Agriculture

21 pages, 921 KiB

Open AccessArticle

Research on the Water–Energy–Carbon Coupling Changes and Their Influencing Factors in the Henan Section of the Sha Ying River Basin, China

by Xueke Liu, Yong Wu, Ling Li, Chi Sun, Jianwei Liu and Wenzhen Wang

Agriculture 2025, 15(11), 1165; https://doi.org/10.3390/agriculture15111165 - 28 May 2025

Abstract

The Henan section of the Sha Ying River Basin, as the core agricultural area of the Central Plains Urban Agglomeration (CPUA), plays a significant role in promoting regional green and sustainable development through the coordinated management of water–energy–carbon (WEC). This study takes the [...] Read more.

The Henan section of the Sha Ying River Basin, as the core agricultural area of the Central Plains Urban Agglomeration (CPUA), plays a significant role in promoting regional green and sustainable development through the coordinated management of water–energy–carbon (WEC). This study takes the Henan section of the Sha Ying River Basin as a case study to analyze the spatiotemporal evolution characteristics of the region from 2010 to 2022, establish an evaluation system to assess the level of coupled coordination development, and utilize the gray correlation model to identify key influencing factors. The results show a fluctuating downward trend in WEC consumption, with low coupling coordination transitioning from high coordination to moderate imbalance. Key factors influencing coupling coordination include water consumption per 10,000 CNY of GDP, agricultural industry structure, and year-end population. Spatial heterogeneity in WEC coupling coordination factors was observed across cities. This research provides a scientific basis for understanding ecosystem dynamics in agricultural cities and supports differentiated environmental policies for sustainable regional development. Full article

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

26 pages, 7751 KiB

Open AccessArticle

Twenty-Year Variability in Water Use Efficiency over the Farming–Pastoral Ecotone of Northern China: Driving Force and Resilience to Drought

by Xiaonan Guo, Meng Wu, Zhijun Shen, Guofei Shang, Qingtao Ma, Hongyu Li, Lei He and Zhao-Liang Li

Agriculture 2025, 15(11), 1164; https://doi.org/10.3390/agriculture15111164 - 28 May 2025

Abstract

Water use efficiency (WUE), as an important metric for ecosystem resilience, has been identified to play a significant role in the coupling of carbon and water cycles. The farming–pastoral ecotone of Northern China (FPENC), which is highly susceptible to drought due to water [...] Read more.

Water use efficiency (WUE), as an important metric for ecosystem resilience, has been identified to play a significant role in the coupling of carbon and water cycles. The farming–pastoral ecotone of Northern China (FPENC), which is highly susceptible to drought due to water scarcity, has long been recognized as an ecologically fragile zone. The ecological restoration projects in China have mitigated land degradation and maintain the sustainability of dryland. However, the process of greening in drylands has the potential to impact water availability. A comprehensive analysis of the WUE in the FPENC can help to understand the carbon absorption and water consumption. Using gross primary production (GPP) and evapotranspiration (ET) data from a MODerate resolution Imaging Spectroradiometer (MODIS), alongside biophysical variables data and land cover information, the spatio-temporal variations in WUE from 2003 to 2022 were examined. Additionally, its driving force and the ecosystem resilience were also revealed. Results indicated that the annual mean of WUE fluctuated between 0.52 and 2.60 gC kgH₂O⁻¹, showing a non-significant decreasing trend across the FPENC. Notably, the annual averaged WUE underwent a significant decline before 2012 (p < 0.05), and then showed a slight increased trend (p = 0.14) during the year afterward (i.e., 2013–2022). In terms of climatic controls, temperature (Temp) and soil volumetric water content (VSWC) dominantly affected WUE from 2003 to 2012; VPD (vapor pressure deficit), VSWC, and Temp showed comprehensive controls from 2013 to 2022. The findings suggest that a wetter atmosphere and increased soil moisture contribute to the decline in WUE. In total, 59.2% of FPENC was shown to be non-resilient, as grassland occupy the majority of the area, located in Mu Us Sandy land and Horqin Sand Land. These results underscore the importance of climatic factors in the regulation WUE over FPENC and highlight the necessity for focused research on WUE responses to climate change, particularly extreme events like droughts, in the future. Full article

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

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24 pages, 2212 KiB

Open AccessArticle

Analysis of the Interactive Response Relationships Between Agricultural Pollution Reduction and Carbon Emission Mitigation and Agricultural Economic Development: A Case Study of Henan Province, China

by Hanghang Fan, Ling Li, Xingming Li, Yongjie Yu, Yong Wu, Donghao Li, Jianwei Liu and Xiuli Wang

Agriculture 2025, 15(11), 1163; https://doi.org/10.3390/agriculture15111163 - 28 May 2025

Abstract

Ensuring the synergistic advancement of agricultural pollution reduction and carbon emission mitigation, along with sustainable development, is crucial for achieving the ‘dual carbon’ target and modernizing agriculture. To ensure sustainable agricultural development, this study employs a coupling coordination model to explore the synergistic [...] Read more.

