Agriculture

19 pages, 2626 KiB

Open AccessArticle

Calibration of Parameters for Leaf-Stem-Cutting Model of Tuber Mustard (Brassica juncea L.) Based on Discrete Element Method

by Man Gu, Haiyang Shen, Weiwen Luo, Jie Ling, Bokai Wang, Fengwei Gu, Shumin Song, Liang Pan and Zhichao Hu

Agriculture 2025, 15(7), 773; https://doi.org/10.3390/agriculture15070773 - 2 Apr 2025

Abstract

The cutting of leaf stems is a critical step in the mechanized harvesting of tuber mustard (Brassica juncea L.). This study focuses on the calibration of parameters for the discrete element model of mustard leaf stems to visualize the cutting process and [...] Read more.

The cutting of leaf stems is a critical step in the mechanized harvesting of tuber mustard (Brassica juncea L.). This study focuses on the calibration of parameters for the discrete element model of mustard leaf stems to visualize the cutting process and facilitate numerical simulations. Intrinsic material properties were measured based on mechanical testing, and EDEM2022 simulation software was utilized to calibrate the model parameters. The Hertz–Mindlin (no-slip) model was employed to simulate the stacking angle of mustard leaf stems, and the contact parameters for the discrete element model were determined using a combination of two-level factorial design, steepest ascent, and CCD (central composite design) tests. The results showed that the coefficient of restitution, coefficient of static friction, and coefficient of rolling friction for the leaf stems were 0.45, 0.457, and 0.167, respectively, while for interactions between the leaf stems and the working parts, these values were 0.45, 0.55, and 0.175, respectively. Based on the Hertz–Mindlin with bonding model, the primary bonding parameters were calculated, and a BBD (Box–Behnken design) test was applied for optimization. The comparison between the simulation and experimental results showed that the relative error in the maximum shear force was within 5%, indicating that the calibrated model can serve as a reliable theoretical reference for the design and optimization of tuber mustard harvesting and cutting equipment. Full article

(This article belongs to the Section Agricultural Technology)

21 pages, 1183 KiB

Open AccessArticle

The Impact of Dissolved Biochar on Oxidative Stress and Its Effect on the Virulence of Steinernema feltiae: Implications for Biocontrol Efficiency

by Xinrui Wang, Jie Li, Jing Li, Lan Luo, Gang Li, Weibin Ruan and Guilong Zhang

Agriculture 2025, 15(7), 772; https://doi.org/10.3390/agriculture15070772 - 2 Apr 2025

Abstract

Dissolved biochar (DBC) can make a significantly impact on soil ecosystems and the associated biota due to its high environmental bioavailability. However, the impact of DBC on the adaptability of entomopathogenic nematodes (EPNs), such as Steinernema feltiae, remains uncertain. This study investigates [...] Read more.

Dissolved biochar (DBC) can make a significantly impact on soil ecosystems and the associated biota due to its high environmental bioavailability. However, the impact of DBC on the adaptability of entomopathogenic nematodes (EPNs), such as Steinernema feltiae, remains uncertain. This study investigates the impact of DBC on oxidative stress, antioxidant enzyme activity, virulence, and gene expression in EPNs through culture assays and RNA-seq analysis. Results showed that DBC exposure significantly increased the accumulation of reactive oxygen species (ROS) accumulation. The nematodes treated with DBC700 exhibited 64.34% higher ROS levels, while those treated with DBC400 had 51.13% higher levels compared to the control. Superoxide dismutase (SOD) and catalase (CAT) activities were significantly suppressed, with a stronger inhibition observed in the DBC700 group. As revealed by virulence assays, DBC treatment reduced the infectivity of EPNs against Galleria mellonella larvae. Transcriptome analysis revealed that DBC primarily affected oxidative stress response, membrane transport, and longevity regulation pathways. Moreover, DBC400 predominantly inhibited carbohydrate metabolism, whereas DBC700 significantly impacted oxidative metabolism, protein processing, and neuronal signaling pathways, suggesting the presence of distinct metabolic adaptation mechanisms between the two DBCs. Overall, this study suggests that DBC may impair the biocontrol efficacy of S. feltiae through oxidative stress and genetic perturbations, providing new insights into its long-term ecological impacts on soil ecosystems. Full article

(This article belongs to the Special Issue Biochar Applications in Agricultural Soil Restoration)

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18 pages, 2248 KiB

Open AccessArticle

Real-Time Caterpillar Detection and Tracking in Orchard Using YOLO-NAS Plus SORT

by Sumesh Nair, Guo-Fong Hong, Chia-Wei Hsu, Chun-Yu Lin and Shean-Jen Chen

Agriculture 2025, 15(7), 771; https://doi.org/10.3390/agriculture15070771 - 2 Apr 2025

Abstract

Detecting and tracking caterpillars in orchard environments is crucial for advancing precision agriculture but remains challenging due to occlusions, variable lighting, wind interference, and the need for precise small-object detection. This study presents a real-time deep learning approach that integrates the YOLO-NAS object [...] Read more.

