Agriculture

29 pages, 18448 KB

Open AccessArticle

A Novel Dataset Generation Strategy and a Multi-Period Farmland Cultivation Zones Dataset from Unmanned Aerial Vehicle Imagery

by Zirui Li, Jinping Gu, Siying Shang, Yang Zhou, Qing Luo, Mingxue Zheng, Xiaokai Li, Chengjun Lin and Xuefeng Guan

Agriculture 2026, 16(1), 32; https://doi.org/10.3390/agriculture16010032 - 22 Dec 2025

Abstract

Accurate delineation of farmland cultivation zones (FCZs) is crucial for advancing precision agriculture. However, identifying FCZs in landscapes where standardized and non-standard (fragmented) farmlands coexist remains a pressing challenge, primarily due to the lack of high-quality datasets covering such mixed patterns. To address [...] Read more.

Accurate delineation of farmland cultivation zones (FCZs) is crucial for advancing precision agriculture. However, identifying FCZs in landscapes where standardized and non-standard (fragmented) farmlands coexist remains a pressing challenge, primarily due to the lack of high-quality datasets covering such mixed patterns. To address this, we propose a novel tiling-based dataset generation method that integrates boundary probes and minimum-overlap Poisson-disk sampling (BP-MOPS). Using this strategy, we constructed a multi-temporal unmanned aerial vehicle (UAV) imagery dataset of FCZs—the multi-period farmland cultivation zones (MPFCZ) dataset—which encompasses three critical phenological stages: the dormant period (DP), the intermediate growing period (IGP), and the vigorous growing period (VGP). The source imagery was acquired over Zhouhu Village in China. The MPFCZ dataset comprises 6467 image patches (1024 × 1024 pixels), containing both standardized fields and fragmented cultivation zones typically missed by conventional methods. Both Transformer- and CNN-based models trained on MPFCZ surpassed those trained on the dataset generated by conventional segmentation strategy. The best-performing model achieved remarkable temporal change detection accuracy (mIoU > 0.82 across three phenological stages) and demonstrated strong cross-region generalization capability (0.8817 precision under zero-shot transfer). MPFCZ thus provides essential support for precise farmland identification in complex agricultural landscapes with standard and nonstandard fields mixed. Full article

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

21 pages, 1428 KB

Open AccessArticle

Genome-Wide Association Study Reveals Candidate Genes Underlying Reproduction-Associated Conformation Traits in Jersey Cattle

by Tianqi Zhao, Hui Jiang, Hao Zhu, Zhijian Zhu, Zeliang Huang, Zhaoying Song, Mudasir Nazar, Xubin Lu and Zhangping Yang

Agriculture 2026, 16(1), 31; https://doi.org/10.3390/agriculture16010031 - 22 Dec 2025

Abstract

Reproductive traits are essential in dairy cattle breeding, and improving body conformation is considered beneficial for reproductive performance. This study systematically analyzed the genetic relationships between six key conformation traits—stature (ST), body depth (BD), loin strength (LS), rump angle (RA), rump width (RW), [...] Read more.

Reproductive traits are essential in dairy cattle breeding, and improving body conformation is considered beneficial for reproductive performance. This study systematically analyzed the genetic relationships between six key conformation traits—stature (ST), body depth (BD), loin strength (LS), rump angle (RA), rump width (RW), bone quality (BQ)—and reproductive performance in 1631 Jersey cattle from China. Heritability estimates for conformation traits ranged from 0.05 to 0.62. We identified significant phenotypic and genetic correlations between conformation and reproductive traits, and regression analyses confirmed the predictive value of conformation traits for reproductive outcomes. Genome-wide association studies detected 24 significant SNPs associated with ST, RW, RA, and BQ. Subsequent bioinformatics analysis revealed seven candidate genes (AZIN1, OR2H1, HS6ST3, ERCC4, KCNH5, KRT19, KRT35) involved in embryonic development and estrous cycle regulation. Notably, incorporating six SNPs, which are linked to these candidate genes, into genomic prediction models significantly improved the accuracy for predicting Age at First Calving (AFC) and Gestation Length (GL). These results elucidate the shared genetic basis of conformation and reproduction, providing theoretical support for using conformation traits in marker-assisted selection to enhance reproductive efficiency in Jersey cattle. Full article

(This article belongs to the Section Farm Animal Production)

16 pages, 5030 KB

Open AccessArticle

Design and Evaluation of an Automated Rod-Feeding Mechanism for Small Arch Shed Machine Based on Kinematics

by Panpan Yuan, Pengfei Wen, Jia You, Sidikejiang Aiwaili, Xingliang Zhu, Huiqing Peng and Zhikun Wang

Agriculture 2026, 16(1), 30; https://doi.org/10.3390/agriculture16010030 - 22 Dec 2025

Abstract

Current small arch shed machine designs rely on manual pole placements, resulting in low construction efficiency and mechanized levels. These machines were not designed with key components tailored to the agronomic requirements of Xinjiang’s small arch shed cotton cultivation model. An automated rod-feeding [...] Read more.

