Agriculture

14 pages, 1185 KB

Open AccessArticle

Significance of Temperature-Rearing Conditions for Shaping the Responses of the Aphid Parasitoid, Aphidius platensis, Under Thermal Stress

by Francisca Zepeda-Paulo, Blas Lavandero, Cinthya Villegas and Mariana Véliz

Agriculture 2025, 15(19), 2014; https://doi.org/10.3390/agriculture15192014 (registering DOI) - 26 Sep 2025

Abstract

A key aspect of climate change’s impact on organisms lies in understanding their ability to adapt to shifting and stressful environmental conditions. Insects, such as parasitoid wasps, are particularly vulnerable due to limited heat tolerance. Adaptive strategies during mass rearing may enhance the [...] Read more.

A key aspect of climate change’s impact on organisms lies in understanding their ability to adapt to shifting and stressful environmental conditions. Insects, such as parasitoid wasps, are particularly vulnerable due to limited heat tolerance. Adaptive strategies during mass rearing may enhance the efficacy and resilience of commercially reared biocontrol agents. This study assessed the effects of constant and fluctuating temperature regimens across four generations of mass-reared aphid parasitoids, examining their fitness traits and parasitism success under three thermal environments: colder [10 °C], standard [20 °C], and heat stress [28 °C]. Parasitoids reared under fluctuating temperatures [day/night: 25 °C/17 °C] showed increased parasitism, but reduced progeny survival compared to those reared at a constant temperature [20 °C]. Fluctuating regimens encouraged greater parasitism under heat stress, whereas constant regimens yielded intermediate parasitism across thermal environments, reflecting a pattern consistent with the evolution of specialist–generalist trade-offs. These findings underscore the value of developing adaptive temperature-rearing strategies for mass-rearing systems of parasitoids that more accurately simulate field conditions, improving their performance under climate stress. Future research involving diverse temperature regimens should deepen our understanding of trait trade-offs, such as survival and fecundity, and aid in identifying optimal thermal profiles to maximize efficacy in mass-rearing parasitoid wasps and their performance at the field level. Full article

(This article belongs to the Special Issue Application of Natural Enemies and Parasitoids in Agricultural Pest Biocontrol)

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18 pages, 12212 KB

Open AccessArticle

YOLO-MSPM: A Precise and Lightweight Cotton Verticillium Wilt Detection Network

by Xinbo Zhao, Jianan Chi, Fei Wang, Xuan Li, Xingcan Yuwen, Tong Li, Yi Shi and Liujun Xiao

Agriculture 2025, 15(19), 2013; https://doi.org/10.3390/agriculture15192013 - 26 Sep 2025

Abstract

Cotton is one of the world’s most important economic crops, and its yield and quality have a significant impact on the agricultural economy. However, Verticillium wilt of cotton, as a widely spread disease, severely affects the growth and yield of cotton. Due to [...] Read more.

Cotton is one of the world’s most important economic crops, and its yield and quality have a significant impact on the agricultural economy. However, Verticillium wilt of cotton, as a widely spread disease, severely affects the growth and yield of cotton. Due to the typically small and densely distributed characteristics of this disease, its identification poses considerable challenges. In this study, we introduce YOLO-MSPM, a lightweight and accurate detection framework, designed on the YOLOv11 architecture to efficiently identify cotton Verticillium wilt. In order to achieve a lightweight model, MobileNetV4 is introduced into the backbone network. Moreover, a single-head self-attention (SHSA) mechanism is integrated into the C2PSA block, allowing the network to emphasize critical areas of the feature maps and thus enhance its ability to represent features effectively. Furthermore, the PC3k2 module combines pinwheel-shaped convolution (PConv) with C3k2, and the mobile inverted bottleneck convolution (MBConv) module is incorporated into the detection head of YOLOv11. Such adjustments improve multi-scale information integration, enhance small-target recognition, and effectively reduce computation costs. According to the evaluation, YOLO-MSPM achieves precision (0.933), recall (0.920), mAP50 (0.970), and mAP50-95 (0.797), each exceeding the corresponding performance of YOLOv11n. In terms of model lightweighting, the YOLO-MSPM model has 1.773 M parameters, which is a 31.332% reduction compared to YOLOv11n. Its GFLOPs and model size are 5.4 and 4.0 MB, respectively, representing reductions of 14.286% and 27.273%. The study delivers a lightweight yet accurate solution to support the identification and monitoring of cotton Verticillium wilt in environments with limited resources. Full article

(This article belongs to the Special Issue Practical Use of Crop, Pest and Diseases Models in Sustainable Agriculture)

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22 pages, 3109 KB

Open AccessArticle

Genome-Wide Transcriptional Analysis Reveals Gamma-Aminobutyric Acid (GABA) Priming Induces Long-Term Stress Memory in Tomato (Solanum lycopersicum)

by Kincső Decsi, Mostafa Ahmed and Zoltán Tóth

Agriculture 2025, 15(19), 2012; https://doi.org/10.3390/agriculture15192012 - 26 Sep 2025

Abstract

Addressing damage inflicted by environmental stress is difficult post-occurrence. The use of externally delivered gamma-aminobutyric acid (GABA) priming to healthy plants may serve as an effective preventive measure by stimulating plant defense pathways. A genome-wide transcriptional investigation was performed on tomato plants following [...] Read more.

Addressing damage inflicted by environmental stress is difficult post-occurrence. The use of externally delivered gamma-aminobutyric acid (GABA) priming to healthy plants may serve as an effective preventive measure by stimulating plant defense pathways. A genome-wide transcriptional investigation was performed on tomato plants following GABA priming, with extended data about the stress memory of previously primed plants subjected to drought stress. GABA significantly stimulates starch and sucrose metabolism, amino sugar and nucleotide sugar metabolism, porphyrin metabolism, glycerolipid metabolism, biosynthesis of phenylalanine, tyrosine, and tryptophan, phenylalanine metabolism, ascorbate and aldarate metabolism, pantothenate and CoA biosynthesis, and plant hormone signal transduction pathways. The initial priming effect could be remembered when subsequent environmental stress arose, but its influence intensified in plants that had previously undergone priming. The application of GABA can establish a novel form of preventative defense against the detrimental effects of stresses. It can effectively enhance long-term plant defense by facilitating the development of plant stress memory. Full article

(This article belongs to the Section Crop Genetics, Genomics and Breeding)

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20 pages, 5349 KB

Open AccessArticle

Regulatory Mechanism of Phosphorus Tailings and Organic Fertilizer Jointly Driving the Succession of Acidic Soil Microbial Functional Groups and Enhancing Corn Yield

by Chuanxiong Geng, Xinling Ma, Xianfeng Hou, Jinghua Yang, Xi Sun, Yi Zheng, Min Zhou, Chuisi Kong and Wei Fan

Agriculture 2025, 15(19), 2011; https://doi.org/10.3390/agriculture15192011 - 26 Sep 2025

Abstract

The continued acidification of red soil reduces phosphorus availability and microbial activity, which restricts corn growth. Phosphorus tailings, a waste product from phosphate mining, can neutralize soil acidity and supply controlled-release phosphorus, but their effects on the red soil-corn system remain unclear. A [...] Read more.

