Agriculture

31 pages, 3120 KB

Open AccessReview

From Contamination to Mitigation: Addressing Cadmium Pollution in Agricultural Soils

by Felicia Chețan, Paula Ioana Moraru, Teodor Rusu, Alina Șimon, Lucian Dinca and Gabriel Murariu

Agriculture 2025, 15(20), 2179; https://doi.org/10.3390/agriculture15202179 - 21 Oct 2025

Viewed by 394

Abstract

Cadmium (Cd) contamination in agricultural soils originates mainly from atmospheric deposition, irrigation water, fertilizers, pesticides, and industrial waste discharges. This human-induced pollution adversely affects soil fertility and structure, disrupts plant growth and physiological activities, and poses severe health risks through food-chain accumulation. Despite [...] Read more.

Cadmium (Cd) contamination in agricultural soils originates mainly from atmospheric deposition, irrigation water, fertilizers, pesticides, and industrial waste discharges. This human-induced pollution adversely affects soil fertility and structure, disrupts plant growth and physiological activities, and poses severe health risks through food-chain accumulation. Despite increasing research attention, comprehensive assessments that integrate global patterns, remediation strategies, and knowledge gaps remain limited. Therefore, this literature review critically synthesizes findings from 1060 peer-reviewed studies (screened using PRISMA guidelines) retrieved from Scopus and Web of Science databases, focusing on Cd sources, environmental behavior, plant responses, and soil remediation techniques. Results show that most research has been concentrated in Asia—particularly China—and Latin America. The most frequently investigated topics include Cd accumulation in crops, soil amendments, phytoremediation, and microbial-assisted remediation. Among remediation strategies, assisted phytoremediation and integrated biological–chemical approaches (biochar, PGPR, and soil amendments) emerged as the most promising for sustainable Cd mitigation. In conclusion, this review highlights regional disparities in research coverage, emphasizes the effectiveness of combined remediation approaches, and identifies the need for interdisciplinary and field-scale studies to advance sustainable solutions for Cd pollution control in agricultural systems. Full article

(This article belongs to the Special Issue Heavy Metal Pollution and Remediation in Agricultural Soils)

► Show Figures

Figure 1

21 pages, 3274 KB

Open AccessArticle

Enhanced SWAP Model for Simulating Evapotranspiration and Cotton Growth Under Mulched Drip Irrigation in the Manas River Basin

by Shuo Zhang, Tian Gao, Rui Sun, Muhammad Arsalan Farid, Chunxia Wang, Ping Gong, Yongli Gao, Xinlin He, Fadong Li, Yi Li, Lianqing Xue and Guang Yang

Agriculture 2025, 15(20), 2178; https://doi.org/10.3390/agriculture15202178 - 21 Oct 2025

Viewed by 259

Abstract

Model-based simulation of farmland evapotranspiration and crop growth facilitates precise monitoring of crop and farmland dynamics with high efficiency, real-time responsiveness, and continuity. However, there are still significant limitations in using crop models to simulate the dynamic process of evapotranspiration and cotton growth [...] Read more.

Model-based simulation of farmland evapotranspiration and crop growth facilitates precise monitoring of crop and farmland dynamics with high efficiency, real-time responsiveness, and continuity. However, there are still significant limitations in using crop models to simulate the dynamic process of evapotranspiration and cotton growth in mulched drip-irrigated cotton fields under different irrigation gradients. The SWAP crop growth model effectively simulates crop growth. However, the original SWAP model lacks a dedicated module to consider the impact of mulching on cotton field evapotranspiration and cotton dry matter mass. Therefore, in this study, the source codes of the soil moisture, evapotranspiration, and crop growth modules of the SWAP model were improved. The evapotranspiration and cotton growth data of the mulched drip-irrigated cotton fields under three irrigation treatments (W1 = 3360 m³·hm⁻², W2 = 4200 m³·hm⁻², and W3 = 5040 m³·hm⁻²) in 2023 and 2024 at the Xinjiang Modern Water-saving Irrigation Key Experimental Station of the Corps were used to verify the simulation accuracy of the improved SWAP model. Research shows the following: (1) The average relative errors of the simulated evapotranspiration, leaf area index, and dry matter weight of cotton in the improved SWAP crop growth model are all <20% compared with the measured values. The root means square errors of the three treatments (W1, W2, and W3) ranged from 0.85 to 1.38 mm, from 0.03 to 0.18 kg·hm⁻², and 55.01 to 69 kg·hm⁻², respectively. The accuracy of the improved model in simulating evapotranspiration and cotton growth in the mulched cotton field increased by 37.49% and 68.25%, respectively. (2) The evapotranspiration rate of cotton fields is positively correlated with the irrigation water volume and is most influenced by meteorological factors such as temperature and solar radiation. During the flowering stage, evapotranspiration accounted for 62.83%, 62.09%, 61.21%, 26.46%, 40.01%, and 38.8% of the total evapotranspiration. Therefore, the improved SWAP model can effectively simulate the evaporation and transpiration of the mulched drip-irrigated cotton fields in the Manas River Basin. This study provides a scientific basis for the digital simulation of mulched farmland in the arid regions of Northwest China. Full article

(This article belongs to the Special Issue Modeling as a Tool to Explore Sustainable Irrigation Practices in Agriculture)

► Show Figures

Figure 1

28 pages, 1846 KB

Open AccessArticle

Evaluation of the Coupled Coordination of the Water–Energy–Food System Based on Resource Flow: A Case of Hubei, China

by Yuetong Han, Xiangyang Xu, Jiayi Lu, Xiaoxiao Tan and Ying Long

Agriculture 2025, 15(20), 2177; https://doi.org/10.3390/agriculture15202177 - 21 Oct 2025

Viewed by 347

Abstract

External environmental changes, such as climate, industrial expansion, and population growth, threaten the sustainable development of the water–energy–food (WEF) system. Clarifying the intricate nonlinear relationships within this system and revealing the degree of coupling coordination and evolutionary trends within the WEF system can [...] Read more.

External environmental changes, such as climate, industrial expansion, and population growth, threaten the sustainable development of the water–energy–food (WEF) system. Clarifying the intricate nonlinear relationships within this system and revealing the degree of coupling coordination and evolutionary trends within the WEF system can provide feasible pathways for regional sustainable development. Taking Hubei Province as the study area, this research quantified resource flows between dual systems from a resource consumption perspective. It then analyzed the temporal evolution characteristics of resource interactions within the WEF system from 2003 to 2023. In addition, this WEF system was evaluated by an evaluation index system according to the resource utilization level of the single system and the resource flow level of the dual system, and the CRITIC method was employed to assess the coordinated development of the WEF system in Hubei Province from 2003 to 2023. Finally, the coupling coordination degree for 2025 to 2040 was predicted through the grey GM (1,1) model. The results show that the comprehensive development evaluation index exhibited a trend of initial decline followed by an increase from 2003 to 2023. Among these, the water resources system demonstrated the relatively optimal comprehensive development status, while the energy system performed the worst. The WEF system remained in a high-level coupling stage, with its degree of coupling coordination showing a pattern of initial decline followed by an increase, reaching its peak in 2023 and entering a moderately coordinated stage. Within the dual-coupling systems, the water–food (WF) system achieved the highest level of coordinated development, reaching the good coordination stage. The GM (1,1) model indicates that Hubei Province’s WEF system can gradually achieve a good coordinated stage between 2024 and 2040. Full article

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

► Show Figures

Figure 1

14 pages, 274 KB

Open AccessArticle

China’s Invisible Chicken Losses: Production Costs Effect of Highly Pathogenic Avian Influenza

by Lintong Zhao, Zeying Huang and Wenjun Long

Agriculture 2025, 15(20), 2176; https://doi.org/10.3390/agriculture15202176 - 21 Oct 2025

Viewed by 300

Abstract

Highly pathogenic avian influenza (HPAI) affects chicken production not only during outbreaks but also afterward. Understanding its delayed effect is essential for facilitating timely production recovery. Employing a dynamic panel data model with annual Chinese provincial data obtained between 2004 and 2021, we [...] Read more.

