Agriculture doi: 10.3390/agriculture16091010

Authors: Yankang Hu Xinglong Yang Lei Zhang

Against the backdrop of increasingly severe agricultural labor aging (ALA), the aging process not only threatens food security but also poses challenges to green and sustainable agricultural development. Existing studies have paid insufficient attention to how ALA simultaneously affects grain production efficiency (GPE) and grain eco-efficiency (GEE), and there is a particular lack of systematic investigation into the moderating roles of different crop types and social networks. To address this gap, this study utilizes survey data from 1056 farm households across five major grain-producing provinces in China and employs Tobit regression models to empirically examine the dual effects of ALA on GPE and GEE, while also revealing the moderating mechanisms of formal and informal dual-layer social networks. The main findings are as follows: (1) ALA generally inhibits both GPE and GEE across different grain crops, with a more prevalent negative impact on GEE. (2) The impact of ALA on the two types of efficiency exhibits crop-specific nonlinear characteristics: a positive U-shaped relationship for maize, an inverted U-shaped relationship for rice, and no significant nonlinear relationship for wheat. (3) Social networks play significant linear and nonlinear moderating roles in mitigating the negative effects of ALA, though their effects vary depending on network type, crop system, and efficiency dimension. Based on these findings, it is recommended to implement differentiated intervention strategies tailored to crop characteristics and aging stages, build a multi-tiered social network support system, and strengthen the research, extension, and service support for green technologies targeting middle-aged and older farmers, thereby synergistically enhancing grain production capacity and ecological sustainability.

Agriculture doi: 10.3390/agriculture16091009

Authors: Fumeng He Binghua Qin Yongqi Wang Md. Abul Kalam Azad Yanzhong Feng Xiangfeng Kong Fenglan Li

Stevia residue (SR), a typical by-product of the stevia industry, is rich in organic matter and has great potential as a feed resource. However, its high fiber content and low utilization efficiency limit its practical application in poultry production. To improve the nutritional value and application potential of SR, this study first optimized the fermentation conditions of SR using response surface methodology (RSM) with chlorogenic acid as the key optimization index and then investigated the effects of different doses of SR and fermented SR (FSR) on laying performance, egg quality, antioxidant capacity, and immunity in laying hens. Six fermentation parameters, including pH, solid-to-liquid ratio, temperature, inoculation quantity, brown sugar addition, and soybean meal addition, were first screened using single-factor experiments and then optimized with RSM. Subsequently, 560 laying hens were randomly divided into seven groups and fed a basal diet supplemented with 0, 0.5%, 1.0%, and 1.5% of either SR or FSR for 28 days. The results showed that the optimal fermentation conditions were a solid-to-liquid ratio of 75.6%, brown sugar addition of 2.7%, temperature of 25 °C, inoculation quantity of 3%, and fermentation time of 9 days. In the animal study, dietary 0.5% SR and FSR reduced average daily feed intake and eggshell strength, whereas the plasma total antioxidant capacity was enhanced in all (SR or FSR) supplemented groups (p < 0.05). Moreover, plasma immunoglobulin (Ig) A level was increased in the 1.0–1.5% SR and 1.5% FSR groups, and plasma IgY was elevated in the 1.0% SR group (p < 0.05). Our results suggested that SR fermentation was effectively optimized through RSM, and dietary FSR supplementation at 1.0% improved the health of laying hens, representing the optimal inclusion level.

Agriculture doi: 10.3390/agriculture16091008

Authors: Radek Aulicky Marcela Frankova Tereza Radostna Pavel Fousek Jana Bowers Hana Vokralova Vaclav Stejskal

The common vole (Microtus arvalis) is a major rodent pest in European agroecosystems, causing periodic outbreaks that result in substantial crop losses and pose potential public health risks. Rodenticides remain the most widely used method for population control; however, current phosphide-based formulations present challenges related to environmental safety and non-target species exposure. This study evaluated the palatability and efficacy of novel alpha-chloralose bait variations for common voles. Laboratory trials were conducted in three phases: (i) screening of non-toxic cereal carriers to identify highly palatable formulations, (ii) comparison of alpha-chloralose from two manufacturers to select the optimal active ingredient, and (iii) enhancement of palatability and attractiveness through incorporation of several attractants. Choice and no-choice feeding tests revealed that alpha-chloralose efficacy is strongly influenced by bait formulation and pellet size, with small pellets (3 mm) ensuring that a single pellet provides a lethal dose for an individual vole. In laboratory conditions, the highest mortality rate, 50% (n = 12), was observed in the bait containing the milkvetch attractant. Subsequent small-scale field trials demonstrated that this bait achieved efficacy (85%) comparable to commercial zinc phosphide bait (90%). The study confirms that alpha-chloralose, when incorporated into optimized bait matrices, could be a viable rodenticide that combines rapid, humane action with a reduced risk of secondary poisoning, making it a promising tool for integrated pest management strategies.

Agriculture doi: 10.3390/agriculture16091007

Authors: Li Guo Xie

Balancing food security with ecological sustainability is a critical challenge for global agricultural development. This research explores how China’s “three rights separation” reform influences the ecological efficiency of cultivated land use. This institutional innovation separates ownership, contract, and management rights to improve land resource allocation. Utilizing panel data from China spanning from 2005 to 2023, this study employs a super-efficiency SBM model to evaluate ecological efficiency, a continuous difference-in-differences (DID) framework to identify the causal effects of the reform, and a mediation effect model to explore the underlying transmission mechanisms. The results show that the “three rights separation” reform significantly improves the ecological efficiency of cultivated land use, with a regression coefficient of 0.632 that is statistically significant at the 1% level. The findings remain robust across multiple robustness tests. Mechanism analysis reveals distinct hierarchical transmission pathways through the promotion of non-agricultural labor transfer, the optimization of planting structure, and the advancement of agricultural technological progress. Among these pathways, agricultural technological progress emerges as the primary driver. Furthermore, heterogeneity analysis indicates that the positive impact of the reform is more pronounced in non-major grain-producing regions, as well as areas characterized by higher levels of mechanization and land transfer. These results suggest that further deepening land tenure reform is essential, with careful consideration of regional disparities and the mediating role of labor factors, land resource allocation, and technological progress.

Agriculture doi: 10.3390/agriculture16091006

Authors: Shuang Guo Guanghui Yang Wei Wu Shuangshuang Liu Yang Wang Weiming Wang Huasen Xu Cheng Xue

Split nitrogen (N) application is an important agronomic measure for improving wheat yield and quality, yet how rhizosphere nitrogen-transforming microbes respond to split N strategies and the underlying mechanisms remain unclear. This study investigated the effects of six N treatments, including control, basal application, jointing-stage soil topdressing, and foliar applications at booting, anthesis, and 10 days post-anthesis, on the community structure and diversity of key rhizospheric nitrogen cyclers (ammonia-oxidizing archaea (AOA), ammonia-oxidizing bacteria (AOB), and nitrite-oxidizing bacteria (NOB)) in wheat. Results showed that AOB and NOB alpha diversity were significantly modified by split N application. N application at anthesis enhanced AOB richness and diversity more than the later application, while concurrently decreasing NOB diversity. Booting-stage application enriched Nitrosospira and Nitrosomonas in the AOB community, whereas anthesis application increased Nitrososphaera sp. JG1 in AOA, but decreased Candidatus Nitrospira inopinata in NOB. Redundancy analysis identified soil pH, moisture, organic carbon, and key enzyme activities as the main drivers of microbial community assembly. Although no significant differences were observed in key agronomic traits among treatments, the 10 days post-anthesis treatment showed numerically superior yield and N uptake. Notably, AOB community evenness was significantly positively correlated with grain yield, protein yield, and N uptake, whereas NOB community diversity showed negative correlations. These findings demonstrate that split N application, particularly late foliar spray at 10 days post-anthesis, can modulate soil physico-chemical properties to selectively shape nitrogen-transforming microbial communities (notably AOB) in the wheat rhizosphere. This study provides a theoretical foundation for designing precise N management strategies rooted in rhizosphere ecology, with the goal of simultaneously improving yield, grain quality, and nitrogen use efficiency.

Agriculture doi: 10.3390/agriculture16091004

Authors: Ali Karamolachab Saman Abdanan Mehdizadeh Yiannis Ampatzidis

This paper presents the design and field evaluation of a low-cost automatic steering system for agricultural tractors. The system employs a PID controller whose gains are tuned using a metaheuristic optimization method. Core hardware includes an ESP32 microcontroller, an MPU9250 inertial measurement unit, a GPS module, and a servo motor for closed-loop yaw angle control, with a complementary filter fusing gyroscope and magnetometer data for robust heading estimation. Nine optimization algorithms were systematically compared: Grid Search, Random Search, Bayesian Optimization, Particle Swarm Optimization (PSO), Grey Wolf Optimizer (GWO), Moth-Flame Optimization (MFO), Sine Cosine Algorithm (SCA), Whale Optimization Algorithm (WOA), and Salp Swarm Algorithm (SSA). A cost function combining overshoot and settling time was used. Step response analysis showed that WOA achieved the best performance, with an integral absolute error of 6.31°·s, a settling time of 2.15 s, and a minimal overshoot of 0.08°. In field tests on asphalt and farmland, the WOA-tuned system reduced lateral deviation by 69% (from 12.4 cm to 3.8 cm) and 67% (from 18.7 cm to 6.2 cm), respectively, compared to manual steering. Repeated-measures ANOVA and paired t-tests confirmed statistically significant improvements (p < 0.001) with large effect sizes (Cohen’s d > 2.7). The core components cost under $150 USD. The study offers a reproducible pipeline for comparative metaheuristic evaluation in agricultural vehicle guidance.

Agriculture doi: 10.3390/agriculture16091005

Authors: Han Chen Yani Guo Tingchang Zheng Yuxuan Ji Xinyu Wu Shuisheng Fan Liyu Mao

Against the background of climate uncertainty, market volatility, and evolving regulatory environments, firms embedded in agricultural value chains face increasing pressure to maintain sustainable growth. This study examines China’s A-share-listed Traditional Chinese Medicine (TCM) firms to explore how internal organizational factors and external institutional conditions jointly shape firm-level sustainable growth capability. This setting is characterized by strong ecological dependence, strict quality regulation, deep policy embeddedness, and supply-chain sensitivity. Drawing on the resource-based view, dynamic capability theory, contingency theory, and the institutional environment perspective, this study applies fuzzy-set qualitative comparative analysis (fsQCA) to 2023 cross-sectional data from 59 A-share-listed TCM firms. The results show that no single condition constitutes a necessary condition for high sustainable growth capability. Instead, high sustainable growth capability is mainly achieved through three configurational pathways: innovation-driven growth, policy-supported development, and market-responsive strategy. Low sustainable growth capability follows asymmetric pathways, mainly reflected in the mismatch between innovation capability and the institutional environment, and the coexistence of high financing constraints and low agility response. The findings indicate that sustainable growth capability is not the result of isolated factors, but a context-specific configurational outcome shaped by innovation, agility response, internationalization, equity governance, ESG performance, government support, marketization level, and financing conditions. This study provides a configurational explanation for growth research on agriculture-related firms and offers differentiated pathway implications for managers and policymakers.

Agriculture doi: 10.3390/agriculture16091003

Authors: Deepashri Kogali Math James Satheesh Kumar Santhosh Krishnan Venkata Bhagya Rajesh Navada

Efficient crop management requires intelligent control strategies capable of handling uncertainty, nonlinear environmental interactions and dynamic crop growth conditions. This study presents a multisensor data fusion-based intelligent crop management framework for Capsicum cultivation using both a Mamdani fuzzy inference system (MFIS) and an adaptive Mamdani fuzzy inference system (AMFIS). The Capsicum dataset from the SmartFasal platform includes temperature, humidity and soil moisture at three depths, recorded over a four-month period (March–June 2020) with a total of 7188 samples. The proposed MFIS and AMFIS models are implemented and evaluated in the simulation environment. A Capsicum yield of 60–63 t/ha (3.6–3.8 kg/plant) is predicted via a regression model built on raw sensor inputs under conventional environmental management. An expert-rule MFIS with triangular memberships improves the regulation of agricultural parameters, increasing yield to 70–73 t/ha (4.2–4.4 kg/plant), a 15–18% increase. To improve adaptability, the AMFIS model incorporates fuzzy C-means (FCM) clustering for the automatic tuning of Gaussian membership functions and enables the controller to adjust dynamically to sensor data distributions. The adaptive system achieves a predicted productivity range of 82–87 t/ha (4.9–5.2 kg/plant), a 30–35% increase over the baseline. The regression model validation metrics R2 = 0.86, RMSE = 2.1 t/ha, and MAE = 1.7 t/ha confirm the reliability of the yield estimation within the simulation framework rather than experimentally measuring crop performance. A correlation analysis, histograms, scatter plots, and Bland–Altman assessments reveal that compared with the MFIS, the AMFIS results in smoother control transitions, lower variability, and higher resource-use efficiency. This study represents a data-driven simulation framework, and future work will focus on real-time implementation and experimental validation under actual greenhouse conditions.

