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Journal Description

Agriculture

Agriculture is an international, peer-reviewed, open access journal published semimonthly online.

Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
High Visibility: indexed within Scopus, SCIE (Web of Science), PubAg, AGRIS, RePEc, and other databases.
Journal Rank: JCR - Q1 (Agronomy) / CiteScore - Q1 (Plant Science)
Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 18.8 days after submission; acceptance to publication is undertaken in 1.9 days (median values for papers published in this journal in the second half of 2025).
Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
Companion journals for Agriculture include: Poultry, Grasses, Crops and AIPA.

Impact Factor: 3.6 (2024); 5-Year Impact Factor: 3.8 (2024)

Imprint Information Journal Flyer Open Access ISSN: 2077-0472

Latest Articles

24 pages, 13852 KB

Open AccessArticle

Research on the Leveling Performance of an Electromechanical Omnidirectional Leveling System for Tracked Mobile Platforms in Hilly and Mountainous Areas

by Yiyong Jiang, Ruochen Wang, Renkai Ding, Zeyu Sun and Wei Liu

Agriculture 2026, 16(4), 458; https://doi.org/10.3390/agriculture16040458 (registering DOI) - 15 Feb 2026

In response to the problems of poor operating stability and easy tipping of small agricultural machinery under the complex terrain of hilly and mountainous areas, this study designed a tracked mobile platform suitable for hilly and mountainous areas and equipped with an omnidirectional [...] Read more.

In response to the problems of poor operating stability and easy tipping of small agricultural machinery under the complex terrain of hilly and mountainous areas, this study designed a tracked mobile platform suitable for hilly and mountainous areas and equipped with an omnidirectional leveling function. The omnidirectional leveling system adopted an innovative coordinated leveling scheme with four servo-electric cylinders of “dual lateral and dual longitudinal” structure. Integrated with dual-axis tilt sensors and a PLC control system, the system enabled decoupled leveling in both the lateral and longitudinal directions. Dynamic simulations of the platform’s leveling process under typical working conditions were performed using ADAMS. The simulation results verified the feasibility of the omnidirectional leveling system. Field tests on slopes in hilly and mountainous areas demonstrated that the omnidirectional leveling system achieves rapid leveling on steep slopes within 5–6 s. After leveling, the average fuselage inclination angle was stabilized within 2°, with a standard deviation of less than 3.4°. This study provided a reliable technical solution and design reference for agricultural machinery manufacturers, while offering users a safer and more efficient platform for operations in complex mountainous areas, significantly reducing the risk of overturning. Full article

(This article belongs to the Special Issue Application of Smart Agricultural Technologies in Mountain Farming Systems)

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34 pages, 1509 KB

Open AccessArticle

Assessing the Economic Sustainability of Price Intervention Policies: Evidence from Thailand’s Cassava Market

by Pakapon Saiyut, Supaporn Poungchompu and Patcharee Suriya

Agriculture 2026, 16(4), 457; https://doi.org/10.3390/agriculture16040457 (registering DOI) - 15 Feb 2026

Although many countries have reduced the use of agricultural price intervention policies, such measures continue to be applied intermittently by the Thai government. In the current work, which examines the cassava price intervention policy from 1981 to 2024 in Thailand through a supply [...] Read more.

Although many countries have reduced the use of agricultural price intervention policies, such measures continue to be applied intermittently by the Thai government. In the current work, which examines the cassava price intervention policy from 1981 to 2024 in Thailand through a supply and demand framework, the authors estimate a dynamic simultaneous equation model (DSEM) via the lag-augmented three-stage least squares (LA-3SLS) approach in order to measure the welfare effects of these interventions. The results indicate that the policy mainly redistributes welfare among market participants rather than improving allocative efficiency. Producers experience temporary income gains during intervention periods, but these gains dissipate once the policy is withdrawn, leaving long-run total surplus largely unchanged. When fiscal costs are incorporated, the intervention generates a net welfare loss, suggesting limited contribution to long-term economic sustainability. The findings suggest that policy approaches emphasizing income stabilization and productivity enhancement are more consistent with long-term welfare and fiscal sustainability than reliance on direct price controls, with direct relevance to SDG 1 (No poverty) and SDG 8 (Decent work and economic growth), highlighting trade-offs between income support, market efficiency, and fiscal sustainability in agricultural policy design. This study contributes by integrating a welfare-based dynamic econometric framework with sustainability assessment, which enables long-term welfare metrics for evaluating the economic sustainability of agricultural price policies. Full article

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

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24 pages, 4946 KB

Open AccessArticle

Orchard Chestnut Visual Harvest Maturity Detection and Segmentation Using an Improved YOLO-Based Method

by Yunhao Zhang, Fan Zhang, Jiasheng Wang, Hao Yang, Wenping Zhang and Juan Li

Agriculture 2026, 16(4), 456; https://doi.org/10.3390/agriculture16040456 (registering DOI) - 15 Feb 2026

Visual harvest maturity is a key visual phenotype for orchard management and harvesting decisions, yet chestnut fruits in natural orchards often exhibit weak color contrast, subtle texture variation, blurred boundaries, and frequent occlusion under complex illumination. This study addresses RGB-based visual harvest maturity [...] Read more.

