Agriculture

20 pages, 6805 KiB

Open AccessArticle

Analysis of Irrigation, Crop Growth and Physiological Information in Substrate Cultivation Using an Intelligent Weighing System

by Jiu Xu, Lili Zhangzhong, Peng Lu, Yihan Wang, Qian Zhao, Youli Li and Lichun Wang

Agriculture 2025, 15(10), 1113; https://doi.org/10.3390/agriculture15101113 - 21 May 2025

Viewed by 166

Abstract

The online dynamic collection of irrigation and plant physiological information is crucial for the precise irrigation management of nutrient solutions and efficient crop cultivation in vegetable soilless substrate cultivation facilities. In this study, an intelligent weighing system was installed in a tomato substrate [...] Read more.

The online dynamic collection of irrigation and plant physiological information is crucial for the precise irrigation management of nutrient solutions and efficient crop cultivation in vegetable soilless substrate cultivation facilities. In this study, an intelligent weighing system was installed in a tomato substrate cultivation greenhouse. The monitored values from the intelligent weighing system’s pressure-type module were used to calculate irrigation start–stop times, frequency, volume, drainage volume, drainage rate, evapotranspiration, evapotranspiration rate, and stomatal conductance. In contrast, the monitored values of the suspension-type weighing module were used to calculate the amount of weight change in the plants, which supported the dynamic and quantitative characterization of substrate cultivation irrigation and crop growth based on an intelligent weighing system. The results showed that the monitoring curves of pressure and flow sensors based on the pressure-type module could accurately identify the irrigation start time and number of irrigations and calculate the irrigation volume, drainage volume, and drainage rate. The calculated irrigation amount was closely aligned with that determined by an integrated-water–fertilizer automatic control system (R² = 0.923; mean absolute error (MAE) = 0.105 mL; root-mean-square error (RMSE) = 0.132 mL). Furthermore, transpiration rate and leaf stomatal conductance were obtained through inversion, and the R², MAE, and RMSE of the extinction coefficient correction model were 0.820, 0.014 mol·m⁻²·s⁻¹, and 0.017 mol·m⁻²·s⁻¹, respectively. Compared to traditional estimation methods, the MAE and RMSE decreased by 12.5% and 15.0%, respectively. The measured values of fruit picking and leaf stripping linearly fitted with the calculated values of the suspended weighing module, and R², MAE, and RMSE were 0.958, 0.145 g, and 0.143 g, respectively. This indicated that data collection based on the suspension-type weighing module could allow for a dynamic analysis of plant weight changes and fruit yield. In summary, the intelligent weighing system could accurately analyze irrigation information and crop growth physiological indicators under the practical application conditions of facility vegetable substrate cultivation, providing technical support for the precise management of nutrient solutions. Full article

(This article belongs to the Section Digital Agriculture)

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25 pages, 4234 KiB

Open AccessArticle

Candidate Pheromone Receptors of the Red-Belted Clearwing Moth Synanthedon myophaeformis Bind Pear Ester and Other Semiochemicals

by Alberto Maria Cattaneo and William B. Walker III

Agriculture 2025, 15(10), 1112; https://doi.org/10.3390/agriculture15101112 - 21 May 2025

Viewed by 201

Abstract

The red-belted clearwing moth Synanthedon myophaeformis is a deleterious pest of apple orchards, wherein the larvae bore tree bark, resulting in reduced fitness and ultimately death. The main control strategies of this pest still rely on the use of pesticides, while alternative agronomic [...] Read more.

The red-belted clearwing moth Synanthedon myophaeformis is a deleterious pest of apple orchards, wherein the larvae bore tree bark, resulting in reduced fitness and ultimately death. The main control strategies of this pest still rely on the use of pesticides, while alternative agronomic methods for its control coexist, with the application of the main pheromone (Z,Z)-3,13-octadecadien-1-yl acetate. Until now, the molecular bases of the chemosensory systems of the red-belted clearwing moth have been less explored. With the aim to identify novel ligands that may interfere with the behaviour of S. myophaeformis, in this study, we have isolated and functionally characterised some key odorant receptors (ORs) of this moth by selecting paralogues from two main subgroups of the Lepidopteran pheromone receptor (PR) clade: the OR3 subgroup (OR3.1 to OR3.4) and the OR22 subgroup (OR22.1 to OR22.4). We generated transgenic D. melanogaster expressing SmyoORs in ab3A neurons, which we approached by single sensillum recording (SSR). Among these ORs, we deorphanized SmyoOR3.4 to ligands that we have previously identified for orthologues of the codling moth Cydia pomonella, including the pear ester ethyl-(E,Z)-2,4-decadienoate, its methyl ester analogue methyl-(E,Z)-2,4-decadienote, and the unsaturated aldehyde (Z)-6-undecenal. With this approach, we also identified a wide pattern of activation of SmyoOR22.4 to several apple-emitted ligands. Despite the fact that combining SSR with gas chromatography (GC-SSR) did not unveil the activation of the SmyoORs to compounds present in the headspace from apples, GC-SSR unveiled the enhancement of the SmyoOR3.4 spiking at nanogram doses of both pear ester, methyl ester, and (Z)-6-undecenal. For the first time, this study deorphanized ORs from the red-belted clearwing moth and identified ligands as possible semiochemicals to add to the ongoing strategies for the control of this pest. Full article

(This article belongs to the Special Issue Chemosensory-Based Pest Management of Insects and Other Protostomes in Crop Protection)

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26 pages, 6391 KiB

Open AccessArticle

Lightweight SCD-YOLOv5s: The Detection of Small Defects on Passion Fruit with Improved YOLOv5s

by Yu Zhou, Zhenye Li, Sheng Xue, Min Wu, Tingting Zhu and Chao Ni

Agriculture 2025, 15(10), 1111; https://doi.org/10.3390/agriculture15101111 - 21 May 2025

Viewed by 144

Abstract

Accurate detection of surface defects on passion fruits is crucial for maintaining market competitiveness. Numerous small defects present significant challenges for manual inspection. Recently, deep learning (DL) has been widely applied to object detection. In this study, a lightweight neural network, StarC3SE-CBAM-DIoU-YOLOv5s (SCD-YOLOv5s), [...] Read more.

Accurate detection of surface defects on passion fruits is crucial for maintaining market competitiveness. Numerous small defects present significant challenges for manual inspection. Recently, deep learning (DL) has been widely applied to object detection. In this study, a lightweight neural network, StarC3SE-CBAM-DIoU-YOLOv5s (SCD-YOLOv5s), is proposed based on YOLOv5s for real-time detection of tiny surface defects on passion fruits. Key improvements are introduced as follows: the original C3 module in the backbone is replaced by the enhanced StarC3SE module to achieve a more efficient network structure; the CBAM module is integrated into the neck to improve the extraction of small defect features; and the CIoU loss function is substituted with DIoU-NMS to accelerate convergence and enhance detection accuracy. Experimental results show that SCD-YOLOv5s performs better than YOLOv5s, with precision increased by 13.2%, recall by 1.6%, and F₁-score by 17.0%. Additionally, improvements of 6.7% in mAP@0.5 and 5.5% in mAP@0.95 are observed. Compared with manual detection, the proposed model enhances detection efficiency by reducing errors caused by subjective judgment. It also achieves faster inference speed (26.66 FPS), and reductions of 9.6% in parameters and 8.6% in weight size, while maintaining high detection performance. These results indicate that SCD-YOLOv5s is effective for defect detection in agricultural applications. Full article

(This article belongs to the Section Digital Agriculture)

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20 pages, 1199 KiB

Open AccessArticle

Diversification of Cultivars and Production of Male Inflorescence Flours for More Sustainable Banana Cultivation

by Lucas Felipe dos Ouros, Magali Leonel, Sarita Leonel, Nicholas Zanette Molha, Paulo Ricardo Rodrigues de Jesus, Hebert Teixeira Cândido, Marco Antonio Tecchio, Mayra Schmidt Rechsteiner and Caio César dos Ouros

Agriculture 2025, 15(10), 1110; https://doi.org/10.3390/agriculture15101110 - 21 May 2025

Viewed by 184

Abstract

Banana inflorescences are usually discarded, but there has been interest in managing this by-product to turn it into a product with added value. Herein, the inflorescences of seven cultivars were processed into flour and evaluated for their physicochemical characteristics. The weight of the [...] Read more.

