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Agriculture
Volume 15
Issue 4
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Agriculture, Volume 15, Issue 4 (February-2 2025) – 88 articles

Cover Story (view full-size image): While microplastics can reduce the bioavailability of pesticides due to adsorption, they also increase the persistence of pesticides and alter their toxicity. Subsequent desorption, influenced by microplastic types and pesticide hydrophobicity and partitioning, replenishes the pesticides in the soil. This permits the gradual release of pesticides and potential sustained actions on target organisms and non-target organisms. As microplastic pollution increases, the frequency or amount of pesticide applications will need to increase to achieve the desired level of crop protection, resulting in negative costs and environmental impacts. Future studies can quantify how microplastic–pesticide interactions affect target pests to more precisely understand the effects of microplastics on pesticide applications. View this paper
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31 pages, 4303 KiB  
Article
Research on Flexible Job Shop Scheduling Method for Agricultural Equipment Considering Multi-Resource Constraints
by Zhangliang Wei, Zipeng Yu, Renzhong Niu, Qilong Zhao and Zhigang Li
Agriculture 2025, 15(4), 442; https://doi.org/10.3390/agriculture15040442 - 19 Feb 2025
Viewed by 287
Abstract
The agricultural equipment market has the characteristics of rapid demand changes and high demand for machine models, etc., so multi-variety, small-batch, and customized production methods have become the mainstream of agricultural machinery enterprises. The flexible job shop scheduling problem (FJSP) in the context [...] Read more.
The agricultural equipment market has the characteristics of rapid demand changes and high demand for machine models, etc., so multi-variety, small-batch, and customized production methods have become the mainstream of agricultural machinery enterprises. The flexible job shop scheduling problem (FJSP) in the context of agricultural machinery and equipment manufacturing is addressed, which involves multiple resources including machines, workers, and automated guided vehicles (AGVs). The aim is to optimize two objectives: makespan and the maximum continuous working hours of all workers. To tackle this complex problem, a Multi-Objective Discrete Grey Wolf Optimization (MODGWO) algorithm is proposed. The MODGWO algorithm integrates a hybrid initialization strategy and a multi-neighborhood local search to effectively balance the exploration and exploitation capabilities. An encoding/decoding method and a method for initializing a mixed population are introduced, which includes an operation sequence vector, machine selection vector, worker selection vector, and AGV selection vector. The solution-updating mechanism is also designed to be discrete. The performance of the MODGWO algorithm is evaluated through comprehensive experiments using an extended version of the classic Brandimarte test case by randomly adding worker and AGV information. The experimental results demonstrate that MODGWO achieves better performance in identifying high-quality solutions compared to other competitive algorithms, especially for medium- and large-scale cases. The proposed algorithm contributes to the research on flexible job shop scheduling under multi-resource constraints, providing a novel solution approach that comprehensively considers both workers and AGVs. The research findings have practical implications for improving production efficiency and balancing multiple objectives in agricultural machinery and equipment manufacturing enterprises. Full article
(This article belongs to the Section Agricultural Technology)
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13 pages, 262 KiB  
Article
Effects of Vegetable Oils Supplemented into Broiler Diet on the Fatty Acid Profile and Lipid Indices in Broiler Meat
by Zlata Kralik, Gordana Kralik and Manuela Košević
Agriculture 2025, 15(4), 441; https://doi.org/10.3390/agriculture15040441 - 19 Feb 2025
Viewed by 305
Abstract
This paper investigates the influence of vegetable oils (sunflower oil (SO), rapeseed oil (RO), and linseed oil (LO)) supplemented into broiler diets on the fatty acids profile and quality of lipids in breasts and thighs, expressed through qualitative, nutritional, and metabolic indices. Broilers [...] Read more.
This paper investigates the influence of vegetable oils (sunflower oil (SO), rapeseed oil (RO), and linseed oil (LO)) supplemented into broiler diets on the fatty acids profile and quality of lipids in breasts and thighs, expressed through qualitative, nutritional, and metabolic indices. Broilers of the Ross 308 hybrid were divided into three groups and fattened over 6 weeks. During the last three weeks of fattening, broilers were fed a finisher diet that differed in types of supplemented oil. Diets were balanced at the level of 19.80% crude protein and 13.5 MJ ME/kg of feed. Feed and water were offered to broilers ad libitum. Fatty acid profiles were determined in samples of broiler breasts and thighs, based on which lipids health indices were calculated. Quantitative indices (polyunsaturated fatty acids-∑PUFA/saturated fatty acids-∑SFA, ∑PUFA n-6/∑PUFA n-3, linoleic acid-LA/α-linolenic acid-ALA, and eicosapentaenoic acid-EPA+ docosahexaenoic acid-DHA) were influenced by the type of oil (p < 0.001), whereas the type of meat was only important for the index of ∑PUFA/∑SFA (p < 0.001). Nutritional indices (nutritional value index-NVI, atherogenicity index-AI, thrombogenicity index-TI, hypo/hypercholesterolemic index-hHI, health-promoting index-HPI) depended on both factors (p < 0.001). The metabolic indices (elongase index-EI, thioesterase index-THI, ∆9-desaturase, ∆5 + ∆6-desaturase, kinetic activity index-KHI) were significantly affected by the type of meat (p < 0.001), as well as by the feeding treatments (p < 0.05), except for the EI index. This research confirmed that oils supplemented into broiler feed influence the fatty acid profiles in broiler meat. It has also been confirmed that the fatty acid profile affects the lipid quality in meat, which may be beneficial for consumers’ health. Full article
(This article belongs to the Special Issue The Impact of Nutrition on Poultry Meat and Egg Quality)
13 pages, 1082 KiB  
Article
Effect of Kaolin Clay on Post-Bloom Thinning Efficacy, Cropping, and Fruit Quality in ‘Gala Vill’ Apple (Malus × domestica) Cultivation
by Sebastian Przybyłko, Jacek Marszał, Wojciech Kowalczyk and Ewa Szpadzik
Agriculture 2025, 15(4), 440; https://doi.org/10.3390/agriculture15040440 - 19 Feb 2025
Viewed by 340
Abstract
Effective thinning methods that balance yield, fruit quality, and ripening dynamics are essential to ensure efficient and sustainable apple production. This study examined the effects of various thinning treatments on ‘Gala Vill’ apples (Malus × domestica Borkh.) to assess their impacts on [...] Read more.
Effective thinning methods that balance yield, fruit quality, and ripening dynamics are essential to ensure efficient and sustainable apple production. This study examined the effects of various thinning treatments on ‘Gala Vill’ apples (Malus × domestica Borkh.) to assess their impacts on fruit set, yield, and quality parameters. The experiment was conducted in 2020 at the experimental orchard of WULS located in Wilanów, Warsaw, Poland. The treatments included chemical thinning using different doses of metamitron (Brevis 150 SG) alone and in combination with kaolin clay at two concentrations (50 and 100 kg∙ha−1), and, as alternatives to the chemical method, using kaolin clay alone (50, 100, and 200 kg∙ha−1) and artificial shading. The results highlight the effectiveness of thinning treatments in modulating key agronomic traits. Artificial shading significantly reduced the number of fruitlets, demonstrating its utility as a non-chemical thinning option. Metamitron application effectively reduced the number of fruitlets in a dose-dependent manner. Combining metamitron with kaolin clay did not enhance the thinning effect compared with metamitron alone. However, kaolin clay applied independently, particularly at higher concentrations, was associated with improved fruit setting and yield. For instance, kaolin clay at 200 kg∙ha−1 (KC200) resulted in the highest fruit set (85.2) and yield (10.1 kg·tree−1), suggesting its adverse effect on thinning to promote fruit retention under certain conditions. Full article
(This article belongs to the Special Issue The Impact of Environmental Factors on the Quality of Horticultural Commodities)
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17 pages, 636 KiB  
Article
Saccharomyces cerevisiae Supplementation Improves Growth Performance and Heat Stress Tolerance in Angus Steers
by Chang-Xiao Shi, Shun-Ran Yang, Ying-Qi Li, Hui-Li Wang, Sheng-Nan Min, Shuo Zhang, Hong-Liang Zhang, Ya-Wen Luo, Wen-Xi Zhao, Yang He, Bing-Hai Cao and Hua-Wei Su
Agriculture 2025, 15(4), 439; https://doi.org/10.3390/agriculture15040439 - 19 Feb 2025
Viewed by 318
Abstract
Saccharomyces cerevisiae (SC) can be incorporated into ruminant diets as a postbiotic product. This study aimed to explore the effects of supplementing different levels of SC in the diets of mid-fattening Angus steers under heat stress conditions. A total of twenty-seven steers were [...] Read more.