Current small arch shed machine designs rely on manual pole placements, resulting in low construction efficiency and mechanized levels. These machines were not designed with key components tailored to the agronomic requirements of Xinjiang’s small arch shed cotton cultivation model. An automated rod-feeding mechanism for a small arch shed was designed using SolidWorks 2023 to bridge this gap. Its major components include rod separation and conveying units, enabling the separation and orderly transportation of tunnel rods. A kinematic simulation of the conveyor rod during the transport process using ADAMS 2024.1 software was performed to examine the effects of motor speed, synchronous belt stop block height, and horizontal distance on the conveyor rod. Using MATLAB 2023a to fit the center-of-mass distance curve yields the optimal values for the parameters (motor speed = 17.57 rpm, stop block height = 16.79 mm, and horizontal distance = 103.95 mm). Bench test results confirmed the simulation performance of the device with a motor speed of 17 rpm, a synchronous belt stop block height of 15 mm, and a horizontal distance of 100 mm. The automated rod-feeding device exhibited an 80.8% feeding rate. The prototype operates stably, and this design can serve as a reference for developing automated equipment for small arch sheds. Full article

(This article belongs to the Topic New Research on Automated and Efficient Agricultural Machineries)

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29 pages, 9117 KB

Open AccessArticle

Transcriptome and Metabolome-Based Analysis of Carbon–Nitrogen Co-Application Effects on Fe/Zn Contents in Dendrobium officinale and Its Metabolic Molecular Mechanisms

by Daoliang Yan, Shang Xiang, Yutang Cheng, Tongyu Li and Bingsong Zheng

Agriculture 2026, 16(1), 29; https://doi.org/10.3390/agriculture16010029 - 22 Dec 2025

Abstract

To explore the impact of combined carbon–nitrogen fertilization on the concentrations of Fe (ferrum) and Zn (zinc) in Dendrobium officinale (D. officinale), and to elucidate the underlying metabolic regulatory mechanisms, two-year-old seedlings of D. officinale were selected as the experimental subjects. [...] Read more.

To explore the impact of combined carbon–nitrogen fertilization on the concentrations of Fe (ferrum) and Zn (zinc) in Dendrobium officinale (D. officinale), and to elucidate the underlying metabolic regulatory mechanisms, two-year-old seedlings of D. officinale were selected as the experimental subjects. Three treatment groups were established: a control group (CK), an α-ketoglutaric acid (AKG) treatment group (C treatment, CT), a urea treatment group (N treatment, NT), and an AKG and urea combined treatment group (CT_NT). Samples were collected at 0, 8, 16, 24, and 32 days post-treatment. Physiological and biochemical analyses measured stem contents of iron, zinc, copper, nitrate nitrogen, soluble proteins, and citric acid. Transcriptomic and metabolomic technologies were employed to elucidate molecular mechanisms. Physiological studies have shown that combined carbon–nitrogen application exerts time-dependent regulation on Fe, Zn, and their key metabolites in the stems of D. officinale, presenting a trend of first increasing and then decreasing. Metabolomic analysis revealed that flavonoids, phenolic compounds, and organic acids are involved in Fe chelation, while quercetin, dopamine, and other substances promote Zn absorption. Transcriptomic analysis indicated that combined carbon–nitrogen application activates the accumulation of Fe and Zn contents by upregulating the expression of related genes. Integrated analysis demonstrated that carbon–nitrogen metabolism affects the metabolic network of D. officinale by regulating primary and secondary metabolic pathways. This study elucidated the physiological and molecular mechanisms underlying the regulation of Fe and Zn contents in D. officinale by combined carbon–nitrogen application, providing theoretical support and a scientific basis for the high-efficiency cultivation and quality improvement of D. officinale. Full article

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

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24 pages, 5274 KB

Open AccessArticle

Improved BiLSTM-TDOA-Based Localization Method for Laying Hen Cough Sounds

by Feng Qiu, Qifeng Li, Yanrong Zhuang, Xiaoli Ding, Yue Wu, Yuxin Wang, Yujie Zhao, Haiqing Zhang, Zhiyu Ren, Chengrong Lai and Ligen Yu

Agriculture 2026, 16(1), 28; https://doi.org/10.3390/agriculture16010028 - 22 Dec 2025

Abstract

Cough sounds are a key acoustic indicator for detecting respiratory diseases in laying hens, which have become increasingly prevalent with the intensification of poultry housing systems. As an important early signal, cough sounds play a vital role in disease prevention and precision health [...] Read more.

Cough sounds are a key acoustic indicator for detecting respiratory diseases in laying hens, which have become increasingly prevalent with the intensification of poultry housing systems. As an important early signal, cough sounds play a vital role in disease prevention and precision health management through timely recognition and spatial localization. In this study, an improved BiLSTM–TDOA method was proposed for the accurate recognition and localization of laying hen cough sounds. Nighttime audio data were collected and preprocessed to extract 81 acoustic features, including formant parameters, MFCC, LPCC, and their first and second derivatives. These features were then input into a BiLSTM-Attention model, which achieved a precision of 97.50%, a recall of 90.70%, and an F1-score of 0.9398. An improved TDOA algorithm was then applied for three-dimensional sound source localization, which resulted in mean absolute errors of 0.1453 m, 0.1952 m, and 0.1975 m along the X, Y, and Z axes across 31 positions. The results demonstrated that the proposed method enabled accurate recognition and 3D localization of abnormal vocalizations in laying hens, which will provide a novel approach for early detection, precise control, and intelligent health monitoring of respiratory diseases in poultry houses. Full article

(This article belongs to the Special Issue Modeling of Livestock Breeding Environment and Animal Behavior)

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15 pages, 3251 KB

Open AccessArticle

Identification and Characterization of Maize Yellow Mosaic Virus Causing Mosaic Symptoms on Maize in Taiwan

by Jing-Han Chen, Hsin-Mei Ku, Ho-Hsiung Chang, Chung-Jan Chang and Fuh-Jyh Jan

Agriculture 2026, 16(1), 27; https://doi.org/10.3390/agriculture16010027 - 22 Dec 2025

Abstract

Maize, as the global highest-yield grain crop, can impact social stability and security based on its annual yield. Given that maize viruses have caused up to 91% yield reductions, investigating maize virus diseases is of the utmost importance. In July 2020, a suspected [...] Read more.