Banana inflorescences are usually discarded, but there has been interest in managing this by-product to turn it into a product with added value. Herein, the inflorescences of seven cultivars were processed into flour and evaluated for their physicochemical characteristics. The weight of the inflorescences ranged from 681.3 to 1245.4 g, with bracts accounting for more than 40%. The Prata Anã cultivar had the largest inflorescence. The part of the inflorescence was the main factor differentiating the flours, with the effect of the cultivar dependent on the part processed. All flours had high levels of fiber (27.70–41.91 g/100 g) and carbohydrates (19.30–33.96 g/100 g). The palm flours were differentiated by their higher levels of protein (17.4–19.4 g/100 g), and the flower flours by their higher levels of lipids (5.89–7.97 g/100 g). The bract flours had a higher water holding capacity (5.62–6.78%) and browning index (40.7–42). The bract and flower flours were less dissimilar. Results revealed the high nutritional quality of the flours and the prospect of using them as a non-conventional food source. Understanding the differences between banana inflorescence flours expands their possible uses and promotes sustainable agricultural production in terms of efficient banana by-product management. Full article

(This article belongs to the Section Crop Production)

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30 pages, 36962 KiB

Open AccessArticle

Analysis on Spatiotemporal Variation in Soil Drought and Its Influencing Factors in Hebei Province from 2001 to 2020

by Biao Zeng, Bo Wen, Xia Zhang, Suya Zhao, Guofei Shang, Shixin An and Zhe Li

Agriculture 2025, 15(10), 1109; https://doi.org/10.3390/agriculture15101109 - 21 May 2025

Viewed by 173

Abstract

As a dominant ecological stress factor of climate change, soil drought has become a key challenge restricting food security. Based on soil moisture data, this paper uses the cumulative anomaly method, coefficient of variation, Sen + Mann–Kendall trend analysis, and center of gravity [...] Read more.

As a dominant ecological stress factor of climate change, soil drought has become a key challenge restricting food security. Based on soil moisture data, this paper uses the cumulative anomaly method, coefficient of variation, Sen + Mann–Kendall trend analysis, and center of gravity shift model to study the spatiotemporal changes in soil drought in Hebei Province from 2001 to 2020 and uses the optimal parameter geographic detector model to analyze the key factors affecting soil drought. The results show the following: (1) over the past 20 years, soil drought in Hebei Province has shown a trend of “first intensifying and then easing”, experiencing two turning points, and its spatial distribution showed significant agglomeration characteristics. (2) Soil moisture showed single-peak seasonal fluctuation, with severe drought from January to May, peak soil moisture from June to August, soil moisture balance from September to October, and soil moisture deficit intensified in winter. (3) Soil moisture stability showed spatial differentiation, being high in the northeast and low in the southwest. Soil drought in about 70% of the region has improved, and the center of gravity of drought-prone areas has moved to the southwest. (4) NDVI and altitude are the main drivers of soil drought spatial differentiation, and the multi-factor interaction shows a nonlinear enhancement effect. Among them, the parameter thresholds such as NDVI > 0.512 and altitude −32~16 m have a significant inhibitory effect on soil drought. This study can make a contribution to improving water resource management and increasing agricultural productivity in the region. Full article

(This article belongs to the Section Digital Agriculture)

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21 pages, 5839 KiB

Open AccessArticle

Organic–Inorganic Fertilization Sustains Crop Yields While Mitigating N₂O and NO Emissions in Subtropical Wheat–Maize Systems

by Yan Liu, Lei Hu, Shihang Zhang, Zhisheng Yao, Minghua Zhou and Bo Zhu

Agriculture 2025, 15(10), 1108; https://doi.org/10.3390/agriculture15101108 - 21 May 2025

Viewed by 87

Abstract

Balancing food security with fertilizer-driven climate impacts remains critical in intensive agriculture. While organic–inorganic substitution enhances soil fertility, its effects on nitrous oxide (N₂O) and nitric oxide (NO) emissions remain uncertain. This study evaluated N₂O/NO emissions, crop yields, and [...] Read more.

Balancing food security with fertilizer-driven climate impacts remains critical in intensive agriculture. While organic–inorganic substitution enhances soil fertility, its effects on nitrous oxide (N₂O) and nitric oxide (NO) emissions remain uncertain. This study evaluated N₂O/NO emissions, crop yields, and agronomic parameters in a subtropical wheat–maize rotation under four fertilization regimes: inorganic-only (NPK), manure-only (OM), and partial substitution with crop residues (CRNPK, 15%) or manure (OMNPK, 30%), all applied at 280 kg N ha⁻¹ yr⁻¹. Emissions aligned with the dual Arrhenius–Michaelis–Menten kinetics and revised “hole-in-the-pipe” model. Annual direct emission factors (EF_d) for N₂O and NO were 1.01% and 0.11%, respectively, with combined emissions (1.12%) exponentially correlated to soil nitrogen surplus (p < 0.01). CRNPK and OMNPK reduced annual N₂O+NO emissions by 15–154% and enhanced NUE by 10–45% compared with OM, though OMNPK emitted 1.7–2.0 times more N₂O/NO than CRNPK. Sole OM underperformed in yield, while partial substitution—particularly with crop residues—optimized productivity while minimizing environmental risks. By integrating emission modeling and agronomic performance, this study establishes CRNPK as a novel strategy for subtropical cereal systems, reconciling high yields with low greenhouse gas emissions. Full article

(This article belongs to the Special Issue Advancements in Best Management Practices for Enhancing Soil Health and Water Quality)

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18 pages, 2081 KiB

Open AccessArticle

The Effects of an Automatic Flushing Valve on the Hydraulic Performance of a Subsurface Drip Irrigation System for Alfalfa

by Zaiyu Li, Yan Mo, Feng Wu, Hao Gao, Ronglian Wang and Jiandong Wang

Agriculture 2025, 15(10), 1107; https://doi.org/10.3390/agriculture15101107 - 21 May 2025

Viewed by 63

Abstract

The automatic flushing valve (AFV) enables automatic flushing of drip irrigation systems, improving their anti-clogging performance. This study focuses on a subsurface drip irrigation system (SDI) for alfalfa, selecting T20 and T70 AFVs (with designed flushing durations of 20 and 70 s, respectively) [...] Read more.