Agriculture doi: 10.3390/agriculture16091001

Authors: Wanessa Alves Lima Paiva Brenda Vieira de Oliveira Camila Ferreira Azevedo Ana Carolina Campana Nascimento Diego Jarquin Moyses Nascimento

The main approach for improving multiple traits simultaneously is the selection index. The most widely used selection indices are those based on factor analysis, which overcome statistical limitations such as multicollinearity and the reliance on arbitrary weights of the classical Smith–Hazel approach and support multi-environment trials. Nevertheless, the efficiency indices are affected by factors such as genotype number, environment and trait correlation, and heritability. In this study, we simulated different scenarios varying the mentioned factors to evaluate the performance of the Factor-Analysis and Ideotype-Design-Based Index (FAI-BLUP), Multi-trait Genotype–Ideotype Distance Index (MGIDI), and Multi-Trait Stability Index (MTSI). All correlations were positive and constant within each scenario, while the ideotype sought genetic gains for traits in opposite directions. Simulations were conducted using AlphaSimR and FieldSimR, and indices were implemented via the metan package. Results showed that index efficiency was higher in scenarios with larger numbers of genotypes, low-to-moderate trait correlations, and moderate-to-high inter-environment correlations. However, strong correlations among traits, particularly when combined with high heritability, compromise selection index efficiency in scenarios with antagonistic trait objectives. Despite that, the MGIDI consistently outperformed the other indices across most scenarios. Therefore, we emphasize accounting for trait genetic architectures, genotype–trait correlations, and target environment correlations.

Agriculture doi: 10.3390/agriculture16091002

Authors: Jing Wang Ennan Zheng Tao Liu Zhe Xing Zhenjiang Si

Non-flooding irrigation is widely promoted as a carbon–water co-benefit strategy in paddy rice, but field-scale trials overlook return flow compensation within irrigation districts and therefore overstate water-saving potential. To reconcile this scale mismatch, we developed a semi-distributed multi-scale water balance model coupled with a carbon footprint and full-component blue–green–grey water footprint framework and applied it across field, district, and provincial scales in Heilongjiang Province—a leading cold-region japonica rice region in Northeast China—using the Qinglongshan Irrigation District on the Sanjiang Plain as the focal case, supported by two growing seasons of field observations and 35 years of provincial records. Under alternate wetting and drying, apparent field-level water savings of 50–60% converge to 33% after return flow correction, implying that field-based indicators overestimate savings by 40–50%. Carbon mitigation is decoupled from water volume: CH4 suppression dominates total abatement and is governed by drying frequency rather than water saved. At the provincial scale, the water footprint has shifted from grey- to blue-water dominance, suggesting that blue-water efficiency now represents a principal remaining lever for further cold-region carbon–water co-benefits. Two-season coverage and fixed parameter assumptions affect magnitudes but not directions. Water-saving irrigation in cold-region paddy systems should therefore be evaluated at the district scale where data permit, rather than relying solely on field-scale indicators.

Agriculture doi: 10.3390/agriculture16091000

Authors: Xinyu Chen Zenglu Shi Xuejun Zhang Jinshan Yan Shaoteng Ma Duijin Wang Jian Chen Yongliang Yu

Under dry sowing and wet emergence conditions in Xinjiang, cotton planting with extra-wide film mulching and sowing faced challenges including low soil moisture content and poor soil plasticity. These conditions resulted in inadequate film edge laying, seed exposure, and unstable sowing depth. This study focused on an extra-wide film mulch planter, conducting operational process analysis and parameter optimization experiments. The research first analyzed the soil layer structure required for a high-quality cotton seedbed, described the structural composition and working principle of the extra-wide film mulch planter, and examined the interaction between key components and soil during operation. The primary factors affecting machine performance were identified, and a soil-deflecting device was added to mitigate rapid soil backflow. A coupled MBD-DEM model was developed to simulate the operation of key components, and simulation experiments were conducted. The optimal parameter combination obtained through optimization was as follows: furrowing disc deflection angle of 11°, primary soil-covering disc deflection angle of 20°, operational speed of 3.5 km/h, longitudinal blade height of 16 mm, and spring stiffness of 14 N/mm. Simulation validation under these parameters yielded the following results: covering soil amount ranged from 3.22 kg/m to 3.67 kg/m, with a mean of 3.43 kg/m; seeding qualification rate ranged from 94.97% to 97.52%, with a mean of 96.3%; film hole length ranged from 43.14 mm to 46.86 mm, with a mean of 45.18 mm; and cotton seed sowing depth ranged from 29.51 mm to 31.82 mm, with a mean of 31.23 mm. These simulation results met the operational requirements for extra-wide film mulching and sowing. Field validation experiments were conducted using the optimal parameter combination. The results showed a mean soil-covering thickness of 35.1 mm, mean soil-covering width of 65.3 mm, mean film hole length of 45.7 mm, and mean cotton seed sowing depth of 29.1 mm, with coefficients of variation of 5.1%, 2.6%, 4.7%, and 5.8%, respectively. The field results were generally consistent with the simulation results, confirming the reliability of the simulation model and demonstrating improved operational performance of the extra-wide film mulch planter, making it more suitable for the dry sowing with wet emergence technique. Twenty days after sowing, the mean emergence rate reached 93.3% with a coefficient of variation of 1.0%, indicating stable emergence, which preliminarily validated the effectiveness of the constructed seedbed in promoting cotton growth.

Agriculture doi: 10.3390/agriculture16090998

Authors: Marcos Adrián Ruiz-Medina Águeda M. González-Rodríguez María José Grajal-Martín

Polyploidy is widely used in plant breeding to generate novel phenotypes and improve agronomic traits, often promoting organ enlargement through the so-called “gigas effect.” However, in mango (Mangifera indica L.), the effects of genome duplication on fruit quality are still poorly understood. This study evaluated the effects of polyploidy on fruit morphology and physicochemical traits by comparing diploid (2n) and autotetraploid (4n) genotypes of six polyembryonic cultivars grown under identical field conditions. Autotetraploids consistently produced larger and heavier fruits across all cultivars, with significant increases in length, width, thickness, and especially fruit weight, confirming a strong and uniform size-enhancing effect of genome duplication. In contrast, quality-related traits showed cultivar-specific responses. Fruit firmness was not significantly affected by ploidy level, while penetration hardness differed only in ‘Kensington Pride’. Total soluble solids decreased in autotetraploids of ‘Kensington Pride’ and ‘Gomera 1’, whereas titratable acidity increased in ‘Kensington Pride’ and ‘Mun’ autotetraploids. These results indicate that autopolyploidization consistently enhances fruit size in mango (e.g., fruit weight increased up to twofold in some cultivars); however, its effects on key quality traits such as soluble solids and acidity are cultivar-dependent, and should therefore be carefully considered in breeding programs.

Agriculture doi: 10.3390/agriculture16090999

Authors: Andy-Felix Mioara Carmen-Luiza Alina Liviu Constanța Mihai Diana

The transition to renewable energy is a central objective of the European Union’s energy and climate policies, yet adoption rates differ significantly across Member States. This study analyses the economic, structural, and energy determinants of renewable energy adoption in the EU-27 over the period 2008–2023, using panel data models with country and year fixed effects and clustered standard errors. The results indicate that the relationship between renewable energy and its main determinants is limited and heterogeneous across countries. Most explanatory variables do not exhibit consistent and statistically significant effects across model specifications. In particular, research and development expenditure does not show a robust impact, while GDP per capita is associated with negative coefficients in several specifications, suggesting the presence of structural constraints and path dependency. Energy-related variables also display weak and unstable relationships. The findings suggest that renewable energy adoption is shaped by context-specific and heterogeneous dynamics rather than by uniform drivers. The study contributes by highlighting the limited explanatory power of standard macroeconomic indicators and supports the need for differentiated policy approaches across Member States.

Agriculture doi: 10.3390/agriculture16090997

Authors: Sun Duan Zhang Zhu Li Zhou Liu Tai Jing Yu

Intensive monoculture exacerbates soil compaction and sodification in the West Liao River Plain. This study evaluated legacy effects of diversified 3-year rotations on sodic soil health (ESP > 15%, ECe < 4 dS m−1) during two subsequent maize seasons. Rotations incorporating salt-tolerant forages and deep-rooted crops (sugar beet–Echinochloa–sorghum and Echinochloa–tall fescue–silage corn) significantly reduced bulk density (8.6–13.1%) and exchangeable sodium percentage (up to 14.1 percentage points) relative to continuous monoculture. Treatments with maximum desalination (22.6% reduction) enhanced fungal α-diversity by 98.0%, while forage-dominated systems enriched Acidobacteriota by 35.2%, shifting bacterial communities toward oligotrophic dominance. Structural equation modeling confirmed that rotation effects on enzyme activity were mediated through reduced bulk density and ESP. These systems provide effective biological models for sustainable maize cultivation in sodic soils via synergistic physical-chemical-biological amelioration.

Agriculture doi: 10.3390/agriculture16090996

Authors: Jie Zhang Chenyao Yang Hailin Peng Xintong Wei Jiaqi Zou Shiyu Wang Zhaohong Lu Xianming Tan Feng Yang

The traditional methods of field-based phenotypic data collection for crop germplasm resources are often inefficient and highly subjective. As the foundation for breeding innovation, these resources require precise identification of phenotypic traits for effective evaluation and utilization. Therefore, efficient and standardized management of germplasm data is critical during the breeding process. To address this, we have developed an intelligent recognition and management system focused on the crop’s organ characteristics. The system consists of a web client for overall project management and data download, and a WeChat Mini Program for data collection and uploading. Both components are integrated with image analysis models. Using a soybean variety screening experiment as a case study, we have constructed multiple high-definition datasets for soybean phenotypic traits, and employed YOLOv11 series models for object detection, image classification, instance segmentation, and pose estimation to build analytical models for each of these traits. All models achieved a mean average precision (mAP@0.5) exceeding 94%, along with a top1_accuracy of 0.999. In practical evaluations, all models took between 0.71 and 3.03 s to make predictions for 100 images, achieving an accuracy rate of over 98%. This system delivers a comprehensive solution for field phenotypic identification of crop germplasm resources, substantially enhancing the efficiency and objectivity of data collection and analysis. It serves as a valuable decision-support tool for precision breeding and digital agriculture.

Agriculture doi: 10.3390/agriculture16090995

Authors: Andy A. Acosta-Monterrosa María Cristina Florián-Pérez Martha Elena Montoya-Vega Ivan David Lozada-Martinez

Agricultural performance is often interpreted through agronomic inputs and technological progress; however, the translation of knowledge into production depends on the structural environments in which food systems operate. This study examined the association between food-security-related publication activity and crop production across global income settings from 2000 to 2025, while testing whether governance, health-system, and financial indicators modify that association. A longitudinal ecological panel was constructed, integrating 61,158 Scopus-indexed peer-reviewed articles on food security and related dimensions of healthy food access and availability with 23 crop production indicators grouped into staple, horticultural, and commodity domains. Income-stratified regression models were followed by hierarchical mixed-effects models and moderator screening. In exploratory stratified models, 67 of 92 income-specific associations reached nominal significance; however, only 5 of those 67 associations (7.5%) remained statistically significant after multilevel modelling and false discovery rate correction. Robust associations were concentrated in selected staple and horticultural outcomes, whereas most commodity indicators lost significance after hierarchical adjustment. Structural moderators related to territorial control, corruption, healthy life expectancy, health researcher density, healthcare access and quality, and official development assistance shifted the conditional slopes linking publication activity to crop output. These findings do not support a uniform linear relationship between publication growth and production volume. Instead, they suggest that the alignment between research ecosystems and agricultural output is structurally conditioned and likely mediated by institutional capacity, health-system resilience, and implementation environments. The ecological design, the use of publication counts as an indirect proxy, and the reliance on production volume rather than yield or efficiency should be considered when interpreting these results.