Ensuring the synergistic advancement of agricultural pollution reduction and carbon emission mitigation, along with sustainable development, is crucial for achieving the ‘dual carbon’ target and modernizing agriculture. To ensure sustainable agricultural development, this study employs a coupling coordination model to explore the synergistic effects of pollution reduction and carbon emission mitigation in Henan Province, considering the agricultural carbon emissions (ACEs), agricultural non-point source pollution (ANP), and the gross value of agricultural output (GVAO) of 18 cities in Henan from 2010 to 2022 as endogenous variables. A panel vector autoregression (PVAR) model is utilized to analyze the interactive responses between agricultural pollution reduction and carbon emission mitigation and agricultural economic development. The results indicate that the degree of synergy between ACE and ANP in Henan Province has shown a trend towards higher values and a diminishing polarization phenomenon between 2010 and 2022, with most regions having degrees of synergy at higher levels. Furthermore, the interactive response relationships between agricultural pollution reduction and carbon emission mitigation and agricultural economic development reveals that the GVAO in Henan Province has a significant positive impact on both ACE and ANP, and that agricultural pollution reduction and carbon emission mitigation are constrained by agricultural economic development, with no significant bidirectional causal relationship observed overall and a lack of positive interaction in the long term. Finally, ACE, ANP, and GVAO in Henan Province exhibit a strong self-reinforcing mechanism, particularly ACE and GVAO, which show a pronounced self-growth trend. Overall, Henan Province should fully utilize the synergistic effects of agricultural pollution reduction and carbon emission mitigation to achieve coordinated progress in agricultural pollution reduction and carbon emission mitigation, as well as green and sustainable development of the agricultural economy. Full article

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

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16 pages, 460 KiB

Open AccessArticle

Generational Preferences and Willingness to Pay for Antioxidant-Rich Pomegranates: Insights into Consumer Behavior and Market Potential

by Anna Uliano and Marco Lerro

Agriculture 2025, 15(11), 1162; https://doi.org/10.3390/agriculture15111162 - 28 May 2025

Abstract

This study investigates consumer preferences and willingness to pay (WTP) for antioxidant-rich pomegranates, focusing on the roles of product attributes and generational differences. A survey of 3019 Italian consumers assessed consumption habits, perceived barriers, and WTP for antioxidant-enriched pomegranates. A Best–Worst Scaling (BWS) [...] Read more.

This study investigates consumer preferences and willingness to pay (WTP) for antioxidant-rich pomegranates, focusing on the roles of product attributes and generational differences. A survey of 3019 Italian consumers assessed consumption habits, perceived barriers, and WTP for antioxidant-enriched pomegranates. A Best–Worst Scaling (BWS) analysis was used to identify key product attributes, and generational segmentation highlighted differences in consumer behavior. The results reveal a strong preference for locally sourced pomegranates and a high valuation of health-related attributes, particularly antioxidant content. However, several consumption barriers emerged, including taste preferences, peeling difficulty, and limited product availability. While older generations, especially Baby Boomers, prioritize antioxidants for their health benefits, younger generations (Gen Z and Millennials) showed the highest WTP for antioxidant-enriched pomegranates, likely influenced by novelty seeking and engagement with food trends. These findings suggest that marketing strategies should emphasize both local origins and health benefits. From a policy perspective, supporting local agriculture and promoting the nutritional value of enriched foods could enhance consumer acceptance and expand the market potential. Full article

(This article belongs to the Special Issue Innovation and Sustainability in Agribusiness: Policies and Market Dynamics)

16 pages, 2615 KiB

Open AccessArticle

GIS Bioclimatic Profile and Seed Germination of the Endangered and Protected Cretan Endemic Plant Campanula cretica (A. DC.) D. Dietr. for Conservation and Sustainable Utilization

by Theodora-Nafsika Panagiotidou, Ioannis Anestis, Elias Pipinis, Stefanos Kostas, Georgios Tsoktouridis, Stefanos Hatzilazarou and Nikos Krigas

Agriculture 2025, 15(11), 1161; https://doi.org/10.3390/agriculture15111161 - 28 May 2025

Abstract

This study focused on the seed germination of the local Cretan endemic Campanula cretica, an endangered and nationally protected species with ornamental value. To determine its seed germination requirements, high-resolution bioclimatic (temperature and precipitation) maps were integrated with geographic distribution data of [...] Read more.