Highly pathogenic avian influenza (HPAI) affects chicken production not only during outbreaks but also afterward. Understanding its delayed effect is essential for facilitating timely production recovery. Employing a dynamic panel data model with annual Chinese provincial data obtained between 2004 and 2021, we quantified the impact of previous-year HPAI outbreaks on current-year chicken production through production costs. The results indicated that a 1% increase in provincial HPAI outbreaks raised production costs per 100 broilers by 0.372%, ultimately reducing annual chicken production by 0.038%. These findings remained robust after controlling for endogeneity and conducting extensive robustness checks. The impact was most pronounced in provinces characterized by high chicken production, a high proportion of scale broilers, and yellow-feathered broiler specialization, where both production costs and production losses were significantly greater. Additionally, previous-year HPAI outbreaks significantly increased production costs by increasing both epidemic prevention and broiler chick costs. Our findings offer robust empirical evidence and actionable insights for managing cost volatility risks along the chicken supply chain in post-epidemic contexts. Full article

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

20 pages, 400 KB

Open AccessArticle

Does Off-Farm Employment Affect Grain Production? Evidence from Wheat-Growing Households in China

by Mohan Wu, Wenli Zhang, Hailong Cai and Nan Jiang

Agriculture 2025, 15(20), 2175; https://doi.org/10.3390/agriculture15202175 - 21 Oct 2025

Viewed by 334

Abstract

Against the backdrop of expanding off-farm employment, it is of great practical significance to examine how off-farm employment affects grain production and its underlying mechanisms, in order to build a more stable and sustainable national food security system. Drawing on micro-level data from [...] Read more.

Against the backdrop of expanding off-farm employment, it is of great practical significance to examine how off-farm employment affects grain production and its underlying mechanisms, in order to build a more stable and sustainable national food security system. Drawing on micro-level data from wheat-producing households in the national Rural Fixed Observation Points survey from 2004 to 2021, this study systematically investigates the impact of off-farm employment on wheat planting decisions and the channels through which it operates. The findings reveal the following: (1) Off-farm employment encourages farmers to adjust their factor input structure and crop choices, leading to an increased proportion of wheat sown area. (2) Agricultural socialized services, especially mechanized operations, enhance the feasibility of factor substitution and effectively channel off-farm income into agricultural investment. Furthermore, the number of service providers at the village level plays a significant moderating role in this process; the more adequate the service supply, the stronger the positive effect of off-farm employment on wheat cultivation. (3) The influence of off-farm employment on wheat production is more pronounced in plain regions with favorable topographic conditions and among large-scale farming households. Based on these findings, the study recommends improving the agricultural service system, promoting better coordination between off-farm employment and agricultural development, and fostering a more stable and sustainable support system for grain production. Full article

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

► Show Figures

Figure 1

17 pages, 3480 KB

Open AccessArticle

Responses of Yield, Efficiency, and Phenotypes of Spring Wheat in Arid Regions to Water Regulation

by Na Li, Pinyuan Zhao, Jiaxin Zhu and Sien Li

Agriculture 2025, 15(20), 2174; https://doi.org/10.3390/agriculture15202174 - 21 Oct 2025

Viewed by 233

Abstract

To clarify the optimal water regulation strategy for spring wheat in arid areas, this study set up three irrigation methods [film-mulched drip irrigation (FD), non-mulched drip irrigation (ND), non-mulched subsurface drip irrigation (MD)] and five water treatments [CK: 80% field capacity; W1–W4: irrigation [...] Read more.

To clarify the optimal water regulation strategy for spring wheat in arid areas, this study set up three irrigation methods [film-mulched drip irrigation (FD), non-mulched drip irrigation (ND), non-mulched subsurface drip irrigation (MD)] and five water treatments [CK: 80% field capacity; W1–W4: irrigation amounts were 90%, 80%, 70%, and 60% of CK, respectively] in the Shiyang River Basin during 2023–2024. The effects of these treatments on the phenotype, yield, and water use efficiency (WUE) of spring wheat were investigated. The results showed that under the same water treatment, the leaf area index (LAI), SPAD value, and stem diameter (SD) significantly decreased with the reduction in irrigation amount (p < 0.05), while plant height (HC) was less affected. FD performed optimally under the W1 treatment: its yield reached 11,868.93 kg·ha⁻¹, which was 54.88% and 38.72% higher than that of ND and MD, respectively; and its WUE reached 4.36 kg/m³, which was 123.19% and 100.83% higher than that of ND and MD, respectively. ND performed better under the CK treatment: its yield was 10,044.33 kg·ha⁻¹, which was 27.07% and 12.25% higher than that of FD and MD, respectively. Annual precipitation had a significant impact: when precipitation was 175 mm in 2023, ND showed an obvious advantage; when precipitation decreased to 110 mm in 2024, FD exhibited stronger stress resistance. The study concludes that FD is suitable for moderate to severe water stress, while ND is suitable for sufficient water conditions or mild stress. This can provide a basis for water-saving and the high-yield production of spring wheat in arid areas. Full article

(This article belongs to the Section Agricultural Water Management)

► Show Figures

Figure 1

17 pages, 3823 KB

Open AccessArticle

Installation and Advanced Method for the Evaluation of Air Velocity over the Sieves of the Cleaning Unit of Combine Harvesters

by Ionuț-Alexandru Dumbravă, Petru-Marian Cârlescu, Radu Roșca and Ioan Ţenu

Agriculture 2025, 15(20), 2173; https://doi.org/10.3390/agriculture15202173 - 20 Oct 2025

Viewed by 782

Abstract

The paper describes an installation and procedure for evaluating the velocity profile for the airflow produced by the fan of the cleaning unit of a New Holland wheat combine harvester. The velocity profile is based on measurements taken at 52 points spread over [...] Read more.

The paper describes an installation and procedure for evaluating the velocity profile for the airflow produced by the fan of the cleaning unit of a New Holland wheat combine harvester. The velocity profile is based on measurements taken at 52 points spread over the entire surface of the top and bottom sieves, for different speeds of the fan, different positions of the wind boards and different opening positions of the sieves. The experimental data obtained were graphically represented using the Radial Basis Function (RBF) interpolation model and highlighted that the airflow generated by the fan at the upper screen level, in the longitudinal plane and, especially, in the transverse plane, is distributed unevenly, and depends on the fan rotor speed, the opening of the louvers of the two screens and the arrangement of the two deflectors. The correct adjustment of the cleaning unit and correct evaluation of the air velocity profile over the sieves result in the reduction in grain losses from the upper sieve due to grain flotation, reduction in the content of broken grains in the grain tank due to the reduction in the material flow from the tailing auger as well as reduction in the impurities content of the grain tank due to better separation of the material over the surface of the lower sieve. Full article

(This article belongs to the Section Agricultural Technology)

► Show Figures

Figure 1

21 pages, 2305 KB

Open AccessArticle

A Novel Approach to Address Lead Exceedance Issue in the Geographical Indication Product Laifeng Ginger (Zingiber officinale cv. Fengtoujiang): Co-Application of Organic Fertilizer and Compound Fertilizer

by Mengdie Song, Hao Huai, Jiawei Wan, Tingyang Ai, Hongzao He, Hong Liu, Rui Qin and Jiao Liu

Agriculture 2025, 15(20), 2172; https://doi.org/10.3390/agriculture15202172 - 20 Oct 2025

Viewed by 359

Abstract

Laifeng ginger (Zingiber officinale cv. Fengtoujiang) is a famous Geographical Indication (GI) ginger variety, which grows specifically in Laifeng County, Hubei, China. In recent years, it faced a serious food safety issue of lead (Pb) exceedance in the rhizomes even though [...] Read more.