Maize, as the global highest-yield grain crop, can impact social stability and security based on its annual yield. Given that maize viruses have caused up to 91% yield reductions, investigating maize virus diseases is of the utmost importance. In July 2020, a suspected maize yellow mosaic virus (MaYMV) was discovered in a maize field, and a MaYMV detection protocol was established. The MaYMV isolate MA70, discovered in a maize plant from Wuri District, Taiwan, in November 2022, was shown to infect both maize 42 days post-inoculation (dpi) and wheat (35 dpi), causing mosaic symptoms, through aphid transmission with corn leaf aphid (Rhopalosiphum maidis). To determine the whole genome sequence of MA70, a 5642 bp sequence was obtained using RT-PCR and Sanger sequencing. Sequencing results indicated a 94.8–96.8% nucleotide sequence similarity with 54 MaYMV isolates from GenBank and with amino acid sequence identities exceeding 90% for all MaYMV proteins. Phylogenetic analysis showed the relationship of MA70 is closest to the Chinese isolate. The nucleotide sequence identity was lower among isolates of more distinct geographical clusters. Between October 2023 and January 2024, survey results indicated that MaYMV prevalence in corn fields across six areas in Taichung reached 17.5% (130/743 plants) and was present in all the sampled fields. MaYMV was present in all sampled fields affirming its ubiquitous presence. This study establishes the first documented case of MaYMV in Taiwan; however, survey findings hint at a potential pre-existing presence in Taiwanese maize fields. Therefore, this research also develops a practical diagnostic tool for field monitoring of MaYMV prevalence, which is crucial for informing future disease management strategies, including the critical need for cross-strait between Taiwan and China collaboration on viral disease surveillance. Full article

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

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12 pages, 328 KB

Open AccessArticle

Exogenous Gibberellins Affect the Setting, Development, and Quality of ‘Golden Delicious’ Apple Fruits

by Sebastian Przybyłko, Konrad Sas, Jacek Marszał, Kamila Łucja Bokszczanin and Ewa Szpadzik

Agriculture 2026, 16(1), 26; https://doi.org/10.3390/agriculture16010026 - 21 Dec 2025

Abstract

The aim of this study was to investigate the effect of gibberellins on the setting and quality of parthenocarpic apples (Malus × domestica Borkh.). The experiment was conducted in 2021 on the ‘Golden Delicious’ cultivar in the Warsaw University of Life Sciences [...] Read more.

The aim of this study was to investigate the effect of gibberellins on the setting and quality of parthenocarpic apples (Malus × domestica Borkh.). The experiment was conducted in 2021 on the ‘Golden Delicious’ cultivar in the Warsaw University of Life Sciences experimental orchard. During the trial, we compared the effect of various gibberellins, such as GA₃, GA₄₊₇, and a mixture of GA₃ + GA₄₊₇. These gibberellins were administered to both intact and mechanically injured flowers (damaged by emasculation and style removal) at the pink bud stage. The results clearly demonstrate that gibberellins applied during blooming supported the induction of parthenocarpic fruit setting in Golden Delicious apples; however, fruitlet retention remained significantly lower than in natural pollinated flowers. The most efficient treatment among emasculated flowers was the mixture of GAs, resulting in a final fruit retention of 23.6%. Fruit size and morphology differed across treatments: GA₃ applied on intact flowers resulted in the largest parthenocarpic fruits, while the GA₄₊₇ and GAs mixture promoted a more elongated fruit shape. Moreover, gibberellin treatment affected other fruit quality traits. Almost all GA treatments led to a higher soluble solids content in fruits. In addition, apples derived from intact flowers treated with GA₃ showed reduced firmness. Overall, our findings indicate that gibberellins can support fruit set, even when flowers are injured, and to lower extent modify fruit quality, but the results depend on flower condi-tions and the type of GA used. Full article

(This article belongs to the Special Issue Adapting Horticultural Plant Cultivation Technology and Storage to Changing Conditions)

41 pages, 572 KB

Open AccessReview

Future Directions for Sustainable Poultry Feeding and Product Quality: Alternatives from Insects, Algae and Agro-Industrial Fermented By-Products

by Petru Alexandru Vlaicu, Raluca Paula Turcu, Mihaela Dumitru, Arabela Elena Untea and Alexandra Gabriela Oancea

Agriculture 2026, 16(1), 25; https://doi.org/10.3390/agriculture16010025 - 21 Dec 2025

Abstract

Due to global increases in poultry meat and egg production, consumers request sustainable agricultural practices, requiring alternative solutions for future feeding. Global egg production increased by over 41% between 2000 and 2020, from 51 to 87 million tonnes, at an average increasing rate [...] Read more.