This study focused on the seed germination of the local Cretan endemic Campanula cretica, an endangered and nationally protected species with ornamental value. To determine its seed germination requirements, high-resolution bioclimatic (temperature and precipitation) maps were integrated with geographic distribution data of C. cretica using Geographic Information Systems. The seed germination was tested at four constant temperatures (10, 15, 20, and 25 °C) with a photoperiod of 12 h light/12 h dark and under light/darkness and darkness at 15 °C. Pre-treatments with gibberellic acid solutions (500 and 1000 mg·L⁻¹ GA₃) and cold moist stratification at 5 °C were applied to investigate seed dormancy. Seed germination was significantly affected by the interaction of temperature and seed pre-treatments; without pre-treatment, the seeds germinated better (>85%) at 10 and 15 °C. The detected seed germination pattern matched the natural temperatures prevailing in situ during late autumn. Pre-treatments with GA₃ solutions and cold stratification first reported herein widened the seed germination range at 20 and 25 °C. The seeds germinated better in light (94.38%) than in darkness (69.38%). The results of this investigation addressed existing research gaps (GIS-derived bioclimatic profiling, effects of incubation temperature, cold stratification, GA₃, and light investigated for the first time), thus facilitating species-specific conservation efforts and enabling sustainable utilization strategies. Full article

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

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23 pages, 3581 KiB

Open AccessArticle

Apple Trajectory Prediction in Orchards: A YOLOv8-EK-IPF Approach

by Jinxing Niu, Zhengyi Liu, Shuo Wang, Jiaxi Huang and Junlong Zhao

Agriculture 2025, 15(11), 1160; https://doi.org/10.3390/agriculture15111160 - 28 May 2025

Abstract

To address the challenge of accurate apple harvesting by orchard robots, which is hindered by dynamic changes in apple position due to wind interference and branch swaying, this study proposes an optimized prediction algorithm based on an integration of the extended Kalman filter [...] Read more.

To address the challenge of accurate apple harvesting by orchard robots, which is hindered by dynamic changes in apple position due to wind interference and branch swaying, this study proposes an optimized prediction algorithm based on an integration of the extended Kalman filter (EKF) and an improved particle filter (IPF), built upon initial apple detection and recognition using YOLOv8. The algorithm first employs spatial partitioning according to the cyclical motion patterns of apples to constrain the prediction results. Subsequently, it optimizes the rationality of particle weights within the particle filter (PF) and reduces its computational resource consumption by implementing historical position weighting and an adaptive particle number strategy. Finally, an adaptive error correction mechanism dynamically adjusts the respective weights of the EKF and IPF components, continuously enhancing the algorithm’s prediction accuracy. Experimental results demonstrate that, compared to the classic unscented Kalman filter (UKF) and unscented particle filter (UPF), the proposed EK-IPF algorithm reduces the mean absolute error (MAE) by 22.25% and 10.89%, respectively, and the root mean square error (RMSE) by 23.70% and 13.25%, respectively, indicating a significant improvement in overall prediction accuracy. This research provides technical support for dynamic apple trajectory prediction in orchard environments. Full article

(This article belongs to the Section Digital Agriculture)

19 pages, 1570 KiB

Open AccessArticle

Properties of Grassland Habitats in Organic and Conventional Farms Located in Mountainous Areas—A Case Study from the Western Sudetes

by Krzysztof Solarz, Agnieszka Dradrach, Marta Czarniecka-Wiera, Adam Bogacz and Anna Karczewska

Agriculture 2025, 15(11), 1159; https://doi.org/10.3390/agriculture15111159 - 28 May 2025

Abstract

Organic farming is becoming increasingly important in agricultural production, especially in mountain and foothill areas. In organic farms, unlike conventional ones, no mineral fertilization or chemical plant protection is used, which often limits the economic efficiency of production. It is commonly believed that [...] Read more.

Organic farming is becoming increasingly important in agricultural production, especially in mountain and foothill areas. In organic farms, unlike conventional ones, no mineral fertilization or chemical plant protection is used, which often limits the economic efficiency of production. It is commonly believed that conventional farming poses a threat to biodiversity due to the use of mineral fertilization, chemical plant protection, and highly productive crop varieties, and the products obtained are in many respects of lower quality than those from organic farms. The aim of this work is to compare the quality and fertility of soils and the biodiversity of grasslands in organic and conventional farms, using the example of a foothill area within the commune of Kamienna Góra located in the Western Sudetes. Thirty-three areas representing 11 farms that produce dairy cattle in a grazing system were selected for analysis. The properties of soils in organic and conventional farms and their nutrient status did not differ significantly, except for the content of available potassium, which was higher in the group of organic farms. This fact seems to be related to the type of parent rock. All soils had acidic, slightly acidic, or strongly acidic pH levels. The greatest differences between pastures in organic and conventional farms concerned the sward species composition and biodiversity indices. Grasslands in organic farms were much richer in species, which was reflected by the species richness (SR) index and the F-fidelity index. The species inventoried clearly formed two groups that are characteristic of organic and conventional grasslands. The greater biodiversity of grasslands in organic farms did not have a significant effect on the fodder value of the sward, which should be considered good, allowing producers to participate in short supply chains. However, in all farms, regardless of their type, it would be advisable to carry out gentle liming. Full article

(This article belongs to the Section Agricultural Systems and Management)

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37 pages, 14623 KiB

Open AccessReview

Research Review of Agricultural Machinery Power Chassis in Hilly and Mountainous Areas

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

Agriculture 2025, 15(11), 1158; https://doi.org/10.3390/agriculture15111158 - 28 May 2025

Abstract

The terrain in hilly and mountainous areas is complex, and the level of agricultural mechanization is low. This article systematically reviews the research progress of key technologies for agricultural machinery power chassis in hilly and mountainous areas, and conducts an analysis of five [...] Read more.