Detecting and tracking caterpillars in orchard environments is crucial for advancing precision agriculture but remains challenging due to occlusions, variable lighting, wind interference, and the need for precise small-object detection. This study presents a real-time deep learning approach that integrates the YOLO-NAS object detection model with the SORT tracking algorithm to overcome these challenges. Evaluated in a jujube orchard, the proposed method significantly improved small caterpillar detection and tracking. Using an RGB-D camera operating at 30 frames per second, the system successfully detected caterpillars measuring 2–5 cm at distances of 20–35 cm, corresponding to resolutions of 21 × 6 to 55 × 10 pixels. The integration of YOLO-NAS with SORT enhanced detection performance, achieving a ~9% increase in true positive detections and an ~8% reduction in false positives compared to YOLO-NAS alone. Even for the smallest caterpillars (21 × 6 pixels), the method achieved over 60% true positive detection accuracy without false positives within 1 s inference. With an inference time of just 0.2 milliseconds, SORT enabled real-time tracking and accurately predicted caterpillar positions under wind interference, further improving reliability. Additionally, selective corner tracking was employed to identify the head and tail of caterpillars, paving the way for future laser-based precision-targeting interventions focused on the caterpillar head. Full article

(This article belongs to the Section Digital Agriculture)

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21 pages, 1663 KiB

Open AccessArticle

Investigating the Impact of Sowing Date on Wheat Leaf Morphology Through Image Analysis

by Junfan Chen, Jianliang Wang, Jiacheng Wang, Zhian Wang, Lihan Zhao, Yaohua Yan, Jiayue Li, Hanzeyu Xu, Chengming Sun and Tao Liu

Agriculture 2025, 15(7), 770; https://doi.org/10.3390/agriculture15070770 - 2 Apr 2025

Abstract

The morphology of wheat leaves is a key indicator of crop stand quality and photosynthetic capacity, with sowing date being a critical factor influencing leaf morphology. To investigate the effects of sowing time on wheat growth, development, and leaf phenotypes, this study utilized [...] Read more.

The morphology of wheat leaves is a key indicator of crop stand quality and photosynthetic capacity, with sowing date being a critical factor influencing leaf morphology. To investigate the effects of sowing time on wheat growth, development, and leaf phenotypes, this study utilized image analysis technology to systematically extract key phenotypic traits of winter wheat leaves, including effective leaf area, leaf color, and leaf shape. The results demonstrated that delayed sowing significantly affected the morphology and color characteristics of winter wheat leaves. Specifically, leaf length and width exhibited a quadratic decreasing trend, resulting in an average reduction in leaf area of over 59%. Additionally, the greenness index (EXG) decreased by 25.84%, while the red pigment index (EXR) increased by 21.69%. Significant differences in leaf color changes were observed among the varieties. This study provides reliable data for determining the optimal sowing period for winter wheat and offers valuable guidance for optimizing field management strategies to enhance crop yield and quality. Full article

(This article belongs to the Special Issue AI-Powered UAVs and Imaging Systems for Precision Wheat and Rice Management)

22 pages, 3438 KiB

Open AccessArticle

Optimization Design and Experiment of Soil-Covering Device for Astragalus Mulching Transplanting Machine

by Bin Feng, Wei Sun, Shanglong Xin, Guanping Wang, Wenjing Lv and Junzeng Wang

Agriculture 2025, 15(7), 769; https://doi.org/10.3390/agriculture15070769 - 2 Apr 2025

Abstract

In response to the low efficiency and poor soil quality of the mechanized transplanting of Astragalus, and in combination with the agronomic requirements of Astragalus mulching and outcrop cultivation, an Astragalus film mulching transplanting machine was designed, which integrates functions such as trenching, [...] Read more.