Agriculture doi: 10.3390/agriculture16090993

Authors: Michael Aliyi Ame Wei Wei Gadisa Fayera Gemechu

Soil erosion and nutrient loss degrade the soil resource base and water quality in dryland agricultural landscapes, yet optimal design of vegetation buffers for soil conservation under intensifying rainfall remains poorly quantified, particularly for nutrient retention. This study is novel in integrating event-scale rainfall-simulation experiments, Bayesian hierarchical modelling, Causal Forest analysis, and WEPP simulations to quantify how the sequential addition of biocrusts and grasses to shrub buffers shifts density thresholds for runoff, soil loss, and nutrient export across varying rainfall intensities. Experiments were conducted across a continuous shrub-density gradient (0–11,429 plants ha−1) representing three configurations: shrub monoculture, shrub-biocrust, and shrub-biocrust-grass on agricultural hillslopes of the Chinese Loess Plateau. Runoff, soil loss, and exports of total nitrogen (TN) and total phosphorus (TP) were measured. Results demonstrate three main findings. First, multilayer shrub–biocrust–grass buffers exhibited lower soil loss than monocultures. Posterior estimates indicate reductions from approximately 3.8 t ha−1 at moderate monoculture density to below 1.0 t ha−1 at lower planting densities, with 94% of the highest-density intervals reflecting uncertainty in these estimates. Second, Causal Forest analysis reveals a functional separation of controls: rainfall intensity dominates soil loss (88% importance) and runoff (84%), whereas nutrient retention responds more strongly to buffer structure and density management. Third, WEPP simulations across rainfall intensities (50–180 mm h−1) and slopes (10–30%) identify an optimal multilayer buffer density of 3800–5700 plants ha−1, which delivers robust multifunctional benefits with 50–67% lower planting requirements than conventional high-density monocultures. These findings demonstrate that multilayer vegetation buffers enhance soil retention and reduce nitrogen and phosphorus losses from hillslopes, sustaining the soil resource base and protecting water quality in dryland agricultural landscapes. The integrated modelling framework provides transferable, evidence-based density recommendations for climate-resilient soil conservation in similar dryland regions.

Agriculture doi: 10.3390/agriculture16090994

Authors: Yan Ma Zhihao Zhao Shuangpeng Xie Xiaohu Jiang

The construction of soil surface microtopography not only effectively mitigates soil erosion, improves soil structure, and enhances soil ecological functions, but also significantly optimizes the seedbed environment for seedling emergence and crop growth. In this study, targeting the specific characteristics of red-yellow soils in Southern China, a quadrangular frustum-shaped soil surface microtopography processing device was designed and fabricated based on the 2BYG-230 rapeseed seeder. The motion trajectory and force distribution of the device were analyzed using the Discrete Element Method (DEM) software, EDEM, followed by three-factor and three-level orthogonal tests. The results indicated that the order of significance for factors affecting the microtopography formation effect was working load > working speed > microstructure height. Using the formation qualification rate as the evaluation index, the soil disturbance patterns were analyzed to determine the optimal combination of operating parameters: a working load of 260 N, a working speed of 0.34 m/s, and a microstructure height of 42 mm. Under these optimized conditions, the microtopography formation qualification rate reached 93.6%. Furthermore, the seedling emergence rate following the operation of the optimized device was 74.33%, representing a 4.96% increase compared to pre-optimization levels. The optimized processing device designed in this study markedly outperformed its predecessor, creating a soil surface microtopography more conducive to rapeseed growth while demonstrating substantial potential for water and soil conservation and ecological improvement. This research provides theoretical support for enhancing the ecological functions of Southern red-yellow soils and for the structural design of surface microtopography processing equipment.

Agriculture doi: 10.3390/agriculture16090992

Authors: Alberto Estalla Jennifer Alvarez Karina Eduardo Milagros Coaguila-Gonza Gabriela Barreto-Tarrillo Juan D. Rios-Mera Erick Saldaña

Cañihua (Chenopodium pallidicaule) is an underutilized Andean pseudocereal of strategic interest for sustainable agriculture in high-altitude, climate-constrained environments, where its tolerance to frost, drought, and saline soils positions it as a potential climate-resilient crop. Despite its high nutritional value and potential for functional food applications, its research landscape remains fragmented and unevenly developed across agronomic, nutritional, and technological dimensions. This study aimed to systematically and bibliometrically analyze the scientific literature on cañihua published between 1995 and 2025. A total of 104 documents indexed in the Scopus database were evaluated following the PRISMA 2020 approach, including analyses of publication trends, geographic distribution, collaboration networks, and thematic structures, together with a qualitative critical appraisal of the included evidence. Results indicate a marked increase in scientific output since 2006, with research predominantly concentrated in food science and technology and limited development in agronomy, clinical nutrition, and socio-economic domains. Thematic analysis reveals a strong focus on bioactive compounds, nutritional composition, and processing technologies, while clinical, socio-economic, and large-scale agricultural studies remain limited. Processing strategies such as germination, malting, and fermentation enhance nutrient bioavailability, reduce antinutritional factors, and improve sensory properties, supporting the incorporation of cañihua into functional and gluten-free foods at levels of up to 25%. Significant gaps persist in clinical validation, agronomic standardization, production scalability, genetic improvement, and integration across research domains. Overall, cañihua shows strong potential to contribute to sustainable Andean agriculture, food security, and functional food innovation, although further interdisciplinary and translational research linking agricultural production with nutritional and technological outcomes is required to realize its full applied potential.

Agriculture doi: 10.3390/agriculture16090991

Authors: Yulei Jiang Siqi Long Yuyang Duan Han Zhang Guolong Gao Jie Qiu Changxing Zhao

A two-year field experiment was conducted to clarify the regulatory effects of nitrogen (N), phosphorus (P), and potassium (K) combined with drip fertigation on the yield, yield components, and grain quality of winter wheat in lime concretion black soil (Calcaric Cambisols). The objective was to screen a sustainable fertilization model for coordinating high yield and quality in the Huang-Huai-Hai Plain. An L16(43) orthogonal design was adopted to investigate yield, protein content, wet gluten, test weight (TW), and grain hardness. Range analysis and ANOVA were used to evaluate factor effects and interactions. The results showed that N was the dominant factor affecting yield and quality (Rank 1), followed by K (Rank 2), while P showed the weakest effect. Compared to the control (N0P0K0), the optimized N–P–K combination increased grain yield by an average of 315.0% and enhanced grain crude protein by 55.3% over the two seasons. The optimal combination for maximum yield was N170P30K120 (kg/ha), which optimized the source–sink relationship by balancing spike density and 1000-grain weight. High N (220 kg/ha) combined with low P and high K achieved the best nutritional quality. The 3D response surface analysis confirmed significant synergistic interactions between N–K and N–P in promoting grain filling and protein synthesis. Rational NPK drip fertigation, particularly when synchronized with critical growth stages (jointing and grain filling), can simultaneously enhance grain yield and quality in this soil type. The optimized combination provides theoretical support and a robust fertilization strategy for green and efficient wheat production in the region.

Agriculture doi: 10.3390/agriculture16090989

Authors: Xiang Wang Jianyang He Yingmei Li Xiuling Peng Ke Yang Lijuan Wang Shundi Zhu Muxi Bai Yongxiang Zhou Naiming Zhang

Addressing the environmental challenges posed by the massive stockpiling of phosphogypsum (PG) has become a global concern, highlighting the urgency of developing large-scale, low-cost and resource-efficient utilization approaches for PG. This study was conducted in the rocky desertification areas of southwestern China, where land and water resources are scarce. Two land creation techniques—layered reconstruction (GA) and integrated construction (GB)—were adopted with modified PG to systematically investigate their impacts on soil properties and potato growth, yield and quality. The results showed that both techniques significantly improved soil conditions and enhanced potato yield and quality, with each presenting distinct characteristics in soil improvement. Specifically, the GA technique showed relatively better performance in soil nutrient enrichment, while the GB technique was more conducive to enhancing soil enzyme activity. Compared with the local red soil control, both techniques reduced heavy metal accumulation in potato tubers; however, Pb and Cd contents still exceeded national food safety limits, indicating potential food safety risks. In summary, land creation using modified PG can effectively increase arable land area, improve soil quality in rocky desertification regions, and simultaneously promote potato yield and quality. Nevertheless, as the current results are based on a single-season field trial, they cannot reflect the long-term patterns of heavy metal migration and accumulation. Therefore, for large-scale application, it is necessary to strengthen the monitoring of heavy metal levels in imported soil and long-term regional environmental impacts so as to ensure the quality and safety of agricultural products from reclaimed land.

Agriculture doi: 10.3390/agriculture16090990

Authors: Aušra Sinkevičienė Vaclovas Bogužas Vaida Steponavičienė Alfredas Sinkevičius Aušra Marcinkevičienė Marta Wyzińska Adam Kleofas Berbeć Rasa Kimbirauskienė

Agronomic practices can modify cereal grain chemical composition and processing performance. Long-term evidence linking agricultural management with functionality-related quality remains limited, especially in terms of combined tillage x crop residue management strategy. We evaluated the effects of long-term tillage simplifications and straw management on productivity and processing-relevant traits of winter wheat and spring barley in a split-plot field experiment (Lithuania). Straw was either removed (S0) or chopped and retained (S1), and six tillage systems were compared (conventional ploughing (CP), shallow ploughing (SP), shallow cultivation (SOW), stubble over winter, no-till with cover crops (NTC), and no-till without cover crops (NT)). The yield and starch content of winter wheat and spring barley groats increased with the addition of straw and the application of SOW, NTC, and NT systems. The hectolitre mass of winter wheat and spring barley grains increased with the addition and removal of straw using SP technology. The protein content and wet gluten content of winter wheat and spring barley grains decreased, while the starch content increased, with the addition and removal of straw using SC technology. In wheat, protein content showed weak separation among treatments, while wet gluten and Zeleny sedimentation displayed mostly directional trends (wet gluten–sedimentation correlation: r = 0.844 under S0 and r = 0.984 under S1). In terms of the tillage systems, it can be stated that in most cases, SP and NT increased grain yield and improved quality indicators, while SC and NTC technologies showed opposite results. Soil-function assessment (CEI, 10–25 cm) indicated substantially higher integrated soil functioning under conservation agriculture (e.g., SOW/NTC/NT: 5.28–5.70) than under conventional systems (CP: 3.23). The results support framing sustainable soil management for cereal functionality as a system package: residue retention enables the productivity benefits of reduced-tillage systems while maintaining key quality proxies.

Agriculture doi: 10.3390/agriculture16090988

Authors: Mei-Chen Zhou Wan-Ying Guo Zhi-Lai Zhan Li-Ping Kang Xiao-Lin Yang Tie-Gui Nan

Driven by increasing demand in the health and wellness industry, Traditional Chinese Medicine (TCM) agriculture currently faces significant challenges related to supply–demand imbalances and continuous cropping obstacles (CCOs). Intercropping and crop rotation can mitigate yield decline and environmental stress by improving microclimates and rhizosphere ecology. However, there is still a lack of bibliometric synthesis within this research area. To analyze research hotspots and evolutionary trends, 192 articles on the intercropping and crop rotation of medicinal plants were collected from the Web of Science Core Collection (1998–2025), including databases such as the Science Citation Index Expanded (SCIE), the Social Science Citation Index (SSCI) and the Conference Proceedings Citation Index (CPCI). The results revealed a steady increase in publication volume over time. China emerged as the most prolific contributor (93 articles), while the United States occupied a pivotal position in the global collaborative network, achieving a high centrality of 0.90. Research hotspots in this field have evolved from an early emphasis on plant yield and quality toward the mechanisms for alleviating CCOs, interspecific interactions within the rhizosphere microbiome, and the ecological management of soil health. Keyword bursts indicate that “microbial community” and “carbon” have emerged as the current research frontiers. To clarify the micro-mechanisms by which intercropping and crop rotation patterns mitigate or prevent CCOs, future research should prioritize the integration of multi-omics approaches to resolve molecular interactions within the “microbe–plant–soil” nexus. Key priorities include the development of functional Synthetic Microbial Communities (SynComs) and the establishment of comprehensive evaluation systems for ecological cultivation. Furthermore, aligning these models with global climate neutrality strategies would facilitate the balance between high-quality medicinal production and ecosystem stability.