The terrain in hilly and mountainous areas is complex, and the level of agricultural mechanization is low. This article systematically reviews the research progress of key technologies for agricultural machinery power chassis in hilly and mountainous areas, and conducts an analysis of five aspects: the power system, walking system, steering system, leveling system, and automatic navigation and path tracking control system. In this manuscript, (1) in terms of the power system, the technical characteristics and application scenarios of mechanical, hydraulic, and electric drive systems were compared. (2) In terms of the walking system, the performance differences between wheeled, crawler, legged, and composite walking devices and the application of suspension systems in agricultural machinery chassis were discussed. (3) In terms of the steering system, the steering characteristics of wheeled chassis and crawler chassis were analyzed, respectively. (4) In terms of the leveling system, the research progress on hydraulic and electric leveling mechanisms, as well as intelligent leveling control algorithms, was summarized. (5) The technology of automatic navigation and path tracking for agricultural machinery chassis was discussed, focusing on multi-sensor fusion and advanced control algorithms. In the future, agricultural machinery chassis will develop towards the directions of intelligence, automation, greening, being lightweight, and being multi-functionality. Full article

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

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34 pages, 3464 KiB

Open AccessReview

Addressing Biological Invasions in Agriculture with Big Data in an Informatics Age

by Rebecca A. Clement, Hyoseok Lee, Nicholas C. Manoukis, Yelena M. Pacheco, Fallon Ross, Mark S. Sisterson and Christopher L. Owen

Agriculture 2025, 15(11), 1157; https://doi.org/10.3390/agriculture15111157 - 28 May 2025

Abstract

Big data approaches are rapidly expanding across many fields of science and are seeing increasing application, yet the use of big data in research related to invasive species lags. Big data can play a key role in predicting, detecting, preventing, controlling, and eradicating [...] Read more.

Big data approaches are rapidly expanding across many fields of science and are seeing increasing application, yet the use of big data in research related to invasive species lags. Big data can play a key role in predicting, detecting, preventing, controlling, and eradicating biological invasions. Here, we assess terms in the literature related to big data, biological invasions, and agriculture and review sources of big data, including museum records, crowdsourcing observations, natural history collections, and DNA-based information. These sources can be combined with environmental data to build models, predict the origins of invasive species, and develop control methods. To harness the power of data for agricultural biological invasions, several action areas are recommended to streamline processes and improve data sources. Full article

(This article belongs to the Section Digital Agriculture)

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33 pages, 7582 KiB

Open AccessArticle

Three-Dimensional Path Planning for Unmanned Aerial Vehicles Based on Hybrid Multi-Strategy Dung Beetle Optimization Algorithm

by Hongmei Fei, Ruru Liu, Leilei Dong, Zhaohui Du, Xuening Liu, Tao Luo and Jie Zhou

Agriculture 2025, 15(11), 1156; https://doi.org/10.3390/agriculture15111156 - 28 May 2025

Abstract

In complex environments, three-dimensional path planning for agricultural UAVs involves the comprehensive consideration of multiple factors, including obstacle avoidance, path optimization, and computational efficiency, which significantly complicates the achievement of safe and efficient flight. As environmental complexity increases, the search space expands exponentially, [...] Read more.

In complex environments, three-dimensional path planning for agricultural UAVs involves the comprehensive consideration of multiple factors, including obstacle avoidance, path optimization, and computational efficiency, which significantly complicates the achievement of safe and efficient flight. As environmental complexity increases, the search space expands exponentially, thereby making the problem more challenging to solve and categorizing it as an NP-hard problem. To obtain an optimal or near-optimal path within this vast search space, it is essential to balance the path length, safety, and computational cost. This paper proposes a novel UAV path planning method based on the Hybrid Multi-Strategy Dung Beetle Optimization Algorithm (HMSDBO), which effectively reduces path length and improves path smoothness. First, a new Latin hypercube sampling strategy is introduced to significantly enhance the population diversity and improve the global search capabilities. Furthermore, an innovative golden sine strategy is proposed to greatly enhance the algorithm’s robustness. Lastly, a new hybrid adaptive weighting strategy is employed to improve the algorithm’s stability and reliability. To validate the effectiveness of HMSDBO, this study compares its performance with that of the Adaptive Chaotic Gray Wolf Optimization Algorithm (ACGWO), Primitive Dung Beetle Optimization Algorithm (DBO), Whale Optimization Algorithm (WOA), Crayfish Optimization Algorithm (COA), and Hyper-Heuristic Whale Optimization Algorithm (HHWOA) in complex agricultural UAV environments. Experimental results show that the path lengths calculated by HMSDBO are reduced by 21.3%, 7.88%, 19.95%, 8.09%, and 4.2%, respectively, compared to the aforementioned algorithms. This reduction significantly enhances both the optimization effectiveness and the smoothness of three-dimensional path planning for agricultural UAVs. Full article