The continued acidification of red soil reduces phosphorus availability and microbial activity, which restricts corn growth. Phosphorus tailings, a waste product from phosphate mining, can neutralize soil acidity and supply controlled-release phosphorus, but their effects on the red soil-corn system remain unclear. A field experiment in Qujing, Yunnan (2023–2024), tested four treatments: CK (standard fertilization), T1 (CK plus phosphorus tailings), T2 (80% of standard fertilizer plus phosphorus tailings), and T3 (80% of standard fertilizer plus phosphorus tailings and organic fertilizer, both applied at 6.0 t·ha⁻¹). Using high-throughput sequencing, redundancy analysis (RDA), and structural equation modeling (SEM), the study evaluated impacts on soil properties, microbial communities, and corn yield and quality. Results showed: (1) Phosphorus tailings reduced soil acidification; T3 raised soil pH in the top 0–10 cm by 0.54–0.9 units compared to CK and increased total, available, and soluble phosphorus in the 0–20 cm layer to 952.82, 28.46, and 2.04 mg/kg, respectively. (2) T3 exhibited the highest microbial diversity (Chao1 and Shannon indices increased by 177.57% and 37.80% versus CK) and a more complex bacterial co-occurrence network (114 edges versus 107 in CK), indicating enhanced breakdown of aromatic compounds. (3) Corn yield under T3 improved by 13.72% over CK, with increases in hundred-grain weight (+6.02%), protein content (+18.04%), and crude fiber (+9.00%). (4) Effective nitrogen, ammonium nitrogen, available phosphorus, and soil conductivity were key factors affecting gcd/phoD phosphorus-reducing bacteria. (5) Phosphorus tailings indirectly increased yield by modifying soil properties and pH, both positively linked to yield, while gcd-carrying bacteria had a modest positive influence. In summary, combining phosphorus tailings with a 20% reduction in chemical fertilizer reduces fertilizer use, recycles mining waste, and boosts corn production in acidic red soil, though further studies are needed to evaluate long-term environmental effects. Full article

(This article belongs to the Section Crop Production)

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23 pages, 1139 KB

Open AccessArticle

Estimating the Impact of Pesticide Use Reduction Policies on Irish Cereal Yields Using an Iterative Expert Panel Methodology

by Robert McDougall, Meghan England, Fiona Thorne, Dermot Forristal, Ewen Mullins and Steven Kildea

Agriculture 2025, 15(19), 2010; https://doi.org/10.3390/agriculture15192010 - 25 Sep 2025

Abstract

The European Union’s (EU) Farm to Fork strategy seeks to reduce agricultural pesticide use by 50%, both of total pesticide use and of the most hazardous chemicals. While Ireland has achieved the goal of overall pesticide use reduction, more progress is needed regarding [...] Read more.

The European Union’s (EU) Farm to Fork strategy seeks to reduce agricultural pesticide use by 50%, both of total pesticide use and of the most hazardous chemicals. While Ireland has achieved the goal of overall pesticide use reduction, more progress is needed regarding more hazardous substances. Ireland’s cool damp climate is unique within the EU, and with little empirical data on the possible impacts of achieving this goal on Irish farming, we sought to estimate these in cereal crops using a ‘Delphi’ style iterative expert panel methodology, conducted over two rounds, rather than until consensus was reached, to allow for knowledge gaps that may exist to become apparent. A total of 17 crop production experts with at least five years of relevant experience were surveyed anonymously, and then their answers were compiled and fed back to them, allowing participants to revise their responses based on the opinion of the group. Participants estimated that reduced use of more hazardous fungicides and insecticides could both reduce yields by 10–15%, while reduced use of herbicides would reduce yields of winter cereals by up to 30%. These impacts are substantially higher than those predicted in other Europe-wide studies. Application of additional Integrated Pest Management measures was estimated to reduce yield loss but not entirely mitigate it. These findings highlight the economic and food security trade-offs that may be required to achieve the Farm to Fork strategy’s goals. Full article

(This article belongs to the Section Agricultural Economics, Policies and Rural Management)

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23 pages, 11596 KB

Open AccessArticle

Combined Hyperspectral Imaging with Wavelet Domain Multivariate Feature Fusion Network for Bioactive Compound Prediction of Astragalus membranaceus var. mongholicus

by Suning She, Zhiyun Xiao and Yulong Zhou

Agriculture 2025, 15(19), 2009; https://doi.org/10.3390/agriculture15192009 - 25 Sep 2025

Abstract

The pharmacological quality of Astragalus membranaceus var. mongholicus (AMM) is determined by its bioactive compounds, and developing a rapid prediction method is essential for quality assessment. This study proposes a predictive model for AMM bioactive compounds using hyperspectral imaging (HSI) and wavelet domain [...] Read more.