The automatic flushing valve (AFV) enables automatic flushing of drip irrigation systems, improving their anti-clogging performance. This study focuses on a subsurface drip irrigation system (SDI) for alfalfa, selecting T20 and T70 AFVs (with designed flushing durations of 20 and 70 s, respectively) installed at the end of the dripline and a buried dripline without an AFV as a control. The aim of this study was to explore the variations in AFV hydraulic performance over two years of operation and the impact on the irrigation uniformity of SDI systems. The results revealed that the flushing duration (FD) and flushing water volume (FQ) of both T20 and T70 fluctuated over time, with an average coefficient of variation (CV) of 13.2%. The FD and FQ of the two types of AFVs are affected by the daily average temperature (T), and when T increases from 20.1 °C to 25.7 °C, the FD and FQ increased by an average of 22.6%. After 2 years of operation, the average relative flow rate (Dra) and irrigation uniformity (Cu) of the T20 and T70 SDI emitters were 93.7% and 96.8%. Both the Dra and Cu were significantly influenced by FD (p < 0.05). Compared with CK and T20, T70 significantly increased the Dra and Cu by 6.3% and 4.6%, respectively. The order of degree of clogging at different positions in the dripline was rear > middle > front for the CK and T20 treatments, whereas for T70, it was middle > front > rear. With the installation of the T70 AFV, the time required for the SDI system to reach moderate clogging (Dra = 50~80%) was extended from 3~7 years to 8~20 years, resulting in a 180% increase in operation time. The T70 AFV is recommended for use in the alfalfa SDI of this study. Full article

(This article belongs to the Topic Irrigation and Fertilization Management for Sustainable Agricultural Production)

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17 pages, 602 KiB

Open AccessArticle

Digital and Entrepreneurial Competencies for the Bioeconomy: Perceptions and Training Needs of Agricultural Professionals in Greece, Italy, Portugal, and Sweden

by Dimitrios Petropoulos, Georgios A. Deirmentzoglou, Nikolaos Apostolopoulos, Bas Paris, Dimitris Michas, Athanasios T. Balafoutis, Elena Athanasopoulou, Leonardo Nibbi, Hailong Li, Lara Carvalho, Maria Helena Moreira da Silva and Joaquim Fernando Moreira da Silva

Agriculture 2025, 15(10), 1106; https://doi.org/10.3390/agriculture15101106 - 21 May 2025

Viewed by 108

Abstract

As the European Union advances its bioeconomy strategy, the agricultural sector emerges as a key domain requiring targeted upskilling in digital and entrepreneurial competencies. This study examines how agricultural professionals perceive the importance of these competencies and identifies related training needs, drawing on [...] Read more.

As the European Union advances its bioeconomy strategy, the agricultural sector emerges as a key domain requiring targeted upskilling in digital and entrepreneurial competencies. This study examines how agricultural professionals perceive the importance of these competencies and identifies related training needs, drawing on the European Commission’s Digital Competence Framework (DigComp) and Entrepreneurship Competence Framework (EntreComp). Using a quantitative survey methodology, data were collected from 140 respondents, including farmers, agronomists, consultants, entrepreneurs, and policymakers, in four European countries: Greece, Italy, Portugal, and Sweden. Descriptive and non-parametric analyses (Mann–Whitney U and Kruskal–Wallis tests) revealed strong recognition of digital competencies across all groups, with significant variation by country, while perceptions of entrepreneurial competencies differed mainly by professional role. Moreover, a significant lack of formal bioeconomy-related education was identified. The findings underscore the need for targeted, competence-based education and policy interventions to equip professionals with the skills required for a sustainable and innovation-driven agricultural sector. Full article

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

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29 pages, 4457 KiB

Open AccessArticle

The Implementation Path for a Policy Balancing Cultivated Land Occupation and Reclamation Based on Land-Type Classification—A Case Study in Heilongjiang Province

by Yanan Liu, Wei Zou, Kening Wu, Xiao Li, Xiaoliang Li and Rui Zhao

Agriculture 2025, 15(10), 1105; https://doi.org/10.3390/agriculture15101105 - 20 May 2025

Viewed by 128

Abstract

Food security is a fundamental issue that has long been of great concern, and cultivated land resources are the core elements of food security. In recent years, the problem of “non-agriculturalization” and “non-grain” conversion of cultivated land has become prominent. The need for [...] Read more.

Food security is a fundamental issue that has long been of great concern, and cultivated land resources are the core elements of food security. In recent years, the problem of “non-agriculturalization” and “non-grain” conversion of cultivated land has become prominent. The need for further strict control of cultivated land use has gained significant attention from the government and academia. Recently, it has been proposed in China that all forms of cultivated land occupation should be integrated into the management policy for balancing cultivated land occupation and reclamation. In this study, the concept of provincial-level land-type classification, along with agricultural land potential productivity evaluation, is adopted to determine the optimal scheme for balancing cultivated land occupation and reclamation. Thus, an analysis of the optimization scheme for implementing the cultivated land occupation and reclamation balance policy in Heilongjiang, along with a macro-level layout of this balance scheme, is carried out at the provincial level. The results show that the land-type classification system constructed from five dimensions—climatic conditions, geomorphic conditions, geological conditions, edaphic conditions, and hydrologic conditions—as well as the agricultural land potential productivity evaluation system constructed based on land types, can effectively identify the potential cultivated land utilization space in Heilongjiang Province. Based on the zoning of land suitable for farming, the cultivated land in unsuitable farming areas in Heilongjiang should be transferred out (403.01 km²) and, according to the principle of the balancing cultivated land occupation and reclamation policy, the non-cultivated land in highly and moderately suitable farming areas should be transferred in (249.80 km² and 163.39 km², respectively) to achieve balance. The results can provide reference for the implementation of the cultivated land occupation and reclamation policy at the provincial level, as well as for promoting the implementation of the strategy of “storing grain in the land”. Full article

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

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24 pages, 3989 KiB

Open AccessArticle

YOLO11-ARAF: An Accurate and Lightweight Method for Apple Detection in Real-World Complex Orchard Environments

by Yangtian Lin, Yujun Xia, Pengcheng Xia, Zhengyang Liu, Haodi Wang, Chengjin Qin, Liang Gong and Chengliang Liu

Agriculture 2025, 15(10), 1104; https://doi.org/10.3390/agriculture15101104 - 20 May 2025

Viewed by 221

Abstract

Accurate object detection is a fundamental component of autonomous apple-picking systems. In response to the insufficient recognition performance and poor generalization capacity of existing detection algorithms under unstructured orchard scenarios, we constructed a customized apple image dataset captured under varying illumination conditions and [...] Read more.

Accurate object detection is a fundamental component of autonomous apple-picking systems. In response to the insufficient recognition performance and poor generalization capacity of existing detection algorithms under unstructured orchard scenarios, we constructed a customized apple image dataset captured under varying illumination conditions and introduced an improved detection architecture, YOLO11-ARAF, derived from YOLO11. First, to enhance the model’s ability to capture apple-specific features, we replaced the original C3k2 module with the CARConv convolutional layer. Second, to reinforce feature learning in visually challenging orchard environments, the enhanced attention module AFGCAM was embedded into the model architecture. Third, we applied knowledge distillation to transfer the enhanced model to a compact YOLO11n framework, maintaining high detection efficiency while reducing computational cost, and optimizing it for deployment on devices with limited computational resources. To assess our method’s performance, we conducted comparative experiments on the constructed apple image dataset. The improved YOLO11-ARAF model attained 89.4% accuracy, 86% recall, 92.3% mAP@50, and 64.4% mAP@50:95 in our experiments, which are 0.3%, 1.1%, 0.72%, and 2% higher than YOLO11, respectively. Furthermore, the distilled model significantly reduces parameters and doubles the inference speed (FPS), enabling rapid and precise apple detection in challenging orchard settings with limited computational resources. Full article

(This article belongs to the Section Digital Agriculture)

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22 pages, 11671 KiB

Open AccessArticle

CFD-Based Flow Field Characteristics of Air-Assisted Sprayer in Citrus Orchards

by Xiangfei Huang, Yunwu Li, Lang Chen and Kechao Wang

Agriculture 2025, 15(10), 1103; https://doi.org/10.3390/agriculture15101103 - 20 May 2025

Viewed by 189

Abstract

Air-assisted sprayers are an essential piece of equipment for improving spraying efficiency and pesticide utilization; their performance directly affects the effectiveness of pesticide application. This study, addressing the plant protection needs of hilly citrus orchards, designed an air duct structure for an air-assisted [...] Read more.