In response to the low efficiency and poor soil quality of the mechanized transplanting of Astragalus, and in combination with the agronomic requirements of Astragalus mulching and outcrop cultivation, an Astragalus film mulching transplanting machine was designed, which integrates functions such as trenching, seedling feeding, mulching, and seed row soil covering. Firstly, based on the analysis of the overall structure of the transplanting machine, the structure and working principle of the soil-covering device are expounded, and the structure and working parameters of the soil-covering disc and soil-covering drum are clarified. In order to optimize the performance of the soil-covering device of the mulching transplanting machine and improve the quality of the covering soil, the Box–Behnken response surface test design method was adopted. The depth of disc extraction, the disc deflection angle, and the rotation speed of the soil-covering drum were selected as the main influencing factors. The quantity of soil cover and variation coefficient of soil cover quantity uniformity were used as the evaluation indicators for the quality of the operation, and parameter optimization experiments were conducted. By establishing a regression mathematical model between influencing factors and evaluation indicators, analyzing the interactive effects of each factor on response values, and comprehensively optimizing the model, the optimal parameter combination was obtained. The results of field experiments show that when the depth of disc extraction is 95 mm, the disc deviation angle is 40°, and the rotation speed of the soil-covering drum is 30 r/min, the corresponding quantity of soil cover and variation coefficient of soil cover quantity uniformity are 10.61 kg/m and 1.79%, respectively, which can meet the soil covering requirements. The research results can provide technical references for the structural optimization and performance improvement of the soil-covering device of the traditional Chinese medicine mulching transplanting machine. Full article

(This article belongs to the Section Agricultural Technology)

23 pages, 1334 KiB

Open AccessReview

Research Progress on the Improvement of Farmland Soil Quality by Green Manure

by Yulong Wang, Aizhong Yu, Yongpan Shang, Pengfei Wang, Feng Wang, Bo Yin, Yalong Liu, Dongling Zhang and Qiang Chai

Agriculture 2025, 15(7), 768; https://doi.org/10.3390/agriculture15070768 - 2 Apr 2025

Abstract

Long-term intensive agricultural management practices have led to a continuous decline in farmland soil quality, posing a serious threat to food security and agricultural sustainability. Green manure, as a natural, cost-effective, and environmentally friendly cover crop, plays a significant role in enhancing soil [...] Read more.

Long-term intensive agricultural management practices have led to a continuous decline in farmland soil quality, posing a serious threat to food security and agricultural sustainability. Green manure, as a natural, cost-effective, and environmentally friendly cover crop, plays a significant role in enhancing soil quality, ensuring food security, and promoting sustainable agricultural development. The improvement of soil quality by green manure is primarily manifested in the enhancement of soil physical, chemical, and biological properties. Specifically, it increases soil organic matter content, optimizes soil structure, enhances nutrient cycling, and improves microbial community composition and metabolic activity. The integration of green manure with agronomic practices such as intercropping, crop rotation, conservation tillage, reduced fertilizer application, and organic material incorporation demonstrates its potential in addressing agricultural development challenges, particularly through its contributions to soil quality improvement, crop yield stabilization, water and nutrient use efficiency enhancement, fertilizer input reduction, and agricultural greenhouse gas emission mitigation. However, despite substantial evidence from both research and practical applications confirming the benefits of green manure, its large-scale adoption faces numerous challenges, including regional variability in application effectiveness, low farmer acceptance, and insufficient extension technologies. Future research should further clarify the synergistic mechanism between green manure and agronomic measures such as intercropping, crop rotation, conservation tillage, reduced fertilization and organic material return to field. This will help explore the role of green manure in addressing the challenges of soil degradation, climate change and food security, develop green manure varieties adapted to different ecological conditions, and optimize green manure planting and management technologies. Governments should comprehensively promote the implementation of green manure technologies through economic incentives, technology extension, and educational training programs. The integration of scientific research, policy support, and technological innovation is expected to establish green manure as a crucial driving force for facilitating the global transition towards sustainable agriculture. Full article

(This article belongs to the Special Issue Soil Chemical Properties and Soil Conservation in Agriculture)

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36 pages, 647 KiB

Open AccessArticle

Irrigation, Nitrogen Supplementation, and Climatic Conditions Affect Resistance to Aspergillus flavus Stress in Maize

by Heltan M. Mwalugha, Krisztina Molnár, Csaba Rácz, Szilvia Kovács, Cintia Adácsi, Tamás Dövényi-Nagy, Károly Bakó, István Pócsi, Attila Dobos and Tünde Pusztahelyi

Agriculture 2025, 15(7), 767; https://doi.org/10.3390/agriculture15070767 - 2 Apr 2025

Abstract

Maize production is increasingly challenged by climate change, which affects plant physiology, fungal colonization, and mycotoxin contamination. Aspergillus flavus, a saprophytic fungus, thrives in warm, dry conditions, leading to aflatoxin B1 (AFB1) accumulation, and posing significant food safety risks. Macro- and micro-climatic [...] Read more.