Agriculture doi: 10.3390/agriculture16090987

Authors: Štefan Bojnec

Sustainable rural development rests on a careful balance between sustainable agriculture and the rural energy sector [...]

Agriculture doi: 10.3390/agriculture16090986

Authors: Ying Zhang Zhengda Li Zhulin Gao Xing Wang Yueyan Wang Zihao Zhao Yonghao Yang Rui Li Haitao Chen

Soil adhesion and abrasive wear severely degrade the performance and service life of soil-covering rollers in no-tillage seeders, particularly in the heavy clay black soil regions of Northeast China. To address the critical issues of soil adhesion and wear on soil-covering rollers used in no-tillage seeders within black soil regions, this study presents a surface engineering strategy that integrates a bionic micro-texture with a functional composite coating. Inspired by the crescent-shaped pits on the body surface of Procambarus clarkii, a bionic texture was designed and combined with a PTFE/PDMS/TiO2 composite coating. Key parameters were optimized using response surface methodology, yielding a TiO2 mass fraction of 6%, coating thickness of 40 μm, remaining texture depth of 50 μm, and texture spacing of 250 μm. A prototype was fabricated and evaluated through orthogonal field experiments in two distinct soil environments. In clay soil (15–25% moisture content), soil moisture and vertical load significantly influenced anti-adhesion performance, with recommended operating parameters of 600 N vertical load and a speed range of 10.8–14.4 km·h−1. In sandy soil (8–18% moisture content), vertical load and operating speed had significant effects on wear resistance, with optimal parameters identified as 600 N vertical load and 10.8 km·h−1. Verification tests confirmed stable low-adhesion and low-wear performance under varying moisture conditions. Compared to conventional and PTFE-coated rollers, the bionic roller reduced soil adhesion by 82.62% and 74.02%, respectively, in high-moisture clay soil, and reduced wear loss by 36.81% and 28.97%, respectively, in dry sandy soil. These results demonstrate that the synergistic “structure–material” design, which leverages stress dispersion and storage from the bionic texture alongside low surface energy and enhanced wear resistance from the composite coating, offers a promising approach for improving the durability and performance of soil-engaging agricultural components.

Agriculture doi: 10.3390/agriculture16090985

Authors: Antonio Raffo Irene Baiamonte Pasquale Buonocore Francesca Masciola Valentina Melini Elisabetta Moneta Nicoletta Nardo Marina Peparaio Stefania Ruggeri Eleonora Saggia Civitelli Pasquale Tripodi

The widespread practice of multiple harvests is known to significantly affect the quality of rocket leaves. Thus, ready-to-eat wild rocket (Diplotaxis tenuifolia L.) was produced under commercial conditions using leaves from five different varieties, harvested at both the first and the second cut, with a 21-day interval between cuts. Both the sensory and nutritional quality of rocket leaves were evaluated one day after packaging (beginning of shelf-life) and after an additional six days of storage at 6 °C (end of shelf-life). At the beginning of the shelf-life, first-cut leaves generally exhibited a more intense flavor, corresponding to a higher level of isothiocyanates, compared to second-cut leaves. At the end of shelf-life, first-cut leaves showed a greater susceptibility to off-flavor development, corresponding to the release of higher levels of sulfur compounds within the packages. First-cut leaves showed higher content of ascorbic acid and folate with respect of second-cut leaves, both at the beginning and the end of the shelf-life. The commonly held assumption that successive cuts yield leaves with more intense flavor compared to the first cut does not appear to be confirmed. It is likely that the differences in quality observed between leaves from the first and second cuts are not attributable solely to the cutting process or to the sequence of multiple harvest per se, but rather to significant variations in environmental conditions, particularly temperature and light, during the leaf growth period between the two harvests.

Agriculture doi: 10.3390/agriculture16090984

Authors: Xinyi Liu Yutian Zhang Qian Wang

Investigating the influence of women’s family status on farmers’ adoption of digital and intelligent production transformation holds significant value in bridging the gender gap in research on modern agricultural production transformation and in facilitating the digital and intelligent transformation of the agricultural sector. Drawing on survey data from Henan Province collected through a household survey conducted in July 2024 by the research team, which employed a combination of stratified and random sampling, and focusing on farmers’ adoption of plant protection drone technology, this paper employs the Triple-Hurdle model to examine the impact of women’s family status on farmers’ digital and intelligent production transformation decisions and the underlying mechanisms. The baseline regression results show that the improvement of women’s family status facilitates farmers’ digital and intelligent production transformation decisions. Specifically, it enhances farmers’ willingness to adopt digital and intelligent production transformation, promotes their adoption behavior of plant protection drone technology, and increases the degree of adoption of such technology. The mechanism analysis reveals that the improvement of women’s family status promotes farmers’ digital and intelligent production transformation decisions by increasing their satisfaction with the institutional environment. The heterogeneity analysis of household characteristics indicates that women’s family status has a greater facilitating effect on the willingness of farmers with lower female labor force participation and those with heavier child or elderly dependency burdens to undergo digital and intelligent production transformation. The heterogeneity analysis of village environmental characteristics shows that women’s family status has a greater facilitating effect on the willingness and behavior of farmers in villages with a larger number of technical personnel to undergo digital and intelligent production transformation. Additionally, it has a greater facilitating effect on the willingness of farmers in villages with a stronger culture of gender equality to undergo such transformation. Using plant protection drone adoption as an example, this paper provides preliminary evidence of the positive impact of women’s family status on the digital and intelligent transformation of agriculture. However, due to the inherent limitations of cross-sectional data, our exploration of the dynamic process of transformation remains inadequate. Therefore, future research is warranted to employ longitudinal panel data to further validate the findings of this study.

Agriculture doi: 10.3390/agriculture16090983

Authors: Jethro Zuwarimwe Obert Tada

The livestock sector underpins food security, employment, and rural livelihoods across the Southern African Development Community (SADC), contributing up to 50% of agricultural GDP and supporting more than 60% of rural households. Yet climate change poses escalating threats through heat stress, declining pasture productivity, water scarcity, and vector-borne diseases that compromise productivity and economic resilience. This review identifies and locates effective climate change mitigation strategies along the livestock value chain, spanning production, processing, transport, and consumption, to promote sustainable, low-emission, and inclusive growth in the SADC region. A broad review of 46 peer-reviewed and institutional sources (2000–2024) was undertaken, focusing on livestock-related mitigation within SADC and comparable agro-ecological systems. Strategies were thematically categorized by value-chain stage and assessed for their emission-reduction and livelihood-enhancement potential. Local strategies include genetic improvement for low-methane and heat-tolerant breeds, adaptive rangeland and feed management, renewable-energy adoption in processing, climate-resilient transport infrastructure, and consumer awareness of low-emission products. Evidence suggests potential GHG-emission reductions of 18–30%, coupled with productivity gains and improved smallholder incomes. Coordinated implementation through the SADC Regional Agricultural Investment Plan (2021–2030) and national policies can transform the livestock sector into a climate-resilient driver of inclusive growth. Further research should quantify the socioeconomic feasibility and scaling potential of these strategies across production systems. Successful integration of climate change mitigation imperatives must be tailored to local biophysical conditions (e.g., rainfall, soil type) and socioeconomic contexts (e.g., market access, cultural practices).

Agriculture doi: 10.3390/agriculture16090981

Authors: Kangxu Zhang Mengjiao Li Huifang Wang Jianguo Liu

Increasing planting density is a common strategy to raise soybean yield, yet it often intensifies light competition within the canopy, leading to diminishing returns at high densities. Optimizing row spacing to improve canopy light distribution and light use efficiency is therefore key to increasing yield under dense planting. This study examined the combined effects of planting density and row spacing on canopy light interception, distribution dynamics, and yield in a drip-irrigated soybean system. A two-year field experiment (2024–2025) was conducted in Shihezi, Xinjiang, using three density levels (D1: 210,000; D2: 330,000; D3: 450,000 plants ha−1) and two row spacing patterns (RS1: alternating wide–narrow rows of 20 + 55 cm; RS2: uniform 38 cm rows). Results demonstrated that plant density establishes the baseline for yield, while row spacing modulates light utilization and unlocks yield potential under high-density conditions. The RS1 treatment increased SPAD values in upper leaves by 6.06% at the R6 growth stage compared to the RS2 treatment. At the R5 stage, the RS1 treatment increased radiation use efficiency (RUE) by an average of 6.44%. This planting pattern alleviated photosynthetic decline in dense canopies and conferred a distinct yield advantage. The highest yield was achieved under the D2 treatment, which was 8.44% and 6.71% higher than that under the D1 and D3 treatments, respectively. In conclusion, integrating moderate plant density with optimized wide–narrow row spacing improves canopy light capture and utilization, synergistically enhancing yield and resource use efficiency. This approach offers a practical strategy to overcome the yield plateau in high-density soybean production systems.

Agriculture doi: 10.3390/agriculture16090982

Authors: Carlos Andrés Trujillo-Salazar Gerard Olivar-Tost Deissy Milena Sotelo-Castelblanco

The coffee berry borer (Hypothenemus hampei) is the primary pest of coffee crops worldwide. Sustainable management strategies increasingly rely on the integration of biological control and interventions activated by population thresholds. In this work, a comparative framework based on dynamical systems is presented, integrating three complementary mathematical models to analyze different management strategies for the coffee berry borer. First, a biologically structured three-dimensional model describes the interaction between adult and immature borers and predatory ants. Second, a two-dimensional formulation allows the maximum per capita consumption rate of the predator to be studied as a bifurcation parameter, identifying critical parameter values that delimit regions of coexistence or effective pest control. Finally, a piecewise-smooth dynamical system incorporates ethological control activated when infestation exceeds a predefined threshold, whose effectiveness depends on the capture intensity associated with the traps. Using stability theory, bifurcation analysis, and techniques from piecewise-smooth dynamical systems, parametric regions associated with persistence, coexistence, or significant pest reduction are characterized. The results show that biological control alone may be insufficient if a predation threshold is not exceeded, whereas its combination with early threshold-based interventions considerably enlarges the dynamical regions favorable to producers. This study provides a dynamical interpretation of the agricultural concept of intervention threshold and offers a quantitative framework to strengthen integrated management and the sustainability of coffee production.

Agriculture doi: 10.3390/agriculture16090980

Authors: Norbey D. Muñoz Julio Barón-Velandia Sebastian-Camilo Vanegas-Ayala

Colombian transitory crop production exhibits marked structural heterogeneity across department–crop combinations, yet empirical characterizations of productive scale at the subnational level remain scarce. This study presents a descriptive analysis and clustering-based productive scale segmentation of Colombian transitory crops at the departmental level for the period 2007–2024. Data from the Evaluaciones Agropecuarias Municipales(EVA) were processed through a structured CRISP-DM pipeline comprising preprocessing of 347,141 records, departmental aggregation, and engineering of five clustering features: average production, average planted area, number of active periods, and temporal and spatial Herfindahl–Hirschman indices. K-Means clustering (k=3)was applied to a final dataset of 490 department–crop pairs and validated based on a global silhouette coefficient of 0.888. The segmentation reveals a markedly asymmetric productive structure: 93.7% small scale (459 pairs), 5.3% medium scale (26 pairs), and 1.0% large scale (5 pairs), with natural breakpoints at approximately 35,386 t and 275,959 t. Large-scale production is concentrated in papa (Cundinamarca, Boyacá, Nariño) and arroz (Casanare, Tolima). Clustering demonstrated quantitative superiority over quartile-based classification, reducing the within-group coefficient of variation from 223.9% to 30.6% for the upper segment. The methodology is replicable across national agricultural statistics systems, and the processed dataset is publicly available under CC BY 4.0.