Saccharomyces cerevisiae (SC) can be incorporated into ruminant diets as a postbiotic product. This study aimed to explore the effects of supplementing different levels of SC in the diets of mid-fattening Angus steers under heat stress conditions. A total of twenty-seven steers were randomly allocated into 3 groups: control, 30 g SC addition and 60 g SC addition groups. After a 7-day adaptation period followed by a 120-day experimental period, including respiratory rate, rectal temperature, growth performance, apparent digestibility of nutrients, rumen fermentation parameters, urine metabolites, serum biochemistry and antioxidant were measured. The results showed that the rectal temperature and respiratory rate of cattle decreased upon the addition of SC during heat stress. Meanwhile, the growth performance of cattle was improved in the 30 g SC addition group. The serum energy metabolism related indexes, such as non-esterified fatty acids, glucose, and β-hydroxybutyric acid, were altered. Additionally, the activity of catalase was significantly enhanced with the addition of SC. Overall, the addition of SC to the diets of mid-fattening Angus steer did not negatively affect rumen fermentation and nutrient apparent digestibility. Instead, it was capable of improving physiological performance under heat stress by modifying the energy metabolism and augmenting antioxidant capacity, which ultimately led to an improvement in growth performance. In conclusion, the most suitable level of SC to be added to the diet of mid-fattening Angus steers is 30 g/steer/d. Full article
(This article belongs to the Topic Feeding Livestock for Health Improvement)
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16 pages, 4698 KiB  
Article
The Effect of Foliar Calcium Spraying on Changes in the Mechanical Properties of Blueberry (Vaccinium corymbosum L.)
by Piotr Komarnicki and Beata Cieniawska
Agriculture 2025, 15(4), 438; https://doi.org/10.3390/agriculture15040438 - 19 Feb 2025
Viewed by 302
Abstract
One of the methods used to improve the durability of blueberry fruits is the application of nutrients through foliar feeding with calcium, which can improve the post-harvest mechanical parameters. This study proposed an optimal selection of calcium spray parameters, which enables a rational [...] Read more.
One of the methods used to improve the durability of blueberry fruits is the application of nutrients through foliar feeding with calcium, which can improve the post-harvest mechanical parameters. This study proposed an optimal selection of calcium spray parameters, which enables a rational minimisation of the negative impact of agrochemicals in the environment. The qualitative evaluation of blueberry fruit showed lime spraying induces a significant effect on the increase in fruit size, especially at a pressure of 0.2 MPa and with AIXR nozzles compared to the control group. To assess the mechanical properties, a modern method of identifying the actual loads and maximum surface pressures generated by the picker during harvesting is presented. Compression and fruit rupture tests were also used to determine the pressure values and forces that are considered safe from the perspective of harvest quality. The comparative analysis of destructive compression and detachment tests confirmed that fruit firmness (Fp) was approximately 80% higher than the detachment force (Fpf), with peak pressures more than twice as high, suggesting that handpicking poses minimal risk of mechanical damage. The implementation of optimal spraying techniques combined with the correct assessment of the mechanical properties of fruits is important in agricultural practice, where it is crucial to obtain high-quality blueberries after harvest. Full article
(This article belongs to the Section Crop Production)
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23 pages, 2503 KiB  
Article
Use of Bacterial-Enzymatic Inoculant Improves Silage Quality and Reduces Fermentation Losses in Intercropped Systems
by Bruno de Souza Marques, Kátia Aparecida de Pinho Costa, Luciana Maria da Silva, Adriano Carvalho Costa, Gerson Carlos Ferrari, João Francisco de Lima, Amilton Ferreira da Silva, Wildo Pereira Matos, Lucas Ferreira Gonçalves, Divino Antonio Santana Lima, Juliany Vale Ferreira, Emilly Farias Pontes and Fabrício Flávio Passos Oliveira
Agriculture 2025, 15(4), 437; https://doi.org/10.3390/agriculture15040437 - 19 Feb 2025
Viewed by 316
Abstract
The ensiling potential of Tamani guinea grass (Panicum maximum cv. BRS Tamani) and Stylosanthes cv. Bela in monoculture or intercropped systems, and the effect of two treatments on ensiling (with and without inoculant) on fermentation quality and nutritional composition of the silage [...] Read more.
The ensiling potential of Tamani guinea grass (Panicum maximum cv. BRS Tamani) and Stylosanthes cv. Bela in monoculture or intercropped systems, and the effect of two treatments on ensiling (with and without inoculant) on fermentation quality and nutritional composition of the silage after 50 days of ensiling, were evaluated. The experiment was conducted at the Instituto Federal Goiano, Campus Rio Verde, Goiás, Brazil, using a randomized block design with four replications in a 3 × 2 factorial scheme, totaling 24 experimental silos. The forage was harvested during a 28-day regrowth cycle. Results indicated that silages without inoculants showed inadequate fermentative characteristics, compromising nutritional preservation. The addition of microbial inoculants improved the fermentation process, ensuring proper preservation of silage. The intercropping of Tamani guinea grass with Stylosanthes cv. Bela resulted in higher dry matter production and improved the nutritional value of the silage, with increases of 3.46% in crude protein content, 20.96% in ADIP (acid detergent insoluble protein), 6.31% in soluble carbohydrates, and 10.06% in starch compared to the silage of Tamani guinea grass in monoculture. Therefore, the use of silage from intercropped Tamani guinea grass and Stylosanthes cv. Bela with the addition of inoculants can be recommended as a productive and sustainable practice, reducing costs associated with protein and mineral supplementation. Full article
(This article belongs to the Special Issue Advances in the Cultivation and Production of Leguminous Plants)
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14 pages, 1387 KiB  
Article
Nematicidal Extracts of Chinaberry, Parsley and Rocket Are Safe to Eisenia fetida, Enchytraeus albidus, Daphnia magna and Danio rerio
by Pelagia Anastasiadou, Nikoletta Ntalli, Katerina Kyriakopoulou and Konstantinos M. Kasiotis
Agriculture 2025, 15(4), 436; https://doi.org/10.3390/agriculture15040436 - 19 Feb 2025
Viewed by 259
Abstract
In the frame of a “greener agriculture”, the development of new natural pesticides that are safer than their synthetic counterparts is gaining ground. Nonetheless, the origin of their nature does not necessarily imply their eco-friendliness. Hence, specific ecotoxicological studies are needed, with products [...] Read more.
In the frame of a “greener agriculture”, the development of new natural pesticides that are safer than their synthetic counterparts is gaining ground. Nonetheless, the origin of their nature does not necessarily imply their eco-friendliness. Hence, specific ecotoxicological studies are needed, with products being subjected to hazard and consequent risk assessment, for registration purposes. We have previously described on the strong nematicidal activity of Melia azedarach (chinaberry), Petroselinum crispum (parsley) and Eruca sativa (rocket) against the nematode Meloidogyne incognita. With this study the effect of the above-mentioned nematicidal botanicals on Eisenia fetida, Enchytraeus albidus, Daphnia magna and Danio rerio (Zebrafish) is reported, being all model organisms for the study of ecotoxicology of pesticides under registration. The implemented protocols are according to the OECD standards used for the evaluation of formulates under authorization. NOEC values were estimated to be higher than the highest concentrations assessed as recommended by OECD guidelines (≥1000 mg test item/kg dry soil). According to the presented results, all tested botanical nematicidals proved ecofriendly, not hindering the reproduction of juvenile worms of Eisenia fetida, and Enchytraeus albidus. Notably, Petroselinum crispum exhibited beneficial effects on reproduction of Eisenia fetida, as the number of juveniles increased. M. azedarach extract demonstrated moderate toxicity to zebrafish embryos (LC50 was 51.41 ± 1.67 mg/L), yet it did not elicit adverse effects on the zebrafish liver. Thus, chinaberry, parsley and rocket are promising to be developed into new “green” nematicides. Full article
(This article belongs to the Section Crop Protection, Diseases, Pests and Weeds)
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15 pages, 3776 KiB  
Article
Characterization of Phytophthora and Pythium Species Associated with Root Rot of Olive Trees in Morocco
by Ikram Legrifi, Abderrahim Lazraq, Jamila Al Figuigui, Zineb Belabess, Moussa El Jarroudi and Rachid Lahlali
Agriculture 2025, 15(4), 435; https://doi.org/10.3390/agriculture15040435 - 19 Feb 2025
Viewed by 287
Abstract
The olive tree is one of the most important fruit crops grown in Morocco, yet extensive decline associated with the root rot of this crop has been observed in many regions. This study aimed to identify and characterize the oomycetes associated with root [...] Read more.