Laifeng ginger (Zingiber officinale cv. Fengtoujiang) is a famous Geographical Indication (GI) ginger variety, which grows specifically in Laifeng County, Hubei, China. In recent years, it faced a serious food safety issue of lead (Pb) exceedance in the rhizomes even though the Pb content in the soil remains at a safe level. This problem severely hinders the local ginger’s market growth. In the present study, a field study across 37 Laifeng ginger farms revealed a connection between the occurrence of Pb exceedance and the choices of fertilizers. Cultivation experiments demonstrated that with more organic fertilizer (OF) applied, the Pb of rhizome effectively declined, and the branching and longitudinal growth were enhanced. The OF application facilitated Pb translocation from rhizomes to stems and leaves. Furthermore, we showed that OF improved the soil properties by altering the pH and the composition of soil microbial communities at the genus level, which was likely to be associated with reduced the Pb content in the ginger rhizomes. This research tackles the critical industry issue of Pb exceedance in Laifeng ginger, providing a basis for the fertilization of root and tuber plants with excessive heavy metal levels, and establishes a foundation for sustainable GI product development. Full article

(This article belongs to the Section Agricultural Soils)

► Show Figures

Figure 1

19 pages, 4661 KB

Open AccessArticle

The Influence of Various Guar Meal Types on Growth Performance, Carcass Composition and Histology of the Liver of Broiler Chickens

by Anna Milczarek, Magdalena Pachnik, Maria Osek and Renata Świnarska

Agriculture 2025, 15(20), 2171; https://doi.org/10.3390/agriculture15202171 - 20 Oct 2025

Viewed by 360

Abstract

This study evaluated how various types of guar meal in diets of broiler chickens affect their rearing results, carcass composition, and liver histology. The experiment was conducted in one hundred sixty Ross 308 broilers randomly allocated to four groups consisting of the same [...] Read more.

This study evaluated how various types of guar meal in diets of broiler chickens affect their rearing results, carcass composition, and liver histology. The experiment was conducted in one hundred sixty Ross 308 broilers randomly allocated to four groups consisting of the same number of birds (C, GM1, GM2, and GM3). The birds were reared for over 42 days and fed with starter (days 1–21), grower (days 22–35), and finisher (days 36–42) rations. All feed rations were prepared using maize meal, soybean meal, oil, mineral, and feed additives. The experimental factor was guar meal type included in feed rations (starter, grower, and finisher stage) at 6% each: C (control group)—without guar meal, GM1—raw guar meal, GM2—Microlam, and GM3—roasted guar meal. Microlam is a high-protein animal feed produced by laminating and micronizing guar meal for enhanced digestibility and protein content, while roasted guar meal (also called korma) is a more basic protein supplement for livestock and poultry that has undergone roasting to improve its taste and digestibility. It was shown that 6% of raw guar meal in the feed rations affected significantly higher (2646 g) body weight of broilers in comparison to birds fed the same amount of Microlam (2583 g), however feed conversion ratio were similar (1.63–1.65 kg/kg; p > 0.05) in all groups. Thus similar musculature and fatness, broiler chickens from GM1 and GM2 groups obtained higher dressing percentage in compare to group GM3 (p ≤ 0.05). No significant effect of guar meal on the physical characteristics (except pH₁), or the results of the proximate composition of the breast muscles was found. Rations fed to broiler chickens had no effect on the microscopic image of the liver or reaction to the presence of neutral fats. In summary, 6% inclusion of raw guar meal should be recommended in broiler chicken diets as a partial substitute for soybean meal because it contributes to achieving the best growth performance results as well as dressing percentage, without deterioration carcass composition, and liver histology. Full article

(This article belongs to the Special Issue Effects of Dietary Interventions on Monogastric Animal Production)

► Show Figures

Figure 1

22 pages, 4351 KB

Open AccessArticle

A Deployment-Oriented Benchmarking of You Look Only Once (YOLO) Models for Orange Detection and Segmentation in Agricultural Robotics

by Caner Beldek, Emre Sariyildiz and Gursel Alici

Agriculture 2025, 15(20), 2170; https://doi.org/10.3390/agriculture15202170 - 20 Oct 2025

Viewed by 358

Abstract

The deployment of autonomous robots is critical for advancing sustainable agriculture, but their effectiveness hinges on visual perception systems that can reliably operate in natural, real-world environments. Selecting an appropriate vision model for these robots requires a practical evaluation that extends beyond standard [...] Read more.

The deployment of autonomous robots is critical for advancing sustainable agriculture, but their effectiveness hinges on visual perception systems that can reliably operate in natural, real-world environments. Selecting an appropriate vision model for these robots requires a practical evaluation that extends beyond standard accuracy metrics to include critical deployment factors such as computational efficiency, energy consumption, and robustness to environmental disturbances. To address this need, this study presents a deployment-oriented benchmark of state-of-the-art You Look Only Once (YOLO)-based models for orange detection and segmentation. Following a systematic process, the selected models were evaluated on a unified public dataset, annotated to rigorously assess real-world challenges. Performance was compared across five key dimensions: (i) identification accurac, (ii) robustness, (iii) model complexity, (iv) execution time, and (v) energy consump-tion. The results show that the YOLOv5 variants achieved the most accurate detection and segmentation. Notably, YOLO11-based models demonstrated strong and consistent results under all disturbance levels, highlighting their robustness. Lightweight architectures proved well-suited for resource-constrained operations. Interestingly, custom models did not consistently outperform their baselines, while nanoscale models showed demonstra-ble potential for meeting real-time and energy-efficient requirements. These findings offer valuable, evidence-based guidelines for the vision systems of precision agriculture robots. Full article

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

► Show Figures

Figure 1

23 pages, 3661 KB

Open AccessArticle

The Establishment of a Geofencing Model for Automated Data Collection in Soybean Trial Plots

by Jiaxin Liang, Bo Zhang, Changhai Chen, Haoyu Cui, Yongcai Ma and Bin Chen

Agriculture 2025, 15(20), 2169; https://doi.org/10.3390/agriculture15202169 - 19 Oct 2025

Viewed by 397

Abstract

Collecting crop growth data in field environments is crucial for breeding research. The team’s current autonomous soybean phenotyping system requires manual control to start and stop data collection. To address the aforementioned issues, this study innovatively proposes an elliptical calibration rotating geofencing technique. [...] Read more.

Collecting crop growth data in field environments is crucial for breeding research. The team’s current autonomous soybean phenotyping system requires manual control to start and stop data collection. To address the aforementioned issues, this study innovatively proposes an elliptical calibration rotating geofencing technique. Preprocess coordinates using Z-scores and mean fitting perform global error calibration via weighted least squares, calculate the inclination angle between the row direction and the relative standard direction by fitting a straight line to the same row of data, and establish a rotation model based on geometric feature alignment. Results show that the system achieves an average response time of 0.115 s for geofence entry, with perfect accuracy and Recall rates of 1, meeting the requirements for starting and stopping geographic fencing in soybean ridge trial plots. This technology provides the critical theoretical foundation for enabling a dynamic, on-demand automatic start–stop functionality in smart data collection devices for soybean field trial zones within precision agriculture. Full article

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

► Show Figures

Figure 1

20 pages, 310 KB

Open AccessArticle

New Sweet Potato Genotypes: Analysis of Agronomic Potential

by Fishua J. U. Dango, Darllan J. L. S. F. Oliveira, Maria E. F. Otoboni, Bruno E. Pavan, Maria I. V. Andrade and Pablo F. Vargas

Agriculture 2025, 15(20), 2168; https://doi.org/10.3390/agriculture15202168 - 19 Oct 2025

Viewed by 342

Abstract

The quantification of genotype x environment interaction is essential for recommending high-yielding genotypes for both favorable and unfavorable environments, thereby increasing production. This study aimed to evaluate the agronomic performance of sweet potato genotypes in the central–east and central–south regions of São Paulo. [...] Read more.

The quantification of genotype x environment interaction is essential for recommending high-yielding genotypes for both favorable and unfavorable environments, thereby increasing production. This study aimed to evaluate the agronomic performance of sweet potato genotypes in the central–east and central–south regions of São Paulo. The experiments were conducted using a randomized block design with 9 plants per plot and 3 replications, consisting of 18 sweet potato genotypes and 3 commercial cultivars, totaling 21 treatments. The characteristics, such as commercial productivity, dry matter, chroma, hue, insect resistance, eyes, and lenticels showed genotype x environment interaction for 77.78% of the variables. The maximum productivity of the genotypes ranged from 31.81 t/ha⁻¹ to 63.60 t/ha⁻¹. Heritability was observed in 88.89% of the analyzed traits, with values ranging from 75.36% to 93.47%, indicating a significant genetic influence on the evaluated characteristics. Location 4 (first cycle in Botucatu, 20 December 2021) was superior and considered the most suitable for sweet potato cultivation. The genotypes CERAT60-05, CERAT56-23, CERAT60-26, and CERAT35-11 performed best, showing promise as new cultivars. Full article

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

32 pages, 2723 KB

Open AccessReview

Nondestructive Quality Detection of Characteristic Fruits Based on Vis/NIR Spectroscopy: Principles, Systems, and Applications

by Chen Wang, Xiaonan Li, Zijuan Zhang, Xuan Luo, Jianrong Cai and Aichen Wang

Agriculture 2025, 15(20), 2167; https://doi.org/10.3390/agriculture15202167 - 18 Oct 2025

Viewed by 648

Abstract

Nondestructive quality detection of characteristic fruits is essential for ensuring nutritional value, economic viability, and consumer safety in global supply chains, yet traditional destructive methods compromise sample integrity and scalability. Visible and near-infrared (Vis/NIR) spectroscopy offers a transformative solution by enabling rapid, non-invasive [...] Read more.