Air-assisted sprayers are an essential piece of equipment for improving spraying efficiency and pesticide utilization; their performance directly affects the effectiveness of pesticide application. This study, addressing the plant protection needs of hilly citrus orchards, designed an air duct structure for an air-assisted sprayer and analyzed its airflow characteristics and droplet deposition effects based on CFD simulation technology. The reliability of the simulation results was verified through air speed boundary tests, revealing that the maximum effective boundaries of the integrated air duct and the independent air duct in different directions were 18.4 cm and 17.2 cm, respectively, providing a reference for the spatial arrangement of the air duct. The study indicates that properly matching the fan speed, spray pressure, and spray distance could optimize droplet deposition, enhance spray uniformity, and improve pesticide utilization. However, excessively high fan speeds (>6000 r/min) or spray pressures (>0.8 MPa) may reduce droplet transport efficiency. This research provides theoretical support for the design and parameter optimization of sprayers in hilly citrus orchards. Full article

(This article belongs to the Special Issue Agricultural Machinery and Technology for Fruit Orchard Management)

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20 pages, 3201 KiB

Open AccessArticle

The Design and Testing of a New Antitangling and Antisticking Knife for a Wet Clay Soil Environment

by Guosheng Geng, Tailai Chen, Maohua Xiao, Chenshuo Xie and Cungan Tang

Agriculture 2025, 15(10), 1102; https://doi.org/10.3390/agriculture15101102 - 20 May 2025

Viewed by 160

Abstract

Aiming at the problem that rotary tiller knife rollers are prone to entanglement with straw in the wet and sticky soil environment of rice fields in the middle and lower reaches of the Yangtze River in China, an antitangling and sticking cutter was [...] Read more.

Aiming at the problem that rotary tiller knife rollers are prone to entanglement with straw in the wet and sticky soil environment of rice fields in the middle and lower reaches of the Yangtze River in China, an antitangling and sticking cutter was designed. The cutter reduces knife roller entanglement in order to reduce rotary tiller energy consumption and improve work efficiency, and its effectiveness was verified through theoretical analysis, discrete element simulation, and field trials. The design’s validity was verified through theoretical analysis, discrete element simulation, and field tests. The blade inclination design was completed through motion force analysis, and the tool geometry was optimized with a 36.87° inclination baffle and staggered arrangement. A simulation model of the soil–straw–rotary tillage knife interaction was established and we used the discrete element method to analyze the variation in torque between the antisticking knife and the China standard rotary tillage knife (IT245) at four different cutter shaft rotational speeds. In the simulation, the average torque for the antisticking knives was smaller than that of the national standard rotary tillage knives, with reductions of 37.1%, 52.1%, 52.8%, and 50.0%, respectively, demonstrating a remarkable effect. Field tests showed that the average operational efficiency of the antisticking knife was 0.57 hm²/h, with an operation qualification rate of 95.72%. The average torque results from simulation (with and without the antisticking knife) and field tests were analyzed, yielding correlation coefficients of 0.994 and 0.973 for the change curves of average torque between the antisticking knife and the national standard rotary tillage knife. This result confirms the accuracy of the simulation model and the consistency between the simulation and field test results. This study can provide some references for the design and test of antisticking of rotary tillers. Full article

(This article belongs to the Section Agricultural Technology)

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4 pages, 136 KiB

Open AccessEditorial

From Planting to Harvesting: The Role of Agricultural Machinery in Crop Cultivation

by Yu Wang and Shan Zeng

Agriculture 2025, 15(10), 1101; https://doi.org/10.3390/agriculture15101101 - 20 May 2025

Viewed by 210

Abstract

The modernization of crop production is inextricably linked to the continuous advancement of agricultural machinery [...] Full article

(This article belongs to the Special Issue From Planting to Harvesting: The Role of Agricultural Machinery in Crop Cultivation)

24 pages, 6894 KiB

Open AccessArticle

Early Yield Prediction of Oilseed Rape Using UAV-Based Hyperspectral Imaging Combined with Machine Learning Algorithms

by Hongyan Zhu, Chengzhi Lin, Zhihao Dong, Jun-Li Xu and Yong He

Agriculture 2025, 15(10), 1100; https://doi.org/10.3390/agriculture15101100 - 19 May 2025

Viewed by 218

Abstract

Oilseed rape yield critically reflects varietal superiority. Rapid field-scale estimation enables efficient high-throughput breeding. This study evaluates unmanned aerial vehicle (UAV) hyperspectral imagery’s potential for yield prediction at the pod stage by utilizing wavelength selection and vegetation indices. Meanwhile, optimized feature selection algorithms [...] Read more.

Oilseed rape yield critically reflects varietal superiority. Rapid field-scale estimation enables efficient high-throughput breeding. This study evaluates unmanned aerial vehicle (UAV) hyperspectral imagery’s potential for yield prediction at the pod stage by utilizing wavelength selection and vegetation indices. Meanwhile, optimized feature selection algorithms identified effective wavelengths (EWs) and vegetation indices (VIs) for yield estimation. The optimal yield estimation models based on EWs and VIs were established, respectively, by using multiple linear regression (MLR), partial least squares regression (PLSR), extreme learning machine (ELM), and a least squares support vector machine (LS-SVM). The main results were as follows: (i) The yield prediction of oilseed rape using EWs showed better prediction and robustness compared to the full-spectral model. In particular, the competitive adaptive reweighted sampling–extreme learning machine (CARS-ELM) model (R_pre = 0.8122, RMSE_P = 170.4 kg/hm²) achieved the best prediction performance. (ii) The ELM model (R_pre = 0.7674 and RMSE_P = 187.6 kg/hm²), using 14 combined VIs, showed excellent performance. These results indicate that the remote sensing image data obtained from the UAV hyperspectral remote sensing system can be used to enable the high-throughput acquisition of oilseed rape yield information in the field. This study provides technical guidance for the crop yield estimation and high-throughput detection of breeding information. Full article

(This article belongs to the Special Issue Multi- and Hyper-Spectral Imaging Technologies for Crop Monitoring—2nd Edition)

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24 pages, 2836 KiB

Open AccessArticle

Response Prediction and Experimental Validation of Vibration Noise in the Conveyor Trough of a Combine Harvester

by Jianpeng Jing, Guangen Yan, Zhong Tang, Shuren Chen, Runzhi Liang, Yuxuan Chen and Xiaoying He

Agriculture 2025, 15(10), 1099; https://doi.org/10.3390/agriculture15101099 - 19 May 2025

Viewed by 252

Abstract

The noise generated by combine harvesters during operation has drawn growing attention, particularly that of the conveying trough shell, whose noise generation mechanism remains unclear. This study investigated the vibration radiation noise characteristics of conveying troughs by analyzing a chain system with 83 [...] Read more.