Maize production is increasingly challenged by climate change, which affects plant physiology, fungal colonization, and mycotoxin contamination. Aspergillus flavus, a saprophytic fungus, thrives in warm, dry conditions, leading to aflatoxin B1 (AFB1) accumulation, and posing significant food safety risks. Macro- and micro-climatic factors, including temperature, humidity, and precipitation, influence kernel development, leaf wetness duration, and mycotoxin biosynthesis. Nitrogen availability and irrigation play crucial roles in modulating plant responses to these stressors, affecting chlorophyll content, yield parameters, and fungal interactions. To investigate these interactions, a Completely Randomized Design (CRD) was employed from 2020 to 2022 to assess physiological changes in SY Orpheus maize hybrid under varying climatic conditions. Rising temperatures and declining relative humidity (RH) significantly reduced kernel number per ear length from 25.60 ± 0.34 in 2020 to 17.89 ± 0.39 in 2022 (p < 0.05), impacting yield. The AFB1 levels peaked in 2021 (156.88 ± 59.02 µg/kg), coinciding with lower humidity and increased fungal stress. Water availability improved kernel numbers and reduced AFB1 accumulation (p < 0.05) but did not significantly affect the total fungal load (p > 0.05). Nitrogen supplementation enhanced plant vigor, suppressed AFB1 biosynthesis, and influenced spectral indices. Potential confounding factors such as soil variability and microbial interactions may require further investigations. Full article

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

23 pages, 1024 KiB

Open AccessArticle

The Effect of Climate Change on Important Climate Variables in Taiwan and Its Potential Impact on Crop Production

by Shih-Lun Fang, Bing-Yun Tsai, Chun-Yi Wu, Sheng-Chih Chang, Yi-Lung Chang and Bo-Jein Kuo

Agriculture 2025, 15(7), 766; https://doi.org/10.3390/agriculture15070766 - 2 Apr 2025

Abstract

Alterations in reference evapotranspiration (ET₀) and precipitation (PP) resulting from global warming substantially affect water resources and agriculture. This study analyzed trends in ET₀, PP, and key climate variables—including air temperature (T), vapor pressure deficit (VPD), wind speed, and [...] Read more.

Alterations in reference evapotranspiration (ET₀) and precipitation (PP) resulting from global warming substantially affect water resources and agriculture. This study analyzed trends in ET₀, PP, and key climate variables—including air temperature (T), vapor pressure deficit (VPD), wind speed, and solar radiation (R_s)—across Taiwan from 1995 to 2022. Trends were assessed using the modified Mann–Kendall test and the multivariate Man–Kendall test at both station-wise and multi-station scales. Results indicated that ET₀ was primarily influenced by R_s, followed by T, wind speed, and VPD. Station-wise analysis revealed increasing trends in annual and seasonal T, R_s, and ET₀, while over 50% of wind speed series showed significant declines. Multi-station analysis confirmed an overall rise in ET₀. In eastern Taiwan, rising T and declining VPD and wind speed may increase the risk of pest and disease outbreaks. The arid index exhibited a general downward trend, particularly in summer, with 75% of the stations in eastern Taiwan exhibiting significant declines, suggesting a shift toward drier conditions. These findings imply that fewer crop options may be suitable for cultivation in eastern Taiwan due to water resource constraints. Additionally, seasonal and annual PP showed slight decreases, with a more uneven distribution observed in central Taiwan. Therefore, improving hydraulic facilities and irrigation systems will become important. Furthermore, comparisons between the multivariate Mann–Kendall test and the traditional univariate approach revealed some different results, indicating the need for further research to identify a more reliable approach. Full article

(This article belongs to the Section Agricultural Water Management)

25 pages, 14345 KiB

Open AccessArticle

Research on an Apple Recognition and Yield Estimation Model Based on the Fusion of Improved YOLOv11 and DeepSORT

by Zhanglei Yan, Yuwei Wu, Wenbo Zhao, Shao Zhang and Xu Li

Agriculture 2025, 15(7), 765; https://doi.org/10.3390/agriculture15070765 - 2 Apr 2025

Abstract

Accurate apple yield estimation is essential for effective orchard management, market planning, and ensuring growers’ income. However, complex orchard conditions, such as dense foliage occlusion and overlapping fruits, present challenges to large-scale yield estimation. This study introduces APYOLO, an enhanced apple detection algorithm [...] Read more.

Accurate apple yield estimation is essential for effective orchard management, market planning, and ensuring growers’ income. However, complex orchard conditions, such as dense foliage occlusion and overlapping fruits, present challenges to large-scale yield estimation. This study introduces APYOLO, an enhanced apple detection algorithm based on an improved YOLOv11, integrated with the DeepSORT tracking algorithm to improve both detection accuracy and operational speed. APYOLO incorporates a multi-scale channel attention (MSCA) mechanism and an enhanced multi-scale prior distribution intersection over union (EnMPDIoU) loss function to enhance target localization and recognition under complex environments. Experimental results demonstrate that APYOLO outperforms the original YOLOv11 by improving mAP@0.5, mAP@0.5–0.95, accuracy, and recall by 2.2%, 2.1%, 0.8%, and 2.3%, respectively. Additionally, the combination of a unique ID with the region of line (ROL) strategy in DeepSORT further boosts yield estimation accuracy to 84.45%, surpassing the performance of the unique ID method alone. This study provides a more precise and efficient system for apple yield estimation, offering strong technical support for intelligent and refined orchard management. Full article