(This article belongs to the Section Digital Agriculture)

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17 pages, 1752 KiB

Open AccessArticle

Carbon–Nitrogen Management via Glucose and Urea Spraying at the Booting Stage Improves Lodging Resistance in Fragrant Rice

by Wenjun Xie, Yiming Mai, Yixian Ma and Zhaowen Mo

Agriculture 2025, 15(11), 1155; https://doi.org/10.3390/agriculture15111155 - 28 May 2025

Abstract

Rice is an important crop that significantly contributes to food security. Lodging is considered an important factor limiting rice yield and quality. The objective of this study was to investigate the effects of carbon and nitrogen on lodging in fragrant rice. A 2-year [...] Read more.

Rice is an important crop that significantly contributes to food security. Lodging is considered an important factor limiting rice yield and quality. The objective of this study was to investigate the effects of carbon and nitrogen on lodging in fragrant rice. A 2-year field experiment (2021 to 2022) was conducted with the fragrant rice cultivars Meixiangzhan 2 and Xiangyaxiangzhan grown under nine carbon and nitrogen co-application treatments (CK: 0 mg/L glucose + 0 mg/L urea; T1: 0 mg/L glucose + 50 mg/L urea; T2: 0 mg/L glucose + 100 mg/L urea; T3: 150 mg/L glucose + 0 mg/L urea; T4: 150 mg/L glucose + 50 mg/L urea; T5: 150 mg/L glucose + 100 mg/L urea; T6: 300 mg/L glucose + 0 mg/L urea; T7: 300 mg/L glucose + 50 mg/L urea; and T8: 300 mg/L glucose + 100 mg/L urea). The lodging index and stem characteristics of fragrant rice were investigated. Compared with the CK treatment, the T5 and T7 treatments significantly increased the pushing resistance force by 22.22–127.78% and 50.00–77.50%, respectively. Compared with the other fertilization treatments, the T5 treatment kept the lodging index at a low level and reduced the plant height. The stem characteristics were regulated under the carbon and nitrogen co-application treatments, and the internode length and dry weight significantly influenced the plant height and the pushing resistance force and then regulated the lodging index. Structural equation modeling and random forest modeling analyses suggest that carbon and nitrogen co-application treatments may further improve the resistance of rice to lodging by increasing the dry weight of the third and fourth internodes. Overall, optimized carbon and nitrogen co-application could regulate stem internode morphology and improved lodging resistance. Furthermore, the T5 treatment (150 mg/L glucose + 100 mg/L urea) improved lodging resistance. This study provides guidelines for enhancing lodging resistance by regulating internode characteristics via the co-application of carbon and nitrogen at the booting stage in fragrant rice. Full article

(This article belongs to the Special Issue The Responses of Food Crops to Fertilization and Conservation Tillage)

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15 pages, 62527 KiB

Open AccessArticle

Towards Intelligent Pruning of Vineyards by Direct Detection of Cutting Areas

by Elia Pacioni, Eugenio Abengózar, Miguel Macías Macías, Carlos J. García-Orellana, Ramón Gallardo and Horacio M. González Velasco

Agriculture 2025, 15(11), 1154; https://doi.org/10.3390/agriculture15111154 - 27 May 2025

Abstract

The development of robots for automatic pruning of vineyards using deep learning techniques seems feasible in the medium term. In this context, it is essential to propose and study solutions that can be deployed on portable hardware, with artificial intelligence capabilities but reduced [...] Read more.

The development of robots for automatic pruning of vineyards using deep learning techniques seems feasible in the medium term. In this context, it is essential to propose and study solutions that can be deployed on portable hardware, with artificial intelligence capabilities but reduced computing power. In this paper, we propose a novel approach to vineyard pruning by direct detection of cutting areas in real time by comparing Mask R-CNN and YOLOv8 performances. The studied object segmentation architectures are able to segment the image by locating the trunk, and pruned and not pruned vine shoots. Our study analyzes the performance of both frameworks in terms of segmentation efficiency and inference times on a Jetson AGX Orin GPU. To compare segmentation efficiency, we used the mAP50 and AP50 per category metrics. Our results show that YOLOv8 is superior both in segmentation efficiency and inference time. Specifically, YOLOv8-S exhibits the best tradeoff between efficiency and inference time, showing an mAP50 of 0.883 and an AP50 of 0.748 for the shoot class, with an inference time of around 55 ms on a Jetson AGX Orin. Full article

(This article belongs to the Special Issue Application of Vision Technology and Artificial Intelligence in Smart Farming—2nd Edition)

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24 pages, 5544 KiB

Open AccessArticle

Coupling Coordination Development Between Cultivated Land and Agricultural Water Use Efficiency in Arid Regions: A Case Study of the Turpan–Hami Basin

by Yue Kong, Abdugheni Abliz, Dongping Guo, Xianhe Liu, Jialin Li and Buasi Nurahmat

Agriculture 2025, 15(11), 1153; https://doi.org/10.3390/agriculture15111153 - 27 May 2025

Abstract

The coupling coordination relationship between cultivated land and water resources in arid regions is crucial for ecological security and sustainable food production. This study explores the interaction between these resources to optimize the allocation of water–land resources, ecological resources, and agricultural resources and [...] Read more.