Visual harvest maturity is a key visual phenotype for orchard management and harvesting decisions, yet chestnut fruits in natural orchards often exhibit weak color contrast, subtle texture variation, blurred boundaries, and frequent occlusion under complex illumination. This study addresses RGB-based visual harvest maturity recognition and proposes AHM-YOLO, an improved instance segmentation model built upon YOLOv11n-seg. The proposed model enhances maturity-related feature representation by strengthening color- and edge-sensitive cues, stabilizing spatial dependencies under occlusion and illumination variation, and improving cross-scale semantic consistency in dense orchard scenes. A chestnut dataset collected from a typical orchard in Shandong Province is annotated into three visual harvest maturity stages (unripe, semi-ripe, and ripe). To ensure reliable evaluation, the dataset is partitioned at the acquisition unit level, and all experiments are conducted using multi-seed repeated runs. Experimental results show that AHM-YOLO achieves 84.3% Mask mAP50 and 72.2% Mask mAP50–95, demonstrating consistent improvements over the baseline model in complex orchard environments. Full article

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

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25 pages, 15267 KB

Open AccessArticle

3D Semantic Map Reconstruction for Orchard Environments Using Multi-Sensor Fusion

by Quanchao Wang, Yiheng Chen, Jiaxiang Li, Yongxing Chen and Hongjun Wang

Agriculture 2026, 16(4), 455; https://doi.org/10.3390/agriculture16040455 (registering DOI) - 15 Feb 2026

Semantic point cloud maps play a pivotal role in smart agriculture. They provide not only core three-dimensional data for orchard management but also empower robots with environmental perception, enabling safer and more efficient navigation and planning. However, traditional point cloud maps primarily model [...] Read more.

Semantic point cloud maps play a pivotal role in smart agriculture. They provide not only core three-dimensional data for orchard management but also empower robots with environmental perception, enabling safer and more efficient navigation and planning. However, traditional point cloud maps primarily model surrounding obstacles from a geometric perspective, failing to capture distinctions and characteristics between individual obstacles. In contrast, semantic maps encompass semantic information and even topological relationships among objects in the environment. Furthermore, existing semantic map construction methods are predominantly vision-based, making them ill-suited to handle rapid lighting changes in agricultural settings that can cause positioning failures. Therefore, this paper proposes a positioning and semantic map reconstruction method tailored for orchards. It integrates visual, LiDAR, and inertial sensors to obtain high-precision pose and point cloud maps. By combining open-vocabulary detection and semantic segmentation models, it projects two-dimensional detected semantic information onto the three-dimensional point cloud, ultimately generating a point cloud map enriched with semantic information. The resulting 2D occupancy grid map is utilized for robotic motion planning. Experimental results demonstrate that on a custom dataset, the proposed method achieves 74.33% mIoU for semantic segmentation accuracy, 12.4% relative error for fruit recall rate, and 0.038803 m mean translation error for localization. The deployed semantic segmentation network Fast-SAM achieves a processing speed of 13.36 ms per frame. These results demonstrate that the proposed method combines high accuracy with real-time performance in semantic map reconstruction. This exploratory work provides theoretical and technical references for future research on more precise localization and more complete semantic mapping, offering broad application prospects and providing key technological support for intelligent agriculture. Full article

(This article belongs to the Special Issue Advances in Robotic Systems for Precision Orchard Operations)

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21 pages, 6687 KB

Open AccessArticle

Visual Navigation Line Detection and Extraction for Hybrid Rapeseed Seed Production Parent Rows

by Ping Jiang, Xiaolong Wang, Siliang Xiang, Cong Liu, Wenwu Hu and Yixin Shi

Agriculture 2026, 16(4), 454; https://doi.org/10.3390/agriculture16040454 (registering DOI) - 14 Feb 2026

We aim to address the insufficient robustness of navigational line detection for rapeseed seed production sires in complex field scenarios and the challenges faced by existing models in balancing precision, real-time performance, and resource consumption. Taking YOLOv8n-seg as the baseline, we first introduced [...] Read more.

We aim to address the insufficient robustness of navigational line detection for rapeseed seed production sires in complex field scenarios and the challenges faced by existing models in balancing precision, real-time performance, and resource consumption. Taking YOLOv8n-seg as the baseline, we first introduced the ADown module to mitigate feature subsampling information loss and enhance computational efficiency. Subsequently, the DySample module was employed to strengthen target feature representation and improve object discrimination in complex scenarios. Finally, the c2f module was replaced with c2f_FB to optimise feature fusion and reinforce multi-scale feature integration. Performance was evaluated through comparative experiments, ablation studies, and scenario testing. The model achieves an average precision of 99.2%, mAP50-95 of 84.5%, a frame rate of 90.21 frames per second, and 2.6 million parameters, demonstrating superior segmentation performance in complex scenarios. SegNav-YOLOv8n balances performance and resource requirements, validating the effectiveness of the improvements and providing reliable technical support for navigating agricultural machinery in rapeseed seed production. Full article

(This article belongs to the Topic Intelligent Agriculture: Perception Technologies and Agricultural Equipment for Crop Production Processes)

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21 pages, 4884 KB

Open AccessArticle

Pyramiding of Low-Nitrogen-Responsive QTL Clusters Enhances Yield and Nutrient-Use Efficiency in Barley

by Bing-Jie Chen, Yao Hou, Zhao-Yong Zeng, Yuan-Feng Huo, De-Yi Hu, Li Yin, Ying-Gang Xu, Yang Li, Shu Yuan and Guang-Deng Chen

Agriculture 2026, 16(4), 453; https://doi.org/10.3390/agriculture16040453 (registering DOI) - 14 Feb 2026

Given that nitrogen (N) is a major limiting factor for global crop production, improving low-nitrogen (LN) tolerance in barley is essential for sustaining yields worldwide. Building on our laboratory’s previous quantitative trait locus (QTL) mapping, which identified three LN-specific QTL clusters on chromosomes [...] Read more.