Due to global increases in poultry meat and egg production, consumers request sustainable agricultural practices, requiring alternative solutions for future feeding. Global egg production increased by over 41% between 2000 and 2020, from 51 to 87 million tonnes, at an average increasing rate of 3%. Similarly, the production of poultry meat reached 145 million tonnes in 2023 and continues to increase, which amplifies the pressure on sustainable alternative feed solutions. Commercial poultry diets are typically based on a cereal (corn or wheat) as an energy source and a quality protein source, especially soybean meal (SBM), to provide essential amino acids. Soybean production is associated with deforesting and land use in several countries, sensitiveness to supply chains and price volatility. As a response to these challenges over the last decade, research and commercial innovation have intensively focused on alternative and novel feed resources that can be integrated into both broiler and layer diets. Some future candidate ingredients are insect meal, algae, agro-industrial by-products such as distiller’s dried grains with solubles (DDGS), brewery spent grains (BSG) and fermented feedstuffs (oilseed cakes/meals). Literature data showed that moderate inclusion of these alternative ingredients can be partly integrated in poultry diets, without compromising egg or meat quality. In some cases, studies showed improvements of productive performances and specific quality traits (yolk color, fatty acids and antioxidant compounds), offering potential to valorize waste streams, improve local circularity and provide functional ingredients for animals and humans. However, challenges still remain, especially in terms of nutrient variability, digestibility limitations, higher processing costs and still-evolving regulations which constrain mainstream adoption of some of these potential future alternatives. Full article

(This article belongs to the Special Issue Alternative and Novel Feeds for Poultry: Nutritive Value, Product Quality and Environmental Aspects)

27 pages, 559 KB

Open AccessArticle

Climate Change Risks and Green Low-Carbon Development in Agriculture: Evidence from China on the Regulatory Role of Agricultural Insurance and Spatial Spillover Effects

by Zhaoyang Lu, Nan Li, Hailong Feng, Jianglai Dong, Diao Gou and Ming Xu

Agriculture 2026, 16(1), 24; https://doi.org/10.3390/agriculture16010024 - 21 Dec 2025

Abstract

Climate change and increasingly severe weather pose dual pressures on agriculture: to reduce carbon emissions and to manage climate risk. These pressures challenge the transition to green, low-carbon development. On the basis of panel data from 31 provinces in China from 2003 to [...] Read more.

Climate change and increasingly severe weather pose dual pressures on agriculture: to reduce carbon emissions and to manage climate risk. These pressures challenge the transition to green, low-carbon development. On the basis of panel data from 31 provinces in China from 2003 to 2023—a period selected for data continuity and to capture the implementation of major national agricultural and environmental policies—in this study, an evaluation index system for agricultural green and low-carbon development (GAC) was established. This study aims to analyze the impact of climate change risks (CPRI) on GAC, focusing on the moderating role of agricultural insurance (INS) and spatial spillover effects. Specifically, it seeks to answer the following questions: (1) What is the direction and magnitude of CPRI’s effect on GAC? (2) Can INS mitigate this effect? (3) Does CPRI exhibit spatial spillover effects on GAC? Using data from the NOAA and Chinese statistical yearbooks, by employing a model with two-way fixed effects, moderating effect analysis, and the spatial Durbin model, the mechanisms underlying the spatial spillover effects of CPRI and regional heterogeneity were examined, as well as the moderating function of INS. CPRI was found to significantly inhibit GAC, as extreme weather events triggered short-term decision-making among farmers and constrained investment in green technologies. These events reduced the capacity of the soil to sequester carbon. This inhibitory effect was greater in nonmajor grain-producing regions and in eastern China. INS helped reduce negative impacts by providing effective risk transfer mechanisms. Furthermore, CPRI was found to exert harmful spillover effects across different regions, with greater indirect effects than direct effects. In conclusion, CPRI significantly hinders agricultural green transition, a process moderated by insurance and characterized by spatial spillovers. On the basis of these observations, we recommend several policies, including the development of regionally tailored adaptation strategies, the achievement of innovation in agricultural insurance products, and the establishment of collaborative governance frameworks that span regions to address these challenges. Full article

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

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26 pages, 9227 KB

Open AccessArticle

Crop Row Line Detection for Rapeseed Seedlings in Complex Environments Based on Improved BiSeNetV2 and Dynamic Sliding Window Fitting

by Wanjing Dong, Rui Wang, Fanguo Zeng, Youming Jiang, Yang Zhang, Qingyang Shi, Zhendong Liu and Wei Xu

Agriculture 2026, 16(1), 23; https://doi.org/10.3390/agriculture16010023 - 21 Dec 2025

Abstract

Crop row line detection is essential for precision agriculture, supporting autonomous navigation, field management, and growth monitoring. To address the low detection accuracy of rapeseed seedling rows under complex field conditions, this study proposes a detection framework that integrates an improved BiSeNetV2 with [...] Read more.