The coupling coordination relationship between cultivated land and water resources in arid regions is crucial for ecological security and sustainable food production. This study explores the interaction between these resources to optimize the allocation of water–land resources, ecological resources, and agricultural resources and promote synergistic development. Taking the Turpan–Hami Basin as a case study, this research analyzed the utilization efficiency of cultivated land and agricultural water resources from 2000 to 2023 using a super-efficiency SBM-DEA model. A coupling coordination degree model was constructed to evaluate their coordinated development level, with spatial autocorrelation and other methods used to examine spatiotemporal patterns. Key findings include: (1) The overall utilization efficiency of both resources was relatively low, with mean values of 0.516 and 0.596, showing a fluctuating upward trend and significant spatial heterogeneity; (2) The mean coupling coordination degree (CCD) ranked as follows: Barkol Kazakh Autonomous County (0.587) > Yiwu County (0.563) > Gaochang District (0.494) > Shanshan County (0.437) > Tuokexun County (0.417) > Yizhou District (0.342), with an annual growth rate of 4.6%; (3) Regional disparities were dominated by intra-regional differences (42.0%), followed by transvariation density (30.64%). This study provides scientific evidence for optimizing resource allocation in arid regions. Full article

(This article belongs to the Section Agricultural Water Management)

23 pages, 6057 KiB

Open AccessArticle

MAMNet: Lightweight Multi-Attention Collaborative Network for Fine-Grained Cropland Extraction from Gaofen-2 Remote Sensing Imagery

by Jiayong Wu, Xue Ding, Jinliang Wang and Jiya Pan

Agriculture 2025, 15(11), 1152; https://doi.org/10.3390/agriculture15111152 - 27 May 2025

Abstract

To address the issues of high computational complexity and boundary feature loss encountered when extracting farmland information from high-resolution remote sensing images, this study proposes an innovative CNN–Transformer hybrid network, MAMNet. This framework integrates a lightweight encoder, a global–local Transformer decoder, and a [...] Read more.

To address the issues of high computational complexity and boundary feature loss encountered when extracting farmland information from high-resolution remote sensing images, this study proposes an innovative CNN–Transformer hybrid network, MAMNet. This framework integrates a lightweight encoder, a global–local Transformer decoder, and a bidirectional attention architecture to achieve efficient and accurate farmland information extraction. First, we reconstruct the ResNet-18 backbone network using deep separable convolutions, reducing computational complexity while preserving feature representation capabilities. Second, the global–local Transformer block (GLTB) decoder uses multi-head self-attention mechanisms to dynamically fuse multi-scale features across layers, effectively restoring the topological structure of fragmented farmland boundaries. Third, we propose a novel bidirectional attention architecture: the Detail Improvement Module (DIM) uses channel attention to transfer semantic features to geometric features. The Context Enhancement Module (CEM) utilizes spatial attention to achieve dynamic geometric–semantic fusion, quantitatively distinguishing farmland textures from mixed ground cover. The positional attention mechanism (PAM) enhances the continuity of linear features by strengthening spatial correlations in jump connections. By cascading front-end feature module (FEM) to expand the receptive field and combining an adaptive feature reconstruction head (FRH), this method improves information integrity in fragmented areas. Evaluation results on the 2022 high-resolution two-channel image dataset from Chenggong District, Kunming City, demonstrate that MAMNet achieves an mIoU of 86.68% (an improvement of 1.66% and 2.44% over UNetFormer and BANet, respectively) and an F1-Score of 92.86% with only 12 million parameters. This method provides new technical insights for plot-level farmland monitoring in precision agriculture. Full article

(This article belongs to the Section Digital Agriculture)

40 pages, 1159 KiB

Open AccessArticle

The Role of Agricultural Socialized Services in Mitigating Rural Labor Shortages: A Multi-Crop Analysis of Production Performance

by Zhixiong Liu, Yuheng Wei, Ruofan Liao and Jianxu Liu

Agriculture 2025, 15(11), 1151; https://doi.org/10.3390/agriculture15111151 - 27 May 2025

Abstract

China’s agricultural sector faces unprecedented challenges due to rapid urbanization. The rural labor force is declining, and the agricultural workforce is aging significantly. This labor shortage, worsened by the exodus of agricultural technicians, threatens food security and agricultural sustainability. This study analyzes data [...] Read more.