Given that nitrogen (N) is a major limiting factor for global crop production, improving low-nitrogen (LN) tolerance in barley is essential for sustaining yields worldwide. Building on our laboratory’s previous quantitative trait locus (QTL) mapping, which identified three LN-specific QTL clusters on chromosomes 2H and 5H, this study investigated the potential of gene pyramiding to improve LN tolerance. We generated two recombinant inbred line populations (C79 and F79) containing these QTLs and evaluated them for thirty-six traits related to yield, agronomy, and N, phosphorus (P), and potassium (K) uptake and utilization. The results confirmed that LN stress significantly reduced most yield, agronomic, and NPK-related traits. Under LN conditions, grain yield and accumulations of N, P, and K in the C79 population increased with the number of QTL clusters harbored by the lines. More compellingly, in the F79 population under LN stress, lines containing all three QTL clusters exhibited superior performance for critical yield components such as grain yield, spike number, grain number, and nutrient efficiency indices. Furthermore, in both populations, lines with the full QTL complement demonstrated higher values for harvest index, grain number, and K harvest index under LN stress than under normal-N conditions. In conclusion, this study is the first to link LN-QTL pyramiding with P and K use efficiency and demonstrates that pyramiding breeding can produce high-yielding barley varieties with enhanced LN tolerance and nutrient absorption capacity. Full article

(This article belongs to the Special Issue Molecular Breeding and Agronomic Traits Improvement of Triticeae Crops)

37 pages, 1334 KB

Open AccessReview

Mechanism and Application of Microbial Amendments in Saline–Alkali Soil Restoration: A Review

by Xiaoxue Zhang, Zhengjiaoyi Wang, Ming Zhang, Shaojie Zhang, Rong Ma and Shaokun Wang

Agriculture 2026, 16(4), 452; https://doi.org/10.3390/agriculture16040452 (registering DOI) - 14 Feb 2026

Saline–alkali soil salinization is a global ecological crisis affecting 932 million hectares of land worldwide, posing a severe threat to food security and ecological sustainability. Traditional improvement methods, such as chemical amendments and hydraulic engineering, are limited by high costs and environmental risks, [...] Read more.

Saline–alkali soil salinization is a global ecological crisis affecting 932 million hectares of land worldwide, posing a severe threat to food security and ecological sustainability. Traditional improvement methods, such as chemical amendments and hydraulic engineering, are limited by high costs and environmental risks, whereas microbial amendments have emerged as eco-friendly and sustainable alternatives due to their ability to regulate soil microenvironments and enhance plant stress resistance. However, a comprehensive synthesis of their core mechanisms, global application progress, and regional adaptation characteristics is still lacking, hindering the standardization and promotion of related technologies. This review, conducted in accordance with PRISMA guidelines, systematically synthesizes 112 core studies (1990–2025) retrieved from Web of Science, Scopus, and CNKI databases, focusing on three core research objects: salt-tolerant microbial communities in saline–alkali soils (dominant taxa, functional genes, metabolic characteristics), development and optimization of microbial amendments (strain screening, composite formulation, carrier selection), and mechanisms and application effects of microbial remediation (soil–plant–microbe interactions, physicochemical improvement, crop growth promotion). Key findings include the following. (1) Dominant microbial taxa (e.g., Proteobacteria, Actinobacteria) exhibit region-specific adaptation strategies, with salt tolerance thresholds and functional characteristics varying by soil type (coastal vs. inland saline–alkali soils). (2) Composite microbial amendments, especially those combined with biochar or organic fertilizers, achieve synergistic effects in desalination, alkali reduction, and fertility improvement. (3) Core mechanisms involve organic acid-mediated pH regulation, EPS-driven ion adsorption, and plant hormone-induced stress tolerance. (4) Microbial remediation technologies have been successfully applied globally (e.g., China, Africa, Americas), resulting in average crop yield increases of 15–42% and soil salinity reductions of 30–50%. This review provides a standardized technical framework for the development and application of microbial amendments, offers theoretical support for region-specific remediation strategies, identifies key challenges (e.g., strain stability, cost control) and future research directions (e.g., gene-edited strains, smart monitoring integration), and thus facilitates the industrialization and large-scale promotion of microbial remediation technologies to address global saline–alkali soil issues. Full article

(This article belongs to the Special Issue Factors Affecting Soil Fertility and Improvement Measures)

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24 pages, 1294 KB

Open AccessArticle

E-Commerce and Agricultural Development: Evidence from a Quasi-Natural Experiment in China

by Qinlei Jing, Jindi Yang and Wenguang Zhang

Agriculture 2026, 16(4), 451; https://doi.org/10.3390/agriculture16040451 (registering DOI) - 14 Feb 2026

Agricultural development is vital to rural economies in developing countries. Rural e-commerce has emerged as an important instrument for promoting rural economic transformation, yet its impact on agricultural development remains underexplored. Using panel data for 1345 counties in China from 2010 to 2022, [...] Read more.