Nondestructive quality detection of characteristic fruits is essential for ensuring nutritional value, economic viability, and consumer safety in global supply chains, yet traditional destructive methods compromise sample integrity and scalability. Visible and near-infrared (Vis/NIR) spectroscopy offers a transformative solution by enabling rapid, non-invasive multi-attribute quantification through molecular overtone vibrations. This review examines recent advancements in Vis/NIR-based fruit quality detection, encompassing fundamental principles, system configurations, and detection strategies calibrated to fruit biophysical properties. Firstly, optical mechanisms and system architectures (portable, online, vehicle-mounted) are compared, emphasizing their compatibility with fruit structural complexity. Then, critical challenges arising from fruit-specific characteristics—such as rind thickness, pit interference, and spatial heterogeneity—are analyzed, highlighting their impact on spectral accuracy. Applications across diverse fruit categories (pitted, thin-rinded, and thick-rinded) are systematically reviewed, with case studies demonstrating the robust prediction of key quality indices. Subsequently, considerations in model development and validation are presented. Finally, persistent limitations in model transferability and environmental adaptability are discussed, proposing future research directions centered on integrating hyperspectral imaging, AI-driven calibration transfer, standardized spectral databases, and miniaturized, field-deployable sensors. Collectively, these methodological breakthroughs will pave the way for autonomous, next-generation quality assessment platforms, revolutionizing postharvest management for characteristic fruits. Full article

(This article belongs to the Special Issue Advances in High-Quality or Value-Added Processing of Fruits and Vegetables—Second Edition)

► Show Figures

Figure 1

18 pages, 14076 KB

Open AccessArticle

Transcriptomic Analysis Identifies GhSACPD-Mediated Fatty Acid Regulation in the Cotton Boll Abscission

by Guangling Shui, Zewei Chang, Peng Han, Qi Zhang, Zhibo Li, Hairong Lin, Xin Wang, Yuanlong Wu and Xinhui Nie

Agriculture 2025, 15(20), 2166; https://doi.org/10.3390/agriculture15202166 - 18 Oct 2025

Viewed by 329

Abstract

Boll abscission in cotton (Gossypium spp.) is a key factor that limits yield; however, the molecular mechanisms underlying this process remain poorly understood. In this study, boll abscission characteristics were uncovered in four cotton varieties that exhibited extreme differences in boll abscission [...] Read more.

Boll abscission in cotton (Gossypium spp.) is a key factor that limits yield; however, the molecular mechanisms underlying this process remain poorly understood. In this study, boll abscission characteristics were uncovered in four cotton varieties that exhibited extreme differences in boll abscission rates via tissue sectioning. Transcriptome analysis was performed on the four cotton varieties. Using weighted gene co-expression network analysis (WGCNA) of the transcriptome data, we identified a stearoyl-(acyl-carrier-protein) desaturase (SACPD) as a potential key regulator of boll abscission. We also performed evolutionary analyses on the SACPD gene family across five cotton species and identified 63 members that were classified into four evolutionary clades, with duplication-polyploidization events being a major driver of gene expansion. Tissue-specific expression profiling revealed that Gossypium hirsutum GhSACPD19 is highly expressed in the abscission zone. Our findings suggest a role of GhSACPD19 in regulating boll abscission, likely through metabolism of jasmonate, a well-known positive regulator of abscission. Our work offers new insights into the regulation of organ abscission at cellular and molecular levels and presents a valuable resource for cotton yield improvement. Full article

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

► Show Figures

Figure 1

26 pages, 28235 KB

Open AccessArticle

Cotton Picker Fire Risk Analysis and Dynamic Threshold Setting Using Multi-Point Sensing and Seed Cotton Moisture

by Zhai Shi, Dongdong Song, Changjie Han, Fangwei Wu and Yi Wu

Agriculture 2025, 15(20), 2165; https://doi.org/10.3390/agriculture15202165 - 18 Oct 2025

Viewed by 275

Abstract

Fire hazards during cotton picker operations pose a significant safety concern, primarily caused by cotton blockages and friction-induced heat generation between the picking spindle and seed cotton under high-load conditions. Existing fire monitoring systems typically employ a uniform temperature threshold across multiple sensors. [...] Read more.

Fire hazards during cotton picker operations pose a significant safety concern, primarily caused by cotton blockages and friction-induced heat generation between the picking spindle and seed cotton under high-load conditions. Existing fire monitoring systems typically employ a uniform temperature threshold across multiple sensors. However, this approach overlooks the distinct characteristics of different cotton picker mechanisms and the influence of seed cotton moisture content, resulting in frequent false alarms and missed detections. To address these issues, this study pioneers and tests a dynamic, tiered temperature threshold warning strategy. This approach accounts for key cotton picker components and varying seed cotton moisture content (MC), specifically MC 9–12% and MC 12–15%. Additionally, based on the operational characteristics of the cotton conveying tube, this study proposes monitoring the wall surface temperature of the conveying tube and investigates the threshold for this temperature. Results indicate that during seed cotton open burning, the average temperature is 324 °C for MC < 9%, 261.9 °C for MC 9–12%, and 178.4 °C for MC 12–15%. After transitioning to smoldering, the temperatures were 226.6 °C, 191.5 °C, and 163.5 °C, respectively, with 163.5 °C being the lowest threshold for seed cotton open burning in the cotton bin. For smoldering seed cotton, the temperature thresholds were 240 °C for MC < 9% and MC 9–12%, and 280 °C for MC 12–15%. The temperature threshold for the cotton conveyor pipe wall surface was 49 °C. The friction-induced heat generation temperature threshold at the picking head, determined through combined testing and simulation, is set at 289 °C for MC < 9%, 306 °C for MC 9–12%, and 319 °C for MC 12–15%. The aforementioned tiered early warning strategy, developed through multi-source experiments and simulations, can be directly configured into controllers. It enables dynamic threshold alarms based on harvester location, seed cotton moisture content, and temperature zones, providing quantitative support for cotton harvester fire monitoring and risk management. Full article

(This article belongs to the Section Agricultural Technology)

► Show Figures

Figure 1

22 pages, 9395 KB

Open AccessArticle

Alteration of Nitrogen Fertilizer Forms Optimizes Nitrogen Balance in Drip-Irrigated Winter Wheat Systems of Northern China by Reducing Gaseous Nitrogen Losses

by Ruixuan Hao, Junyi Mu, Xiaoting Xie, Qiqi Ha, Yuanyuan Wang, Wenbo Zhai, Peng Wu, Aixia Ren, Zhiqiang Gao, Ru Guo and Min Sun

Agriculture 2025, 15(20), 2164; https://doi.org/10.3390/agriculture15202164 - 18 Oct 2025

Viewed by 306

Abstract

Winter wheat covers approximately 2.21 × 10⁸ ha globally, making it the most widely cultivated cereal crop in the world. In recent years, integrated water and fertilizer management has significantly improved winter wheat yield and nitrogen use efficiency; however, quantitative assessments of [...] Read more.