Agriculture doi: 10.3390/agriculture16090979

Authors: Yufei Lin Jie Wang Li Tian Hao Liang Xiaping Fu Chuanyu Wu

To explore robotic peach picking in different modes, this study examined the effects of various peach picking modes on harvesting force and time. A finite element model of peach harvesting structure was established, and harvesting experiment parameters were based on the Box–Behnken design. Harvesting was simulated to collect response time and force data. Subsequently, the optimal harvesting rate under different picking modes was determined. Different picking modes were tested by simulating identical fruit harvesting in the laboratory at the optimal harvesting speed to determine the peak harvesting force and duration. The Bend mode had the lowest picking pressure and the shortest average picking time at 0.7 MPa and 4.2 s, respectively. The Pull and Twist modes had similar pressures and picking times at 1.2 and 1.1 MPa and 5.2 and 5.6 s, respectively. Harvesting in the orchard allowed for harvesting force and duration measurement under different picking modes. The differences in picking pressure and time among the three picking modes increased compared with those of simulated picking, with specific patterns being observed. Picking pressure appeared at P1max, and differences in picking time were prevalent during separation. This study offers valuable insights for future improvements in harvesting modes and efficiency enhancement.

Agriculture doi: 10.3390/agriculture16090978

Authors: Monika Vidak Dunja Blažević Tomislav Javornik Klaudija Carović-Stanko

The increasing volume of plant waste generated by the agro-food industry presents significant environmental and economic challenges. This review synthesizes peer-reviewed literature on the valorization of fruit and vegetable by-products as seed priming agents, focusing on extraction approaches, bioactive compounds, physiological mechanisms, and practical limitations. Seed priming with plant extracts derived from agro-food by-products has emerged as a sustainable approach to enhance seed germination, seedling vigour, and tolerance to abiotic stresses. Recent findings on the composition of bioactive compounds in plant waste, extraction techniques, and the physiological and biochemical effects of these extracts on seeds and seedlings are reviewed. Phenolics, flavonoids, and phytohormones present in these extracts activate antioxidant enzymes and promote secondary metabolite accumulation, mitigating oxidative damage and improving seedling performance. Critical analysis highlights the potential of plant-waste-based extracts for sustainable agriculture and identifies research gaps to optimize their practical application.

Agriculture doi: 10.3390/agriculture16090977

Authors: Addis Getu Mastewal Birhan Hailu Dadi Solomon Abegaz Malede Birhan Nega Berhane

This study was conducted in Northwest Ethiopia in 2025 to estimate genetic parameters for dairy cattle hybrids under a group-based mass selection scheme. The objective was to investigate lactation milk yield (MY), lactation length (LL), and key fitness traits across varying breed compositions, aligned with suitable agro-ecological zones and milkshed systems. The findings may then serve as a framework to develop economically efficient and sustainable dairy genotypes tailored to the region. Data were collected from 355 dairy households using semi-structured questionnaires and monthly monitoring of MY. A mass selection scheme was applied to evaluate the productive and reproductive performance of Holstein-Friesian (HF) and Jersey hybrids across varying levels of exotic breed compositions. To identify superior genotypes, a total merit index (TMI) was developed, utilizing economic weights of +0.20 for production traits and −0.12 for reproductive traits. General liner model (GLM) analyses were performed to evaluate the performance of different breeds and exotic breed composition. Realized genetic parameters including genetic correlations (rg) as an indicator of pleiotropy, genetic gain (GG) per trait, and aggregate genetic response (AGG) were estimated for each group using specialized procedures in R software. Breed type (stratified by exotic breed composition), agro-ecology zone, and milkshed system were defined as the main and sub-fixed effects. The genetic contribution to the performance of hybrids indicated that the Holstein-Friesian (HF) hybrid baseline scheme achieved significantly higher efficiency, with an aggregate genetic gain) (AGG) of 155.50, compared with 136.03 for the Jersey hybrid schemes. Specifically, the >75% HF hybrid group exhibited the highest predicted AGG (183.00), a result primarily underpinned by significant gains in MY (182.53 L) and extended LL (0.28 months). This indicated that higher exotic breed composition in HF crosses maximizes the genetic gain when selection is weighted toward productivity. Conversely, the 62.5% Jersey hybrid exhibited the lowest AGG (110.38) and GG for MY (109.86 L), indicating that intermediate Jersey breed compositions may be suboptimal under the studied conditions. Analysis of interaction effects revealed environment-specific superiorities: in the Bahir Dar midland milkshed, the >75% HF hybrids achieved the highest genetic gains in MY (182.53 L) and a superior AGG (181.34). In contrast, within the Gondar midland milkshed, >75% Jersey hybrids reached the highest overall AGG (177.11), with a corresponding GG for MY of 178.75 L per lactation. The observed variance in MY (δ2 = 362.44) indicated significant potential for genetic improvement through group-based selection. Pleiotropy was identified between MY and LL (rg = 0.14), whereas an antagonistic trade-off was observed between maturity and conception efficiency (rg = −0.34). The consistent upward trend in the performance of hybrids as breed composition increased from 50% to >75% across both main and sub-effects suggests that these genotypes are suited to the environment. In conclusion, single- and multiple-trait predictions based solely on breed and breed comparisons were suboptimal; instead, selection strategies incorporating genotype-by-environment (G × E) interactions offered the most effective alternative for regional dairy selection alternatives.

Agriculture doi: 10.3390/agriculture16090976

Authors: Tapelo Blessing Nkambule Isaac Azikiwe Agholor

Conservation agriculture (CA) is widely promoted as a climate-smart approach to improve productivity and resilience, especially among small-scale farmers who face socioeconomic and climate-related risks that threaten their livelihoods. However, evidence linking CA adoption to household food-security outcomes in South Africa remains limited. This study examines patterns and determinants of CA adoption and assesses its implications for household food security among small-scale farmers in three municipalities of Mpumalanga Province. A quantitative cross-sectional survey was conducted among 391 farmers selected through stratified random sampling. Data were collected using a structured questionnaire and analyzed using descriptive statistics, chi-square tests, Kruskal–Wallis tests, and binary logistic regression. Results show that CA adoption was widespread but largely partial, with most farmers adopting one or two principles rather than the full CA package. Access to CA-related resources and information, household size, livelihood strategy, farm income, and farm size significantly influenced adoption. Higher adoption intensity was consistently associated with improved food-security outcomes, including increased production, lower food-insecurity severity, greater crop diversification, higher likelihood of year-round production, and increased market participation. The study concludes that conservation agriculture can contribute positively to multiple dimensions of household food security when adopted as an integrated system, but partial adoption yields limited benefits. Targeted extension support, improved access to resources, and context-specific interventions are required to enhance sustained and holistic CA adoption among small-scale farmers.

Agriculture doi: 10.3390/agriculture16090975

Authors: Wang Liu Yang Liu Xu Hou Chen

Selecting an appropriate disc coulter is crucial for reducing the power consumption of no-till seeders, preventing straw from being pressed into seed furrows, improving the soil penetration performance of the disc coulter, and thus minimizing the weight of no-till seeders. This study utilized the quadratic regression orthogonal rotation central composite approach. With the application of EDEM and RecurDyn software, a virtual simulation model of the interaction between a toothed disc coulter and soil was developed. The angle of front serration δ, the angle of rear serration θ, and the number of serrations n were taken as experimental factors. The draft Fv and penetration resistance FN were selected as performance evaluation indicators for parameter combination optimization simulation tests. The results indicated that δ, θ, and n have significant influences on Fv and FN (p < 0.05). When the optimized parameter combinations δ, θ, and n were respectively determined as 16°, 39.1°, and 13, both Fv and FN reached their minimum values. A comparative experimental study was conducted with the optimized toothed disc coulter and six existing disc coulters; under the working conditions of 14.4 km·h−1, both the draft and penetration resistance of the toothed disc coulter are minimized. The draft was 227.5 ± 8.9 N and the penetration resistance was 415.9 ± 5.3 N. Meanwhile, the toothed disc coulter had the highest ratio of soil disturbance area to draft, indicating better soil loosening effects.

Agriculture doi: 10.3390/agriculture16090974

Authors: Jie Huang Zhiyong Li

Food security remains one of the core issues for the sustainable development of human society, and with the continuous growth of the global population, accelerated urbanization, [...]

Agriculture doi: 10.3390/agriculture16090973

Authors: Stamatis Chrysanthopoulos João Coutinho Mariana Mota Ana Carla Silva Luisa Brito David Fangueiro

This study aimed to evaluate the leaching of nutrients and pathogens following the surface application of pH-modified slurry on sandy soil. Three slurry pH modification strategies—mineral and biological acidification (pH 5) and alkalinization (pH 9.5)—were tested using mineral acids or bases, paper-industry by-products, or combinations of additives. We hypothesized that: (i) acidification increases nitrogen (N) and phosphorus (P) leaching through nutrient solubilization, and (ii) effective sanitization reduces the risk of pathogen leaching. A 24-day column leaching experiment was conducted with slurry applied at 240 kg N ha−1 and four weekly irrigation events. Results indicated that nitrate (NO3−) leaching accounted for less than 15% of the total nitrogen applied; however, acidified slurry significantly increased ammonium (NH4+) leaching by 72%. The combination of H2SO4 with sucrose reduced NH4+ and NO3− leaching, although P leaching exceeded 35% of the total P applied. Sulphur (S) concentrations in leachates ranged from 42.3 to 112.8 mg S kg−1 soil, particularly in treatments involving H2SO4 or SO42−—rich additives such as spent acid. Faecal coliform leaching declined throughout the study, with acidified slurry consistently maintaining levels below the threshold for irrigation water (<100 MPN/100 mL). Regarding nutrient leaching, pH-modified slurry may present a higher risk of N, P and S leaching compared to untreated slurry, which could also be interpreted as an increase in plant nutrient availability.

Agriculture doi: 10.3390/agriculture16090972

Authors: Meiling Liu Zhihui Wang Ruiqing Zhu Huichun Xie Yan Lu

Continuous maize cropping is often associated with yield decline and soil degradation, yet the temporal responses of rhizosphere bacterial communities to prolonged monocropping remain incompletely understood. Here, we used a continuous maize cropping chronosequence representing 0, 1, 2, 3, 6, 7, and 8 years of cropping to evaluate soil physicochemical properties, maize yield, rhizosphere bacterial community composition, and BugBase-predicted phenotypes using 16S rRNA gene amplicon sequencing. Available potassium declined progressively with cropping duration, whereas alkali-hydrolyzable nitrogen (AN) increased and available phosphorus (AP) changed nonlinearly. Soil pH declined in the later stages of the chronosequence. Maize yield declined progressively with prolonged cropping, with reduction of 46–55% in the 6–8 years treatments relative to earlier within-plot peaks. Bacterial alpha diversity changed nonlinearly, with Shannon diversity peaking at C3, declining at C6, and partially recovering at C7–C8. Because years 4 and 5 were not sampled, the exact shape of the transition between C3 and C6 remains unknown. Community composition also shifted with cropping duration, including a relative decline in Proteobacteria and enrichment of Actinobacteria in the longer-duration treatments. At the genus level, Arthrobacter increased in the later stages of the chronosequence. Redundancy analysis indicated broad associations between community composition and soil variables, although the phylum-level model was only marginally significant. BugBase-predicted phenotypes also varied across treatments, but these functional inferences should be interpreted cautiously because they were derived from 16S-based predictions. Overall, our findings support nonlinear changes in rhizosphere bacterial communities along the continuous maize cropping chronosequence and suggest an unresolved transition between C3 and C6, followed by partial stabilization at later stages. However, due to the missing data for years 4–5 and the inherent limitations of the chronosequence design, the existence and timing of a proposed mid-term transition remain tentative. These findings highlight the need for complete annual sampling to resolve successional trajectories.

Agriculture doi: 10.3390/agriculture16090971

Authors: Cristiana Bernardi Rankrape Danillo C. G. Leite Karla L. Gage Ahmad M. Fakhoury

Waterhemp (Amaranthus tuberculatus (Moq.) J. D. Sauer) is one of the most competitive and herbicide-resistant weed species in soybean cropping systems across North America. While its competitive and adaptive traits are well-documented, its role as an alternative host for plant pathogens remains underexplored. This review synthesizes current knowledge on fungal, bacterial, viral, and nematode pathogens that infect waterhemp and examines the ecological and management implications of these interactions. We discuss how waterhemp may serve as a reservoir for inoculum, potentially influencing disease dynamics in soybean under changing climate conditions. Furthermore, we assess the potential of host-specific pathogens as biological control agents within the integrated weed management (IWM) approach. Despite promising experimental results, several barriers limit large-scale adoption of bioherbicides, including environmental sensitivity, narrow host specificity, challenges in mass production, and regulatory constraints. Understanding weed–pathogen interactions could inform dual-purpose strategies that reduce both weed pressure and disease risk in soybean systems. Further research is needed to optimize biocontrol scalability, assess climate-driven epidemiological shifts, and develop robust integrated weed and disease management approaches.