The noise generated by combine harvesters during operation has drawn growing attention, particularly that of the conveying trough shell, whose noise generation mechanism remains unclear. This study investigated the vibration radiation noise characteristics of conveying troughs by analyzing a chain system with 83 links using numerical simulation and experimental validation. A dynamic model of the conveyor chain system was developed, and the time domain reaction force at the bearing support was used as excitation for the trough shell’s finite element model. Modal and harmonic response analyses were performed to obtain the vibration response, which served as an acoustic boundary input for the LMS Virtual Lab. The indirect boundary element method was used to compute the radiated noise, achieving coupled modeling of chain system vibration and trough shell noise. Simulation results revealed that the maximum radiated noise occurred at approximately 112 Hz, closely matching experimental data. Comparative analysis of transmitted noise at 500 Hz and 700 Hz showed acoustic power levels of 98.4 dB and 109.52 dB, respectively. Results indicate that transmitted noise dominates over structural radiation in energy contribution, highlighting it as the primary noise path. This work offers a validated prediction model and supports noise control design for combine harvester conveying troughs. Full article

(This article belongs to the Section Agricultural Technology)

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3 pages, 145 KiB

Open AccessEditorial

Integrated Management and Efficient Use of Nutrients in Crop Systems

by Magdalena Jastrzębska

Agriculture 2025, 15(10), 1098; https://doi.org/10.3390/agriculture15101098 - 19 May 2025

Viewed by 146

Abstract

The sustainability of global food production relies heavily on the ability to optimize the nutrient economy in cropping systems around the world [...] Full article

(This article belongs to the Special Issue Integrated Management and Efficient Use of Nutrients in Crop Systems)

12 pages, 502 KiB

Open AccessArticle

Effectiveness of Different Beer Types in Slug Trapping: A Two-Year Field Study on Arion vulgaris Moquin-Tandon and Limax maximus L.

by Žiga Laznik, Stanislav Trdan, Miha Ocvirk and Iztok Jože Košir

Agriculture 2025, 15(10), 1097; https://doi.org/10.3390/agriculture15101097 - 19 May 2025

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Abstract

Slugs are significant agricultural pests, causing extensive crop damage and economic losses. While chemical molluscicides are commonly used for control, concerns about their environmental impact have driven interest in alternative methods, including beer traps. This study evaluated the effectiveness of different beer types [...] Read more.

Slugs are significant agricultural pests, causing extensive crop damage and economic losses. While chemical molluscicides are commonly used for control, concerns about their environmental impact have driven interest in alternative methods, including beer traps. This study evaluated the effectiveness of different beer types as attractants for slug trapping in field conditions over two consecutive years (2022–2023). Five types of beer—Union Lager, Paulaner Weissbier, BrewDog Punk IPA, Guinness Draught, and Chimay Blue—were tested alongside ethanol (10%) and a control treatment. The results demonstrated that Paulaner Weissbier and Union Lager were the most effective attractants, followed by Guinness Draught and Chimay Blue, while BrewDog Punk IPA had moderate effectiveness. Ethanol (10%) and the control treatment failed to attract slugs, confirming that volatile compounds, rather than alcohol alone, drive slug attraction. Gas chromatography–mass spectrometry (GC-MS) analysis revealed that Paulaner Weissbier contained high levels of isoamyl acetate and limonene, while Union Lager exhibited elevated ethyl esters, which likely contributed to their effectiveness. Environmental factors influenced slug activity, with higher temperatures correlating with increased slug capture rates, while precipitation had no significant effect. These findings highlight the role of fermentation-derived volatile compounds in slug attraction and suggest that optimizing beer traps based on beer composition and environmental conditions could improve their effectiveness as a non-chemical slug control method. Future research should explore the long-term stability of beer attractants, the potential of synthetic formulations, and alternative yeast-based attractants to enhance slug management strategies. Full article

(This article belongs to the Special Issue Development and Implementation of Integrated Pest Management (IPM) Methods for Irrigated Crops)

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18 pages, 2322 KiB

Open AccessArticle

Heavy Metal Contamination of Guizhou Tea Gardens: Soil Enrichment, Low Bioavailability, and Consumption Risks

by Zhonggen Li, Xuemei Cai, Guan Wang and Qingfeng Wang

Agriculture 2025, 15(10), 1096; https://doi.org/10.3390/agriculture15101096 - 19 May 2025

Viewed by 335

Abstract

The content and health impact of harmful heavy metals in agricultural products from strong geological background concentration areas have received increasing attention. To investigate the impact of soil heavy metal contamination on the tea plantation gardens of Guizhou Province, a major tea-producing area [...] Read more.

The content and health impact of harmful heavy metals in agricultural products from strong geological background concentration areas have received increasing attention. To investigate the impact of soil heavy metal contamination on the tea plantation gardens of Guizhou Province, a major tea-producing area with strong geological background concentrations in China, a total of 37 paired soil–tender tea leaf samples (containing one bud and two leaves) were collected and analyzed for eight harmful heavy metals. The results showed that the average contents of Hg, As, Pb, Cd, Cr, Ni, Sb, and Tl in the surface soil (0–20 cm) were 0.26, 23.9, 37.9, 0.29, 75.9, 37, 2.78, and 0.84 mg/kg, respectively. The majority of the soil Hg, As, Pb, Sb, and Tl levels exceeded their background values for cultivated land soil in Guizhou Province to some extent. The geo-accumulation index revealed that Sb and As are the main pollutants of tea garden soil. The average contents of Hg, As, Pb, Cd, Cr, Ni, Sb, and Tl in the tea leaves were 4, 49, 310, 55, 717, 12,100, 30, and 20 μg/kg (on a dry weight basis), respectively, all of which were significantly lower than their national recommended limits for tea. The bioconcentration factors of these eight heavy metals in tea leaves were relatively low when compared with those in soil, ranging between 0.003 (for As) and 0.603 (for Ni). The health risk assessment indicated that the total hazard quotient (THQ) due to drinking tea was in the order of Tl > Ni > As > Pb > Cd >Sb > Hg > Cr, with both the THQ for each heavy metal and the health risk index (HI) being less than 0.29, indicating that the risk of exposure to these heavy metals through drinking Guizhou green tea is low. Although some harmful heavy metals are present in the tea garden soil of Guizhou, their bioavailability for young tea leaves is extremely low. This may be related to the physical and chemical properties of the soil, such as the high proportion of organic matter (up to 9%) which strongly binds with these elements. Full article

(This article belongs to the Section Agricultural Soils)

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15 pages, 1610 KiB

Open AccessArticle

Growth and Yield of Two High-Density Tuono Almond Trees Planted at Two Different Intra-Row Spacings

by Annalisa Tarantino, Laura Frabboni and Grazia Disciglio

Agriculture 2025, 15(10), 1095; https://doi.org/10.3390/agriculture15101095 - 19 May 2025

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Abstract

One of the key techniques for successful almond tree cultivation in newly irrigated areas is increasing planting density. To investigate this, field experiments were carried out over five consecutive growing seasons (2019–2023) to evaluate the effects of two different tree densities on the [...] Read more.

One of the key techniques for successful almond tree cultivation in newly irrigated areas is increasing planting density. To investigate this, field experiments were carried out over five consecutive growing seasons (2019–2023) to evaluate the effects of two different tree densities on the vegetative growth and productivity of almond trees (Prunus dulcis, cv. Tuono) in a semi-arid climate in Southern Italy. The two planting densities tested were 1660 trees per hectare (achieved with 1.5 m intra-row spacing × 4.0 m inter-row spacing) and 833 trees per hectare (3.0 m × 4.0 m spacing). The results showed that significantly lower values of annual shoot length were recorded in both 2020 and 2021, years characterized by late frosts in March and April. However, with the exception of the first year (2019), when the plants had not yet been influenced by the different planting densities, the annual shoot length was significantly higher in the lowest planting density compared to the highest one in the following years. Additionally, higher annual trunk growth values were recorded at the lower planting density compared to the higher density. By the end of the five seasons, trees at the lower density showed a cumulative trunk growth of 177 mm, whereas those at the higher density reached only 137 mm. No significant effect of the two different tree planting densities on overall fruit development, specifically length, width, and thickness, was observed. As the trees matured, kernel yield per tree increased under both planting densities. However, significantly higher individual tree yields were recorded in the lower-density configuration, reaching 2.70 kg per tree by the end of five seasons, compared to 1.68 kg per tree in the high-density arrangement. In contrast, kernel yield per hectare was greater in the densely planted configuration, achieving 2.81 t ha⁻¹, whereas the lower-density planting resulted in a yield of 2.25 t ha⁻¹ by the end of the same period. Furthermore, no significant differences were observed between the two tree planting densities in terms of the percentage of hull per fruit, kernel per nut, or the occurrence of double seeds. Similarly, morphological traits of the nuts and kernels, such as weight, length, width, and thickness, remained unaffected. However, slightly higher kernel weights were noted at the lower planting density. Full article