(This article belongs to the Section Digital Agriculture)

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27 pages, 1531 KiB

Open AccessArticle

Driving Mechanisms of the Integration of Ecological Farms and Rural Tourism: A Mixed Method Study

by Xia Xiao, Pingan Xiang, Haisong Wang and Maosen Xia

Agriculture 2025, 15(7), 764; https://doi.org/10.3390/agriculture15070764 - 2 Apr 2025

Abstract

Integration with rural tourism is an important way to achieve the sustainable development of ecological farms. Existing literature on the integration of agriculture and tourism lacks discussion from the microscopic farm level, making it difficult to capture the complex mechanisms of the integration [...] Read more.

Integration with rural tourism is an important way to achieve the sustainable development of ecological farms. Existing literature on the integration of agriculture and tourism lacks discussion from the microscopic farm level, making it difficult to capture the complex mechanisms of the integration of ecological farms and rural tourism. This paper attempts to address this problem by exploring the driving factors of the integration of ecological farms and rural tourism. The research aim of this paper is to construct a theoretical framework for driving the integration of ecological farms and rural tourism. We first conducted research on farms in four ecological agriculture demonstration zones: Ziquejie in Loudi, Hunan Province; Heshi in Shilin, Yunnan Province; Rongjiang in Dali, Yunnan Province; and Youxiqiao Village in Hunan Province. We interviewed 64 stakeholders in ecotourism and used grounded theory methods to construct a model and propose hypotheses. On this basis, a measurement scale was designed, and data was collected from 1041 Chinese ecological farms (ecological farm operators) using a structured questionnaire. The partial least squares structural equation model (PLS-SEM) was used to model and analyze the data to test the constructed model. The study found that higher market demand, regional economic level, intrinsic development needs, intrinsic resource endowments, technical support, and resource integration can promote the integration of ecological farms and rural tourism. Market demand and intrinsic development needs constitute the generative force of agritourism integration, while resource integration and intrinsic resource endowments constitute the development force of agritourism integration, and technical support and the regional economic level constitute the supporting force of agritourism integration. Full article

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

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20 pages, 9671 KiB

Open AccessArticle

Design and Experimental Study of a Dual-Side-Disturbance-Facilitated Air-Suction Precision Seed Metering Device for Corn

by Fazhan Yang, Quan Song, Yuhuan Li, Sen Chu, Baogang Li and Shuo Zhao

Agriculture 2025, 15(7), 763; https://doi.org/10.3390/agriculture15070763 - 2 Apr 2025

Abstract

To address the issue of a poor seed-filling performance and seeding quality in air-suction corn seed metering devices during high-speed operation, an energy-efficient precision corn seeder with dual-side-disturbance-facilitated guiding slots is designed. The dual-side-disturbance-promoting method effectively increases the seed agitation, directing the corn [...] Read more.

To address the issue of a poor seed-filling performance and seeding quality in air-suction corn seed metering devices during high-speed operation, an energy-efficient precision corn seeder with dual-side-disturbance-facilitated guiding slots is designed. The dual-side-disturbance-promoting method effectively increases the seed agitation, directing the corn seeds toward the suction holes and improving the seed-filling quality. The theoretical design of the dual-side guiding slot angles results in an upper-side guiding slot angle range of 29° to 19° and a lower-side guiding slot angle range of 72° to 90°. Bench tests are conducted to further optimize the parameter range, with the negative suction chamber pressure, upper-side guiding slot angle, and lower-side guiding slot angle as the experimental factors and the seedling qualification rate, missed sowing rate, and double-sowing rate as the evaluation indicators. An orthogonal experiment is carried out to analyze the interaction effects of factors on the evaluation indicators, followed by parameter optimization and verification tests. When the negative suction chamber pressure is 3.7 kPa, the upper-side guiding slot angle is 26.9°, and the lower-side guiding slot angle is 72.9°, the verification test results show a qualification index of 97.7%, a missed sowing index of 1.3%, and a row-spacing variation coefficient of 1%. The operational speed adaptability test results show that when the working speed is ≤14 km/h, the seed metering device achieves a qualification index above 97.1%, a missed sowing index below 1.5%, and a double sowing index below 1.4%, indicating good adaptability to working speeds. The comparison test results show that when the operating speed is between 8 and 12 km/h, the air-suction seed metering device with dual-side-disturbance-facilitated guiding slots achieves a 2.1% increase in the qualification index, significantly improving seeding quality. The energy consumption comparison test results indicate that under the same operational speed and approximately equal seeding quality, the air-suction seed metering device with dual-side guiding slots and dual-side-disturbance-facilitated air suction requires a reduction in negative pressure of more than 0.7 kPa, resulting in lower energy consumption. Full article