Crop row line detection is essential for precision agriculture, supporting autonomous navigation, field management, and growth monitoring. To address the low detection accuracy of rapeseed seedling rows under complex field conditions, this study proposes a detection framework that integrates an improved BiSeNetV2 with a dynamic sliding-window fitting strategy. The improved BiSeNetV2 incorporates the Efficient Channel Attention (ECA) mechanism to strengthen crop-specific feature representation, an Atrous Spatial Pyramid Pooling (ASPP) decoder to improve multi-scale perception, and Depthwise Separable Convolutions (DS Conv) in the Detail Branch to reduce model complexity while preserving accuracy. After semantic segmentation, a Gaussian-filtered vertical projection method is applied to identify crop-row regions by locating density peaks. A dynamic sliding-window algorithm is then used to extract row trajectories, with the window size adaptively determined by the row width and the sliding process incorporating both a lateral inertial-drift strategy and a dynamically adjusted longitudinal step size. Finally, variable-order polynomial fitting is performed within each crop-row region to achieve precise extraction of the crop-row lines. Experimental results indicate that the improved BiSeNetV2 model achieved a Mean Pixel Accuracy (mPA) of 87.73% and a Mean Intersection over Union (MIoU) of 79.40% on the rapeseed seedling dataset, marking improvements of 9.98% and 8.56%, respectively, compared to the original BiSeNetV2. The crop row detection performance for rapeseed seedlings under different environmental conditions demonstrated that the Curve Fitting Coefficient (CFC), Root Mean Squared Error (RMSE), and Mean Absolute Error (MAE) were 0.85, 1.57, and 1.27 pixels on sunny days; 0.86, 2.05 and 1.63 pixels on cloudy days; 0.74, 2.89, and 2.22 pixels on foggy days; and 0.76, 1.38, and 1.11 pixels during the evening, respectively. The results reveal that the improved BiSeNetV2 can effectively identify rapeseed seedlings, and the detection algorithm can identify crop row lines in various complex environments. This research provides methodological support for crop row line detection in precision agriculture. Full article

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

17 pages, 2184 KB

Open AccessArticle

Soybean Yield Prediction with High-Throughput Phenotyping Data and Machine Learning

by Predrag Ranđelović, Vuk Đorđević, Jegor Miladinović, Simona Bukonja, Marina Ćeran, Vojin Đukić and Marjana Vasiljević

Agriculture 2026, 16(1), 22; https://doi.org/10.3390/agriculture16010022 - 21 Dec 2025

Abstract

The non-destructive estimation of grain yield could increase the efficiency of soybean breeding through early genotype testing, allowing for more precise selection of superior varieties. High-throughput phenotyping (HTPP) data can be combined with machine learning (ML) to develop accurate prediction models. In this [...] Read more.

The non-destructive estimation of grain yield could increase the efficiency of soybean breeding through early genotype testing, allowing for more precise selection of superior varieties. High-throughput phenotyping (HTPP) data can be combined with machine learning (ML) to develop accurate prediction models. In this study, an unmanned aerial vehicle (UAV) equipped with a multispectral camera was utilized to collect data on plant density (PD), plant height (PH), canopy cover (CC), biomass (BM), and various vegetation indices (VIs) from different stages of soybean development. These traits were used within random forest (RF) and partial least squares regression (PLSR) algorithms to develop models for soybean yield estimation. The initial RF model produced more accurate results, as it had a smaller error between actual and predicted yield compared with the PLSR model. To increase the efficiency of the RF model and optimize the data collection process, the number of predictors was gradually decreased by eliminating highly correlated VIs and selecting the most important variables. The final prediction was based only on several VIs calculated from a few mid-soybean stages. Although the reduction in the number of predictors increased the yield estimation error to some extent, the R² in the final model remained high (R² = 0.79). Therefore, the proposed ML model based on specific HTPP variables represents an optimal balance between efficiency and prediction accuracy for in-season soybean yield estimation. Full article

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

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17 pages, 641 KB

Open AccessReview

Recent Advances in Nematicides and Their Modes of Action

by Dongdong Yan, Reza Ghaderi, Jizheng He, Aocheng Cao and Qiuxia Wang

Agriculture 2026, 16(1), 21; https://doi.org/10.3390/agriculture16010021 - 21 Dec 2025

Abstract

Plant parasitic nematodes cause substantial economic losses in agricultural products worldwide. Chemical control remains the predominant strategy among available approaches for nematode management. In recent years, a new generation of synthetic nematicides with distinct biochemical targets and improved selectivity has emerged. However, our [...] Read more.

Plant parasitic nematodes cause substantial economic losses in agricultural products worldwide. Chemical control remains the predominant strategy among available approaches for nematode management. In recent years, a new generation of synthetic nematicides with distinct biochemical targets and improved selectivity has emerged. However, our understanding of the mechanisms of action, activity spectra, and safety of these new agents remains fragmented and lacks systematic integration. Clarifying their modes of action is essential for both the rational development and effective application of these compounds. This article reviews the characteristics and modes of action of both traditional and innovative nematicides, including organophosphates, carbamates, avermectins, cyclobutrifluram, fluazaindolizine, tioxazafen, fluensulfone, and fluopyram, following the classification by the Insecticide and Fungicide Resistance. This review addresses this gap by critically examining modern nematicides currently in use or under development, highlighting their molecular targets, toxicological considerations, and potential roles in sustainable nematode management. Full article

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

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21 pages, 7449 KB

Open AccessArticle

Identification of Spatiotemporal Variations and Influencing Factors of Groundwater Drought Based on GRACE Satellite

by Weiran Luo, Fei Wang, Jianzhong Guo, Ziwei Li, Ning Li, Mengting Du, Ruyi Men, Rong Li, Hexin Lai, Qian Xu, Kai Feng, Yanbin Li, Shengzhi Huang and Qingqing Tian

Agriculture 2026, 16(1), 20; https://doi.org/10.3390/agriculture16010020 - 21 Dec 2025

Abstract

The Gravity Recovery and Climate Experiment (GRACE) tracks drought events by detecting changes in the global gravitational field and capturing abnormal information on the reserves of surface water, soil water, and groundwater, which makes it possible for a more comprehensive and unified global [...] Read more.