(This article belongs to the Section Crop Production)

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17 pages, 973 KiB

Open AccessArticle

Enhancing Genomic Prediction Accuracy in Beef Cattle Using WMGBLUP and SNP Pre-Selection

by Huqiong Zhao, Xueyuan Xie, Haoran Ma, Peinuo Zhou, Boran Xu, Yuanqing Zhang, Lingyang Xu, Huijiang Gao, Junya Li, Zezhao Wang and Xiaoyan Niu

Agriculture 2025, 15(10), 1094; https://doi.org/10.3390/agriculture15101094 - 19 May 2025

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Abstract

Genomic selection (GS) plays a crucial role in livestock breeding. However, its implementation in Chinese beef cattle breeding is constrained by a limited reference population and incomplete data records. To address these challenges, this study aimed to identify more effective models for multi-population [...] Read more.

Genomic selection (GS) plays a crucial role in livestock breeding. However, its implementation in Chinese beef cattle breeding is constrained by a limited reference population and incomplete data records. To address these challenges, this study aimed to identify more effective models for multi-population genomic selection. We simulated five different beef cattle populations and selected three populations with varying levels of kinship to investigate the impact of population relationships on genomic prediction. Utilizing results from a genome-wide association study (GWAS), we preselected different proportions of single nucleotide polymorphism (SNP). Subsequently, we employed three models—genomic best linear unbiased prediction (GBLUP), multi-genomic best linear unbiased prediction (MGBLUP), and weighted multi-genomic best linear unbiased prediction (WMGBLUP)—for within-population and multi-population genomic prediction. Our results showed that increasing the size of the training set improved within-population prediction accuracy. Furthermore, both MGBLUP and WMGBLUP outperformed GBLUP in terms of prediction accuracy for both within-population and multi-population analyses. Among the models evaluated, the WMGBLUP model, which utilized the top 5% of preselected SNPs based on GWAS findings, demonstrated superior performance, yielding an improvement of up to 11.1% in within-population prediction and 16.5% in multi-population prediction. In summary, both WMGBLUP and MGBLUP models exhibit enhanced efficacy in improving genomic prediction accuracy, and the incorporation of GWAS results can further optimize their performance. Full article

(This article belongs to the Section Farm Animal Production)

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17 pages, 3691 KiB

Open AccessArticle

Geographical Types and Driving Mechanisms of Rural Population Aging–Weakening in the Yellow River Basin

by Zhanhui Fu, Yahan Yang and Shuju Hu

Agriculture 2025, 15(10), 1093; https://doi.org/10.3390/agriculture15101093 - 19 May 2025

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Abstract

Population aging–weakening has become a critical constraint on rural sustainability in China’s Yellow River Basin (YRB), posing substantial challenges to ecological conservation and high-quality development. This study develops a multidimensional evaluation framework categorizing rural aging–weakening into four typologies: general development type (GDT), shallow [...] Read more.

Population aging–weakening has become a critical constraint on rural sustainability in China’s Yellow River Basin (YRB), posing substantial challenges to ecological conservation and high-quality development. This study develops a multidimensional evaluation framework categorizing rural aging–weakening into four typologies: general development type (GDT), shallow aging–weakening type (SAT), medium aging–weakening type (MAT), and deep aging–weakening type (DAT). Then, the XGBoost model is used to assess the factors influencing the spatial diversity of aging–weakening types in the rural population at different spatial and temporal scales. The key findings reveal the following: (1) The proportion of aging–weakening areas increased from 65% (2000) to 72% (2020), exhibiting distinct regional trajectories. Upper reaches demonstrate severe manifestations (34% combined MAT/DAT in 2020), contrasting with middle reaches dominated by GDT/SAT (>80%). Lower reaches show accelerated deterioration (MAT/DAT surged from 10% to 31%). (2) Spatial differentiation primarily arises from terrain-habitat conditions, industrial capacity, urbanization, and agricultural income. While most factors maintained stable directional effects, agricultural income transitioned from positive to negative correlation post-2010. Upper/middle reaches are predominantly influenced by geographical environment, with the role of socioeconomic factors gradually increasing. Lower reaches exhibit stronger economic–environmental interactions. (3) This research provides actionable insights for differentiated regional strategies: upper reaches require ecological migration programs, middle areas need industrial transition support, while lower regions demand coordinated economic–environmental governance. Our typological framework offers methodological advancements for assessing demographic challenges in vulnerable watersheds, with implications extending to similar developing regions globally. Full article

(This article belongs to the Topic Remote Sensing and GIS for Monitoring Land Use Change and Its Ecological Effects)

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16 pages, 2042 KiB

Open AccessArticle

Microbial Population in Curcuma Species at Different Growth Stages

by Neptu Islamy Raharja, Mohammad Amzad Hossain and Hikaru Akamine

Agriculture 2025, 15(10), 1092; https://doi.org/10.3390/agriculture15101092 - 19 May 2025

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Abstract

Turmeric (Curcuma spp.) is widely cultivated in tropical regions for its use in traditional medicine and culinary purposes. This study investigated the bacterial populations in the rhizosphere, stems, and leaves of the Curcuma species and strains at different growth stages. Bacterial population [...] Read more.

Turmeric (Curcuma spp.) is widely cultivated in tropical regions for its use in traditional medicine and culinary purposes. This study investigated the bacterial populations in the rhizosphere, stems, and leaves of the Curcuma species and strains at different growth stages. Bacterial population cultivated in the field and plastic house showed variations across growth stages. The rhizosphere possessed the highest bacterial populations in both experiments (1.8 to 11.9 × 10⁶ CFU/g and 1.7 to 24.3 × 10⁶ CFU/g, respectively), with C. amada and Ryudai gold as the highest. Endophytic bacteria in stems and leaves also peaked at the middle growth stage. Principal Component Analysis (PCA) revealed distinct separations among Curcuma species planted in the field and plastic house at different growth stages. C. aromatica and C. longa strain L2 clustered differently under field conditions, while C. zedoaria and C. xanthorrhiza were distinct under plastic house conditions. Combined PCA revealed a clear separation between the field and plastic house, with tighter clustering observed in the plastic house. Leaf-associated bacterial populations were compositionally distinct from those in the rhizosphere and stems. These findings suggest that the Curcuma growth stage and species significantly affect bacterial community structure, supporting the development of targeted cultivation strategies and microbial applications to enhance productivity and sustainability in turmeric farming. Full article

(This article belongs to the Special Issue Beneficial Microbes for Sustainable Crop Production)

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20 pages, 1965 KiB

Open AccessArticle

Short-Term Effects of Wood Biochar on Soil Fertility, Heterotrophic Respiration and Organic Matter Composition

by Rossella Curcio, Raffaele Bilotti, Carmine Lia, Michele Compitiello, Silvana Cangemi, Mariavittoria Verrillo, Riccardo Spaccini and Pierluigi Mazzei

Agriculture 2025, 15(10), 1091; https://doi.org/10.3390/agriculture15101091 - 19 May 2025

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Abstract

Biochar may represent a sustainable and eco-friendly strategy to recycle agroforestry wastes, sequester carbon and improve soil health. With the aim of proving these benefits in a real scenario, we treated several soil parcels with 0 (CTRL), 1 (LOW) and 3 (HIGH) kg/m [...] Read more.