Winter wheat covers approximately 2.21 × 10⁸ ha globally, making it the most widely cultivated cereal crop in the world. In recent years, integrated water and fertilizer management has significantly improved winter wheat yield and nitrogen use efficiency; however, quantitative assessments of nitrogen cycling under different fertilizer forms in such high-yield systems remain limited. From 2022 to 2024, a two-year field experiment was conducted in drip-irrigated winter wheat fields in northern China. Four nitrogen fertilizer forms were applied: nitrate nitrogen fertilizer (NON), ammonium nitrogen fertilizer (NHN), amide nitrogen fertilizer (CON), and urea ammonium nitrate fertilizer (UAN), along with an unfertilized control (CK). Compared with NON, NHN, and CON, UAN reduced cumulative N₂O emissions by 10.40–15.64% and NH₃ volatilization by 2.04–9.33% (p < 0.05). It also increased the leaf area index and biomass accumulation at maturity, as well as grain yield (3.70–10.28%), nitrogen harvest index (4.58–12.88%), and nitrogen use efficiency (12.14–39.25%) (p < 0.05). Furthermore, UAN significantly decreased the net nitrogen surplus (24.18–45.70%) and nitrogen balance values (25.64–55.82%) (p < 0.05). Correlation analysis indicated that the reduction in nitrogen balance was primarily attributed to lower N₂O emissions and improved nitrogen use efficiency (p < 0.05). In conclusion, the application of urea ammonium nitrate under integrated water–fertilizer management achieved higher yield, greater efficiency, and environmentally sustainable production in drip-irrigated winter wheat systems in northern China. Full article

(This article belongs to the Section Agricultural Water Management)

► Show Figures

Figure 1

19 pages, 5819 KB

Open AccessArticle

Research on Driving Forces of Spatiotemporal Patterns in Cotton Cultivation Considering Spatial Heterogeneity

by Meng Du, Deyu Shen, Xun Yang, Fenfang Lin, Chunfa Wu and Dongyan Zhang

Agriculture 2025, 15(20), 2163; https://doi.org/10.3390/agriculture15202163 - 18 Oct 2025

Viewed by 220

Abstract

Cotton is increasingly important in global development. The exploration of drivers of spatiotemporal patterns for cotton planting, considering spatial heterogeneity, is essential for optimizing its distribution and supporting sustainable production. This study combined the locally explained stratified heterogeneity (LESH) model with geographically weighted [...] Read more.

Cotton is increasingly important in global development. The exploration of drivers of spatiotemporal patterns for cotton planting, considering spatial heterogeneity, is essential for optimizing its distribution and supporting sustainable production. This study combined the locally explained stratified heterogeneity (LESH) model with geographically weighted regression (GWR) to investigate the factors shaping cotton-planting patterns in the northern slope of the Tianshan Mountains (NSTM), China, from 2000 to 2020. Cotton distribution was derived from long-term Landsat image series, and its expansion showed an average annual growth rate of 2.10 × 10³ km², with intensive cultivation primarily distributed across the central and western counties. The dominant drivers of cotton distribution were elevation (ELE), sunshine duration (SD), slope (SLO), temperature (TEM), runoff (RO), and gross domestic product (GDP). ELE explained about 40% of the spatial heterogeneity. SD showed a declining influence, SLO remained stable, TEM increased in importance, and GDP exhibited a progressive upward trend, although weaker. Moreover, nonlinear weakening interactions, especially between ELE and other factors, as well as between socio-economic and climatic variables, substantially enhanced explanatory power. These findings highlight the significance of accounting for spatial heterogeneity and factor interactions in guiding the spatial optimization and sustainable management of cotton cultivation. Full article

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

► Show Figures

Figure 1

26 pages, 3281 KB

Open AccessArticle

Canonical Analysis of the Impact of Climate Predictors on Sugarcane Yield in the Eastern Region of Pernambuco, Brazil

by Rodrigo Rogério da Silva, Geber Barbosa de Albuquerque Moura, Pabrício Marcos Oliveira Lopes, Cristina Rodrigues Nascimento and Pedro Rogério Giongo

Agriculture 2025, 15(20), 2162; https://doi.org/10.3390/agriculture15202162 - 18 Oct 2025

Viewed by 491

Abstract

Sugarcane yield plays a crucial role in food safety and biofuel production, and it is strongly influenced by climatic variations. In this context, this study applies canonical correlation analysis (CCA) to identify the climatic predictors, such as sea surface temperature, atmospheric pressure, and [...] Read more.

Sugarcane yield plays a crucial role in food safety and biofuel production, and it is strongly influenced by climatic variations. In this context, this study applies canonical correlation analysis (CCA) to identify the climatic predictors, such as sea surface temperature, atmospheric pressure, and wind speed, that affect sugarcane yield from 1990 to 2019. Hierarchical cluster analysis applied to the performance of 58 municipalities in the eastern region of Pernambuco identified three distinct and homogeneous groups. An analysis of the CCA for the three sugarcane yield groups and climatic variables revealed that the first canonical function was significant with R = 0.82 and precision of 0.67 (p ≤ 0.05 at 95% confidence level), and that the sugarcane yield groups and climatic variables were different (Wilks’ lambda = 0.14), but they were associated. Climatic variables affected the three sugarcane productivity groups, with redundancy indices of 29.7%, 52.2%, and 59.9%. Climatic variables with positive canonical weights enhance performance, while those with negative weights decrease yields. The structural canonical loads and cross-loadings reveal that sea surface temperature plays a crucial role in determining sugarcane yield, potentially influencing precipitation and temperature patterns in the region. The sensitivity analysis confirms the stability of the canonical loads and the robustness of the results, demonstrating that this research can support yield forecasting, regional agricultural policy, and drought management. Identifying climate predictors, such as sea surface temperature, wind speed, and atmospheric pressure, enables the creation of accurate models to predict sugarcane productivity, assisting farmers in planning input management, irrigation during dry periods, and harvesting. Furthermore, climate data can inform policies that encourage sustainable agricultural practices and adaptation to climate conditions, strengthening food security and guiding the selection of more resilient sugarcane varieties, increasing production resilience. Full article

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

► Show Figures

Figure 1

21 pages, 3317 KB

Open AccessArticle

Evolution and Reduction in Sulfonamide Resistance Genes in Aerobic Compost of Pig Manure

by Yihao Huang, Pengyan Wang, Shenao Liu, Shengguo Zhang, Zhuqing Ren and Jian Wu

Agriculture 2025, 15(20), 2161; https://doi.org/10.3390/agriculture15202161 - 17 Oct 2025

Viewed by 331

Abstract

This study identified that the absolute abundance of 15 types of antibiotic resistance genes (ARGs) across 21 organic fertilizer samples ranged between 1.15 × 10⁴ and 6.74 × 10¹⁰ copies/g, with sulfonamide ARGs and the intI1 gene exhibiting relatively higher residuals. [...] Read more.

This study identified that the absolute abundance of 15 types of antibiotic resistance genes (ARGs) across 21 organic fertilizer samples ranged between 1.15 × 10⁴ and 6.74 × 10¹⁰ copies/g, with sulfonamide ARGs and the intI1 gene exhibiting relatively higher residuals. Subsequent analyses delved into the evolutionary patterns and reduction mechanisms pertinent to sulfonamide ARGs throughout aerobic composting processes. Three bacteria, Bacillus amyloliquefaciens, Bacillus subtilis, and Bacillus velezensis, capable of significantly reducing sulfonamide-resistant bacteria and their sul1 gene were identified. The study revealed that adding composite microbial agent, lowering the pH, or increasing the temperature could inhibit the growth of sulfonamide-resistant bacteria and decrease the abundance of the sul1 gene. Additionally, it was ascertained that the optimization of initial compost pH levels or the incorporation of a compound microbial inoculant effectively reduced the abundance of intracellular and extracellular sulfonamide ARGs and the intI1 gene. The proliferation of Actinobacteria and certain genera during the maturation phase was closely associated with the enrichment of sulfonamide ARGs. This research provides references for the multi-pathway comprehensive control of sulfonamide ARG pollution in composting. Full article

(This article belongs to the Special Issue Impacts of Emerging Agricultural Pollutants on Environmental Health)

► Show Figures

Graphical abstract

25 pages, 1888 KB

Open AccessArticle

Linking Yield, Baking Quality, and Rheological Properties to Guide Sustainable Improvement of Rwandan Wheat Varieties

by Yves Theoneste Murindangabo, Trong Nghia Hoang, Innocent Habarurema, Petr Konvalina, Marguerite Niyibituronsa, Protegene Byukusenge, Protogene Mbasabire, Josine Uwihanganye, Roger Bwimba, Marie Grace Ntezimana and Dang Khoa Tran

Agriculture 2025, 15(20), 2160; https://doi.org/10.3390/agriculture15202160 - 17 Oct 2025

Viewed by 406

Abstract

Wheat is an important crop in Rwanda; however, rapid population growth, urbanization, and shifting dietary preferences have driven demand far beyond domestic production capacity, resulting in a steady increase in imports. Closing this gap requires a variety of management strategies that jointly optimise [...] Read more.