The olive tree is one of the most important fruit crops grown in Morocco, yet extensive decline associated with the root rot of this crop has been observed in many regions. This study aimed to identify and characterize the oomycetes associated with root rot disease in olive trees. During the 2021 and 2022 growing seasons, symptomatic root tissues and soil samples were collected for isolation. Based on morphological traits and the sequencing of the internal transcribed spacer (ITS) region of rDNA, 10 oomycete species were identified, belonging to the Phytophthora and Pythium sensu lato (s.l.) genera. Seven species were assigned to Phytophthora, namely, P. palmivora, P. plurivora, P. acerina, P. oleae, P. cactorum, P. gonapodyides, and P. megasperma. The Pythium s.l. genus was represented by three species, including P. schmitthenneri, P. aphanidermatum, and P. irregulare. A pathogenicity assay was conducted by soil infestation to evaluate the effect of these pathogens on one-year-old olive saplings (var. Picholine Marocaine). Results revealed that all 10 species were pathogenic to olive saplings. Inoculated saplings exhibited symptoms, such as root rot, vascular discoloration, and wilting. The pathogens were successfully re-isolated from necrotic roots, thereby fulfilling Koch’s postulates. These findings highlight the complex etiology of root rot disease in olive trees, as multiple species can induce similar symptoms. This study represents the first detailed report of Phytophthora and Pythium s.l. species associated with olive root rot disease in Morocco. Full article
(This article belongs to the Special Issue Detection, Diagnostics and Management Control Strategies of Plant Pathogens)
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25 pages, 12991 KiB  
Article
A Semi-Supervised Diffusion-Based Framework for Weed Detection in Precision Agricultural Scenarios Using a Generative Attention Mechanism
by Ruiheng Li, Xuaner Wang, Yuzhuo Cui, Yifei Xu, Yuhao Zhou, Xuechun Tang, Chenlu Jiang, Yihong Song, Hegan Dong and Shuo Yan
Agriculture 2025, 15(4), 434; https://doi.org/10.3390/agriculture15040434 - 19 Feb 2025
Viewed by 190
Abstract
The development of smart agriculture has created an urgent demand for efficient and accurate weed recognition and detection technologies. However, the diverse and complex morphology of weeds, coupled with the scarcity of labeled data in agricultural scenarios, poses significant challenges to traditional supervised [...] Read more.
The development of smart agriculture has created an urgent demand for efficient and accurate weed recognition and detection technologies. However, the diverse and complex morphology of weeds, coupled with the scarcity of labeled data in agricultural scenarios, poses significant challenges to traditional supervised learning methods. To address these issues, a weed detection model based on a semi-supervised diffusion generative network is proposed. This model integrates a generative attention mechanism and semi-diffusion loss to enable the efficient utilization of both labeled and unlabeled data. Experimental results demonstrate that the proposed method outperforms existing approaches across multiple evaluation metrics, achieving a precision of 0.94, recall of 0.90, accuracy of 0.92, and mAP@50 and mAP@75 of 0.92 and 0.91, respectively. Compared to traditional methods such as DETR, precision and recall are improved by approximately 10% and 8%, respectively. Additionally, compared to the enhanced YOLOv10, mAP@50 and mAP@75 are increased by 1% and 2%, respectively. The proposed semi-supervised diffusion weed detection model provides an efficient and reliable solution for weed recognition and introduces new research perspectives for the application of semi-supervised learning in smart agriculture. This framework establishes both theoretical and practical foundations for addressing complex target detection challenges in the agricultural domain. Full article
(This article belongs to the Special Issue Application of Vision Technology and Artificial Intelligence in Smart Farming—2nd Edition)
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17 pages, 1740 KiB  
Review
Addressing Cadmium in Cacao Farmland: A Path to Safer, Sustainable Chocolate
by Gina Alexandra García Porras, Jéssica Aires dos Santos, Mariana Rocha de Carvalho, Elberth Hernando Pinzón-Sandoval, Aline Aparecida Silva Pereira and Luiz Roberto Guimarães Guilherme
Agriculture 2025, 15(4), 433; https://doi.org/10.3390/agriculture15040433 - 19 Feb 2025
Viewed by 443
Abstract
Cacao cultivation is an important economic and social activity for tropical regions worldwide. Elevated cadmium (Cd) concentrations in soil and cacao beans have become a serious concern for producers and consumers, particularly following the implementation of stricter Cd limits for cacao products in [...] Read more.
Cacao cultivation is an important economic and social activity for tropical regions worldwide. Elevated cadmium (Cd) concentrations in soil and cacao beans have become a serious concern for producers and consumers, particularly following the implementation of stricter Cd limits for cacao products in the European Union since 2019. Cadmium is a potentially toxic element that can bioaccumulate in different plant tissues, raising concerns about the future of cacao exports and posing a significant threat to the food chain through consuming products with high Cd concentrations. Therefore, understanding the origins of Cd in cacao-producing countries’ agricultural soils is essential. Equally important is the need to investigate the factors influencing its availability, uptake, translocation, and distribution within the cacao plant, in addition to strategies for mitigating its effects or reducing its concentration in agriculturally relevant tissues. This review aims to contextualize the sources of Cd in the cacao agroecosystems while highlighting recent advances and perspectives in applying essential and beneficial elements, selecting low-accumulator genotypes, and utilizing associated microbiota. These strategies seek to mitigate Cd bioaccumulation and minimize its negative impacts on the cocoa value chain. Full article
(This article belongs to the Special Issue Heavy Metals in Farmland Soils: Mechanisms and Remediation Strategies)
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24 pages, 4942 KiB  
Article
Cross-Effect Between Cover Crops and Glyphosate-Based Herbicide Application on Microbiote Communities in Field Crops Soils
by Jérôme Bernier Brillon, Marc Lucotte, Blandine Giusti, Gilles Tremblay and Matthieu Moingt
Agriculture 2025, 15(4), 432; https://doi.org/10.3390/agriculture15040432 - 19 Feb 2025
Viewed by 299
Abstract
This study investigates how cover crops (CC) and different application rates of glyphosate-based herbicide (GBH) may affect soil microbial communities. Our hypothesis was that the use of CC would promote the presence of certain microbial communities in soils and mitigate the potential impact [...] Read more.