The Gravity Recovery and Climate Experiment (GRACE) tracks drought events by detecting changes in the global gravitational field and capturing abnormal information on the reserves of surface water, soil water, and groundwater, which makes it possible for a more comprehensive and unified global and regional monitoring of groundwater drought. This study adopted the gravity satellite GRACE data and combined it with the hydrological model dataset. Additionally, we assessed the temporal evolution and spatial pattern of groundwater drought in the Yangtze River Basin (YRB) and its sub-basins from 2003 to 2022, determined the change points of the hidden seasonal and trend components in groundwater drought, and identified the direct/indirect driving contributions of the main climatic and circulation factors to groundwater drought. The results show that (1) as a normalized index, the groundwater drought index (GDI) can reflect direct evidence of any surplus and deficit in groundwater availability. During the study period, the minimum value (−1.66) of the GDI occurred in July 2020 (severe drought). (2) The average value of GDI in the entire basin ranged from −1.66 (severe drought) to 0.52 (no drought). (3) The average Z_s values (Mann–Kendall Z-statistic) of GDI were −0.23, −0.16, −0.43, and 0.14, respectively, and the proportions of areas with aggravated drought reached 65.21%, 61.05%, 89.70% and 43.67%, respectively. (4) Partial wavelet coherence analysis can simultaneously reveal the local correlations of time series at different time scales and frequencies. Based on partial wavelet analysis, precipitation was the best factor for explaining the dynamic changes in groundwater drought. (5) The North Pacific Index (NPI), the Pacific/North American Index (PNA), and the Sunspot Index (SSI) can serve as the main predictors that can effectively capture the drought changes in groundwater in the YRB. The GRACE satellite can provide a new tool for monitoring, tracking, and assessing groundwater drought situations, which is of great significance for guiding the development of the drought early warning system in the YRB and effectively preventing and responding to drought disasters. Full article

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

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18 pages, 3023 KB

Open AccessArticle

Integrated Transcriptome and Metabolome Analysis Revealed the Molecular Mechanisms of Cold Stress in Japonica Rice at the Booting Stage

by Wendong Ma, Zhenhua Guo, Peng Li, Hu Cao, Yongsheng Cai, Xirui Zhang, Xiao Han, Yanjiang Feng, Jinjie Li and Zichao Li

Agriculture 2026, 16(1), 19; https://doi.org/10.3390/agriculture16010019 - 21 Dec 2025

Abstract

Japonica rice is susceptible to cold stress at the booting stage, yet the systematic molecular mechanisms underlying varietal disparities in cold tolerance at this stage remain poorly understood. To fill this research gap, cold-tolerant LG1934 (V3) and cold-sensitive KD8 (V6) were subjected to [...] Read more.

Japonica rice is susceptible to cold stress at the booting stage, yet the systematic molecular mechanisms underlying varietal disparities in cold tolerance at this stage remain poorly understood. To fill this research gap, cold-tolerant LG1934 (V3) and cold-sensitive KD8 (V6) were subjected to low-temperature treatment (15 °C) for 0 h (T1), 72 h (T3), and 120 h (T5) at the booting stage, followed by analyses of agronomic traits, antioxidant physiology, metabolome, transcriptome, and weighted gene co-expression network analysis (WGCNA). Phenotypic results showed that low temperature was the main driver of differences in panicle length, seed setting rate, and grain weight between the two varieties, with V3 exhibiting significantly stronger cold tolerance. Under cold stress, V3 maintained higher activities of superoxide dismutase (SOD), peroxidase (POD), and catalase (CAT), accompanied by lower O₂⁻ accumulation and higher contents of malondialdehyde (MDA), H₂O₂, and proline compared to V6. Metabolomic analysis identified 56 differential accumulated metabolites (DAMs), with amino acids and their derivatives (notably L-aspartic acid) as key contributors. RNA-seq analysis identified 472 common differentially expressed genes (DEGs) that were enriched in alanine, aspartate, and glutamate metabolism, with 20 transcription factors (TFs) from TCP, WRKY, and bHLH families screened. The WGCNA revealed nine DEM-correlated modules, with orange and pink modules positively associated with L-aspartic acid. Eleven core TFs were identified, among which OsPCF5 acted as a hub regulator that activated OsASN1 transcription to promote L-aspartate biosynthesis, enhancing ROS scavenging and cold tolerance. This study systematically demonstrated the cold tolerance molecular network in japonica rice at the booting stage, highlighting the antioxidant system and L-aspartate-mediated pathway, and the core genes provided valuable resources for cold-tolerance breeding. Full article

(This article belongs to the Section Crop Production)

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22 pages, 987 KB

Open AccessReview

Sodium Butyrate in Pig Nutrition: Applications and Benefits

by Katerina P. Burlakova and Kiril K. Dimitrov

Agriculture 2026, 16(1), 18; https://doi.org/10.3390/agriculture16010018 - 20 Dec 2025

Abstract

Efficient, cost-effective and sustainable pork production remains a primary objective in modern pig farming. However, the extensive use of antibiotics in animal nutrition has raised significant concerns regarding food safety and the emergence of antibiotic-resistant bacteria. These challenges have prompted the search for [...] Read more.