Agricultural development is vital to rural economies in developing countries. Rural e-commerce has emerged as an important instrument for promoting rural economic transformation, yet its impact on agricultural development remains underexplored. Using panel data for 1345 counties in China from 2010 to 2022, this study exploits a quasi-natural experiment created by the phased implementation of the Rural E-Commerce Demonstration County (REDC) program and applies a staggered difference-in-differences approach to identify its causal effects on agricultural development. The results show that the REDC program significantly promotes agricultural development, mainly through expanded consumer demand and greater social investment. Its effects are particularly evident in regions with balanced production and consumption and in economically developed counties. Moreover, the REDC program shows no evidence of a significant negative siphon effect within 50 km of pilot counties but generates strong positive spillovers in the 50–200 km surrounding range. Taken together, these findings provide empirical evidence supporting the advancement of rural e-commerce and agricultural scaling in China, while also offering policy implications for other developing countries seeking to promote rural e-commerce. Full article

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

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31 pages, 2566 KB

Open AccessReview

Advancing Poultry Nutrition: AI Innovations for Sustainable Nutrient Requirements of Poultry: A Review

by Ahmed A. A. Abdel-Wareth and Ahmed Abdelmoamen Ahmed

Agriculture 2026, 16(4), 450; https://doi.org/10.3390/agriculture16040450 (registering DOI) - 14 Feb 2026

The poultry sector plays a crucial role in global food production by meeting the growing demand for affordable, nutritious protein sources. However, it faces significant challenges in providing sustainable and cost-effective nutritional solutions that improve poultry health, performance, and product quality. Recent advancements [...] Read more.

The poultry sector plays a crucial role in global food production by meeting the growing demand for affordable, nutritious protein sources. However, it faces significant challenges in providing sustainable and cost-effective nutritional solutions that improve poultry health, performance, and product quality. Recent advancements in artificial intelligence (AI) have the potential to enhance poultry nutrition through the development of precise feeding strategies. AI helps monitor and optimize nutrient intake, thereby boosting feed efficiency, reducing waste, and lowering costs. This article examines how AI-driven innovations may advance the management of poultry feed ingredients, nutrient monitoring, and dietary formulations. By utilizing AI tools such as machine learning algorithms and real-time data analytics, poultry producers can track and assess the nutritional needs of individual birds. This allows for the development of more precise feed formulations tailored to the specific needs of different age groups, breeds, and environmental conditions. These AI technologies help select the best feed ingredients and enable precise adjustments to nutrient composition. This results in healthier birds, better feed conversion rates, and higher-quality poultry products. Additionally, AI advancements help reduce the environmental impact of poultry farming by reducing feed waste and resource consumption. This article highlights how AI-driven insights enhance decision-making, enabling the poultry industry to grow sustainably while promoting animal welfare, increasing efficiency, and producing high-quality poultry products that meet consumer expectations for both sustainability and nutritional value. Full article

(This article belongs to the Section Farm Animal Production)

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19 pages, 590 KB

Open AccessArticle

Formulation of Nutrient Solutions Using Simulated Annealing

by Juan Pablo Guerra Ibarra, Francisco Javier Cuevas de la Rosa and Aaron Junior Rocha Rocha

Agriculture 2026, 16(4), 449; https://doi.org/10.3390/agriculture16040449 (registering DOI) - 14 Feb 2026

Modern agriculture requires optimizing available resources to maximize production while minimizing environmental impact without increasing economic costs. Hydroponic agriculture replaces soil with inert media that provide physical support for plants but do not supply nutrients. In this type of agricultural production, fertilization with [...] Read more.

Modern agriculture requires optimizing available resources to maximize production while minimizing environmental impact without increasing economic costs. Hydroponic agriculture replaces soil with inert media that provide physical support for plants but do not supply nutrients. In this type of agricultural production, fertilization with nutrient solutions is essential, as they supply the 15 elements necessary for proper plant development. These solutions consist of mixtures of different amounts of fertilizers dissolved in water. In this context, a method based on a simulated annealing algorithm is proposed, a metaheuristic that optimizes fertilizer quantities in grams to achieve target concentrations in parts per million for six macronutrients and nine micronutrients. The algorithm addresses a multi-objective optimization problem, balancing two competing goals: first, maximizing the accuracy of the fertilizer balance to achieve the required nutritional levels, and second, minimizing the total cost of the fertilizer mixture. The algorithm’s fitness function weights the total cost of the fertilizers used and the total relative error between the concentrations obtained and those desired, allowing the relative importance of cost and accuracy in the nutrient solution to be adjusted. The results of three experiments with varying nutrient levels are presented for a 1000-L water tank. The first experiment consisted of three macronutrients and two micronutrients. The second configuration added three macronutrients and two micronutrients, for a total of ten nutrients. Finally, five micronutrients were added to complete the 15 essential nutrients for plants. It is important to note that there are several methods for calculating micronutrients that contribute to precision agriculture, increasing the complexity of finding a solution that meets established nutritional requirements. The nutrient concentrations in parts per million required for tomato cultivation during the vegetative development stage. To balance nutrient accuracy and solution cost, we applied weighting factors of

0.65, 0.75, 0.85, 0.90, 0.95,

and

1.0

for accuracy. The corresponding weights for cost were calculated as the complement of these values (totaling 1). By favoring nutrient accuracy with a weighting of 1, accuracies of 0.00500, 0.02618, and 0.03077 parts per million were achieved in each experiment, respectively. Meanwhile, the lowest cost is

2.06

,

2.72

, and

2.70

USD for the aforementioned experiments. Full article

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

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22 pages, 4080 KB

Open AccessArticle

Land Use Classification, Prediction, and the Relationship Between Land Use and Sediment Loss in the Lam Phra Phlong Watershed, Thailand

by Uma Seeboonruang, Ranadheer Mandadi, Prapas Thammaboribal, Arlene L. Gonzales and Satya Venkata Sai Aditya Bharadwaz Ganni

Agriculture 2026, 16(4), 448; https://doi.org/10.3390/agriculture16040448 (registering DOI) - 14 Feb 2026

This study aims to assess the evolution of land cover in the Lam Phra Phloeng (LPP) watershed and predict future land use patterns. By employing the Gray Level Co-occurrence Matrix (GLCM) and several spectral indices, high classification accuracy (>92%) was achieved using the [...] Read more.