(This article belongs to the Section Agricultural Technology)

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14 pages, 1927 KiB

Open AccessArticle

Food Safety Practices in Artisanal and Semi-Automated Dairy Processors: Evidence from Fier, Albania

by Pranvera Troka, Marsela Luarasi and Ilir Kapaj

Agriculture 2025, 15(7), 762; https://doi.org/10.3390/agriculture15070762 - 2 Apr 2025

Abstract

Food safety and traceability in dairy processing plants are essential for public health and industry sustainability. This study provides an empirical assessment of food safety and traceability practices among artisanal and semi-automated dairy processors in Fier, Albania, which is the country’s leading milk-producing [...] Read more.

Food safety and traceability in dairy processing plants are essential for public health and industry sustainability. This study provides an empirical assessment of food safety and traceability practices among artisanal and semi-automated dairy processors in Fier, Albania, which is the country’s leading milk-producing region. Based on structured interviews with 18 dairy processors, we examined practices related to supplier management, quality control, facility conditions, staff hygiene, and equipment sanitation. The results reveal significant gaps in milk supplier inspections, biochemical testing, and traceability systems. The majority of processors lack barcode systems, regulated contracts with farmers, and formalized product tracking mechanisms, decreasing the chances of market formalization. Moreover, none of the dairies in this study have ISO certification, which restricts access to international markets. This paper also compares food safety practices between semi-automated and artisanal processors, with the former having slightly better compliance in certain key areas such as milk supply monitoring and biochemical testing. However, both groups face major challenges in complying with food safety standards due to weak regulatory enforcement, limited financial resources, and insufficient training. Implementing stricter food safety measures and modern traceability systems is not only a regulatory necessity but a strategic step toward improving public health, market access, and the long-term sustainability of Albania’s dairy sector. Full article

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

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14 pages, 2450 KiB

Open AccessArticle

Assessment of Heterozygosity in European Local and Cosmopolitan Pig Populations

by Maria Chiara Fabbri, Katherine D. Arias, Marcos P. G. Rezende, Francesco Tiezzi, Stefano Biffani, Felix Goyache, Giuseppina Schiavo, Samuele Bovo, Luca Fontanesi, Marjeta Čandek-Potokar, Maria Muñoz, Cristina Ovilo, Klavdija Poklukar, Martin Škrlep and Riccardo Bozzi

Agriculture 2025, 15(7), 761; https://doi.org/10.3390/agriculture15070761 - 1 Apr 2025

Abstract

Researchers focused on assessing differences in gene diversity within and between populations, whether cosmopolitan or local. However, the identification of patterns of variation in non-random heterozygous genomic stretches, known as Heterozygosity-Rich regions (HRRs), has not yet been determined in European local pig breeds. [...] Read more.

Researchers focused on assessing differences in gene diversity within and between populations, whether cosmopolitan or local. However, the identification of patterns of variation in non-random heterozygous genomic stretches, known as Heterozygosity-Rich regions (HRRs), has not yet been determined in European local pig breeds. A total of 23 pig breeds (20 local and 3 cosmopolitan) were assessed and compared in terms of heterozygosity-rich regions. The breeds with the highest number of HRRs were Large White, Lithuanian Old type, and Landrace, followed by Lithuanian Native, Mora Romagnola, and Duroc. The breeds with the lowest number were Alentejana, Iberian, and Majorcan Black. No shared HRR islands were found in all breeds, but gene enrichment analysis performed in the most common HRRs revealed several biologically important genes that cluster together and play significant roles, primarily related to the immune system. Permutation analysis indicated that some local breeds serve as true reservoirs of genetic diversity, displaying distinct and unique characteristics in terms of heterozygosity. This study suggests the importance of investigating heterozygosity to develop a comprehensive picture of pig breeds, regardless of the production system, country of origin, or population size. Full article

(This article belongs to the Special Issue Genetic Diversity, Adaptation and Evolution of Livestock)

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23 pages, 25923 KiB

Open AccessArticle

Fast and Accurate Detection of Forty Types of Fruits and Vegetables: Dataset and Method

by Xiaosheng Bu, Yongfeng Wu, Hongtai Lv and Youling Yu

Agriculture 2025, 15(7), 760; https://doi.org/10.3390/agriculture15070760 - 1 Apr 2025

Abstract

Accurate detection of fruits and vegetables is a key task in agricultural automation. However, existing detection methods typically focus on identifying a single type of fruit or vegetable and are not equipped to handle complex and diverse environments. To address this, we introduce [...] Read more.