The pharmacological quality of Astragalus membranaceus var. mongholicus (AMM) is determined by its bioactive compounds, and developing a rapid prediction method is essential for quality assessment. This study proposes a predictive model for AMM bioactive compounds using hyperspectral imaging (HSI) and wavelet domain multivariate features. The model employs techniques such as the first-order derivative (FD) algorithm and the continuum removal (CR) algorithm for initial feature extraction. Unlike existing models that primarily focus on a single-feature extraction algorithm, the proposed tree-structured feature extraction module based on discrete wavelet transform and one-dimensional convolutional neural network (1D-CNN) integrates FD and CR, enabling robust multivariate feature extraction. Subsequently, the multivariate feature cross-fusion module is introduced to implement multivariate feature interaction, facilitating mutual enhancement between high- and low-frequency features through hierarchical recombination. Additionally, a multi-objective prediction mechanism is proposed to simultaneously predict the contents of flavonoids, saponins, and polysaccharides in AMM, effectively leveraging the enhanced, recombined spectral features. During testing, the model achieved excellent predictive performance with R² values of 0.981 for flavonoids, 0.992 for saponins, and 0.992 for polysaccharides. The corresponding RMSE values were 0.37, 0.04, and 0.86; RPD values reached 7.30, 10.97, and 11.16; while MAE values were 0.14, 0.02, and 0.38, respectively. These results demonstrate that integrating multivariate features extracted through diverse methods with 1D-CNN enables efficient prediction of AMM bioactive compounds using HSI. Full article

(This article belongs to the Section Artificial Intelligence and Digital Agriculture)

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29 pages, 22819 KB

Open AccessArticle

Enhanced Spatially Explicit Modeling of Soil Particle Size and Texture Classification Using a Novel Two-Point Machine Learning Hybrid Framework

by Liya Qin, Zong Wang and Xiaoyuan Zhang

Agriculture 2025, 15(19), 2008; https://doi.org/10.3390/agriculture15192008 - 25 Sep 2025

Abstract

Accurately predicting soil particle size fractions (PSFs) and classifying soil texture types are essential for soil resource assessment and sustainable land management. PSFs, comprising clay, silt, and sand, form a compositional dataset constrained to sum to 100%. The practical implications of incorporating compositional [...] Read more.

Accurately predicting soil particle size fractions (PSFs) and classifying soil texture types are essential for soil resource assessment and sustainable land management. PSFs, comprising clay, silt, and sand, form a compositional dataset constrained to sum to 100%. The practical implications of incorporating compositional data characteristics into PSF mapping remain insufficiently explored. This study applies a two-point machine learning (TPML) model, integrating spatial autocorrelation and attribute similarity, to enhance both the quantitative prediction of PSFs and the categorical classification of soil texture types in the Heihe River Basin, China. TPML was compared with random forest regression kriging (RFRK), random forest (RF), XGBoost, and ordinary kriging (OK), and a novel TPML-C model was developed for multi-class classification tasks. Results show that TPML achieved R² values of 0.58, 0.55, and 0.64 for clay, silt, and sand, respectively. Among all models, the ALR_TPML predictions showed the most consistent agreement with the observed variability, with predicted ranges of 2.63–98.28% for silt, 0.26–36.16% for clay, and 0.64–96.90% for sand. Across all models, the dominant soil texture types were identified as Sandy Loam (SaLo), Loamy Sand (LoSa), and Silty Loam (SiLo). For soil texture classification, TPML with raw, ALR-, and ILR-transformed data reached right ratios of 61.09%, 55.78%, and 60.00%, correctly identifying 25, 26, and 27 types out of 43. TPML with raw data exhibited strong performance in both regression and classification, with superior ability to separate ambiguous boundaries. Log-ratio transformations, particularly ILR, further improved classification performance by addressing the constraints of compositional data. These findings demonstrate the promise of hybrid machine learning approaches for digital soil mapping and precision agriculture. Full article

(This article belongs to the Section Agricultural Soils)

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22 pages, 3275 KB

Open AccessReview

Permanent Magnet Synchronous Motor Drive System for Agricultural Equipment: A Review

by Chao Zhang, Xiongwei Xia, Hong Zheng and Hongping Jia

Agriculture 2025, 15(19), 2007; https://doi.org/10.3390/agriculture15192007 - 25 Sep 2025

Abstract

The electrification of agricultural equipment is a critical pathway to address the dual challenges of increasing global food production and ensuring sustainable agricultural development. As the core power unit, the permanent magnet synchronous motor (PMSM) drive system faces severe challenges in achieving high [...] Read more.

The electrification of agricultural equipment is a critical pathway to address the dual challenges of increasing global food production and ensuring sustainable agricultural development. As the core power unit, the permanent magnet synchronous motor (PMSM) drive system faces severe challenges in achieving high performance, robustness, and reliable control in complex farmland environments characterized by sudden load changes, extreme operating conditions, and strong interference. This paper provides a comprehensive review of key technological advancements in PMSM drive systems for agricultural electrification. First, it analyzes solutions to enhance the reliability of power converters, including high-frequency silicon carbide (SiC)/gallium nitride (GaN) power device packaging, thermal management, and electromagnetic compatibility (EMC) design. Second, it systematically elaborates on high-performance motor control algorithms such as Direct Torque Control (DTC) and Model Predictive Control (MPC) for improving dynamic response; robust control strategies like Sliding Mode Control (SMC) and Active Disturbance Rejection Control (ADRC) for enhancing resilience; and the latest progress in fault-tolerant control architectures incorporating sensorless technology. Furthermore, the paper identifies core challenges in large-scale applications, including environmental adaptability, real-time multi-machine coordination, and high reliability requirements. Innovatively, this review proposes a closed-loop intelligent control paradigm encompassing environmental disturbance prediction, control parameter self-tuning, and actuator dynamic response. This paradigm provides theoretical support for enhancing the autonomous adaptability and operational quality of agricultural machinery in unstructured environments. Finally, future trends involving deep AI integration, collaborative hardware innovation, and agricultural ecosystem construction are outlined. Full article

(This article belongs to the Section Agricultural Technology)

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21 pages, 3127 KB

Open AccessArticle

Experimental Research and Parameter Optimization on Dust Emission Reduction for Peanut Pickup Combine Harvesting

by Hongbo Xu, Peng Zhang, Fengwei Gu, Feng Wu, Hongguang Yang, Zhichao Hu, Enrong Mao and Jiangtao Wang

Agriculture 2025, 15(19), 2006; https://doi.org/10.3390/agriculture15192006 - 25 Sep 2025

Abstract

In response to the dust pollution issue during the harvesting operations of peanut pickup combines, this study involved conducting bench tests to explore the variation patterns of dust emission parameters and harvesting operation indicators under diverse working parameter conditions of the combine’s working [...] Read more.