This study investigates how cover crops (CC) and different application rates of glyphosate-based herbicide (GBH) may affect soil microbial communities. Our hypothesis was that the use of CC would promote the presence of certain microbial communities in soils and mitigate the potential impact of GBH on these communities. CC can promote biodiversity by increasing plant diversity in fields, while GBH may have non-target effects on species that utilize the shikimate pathway. Crop managements in an experimental field in Southern Québec (Canada) consisted in Glyphosate-based Herbicide (GBH) applications rates at 0.84, 1.67 and 3.33 L ha−1 in corn, soybean and wheat fields cultivated with Direct Seeding along with CC (DSCC) and at 3.33 L ha−1 in similar crops cultivated with direct seeding but without CC (DS). DSCC did not significantly impact microbial richness compared to DS, but did alter specific abundance among prokaryotes and eukaryotes. A permutational multivariate analysis revealed that the type of crop (soybean, wheat, maize) significantly influenced the composition of eukaryotic communities in 2018 and 2019, but not prokaryotic communities. Importantly, the study identifies a cross-effect between CC and GBH application rates suggesting that herbicide use in soybean plots can influence Anaeromyxobacter populations. Also, higher abundance of Enoplea and Maxilopoda were observed in plots with the lower application rate of GBH. Both eukaryotes group are known to be sensitive to crop management. These findings emphasize the need for a holistic approach to agricultural practices, considering the combined effects of both CC and GBH application rates on soil microbial health. Ultimately, the study calls for sustainable agricultural practices that preserve microbial diversity, which is essential for maintaining ecosystem services and soil health. Full article
(This article belongs to the Special Issue Benefits and Challenges of Cover Crops in Agricultural Systems)
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19 pages, 2255 KiB  
Article
Attraction Behavior and Functional Response of Orius insidiosus to Semiochemicals Mediating Rose–Western Flower Thrips Interactions
by Marco A. Díaz, Ericsson Coy-Barrera and Daniel Rodríguez
Agriculture 2025, 15(4), 431; https://doi.org/10.3390/agriculture15040431 - 19 Feb 2025
Viewed by 305
Abstract
The Western Flower Thrips (Frankliniella occidentalis) constitutes a significant threat to rose greenhouses in Colombia. An eco-friendly approach to managing this pest involves using the predatory bug Orius insidiosus. The pest and its predator’s food search and selection mechanisms are [...] Read more.
The Western Flower Thrips (Frankliniella occidentalis) constitutes a significant threat to rose greenhouses in Colombia. An eco-friendly approach to managing this pest involves using the predatory bug Orius insidiosus. The pest and its predator’s food search and selection mechanisms are influenced by ecological interactions mediated by volatile organic compounds (VOCs) emitted during plant–pest interactions. To investigate the role of VOCs in the foraging and host-selection behaviors of O. insidiosus, we conducted functional response assays in greenhouses and olfactometry experiments in laboratory settings. These experiments used flowers from two rose cultivars, with and without female adult thrips, over 24, 48, and 72 h. Functional response analysis revealed a shift in O. insidiosus foraging behavior based on the duration of thrips interaction with rose flowers, transitioning from a Type II to a Type III functional response between 24 and 48 h in the ‘Freedom’ cultivar. The maximum consumption rates increased significantly, from 7.98 individuals at 24 h to 16.18 individuals at 48 h, before slightly decreasing to 14.37 individuals at 72 h. This shift coincided with an increase in O. insidiosus preference for thrips-infested ‘Freedom’ flowers over time, with selection proportions rising from 0.37 at 24 h to 0.46 at 72 h, suggesting a learning effect on prey-searching behavior mediated by VOCs. Olfactometry analyses revealed that O. insidiosus did not respond to the same VOCs that attracted F. occidentalis during flower infestation. However, O. insidiosus responded to certain VOCs likely associated with floral resources such as nectar and pollen, which also attract pollinators and zoophytophagous predators. This observation suggests a potential overlap in the chemical cues used by O. insidiosus for distinct ecological purposes. These findings highlight the complex chemical ecology underlying predator–prey interactions in agroecosystems and underscore the importance of considering VOCs in shaping the foraging behavior of natural enemies and their interactions with insect pests. Full article
(This article belongs to the Special Issue Advances in Biological Pest Control in Agroecosystems)
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25 pages, 8082 KiB  
Article
Development of a Crawler-Type Self-Propelled Machine with Trenching, Fertilizing, and Soil-Covering Components for Hilly Orchard
by Jun Li, Chaodong Mai, Ye Zeng, Zhao Li, Runpeng Jiang, Qinglin Weng, Jiamin Cai, Qian Wang and Can Li
Agriculture 2025, 15(4), 430; https://doi.org/10.3390/agriculture15040430 - 19 Feb 2025
Viewed by 260
Abstract
In response to the issues of high energy consumption, limited functionality, and uneven soil–fertilizer mixing in mechanical operations for trenching and fertilizing in hilly orchards, this study proposes the design of a crawler-type self-propelled machine, integrating three main functions: trenching, fertilizing, and soil [...] Read more.
In response to the issues of high energy consumption, limited functionality, and uneven soil–fertilizer mixing in mechanical operations for trenching and fertilizing in hilly orchards, this study proposes the design of a crawler-type self-propelled machine, integrating three main functions: trenching, fertilizing, and soil covering. The key components of the trenching device, fertilizing device, and soil-covering device were designed. Three fertilizing simulation models (pre-plant, mid-plant, and post-plant) were established using EDEM discrete element software. The soil–fertilizer mixing effects under each mode were analyzed, with results indicating that the post-plant fertilizing mode better meets the soil–fertilizer mixing requirements for deep organic fertilizer application. Using trenching speed, forward speed, and bending angle of the trenching knife as experimental factors, with operating power consumption and soil–fertilizer mixing uniformity as evaluation indicators, a Box–Behnken experiment was conducted to optimize the parameters of the trenching and fertilizing components. A regression model was established to analyze the interaction between experimental factors and indicators. The optimal operational parameter combination was determined as follows: trenching speed of 265.03 r/min, forward speed of 0.40 m/s, and bending angle of trenching knife of 130°. Under these parameters, the trenching power consumption and soil–fertilizer mixing uniformity were 1.74 kW and 77.15%, respectively. Orchard verification tests on the machine showed that under the optimal parameters, the relative errors in trenching power consumption and soil–fertilizer mixing uniformity between the field tests and simulations were 7.40% and 4.50%, respectively. These results meet the agronomic requirements for trenching and fertilizing, and the study provides valuable references for the application of related technologies in orchard trenching and fertilizing operations. Full article
(This article belongs to the Special Issue Feature Papers in Agriculture Technology—Using Computer Simulation for Agricultural Machinery Design and Development)
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19 pages, 3539 KiB  
Article
Optimizing Straw and Manure Co-Substitution Regimes to Maintain Stable Crop Yields Through Enhanced Soil Stoichiometric Balance
by Peipei Li, Yuanyi Shang, Hui Li, Fang Li, Yi Wang, Xueqiang Zhu, Shiying Li, Xiaolin Wang and Yanlai Han
Agriculture 2025, 15(4), 429; https://doi.org/10.3390/agriculture15040429 - 18 Feb 2025
Viewed by 290
Abstract
The benefits of partially substituting inorganic fertilizers with organic fertilizers have been extensively acknowledged. However, the key mechanisms behind nutrient transformation and supply for stable crop yields are still not fully understood. Based on an 11-year field experiment with a wheat–maize rotation system, [...] Read more.
The benefits of partially substituting inorganic fertilizers with organic fertilizers have been extensively acknowledged. However, the key mechanisms behind nutrient transformation and supply for stable crop yields are still not fully understood. Based on an 11-year field experiment with a wheat–maize rotation system, this study explored the advantages of combined straw and manure substitution under various organic substitution regimes. These regimes included an unfertilized control (CK), inorganic nitrogen, phosphorus, and potassium fertilizers (NPK), NPK substituted with straw (NPKS), NPK substituted with manure (NPKM), and NPK substituted with both straw and manure (NPKSM). Compared to NPK and NPKS, NPKM and NPKSM significantly improved wheat yield by 12.8% and 13.8%, respectively. Bulk soil organic carbon (SOC), total nitrogen (TN), available superphosphate (AP), β-glucosidase (βG), urease (URE), and alkaline phosphatase (ALP) were all higher in the NPKM treatment than in the NPKSM treatment. However, compared to NPKM, NPKSM significantly decreased the potential nitrification rate by 31.0% and increased the soil NH4+-N content. Correspondingly, the functional genes of nitrification were also found to be decreased in the NPKSM treatment. In the rhizosphere, most soil factors increased compared to bulk soil, but treatment differences were smaller. However, the differences among treatments were reduced in the rhizosphere. The high amount of manure applied in the NPKM treatment caused excessive soil phosphorus accumulation, reaching over 46.7 mg/kg, resulting in lower N/P and C/P ratios. The soil quality index (SQI), based on soil nutrients, enzymes, functional genes, and C:N:P stoichiometry, was 9.9% higher in NPKSM than in NPKM. Bulk soil SQIs showed stronger correlations with wheat yields than rhizosphere SQIs, highlighting that bulk soil was superior to rhizosphere in predicting crop yield. Partial least squares path modeling showed that C/N, N/P, and C/P ratios strongly influenced SQIs. The NPKSM treatment, which improved soil nutrients, biological factors, and balanced C:N:P stoichiometry, is an effective strategy for sustainable agriculture. Future practices should focus on maintaining stoichiometric balance to sustain soil quality and crop yields. Full article
(This article belongs to the Section Agricultural Soils)
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21 pages, 16087 KiB  
Article
Design and Experiments of Automatic Seedling Separation Device for Vegetable Substrate Block Seedling Transplanter
by Shuhe Zheng, Jicheng Li, Zhenfa Dong, Jufei Wang, Wuxiong Weng, Zhichao Cui, Can Wang and Xinhui Wu
Agriculture 2025, 15(4), 428; https://doi.org/10.3390/agriculture15040428 - 18 Feb 2025
Viewed by 289
Abstract
To address the critical challenges of low success rates and high seedling damage in automatic transplanters for vegetable substrate block seedlings, this study took cabbage substrate block seedlings as the research object and designed a silica gel wheel–synchronous belt clamping seedling separation device. [...] Read more.