Agriculture doi: 10.3390/agriculture16090970

Authors: Zilin Fan Xiaxue Weng Lisiren Cao Jinyao Lin

Protecting high-standard farmland is pivotal for sustainable land utilization and long-term regional food security. However, delineating high-standard farmland in metropolitan areas often neglects the influences of future urban expansion and farmland morphology, critical factors for enhancing farmland productivity. To address this, this study established a systematic evaluation framework for high-standard farmland delineation. It employed the patch-generating land use simulation model to forecast the probability of future urban expansion while employing the analytic hierarchy process and entropy weight method to calculate combined weights for evaluating farmland suitability. An ant colony optimization algorithm was implemented to improve farmland suitability and morphological compactness, thereby scientifically delineating high-standard farmland. Results from Guangzhou reveal that farmland area decreased between 2000 and 2020, primarily driven by urban expansion. The delineated high-standard farmland covers 682.18 km2, achieving dual optimization of farmland suitability and compactness. The results are predominantly located within permanent basic farmland and grain production functional zones. This finding aligns with previous studies and existing plans, demonstrating the methodology’s superiority. Furthermore, this study categorizes Guangzhou’s high-standard farmland into four grades and proposes targeted policy recommendations. In summary, this study presents a new and scientific approach for high-standard farmland delineation, offering valuable policy support for sustainable farmland management.

Agriculture doi: 10.3390/agriculture16090969

Authors: Yurii V. Kornilev Stephan Burgstaller Janette Siebert Magdalena Spießberger Dmytro Monoshyn Yoko Muraoka Werner Kammel Florian Glaser Werner Weißmair Ute Nüsken Silke Schweiger Johann G. Zaller Lukas Landler

Pesticides pose risks to human health and the environment. Monitoring schemes often exclude small sites with fluctuating water levels, inhabited by many species, including amphibians. We sampled for pesticides and their metabolites in 68 amphibian spawning waters in Austria. We analyzed the number of pesticides and concentrations in relation to the surrounding land use. We tested for 165 pesticides and metabolites and found 54; 46% were herbicides. The median total pesticide concentration per site was 0.097 µg/L (range: 0–20.419 µg/L). Pesticides found were generally of lower toxicity. We calculated the pesticide toxicity for aquatic invertebrates, fish, birds, and mammals, as proxies for amphibians and the overall ecosystems. Arable land was associated with pesticide number, concentration and toxicity according to the Boruta model selection. However, due to highly variable concentrations (and therefore also variable toxicity) only pesticide number showed significances in a generalized linear model. In this model arable land was positively associated with the number of pesticides detected, while the proportion of grassland, scrubs, artificial surfaces and tree cover had negative effects according to the linear model. Our results highlight (i) a widespread contamination of small temporary water bodies, (ii) the presence of multiple pesticide residues (cocktails), commonly more harmful than single pesticides, at amphibian spawning waters. These results provide a basis for future studies investigating the effects of common pesticide combinations in controlled settings using realistic scenarios and enable better assessment of the potential risks to wildlife.

Agriculture doi: 10.3390/agriculture16090968

Authors: Yufei Dong Congying Han Shuai Pan Xinli Lin Lingyuan Chen Yinlong Zhang Haiying Lu

Microplastics (MPs) are emerging pollutants that affect soil–microbe interactions in paddy ecosystems. Periphytic biofilms (PBs) are complex microbial consortia that ubiquitously distribute at the soil–water interface of paddy ecosystems, playing essential roles in nutrient cycling and pollutant migration. However, whether MPs affect the community composition of PBs remains largely unknown. This microcosm study investigated the effects of three types of MPs (polyacrylonitrile, PAN; polyethylene, PE; and polyethylene terephthalate, PET) on the community characteristics of PBs via high-throughput sequencing (16S/18S rRNA) technology. Results showed that the addition of all MPs significantly increased the biomass and chlorophyll-a content of PBs, with PAN inducing the maximum increase (by 331.9% and 128.6%). However, all MPs had no significant effect on the PB α-diversity of bacterial and eukaryotic communities (p > 0.05). As for PB composition, PAN and PET increased the relative abundance of Cyanobacteria, Proteobacteria and Holozoa, PE increased that of Cyanobacteria, Bacteroidota and Blastocladiomycota, and all MPs decreased the relative abundance of Chloroflexi, Actinobacteriota and Basidiomycota. Furthermore, PET decreased the predicted functional potential of natural polymer degradation (cellulolysis, ligninolysis, xylanolysis, ureolysis), nitrogen fixation and nitrate ammonification, while PE increased predicted potential for plastic degradation, nitrate reduction and denitrification. Co-occurrence network analysis suggested that the PE network showed higher connectivity and lower modularity, while the PAN network showed higher modularity. This study advances our understanding of soil MPs–microbe interactions under high-concentration conditions. It also suggests that PB community characteristics may serve as potential bioindicators for soil MP pollution.

Agriculture doi: 10.3390/agriculture16090966

Authors: Gessica Altieri Nicola Gargano Daniele Curcio Antonio Tedesco Giuseppe Celano

Compost-derived products are increasingly used to enhance soil biological activity and plant performance in perennial fruit systems, but the effects of compost tea (CT) in kiwifruit orchards remain unexplored. This study assessed root-zone applications of aerated CT from 2023 to 2025 on the yield and fruit quality of gold kiwifruit in a commercial pergola-trained orchard. Two treatments were compared: weekly CT fertigation during summer and an untreated control (Ctrl). Yield, fruit number, mean fruit weight, and fruit quality—hue angle (H°), firmness, soluble solids content (SSC), and dry matter were evaluated annually. The CT application did not significantly affect total yield or fruit number over three seasons. However, it increased the mean fruit weight and shifted fruit distribution toward larger size classes. Fruit quality responses varied: CT-treated fruits initially showed lower firmness and SSC, but in the final year, firmness and SSC matched controls. Dry matter content was higher in CT fruits (18.87%) than in controls (16.71%). These results indicate that during the early to mid-bearing phase, CT promotes fruit growth toward larger sizes and enhances dry matter accumulation. Gradual benefits appeared after three annual applications, suggesting CT is a promising tool for medium- to long-term soil and rhizosphere management in kiwifruit.

Agriculture doi: 10.3390/agriculture16090967

Authors: Min Zhao Zilian Li Meihua Ye Xuefang Huang Nana Li Kexing Hao Gaimei Liang

Increasing total soil porosity and optimizing pore distribution improve soil water-holding capacity, thereby alleviating drought impacts on crop yields in semi-arid regions. A three year split-plot field experiment was conducted, with organic fertilizer (sheep manure) rates as main plots and water-retaining agent (WRA) rates as subplots. Four organic fertilizer (0, 45, 60, and 75 Mg hm−2) and four WRA rates (0, 0.3, 0.6, and 0.9 Mg hm−2) were set, resulting in 16 combined treatments. Undisturbed soil samples were collected to analyze pore distribution and water availability using the soil water retention curve. The results showed significant variations in ameliorative effects with soil depth. Individual applications of either organic fertilizer or WRA significantly improved topsoil pore distribution and water availability but exerted negative effects on the subsoil. Combined application enhanced both soil layers, with a stronger synergistic effect in the subsoil. The combination of 45 Mg ha−2 organic fertilizer + 0.9 Mg ha−2 WRA achieved optimal soil improvement in the 0–20 cm layer, increasing aeration porosity by 21.89% compared to organic fertilizer alone; this improvement led to 14.99% and 15.65% increases in plant available water (PAW) and readily available water (RAW), respectively. For the 20–40 cm layer, the combination of 60 Mg ha−2 organic fertilizer + 0.9 Mg ha−2 WRA was optimal, increasing total, aeration, and capillary porosity by 24.18%, 183.50%, and 56.73%, respectively, compared to organic fertilizer alone. Consequently, subsoil water availability was enhanced, resulting in 57.53% and 61.18% higher PAW and RAW than the control without WRA. These findings highlight the necessity of layer-specific regulation and differentiated management. The optimal combinations (OF45+W0.9 for 0–20 cm and OF60+W0.9 for 20–40 cm) effectively optimize pore distribution and increase water availability through the complementary synergistic effects of organic fertilizer and WRA. Consequently, this strategy alleviates drought stress on crop yields in semi-arid regions.

Agriculture doi: 10.3390/agriculture16090965

Authors: Hao Liang Jinwu Li Qiang Zhang Ziyu Liu Beihan Han Xiongwei Lou Nan Wang Yufei Lin

Near-infrared spectroscopy (NIRS) offers significant advantages for the rapid and non-destructive detection of nutrients in livestock manure slurry. However, conventional models based only on spectral features often show limited robustness under cross-seasonal and multi-farm conditions due to differences in farm source, treatment stage, and complex spatiotemporal background. To improve the accuracy and applicability of total nitrogen (TN) prediction in dairy farm manure slurry, this study used 747 samples collected from 36 large-scale dairy farms in Tianjin, China, covering 24 treatment stages and four seasons, together with sample-contextual information such as farm name, longitude, latitude, and season. Competitive adaptive reweighted sampling (CARS) was applied to select key wavelengths from near-infrared spectra. On this basis, a multi-branch gated fusion deep learning model, MultiScaleSE-GatedCNN, was developed to integrate spectral and sample-contextual information. The model combines multi-scale one-dimensional convolution for spectral feature extraction, separate encoding branches for numerical and categorical inputs, and a gated fusion unit for adaptive weighting of different information sources. Results showed that partial least squares regression remained a strong baseline under single-source spectral conditions, but the proposed deep learning fusion model achieved superior predictive performance after introducing sample-contextual information. Ablation experiments demonstrated that different combinations of sample-contextual information contributed differently to model performance, and the combination of spectra, farm name, longitude, and season yielded the best results. Under this optimal input combination, MultiScaleSE-GatedCNN achieved a test-set R2 of 0.905, an RMSEP of 367.389, and an RPD of 3.242. These results demonstrate that integrating NIRS with sample-contextual information can effectively improve the accuracy and robustness of TN prediction in dairy farm manure slurry.

Agriculture doi: 10.3390/agriculture16090964

Authors: Lixin Zhang Jiao Wang Congling Zhu Jiani Li Qun Yang Minjie Fu Yongjun Wang

Straw return improves paddy soil quality and nutrient cycling, but its combined effects with nitrogen application on extracellular enzyme activities and greenhouse gas emissions in cold-region paddies remain unclear. A field experiment was conducted in Northeast China under full straw return (8.8 t ha−1) with six nitrogen rates (0, 110, 120, 130, 140, and 150 kg ha−1); conventional nitrogen application without straw return (130 kg ha−1) was the control (CK), while N0 distinguished straw input from nitrogen effects. Soil properties, extracellular enzyme activities, and CO2, CH4, and N2O emissions were measured 20, 50, 80, 110, and 140 days after straw return. At 140 days, compared with CK, straw return increased the NH4+-N and organic matter in the 0–15 cm soil layer by 41.75% and 28.69%, respectively, and reduced pH by 4.34%. Under N110–N150, straw return enhanced the carbon- and nitrogen-acquiring enzymes and oxidative enzymes by 15.88–162.23%. In particular, β-glucosidase, phenol oxidase, and peroxidase activities were significantly higher under N130–N140 than under CK. Compared with N150, N130–N140 maintained organic matter turnover without further increasing greenhouse gas emissions. Overall, under full straw incorporation in the Mollisol paddies of cool Northeast China, N130–N140 sustained high yield while balancing nutrient cycling, enzyme activity, and greenhouse gas mitigation.