This study aims to assess the evolution of land cover in the Lam Phra Phloeng (LPP) watershed and predict future land use patterns. By employing the Gray Level Co-occurrence Matrix (GLCM) and several spectral indices, high classification accuracy (>92%) was achieved using the Random Forest (RF) algorithm. Based on classified land use maps from 2003 and 2023, future land use predictions for 2030, and 2050 were generated using the CA-Markov chain model. The predictions suggest a gradual trend toward deforestation and the expansion of croplands, driven by population growth and increased anthropogenic activity in the region. The Sediment Delivery Ratio (SDR) model, part of the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) suite, was used to simulate soil loss in the LPP watershed. The results indicate minimal soil loss in vegetated areas and significant erosion in regions adjacent to water bodies, primarily due to rainfall erosivity. This research highlights the social, ecological, and economic implications of land use change. Furthermore, best management practices (BMPs) are identified as effective strategies for land restoration and erosion reduction. The study also discusses three widely adopted soil erosion control techniques, providing recommendations for reforestation and erosion mitigation programmes. Full article

(This article belongs to the Section Agricultural Water Management)

32 pages, 4123 KB

Open AccessArticle

Design and Experiment of Electromagnetic Vibration Lime Spreader

by Xinge Wang, Xueguan Zhao, Xiaoyong Liao, Chunfeng Zhang, Yunbing Gao, Zhanwei Ma, Changyuan Zhai and Liping Chen

Agriculture 2026, 16(4), 447; https://doi.org/10.3390/agriculture16040447 (registering DOI) - 14 Feb 2026

To address the low application accuracy and poor spreading uniformity of conventional lime spreaders, an electromagnetic vibration-assisted variable-rate lime spreader integrating a shaftless screw metering mechanism was developed. The overall configuration and operating principle are presented. Considering the physicochemical characteristics of lime powder, [...] Read more.

To address the low application accuracy and poor spreading uniformity of conventional lime spreaders, an electromagnetic vibration-assisted variable-rate lime spreader integrating a shaftless screw metering mechanism was developed. The overall configuration and operating principle are presented. Considering the physicochemical characteristics of lime powder, including fine particle size, strong drift tendency, and poor flowability, a shaftless screw metering unit was designed to improve discharge stability and metering accuracy. To enhance dispersion uniformity, a vertical electromagnetic vibration device was developed, and its key parameters were determined through a theoretical analysis of vibration frequency and amplitude. In addition, the structure and kinematic parameters of the spreading disc were optimized by analyzing particle trajectories and outlet distribution patterns. A closed-loop feedback control strategy was implemented to enable precise variable-rate application. Static bench tests demonstrated a metering accuracy of 96.42%, and the dispersion uniformity was at least 84.14% at an electromagnetic vibration frequency of 10 to 18 Hz. Field evaluations further showed that the coefficient of variation for transverse uniformity was no more than 17.88%, while the maximum coefficient of variation for longitudinal stability was 18.09%. These results indicate that the proposed spreader satisfies the operational requirements for accurate and uniform variable-rate application of lime powder. Full article

(This article belongs to the Section Agricultural Technology)

37 pages, 5815 KB

Open AccessReview

Current Status and Future Prospects of Simulation Technology in Cleaning Systems for Crop Harvesters

by Peng Chen, Hongguang Yang, Chenxu Zhao, Jiayong Pei, Fengwei Gu, Yurong Wang, Zhaoyang Yu and Feng Wu

Agriculture 2026, 16(4), 446; https://doi.org/10.3390/agriculture16040446 (registering DOI) - 14 Feb 2026

The performance of the cleaning system in crop harvesters directly impacts overall operational efficiency and harvest quality. Against the background of traditional design relying on physical experiments—which is costly and provides limited mechanistic insight—Discrete Element Method (DEM), Computational Fluid Dynamics (CFD), and their [...] Read more.

The performance of the cleaning system in crop harvesters directly impacts overall operational efficiency and harvest quality. Against the background of traditional design relying on physical experiments—which is costly and provides limited mechanistic insight—Discrete Element Method (DEM), Computational Fluid Dynamics (CFD), and their coupled simulation (CFD-DEM) have become key means for in-depth study of the cleaning process, capable of revealing the complex interactions between particles and between particles and airflow. With the increasingly widespread and deep application of computer simulation technology in agricultural machinery research and development, it is particularly necessary to systematically review its research progress in cleaning systems. Therefore, this study provides a comprehensive and systematic analysis and summary of the key technologies in cleaning system simulation, aiming to address the current gap in systematic reviews of simulation technology in this field. Compared with previous studies that mostly focus on a single method or a specific crop type, this paper systematically reviews the application of three simulation technologies in cleaning systems of various crop harvesters. First, based on the working principle and core operational challenges of cleaning systems, the necessity of applying simulation technology is clarified. Second, the basic principles, modeling processes, and suitable application scenarios and key points for the cleaning simulation of each method are analyzed. Third, typical cases are reviewed to summarize their key achievements in structural innovation, parameter optimization of cleaning devices, and revealing the mechanisms of material separation. Finally, current bottlenecks in simulation applications are pointed out, and future development directions are outlined, including high-precision multi-field coupling, integration with intelligent algorithms, and the construction of digital twin systems. This study aims to provide systematic theoretical reference and methodological support for the innovative design and performance improvement of cleaning systems. Full article