In response to the dust pollution issue during the harvesting operations of peanut pickup combines, this study involved conducting bench tests to explore the variation patterns of dust emission parameters and harvesting operation indicators under diverse working parameter conditions of the combine’s working components. A multi-factor mathematical model was established to predict both the dust emission rate of peanut pickup combines and the quality of harvesting operations. The model was utilized to identify the optimal combination of operation parameters for achieving high-quality and low-emission performance. The optimal parameter combination was determined as follows: a pod threshing roller speed of 313 r/min, a cleaning fan speed of 2535 r/min, a vine crushing roller speed of 1970 r/min, and a lifting fan speed of 1604 r/min. Under these conditions, the theoretical dust emission rate was calculated to be 10,603 mg/s, with a pod loss rate of 4.73% and a pod impurity rate of 5.21%. Compared to previous settings, the optimized operation parameters effectively reduced the combine’s dust emissions by 9.95%. Notably, the harvesting operation quality still complies with the industry standards for peanut harvesters. These research findings offer theoretical insights and robust technical support for minimizing dust pollution during the whole-feed harvesting of peanuts, contributing to more environmentally friendly and efficient peanut harvesting practices. Full article

(This article belongs to the Section Agricultural Technology)

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22 pages, 2252 KB

Open AccessArticle

Comparison of the Effects of Prohexadione Calcium and Uniconazole on Sweet Potato Storage and Texture Quality

by Jiayi Li, Jiaping Xia, Ximing Xu, Tiechen Shen, Kanghao Gao, Yueming Zhu, Guoquan Lu and Zunfu Lv

Agriculture 2025, 15(19), 2005; https://doi.org/10.3390/agriculture15192005 - 25 Sep 2025

Abstract

Storage quality and texture properties determine the processing quality of sweet potato (Ipomoea batatas Lam.). Prohexadione calcium (Pro-Ca) and uniconazole (UCZ) are plant growth regulators that inhibit gibberellin biosynthesis, reducing excessive sweet potato growth and improving stress resistance. This study evaluated the [...] Read more.

Storage quality and texture properties determine the processing quality of sweet potato (Ipomoea batatas Lam.). Prohexadione calcium (Pro-Ca) and uniconazole (UCZ) are plant growth regulators that inhibit gibberellin biosynthesis, reducing excessive sweet potato growth and improving stress resistance. This study evaluated the impact of foliar applications—applied at 37.5 g·hm⁻² for both treatments—on the postharvest texture characteristics and storage performance of sweet potato storage roots. The experiments were conducted over two years (2023 and 2024) using two sweet potato cultivars, Zheshu13 (Z13) and Wanshu10 (W10). The results showed that Pro-Ca significantly improved the textural properties of sweet potatoes, including firmness, chewiness, and maximum adhesion force, especially in Z13 (p < 0.05). Pro-Ca also reduced the percentage of rotting and weight loss during storage (p < 0.05), offering a more sustainable option for sweet potato postharvest management compared to UCZ. Additionally, Pro-Ca treatment increased the soluble sugar content of Z13-2023 and W10-2024, as well as the amylose content, except for W10 (p < 0.05), which could enhance both the sweetness and texture of sweet potatoes. This study highlights the potential of Pro-Ca as an effective growth regulator for improving sweet potato storage and processing quality. Further research is needed to investigate the long-term effects and the molecular mechanisms underlying these benefits, particularly in relation to gibberellin inhibition, carbohydrate metabolism, and cell wall integrity during storage. Full article

(This article belongs to the Special Issue Phytochemical Changes in Vegetables and Fruits During Post-Harvest Storage and Processing)

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26 pages, 1787 KB

Open AccessReview

Enhancing Agroecological Resilience in Arid Regions: A Review of Shelterbelt Structure and Function

by Aishajiang Aili, Fabiola Bakayisire, Hailiang Xu and Abdul Waheed

Agriculture 2025, 15(19), 2004; https://doi.org/10.3390/agriculture15192004 - 25 Sep 2025

Abstract

Farmland shelterbelts are vital ecological infrastructure for sustaining agriculture in arid regions, where high winds, soil erosion, and water scarcity severely constrain productivity. While their protective functions—reducing wind speed, controlling erosion, moderating microclimates, and enhancing yields—are well documented, previous studies have largely examined [...] Read more.

Farmland shelterbelts are vital ecological infrastructure for sustaining agriculture in arid regions, where high winds, soil erosion, and water scarcity severely constrain productivity. While their protective functions—reducing wind speed, controlling erosion, moderating microclimates, and enhancing yields—are well documented, previous studies have largely examined individual structural elements in isolation, leaving their interactive effects and trade-offs poorly understood. This review synthesizes current research on the structural optimization of shelterbelts, emphasizing the critical relationship between their physical and biological attributes and their protective functions. Key structural parameters—such as optical porosity, height, width, orientation, and species composition—are examined for their individual and interactive impacts on shelterbelt performance. Empirical and modeling studies indicate that moderate porosity maximizes wind reduction efficiency and extends the leeward protection zone, while multi-row, multi-species configurations effectively suppress soil erosion and improve microclimate conditions. Sheltered areas experience reduced evapotranspiration, increased humidity, and moderated temperatures, collectively enhancing crop water use efficiency and yielding significant improvements in crop production. Advanced methodologies, including field monitoring, wind tunnel testing, computational fluid dynamics, and remote sensing, are employed to quantify benefits and refine designs. A multi-objective optimization framework is essential to balance competing goals: maximizing wind reduction, minimizing water consumption, enhancing biodiversity, and ensuring economic viability. Future challenges involve adapting designs to climate change, integrating water-efficient and native species, leveraging artificial intelligence for predictive modeling, and addressing socio-economic barriers to implementation. Building on this evidence, we propose a multi-objective optimization framework to balance competing goals: maximizing wind protection, minimizing water use, enhancing biodiversity, and ensuring economic viability. We identify key research gaps including unresolved porosity thresholds, the climate resilience of alternative species compositions, and the limited application of optimization algorithms and outline future priorities such as region-specific design guidelines, AI-driven predictive models, and policy incentives. This review offers a novel, trade-off–aware synthesis to guide next-generation shelterbelt design in arid agriculture. Full article

(This article belongs to the Section Ecosystem, Environment and Climate Change in Agriculture)

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12 pages, 498 KB

Open AccessArticle

The Infection of Yellow Lupin (Lupinus luteus L.) with Bean Yellow Mosaic Virus (BYMV) and Cucumber Mosaic Virus (CMV) in Organic Farming in Eastern Poland

by Anna Czubacka, Diana Czarnecka and Jerzy Księżak

Agriculture 2025, 15(19), 2003; https://doi.org/10.3390/agriculture15192003 - 25 Sep 2025

Abstract

Yellow lupin seeds are a rich source of protein, which is why they are grown for animal feed and human consumption. At the same time, there is growing interest in organic farming. However, this type of cultivation is more susceptible to diseases, including [...] Read more.