To address the critical challenges of low success rates and high seedling damage in automatic transplanters for vegetable substrate block seedlings, this study took cabbage substrate block seedlings as the research object and designed a silica gel wheel–synchronous belt clamping seedling separation device. An experimental platform was constructed to perform a three-factor, three-level orthogonal test, investigating the effects of the wheelbase of the silica gel wheel, the inclination angle of the conveyor belt, and the wheelbase of the silica gel wheel and the synchronous belt on seedling separation success rate and substrate block breakage rate. A quadratic regression model was established to analyze the influence of each factor on the index and to optimize the parameter combination verification test. The results showed that the seedling separation effect was better when the wheelbase of the silica gel wheel was 60.47 mm, the inclination angle of the conveyor belt was 8.67°, and the wheelbase of the silica gel wheel and seedling separation synchronous belt was 39.8 mm. The success rate of seedling separation was 90.21% and the substrate block breakage rate was 6.88% in the field verification test of this parameter combination. When the operating speed is 60 plants/min, there is a higher success rate of seedling separation and a lower substrate block breakage rate. This study explored the conditions for stable seedling separation using the seedling separation device, and provided practical reference for the study of the automatic seedling separation of substrate block seedlings. Full article
(This article belongs to the Section Agricultural Technology)
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18 pages, 5579 KiB  
Article
Bio-Adsorbents Derived from Allium cepa var. aggregatum Waste for Effective Cd Removal and Immobilization in Black Soil
by Yaru Hou, Jilong Lu, Yawen Lai, Qiaoqiao Wei, Zhiyi Gou and Xiaoxiao Zou
Agriculture 2025, 15(4), 427; https://doi.org/10.3390/agriculture15040427 - 18 Feb 2025
Viewed by 243
Abstract
The black soil in northeast China plays an important role in coping with global climate change. However, long-term predatory production methods and the excessive application of pesticides and fertilizers to respond to the growing demand resulted in a severe contamination of the black [...] Read more.
The black soil in northeast China plays an important role in coping with global climate change. However, long-term predatory production methods and the excessive application of pesticides and fertilizers to respond to the growing demand resulted in a severe contamination of the black soil with Cd, leading to a decrease in the properties of black soil. In this study, we propose the preparation of bio-adsorbents including a natural bio-adsorbent (AW), a modified bio-adsorbent (AM), biochar cracking at 300, 500, and 700 °C (C300, C500, C700), modified biochar (CM), and a magnetic bio-adsorbent particle (MBP) using the waste of black soil autotrophic specialty crop multiplier onion (Allium cepa var. aggregatum) to investigate the adsorption and immobilization of Cd in contaminated soil. The results show that the application of bio-adsorbents resulted in a 17.29–35.67% and 18.24–30.76% decrease in effective and total Cd content in soil after dry–wet–freeze circulation. Exchangeable Cd in soil decreased and gradually transformed to more stable fractions, with a reduction in Cd bioavailability after remediation. Interestingly, an increase in plant uptake of Cd was observed in the biochar-treated group for a short period, causing a 93.72% increase in Cd concentration in plants after the application of C700, which can be applied concomitantly with hyperaccumulator plants harvested multiple times annually by encouraging higher Cd uptake by plants. Additionally, the rich content of humic acid (HA) in black soil was capable of promoting the immobilization of Cd in soil, enhancing the Cd resistance of black soil. Bio-adsorbents derived from Allium cepa var. aggregatum waste can be applied as a new type of green and effective material for the long-term remediation of Cd in the soil at a lower cost. Full article
(This article belongs to the Special Issue Soil Contamination and the Strategies to Reduce Pollutant Accumulation in Crops)
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19 pages, 8113 KiB  
Article
Microbial Inoculation Is Crucial for Endocarp Opening of Panax ginseng Seeds in Warm Indoor Stratification
by Haenghoon Kim
Agriculture 2025, 15(4), 426; https://doi.org/10.3390/agriculture15040426 - 18 Feb 2025
Viewed by 267
Abstract
Panax ginseng Meyer is one of the most popular traditional medicinal plants in Korea. Since ginseng seeds are morpho-physiologically dormant and have a very short lifespan, the harvested seeds need outdoor warm and cold stratification for 100 days each. The seeds were covered [...] Read more.
Panax ginseng Meyer is one of the most popular traditional medicinal plants in Korea. Since ginseng seeds are morpho-physiologically dormant and have a very short lifespan, the harvested seeds need outdoor warm and cold stratification for 100 days each. The seeds were covered by a fruit coat (endocarp), which opened during warm stratification. Farmers must, therefore, dehisce (open the endocarp) seeds annually. The conditions for embryo growth, dehiscence percentage, and endocarp hardness were temperature, watering, stratification substances, solution scarification, and microbial inoculation of the seed endocarp. Watering, temperature (17.5 °C), and aeration are crucial for embryo growth as a germination condition. Moreover, microbial-mediated endocarp decomposition is necessary for dehiscence and embryonic development. This study suggests that a combination of embryo growth and microbial-mediated decomposition of the endocarp during warm stratification is a prerequisite for the dehiscence of ginseng seeds, implying physical and morpho-physiological dormancy. Any microbes (fungi, actinomycetes, and bacteria) tested with high or low cellulose-decomposing ability increased the dehiscence percentage by 66% compared to the untreated control. Seeds of three varieties of P. ginseng and one variety of P. quinquefolius were successfully dehisced by fungal inoculation of seeds. This approach opens the door for year-round indoor dehiscence of ginseng seeds without substrates, such as sand. Full article
(This article belongs to the Section Seed Science and Technology)
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22 pages, 2335 KiB  
Article
Contribution of Acid Additive to Co-Composting of Chicken Manure: Gas Emission Reduction and Economic Assessment
by Wentao Xue, Mao Li, Ling Zhang, Qinping Sun, Shanjiang Liu, Hao Sun, Rong Wu, Guoyuan Zou and Na Duan
Agriculture 2025, 15(4), 425; https://doi.org/10.3390/agriculture15040425 - 18 Feb 2025
Viewed by 261
Abstract
Acidic additives have garnered significant attention due to their ability to reduce ammonia (NH3) emissions, enhance nitrogen retention, and balance function with cost-effectiveness. This study aimed to investigate the potential of oxalic acid (OA) in reducing gas emissions, promoting compost humification, [...] Read more.