(This article belongs to the Section Agricultural Technology)

34 pages, 4463 KB

Open AccessReview

Climate-Resilient Soybean: Integrated Breeding Strategies for Mitigating Drought and Heat Stress

by Kyung-Hee Kim, Sun Hee Lim, Sung Don Lim, Jungmin Ha and Byung-Moo Lee

Agriculture 2026, 16(4), 445; https://doi.org/10.3390/agriculture16040445 (registering DOI) - 14 Feb 2026

Soybean (Glycine max (L.) Merr.) plays a pivotal role in global food security as a primary source of vegetable protein and oil. However, its production is increasingly jeopardized by the frequent concurrence of drought and heat stress, a scenario predicted to intensify [...] Read more.

Soybean (Glycine max (L.) Merr.) plays a pivotal role in global food security as a primary source of vegetable protein and oil. However, its production is increasingly jeopardized by the frequent concurrence of drought and heat stress, a scenario predicted to intensify under ongoing climate change. While the effects of individual stresses have been well documented, the combined occurrence of drought and heat imposes unique physiological challenges, such as the conflict between stomatal closure for water conservation and transpirational cooling, that critically impair yield stability. This review provides a comprehensive synthesis of the physiological and molecular mechanisms governing soybean responses to these combined stresses, with a specific focus on modifications of root system architecture and the sensitivity of biological nitrogen fixation. We critically analyze recent advances in genomic resources, highlighting key quantitative trait loci (QTLs) and candidate genes identified through genome-wide association studies (GWAS) and multi-omics integration. Furthermore, we propose integrated breeding strategies that bridge conventional breeding with cutting-edge technologies, including high-throughput phenotyping, speed breeding, and CRISPR/Cas9-mediated genome editing, underpinned by high-throughput phenotyping and speed breeding. By presenting a roadmap for developing climate-smart soybean cultivars, this review aims to support sustainable agricultural practices that ensure both adaptation and mitigation in a changing climate. Full article

(This article belongs to the Special Issue Climate Change in Agriculture: An Interdisciplinary Approach to Adaptation and Mitigation)

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20 pages, 1564 KB

Open AccessArticle

Genetic Control, Stability, and Multivariate Analysis of Wheat Seed Quality Traits in Elite Pure Lines Under Mediterranean Environments

by Vasileios Greveniotis, Elisavet Bouloumpasi, Adriana Skendi, Stylianos Zotis, Dimitrios Kantas and Constantinos G. Ipsilandis

Agriculture 2026, 16(4), 444; https://doi.org/10.3390/agriculture16040444 (registering DOI) - 14 Feb 2026

Grain quality traits in wheat (Triticum aestivum L.), including protein content, gluten strength, and carbohydrate composition, are key determinants of end-use performance and breeding potential. This study assessed the genetic variability, stability, and multivariate relationships of seed quality traits among elite F7 [...] Read more.

Grain quality traits in wheat (Triticum aestivum L.), including protein content, gluten strength, and carbohydrate composition, are key determinants of end-use performance and breeding potential. This study assessed the genetic variability, stability, and multivariate relationships of seed quality traits among elite F7 pure lines derived from six long-term cultivated wheat cultivars. Field trials were conducted across six contrasting environments to evaluate genotype, environment, and genotype × environment (G × E) effects on crude protein, fat, ash, starch, crude fiber, Zeleny sedimentation, carbohydrates, non-starch carbohydrates, and moisture. Combined ANOVA revealed that genotypic effects accounted for the largest proportion of variation, though significant environmental and G × E effects were also observed. Broad-sense heritability was high for protein, Zeleny, and carbohydrate content. Stability analysis using the Stability Index (SI) highlighted A1, A2, A4, C2, E1, and F2 as genotypes combining high mean performance with a consistent expression across all environments. Principal component analysis (PCA) illustrated key trait relationships and trade-offs, particularly the negative association between protein-related traits and carbohydrate accumulation, while revealing the partial clustering of genotypes with similar quality profiles. AMMI and GGE biplots further supported broad adaptation for some genotypes (e.g., E1, F4, E2 for crude protein; F3, F4, E2 for Zeleny) and trait- or environment-specific performance for others. Correlation analyses confirmed positive associations between protein and gluten strength, and negative correlations with carbohydrate traits. Overall, targeted pure-line selection effectively exploits intracultivar genetic variation, offering a practical strategy for identifying superior, resilient wheat lines for breeding programs across diverse environments. Full article

(This article belongs to the Section Seed Science and Technology)

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20 pages, 405 KB

Open AccessReview

Phytobiotics as Dietary Natural Growth Promoters in Producing High-Quality and Safe Poultry Products—A Narrative Review

by Laurian-Cristian Cojocariu, Marius-Giorgi Usturoi, Alexandru Usturoi, Mircea Lazăr, Ioana Miruna Balmuș, Daniel Simeanu and Răzvan-Mihail Radu-Rusu

Agriculture 2026, 16(4), 443; https://doi.org/10.3390/agriculture16040443 (registering DOI) - 14 Feb 2026

As the demand for poultry meat and eggs is increasing in the world, and the use of antibiotics is forbidden in Europe (since 2006), with countries such as the Philippines, Thailand, Bangladesh and China having imposed restriction or prohibitions, researchers and producers have [...] Read more.