Yellow lupin seeds are a rich source of protein, which is why they are grown for animal feed and human consumption. At the same time, there is growing interest in organic farming. However, this type of cultivation is more susceptible to diseases, including viral ones. Yellow lupin is most commonly affected by the bean yellow mosaic virus (BYMV) and cucumber mosaic virus (CMV). We have therefore determined the occurrence of these two pathogens in six new Polish yellow lupin cultivars (Goldeneye, Salut, Diament, Puma, Mister and Bursztyn) grown in accordance with organic farming rules. Field experiments were conducted over three years, from 2022 to 2024, in three locations in eastern Poland. The Goldeneye cultivar was the most susceptible to BYMV, with an average infection rate of 59.17% of plants. In contrast, the Puma cultivar was the least susceptible to BYMV infection, with an average infection rate of 23.34%. However, even within this cultivar, most plants were infected under conditions of strong pathogen pressure (up to 90% in one of the locations in 2024). CMV infections were less frequent, with no statistical differences being found between cultivars in terms of the number of infected plants. Full article

(This article belongs to the Section Crop Protection, Diseases, Pests and Weeds)

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25 pages, 1346 KB

Open AccessArticle

Impact of Monoculture and Various Ratios of Intercropped Oats and Daikon Radish Cover Crops on Soil Properties, Weed Suppression, and Spinach Yield

by Fatemeh Ahmadnia, Ali Ebadi, Mohammad Taghi Alebrahim and Masoud Hashemi

Agriculture 2025, 15(19), 2002; https://doi.org/10.3390/agriculture15192002 - 25 Sep 2025

Abstract

Optimizing seeding ratios in mixed cover crop species can maximize their ecological benefits, such as soil properties and weed suppression. A two-year field study assessed seven oat (O) and daikon radish (D) ratios (100:0 to 0:100) for their effects on soil quality, weed [...] Read more.

Optimizing seeding ratios in mixed cover crop species can maximize their ecological benefits, such as soil properties and weed suppression. A two-year field study assessed seven oat (O) and daikon radish (D) ratios (100:0 to 0:100) for their effects on soil quality, weed pressure, and subsequent spinach yield. Measured parameters included cover crop biomass, C:N ratio, land equivalence ratio (LER), soil organic carbon (SOC), microbial population, soil enzyme activities, bulk density, porosity, moisture, and water infiltration time. The impact of intercrop residues and two weeding strategies (hand weeding and no weeding) on weed pressure and spinach yield was also assessed. Oat monoculture produced the highest biomass (338.7 g m⁻²), while radish monoculture biomass was the lowest (256.1 g m⁻²). Yet the 30:70 (O:D) ratio contributed to the highest SOC (0.96). The C:N ratio of all intercropped combinations was below the critical threshold (25:1) that causes N immobilization, with oat monoculture having the highest value (23:1). The microbial population was highest with the 10:90 (O:D) ratio, with 12.8 × 10⁻⁴ most probable number per g⁻¹ soil. While urease and dehydrogenase enzyme activities were not affected by intercrop ratios, β-glucosidase and alkaline phosphatase activities were up to 30% higher in daikon radish-dominated intercrops. Bulk density decreased by 31.7% in oat monoculture, whereas infiltration time was shortened in daikon radish monoculture by 41.7% (4.6 s). Weed suppression was strongest in oat monoculture and the 90:10 (O:D) intercropping, reducing weed populations by over 30%. Spinach yield was highest in oat monoculture with hand weeding (842.9 g m⁻²), with a 40.2% increase over weeding alone. Overall, daikon radish-dominated intercropping ratios were more effective in enhancing soil properties, whereas oat-dominated intercropping improved spinach yield, mainly due to slower decomposition, thus better suppressing weeds. Full article

(This article belongs to the Section Crop Production)

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25 pages, 24115 KB

Open AccessArticle

SLW-YOLO: A Hybrid Soybean Parent Phenotypic Consistency Detection Model Based on Deep Learning

by Chuntao Yu, Jinyang Li, Wenqiang Shi, Liqiang Qi, Zheyun Guan, Wei Zhang and Chunbao Zhang

Agriculture 2025, 15(19), 2001; https://doi.org/10.3390/agriculture15192001 - 25 Sep 2025

Abstract

During hybrid soybean seed production, the parents’ phenotypic consistency is assessed by breeders to ensure the purity of soybean seeds. Detection traits encompass the hypocotyl, leaf, pubescence, and flower. To achieve the detection of hybrid soybean parents’ phenotypic consistency in the field, a [...] Read more.

During hybrid soybean seed production, the parents’ phenotypic consistency is assessed by breeders to ensure the purity of soybean seeds. Detection traits encompass the hypocotyl, leaf, pubescence, and flower. To achieve the detection of hybrid soybean parents’ phenotypic consistency in the field, a self-propelled image acquisition platform was used to obtain soybean plant image datasets. In this study, the Large Selective Kernel Network (LSKNet) attention mechanism module, the detection layer Small Network (SNet), dedicated to detecting small objects, and the Wise Intersection over Union v3 (WIoU v3) loss function were added into the YOLOv5s network to establish the hybrid soybean parent phenotypic consistency detection model SLW-YOLO. The SLW-YOLO achieved the following: F1 score: 92.3%; mAP: 94.8%; detection speed: 88.3 FPS; and model size: 45.1 MB. Compared to the YOLOv5s model, the SLW-YOLO model exhibited an improvement in F1 score by 6.1% and in mAP by 5.4%. There was a decrease in detection speed by 42.1 FPS, and an increase in model size by 31.4 MB. The parent phenotypic consistency detected by the SLW-YOLO model was 98.9%, consistent with manual evaluation. Therefore, this study demonstrates the potential of using deep learning technology to identify phenotypic consistency in the seed production of large-scale hybrid soybean varieties. Full article

(This article belongs to the Section Artificial Intelligence and Digital Agriculture)

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23 pages, 4868 KB

Open AccessArticle

Design and Experiment of Drying Equipment for Alfalfa Bales

by Jianqiang Du, Zhiwen Sun and Zeqi Chen

Agriculture 2025, 15(19), 2000; https://doi.org/10.3390/agriculture15192000 - 24 Sep 2025

Abstract

Inefficient drying of alfalfa round bales causes significant nutrient loss (up to 50%) and quality degradation due primarily to uneven drying in existing processing methods. To address this challenge requiring dedicated equipment and optimized processes, this study developed a specialized hot-air drying test [...] Read more.