Accurate detection of fruits and vegetables is a key task in agricultural automation. However, existing detection methods typically focus on identifying a single type of fruit or vegetable and are not equipped to handle complex and diverse environments. To address this, we introduce the first large-scale benchmark dataset for fruit and vegetable detection—FV40. This dataset contains 14,511 images, covering 40 different categories of fruits and vegetables, with over 100,000 annotated bounding boxes. Additionally, we propose a novel framework for fruit and vegetable detection—FVRT-DETR. Based on the Transformer architecture, this framework features an end-to-end real-time detection algorithm. FVRT-DETR enhances feature extraction by integrating the Mamba backbone network and improves detection performance for objects of varying scales through the design of a multi-scale deep feature fusion encoder (MDFF encoder) module. Extensive experiments show that FVRT-DETR performs excellently on the FV40 dataset. In particular, it demonstrates a significant performance advantage in detection of small objects and under complex scenarios. Compared to existing state-of-the-art detection algorithms, such as YOLOv10, FVRT-DETR achieves better results across multiple key metrics. The FVRT-DETR framework and the FV40 dataset provide an efficient and scalable solution for fruit and vegetable detection, offering significant academic value and practical application potential. Full article

(This article belongs to the Section Digital Agriculture)

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20 pages, 577 KiB

Open AccessArticle

A Study on the Impact of Social Trust on Farmers’ Agricultural Waste Resource Utilization Behavior in the Context of Environmental Regulation Policy

by Jianhua Wang and Ling Ma

Agriculture 2025, 15(7), 759; https://doi.org/10.3390/agriculture15070759 - 1 Apr 2025

Abstract

The resource utilization of agricultural waste is an important way to achieve the green transformation of agriculture. Based on micro-survey data from 701 farmers in Jiangsu Province, this paper constructs a binary logistic model to explore how farmers’ social trust affects their decisions [...] Read more.

The resource utilization of agricultural waste is an important way to achieve the green transformation of agriculture. Based on micro-survey data from 701 farmers in Jiangsu Province, this paper constructs a binary logistic model to explore how farmers’ social trust affects their decisions regarding agricultural waste resource utilization. It also examines the moderating effect of environmental regulation policies between the two. The results show that social trust has a significant positive impact on farmers’ agricultural waste resource utilization behavior. Secondly, guiding environmental regulation policies positively moderate the effect of interpersonal trust on farmers’ agricultural waste resource utilization behavior, while both guiding and restrictive environmental regulation policies serve as substitute moderators in the relationship between institutional trust and farmers’ participation behavior. Finally, heterogeneity analysis shows that, due to differences in household endowments, the impact of interpersonal trust and institutional trust on agricultural waste resource utilization behavior differs across different farmer groups. Therefore, this paper suggests cultivating and enhancing the level of social trust among farmers, thereby promoting their participation in waste resource utilization while strengthening the regulatory role of environmental regulation policies in shaping farmers’ behavior. Full article

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

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17 pages, 1840 KiB

Open AccessArticle

Sustainability Indicators of the Banana and Lemongrass Intercropping System in Different Harvest Seasons: Growth, Yield, Seasonality and Essential Oil Properties

by Paulo Ricardo Rodrigues de Jesus, Sarita Leonel, Marcelo de Souza Silva, Filipe Pereira Giardini Bonfim, Magali Leonel, Hebert Teixeira Cândido, Marco Antonio Tecchio, Nicholas Zanette Molha and Vinicius Martins Domiciano

Agriculture 2025, 15(7), 758; https://doi.org/10.3390/agriculture15070758 - 31 Mar 2025

Abstract

Lemongrass (Cymbopogon citratus) has potential for intercropping with banana (Musa spp.) plants, thus contributing to the sustainability of plantations. The study evaluated the growth and yield of ‘Prata Anã’ banana and seasonality, yield and essential oil properties of lemongrass grown [...] Read more.

Lemongrass (Cymbopogon citratus) has potential for intercropping with banana (Musa spp.) plants, thus contributing to the sustainability of plantations. The study evaluated the growth and yield of ‘Prata Anã’ banana and seasonality, yield and essential oil properties of lemongrass grown in intercropping and the land equivalent ratio. A randomized block design in a split plot arrangement was used, evaluating two cropping systems (sole crop and intercropping) and three harvest seasons during the year for lemongrass and two harvest seasons for banana, separately. The banana can be intercropped with lemongrass without interfering with its growth and production. The biomass production and essential oil yield of lemongrass differed according to cropping system and seasonality. The chemical composition of the essential oil showed stability in the concentration of citral (mixture of neral and geranial), with an average of 94.43%. Seasonal variations were observed in the content of these compounds and other components of the essential oil, emphasizing the importance of the time of harvest in the overall value of the oil. The result demonstrates the viability of intercropping, which not only provides crop yields for both species and produces more per unit area than a sole crop but also optimizes the use of resources and promotes more sustainable farming practices. Full article