Biochar may represent a sustainable and eco-friendly strategy to recycle agroforestry wastes, sequester carbon and improve soil health. With the aim of proving these benefits in a real scenario, we treated several soil parcels with 0 (CTRL), 1 (LOW) and 3 (HIGH) kg/m² of wood biochar, in open-field trials. The heterotrophic soil respiration (SR) was monitored continuously for two months via a Closed Dynamic Chamber (CDC) associated with an innovative pilot system, and the most important soil chemical parameters were measured 9 and 54 days after biochar application. Biochar induced an immediate dose-dependent increase in organic matter content and CEC (up to 41.6% and 36.8% more than CTRL, respectively), which tended to slightly and gradually decrease after 54 days. In all cases, biochar induced a more pronounced SR, although the most enhanced microbial response was detected for the LOW parcel (19.3% higher than CTRL). Fennels were grown in treated soils and only LOW microplots gave a significantly better response (weight and size). Finally, NMR, FT-IR and Pyr-GC/MS analyses of LOW SOM extracts revealed a relevant impact on the composition, which was accompanied by a higher content of carbohydrates, indole-based compounds and FAME species correlating with enhanced microbial activity. Our findings demonstrate that the proper biochar dose improves soil fertility by creating an environment favorable to plants and promoting microbial activity. Full article

(This article belongs to the Section Agricultural Soils)

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18 pages, 2493 KiB

Open AccessArticle

Techno-Economic Analysis of Innovative Phytogenic-Based Supplements for Ruminant Health and Productivity

by Maria Spilioti, Konstantinos Tousis, Georgios Papakonstantinou, Eleftherios Meletis, Alexis Manouras, Eleftherios Nellas, Garyfalia Economou, Vasileios G. Papatsiros and Konstantinos Tsiboukas

Agriculture 2025, 15(10), 1090; https://doi.org/10.3390/agriculture15101090 - 18 May 2025

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Abstract

The aim of this study was to evaluate the technical and economic impact of using commercial phytogenic feed supplements and dried Greek Oregano leaves as feed additives on dairy sheep farms. Fifteen farms in the Greek region of Thessaly were divided into intervention [...] Read more.

The aim of this study was to evaluate the technical and economic impact of using commercial phytogenic feed supplements and dried Greek Oregano leaves as feed additives on dairy sheep farms. Fifteen farms in the Greek region of Thessaly were divided into intervention and control farms, and techno-economic data were collected before and after supplementation through structured interviews and cost analysis. The results showed that the administration of certain phytogenic supplements and oregano to ewes resulted in improved animal health, higher milk yield, and lower production costs, which created a positive trend in the financial results of the farm. Further research is needed to accurately determine the ideal production stage of the animals for the interventions, the amount of supplements administered, and the selection of appropriate plant species, which would lead to better financial management of the farms. Full article

(This article belongs to the Special Issue Assessing and Improving Farm Animal Welfare)

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17 pages, 4701 KiB

Open AccessArticle

Low-Injury Rubber Tapping Robots: A Novel PSO-PID Approach for Adaptive Depth Control in Hevea Brasiliensis

by Ruiwu Xu, Yulan Liao, Junxiao Liu, Zhifu Zhang and Xirui Zhang

Agriculture 2025, 15(10), 1089; https://doi.org/10.3390/agriculture15101089 - 18 May 2025

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Abstract

Rubber tapping robots represent a significant research direction in modern robotics in agricultural automation. Nevertheless, natural rubber tapping robots encounter considerable challenges in achieving precise tapping, particularly in controlling tapping depth, due to the lack of suitable control algorithms. To solve this problem, [...] Read more.

Rubber tapping robots represent a significant research direction in modern robotics in agricultural automation. Nevertheless, natural rubber tapping robots encounter considerable challenges in achieving precise tapping, particularly in controlling tapping depth, due to the lack of suitable control algorithms. To solve this problem, an improved Particle Swarm Optimization/Proportional–Integral–Derivative (PSO-PID) control method has been proposed in this paper. It enhances the inertia weight of the particle swarm by introducing adaptive inertia weight, solving the shortcomings of the traditional PSO algorithm, such as insufficient local search ability and early convergence. The experimental results show that the rubber tapping depth system based on the improved PSO-PID algorithm has high responsiveness and robustness, with an average settling time of 0.419 s and an overshoot that can be kept below 2.5%. The depth control accuracy, robustness and convergence speed of the system are significantly better than other well-known optimization algorithms. At a tapping depth of 3.0 mm, the injury rate was reduced to 2%, surpassing the level of skilled manual tapping workers. It has been proven that this method can effectively solve the key problem of accurate depth control in current rubber tapping. Full article

(This article belongs to the Section Agricultural Technology)

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22 pages, 46263 KiB

Open AccessArticle

The Rapid Detection of Foreign Fibers in Seed Cotton Based on Hyperspectral Band Selection and a Lightweight Neural Network

by Yeqi Fei, Zhenye Li, Dongyi Wang and Chao Ni

Agriculture 2025, 15(10), 1088; https://doi.org/10.3390/agriculture15101088 - 18 May 2025

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Abstract

Contamination with foreign fibers—such as mulch films and polypropylene strands—during cotton harvesting and processing severely compromises fiber quality. The traditional detection methods often fail to identify fine impurities under visible light, while full-spectrum hyperspectral imaging (HSI) techniques—despite their effectiveness—tend to be prohibitively expensive [...] Read more.

Contamination with foreign fibers—such as mulch films and polypropylene strands—during cotton harvesting and processing severely compromises fiber quality. The traditional detection methods often fail to identify fine impurities under visible light, while full-spectrum hyperspectral imaging (HSI) techniques—despite their effectiveness—tend to be prohibitively expensive and computationally intensive. Specifically, the vast amount of redundant spectral information in full-spectrum HSI escalates both the system’s costs and processing challenges. To address these challenges, this study presents an intelligent detection framework that integrates optimized spectral band selection with a lightweight neural network. A novel hybrid Harris Hawks–Whale Optimization Operator (HWOO) is employed to isolate 12 discriminative bands from the original 288 channels, effectively eliminating redundant spectral data. Additionally, a lightweight attention mechanism, combined with a depthwise convolution module, enables real-time inference for online production. The proposed attention-enhanced CNN architecture achieves a 99.75% classification accuracy with real-time processing at 12.201 μs per pixel, surpassing the full-spectrum models by 11.57% in its accuracy while drastically reducing the processing time from 370.1 μs per pixel. This approach not only enables the high-speed removal of impurities in harvested seed cotton production lines but also offers a cost-effective pathway to practical multispectral solutions. Moreover, this methodology demonstrates broad applicability for quality control in agricultural product processing. Full article

(This article belongs to the Section Digital Agriculture)

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20 pages, 5255 KiB

Open AccessArticle

YOLOv8-SDC: An Improved YOLOv8n-Seg-Based Method for Grafting Feature Detection and Segmentation in Melon Rootstock Seedlings

by Lixia Li, Kejian Gong, Zhihao Wang, Tingna Pan and Kai Jiang

Agriculture 2025, 15(10), 1087; https://doi.org/10.3390/agriculture15101087 - 17 May 2025

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Abstract

To address the multi-target detection problem in the automatic seedling-feeding procedure of vegetable-grafting robots from dual perspectives (top-view and side-view), this paper proposes an improved YOLOv8-SDC detection segmentation model based on YOLOv8n-seg. The model improves rootstock seedlings’ detection and segmentation accuracy by SAConv [...] Read more.