China’s agricultural sector faces unprecedented challenges due to rapid urbanization. The rural labor force is declining, and the agricultural workforce is aging significantly. This labor shortage, worsened by the exodus of agricultural technicians, threatens food security and agricultural sustainability. This study analyzes data from 30 Chinese provinces from 2011 to 2022 using a transcendental logarithmic production function. The research examines how agricultural socialized services can alleviate rural labor shortages by improving production efficiency. It also investigates these services’ impact on labor input intensity and grain yield across different crops and regions. The results show that socialized agricultural services effectively promote food production. At the national level, these services can promote a 54.4% increase in total crop production. Agricultural socialized services are gradually developing toward labor substitution. The significant negative interaction coefficient between services and labor confirms this substitution effect. The input–output elasticity of these services is positive for total crop and cereal crop production in major production areas. It also shows positive elasticity for total crop and tuber crop production in non-major production areas. The national-level “service-labor” technical elasticity of substitution maintains values above zero, averaging 0.37 across regions, offering an effective solution to agricultural labor shortages. This study identifies a threshold effect where these services’ impact on food production significantly increases with business scale expansion. These findings highlight the importance of optimizing agricultural socialized services through strengthened service systems, differentiated regional strategies, technological innovation, and comprehensive support policies. Such targeted approaches would enhance substitution effects and service efficiency, addressing labor shortages and boosting food production. Full article

(This article belongs to the Topic Efficient and Sustainable Agricultural Resource Use: Advances in Research Methods and Applications)

22 pages, 7231 KiB

Open AccessArticle

Tea Plant/Ophiopogon japonicus Intercropping Drives the Reshaping of Soil Microbial Communities in Terraced Tea Plantation’s Micro-Topographical Units

by Yangxin Li, Le Sun, Jialin Zhang, Hongxue Zhao, Tejia Su, Wenhui Li, Linkun Wu, Pumo Cai, Christopher Rensing, Yuanping Li, Jianming Zhang, Feiquan Wang and Qisong Li

Agriculture 2025, 15(11), 1150; https://doi.org/10.3390/agriculture15111150 - 27 May 2025

Abstract

The monoculture planting in terraced tea plantations has led to severe soil degradation, which poses a significant threat to the growth of tea plants. However, the mechanisms by which intercropping systems improve soil health through the regulation of soil microbial communities at the [...] Read more.

The monoculture planting in terraced tea plantations has led to severe soil degradation, which poses a significant threat to the growth of tea plants. However, the mechanisms by which intercropping systems improve soil health through the regulation of soil microbial communities at the micro-topographical scale of terraced tea plantations (i.e., terrace surface, inter-row, and terrace wall) remain unclear. This study investigates the effects of intercropping Ophiopogon japonicus in a five-year tea plantation on the soil physicochemical properties, enzyme activities, and microbial community structure and functions across different micro-topographical features of terraced tea plantations in Wuyi Mountain. The results indicate that intercropping significantly improved the soil organic matter, available nutrients, and redox enzyme activities in the inter-row, terrace surface, and terrace wall, with the effects gradually decreasing with increasing distance from the tea plant rhizosphere. In the intercropping group, tea leaf yield increased by 13.17% (fresh weight) and 19.29% (dry weight) compared to monoculture, and the disease indices of new and old leaves decreased by 40.63% and 38.7%, respectively. Intercropping strengthened the modularity of bacterial networks and the role of stochasticity in shaping bacterial communities in different micro-topographic environments, in contrast to the patterns observed in fungal communities. The importance of microbial phyla such as Proteobacteria and Ascomycota in different micro-topographical features was significantly regulated by intercropping. In different micro-topographical zones of the terraced tea plantation, beneficial bacterial genera such as Sinomonas, Arthrobacter, and Ferruginibacter were significantly enriched, whereas potential fungal pathogens like Nigrospora, Microdochium, and Periconia were markedly suppressed. Functional annotations revealed that nitrogen cycling functions were particularly enhanced in inter-row soils, while carbon cycling functions were more prominent on the terrace surface and wall. This study sheds light on the synergistic regulatory mechanisms between micro-topographical heterogeneity and intercropping systems, offering theoretical support for mitigating soil degradation and optimizing management strategies in terraced tea agroecosystems. Full article

(This article belongs to the Section Agricultural Soils)

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18 pages, 3965 KiB

Open AccessArticle

Health Assessment of Natural Selenium-Rich Soil in Yuanzhou District Based on Selenium–Cadmium Principal Factors and the Accumulation of Selenium and Cadmium in the Area Crops

by Ning He, Yuting Su, Fang Huang, De Yu, Chengyun Han, Xingjie Li, Zhigang Zhao and Xian Sun

Agriculture 2025, 15(11), 1149; https://doi.org/10.3390/agriculture15111149 - 27 May 2025

Abstract

Selenium (Se) is essential for human health, but it interacts with cadmium (Cd). However, there has been little focus on developing soil health evaluation models based on the interaction between Se and heavy metals, or the transport of Se and Cd in oilseed [...] Read more.