Agriculture doi: 10.3390/agriculture16090963

Authors: Sagadat Turebayeva Aigul Zhapparova Dossymbek Sydyk Elmira Saljnikov

Rainfed wheat (Triticum aestivum L.) production in semi-arid regions is strongly influenced by precipitation variability, soil water availability, and crop management practices. This study evaluated the effects of nutrient management under uniform weed control on soil water dynamics, weed density, and grain yield of winter wheat grown under rainfed no-till conditions in southern Kazakhstan. Field experiments were conducted during the 2018–2021 growing seasons on gray soils characterized by low organic matter and limited nitrogen and phosphorus availability. Eight fertilization treatments, including phosphorus and nitrogen combinations and a micronutrient treatment, were arranged in a randomized complete block design. Soil moisture reserves, weed density, and grain yield were analyzed in relation to precipitation variability. Productive soil moisture reserves in the 0–100 cm layer at tillering (BBCH 21–25) ranged from 155 to 178.8 mm and were closely associated with overwinter precipitation. Balanced nitrogen–phosphorus fertilization reduced weed density from 38 plants m−2 in the control to 16 plants m−2 under the P45N70 treatment. Yield stability varied across dry, normal, and wet years, reflecting the influence of precipitation conditions on crop performance. Overall, the results suggest balanced fertilization in no-till systems contributes to improved resource use and more stable wheat production under variable precipitation.

Agriculture doi: 10.3390/agriculture16090962

Authors: Andi Cao Xingyi Zuo Haoyu Wen Houjian Li

As China advances high-quality agricultural development, promoting green production among farmers has become an important policy priority. Using survey data from 1787 rice farmers in seven major rice-producing provinces in southern China, this study examines whether enterprise-led contract farming can promote farmers’ green production behavior. Green production behavior is measured by a composite index based on six practices, including green control technology, soil testing and formulated fertilization, organic fertilizer substitution, water-saving irrigation, agricultural film recycling, and straw return. Empirical analysis results show that enterprise-led contract farming can significantly promote farmers’ green production behavior. Further analysis suggests that food safety certification, planting technology training, and lower perceived price volatility are important pathways through which contract farming is linked to green production practices. The promoting effect is weaker among older farmers, stronger for farmers cultivating land with medium soil fertility, and more pronounced among small-scale rice farmers. These findings highlight the role of enterprise-led contract farming in promoting farmers’ green production and offer policy implications for encouraging wider participation in green production practices.

Agriculture doi: 10.3390/agriculture16090961

Authors: Jiajia Liu Senqiu Chang Qing Li Zhenyu Gao

Nitrogen is a critical macronutrient for plants, playing a central role in the synthesis of proteins, amino acids, and nucleic acids. To enhance nitrogen use efficiency (NUE) and ensure sustainable agricultural production, identification of nitrogen-efficient genes and application of molecular breeding techniques are crucial for developing high-NUE rice germplasm. The nitrogen signaling pathway exhibits close crosstalk with phytohormones, including auxins (IAA), gibberellins (GAs), abscisic acid (ABA), cytokinins (CTKs), brassinosteroids (BRs), and strigolactones (SLs). This review systematically summarizes the molecular mechanisms underlying crosstalk between nitrogen and phytohormones, focusing on the physiological and molecular basis underlying their synergistic regulation of root development and NUE in rice, and outlines challenges for the complicated research field and prospective directions in future.

Agriculture doi: 10.3390/agriculture16090960

Authors: Li Chen Jie Chai Xinhua Hou Longchao Zhang Jinyong Wang Lixian Wang Ligang Wang

Consumer preferences for pork are increasingly prioritizing quality traits such as flavor and tenderness, which are often superior in Chinese indigenous pig breeds. The primary objective of this study was to explore the molecular basis of flavor traits using Rongchang (RR), Yorkshire (YY), and RR × YY (YR) breeds. The investigation focused on meat quality traits, along with untargeted metabolomics, lipidomics, and volatile flavor compound (VOC) profiling of the longissimus dorsi muscle. The results indicated that RR pork exhibited higher pH levels and overall acceptability. Analyses using electronic nose and tongue demonstrated that RR pork elicited stronger responses for W2S, W1S, and W1C sensors, as well as for umami and sourness. A total of 15 VOCs were identified as differing among the breeds. RR pork contained higher levels of benzothiazole and dimethyl sulfoxide, but lower levels of nonane, 2-methylheptane, and 2,4-dimethylheptane. Metabolomic analysis revealed 45 distinct metabolites, with a greater abundance of flavor precursors such as α-ketoglutaric acid in RR pork. Lipidomic analysis identified 22 different lipids, with triglycerides being more enriched in RR pork. Phospholipids, such as phosphatidylcholine (PC) and phosphatidylethanolamine (PE), varied by breed, with PC (e) being lowest and cardiolipin highest in RR pork. Correlation network analysis revealed that nonane, 2-methylheptane was the most connected flavor compound, positively correlating with certain lipids and metabolites, such as PC (18:1_18:1), PE (18:2e_22:6), PC (36:4) and 2-phenylglycine, and negatively correlating with PC (32:0e), SM (d41:1), N-hydroxy-2-acetamidofluorene, and histamine. This multi-omics approach provides a comprehensive view of the molecular signatures associated with pork preference, identifying potential biomarkers for meat quality that can be leveraged for future breeding strategies.

Agriculture doi: 10.3390/agriculture16090957

Authors: Eleftheria Bempelou Kyriaki Varikou Antonios Nikolakakis George P. Balayiannis

In Greece, the protection of olive orchards against the olive fruit fly (Bactrocera oleae), the most serious pest of olive fruits, is implemented through a national control program. This program is implemented by the Ministry of Rural Development and Food in co-operation with various public and private organizations. A new approach followed for this goal is the use of insecticide spray solutions combined with trophic attractant to attract and kill the olive fruit fly. In the present study, a method for the determination of the major insecticides, lambda-cyhalothrin and Spinosad, in their spraying solutions in combinations with trophic attractants was developed and validated and the monitoring of their residual concentration under various temperature conditions was examined. The reliability of the analytical method was achieved by obtaining acceptable results regarding the core criteria of specificity, linearity (R2 ≥ 0.99), accuracy (recoveries ranged from 91.01% to 116.29%), and precision (RSDs ranged from 0.47% to 3%). Furthermore, no significant effect on the stability of lambda-cyhalothrin and spinosad was noted from the various attractants that were added. As it was observed, in all cases the concentration of the insecticide remained stable. On the other hand, the effect of temperature as well as pH seems to be significant, with the degradation rates at 30 °C clearly higher in all cases than those at 20 °C. Therefore, preliminary data have been provided on recording the duration that the formulation remains stable and effective in spray solutions.

Agriculture doi: 10.3390/agriculture16090959

Authors: Motlalepule John Seema Uwe Peter Hermann Grany Mmatsatsi Senyolo

The agricultural sector is increasingly confronted with numerous challenges, including declining prices for agricultural products, escalating production costs, intensified globalization, rapid industrialization, urban expansion and growing competition in global markets. To promote rural development and improve farmers’ livelihoods through diversified sources of income, agritourism has been identified as a viable alternative strategy. This study aims to determine the factors influencing farmers’ willingness to participate in agritourism in Mpumalanga Province, South Africa. Primary data were collected from November 2022 to June 2023 using a structured questionnaire and a simple random sampling technique to select 100 farmers. A logistics regression model was used to analyse data. The findings revealed that profitability, non-farm employment, the number of labourers, and access to information positively influence WTP. Age also positively influenced WTP, while marital status showed a negative but significant effect. The findings imply that farmers with stronger financial capacity, labour availability and access to information are more likely to consider agritourism as a diversification strategy. The study suggests strengthening extension services, improving farm profitability and enhancing access to information to increase readiness to engage in agritourism.

Agriculture doi: 10.3390/agriculture16090958

Authors: Jose Leonardo Santos-Jiménez Maite Freitas Silva Vaslin

Passion fruit (Passiflora edulis) quality is defined by integrated sensory and nutritional traits, including sugar–acid balance, volatile organic compounds (VOCs), pigment-related attributes, and bioactive compounds such as ascorbic acid and phenolics. These traits emerge from coordinated regulation of carbon allocation, mineral nutrition, ripening metabolism, and stress- and defense-related signaling pathways, which are strongly modulated by environmental conditions. Sustainable biological inputs are increasingly explored as tools to influence these regulatory networks; however, evidence linking such interventions to reproducible fruit quality outcomes in Passiflora remains fragmented. This review first synthesizes current knowledge on the physiological, biochemical, and molecular mechanisms underlying passion fruit quality formation and maintenance, and then discusses how biofertilizers; microbial inoculants (including plant growth-promoting rhizobacteria—PGPR and arbuscular mycorrhizal fungi—AMF); fungal-derived elicitors such as chitosan and chitooligosaccharides; and complementary postharvest biological strategies may modulate these processes. Emphasis is placed on traits beyond yield, including sugar–acid balance, aroma and VOC profiles, color, nutritional quality, texture, and shelf life. By integrating genomics, transcriptomics, metabolomics, proteomics, and microbiome-based evidence, we examine how environmental modulation and key signaling pathways intersect with metabolic networks underlying fruit quality. Available studies indicate that responses to biological inputs are context-dependent and often non-linear. Key knowledge gaps and priorities for mechanism-informed sustainable management of passion fruit quality are identified.

Agriculture doi: 10.3390/agriculture16090956

Authors: Shan Liu Shilin Fang Luhao Zhang Pengcheng Wang Xiaorong Cheng Lei Xu Jian Sun Tengping Jiang

Instance segmentation of plant point clouds is challenging due to intricate structures, non-uniform density, and large intra-class variation. Conventional methods often suffer from blurred boundaries, instance adhesion, and insufficient coupling of semantic and instance features. To address these issues, this paper proposes MPRSF-CSA, a novel network integrating recursive slice-based feature extraction with an attention-embedding mechanism. The method first transforms disordered point clouds into ordered sequences via a multi-directional recursive slicing strategy and models inter-slice dependencies using BiLSTM. Parallel decoding branches for semantic and instance segmentation are constructed, and a core attention-embedding module facilitates bidirectional fusion of semantic and instance features. Instance segmentation is achieved via clustering and semantic-aware optimization. Experiments on two public datasets demonstrate that MPRSF-CSA outperforms existing approaches in segmentation accuracy, boundary preservation, and adaptability to complex plant scenes.

Agriculture doi: 10.3390/agriculture16090955

Authors: Taiwei Zhao Hua Zhang Wei Sun Luhai Zhang

To address the poor coating quality and low efficiency of Astragalus membranaceus seed pelletizing, this study combined theoretical analysis, DEM simulations, and experiments. The motion and force conditions of seed-powder particles were analyzed to identify key parameters. Using the coefficient of variation (Cv) as the evaluation index, the disc diameter, pan edge inclination, and rotational speed were optimized via response surface methodology. The optimal structural parameters were 605.5 mm, 15.7°, and 20.3 r·s−1. Liquid adhesion was represented by a custom time-varying cohesion model in DEM. Physical experiments showed that the optimized structure increased the pelletization qualification rate from 74.8% to 94.3%. Orthogonal experiments further optimized the process parameters: a single powder feed of 20 g, a single binder solution feed of 25 mL, and a coating duration of 8 min, achieving a qualification rate of 98.3%. Seedling emergence tests revealed that pelleted seeds had a significantly higher emergence rate (97.6%) than non-pelleted seeds (67.3%). These findings provide theoretical and technical references for pelletizing the coating of irregularly shaped seeds.

Agriculture doi: 10.3390/agriculture16090954

Authors: Guofeng Wang Mingyan Gao Lingchen Mi

This paper is based on data from 121 cities in China’s ecologically fragile regions from 2008 to 2022; it constructs an indicator system for the efficiency of pollution control and carbon reduction in agricultural practices. This system includes expenditures on agriculture, forestry, and water affairs, arable land area, agricultural laborers, total agricultural output value, agricultural carbon emissions, and agricultural non-point source pollution. It uses a super-efficiency SBM model that incorporates non-desirable outputs to measure the synergistic efficiency and analyzes its dynamic evolution using the Malmquist–Luenberger index to reveal the spatiotemporal characteristics of the synergistic efficiency. A Tobit model identifies the influence of factors, such as the level of rural economic development, crop planting structure, the strength of fiscal support for agriculture, rural education level, urbanization rate, and mechanization level on the synergistic efficiency. The results show that, from a temporal perspective, the average synergistic efficiency was only 0.58, significantly below the effective value of 1, indicating substantial room for overall improvement. Only 10 cities met the benchmark, with distinctly different reasons for compliance, while the remaining 111 cities remained inefficient. Regarding influencing factors, crop planting structure, the strength of fiscal support for agriculture, and urbanization rate significantly and positively drive efficiency; the level of rural economic development and mechanization level significantly inhibit efficiency, and rural education level shows no significant impact. These findings provide targeted policy recommendations for the synergy effect in ecologically fragile areas, as well as for low-carbon agricultural development.