To address the multi-target detection problem in the automatic seedling-feeding procedure of vegetable-grafting robots from dual perspectives (top-view and side-view), this paper proposes an improved YOLOv8-SDC detection segmentation model based on YOLOv8n-seg. The model improves rootstock seedlings’ detection and segmentation accuracy by SAConv replacing the original Conv c2f_DWRSeg module, replacing the c2f module, and adding the CA mechanism. Specifically, the SAConv module dynamically adjusts the receptive field of convolutional kernels to enhance the model’s capability in extracting seedling shape features. Additionally, the DWR module enables the network to more flexibly adapt to the perception accuracy of different cotyledons, growth points, stem edges, and contours. Furthermore, the incorporated CA mechanism helps the model eliminate background interference for better localization and identification of seedling grafting characteristics. The improved model was trained and validated using preprocessed data. The experimental results show that YOLOv8-SDC achieves significant accuracy improvements over the original YOLOv8n-seg model, YOLACT, Mask R-CNN, YOLOv5, and YOLOv11 in both object detection and instance segmentation tasks under top-view and side-view conditions. The mAP of Box and Mask for cotyledon (leaf1, leaf2, leaf), growing point (pot), and seedling stem (stem) assays reached 98.6% and 99.1%, respectively. The processing speed reached 200 FPS. The feasibility of the proposed method was further validated through grafting features, such as cotyledon deflection angles and stem–cotyledon separation points. These findings provide robust technical support for developing an automatic seedling-feeding mechanism in grafting robotics. Full article

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

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17 pages, 887 KiB

Open AccessArticle

Biomass, Physiological, and Antioxidant Activity Responses of Wheat Plants After Selenium Foliar Spray Under Water Deficit

by Luís Rocha, Ermelinda Silva, Alexandre Gonçalves, Cátia Brito, Helena Ferreira, Carlos Matos, Aureliano C. Malheiro, Susana Araújo, José Lima-Brito and José Moutinho-Pereira

Agriculture 2025, 15(10), 1086; https://doi.org/10.3390/agriculture15101086 - 17 May 2025

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Abstract

The ability of selenium (Se) to trigger modifications in plant metabolism, thereby triggering tolerance to abiotic stresses, is well established. This research aimed to understand the following: (1) how Se supplementation in wheat plants can lead to beneficial Se concentrations in grains and [...] Read more.

The ability of selenium (Se) to trigger modifications in plant metabolism, thereby triggering tolerance to abiotic stresses, is well established. This research aimed to understand the following: (1) how Se supplementation in wheat plants can lead to beneficial Se concentrations in grains and straw; (2) whether the applied Se concentrations have any negative impacts on plant performance; and (3) if Se can aid wheat development under water-limited conditions. To address this, we evaluated the physiological, biochemical, and morphological effects of foliar Se application on wheat plants subjected to well-watered (WW, full irrigation) and water-deficit (WD, 25% of full irrigation) regimes. Three foliar concentrations of sodium selenate (Se) solution (0, 16, and 160 g ha⁻¹ Se) were tested. Under WW, treatment with 160 g/ha leads to the highest Se content in straw (4253 ± 171 µg plant⁻¹), enhanced straw biomass accumulation, and increased total soluble sugar content. WW plants treated with 16 g/ha Se were found to have the highest amounts of photosynthetic pigments and total soluble proteins. Under WD, Se treatments increased spike length, total phenols, and ortho-diphenols when compared to Se-untreated plants. In general, Se treatments increased the Se contents in both straw and grains, but with a noticeably higher accumulation in straw. Altogether, the results suggest that foliar application of 160 g/ha Se, under irrigation, is a promissory approach to enhance Se content in bread wheat. Full article

(This article belongs to the Section Crop Production)

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14 pages, 460 KiB

Open AccessArticle

Optimization of Deoxynivalenol Removal from Wheat Grains Using Single- and Multi-Frequency Ultrasound and Impact on Quality Characteristics

by Bengang Wu, Chenyu Song, Shenao Nan, Baosheng Sun, Haile Ma and Yiting Guo

Agriculture 2025, 15(10), 1085; https://doi.org/10.3390/agriculture15101085 - 17 May 2025

Viewed by 261

Abstract

This study systematically investigated the efficacy of ultrasound technology in removing deoxynivalenol (DON, also known as vomitoxin) from contaminated wheat grains and its impact on grain quality. By applying different ultrasonic frequencies (single-frequency 22 kHz, dual-frequency 22/40 kHz, and tri-frequency 22/33/40 kHz) and [...] Read more.

This study systematically investigated the efficacy of ultrasound technology in removing deoxynivalenol (DON, also known as vomitoxin) from contaminated wheat grains and its impact on grain quality. By applying different ultrasonic frequencies (single-frequency 22 kHz, dual-frequency 22/40 kHz, and tri-frequency 22/33/40 kHz) and treatment durations (10–40 min), the removal efficiency of DON and changes in quality characteristics—including moisture content, weight gain, solid loss, color, hardness, and viscosity—were analyzed. Experimental results demonstrated that dual-frequency ultrasound (22/40 kHz) achieved the highest DON removal rate (25.84%) after 40 min, significantly outperforming single- and tri-frequency treatments. Ultrasound treatment increased the moisture content and weight of wheat grains, reduced hardness (though without significant differences), and affected color and viscosity. This study revealed that multi-frequency ultrasound enhances DON removal through synergistic cavitation effects, with dual-frequency ultrasound offering a superior balance between removal efficiency and energy consumption. This research provides a theoretical foundation and technical references for the safe and efficient elimination of DON contamination in wheat. Full article

(This article belongs to the Special Issue Agricultural Products Processing and Quality Detection)

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20 pages, 7158 KiB

Open AccessArticle

Three Decades of Tillage Driven Topsoil Displacement and Soil Erosion Attenuation on Loess Plateau Slope Farmlands

by Shuanhu Li, Bohan Zhao, Huimin Wu, Rongbiao Li and Ping Wang

Agriculture 2025, 15(10), 1084; https://doi.org/10.3390/agriculture15101084 - 17 May 2025

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Abstract

The slope lands of the Loess Plateau represent a critical region impacted by soil erosion, which directly contributes to the globally recognized high sediment concentration in the Yellow River. However, the extent to which sloped farmland contributes to soil loss remains scientifically contentious. [...] Read more.

The slope lands of the Loess Plateau represent a critical region impacted by soil erosion, which directly contributes to the globally recognized high sediment concentration in the Yellow River. However, the extent to which sloped farmland contributes to soil loss remains scientifically contentious. In this study, farmland with an initial slope gradient of 20° was selected for the experiment, and three decades of field monitoring data (1990s–2020s) and the Universal Soil Loss Equation (USLE) model were used for comparative calculation. The data indicated that the model-predicted soil loss rate in sloped farmland from the 1990s to the 2020s was calculated to be 62.48 t·ha⁻¹·yr⁻¹. Field-measured values averaged 45.67 t·ha⁻¹·yr⁻¹, whereas the current value is approximately 15.00 t·ha⁻¹·yr⁻¹. Anthropogenic disturbances, including tillage, manual weeding, and ovine grazing, mean that the topsoil of slope farmland has undergone cumulative displacement of 450~870 cm in 30 years, which is resulting in progressive slope gradient reduction from 20° to 5°. The soil erosion rates exhibited exponential decay characteristics, and finally gradually reached the level of flat farmland. When using the USLE model, the evolving slope gradient must be incorporated, rather than the slope angle extracted by DEM. Therefore, the key finding of this study is that the primary sources of soil loss in the Loess Plateau are non-agricultural slopes and gullies. Conversely, soil erosion on slope farmlands does not constitute a critical problem requiring urgent intervention. This finding should attract the attention of the local agricultural sector. Full article

(This article belongs to the Section Agricultural Soils)

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