As the demand for poultry meat and eggs is increasing in the world, and the use of antibiotics is forbidden in Europe (since 2006), with countries such as the Philippines, Thailand, Bangladesh and China having imposed restriction or prohibitions, researchers and producers have sought for effective non-antibiotic alternatives. Probiotics, prebiotics, synbiotics and phytobiotics are frequently used as alternatives in the field of poultry production. Phytobiotics, plant-derived substances, also referred to as botanicals or phytogenics, are used as animal diets supplements due to their wide range of bioactive compounds (menthol, curcumin, eugenol, allicin and others) and many advantages. They are classified as herbs, spices, plant extracts and essential oils. Some of the benefits offered by the dietary phytobiotics are antimicrobial, antioxidant, digestion stimulant, anti-inflammatory, immunomodulatory, carminative, antiseptic and appetite stimulant, the modulation of gut microbiota and improvement in the intestinal histology. Some representatives of phytobiotics are turmeric, oregano, sage, thyme, black pepper, ginger, garlic, echinacea, rosemary and others. Despite the significant potential of phytobiotics, their widespread adaptation is currently inhibited by challenges regarding cost-effectiveness (high price for raw materials), scarce regulatory frameworks, and inconsistent biological efficacy. The lack of standardization reflects a dual challenge, enclosing both the inherent chemical variability of raw botanical materials and the technical inconsistencies present throughout the industrial manufacturing, and extraction processes as producers use different machinery for extracting and producing the animal feed. To address these systemic impediments, a joint effort across the entire value chain—from primary producers to regulatory authorities—is essential for the development of unified testing protocols and standardization dosage guidelines that ensure the pharmacological safety and reliability of phytobiotic products. Full article

(This article belongs to the Special Issue Quality Assessment and Processing of Farm Animal Products)

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16 pages, 1237 KB

Open AccessArticle

Biosecurity Practices on Small- and Medium-Scale Dairy Farms in Northern Kosovo: A Risk-Based Scoring Assessment

by Blerta Mehmedi, Diellor Voca, Curtis R. Youngs, Claude Saegerman, Arben Sinani, Behlul Behluli, Sadik Heta and Armend Cana

Agriculture 2026, 16(4), 442; https://doi.org/10.3390/agriculture16040442 (registering DOI) - 14 Feb 2026

Biosecurity plays a central role in preventing disease transmission in dairy production systems and animal welfare. However, quantitative data on biosecurity implementation in smallholder and medium-scale dairy farms remains inconsistent, especially in developing countries. This study provides a structured assessment of on-farm biosecurity [...] Read more.

Biosecurity plays a central role in preventing disease transmission in dairy production systems and animal welfare. However, quantitative data on biosecurity implementation in smallholder and medium-scale dairy farms remains inconsistent, especially in developing countries. This study provides a structured assessment of on-farm biosecurity practices in northern Kosovo using a standardized, risk-based scoring approach. A cross-sectional survey was conducted on 55 dairy farms using the unmodified Biocheck.UGent™ dairy questionnaire. External and internal biosecurity scores were calculated through predefined, weighted algorithms and analyzed using non-parametric descriptive statistics. Farm-level results were subsequently compared with international reference values derived from the Biocheck.UGent™ global database. The median biosecurity scores for Kosovo farms were 47.8% for external biosecurity and 29.0% for internal biosecurity, indicating uneven implementation with pronounced weaknesses in measures designed to limit within-herd transmission. The lowest-scoring domains were purchase and reproduction and feed and water within external biosecurity, and working organization and equipment, calf management, and calving management within internal biosecurity. In contrast, visitors and farmworkers, control of vermin and other animals among external measures, and adult cattle management among internal measures, showed relatively higher scores, although all remained below international reference levels. When compared with the global overall biosecurity reference median of 76.7% derived from the Biocheck.UGent™ database, the biosecurity performance of the surveyed dairy farms in Kosovo was substantially lower. This gap does not indicate a complete absence of biosecurity measures but rather an uneven application, with the most pronounced deficiency observed in routine practices that govern within-herd disease transmission. The use of a risk-based scoring system allowed these weaknesses to be identified in a structured manner and placed the Kosovo results within an international benchmarking framework. In this context, the approach functions as a practical diagnostic tool, enabling farmers and veterinarians to prioritize feasible, epidemiological-relevant improvements within small- and medium-scale dairy production settings. Full article

(This article belongs to the Special Issue Biosecurity for Animal Premises in Action)

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21 pages, 718 KB

Open AccessArticle

Do Integrated CMD Management Practices Increase Cassava Yields? A Local Average Treatment Effect Analysis from Burkina Faso

by Agnès Ouédraogo, Eveline Sawadogo-Compaore, Ezechiel Bionimian Tibiri, Noël Thiombiano, Adama Sagnon, Seydou Sawadogo, Fidèle Tiendrébéogo and Justin Simon Pita

Agriculture 2026, 16(4), 441; https://doi.org/10.3390/agriculture16040441 - 13 Feb 2026

Cassava mosaic disease (CMD) is a major constraint to cassava production in sub-Saharan Africa, particularly in Burkina Faso, where it poses a serious threat to rural food security. This study examined the impact of adopting innovative cassava mosaic disease management practices on cassava [...] Read more.