Selenium (Se) is essential for human health, but it interacts with cadmium (Cd). However, there has been little focus on developing soil health evaluation models based on the interaction between Se and heavy metals, or the transport of Se and Cd in oilseed rape. Through detection, it was found that the soil in Yuanzhou District is mostly Se-rich (average 0.62 mg kg⁻¹). Correlation analysis of the soil showed a positive correlation between Se content with Cd (r = 0.62, p < 0.01) and organic matter (r = 0.60, p < 0.01). A soil health score model was developed and performed well, indicating that the model can be used to estimate relevant soil health scores. Furthermore, the natural Se content of rice ranges from 0.07 to 0.28 mg kg⁻¹, and the overall enrichment ability of Se and Cd in oilseed rape is stronger than it is in rice. According to the correlation analysis, the Cd content in the soil was significantly correlated with the stems of oilseed rape (r = 0.49, p < 0.01) and rice (r = 0.37, p < 0.05). As a result, this study suggests using the rice/oilseed rape intercropping model of farming to transfer Cd into oilseed rape to reduce the Cd content in rice. Full article

(This article belongs to the Section Agricultural Soils)

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27 pages, 2400 KiB

Open AccessArticle

Advanced 3D Depth Imaging Techniques for Morphometric Analysis of Detected On-Tree Apples Based on AI Technology

by Eungchan Kim, Sang-Yeon Kim, Chang-Hyup Lee, Sungjay Kim, Jiwon Ryu, Geon-Hee Kim, Seul-Ki Lee and Ghiseok Kim

Agriculture 2025, 15(11), 1148; https://doi.org/10.3390/agriculture15111148 - 27 May 2025

Abstract

This study developed non-destructive technology for predicting apple size to determine optimal harvest timing of field-grown apples. RGBD images were collected in field environments with fluctuating light conditions, and deep learning techniques were integrated to analyze morphometric parameters. After training various models, the [...] Read more.

This study developed non-destructive technology for predicting apple size to determine optimal harvest timing of field-grown apples. RGBD images were collected in field environments with fluctuating light conditions, and deep learning techniques were integrated to analyze morphometric parameters. After training various models, the EfficientDet D4 and Mask R-CNN ResNet101 models demonstrated the highest detection accuracy. Morphometric metrics were measured by linking boundary box information with 3D depth information to determine horizontal and vertical diameters. Without occlusion, mean absolute percentage error (MAPE) using boundary box-based methods was 6.201% and 5.164% for horizontal and vertical diameters, respectively, while mask-based methods achieved improved accuracy with MAPE of 5.667% and 4.921%. Volume and weight predictions showed MAPE of 7.183% and 6.571%, respectively. For partially occluded apples, amodal segmentation was applied to analyze morphometric parameters according to occlusion rates. While conventional models showed increasing MAPE with higher occlusion rates, the amodal segmentation-based model maintained consistent accuracy regardless of occlusion rate, demonstrating potential for automated harvest systems where fruits are frequently partially obscured by leaves and branches. Full article

(This article belongs to the Special Issue Smart Agriculture Sensors and Monitoring Systems for Field Detection)

19 pages, 3131 KiB

Open AccessArticle

Design and Experiment of Opposed Roller-Type Picking Device for Chrysanthemum Indicum

by Yiduo Bai, Zhuanghong Ma, Suyuan Liu, Zhengdao Liu, Xiaoli Yan and Yuxiang Huang

Agriculture 2025, 15(11), 1147; https://doi.org/10.3390/agriculture15111147 - 27 May 2025

Abstract

Wild chrysanthemum stems are cluttered and their flowers are dense, which makes them difficult to pick. In order to solve this problem, in this study, we designed a kind of opposed roller picking device. It was designed based on an analysis of the [...] Read more.

Wild chrysanthemum stems are cluttered and their flowers are dense, which makes them difficult to pick. In order to solve this problem, in this study, we designed a kind of opposed roller picking device. It was designed based on an analysis of the mechanical characteristics involved in the picking of wild chrysanthemum. The design focused on an opposed drum picking mechanism. Taking the critical post-collision acceleration as the evaluation metric, a theoretical analysis was conducted on the post-collision motion behaviors of wild chrysanthemum and the roller bow tooth. This study found that the primary factors affecting the picking process are the roller rotational speed, the feeding speed, and the impact angle. Furthermore, simulation experiments confirmed that when the roller rotational speed was 3.73 rad/s and the clamping chain moved at 1.3 m/s, the wild chrysanthemum picking platform achieved a picking efficiency of 87.72%, thereby meeting the corresponding requirements for wild chrysanthemum harvesting. Through bench tests, it was found that, when the roller gap was 100 mm, the roller bow tooth bending angle was 56°, and the feeding rate was 2.1 kg/s, the clean picking rate reached 95.9%, thereby meeting the requirements for wild chrysanthemum harvesting. The development of an opposite roller-type wild chrysanthemum-picking device can provide technical support for the development of wild chrysanthemum picking equipment. Full article

(This article belongs to the Section Agricultural Technology)

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