Wheat is an important crop in Rwanda; however, rapid population growth, urbanization, and shifting dietary preferences have driven demand far beyond domestic production capacity, resulting in a steady increase in imports. Closing this gap requires a variety of management strategies that jointly optimise yield, processing quality, and sustainability. This study evaluated ten widely cultivated wheat (Triticum aestivum L.) varieties in Rwanda through an integrated assessment of grain yield, quality traits, and rheological properties. Yields ranged from 4.3 to 6.3 t ha⁻¹, with Nyaruka and Gihundo achieving the highest productivity. Quality attributes, including protein content (PC), wet gluten (WG), gluten index (GI), falling number (FN), and Zeleny sedimentation value (ZSV), varied significantly, with Cyumba and Reberaho showing superior protein levels. Mixolab-based rheological analyses revealed marked diversity in dough development time, torque, and water absorption, with Keza and Nyangufi exhibiting favorable baking profiles. Statistical analyses highlighted trade-offs between yield and quality, as high-yielding varieties such as Nyaruka showed weaker baking characteristics. These findings demonstrate that linking agronomic performance with grain and dough quality traits provides a pathway towards targeted breeding, sustainable intensification, and enhanced food security. Integrating genetic selection with tailored management and processing strategies can improve both productivity and product value, strengthening the resilience and economic viability of Rwanda’s wheat sector. Full article

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

► Show Figures

Figure 1

19 pages, 12173 KB

Open AccessArticle

Evaluating the Seedling Emergence Quality of Peanut Seedlings via UAV Imagery

by Guanchu Zhang, Qi Wang, Guowei Li, Dunwei Ci, Chen Zhang and Fangyan Ma

Agriculture 2025, 15(20), 2159; https://doi.org/10.3390/agriculture15202159 - 17 Oct 2025

Viewed by 283

Abstract

Accurate evaluation of peanut seedling emergence is critical for ensuring agronomic research accuracy and planting benefit efficiency, but traditional manual methods are limited by strong subjectivity and inconsistent batch inspection standards. In order to quickly and accurately evaluate the emergence rate and quality [...] Read more.

Accurate evaluation of peanut seedling emergence is critical for ensuring agronomic research accuracy and planting benefit efficiency, but traditional manual methods are limited by strong subjectivity and inconsistent batch inspection standards. In order to quickly and accurately evaluate the emergence rate and quality of peanuts, this study proposes an intelligent evaluation system for peanut seedling conditions, which is constructed based on an improved YOLOv11 combined with the Segment Anything Model (SAM) for peanut seedling emergence evaluation, using high-resolution images collected by Unmanned Aerial Vehicles as the data foundation. Experimental results show that the improved YOLOv11 model achieves a detection precision of 96.36%, a recall rate of 96.76%, and an mAP@0.5 of 99.03%. The segmentation performance of SAM is outstanding in terms of integrity. In practical applications, the detection time for a single image by the system is as low as 83.4 ms, and the efficiency of video counting is 6–10 times higher than that of manual counting. Without extensive data annotation, this method performs excellently in peanut seedling emergence quantity statistics and growth status classification, providing efficient, accurate technical support for refined peanut cultivation management and mechanical sowing quality evaluation. Full article

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

► Show Figures

Figure 1

23 pages, 1022 KB

Open AccessArticle

Eco-Efficiency of Crop Production in the European Union and Serbia

by Tihomir Novaković, Dragan Milić, Dragana Novaković, Mirela Tomaš Simin and Vladislav Zekić

Agriculture 2025, 15(20), 2158; https://doi.org/10.3390/agriculture15202158 - 17 Oct 2025

Viewed by 299

Abstract

This paper evaluates the eco-efficiency of crop production in the European Union (EU) and the Republic of Serbia for the period 2015–2023, using a stochastic frontier analysis (SFA) model based on panel data. Eco-efficiency was assessed as the ratio of agricultural output to [...] Read more.

This paper evaluates the eco-efficiency of crop production in the European Union (EU) and the Republic of Serbia for the period 2015–2023, using a stochastic frontier analysis (SFA) model based on panel data. Eco-efficiency was assessed as the ratio of agricultural output to key environmental pressures, with expenditures on fertilizers, plant protection products, and energy serving as proxies for ecological burden. The analysis shows that the average eco-efficiency score (Total EE) across the sample is 59.26%, implying that nearly 41% of inputs could be reduced without decreasing output. Decomposition reveals high residual eco-efficiency (93.62%) and lower persistent eco-efficiency (63.30%), suggesting that systematic inefficiencies dominate and are primarily linked to internal farm-level factors such as management practices, organizational structures, and technology adoption. Serbia’s total eco-efficiency score of 63.0% places it close to the EU average, confirming structural similarities with Southern and Eastern European countries. Eco-efficiency scores exhibit notable cross-country variation, ranging from approximately 35% to 96%. About 59% of countries fall within the 50–75% interval, while roughly 11% exceed 75%, indicating considerable scope for further improvement. Cluster analysis further indicates that while Serbia belongs to the lower-intensity group, it has significant potential to converge toward EU frontrunners through farm-level improvements. The findings highlight the importance of targeting internal determinants of efficiency, while recognizing that policy measures can provide enabling conditions and long-term incentives for the green transition. A coherent policy for the green transition should prioritize farm-level structural upgrades, such as technology adoption, advisory and knowledge transfer, and sustainable nutrient and soil management, supported by enabling CAP instruments (eco-schemes and GAEC) and IPARD measures to accelerate improvements in resource efficiency and environmental performance. Full article

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

► Show Figures

Figure 1

23 pages, 5077 KB

Open AccessArticle

Spatiotemporal Variation in Water–Energy–Food Synergy Capacity Based on Projection Pursuit Model in the Central Area of Yangtze River Delta, China

by Zhengwei Ye, Zonghua Li, Qilong Ren, Jingtao Wu, Manman Fan and Hongwen Xu

Agriculture 2025, 15(20), 2157; https://doi.org/10.3390/agriculture15202157 - 17 Oct 2025

Viewed by 351

Abstract

Water, energy, and food (WEF) constitute the core strategic resources essential for regional sustainable development, and the governance of the WEF system holds critical significance for the Central Area of the Yangtze River Delta (caYRD)—one of China’s most economically dynamic regions. In this [...] Read more.

Water, energy, and food (WEF) constitute the core strategic resources essential for regional sustainable development, and the governance of the WEF system holds critical significance for the Central Area of the Yangtze River Delta (caYRD)—one of China’s most economically dynamic regions. In this area, however, the potential risks associated with insufficient WEF synergy capacity have become increasingly prominent amid continuous population growth and rapid urbanization. Against this backdrop, this study aimed to evaluate the WEF synergy capacity of 27 prefecture-level cities (PLCs) in the caYRD over the period 2005–2023 using the Projection Pursuit Model (PPM), based on an evaluation framework encompassing 12 indicators. Our results revealed that (1) the WEF system exhibits significant spatiotemporal heterogeneity, which is evident not only in the water resource, energy resource, and food resource subsystems but also in the overall WEF synergy capacity. In the water subsystem, Wenzhou and Ma’anshan achieved the highest and lowest PPM evaluation scores, respectively; in the energy subsystem, Zhoushan and Shanghai recorded the highest and lowest scores, respectively; and in the food subsystem, Yancheng and Zhoushan ranked first and last in terms of PPM scores, respectively. (2) For the integrated WEF synergy capacity evaluation, Yancheng obtained the highest score, whereas Shanghai ranked the lowest; additionally, Chuzhou exhibited the largest fluctuation range in scores, while Taizhou (Jiangsu) exhibited the smallest fluctuation range. (3) Subsequently, based on the PPM evaluation values of WEF synergy capacity, the 27 PLCs were clustered into three groups: the High WEF synergy capacity value cluster, which includes Yancheng and Chuzhou; the Low WEF synergy capacity value cluster, which consists of Shanghai and Suzhou; and the Mid-level WEF synergy capacity value cluster, which comprises the remaining 22 PLCs and is further subdivided into three sub-clusters. The cluster results of WEF synergy capacity imply that special attention to the consumption control of WEF resources is required for different PLCs. The variations in WEF synergy capacity and its spatial distribution patterns provide critical insights for formulating region-specific strategies to optimize the WEF system, which is of great significance for supporting sustainable development decision-making in the caYRD. Full article