(This article belongs to the Section Crop Production)

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4 pages, 139 KiB

Open AccessEditorial

Big Data Analytics and Machine Learning for Smart Agriculture

by Maciej Zaborowicz and Jakub Frankowski

Agriculture 2025, 15(7), 757; https://doi.org/10.3390/agriculture15070757 - 31 Mar 2025

Abstract

Modern technologies are continuously entering every aspect of our lives... Full article

(This article belongs to the Special Issue Big Data Analytics and Machine Learning for Smart Agriculture)

20 pages, 10432 KiB

Open AccessArticle

Apple Watercore Grade Classification Method Based on ConvNeXt and Visible/Near-Infrared Spectroscopy

by Chunlin Zhao, Zhipeng Yin, Yushuo Tan, Wenbin Zhang, Panpan Guo, Yaxing Ma, Haijian Wu, Ding Hu and Quan Lu

Agriculture 2025, 15(7), 756; https://doi.org/10.3390/agriculture15070756 - 31 Mar 2025

Abstract

To address the issues of insufficient rigor in existing methods for quantifying apple watercore severity and the complexity and low accuracy of traditional classification models, this study proposes a method for watercore quantification and a classification model based on a deep convolutional neural [...] Read more.

To address the issues of insufficient rigor in existing methods for quantifying apple watercore severity and the complexity and low accuracy of traditional classification models, this study proposes a method for watercore quantification and a classification model based on a deep convolutional neural network. Initially, visible/near-infrared transmission spectral data of apple samples were collected. The apples were then sliced into 4.5 mm thick sections using a specialized tool, and image data of each slice were captured. Using BiSeNet and RIFE algorithms, a three-dimensional model of the watercore regions was constructed from the apple slices to calculate the watercore severity, which was subsequently categorized into five distinct levels. Next, methods such as the Gramian Angular Summation Field (GASF), Gram Angular Difference Field (GADF), and Markov Transition Field (MTF) were applied to transform the one-dimensional spectral data into two-dimensional images. These images served as input for training and prediction using the ConvNeXt deep convolutional neural network. The results indicated that the GADF method yielded the best performance, achieving a test set accuracy of 98.73%. Furthermore, the study contrasted the classification and prediction of watercore apples using traditional methods with the existing quantification approaches for watercore levels. The comparative results demonstrated that the proposed GADF-ConvNeXt model is more straightforward and efficient, achieving superior performance in classifying watercore grades. Furthermore, the newly proposed quantification method for watercore levels proved to be more effective. Full article

(This article belongs to the Section Digital Agriculture)

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21 pages, 1764 KiB

Open AccessArticle

Designing a Theoretical Framework for Ecosystem Products of Agricultural Heritage Systems

by Ruyu Ye, Moucheng Liu and Zhidong Li

Agriculture 2025, 15(7), 755; https://doi.org/10.3390/agriculture15070755 - 31 Mar 2025

Abstract

Agricultural Heritage Systems (AHS) formed by the long-term synergistic evolution of the countryside and its environment carry significant ecological, cultural, and economic value. The protection and sustainable utilization of AHS has become a critical issue for promoting the sustainable development of heritage regions. [...] Read more.

Agricultural Heritage Systems (AHS) formed by the long-term synergistic evolution of the countryside and its environment carry significant ecological, cultural, and economic value. The protection and sustainable utilization of AHS has become a critical issue for promoting the sustainable development of heritage regions. This study aims to provide a comprehensive framework for research on value realization from ecosystem products of agricultural heritage system (EPAHS). The study establishes a systematic research paradigm, which includes “specialization analysis–value realization pathways–evaluation methods.” A dual classification system based on “functional and consumption attributes” is introduced. Based on the principle of attribute alignment, three primary value realization pathways are proposed: market-driven, government-driven, and market–government collaboration. Additionally, a dual-dimensional evaluation index system is developed, including total value and structural evaluation indicators, to quantify the composite value and conversion effects of EPAHS. The findings emphasize that EPAHS, due to their cultural attributes and regional uniqueness, differ from general ecosystem products. They require tailored value realization pathways that integrate agricultural production, community benefits, and AHS preservation. This study provides both theoretical and practical support for the sustainable protection and utilization of AHS and offers valuable insights for rural revitalization and the development of ecological civilization. Full article

(This article belongs to the Special Issue Exploring, Assessing and Utilizing the Multifunctional Value of Agricultural Heritage Systems)

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