Efficient, cost-effective and sustainable pork production remains a primary objective in modern pig farming. However, the extensive use of antibiotics in animal nutrition has raised significant concerns regarding food safety and the emergence of antibiotic-resistant bacteria. These challenges have prompted the search for safe and effective alternatives to antibiotic growth promoters. Sodium butyrate (SB), the sodium salt of butyric acid, has gained considerable attention as a functional feed additive in swine production. Its supplementation has been shown to improve intestinal morphology, regulate gut microbiota composition and enhance immune competence, resulting in better nutrient utilization and growth performance. Moreover, SB supplementation may support environmental sustainability in livestock production by mitigating the emission of harmful gases in swine housing facilities. Although current evidence is limited, in vitro studies have reported promising reductions in NH₃, H₂S and total gas production by 17.96%, 12.26% and 30.30%, respectively. Comparable effects have also been observed in laying hens, where NH₃ emissions were reduced by 26.22%. This review summarizes current knowledge on the application of sodium butyrate in pig nutrition, focusing on its mechanisms of action, effects on health and productivity, and potential environmental benefits. The findings indicate that SB represents a promising and safe alternative to antibiotics, supporting both animal welfare and sustainable pork production within modern livestock systems. Full article

(This article belongs to the Special Issue Impact of Novel Dietary Regimen on Growth Performance and Nutrient Utilization in Monogastric Animals)

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19 pages, 485 KB

Open AccessArticle

Are Andean Dairy Farms Losing Their Efficiency?

by Carlos Santiago Torres-Inga, Ángel Javier Aguirre-de Juana, Raúl Victorino Guevara-Viera, Paola Gabriela Alvarado-Dávila and Guillermo Emilio Guevara-Viera

Agriculture 2026, 16(1), 17; https://doi.org/10.3390/agriculture16010017 - 20 Dec 2025

Abstract

(1) Background: Ecuador is the fourth largest milk producer in Latin America, where ap-proximately 80% of production originates from small family farms located in the Andean region. Despite their socioeconomic importance, these farms face challenges related to low technical efficiency. While there are [...] Read more.

(1) Background: Ecuador is the fourth largest milk producer in Latin America, where ap-proximately 80% of production originates from small family farms located in the Andean region. Despite their socioeconomic importance, these farms face challenges related to low technical efficiency. While there are specific studies on efficiency in dairy systems from other regions, a knowledge gap persists regarding the temporal evolution of technical efficiency (TE) in Ecuadorian Andean dairy farms, especially during crisis periods such as the COVID-19 pandemic. The objective of this study was to evaluate the evolution of TE of family dairy farms in the Ecuadorian Andean region during the period 2018–2024 and to analyze the impact of the pandemic on said efficiency. (2) Methods: Data Envelopment Analysis (DEA) with input orientation and bootstrap simulation was employed to estimate TE, using data from a representative sample that included between 2370 and 2987 farms per year (approximately 25% of the national database of the Ministry of Agriculture and Livestock). Farms were selected based on the availability of complete information on key variables: number of milking cows, area dedicated to forage, family and hired labor (annual hours), and total annual milk production. Statistical analysis included ANOVA to compare mean TE values between years, post-hoc tests to identify specific differences between periods, and the identification of factors related to the TE. (3) Results: The mean TE of Andean dairy farms increased significantly from 0.37 in 2018 to 0.44 in 2024 (p < 0.10), evidencing sustained improvement, although the mean is still distant from the efficiency frontier. The analysis revealed a notable decrease in TE during 2020–2021, coinciding with the period of greatest impact of the COVID-19 pandemic, followed by progressive recovery in subsequent years. The TE distribution showed that between 70% and 75% of farms remained below 0.50 throughout the analyzed period, while only 8–12% achieved levels above 0.70. The main sources of technical inefficiency identified were relative excesses of labor and forage area in relation to milk production obtained. When compared with international studies, Ecuadorian farms present TE levels substantially lower than those reported in the European Union (>0.80) and similar to or slightly lower than those found in Turkey (0.61–0.71). (4) Conclusions: Family dairy farms in the Ecuadorian Andean region operate with technical efficiency levels considerably below their potential and international standards, suggesting substantial scope for improvement through the optimization of productive resource use, particularly labor and land. The COVID-19 pandemic impacted the sector’s efficiency negatively but temporarily, demonstrating resilience and recovery capacity. These findings are relevant to the design of public policies and technical assistance programs aimed at sustainable intensification of family dairy production in the Andes, with an emphasis on improving labor productivity and the efficient use of forage area. Full article

(This article belongs to the Section Farm Animal Production)

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10 pages, 435 KB

Open AccessArticle

Host Feeding by Jaliscoa hunteri Crawford (Hymenoptera: Pteromalidae) Suppresses Populations of Anthonomus testaceosquamosus Linell (Coleoptera: Curculionidae)

by German Vargas, Yisell Velázquez-Hernández, Dakshina Seal, Nagamani Kanchupati and Alexandra M. Revynthi

Agriculture 2026, 16(1), 16; https://doi.org/10.3390/agriculture16010016 - 20 Dec 2025

Abstract

The hibiscus bud weevil (Anthonomus testaceosquamosus, HBW) is an economically important pest of tropical hibiscus, Hibiscus rosa-sinensis. Although Jaliscoa hunteri parasitizes other Anthonomus species, its suitability as a biocontrol agent for HBW remains unknown. This study evaluated its potential under [...] Read more.