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

► Show Figures

Figure 1

16 pages, 2060 KB

Open AccessArticle

Characteristics of the Spatiotemporal Evolution and Driving Mechanisms of Soil Organic Matter in the Songnen Plain in China

by Yao Wang, Yimin Chen, Xinyuan Wang, Baiting Zhang, Yining Sun, Yuhan Zhang, Yuxuan Li, Yueyu Sui and Yingjie Dai

Agriculture 2025, 15(20), 2156; https://doi.org/10.3390/agriculture15202156 - 17 Oct 2025

Viewed by 390

Abstract

Soil organic matter (SOM) is a key component of nutrient cycling and soil fertility in terrestrial ecosystems. SOM is of great significance to the stability of terrestrial ecosystems and the improvement of soil productivity; to further exert its role, it is first necessary [...] Read more.

Soil organic matter (SOM) is a key component of nutrient cycling and soil fertility in terrestrial ecosystems. SOM is of great significance to the stability of terrestrial ecosystems and the improvement of soil productivity; to further exert its role, it is first necessary to clarify its actual distribution and occurrence status in specific regions. Under the combined impacts of intensive agriculture, unreasonable farming practices, and climate change, the SOM content in the Songnen Plain is showing a degradation trend, posing multiple stresses on its soil ecosystem functions. This study aims to systematically track the dynamic changes of SOM in the Songnen Plain, assess its spatiotemporal evolution characteristics, and reveal its driving mechanisms. A total of 113 representative soil profiles were selected in 2023; standardized excavation and sampling procedures were employed in the Songnen Plain. Soil pH, SOM, total nitrogen (TN), total phosphorus (TP), total potassium (TK), particle size (PSD), texture, and Munsell soil colors of samples were determined. Temporal variation characteristics, as well as horizontal and vertical spatial distribution patterns, in SOM content in the Songnen Plain were assayed. Structural equation modeling (SEM), together with freeze–thaw of soil and soil color mechanism analyses, was applied to reveal the spatiotemporal dynamics and driving mechanisms of SOM. The result indicated that the distribution pattern of SOM content in horizontal space shows higher levels in the northeastern region and lower levels in the southwestern region, and decreased with increasing soil depth. SEM analysis indicated that TN and PSD were the main positive factors, whereas bulk density exerted a dominant negative effect. The ranking of contribution rates is TN > TK > TP > PSD > annual average temperature > annual precipitation > bulk density. Mechanistic analysis revealed a significant negative correlation between SOM content and R, G, B values, with soil color intensity serving as a visual indicator of SOM content. Freeze–thaw thickness of soil was positively correlated with SOM content. These findings provide a scientific basis for soil fertility management and ecological conservation in cold regions. Full article

(This article belongs to the Section Agricultural Soils)

► Show Figures

Figure 1

27 pages, 1490 KB

Open AccessReview

Application of Gene Editing Technology in Livestock: Progress, Challenges, and Future Perspectives

by Jing Wang, Lei Zhang, Chuanying Pan, Xianyong Lan, Baosong Xing and Mingxun Li

Agriculture 2025, 15(20), 2155; https://doi.org/10.3390/agriculture15202155 - 17 Oct 2025

Viewed by 1053

Abstract

Gene editing technologies, particularly CRISPR/Cas9, have revolutionized livestock genetics. They enable precise, efficient, and inheritable genome modifications. This review summarizes recent advances in the application of gene editing in livestock. We focus on six key areas: enhancement of disease resistance, improvement of growth [...] Read more.

Gene editing technologies, particularly CRISPR/Cas9, have revolutionized livestock genetics. They enable precise, efficient, and inheritable genome modifications. This review summarizes recent advances in the application of gene editing in livestock. We focus on six key areas: enhancement of disease resistance, improvement of growth performance and meat production traits, modification of milk composition, regulation of reproductive traits, adaptation to environmental stress, and promotion of animal welfare. For example, they have played an important role in improving mastitis resistance in cows, enhancing meat production performance in pigs, increasing milk yield in goats, and producing polled cows. Despite rapid progress, practical implementation in animal breeding still faces challenges. These include off-target effects, low embryo editing efficiency, delivery limitations, and ethical as well as regulatory constraints. Future directions emphasize the development of advanced editing tools, multiplex trait integration, and harmonized public policy. With continued innovation and responsible oversight, gene editing holds great promise for sustainable animal agriculture and global food security. Full article

(This article belongs to the Section Farm Animal Production)

► Show Figures

Figure 1

24 pages, 6739 KB

Open AccessArticle

Linking Microstructure and Hydraulic Behavior in Cocopeat–Based Substrates Using Pore-Scale Flow Simulation and Micro-CT

by Kai Yao, Tianxiao Li, Qiang Fu, Jing Wang, Weikang Li, Xuan Zhang and Jing Li

Agriculture 2025, 15(20), 2154; https://doi.org/10.3390/agriculture15202154 - 17 Oct 2025

Viewed by 400

Abstract

The pore structure of cocopeat-based substrates critically influences their hydraulic properties, directly affecting water use efficiency in soilless cultivation systems. Previous macroscopic modeling approaches infer pore structures indirectly from water retention curves and rely on empirical parameterization of pore geometry and connectivity, overlooking [...] Read more.

The pore structure of cocopeat-based substrates critically influences their hydraulic properties, directly affecting water use efficiency in soilless cultivation systems. Previous macroscopic modeling approaches infer pore structures indirectly from water retention curves and rely on empirical parameterization of pore geometry and connectivity, overlooking microscale features that directly control fluid pathways and permeability. To address this gap, this study employed micro-CT imaging to reconstruct the three-dimensional pore structures of coarse cocopeat and a fine cocopeat–perlite mixture. Nine regions of interest (ROIs), representing three typical pore types in each substrate, were selected for quantitative pore structure analysis and pore-scale saturated flow simulations. Results show that over 90% of pore diameters in both substrates fall within the 0–400 μm range, and variations in cocopeat particle size and perlite addition significantly affect average pore diameter, porosity, fractal dimension, and tortuosity, thereby influencing permeability and local flow distribution. This study provides new insights into the microscale mechanisms governing water movement in cocopeat-based substrates and reveals key structural factors regulating hydraulic behavior in soilless cultivation systems. Full article

(This article belongs to the Section Agricultural Water Management)

► Show Figures

Figure 1

15 pages, 3498 KB

Open AccessArticle

Synergistic Effects of Phosphorus and EDDS on Enhancing Phytoremediation Efficiency of Ricinus communis L. in Cu and Cd Co-Contaminated Soils

by Wenying Liu, Rongli Tang, Xinlei Peng, Xueting Yang, Yi Wang and Hongqing Hu

Agriculture 2025, 15(20), 2153; https://doi.org/10.3390/agriculture15202153 - 16 Oct 2025

Viewed by 262

Abstract

The use of biodegradable chelating agents and fertilizer to improve phytoremediation is a cost-effective and environmental-friendly method for remediation of copper (Cu)- and cadmium (Cd)-polluted agricultural soil. A pot experiment was conducted to investigate the effects of phosphorus (P) fertilizer and the chelator [...] Read more.