Acidic additives have garnered significant attention due to their ability to reduce ammonia (NH3) emissions, enhance nitrogen retention, and balance function with cost-effectiveness. This study aimed to investigate the potential of oxalic acid (OA) in reducing gas emissions, promoting compost humification, and enhancing nutrient retention during the co-composting of chicken manure. Moreover, the comparative analysis of the effects and the economic benefits was conducted among OA groups with varying concentrations (OA1: 0.03 mol·kg−1, OA2: 0.10 mol·kg−1, and OA3: 0.15 mol·kg−1) and a sulfuric acid (SA) group (SA1: 0.03 mol·kg−1). The results indicated that the addition of OA can extend the thermophilic phase to some extent and achieve the required composting maturity. As the amount of OA increased, the NH3 emissions (p < 0.05) and the total nitrogen loss rate was decreased; however, this also increased the cost. No significant difference in the total nitrogen loss rate was observed between SA1 and OA1 (p < 0.05). It is worth noting that the addition of SA increased the SO42− content, leading to an increase of 113.52% in H2S emissions. In contrast, the addition of OA resulted in a reduction in H2S emissions by 29.92–45.90%. In terms of economic analysis, OA1 was the most effective (OA1 > OA2 > OA3 > SA1). Thereby, OA was proved to be a good alternative for SA in the co-composting of chicken manure, and 0.03 mol·kg−1 OA is recommended. Full article
(This article belongs to the Section Farm Animal Production)
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24 pages, 8271 KiB  
Article
Research on a Potato Leaf Disease Diagnosis System Based on Deep Learning
by Chunhui Zhang, Shuai Wang, Chunguang Wang, Haichao Wang, Yingjie Du and Zheying Zong
Agriculture 2025, 15(4), 424; https://doi.org/10.3390/agriculture15040424 - 18 Feb 2025
Viewed by 420
Abstract
Potato is the fourth largest food crop in the world. Disease is an important factor restricting potato yield. Disease detection based on deep learning has strong advantages in network structure, training speed, detection accuracy, and other aspects. This article took potato leaf diseases [...] Read more.
Potato is the fourth largest food crop in the world. Disease is an important factor restricting potato yield. Disease detection based on deep learning has strong advantages in network structure, training speed, detection accuracy, and other aspects. This article took potato leaf diseases (early blight and viral disease) as the research objects, collected disease images to construct a disease dataset, and expanded the dataset through data augmentation methods to improve the quantity and diversity of the dataset. Four classic deep learning networks (VGG16, MobilenetV1, Resnet50, and Vit) were used to train the dataset, and the VGG16 network had the highest accuracy of 97.26%; VGG16 was chosen as the basic research network. A new, improved algorithm, VGG16S, was proposed to solve the problem of large network parameters by using three improvement methods: changing the network structure of the VGG16 network from “convolutional layer + flattening layer + fully connected layer” to “convolutional layer + global average pooling”, integrating CBAM attention mechanism, and introducing Leaky ReLU activation function for learning and training. The improved VGG16S network has a parameter size of 15 M (1/10 of VGG16), and the recognition accuracy of the test set is 97.87%. This article used response surface analysis to optimize hyperparameters, and the test results indicated that VGG16S, after hyperparameter tuning, had further improved its diagnostic performance. At last, this article completed ablation experiments and public dataset testing. The research results will provide a theoretical basis for the timely adoption of corresponding prevention and control measures, improving the yield and quality of potatoes and increasing economic benefits. Full article
(This article belongs to the Section Digital Agriculture)
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24 pages, 16942 KiB  
Article
Optimal Drought Index Selection for Soil Moisture Monitoring at Multiple Depths in China’s Agricultural Regions
by Peiwen Yao, Hong Fan and Qilong Wu
Agriculture 2025, 15(4), 423; https://doi.org/10.3390/agriculture15040423 - 17 Feb 2025
Viewed by 324
Abstract
Droughts are a major driver of global environmental degradation, threatening lives and causing significant economic losses, with approximately 80% of these losses linked to agricultural drought, characterized by soil moisture deficits. Remote sensing technology offers high spatiotemporal resolution data for continuous monitoring of [...] Read more.
Droughts are a major driver of global environmental degradation, threatening lives and causing significant economic losses, with approximately 80% of these losses linked to agricultural drought, characterized by soil moisture deficits. Remote sensing technology offers high spatiotemporal resolution data for continuous monitoring of soil moisture and drought severity. However, the effectiveness of remote sensing drought indices across different soil depths remains unclear. This study assessed the performance of eight widely used drought indices—Perpendicular Drought Index (PDI), Modified Perpendicular Drought Index (MPDI), Temperature Condition Index (TCI), Vegetation Condition Index (VCI), Vegetation Health Index (VHI), Normalized Vegetation Supply Water Index (NVSWI), Temperature–Vegetation Dryness Index (TVDI), and Standardized Precipitation–Evapotranspiration Index (SPEI) at multiple timescales—in monitoring soil moisture at five depths (0–50 cm, at 10 cm intervals) across nine agricultural regions of China from 2001 to 2020. Results reveal that the monitoring performance of drought indices varies significantly across regions and soil depths, with a general decline in performance as soil depth increases. For soil depths between 10–40 cm, VCI and NVSWI exhibited the highest accuracy, while PDI, MPDI, and VHI performed optimally in the Northeast China Plain. At 50 cm depth, however, optical remote sensing indices struggled to accurately capture soil moisture conditions. Additionally, TCI and TVDI showed notable lag effects, with 4-month and 5-month delays, respectively, while SPEI exhibited cumulative effects over 3–6 months. These findings provide critical insights to guide the selection of appropriate drought indices for soil moisture monitoring, aiding agricultural drought management and decision-making. Full article
(This article belongs to the Section Agricultural Soils)
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20 pages, 13304 KiB  
Article
Discrete Element Method Analysis of Soil Penetration Depth Affected by Spreading Speed in Drone-Seeded Rice
by Kwon Joong Son
Agriculture 2025, 15(4), 422; https://doi.org/10.3390/agriculture15040422 - 17 Feb 2025
Viewed by 312
Abstract
This research explores, using discrete element method (DEM) simulations, the behavior of rice seed infiltration into soil when it is deployed via unmanned aerial vehicle (UAV)-mounted systems. Five distinct sowing strategies were analyzed to evaluate their effectiveness in embedding seeds within paddy soil: [...] Read more.
This research explores, using discrete element method (DEM) simulations, the behavior of rice seed infiltration into soil when it is deployed via unmanned aerial vehicle (UAV)-mounted systems. Five distinct sowing strategies were analyzed to evaluate their effectiveness in embedding seeds within paddy soil: gravitational drop, centrifugal spreading, airflow propulsion, pneumatic discharge, and pneumatic shooting. A two-step analysis was performed. Initially, the flight dynamics of rice seeds were modeled, and the influence of air and water drag forces were accounted for. Subsequently, soil penetration was simulated with DEM based on the material properties and contact parameters sourced from the existing literature. The results show that the pneumatic methods effectively penetrated the soil, with pneumatic shooting proving to be the most efficient due to its superior impact momentum. Conversely, the methods that failed to penetrate left seeds on the soil surface. These findings demonstrate the necessity to enhance UAV sowing technology to improve penetration depth while maintaining operational efficiency, and they also offer crucial insights for the progress of UAV applications in agriculture. Full article
(This article belongs to the Section Agricultural Technology)
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21 pages, 4676 KiB  
Article
LCDDN-YOLO: Lightweight Cotton Disease Detection in Natural Environment, Based on Improved YOLOv8
by Haoran Feng, Xiqu Chen and Zhaoyan Duan
Agriculture 2025, 15(4), 421; https://doi.org/10.3390/agriculture15040421 - 17 Feb 2025
Viewed by 307
Abstract
To address the challenges of detecting cotton pests and diseases in natural environments, as well as the similarities in the features exhibited by cotton pests and diseases, a Lightweight Cotton Disease Detection in Natural Environment (LCDDN-YOLO) algorithm is proposed. The LCDDN-YOLO algorithm is [...] Read more.