Inefficient drying of alfalfa round bales causes significant nutrient loss (up to 50%) and quality degradation due primarily to uneven drying in existing processing methods. To address this challenge requiring dedicated equipment and optimized processes, this study developed a specialized hot-air drying test bench (CGT-1). A coupled heat and mass transfer model was established, and 3D dynamic simulations of temperature, humidity, and wind speed distributions within bales were performed using COMSOL multiphysics to evaluate drying inhomogeneity. Single-factor experiments and multi-factor response surface methodology (RSM) based on Box–Behnken design were employed to investigate the effects of hot air temperature (50–65 °C), wind speed (2–5 m/s), and air duct opening diameter (400–600 mm) on moisture content, drying rate, and energy consumption. Results demonstrated that larger duct diameters (600 mm) and higher wind speeds (5 m/s) significantly enhanced field uniformity. RSM optimization identified optimal parameters: temperature at 65 °C, wind speed of 5 m/s, and duct diameter of 600 mm, achieving a drying time of 119.2 min and a drying rate of 0.62 kg/(kg·min). Validation experiments confirmed the model’s accuracy. These findings provide a solid theoretical foundation and technical support for designing and optimizing alfalfa round-bale drying equipment. Future work should explore segmented drying strategies to enhance energy efficiency. Full article

(This article belongs to the Section Agricultural Technology)

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21 pages, 8214 KB

Open AccessReview

Basil Downy Mildew (Peronospora belbahrii): A Major Threat to Ocimum basilicum L. Production

by Massimo Pugliese, Giovanna Gilardi, Angelo Garibaldi and Maria Lodovica Gullino

Agriculture 2025, 15(19), 1999; https://doi.org/10.3390/agriculture15191999 - 24 Sep 2025

Abstract

Basil (Ocimum basilicum L.), a key herb in Mediterranean cuisine, holds substantial economic and cultural value due to its aromatic and medicinal properties. Cultivated globally, particularly in Italy’s Liguria region, basil is consumed both fresh and processed, with pesto sauce as its [...] Read more.

Basil (Ocimum basilicum L.), a key herb in Mediterranean cuisine, holds substantial economic and cultural value due to its aromatic and medicinal properties. Cultivated globally, particularly in Italy’s Liguria region, basil is consumed both fresh and processed, with pesto sauce as its most notable derivative. Despite its commercial success, basil production is significantly constrained by a broad spectrum of fungal pathogens, with Peronospora belbahrii, the causal agent of downy mildew, posing the most severe threat. This study aims to provide a comprehensive overview of basil’s disease susceptibility and control. Special emphasis is placed on the biology, epidemiology, global spread, and diagnosis of P. belbahrii, which has become a critical challenge for both conventional and organic farming systems. Disease management strategies, including cultural practices, genetic resistance, fungicide applications, resistance inducers, and biocontrol agents, are reviewed in detail. The development of downy mildew-resistant cultivars—although limited for PDO-designated Genovese basil—has emerged as the most sustainable control measure; however, the increasing genetic variability in P. belbahrii underscores the ongoing need for integrated pest management and resistant cultivar development. Seed health and quality remain the starting points of any fully integrated approach, although the suggested management measures for basil production should be combined with appropriate cultivation techniques aimed at reducing the relative humidity of the environment, while taking into account whether basil production takes place in open fields or under protection. Full article

(This article belongs to the Special Issue Agronomic Practices for Enhancing Quality and Yield of Aromatic and Medicinal Crops)

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19 pages, 3107 KB

Open AccessArticle

Diurnal Behaviour, Health and Hygiene of Dairy Cows in Compost Barn Systems Under Different Climates in Argentina: A Bayesian Approach

by Gabriela Marcela Martinez, Pablo Viretto, Georgina Frossasco, Víctor Humberto Suarez, Ayoola Olawole Jongbo, Edgar de Souza Vismara and Frederico Márcio Corrêa Vieira

Agriculture 2025, 15(19), 1998; https://doi.org/10.3390/agriculture15191998 - 23 Sep 2025

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Abstract

Compost barn systems are relevant alternatives to discussing production efficiency, welfare, and sustainability in dairy farming. However, studies evaluating these systems in different climates are still scarce, especially in subtropical climate zones. Here, we assess whether dairy cows’ behaviour, health and hygiene in [...] Read more.

Compost barn systems are relevant alternatives to discussing production efficiency, welfare, and sustainability in dairy farming. However, studies evaluating these systems in different climates are still scarce, especially in subtropical climate zones. Here, we assess whether dairy cows’ behaviour, health and hygiene in compost barn systems are influenced by different climatic conditions and calving orders in Argentina’s central and extra-Pampean basins from the perspective of Bayesian inference. We evaluated dairy cows (n = 40) in a compost barn system simultaneously at two locations in Argentina: Rafaela and Salta. The following variables were evaluated: environmental factors, animal behaviour, respiratory rate, udder and hock hygiene, and locomotion degree of milking cows. There was a total of 10 primiparous cows and 10 multiparous cows at each location, randomly selected, which were in the first third of lactation (<90 DIM). Using Bayesian inference, we observed that Rafaela had a temperature-humidity index (THI) above 70, and Salta had a milder environment, with lower average temperature and higher relative humidity. Thus, climatic interference is evident in behaviour, triggering more behavioural and physiological mechanisms for heat abatement in primiparous females in Rafaela. At the same time, the mild conditions in Salta led to better thermal energy transfer by multiparous females compared to primiparous cows. This shows that the microclimate could interfere with the social hierarchy of cows when they are under heat stress. These findings highlight the importance of considering both calving orders and climate when designing management strategies for dairy systems. Full article

(This article belongs to the Special Issue Livestock Building Environment Improvements and Their Influence on the Animal’s Welfare)

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14 pages, 584 KB

Open AccessArticle

Consumer Perceptions of Greenwashing in Local Agri-Food Systems and Rural Tourism

by Gunta Grinberga-Zalite, Ksenija Furmanova, Sandija Zeverte-Rivza, Liga Paula and Inita Kindzule

Agriculture 2025, 15(19), 1997; https://doi.org/10.3390/agriculture15191997 - 23 Sep 2025

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Abstract

The current article examines how Latvian consumers perceive the sustainability of rural tourism services and locally produced food, with particular attention paid to their views on misleading environmental claims. For small-scale agricultural producers and rural tourism providers, sustainability communication has become common, yet [...] Read more.