Cassava mosaic disease (CMD) is a major constraint to cassava production in sub-Saharan Africa, particularly in Burkina Faso, where it poses a serious threat to rural food security. This study examined the impact of adopting innovative cassava mosaic disease management practices on cassava yields in the Guiriko and Nando regions of Burkina Faso. To address potential biases arising from differences in characteristics between adopters and non-adopters, an econometric approach based on the instrumental variables (IV) method within a counterfactual framework was employed to estimate the local average treatment effect (LATE). The data were drawn from a survey conducted in September 2023 among 511 cassava producers. The results indicate that the adoption of innovative cassava mosaic disease management practices had a positive and statistically significant effect on agricultural yields. Productivity gains were estimated at 29% in the Guiriko region and 41% in the Nando region, highlighting spatial heterogeneity in impacts. These findings suggest that promoting the diffusion of such practices can substantially improve cassava productivity and reduce the vulnerability of rural households. In addition, the analysis showed that socioeconomic and technical factors, including farmers’ age, membership in cassava producer organizations, household income levels, and the use of chemical fertilizers, also influence productivity outcomes. Overall, the study underscores the importance of strengthening agricultural extension services, supporting producer organizations, and promoting appropriate technologies to maximize the benefits of cassava mosaic disease management practices for food security and rural development. Full article

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

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18 pages, 5207 KB

Open AccessArticle

Establishment of a Breakable Layered Bonding Model for Peanut Pods Based on the DEM and Research on the Shelling Process

by Tianyue Xu, Xiaoman Tang, Yajun Yu, Xinming Jiang and Chunrong Li

Agriculture 2026, 16(4), 440; https://doi.org/10.3390/agriculture16040440 - 13 Feb 2026

The peanut, a globally important oil and economic crop, has thin, brittle pods that are prone to breakage under external forces during mechanical harvesting, transportation, and processing. To minimize this loss and reduce production costs, we conducted an in-depth study of the pod-breaking [...] Read more.

The peanut, a globally important oil and economic crop, has thin, brittle pods that are prone to breakage under external forces during mechanical harvesting, transportation, and processing. To minimize this loss and reduce production costs, we conducted an in-depth study of the pod-breaking process by integrating manual and automatic filling approaches within the discrete element method (DEM) with the Hertz–Mindlin with bonding model. A breakable layered bonding model for peanut pods was developed, which is capable of precisely characterizing the disparities in the mechanical properties of peanut pod shells and kernels. Physical tests were performed to obtain the relevant contact parameters of peanut pods. Compression tests combined with calibration approaches were employed to identify the bonding parameters of peanut pods, which are not easily accessible via direct experimental measurements. The optimal combination of simulation parameters for the model was determined via a Plackett–Burman test, steepest ascent test, and Box–Behnken test. The results indicated that the critical normal stress between pod shells is the most significant influencing factor. The optimal parameter combination for the proposed model is as follows: the normal stiffness per unit area between pod shells is 7.81 × 10¹⁰ N/m³, the shear stiffness per unit area between pod shells is 9.00 × 10⁸ N/m³, the critical normal stress between pod shells is 2.17 × 10⁵ N/m³, and the critical shear stress between pod shells is 2.25 × 10⁵ N/m³. The established layered bonding model for breakable peanut pods was validated using both cylinder-lifting simulation tests and physical shelling experiments. The relative error in the angle of repose between the cylinder-lifting simulation and physical tests was 1.6%, while the deviation in the shelling experiment was only 0.7%. This model provides a theoretical foundation for the design and optimization of machinery used in peanut pod harvesting, transportation, and processing. Full article

(This article belongs to the Section Agricultural Technology)

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17 pages, 944 KB

Open AccessArticle

Quantifying the Spread and Economic Consequences of the Codling Moth (Cydia pomonella) in China Using Biomod2 and Monte Carlo Synergy

by Shengkang Zou, Zhongxiang Sun, Hongkun Huang, Xiaoqing Xian and Guifen Zhang

Agriculture 2026, 16(4), 439; https://doi.org/10.3390/agriculture16040439 - 13 Feb 2026

The codling moth, Cydia pomonella (Linnaeus, 1758) (Lepidoptera: Tortricidae), was first detected in Xinjiang, China, in 1953 and has since spread to nine provinces, with its distribution continuing to expand into other apple- and pear-producing regions. In this study, we combined the Biomod2 [...] Read more.

The codling moth, Cydia pomonella (Linnaeus, 1758) (Lepidoptera: Tortricidae), was first detected in Xinjiang, China, in 1953 and has since spread to nine provinces, with its distribution continuing to expand into other apple- and pear-producing regions. In this study, we combined the Biomod2 model with Monte Carlo simulations to perform a spatially explicit, pixel-level assessment of the moth’s potential habitat suitability and associated economic impacts in China’s major fruit-producing areas. Results indicate that temperature is the primary factor limiting its distribution, followed by human activities, while topography plays a regulatory role at local scales. The Loess Plateau and Bohai Rim regions were identified as core suitable areas, with moderate suitability in the Northern Cold region and Xinjiang and lower suitability in the Southwest and Yangtze River Basin. Pearson correlation analysis revealed weak spatial coupling between suitable habitats and fruit yields. Monte Carlo simulations showed that potential economic losses vary spatially across regions and crop types. These findings suggest that the codling moth’s suitability differs among regions; high-yield areas do not necessarily face higher invasion risk, but once an invasion occurs, economic losses tend to be concentrated and severe. Accordingly, early warning and region-specific, differentiated management should be prioritized in key areas to mitigate damage. Full article

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

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