The use of biodegradable chelating agents and fertilizer to improve phytoremediation is a cost-effective and environmental-friendly method for remediation of copper (Cu)- and cadmium (Cd)-polluted agricultural soil. A pot experiment was conducted to investigate the effects of phosphorus (P) fertilizer and the chelator ethylenediamine disuccinic acid (EDDS), both individually and in combination, on the phytoremediation efficiency of castor plants. The experiment included six treatments with three replicates, which were as follows: control (no P or EDDS), EDDS alone, P at 100 mg kg⁻¹, P at 300 mg kg⁻¹, P at 100 mg kg⁻¹ + EDDS, and P at 300 mg kg⁻¹ + EDDS. The results demonstrated that phosphorus significantly promoted the growth of castor plants. In the treatment in which 300 mg kg⁻¹ P₂O₅ and 5.0 mmol kg⁻¹ EDDS were added, the shoot dry weight and root dry weight increased by 42.0% and 67.6%, respectively, when compared to the treatment only applying EDDS, and this treatment significantly promoted the absorption of Cd by shoots of castor. In the absence of phosphorus application, EDDS significantly diminished the dry weight of castor roots by 27.3%. Nevertheless, it improved the concentrations of Cu in the shoots and roots of castor plants, which were 3.43 times and 3.27 times higher than those of the control, respectively. Furthermore, when combined with phosphorus fertilizers, EDDS further promoted the absorption of Cu and Cd in the shoots of castor, which significantly increased by 13.34 times and 0.47 times, respectively, with addition of 100 mg kg⁻¹ phosphorus and 5.0 mmol kg⁻¹ of EDDS compared with the control. Phosphorus and EDDS synergistically decreased the activity of POD enzymes in leaves and roots compared with those treated with only EDDS and alleviated the toxicity of EDDS and heavy metals to castor plants. These findings provide scientific evidence for the use of agronomic measures and chelators to optimize phytoremediation efficiency in Cu and Cd co-contaminated soils. Full article

(This article belongs to the Section Agricultural Soils)

► Show Figures

Figure 1

19 pages, 4056 KB

Open AccessArticle

Data-Driven Multi-Objective Optimization Design of Micro-Textured Wet Friction Pair

by Yulin Xiao, Donghui Chen, Shiqi Hao, Chong Ning, Xiaotong Ma, Bingyang Wang and Xiao Yang

Agriculture 2025, 15(20), 2152; https://doi.org/10.3390/agriculture15202152 - 16 Oct 2025

Viewed by 325

Abstract

Friction pairs in heavy-duty power-shift tractor wet clutches operate under complex conditions, making them vulnerable to damage and reducing reliability. Optimizing their tribological performance requires a trade-off between a high coefficient of friction (COF) for torque transmission and a low temperature rise ( [...] Read more.

Friction pairs in heavy-duty power-shift tractor wet clutches operate under complex conditions, making them vulnerable to damage and reducing reliability. Optimizing their tribological performance requires a trade-off between a high coefficient of friction (COF) for torque transmission and a low temperature rise (

∆ T

) to prevent thermal damage. Surface texturing is an effective method for improving the tribological performance of friction pairs. This study simulated the friction of wet clutch pairs via pin-on-disk tests and designed micro-textures on the pin surface to enhance tribological performance. Based on the experimental data, a Gaussian Process Regression (GPR) surrogate model was developed to accurately predict COF and

∆ T

as a function of the clutch’s operating and micro-texture’s geometric parameters. A Multi-Objective Particle Swarm Optimization (MOPSO) algorithm was then employed to obtain the optimal set of solutions. The obtained pareto front clearly revealed the COF–temperature rise trade-off. From the optimal solution set, optimal micro-texture parameters for two typical operating conditions of different clutches were extracted. Compared with the untextured surface, the optimal solutions increased COF by 2.6%/1.2% and reduced

∆ T

by 39.2%/12.1%. Relative to neighboring experimental points, COF further increased by 11.3%/2.7% and

∆ T

decreased by 16.6%/1.7%. This work establishes a method for balancing the frictional and thermal performance of friction pairs. Full article

(This article belongs to the Section Agricultural Technology)

► Show Figures

Figure 1

37 pages, 1690 KB

Open AccessReview

Advances in Crop Row Detection for Agricultural Robots: Methods, Performance Indicators, and Scene Adaptability

by Zhen Ma, Xinzhong Wang, Xuegeng Chen, Bin Hu and Jingbin Li

Agriculture 2025, 15(20), 2151; https://doi.org/10.3390/agriculture15202151 - 16 Oct 2025

Viewed by 656

Abstract

Crop row detection technology, as one of the key technologies for agricultural robots to achieve autonomous navigation and precise operations, is related to the precision and stability of agricultural machinery operations. Its research and development will also significantly determine the development process of [...] Read more.

Crop row detection technology, as one of the key technologies for agricultural robots to achieve autonomous navigation and precise operations, is related to the precision and stability of agricultural machinery operations. Its research and development will also significantly determine the development process of intelligent agriculture. The paper first summarizes the mainstream technical methods, performance evaluation systems, and adaptability analysis of typical agricultural scenes for crop row detection. The paper also summarizes and explains the technical principles and characteristics of traditional methods based on visual sensors, point cloud preprocessing based on LiDAR, line structure extraction and 3D feature calculation methods, and multi-sensor fusion methods. Secondly, a review was conducted on performance evaluation criteria such as accuracy, efficiency, robustness, and practicality, analyzing and comparing the applicability of different methods in typical scenarios such as open fields, facility agriculture, orchards, and special terrains. Based on the multidimensional analysis above, it is concluded that a single technology has specific environmental adaptability limitations. Multi-sensor fusion can help improve robustness in complex scenarios, and the fusion advantage will gradually increase with the increase in the number of sensors. Suggestions on the development of agricultural robot navigation technology are made based on the current status of technological applications in the past five years and the needs for future development. This review systematically summarizes crop row detection technology, providing a clear technical framework and scenario adaptation reference for research in this field, and striving to promote the development of precision and efficiency in agricultural production. Full article

(This article belongs to the Section Agricultural Technology)

► Show Figures

Figure 1

18 pages, 890 KB

Open AccessArticle

Genotype × Environment Interaction and Yield Stability of “Pinto” Bean (Phaseolus vulgaris L.) Lines in a Semi-arid Region of Mexico

by Odilón Gayosso Barragán, Jorge Alberto Acosta Gallegos, Juan Samuel Guadalupe Jesús Alcalá Rico, Yanet Jiménez Hernández, Griselda Chávez Aguilar, Ismael Fernando Chávez Díaz and Ulises Aranda Lara

Agriculture 2025, 15(20), 2150; https://doi.org/10.3390/agriculture15202150 - 16 Oct 2025

Viewed by 448

Abstract

The present study aimed to determine the Genotype × Environment interaction (GEI), yield stability, and agronomic performance of 24 “Pinto” bean lines under semi-arid conditions in Central-West Mexico. All the lines possess a slow-darkening seed coat, a trait that prolongs visual quality and [...] Read more.

The present study aimed to determine the Genotype × Environment interaction (GEI), yield stability, and agronomic performance of 24 “Pinto” bean lines under semi-arid conditions in Central-West Mexico. All the lines possess a slow-darkening seed coat, a trait that prolongs visual quality and increases market value. The lines, which exhibit an indeterminate prostrate growth habit, were evaluated in three contrasting environments: irrigated, rainfed, and drought-stressed. A combined analysis of variance, Tukey’s test, and the additive main effects and multiplicative interaction (AMMI 2) model were applied to assess seed yield and agronomic traits. Average seed yield declined markedly across environments, from 2279 kg ha⁻¹ under irrigation to 593 kg ha⁻¹ under drought stress, with different lines performing best in each environment. AMMI 2 biplot analysis showed that the first two principal components explained 100% of GEI variability for seed yield, dry shoot biomass, total biomass, harvest index, pods per plant, and seeds per pod. Both genetic and environmental effects were significant, with notable GEI patterns. Despite pronounced environmental influence, several lines exhibited stable performance across environments. Line 11 consistently combined high yield and stability, positioning it as a strong candidate for cultivar registration and as a parent in breeding programs targeting semiarid regions. These results underscore the importance of multi-environment evaluation for identifying genotypes with broad or specific adaptation, contributing to genetic improvement and sustainable bean production under variable moisture regimes. Full article

(This article belongs to the Special Issue Advancements in Genotype Technology and Their Breeding Applications)

► Show Figures

Figure 1

Journal Menu

Journal Browser

Agriculture, Volume 15, Issue 20 (October-2 2025) – 78 articles

Further Information

Guidelines

MDPI Initiatives

Follow MDPI