The current article examines how Latvian consumers perceive the sustainability of rural tourism services and locally produced food, with particular attention paid to their views on misleading environmental claims. For small-scale agricultural producers and rural tourism providers, sustainability communication has become common, yet formal regulation and consumer clarity issues often remain uncertain. The study is based on a mixed-methods approach that contains a comprehensive, multi-dimensional literature analysis and quantitative nation-wide survey data analysis (SPSS 27) with a thematic interpretation of consumer attitudes towards sustainability, trust, and greenwashing. The research findings show that while consumers generally support sustainable and ethically produced goods and services, their trust depends heavily on the transparency and credibility of the information provided. Official certifications and clear communication were seen as trustworthy, while vague promotional claims, especially in digital media, were often met with scepticism. The study also reveals how different factors such as education level, income, and place of residence influence the ability to recognize potential greenwashing. Given the growing global concern about false environmental claims, this article provides valuable insights not only for Latvia but also for other countries facing similar challenges in promoting sustainable rural development while preserving consumer trust in the green economy. Full article

(This article belongs to the Special Issue Strategies for Resilient and Sustainable Agri-Food Systems—2nd Edition)

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27 pages, 14691 KB

Open AccessArticle

DOSA-YOLO: Improved Model Research for the Detection of Common Chicken Diseases Using Phenotypic Features

by Xiaofeng Guo, Yun Wang, Jianhui Li, Qin Li, Zhenhuan Zuo and Zhenyu Liu

Agriculture 2025, 15(19), 1996; https://doi.org/10.3390/agriculture15191996 - 23 Sep 2025

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Abstract

Chicken farming plays a crucial role in the global food supply; however, the frequent occurrence of chicken diseases presents a substantial challenge to the industry’s sustainable development. This study introduces an enhanced YOLOv11 model, DOSA-YOLO, designed to detect four prevalent chicken diseases: avian [...] Read more.

Chicken farming plays a crucial role in the global food supply; however, the frequent occurrence of chicken diseases presents a substantial challenge to the industry’s sustainable development. This study introduces an enhanced YOLOv11 model, DOSA-YOLO, designed to detect four prevalent chicken diseases: avian pox, coccidiosis, Mycoplasma gallisepticum, and Newcastle disease. The research team developed an intelligent inspection robot to capture multi-angle images in intensive farming environments, constructing a five-class dataset comprising 8052 images. These images were categorized based on phenotypic features such as comb, eyes, and wattles, as well as pathological anatomical characteristics. To address challenges such as complex backgrounds, multi-scale lesions, and occlusion interference, three attention-enhancement modules—MSDA, MDJA, and SEAM—were integrated into the YOLOv11. The model was trained and validated using the constructed dataset and compared against seven other algorithms, including YOLOv5n, YOLOv7tiny, YOLOv8n, YOLOv9t, YOLOv10n, YOLOv11n, YOLOv12n, and Faster R-CNN. Experimental results demonstrated that DOSA-YOLO achieved a mean Average Precision (mAP) of 97.2% and an F1-score of 95.0%, outperforming the seven other algorithms while maintaining a balance between lightweight design and performance with GFLOPs of 6.9 and 2.87 M parameters. The model provides strong support for real-time chicken health monitoring in intensive farming environments. Full article

(This article belongs to the Section Farm Animal Production)

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18 pages, 4179 KB

Open AccessArticle

Distribution Characteristics of Rotor Airflow and Droplet Deposition of Plant Protection UAVs Under Varying Rotor–Nozzle Distances

by Xiaojie Xu, Shengde Chen, Zhihong Li, Zehong Wu, Yuxiang Tan, Shimin Huang and Yubin Lan

Agriculture 2025, 15(19), 1995; https://doi.org/10.3390/agriculture15191995 - 23 Sep 2025

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Abstract

The rotor airflow intensity and distribution characteristics of plant protection UAVs vary significantly with spatial positions below the rotor. Consequently, changes in the rotor–nozzle distance directly affect droplet motion and deposition patterns. To optimize the spraying effect of UAVs, this study combined a [...] Read more.

The rotor airflow intensity and distribution characteristics of plant protection UAVs vary significantly with spatial positions below the rotor. Consequently, changes in the rotor–nozzle distance directly affect droplet motion and deposition patterns. To optimize the spraying effect of UAVs, this study combined a numerical simulation of rotor airflow and droplet deposition at different vertical distances between rotor and nozzle with field validation tests. The simulation results revealed that airflow intensity initially increases and then decreases with greater rotor–nozzle distance, peaking at 300–400 mm below the rotor with a maximum airflow velocity of 8.1 m/s. At 360 mm, the droplet swarm achieved its highest average velocity, corresponding to optimal deposition effect. Field tests confirmed a non-linear relationship between rotor–nozzle distance and droplet deposition. Droplet deposition first increased but declined sharply beyond the optimal range. When the distance was 360 mm, the target area exhibited the highest droplet deposition of 0.766 μL·cm⁻² and the lowest drift rate of 23.31%. Although a certain deviation existed between numerical simulation results and field test values, both methods consistently identified 360 mm as the ideal distance for balancing deposition efficiency and drift control. These findings provide actionable insights for field trial design and advance precision spraying strategies for plant protection UAVs. Full article

(This article belongs to the Special Issue How Optical Sensors and Deep Learning Enhance the Production Management in Smart Agriculture)

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16 pages, 1999 KB

Open AccessArticle

Molecular Identification, Pathogenicity, and Fungicide Sensitivity of Sclerotinia spp. Isolates Associated with Sclerotinia Stem Rot in Rapeseed in Germany

by Nazanin Zamani-Noor, Dorsa Daneshbakhsh and Beatrice Berger

Agriculture 2025, 15(19), 1994; https://doi.org/10.3390/agriculture15191994 - 23 Sep 2025

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Abstract

(1) Background: Sclerotinia sclerotiorum is the main causal agent of Sclerotinia stem rot in rapeseed, while the related species S. subarctica has also been reported. However, its prevalence and impact in Germany remain unclear. Understanding the pathogenicity and fungicide sensitivity of Sclerotinia spp. [...] Read more.

