensive responses has become a subject of increasing interest in plant biology and systems biology, but determining when and where specialized metabolites are produced and accumulated currently remains a somewhat elusive goal. Herein, we demonstrated the use of a TiO₂ nanotube-based composite substrate modified with plasmonic gold nanoparticles and hydrophobic polydopamine (AuNP-hPDA-TDNT) for surface-assisted laser desorption/ionization mass spectrometry (SALDI-MS) analysis of a wide range of pesticides and for visualizing the stress-responsive metabolites of citrus leaves during various plant defense processes. This method enabled the visualization of non-uniform and tissue-specific distribution patterns of functional metabolites of citrus leaves that were mechanically damaged, fed to larvae, and infected by Huanglongbing disease. Interestingly, some specialized metabolites exhibited different accumulation and regulation patterns for mechanical damage and larval feeding, suggesting that plant-derived secondary metabolites exercise specific defensive functions with respect to various damage processes. Moreover, the early diagnosis and detection of HLB disease-associated biomarkers can facilitate the prevention of citrus HLB diseases. Overall, this imprinting MS imaging strategy will expand the scope of MS techniques in plant biology, providing more biologically relevant insights into the biosynthesis, accumulation, and defensive role of bioactive metabolites in economically important plants. Full article

(This article belongs to the Special Issue Pests, Pesticides, Pollinators and Sustainable Farming)

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9 pages, 751 KiB

Open AccessArticle

Spring Abundance, Migration Patterns and Damaging Period of Aleyrodes proletella in the Czech Republic

by Kamil Holý and Kateřina Kovaříková

Agronomy 2024, 14(7), 1477; https://doi.org/10.3390/agronomy14071477 - 8 Jul 2024

Viewed by 778

Abstract

The cabbage whitefly has become an important pest on brassica vegetables in Central Europe. It does not destroy the affected plants, but the product becomes unmarketable, causing considerable economic losses. The pest is also difficult to control due to its way of life and because it develops resistance to some of the active components of insecticides. In organic farming systems, insecticides are strictly restricted, but neither predators nor whitefly parasitoids are able to keep the pest at a tolerable level. It is, therefore, necessary to become familiar with the whitefly’s life cycle and habits, including mass migration from winter hosts to vegetables. We inspected 44 rapeseed fields across the republic in the period 2014–2021 in order to find the connection between the presence of oilseed rape fields near vegetable growing areas (VGAs) and the abundance of the overwintering cabbage whiteflies. We also conducted regular weekly monitoring of whitefly occurrence in the main cultivation area of the Czech Republic (Polabí) with the aim of specifying critical data important for the successful control of this pest. We found that the cabbage whitefly incidences were many times higher in rapeseed fields close to VGAs compared to areas where the crops are not adjacent. The average number of whiteflies was 0.59 individuals per plant in VGA-1 (oilseed rape grown inside this area or up to 1 km far), 0.052 in VGA-2 (distance 3–10 km from vegetable fields) and 0.014 in VGA-3 (more than 20 km). In the extremely warm year 2016, the difference was up to sixty times. The first CW eggs laid on cruciferous vegetables were usually found around 20 May. The period of mass migration of CW adults to cruciferous vegetables was between 6 June and 2 August. At this time, vegetables are most vulnerable to damage. Successful control of the cabbage whitefly requires the use of fabric netting, combined with an insecticide as needed and trap plants as needed; the latter have to be destroyed before adult whiteflies hatch—typically in early July. Full article

(This article belongs to the Special Issue Pests, Pesticides, Pollinators and Sustainable Farming)

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22 pages, 43859 KiB

Open AccessEditor’s ChoiceArticle

Enhanced Tomato Pest Detection via Leaf Imagery with a New Loss Function

by Lufeng Mo, Rongchang Xie, Fujun Ye, Guoying Wang, Peng Wu and Xiaomei Yi

Agronomy 2024, 14(6), 1197; https://doi.org/10.3390/agronomy14061197 - 1 Jun 2024

Cited by 4 | Viewed by 1289

Abstract

Pests have caused significant losses to agriculture, greatly increasing the detection of pests in the planting process and the cost of pest management in the early stages. At this time, advances in computer vision and deep learning for the detection of pests appearing in the crop open the door to the application of target detection algorithms that can greatly improve the efficiency of tomato pest detection and play an important technical role in the realization of the intelligent planting of tomatoes. However, in the natural environment, tomato leaf pests are small in size, large in similarity, and large in environmental variability, and this type of situation can lead to greater detection difficulty. Aiming at the above problems, a network target detection model based on deep learning, YOLONDD, is proposed in this paper. Designing a new loss function, NMIoU (Normalized Wasserstein Distance with Mean Pairwise Distance Intersection over Union), which improves the ability of anomaly processing, improves the model’s ability to detect and identify objects of different scales, and improves the robustness to scale changes; Adding a Dynamic head (DyHead) with an attention mechanism will improve the detection ability of targets at different scales, reduce the number of computations and parameters, improve the accuracy of target detection, enhance the overall performance of the model, and accelerate the training process. Adding decoupled head to Head can effectively reduce the number of parameters and computational complexity and enhance the model’s generalization ability and robustness. The experimental results show that the average accuracy of YOLONDD can reach 90.1%, which is 3.33% higher than the original YOLOv5 algorithm and is better than SSD, Faster R-CNN, YOLOv7, YOLOv8, RetinaNet, and other target detection networks, and it can be more efficiently and accurately utilized in tomato leaf pest detection. Full article

(This article belongs to the Special Issue Pests, Pesticides, Pollinators and Sustainable Farming)

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13 pages, 1231 KiB

Open AccessArticle

Developing an Effective Push–Pull System for Managing Outbreaks of the Invasive Pest Bactrocera dorsalis (Diptera: Tephritidae) in Nephelium lappaceum Orchards

by Jian Wen, Zhe Shan, Yan Zou, Xianwu Lin, Zhifu Cui, Rihui Yan and Fengqin Cao

Agronomy 2024, 14(5), 890; https://doi.org/10.3390/agronomy14050890 - 24 Apr 2024

Viewed by 1715

Abstract

Outbreaks of the oriental fruit fly, Bactrocera dorsalis (Hendel), present significant challenges to global fruit production, necessitating effective control measures that minimize environmental risks and pesticide resistance. This study aimed to develop and evaluate the effectiveness of four distinct push–pull control strategies for managing B. dorsalis outbreaks in a Nephelium lappaceum orchard. These strategies involved the inclusion of low-concentration abamectin, spraying repellent with a drone or manually, using methyl eugenol (ME) or food bait and employing either two types of attractants and repellents or a single type. The findings indicated that incorporating the low-concentration abamectin into the push–pull system, utilizing ME as an attractant instead of food lures and manually applying abamectin and attractants were all effective in reducing the B. dorsalis population size and minimizing fruit damage. While increasing the diversity of repellents and attractants enhanced the long-term effectiveness of the system, it did not result in a significant decrease in B. dorsalis population size or fruit damage rate compared to using a single repellent or attractant. In conclusion, the push–pull strategy emerged as a viable method for managing B. dorsalis outbreaks, offering potential benefits in reducing environmental risks and pesticide resistance. However, the study underscored the importance of the context-specific construction of push–pull strategies to optimize their effectiveness in orchard settings. Full article

(This article belongs to the Special Issue Pests, Pesticides, Pollinators and Sustainable Farming)

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