To address the challenges of detecting cotton pests and diseases in natural environments, as well as the similarities in the features exhibited by cotton pests and diseases, a Lightweight Cotton Disease Detection in Natural Environment (LCDDN-YOLO) algorithm is proposed. The LCDDN-YOLO algorithm is based on YOLOv8n, and replaces part of the convolutional layers in the backbone network with Distributed Shift Convolution (DSConv). The BiFPN network is incorporated into the original architecture, adding learnable weights to evaluate the significance of various input features, thereby enhancing detection accuracy. Furthermore, it integrates Partial Convolution (PConv) and Distributed Shift Convolution (DSConv) into the C2f module, called PDS-C2f. Additionally, the CBAM attention mechanism is incorporated into the neck network to improve model performance. A Focal-EIoU loss function is also integrated to optimize the model’s training process. Experimental results show that compared to YOLOv8, the LCDDN-YOLO model reduces the number of parameters by 12.9% and the floating-point operations (FLOPs) by 9.9%, while precision, mAP@50, and recall improve by 4.6%, 6.5%, and 7.8%, respectively, reaching 89.5%, 85.4%, and 80.2%. In summary, the LCDDN-YOLO model offers excellent detection accuracy and speed, making it effective for pest and disease control in cotton fields, particularly in lightweight computing scenarios. Full article
(This article belongs to the Section Digital Agriculture)
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23 pages, 4913 KiB  
Article
Sweet Potato Yield Prediction Using Machine Learning Based on Multispectral Images Acquired from a Small Unmanned Aerial Vehicle
by Kriti Singh, Yanbo Huang, Wyatt Young, Lorin Harvey, Mark Hall, Xin Zhang, Edgar Lobaton, Johnie Jenkins and Mark Shankle
Agriculture 2025, 15(4), 420; https://doi.org/10.3390/agriculture15040420 - 17 Feb 2025
Viewed by 382
Abstract
Accurate prediction of sweet potato yield is crucial for effective crop management. This study investigates the use of vegetation indices (VIs) extracted from multispectral images acquired by a small unmanned aerial vehicle (UAV) throughout the growing season, along with in situ-measured plant physiological [...] Read more.
Accurate prediction of sweet potato yield is crucial for effective crop management. This study investigates the use of vegetation indices (VIs) extracted from multispectral images acquired by a small unmanned aerial vehicle (UAV) throughout the growing season, along with in situ-measured plant physiological parameters, to predict sweet potato yield. The data acquisition process through UAV field imaging is discussed in detail along with the extraction process for the multispectral bands that we use as features. The experiment is designed with a combination of different nitrogen application rates and cover crop treatments. The dependence of VIs and crop physiological parameters, such as leaf chlorophyll content, plant biomass, vine length, and leaf nitrogen content, on yield is evaluated through feature selection methods and model performance. Classical machine learning (ML) approaches and tree-based algorithms, like XGBoost and Random Forest, are implemented. Additionally, a soft-voting ML model ensemble approach is employed to improve performance of yield prediction. Individual models are trained and tested for different cover crop and nitrogen treatments to capture the relationships between the treatments and the target yield variable. The performance of the ML algorithms is evaluated using various popular model performance metrics like R2, RMSE, and MAE. Through modelling the data for cover crops and nitrogen treatment rates using individual models, the relationships and effects of different treatments on yield are explored. Important VIs useful for the study are identified through feature selection and model performance evaluation. Full article
(This article belongs to the Section Digital Agriculture)
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15 pages, 2517 KiB  
Article
Effects of Chlorella vulgaris at Different Growth Stages and Concentrations on the Growth of Pelargonium × hortorum
by Alejandro Rápalo-Cruz, Cintia Gomez-Serrano, Cynthia Victoria Gonzalez-Lopez, Mohammad Bagher Hassanpouraghdam, Asghar Ebrahimzadeh and Silvia Jimenez-Becker
Agriculture 2025, 15(4), 419; https://doi.org/10.3390/agriculture15040419 - 17 Feb 2025
Viewed by 266
Abstract
Microalgae are gaining attention as a sustainable and efficient alternative in modern agriculture due to their biostimulant and biofertilizer effects, which promote plant growth and improve plant resistance to abiotic stress factors. Their effectiveness vary according to factors such as concentration and growth [...] Read more.
Microalgae are gaining attention as a sustainable and efficient alternative in modern agriculture due to their biostimulant and biofertilizer effects, which promote plant growth and improve plant resistance to abiotic stress factors. Their effectiveness vary according to factors such as concentration and growth stage. This study evaluates the potential of Chlorella vulgaris (C. vulgaris) to stimulate various plant parameters, including growth, biomass, leaf development, and flowering. The trial was carried out in a greenhouse, using Pelargonium × hortorum plants grown on coconut fiber substrate. A nested factorial design was applied, with treatments including a control (irrigation water only) and four experimental groups with microalgae applied at concentrations of 0.1 g L−1 and 1 g L−1, harvested in the stationary or exponential growth phases. The experiment was repeated in autumn and spring to assess seasonal effects. Variables such as plant height, diameter, number of leaves and flowers, as well as the fresh and dry weight of the different plant organs were measured. In addition, leaf area was determined. The results indicate that higher application rates (1 g L−1) increased nitrate, phosphate, and potassium levels, highlighting the role of C. vulgaris in improving plant nutrition. The application of C. vulgaris at 1 g L−1, especially in the stationary growth phase, promoted growth and advanced flowering in Pelargonium × hortorum. In conclusion, C. vulgaris shows significant potential as an agricultural biofertilizer, promoting the growth of Pelargonium × hortorum. Full article
(This article belongs to the Section Crop Production)
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19 pages, 11226 KiB  
Article
Evaluation of Weed Infestations in Row Crops Using Aerial RGB Imaging and Deep Learning
by Plamena D. Nikolova, Boris I. Evstatiev, Atanas Z. Atanasov and Asparuh I. Atanasov
Agriculture 2025, 15(4), 418; https://doi.org/10.3390/agriculture15040418 - 16 Feb 2025
Viewed by 483
Abstract
One of the important factors negatively affecting the yield of row crops is weed infestations. Using non-contact detection methods allows for a rapid assessment of weed infestations’ extent and management decisions for practical weed control. This study aims to develop and demonstrate a [...] Read more.
One of the important factors negatively affecting the yield of row crops is weed infestations. Using non-contact detection methods allows for a rapid assessment of weed infestations’ extent and management decisions for practical weed control. This study aims to develop and demonstrate a methodology for early detection and evaluation of weed infestations in maize using UAV-based RGB imaging and pixel-based deep learning classification. An experimental study was conducted to determine the extent of weed infestations on two tillage technologies, plowing and subsoiling, tailored to the specific soil and climatic conditions of Southern Dobrudja. Based on an experimental study with the DeepLabV3 classification algorithm, it was found that the ResNet-34-backed model ensures the highest performance compared to different versions of ResNet, DenseNet, and VGG backbones. The achieved performance reached precision, recall, F1 score, and Kappa, respectively, 0.986, 0.986, 0.986, and 0.957. After applying the model in the field with the investigated tillage technologies, it was found that a higher level of weed infestation is observed in subsoil deepening areas, where 4.6% of the area is infested, compared to 0.97% with the plowing treatment. This work contributes novel insights into weed management during the critical early growth stages of maize, providing a robust framework for optimizing weed control strategies in this region. Full article
(This article belongs to the Section Digital Agriculture)
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29 pages, 578 KiB  
Article
Evaluating the Impact of EU Expenditures Under Agricultural Priorities on Energy Sustainability in CEE Countries
by Nicoleta Mihaela Doran, Gabriela Badareu, Marius Dalian Doran, Mihai Alexandru Firu and Anamaria Liliana Staicu
Agriculture 2025, 15(4), 417; https://doi.org/10.3390/agriculture15040417 - 16 Feb 2025
Viewed by 397
Abstract
This study examines the impact of EU agricultural expenditures on renewable energy production and energy efficiency in the agricultural sector across nine Central and Eastern European (CEE) countries over the period 2015–2022. The analysis is based on a panel dataset compiled from European [...] Read more.
This study examines the impact of EU agricultural expenditures on renewable energy production and energy efficiency in the agricultural sector across nine Central and Eastern European (CEE) countries over the period 2015–2022. The analysis is based on a panel dataset compiled from European Commission databases, incorporating annual expenditures under five Common Agricultural Policy (CAP) priorities, as well as indicators of renewable energy production and direct energy consumption in agriculture and forestry. Using panel regression models, the study assesses how different CAP funding priorities influence energy sustainability outcomes. The findings indicate that certain funding priorities significantly contribute to renewable energy adoption, while others have a limited effect, emphasizing the need for a more targeted policy approach. The results also highlight regional disparities in the effectiveness of CAP funding, suggesting that farm structure, institutional capacity, and climate conditions mediate the impact of EU expenditures on energy sustainability. These insights contribute to the ongoing discourse on optimizing EU funding mechanisms to support a sustainable agricultural transition in the CEE region. Full article
(This article belongs to the Section Agricultural Economics, Policies and Rural Management)
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22 pages, 6281 KiB  
Article
Integrated Evaluation of Sustainability and Quality of Italian Tomato Cultivars Grown Under Irrigated and Non-Irrigated Systems
by Giuliana Vinci, Paola Campana, Laura Gobbi, Sabrina Antonia Prencipe and Marco Ruggeri
Agriculture 2025, 15(4), 416; https://doi.org/10.3390/agriculture15040416 - 16 Feb 2025
Viewed by 556
Abstract
This research aimed to assess how irrigation can affect the sustainability and quality of two Italian tomato cultivars: the “Riccio di Parma Casertano,” which is grown without irrigation, and the “Piennolo del Vesuvio DOP,” which requires irrigation. Life cycle assessment and water footprint [...] Read more.