(1) Background: Sclerotinia sclerotiorum is the main causal agent of Sclerotinia stem rot in rapeseed, while the related species S. subarctica has also been reported. However, its prevalence and impact in Germany remain unclear. Understanding the pathogenicity and fungicide sensitivity of Sclerotinia spp. is important for effective and sustainable disease management. (2) Methods: Isolates were collected from symptomatic rapeseed plants across Germany. Molecular identification was performed via ITS rRNA sequencing. Pathogenicity was assessed by stem inoculation of five rapeseed cultivars at the flowering stage. Fungicide sensitivity was tested in vitro against seven active substances, including azoles, boscalid, azoxystrobin, and fludioxonil. (3) Results: All isolates were identified as S. sclerotiorum; S. subarctica was not detected. Of the tested isolates, 23 showed low aggressiveness (relative lesion length < 15% of total plant length), 29 were moderately aggressive (15–20%), and 10 were highly aggressive (>20%). Azole fungicides were highly effective (EC₅₀ < 1.6 μg a.s. mL⁻¹), while reduced sensitivity was observed for boscalid, azoxystrobin, and fludioxonil (EC₅₀ > 4.0). (4) Conclusions: This study provides insight into the molecular identity, pathogenicity, and fungicide sensitivity of Sclerotinia isolates. The observed variability in aggressiveness and mycelial growth to fungicide emphasize the need for integrated management strategies to ensure Sclerotinia stem rot control. Full article

(This article belongs to the Section Crop Protection, Diseases, Pests and Weeds)

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17 pages, 1510 KB

Open AccessArticle

Tritrophic Interactions Among Fruit Flies (Diptera: Tephritidae), Its Parasitoids and Cultivated and Wild Hosts in the Pampa Biome, Rio Grande do Sul, Brazil

by Emily S. Araujo, Alexandra P. Krüger, Maria V. Calvo, Marcos H. F. Telles, Alexandre M. Neumann, Iris B. Scatoni, Valmir A. Costa, Dori E. Nava, José M. Mirás-Avalos and Flávio R. M. Garcia

Agriculture 2025, 15(19), 1993; https://doi.org/10.3390/agriculture15191993 - 23 Sep 2025

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Abstract

Fruit fly (Diptera: Tephritidae) species are a serious threat for fruit-growers worldwide. The parasitoids (Hymenoptera) are natural enemies of these flies. In this context, the aim of this work was to assess fruit infestation by tephritid flies, both in native and exotic fruit [...] Read more.

Fruit fly (Diptera: Tephritidae) species are a serious threat for fruit-growers worldwide. The parasitoids (Hymenoptera) are natural enemies of these flies. In this context, the aim of this work was to assess fruit infestation by tephritid flies, both in native and exotic fruit trees, in the Southern region of Rio Grande do Sul (Brazil). Moreover, the incidence of native parasitoids on fly larvae was estimated. Fruits with signals of attack by fruit flies were collected randomly both in the trees and on the ground. From 2013 to 2015, a total of 5729 fruits (194.48 kg) were collected, corresponding to 34 tree species from 16 botanical families. Fruits were taken to the laboratory, individualized, weighted and kept in vermiculite for pupae emergence. Pupae were counted and emerged adults were counted and identified. The association between fruit flies, hosts and parasitoids was determined when only a given species of tephritid emerged. Half of the sampled fruit tree species presented infestation by flies. The main species of tephritid fly was Anastrepha fraterculus. This study showed that natural parasitism rates of fruit flies were low; however, several parasitoid species from the Figitidae and Braconidae families were detected, including Aganaspis pelleranoi, Doryctobracon areolatus, Doryctobracon brasiliensis, Opius bellus, Utetes anastrephae, and Cerchysiella insularis. Full article

(This article belongs to the Section Crop Protection, Diseases, Pests and Weeds)

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20 pages, 3813 KB

Open AccessArticle

Molecular and Phytopathological Characterization of Fusarium Wilt-Resistant Chickpea Genotypes for Breeding Applications

by Raushan Yerzhebayeva, Alfiya Abekova, Kuralay Baitarakova, Mukhtar Kudaibergenov, Aydarkhan Yesserkenov, Bekzhan Maikotov and Svetlana Didorenko

Agriculture 2025, 15(19), 1992; https://doi.org/10.3390/agriculture15191992 - 23 Sep 2025

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Abstract

Fusarium wilt, caused by Fusarium oxysporum f. sp. ciceris (Foc), is a devastating disease of chickpea (Cicer arietinum L.), leading to vascular necrosis and plant death. This study evaluated 120 chickpea genotypes under natural infection field conditions during spring sowing [...] Read more.

Fusarium wilt, caused by Fusarium oxysporum f. sp. ciceris (Foc), is a devastating disease of chickpea (Cicer arietinum L.), leading to vascular necrosis and plant death. This study evaluated 120 chickpea genotypes under natural infection field conditions during spring sowing in southeastern Kazakhstan, assessing disease incidence (DI) and severity (DS) to identify resistant germplasm. Molecular screening using eight SSR markers linked to Foc-1, Foc-2, Foc-3, and Foc-5 loci detected resistant alleles in 18, 26, 19, and 42 genotypes, respectively. The correlation between molecular marker data and phenotypic resistance evaluations confirmed UBC-170 (Foc-2) and TA-194 (Foc-5) as the most predictive diagnostic markers (p < 0.01). Ten genotypes showed complete disease resistance (DI < 5%, R), corresponding to the resistant control (cultivar “WR-315”), with confirmed presence of multiple Foc resistance genes. The results of this study revealed valuable genetic resources for marker-assisted breeding programs aimed at developing Fusarium wilt-resistant chickpea cultivars adapted to Central Asian agroclimatic conditions. Full article

(This article belongs to the Section Crop Protection, Diseases, Pests and Weeds)

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