The hibiscus bud weevil (Anthonomus testaceosquamosus, HBW) is an economically important pest of tropical hibiscus, Hibiscus rosa-sinensis. Although Jaliscoa hunteri parasitizes other Anthonomus species, its suitability as a biocontrol agent for HBW remains unknown. This study evaluated its potential under laboratory and greenhouse conditions. In laboratory assays, a couple of parasitoids were exposed to HBW at different developmental stages. Parasitism was rarely observed, but host feeding was evident, and eggs, first instar larvae, and pupae showed high mortality in comparison to controls with no parasitoids. Cage experiments compared three release rates (one, two, or three parasitoid pairs) on infested flower buds. Mortality was lowest in controls, but increasing parasitoid numbers did not enhance pest suppression. In greenhouse trials, hibiscus plants were infested and exposed to the same release rates. Mortality was higher in the one-pair treatment than in controls, whereas higher release rates produced intermediate mortality, suggesting possible disruption of female reproductive activity or other unknown limiting factors. Overall, J. hunteri showed promising potential as a natural enemy of HBW, functioning like a predator rather than a parasitoid. Additional research on its reproductive biology, host interactions, and release strategies is needed to improve its effectiveness for biological control in hibiscus nurseries. Full article

(This article belongs to the Special Issue Advances in Biological Pest Control in Agroecosystems)

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28 pages, 9145 KB

Open AccessArticle

The Spatiotemporal Characteristics and Prediction of Soil and Water Conservation as Carbon Sinks in Karst Areas Based on Machine Learning: A Case Study of Puding County, China

by Man Li, Lijun Xie, Rui Dong, Shufen Huang, Qing Yang, Guangbin Yang, Ruidi Ma, Lin Liu, Tingyue Wang and Zhongfa Zhou

Agriculture 2026, 16(1), 15; https://doi.org/10.3390/agriculture16010015 - 20 Dec 2025

Abstract

Carbon sequestration by vegetation and soil conservation are vital components in balancing greenhouse gas emissions and enhancing terrestrial ecosystem carbon sinks. They also represent an efficient pathway towards achieving carbon neutrality objectives and addressing numerous environmental challenges arising from global warming. Soil and [...] Read more.

Carbon sequestration by vegetation and soil conservation are vital components in balancing greenhouse gas emissions and enhancing terrestrial ecosystem carbon sinks. They also represent an efficient pathway towards achieving carbon neutrality objectives and addressing numerous environmental challenges arising from global warming. Soil and water conservation, as crucial elements of ecological civilisation development, constitute a key link in realising carbon neutrality. This study systematically quantifies and forecasts the spatiotemporal characteristics of carbon sink capacity in soil and water conservation within the study area of Puding County, a typical karst region in Guizhou Province, China. Following a research approach of “mechanism elucidation–model construction–categorised estimation”, we established a carbon sink calculation system based on the dual mechanisms of vertical biomass carbon fixation via vegetative measures and horizontal soil organic carbon (SOC) retention using engineering measures. This system combines forestry, grassland, and engineering, with the aim of quantifying regional carbon sinks. Machine learning regression algorithms such as Random Forest, ExtraTrees, CatBoost, and XGBoost are used for backtracking estimation and optimisation modelling of soil and water conservation as carbon sinks from 2010 to 2022. The results show that the total carbon sink capacity of soil and water conservation in Puding County in 2017 was 34.53 × 10⁴ t, while the contribution of engineering measures was 22.37 × 10⁴ t. The spatial distribution shows a pattern of “higher in the north and lower in the south”. There are concentration hotspots in the central and western regions. Model comparison demonstrates that the Random Forest and extreme gradient boosting regression models are the best models for plantations/grasslands and engineering measures, respectively. The LSTM model was applied to predict carbon sink variables over the next ten years (2025–2034), showing that the overall situation is relatively stable, with only slight local fluctuations. This study solves the problem of the lack of quantitative data on soil and water conservation as carbon sinks in karst areas and provides a scientific basis for regional ecological governance and carbon sink management. Our findings demonstrate the practical significance of promoting the realisation of the “double carbon” goal. Full article

(This article belongs to the Section Agricultural Soils)

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28 pages, 5880 KB

Open AccessArticle

Load Dynamic Characteristics and Energy Consumption Model of Manipulator Joints for Picking Robots Based on Bond Graphs: Taking Joints V and VI as Examples

by Jinzhi Xie, Yunfeng Zhang, Changpin Chun, Congbo Li, Gang Xu and Li Li

Agriculture 2026, 16(1), 14; https://doi.org/10.3390/agriculture16010014 - 20 Dec 2025

Abstract

The manipulator is a key component for harvesting citrus and other fruit crops. A study of the dynamic characteristics and energy consumption modelling of its joints is the foundation for optimising the manipulator’s load parameters and achieving efficient operation. To address the issues [...] Read more.

The manipulator is a key component for harvesting citrus and other fruit crops. A study of the dynamic characteristics and energy consumption modelling of its joints is the foundation for optimising the manipulator’s load parameters and achieving efficient operation. To address the issues of the 6-DOF citrus-picking manipulator’s high degrees of freedom and complex structure, which lead to complex dynamic characteristics and an unclear energy transfer and consumption mechanism, the electromechanical coupling dynamics and energy consumption of the joint system are systematically studied using bond graphs. Firstly, the bond graph model is constructed by combining it with the joint system’s physical structure. On this basis, the corresponding dynamic characteristic state equation and energy consumption model are established. Secondly, the dynamic response and energy consumption characteristics of the joint system are analysed, revealing the system’s energy consumption and dynamic characteristics under different working conditions. Finally, the effectiveness and precision of the proposed model in describing the dynamic behaviour of the joint system and energy consumption are verified through experiments. The model provides a theoretical basis and a new research perspective for optimizing joint parameters, load solutions, and energy efficiency of the harvesting manipulator. Full article

(This article belongs to the Section Agricultural Technology)

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