This research aimed to assess how irrigation can affect the sustainability and quality of two Italian tomato cultivars: the “Riccio di Parma Casertano,” which is grown without irrigation, and the “Piennolo del Vesuvio DOP,” which requires irrigation. Life cycle assessment and water footprint analysis were used for sustainability assessment, while, for quality assessment, the content of bioactive compounds was analyzed by UV-Vis spectrophotometric assays. The results indicate that ‘Riccio di Parma Casertano’ is a more sustainable cultivar than ‘Piennolo del Vesuvio DOP’, with lower environmental impacts in all 18 impact categories, showing reductions ranging from 54.55% to 99.90%. This higher sustainability performance of “Riccio di Parma Casertano” is also characterized by increases of +32% in total polyphenol content and +43% in total flavonoid content as an adaptive response to water stress compared with “Piennolo del Vesuvio DOP”. However, “Piennolo del Vesuvio DOP” has a higher yield and better overall nutritional and functional quality, with higher concentrations of hydrophilic and lipophilic compounds, such as lycopene and β-carotene, due to irrigation. The results, therefore, show how the choice between the two cultivars might depend on a trade-off between sustainability and quality. In particular, ’Riccio di Parma Casertano’ could excel in contexts with low water availability while maintaining a good nutritional profile due to the synthesis of bioactive compounds; on the other hand, “Piennolo del Vesuvio DOP” could offer higher yield and nutritional qualities, although it needs improved agricultural practices to reduce overall environmental impacts. Full article
(This article belongs to the Section Crop Production)
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15 pages, 9000 KiB  
Article
A Neural Network with Multiscale Convolution and Feature Attention Based on an Electronic Nose for Rapid Detection of Common Bunt Disease in Wheat Plants
by Zhizhou Ren, Kun Liang, Yihe Liu, Xiaoxiao Wu, Chi Zhang, Xiuming Mei and Yi Zhang
Agriculture 2025, 15(4), 415; https://doi.org/10.3390/agriculture15040415 - 16 Feb 2025
Viewed by 318
Abstract
Common bunt disease in wheat is a serious threat to crops and food security. Rapid assessments of its severity are essential for effective management. The electronic nose (e-nose) system is used to capture volatile organic compounds (VOCs), particularly trimethylamine (TMA), which serves as [...] Read more.
Common bunt disease in wheat is a serious threat to crops and food security. Rapid assessments of its severity are essential for effective management. The electronic nose (e-nose) system is used to capture volatile organic compounds (VOCs), particularly trimethylamine (TMA), which serves as a key marker of common bunt disease in wheat. In this paper, the GFNN (gas feature neural network) model is proposed for detecting VOCs from the e-nose system, providing a lightweight and efficient approach for assessing disease severity. Multiscale convolution is employed to extract both global and local features from gas data, and three attention mechanisms are used to focus on important features. GFNN achieves 98.76% accuracy, 98.79% precision, 98.77% recall, and an F1-score of 98.75%, with only 0.04 million parameters and 0.42 million floating-point operations per second (FLOPS). Compared to traditional and current deep learning models, GFNN demonstrates superior performance, particularly in small-sample-size scenarios. It significantly improves the deep learning performance of the model in extracting key gas features. This study offers a practical, rapid, and cost-effective method for monitoring and managing common bunt disease in wheat, enhancing crop protection and food security. Full article
(This article belongs to the Special Issue Agricultural Products Processing and Quality Detection)
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12 pages, 757 KiB  
Article
Streamlining the Identification of the Orange Spiny Whitefly, Aleurocanthus spiniferus (Hemiptera: Aleyrodidae), with Real-Time PCR Probe Technology
by Domenico Rizzo, Claudia Gabriela Zubieta, Michela Moriconi, Marco Carli, Andrea Marrucci, Chiara Ranaldi, Bruno Palmigiano, Linda Bartolini, Feliciana Pica, Carmela Carbone, Giuseppe Eros Massimino Cocuzza and Francesco Nugnes
Agriculture 2025, 15(4), 414; https://doi.org/10.3390/agriculture15040414 - 16 Feb 2025
Viewed by 327
Abstract
Aleurocanthus spiniferus (Quaintance) (Hemiptera: Aleyrodidae) has rapidly spread, mainly in the central and eastern Mediterranean coastal area, infesting various new host plants alongside known ones. This invasive species poses a significant threat to agricultural ecosystems, necessitating urgent action to monitor and control outbreaks [...] Read more.
Aleurocanthus spiniferus (Quaintance) (Hemiptera: Aleyrodidae) has rapidly spread, mainly in the central and eastern Mediterranean coastal area, infesting various new host plants alongside known ones. This invasive species poses a significant threat to agricultural ecosystems, necessitating urgent action to monitor and control outbreaks in previously pest-free areas. While entomological and morphological recognitions are crucial for initial detection, challenges often arise in quickly identifying different developmental stages or genus-level distinctions, particularly in surveys conducted by personnel with limited entomological skills. Due to these challenges, a qPCR probe protocol was developed to enhance the diagnostic capacity of laboratories responsible for the territorial control of pests. This biomolecular tool integrates morphological surveys, enabling prompt and reliable proof of A. spiniferus presence in free areas, delimited territories, or during phytosanitary import inspections. The protocol’s high analytical specificity, inclusivity, and exclusivity ensure accurate identification of A. spiniferus, while its low limit of detection and high repeatability and reproducibility reinforce its utility as a standardized diagnostic method. By facilitating prompt and targeted control efforts, this innovative approach strengthens the resilience of agricultural systems against the widespread threat of A. spiniferus infestations. Full article
(This article belongs to the Special Issue Sustainable Cutting-Edge Solutions for Pest Management)
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16 pages, 7077 KiB  
Article
A Variable-Threshold Segmentation Method for Rice Row Detection Considering Robot Travelling Prior Information
by Jing He, Wenhao Dong, Qingneng Tan, Jianing Li, Xianwen Song and Runmao Zhao
Agriculture 2025, 15(4), 413; https://doi.org/10.3390/agriculture15040413 - 15 Feb 2025
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Abstract
Accurate rice row detection is critical for autonomous agricultural machinery navigation in complex paddy environments. Existing methods struggle with terrain unevenness, water reflections, and weed interference. This study aimed to develop a robust rice row detection method by integrating multi-sensor data and leveraging [...] Read more.
Accurate rice row detection is critical for autonomous agricultural machinery navigation in complex paddy environments. Existing methods struggle with terrain unevenness, water reflections, and weed interference. This study aimed to develop a robust rice row detection method by integrating multi-sensor data and leveraging robot travelling prior information. A 3D point cloud acquisition system combining 2D LiDAR, AHRS, and RTK-GNSS was designed. A variable-threshold segmentation method, dynamically adjusted based on real-time posture perception, was proposed to handle terrain variations. Additionally, a clustering algorithm incorporating rice row spacing and robot path constraints was developed to filter noise and classify seedlings. Experiments in dryland with simulated seedlings and real paddy fields demonstrated high accuracy: maximum absolute errors of 59.41 mm (dryland) and 69.36 mm (paddy), with standard deviations of 14.79 mm and 19.18 mm, respectively. The method achieved a 0.6489° mean angular error, outperforming existing algorithms. The fusion of posture-aware thresholding and path-based clustering effectively addresses the challenges in complex rice fields. This work enhances the automation of field management, offering a reliable solution for precision agriculture in unstructured environments. Its technical framework can be adapted to other row crop systems, promoting sustainable mechanization in global rice production. Full article
(This article belongs to the Section Digital Agriculture)
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