Agriculture doi: 10.3390/agriculture16090953

Authors: Haoran Shi Xiaoyue Zhang Lin Chen Bin Yang Sihan Liu Guangming Li Yang Liu

Teat number is an important economic trait in pigs because it affects sow reproductive performance and piglet nursing ability, yet its genetic basis and molecular regulatory mechanisms remain incompletely understood. In this study, a combined-population genome-wide association study was performed in Canadian and French Large White pigs to identify loci associated with teat number traits. A total of 4217 pigs were genotyped, and 2,244,684 autosomal single-nucleotide polymorphisms were retained after quality control and genotype imputation. Multiple association signals for total teat number were detected, with major peaks located on chromosomes 7 and 10. Among the positional candidate genes, PROX2 was prioritized for further validation, and genotype–phenotype association analysis showed that pigs with the CC genotype at the PROX2 polymorphic locus had significantly lower total teat number than those with the CT and TT genotypes. To investigate its biological role, PROX2 was silenced in porcine mammary epithelial cells. Transcriptome analysis identified 887 differentially expressed genes after PROX2 knockdown, and functional assays showed that PROX2 silencing inhibited cell proliferation, altered cell cycle progression, and affected the expression of proliferation- and development-related genes. These findings indicate that PROX2 is an important candidate gene associated with teat number variation in pigs.

Agriculture doi: 10.3390/agriculture16090952

Authors: Shunlei Li Claudia Chiodi Francesca Ragazzi Marco Gnudi Federico Gavinelli Giulia Zardinoni Carmelo Maucieri Maria Giordano Lucia Giagnoni Samathmika Ravi Andrea Squartini Giuseppe Concheri Gui Geng Yuguang Wang Piergiorgio Stevanato

(1) Background: Soil fertility in organic systems depends on interactions between physicochemical properties and biological processes that regulate nutrient availability along the soil profile. However, information on their vertical distribution remains limited, particularly for root crops such as sugar beet. This study evaluated depth-related patterns in soils from three organic farms growing sugar beet. (2) Methods: Soil profiles (0–120 cm) were sampled and analyzed for physicochemical properties, mineral nitrogen (N) forms, and biological indicators, including the QBS-ar index, microbial abundance, and functional genes involved in N and carbon cycling. (3) Results: Nitrate-N and total mineral N were mainly concentrated in the 0–40 cm layer and declined markedly with depth. Microbial abundance and most N-cycling functional genes were similarly enriched in the topsoil, showing clear vertical stratification. Statistical analyses suggested that functional gene composition was associated with mineral N gradients after accounting for soil depth. (4) Conclusions: These findings provide an exploratory indication of relationships between mineral N forms and microbial indicators in an organically managed sugar beet system. Given the limited number of sampling units, results should be interpreted cautiously. However, these results highlight the value of soil profile approaches for understanding N redistribution and improving nutrient management strategies.

Agriculture doi: 10.3390/agriculture16090951

Authors: Shuxin Zhu Jiarui Feng Hongfeng Yu Xianglin Dou Huanliang Xu Zhaoyu Zhai

Soybean rust is a widespread and rapidly spreading fungal disease that poses a serious threat to both the yield and quality of soybeans. Traditional vegetation indices struggle to effectively assess disease severity across different infection stages, particularly during early or mild stages, due to weak spectral responses. In this study, we propose a soybean rust resistance identification model, RustNet-3D (Soybean Rust Disease Diagnosis Network-3D), which integrates a 3D deformable convolution module and a spectral dilated convolution module to achieve accurate classification of different disease severity levels. We further introduce a spectral feature band extraction module, iBSAM (improved Band Selection and Attention Module), which employs a modified depthwise separable convolution architecture. iBSAM incorporates bandwise independent convolution to enable individualized modeling of each spectral band. It also applies a hard thresholding strategy to remove redundant information, and integrates a channel attention mechanism to reinforce the model’s sensitivity to discriminative wavelengths. By modeling the temporal hyperspectral data of soybean rust, five highly sensitive spectral bands—581 nm, 605 nm, 596 nm, 609 nm, and 628 nm—are identified and subsequently used to construct the Soybean Rust Spectral Index (SRSI). Experimental results demonstrate that the RustNet-3D model achieves an overall accuracy (OA) of 92.74%, and the correlation coefficient between SRSI and disease severity reaches 0.89, validating the effectiveness of the selected spectral features. This study provides a rapid and accurate solution for soybean rust severity evaluation, offering a high-efficiency and automated approach for resistance identification and intelligent breeding.

Agriculture doi: 10.3390/agriculture16090950

Authors: Krzysztof Rutkowski Grzegorz P. Łysiak

Ethylene is a key phytohormone regulating fruit ripening, the senescence of ornamental plants, and the post-harvest quality of horticultural products. Although numerous studies have described compounds that inhibit ethylene biosynthesis or perception, the available evidence remains fragmented across chemical groups, plant species, and pre- and post-harvest applications. This review addresses that gap by critically integrating current knowledge on the principal inhibitors of ethylene biosynthesis and perception used in horticulture, with emphasis on their sites of action, practical effectiveness, and limitations. Biosynthesis inhibitors, including aminoethoxyvinylglycine (AVG), aminooxyacetic acid (AOA), daminozide, benzyl isothiocyanate (BITC), and oxalic acid (OA), reduce ethylene production at different stages of the ethylene pathway, whereas perception inhibitors such as 1-methylcyclopropene, 1-DCP, silver compounds, alkenes, and diazocyclopentadiene interfere with receptor binding and downstream ripening responses. The available literature indicates that 1-methylcyclopropene remains the most widely used commercial inhibitor, while oxalic acid is emerging as a promising natural modulator of ethylene-related processes. However, the efficacy of these compounds is strongly dependent on species, maturity stage, dose, temperature, and storage conditions, and some are additionally constrained by regulatory concerns, incomplete mechanistic understanding, or inconsistent performance. Overall, ethylene inhibitors are important tools for extending shelf life, maintaining firmness, delaying senescence, and reducing post-harvest losses. Further comparative and crop-specific studies are needed to optimize application strategies, improve environmental safety, and support the development of effective natural alternatives.

Agriculture doi: 10.3390/agriculture16090949

Authors: Shuhong Zhao Changle Jiang Xize Liu Yueqian Yang Mingxuan Du Bin Lü Shoukun Dong

Subsoiling can break the plough pan and improve the root growth environment. The effect of the traditional subsoiler is poor, as it relies only on the chisel tine, but pneumatic subsoiling can improve the soil structure more efficiently through the negative pressure generated by the jet hole. This research used computational fluid dynamics and the discrete element method to optimize the biomimetic structure of the jet hole, model the pneumatic subsoiling process at a depth of 330 mm, and observe the movement of soil particles as airflow passes through. The effect of the jet hole at different positions and sizes on the plough pan soil was analyzed, and fluid domains and measurement areas were set up to observe the upward movement, diffusion, stabilization, and settling of soil particles under the action of airflow. The results of the soil bin experiment validated the accuracy of the simulation model through draft force and vertical force, and the average error between the simulation and experimental data was 2.8%. The study revealed that the increase in the rate of soil porosity reached a maximum of 3.65% when the jet hole was positioned above the chisel tine with a radius of 4 mm. The biomimetic jet hole pneumatic subsoiler designed in this study, along with the established CFD-DEM coupled simulation model capable of predicting pneumatic subsoiling performance, can provide references for the design and application of a pneumatic subsoiler. Furthermore, it also provides a theoretical basis for understanding the mechanism of airflow on soil during pneumatic subsoiling operations.

Agriculture doi: 10.3390/agriculture16090948

Authors: Rubén Félix-Gastelum Jesús Ramon Escalante-Castro Karla Yeriana Leyva-Madrigal Ignacio Eduardo Maldonado-Mendoza Gabriel Herrera-Rodríguez

Brown spot on the leaf sheath is an emerging disease of sweet corn (Zea mays L.) in Sinaloa, Mexico, with an unknown etiology. This study aimed to identify the causal agent of the disease and assess its pathogenicity on commercial sweet corn hybrids. Bacterial strains were isolated from symptomatic leaf sheaths collected from commercial fields. Identification was performed through biochemical profiling (API 50CHB/E), pathogenicity tests on alternative hosts (potato, onion, celery), and molecular analysis (16S rRNA and recA genes sequencing and phylogenetic reconstruction). Pathogenicity and virulence were confirmed by inoculating four sweet corn hybrids in a greenhouse. The strains were Gram-negative rods, identified as Burkholderia gladioli based on biochemical profiles and molecular data (99% 16S rRNA+ recA similarity; phylogenetic clustering within the B. gladioli clade). In greenhouse trials, the strains induced brown spot lesions on the leaf sheaths of all tested hybrids, replicating field symptoms fulfilling Koch’s postulates. This is the first report of B. gladioli as the causal agent of brown spot on the leaf sheath of sweet corn in Mexico. The pathogen’s broad host range highlights its potential as an emerging threat to horticultural crops in the region.

Agriculture doi: 10.3390/agriculture16090947

Authors: Qi Wang Zhiyu Wang

Plant disease detection in natural environments is significantly challenged by variations in lesion scales and interference from complicated background clutter. Nevertheless, current models often remain limited in effectively capturing multi-scale features and mitigating background interference simultaneously. To tackle these challenges, we present TGL-YOLO, an improved detection network built on the YOLO11 framework. Methodologically, we introduce the Tri-Scale Dynamic Block (TSDBlock) to adaptively extract fine-grained features across highly variable lesion sizes. Furthermore, a Gated Pyramid Spatial Transformer (GPST) is designed to fuse cross-scale features and suppress background interference, while a Large Separable Pyramid Attention (LSPA) module expands the spatial receptive field to capture global context. Experimental results on two public datasets show that TGL-YOLO demonstrates improved performance over the YOLO11s baseline. On the PlantDoc dataset, it improves mAP50 and mAP50:95 by 4.7% and 3.7%, reaching 0.591 and 0.449, respectively. On the FieldPlant dataset, it reaches 0.793 and 0.608, yielding improvements of 2.3% and 1.9%. The proposed method demonstrates the capability to reduce missed detections and false positives caused by multi-scale lesions and environmental noise, providing a competitive and computationally viable solution for agricultural disease monitoring in natural environments.

Agriculture doi: 10.3390/agriculture16090946

Authors: Qingting Jin Runqi Yuan Jiayan Fang Jing Huang Jiayu Chen Shilei Lyu Zhen Li Yu Deng

In modern intelligent food processing, the unpredictable variability in pomelo orientation on high-speed conveyors poses a significant challenge to automated grading and precision peeling operations. To address this, a deep learning-based method is proposed for the real-time detection of pomelo posture. Firstly, a pomelo posture dataset was constructed to support model training and validation. Secondly, to balance the extraction of posture features from uniform fruits with the low-power constraints of edge deployment, a domain-specific architectural optimization is presented. Building on the YOLOv8n framework, the proposed model synergistically integrates specialized modules. A lightweight GhostHGNetV2 foundation is utilized to significantly reduce computational redundancy while maintaining the resolution required to detect key anatomical landmarks. To overcome spatial confusion and capture multi-scale global appearance information, a multi-path coordinate attention (MPCA) module is introduced. Furthermore, the SlimNeck architecture and VoVGSCSP module streamline multi-scale feature fusion via one-time aggregation, effectively preventing computational bottlenecks. This design optimizes the computational efficiency of the model while maintaining detection accuracy. Experimental results demonstrate that compared with the baseline YOLOv8n model, the proposed method increased the mAP50 accuracy by 3.67% while reducing parameter count and computational load by 17.5% and 23.3%, respectively. Additionally, it achieved a processing speed of 19.3 FPS on the Jetson Orin Nano 6G edge platform. This research provides a critical technical foundation for the recognition of pomelo posture, enabling subsequent orientation rectification and fostering the development of streamlined, automated pomelo processing lines.

Agriculture doi: 10.3390/agriculture16090945

Authors: Szczepan Figiel Janusz Gajda Justyna Kufel-Gajda

Prices and quantities in agricultural commodity and food product markets are subject to constant changes due to evolving supply and demand conditions. Big and sudden shifts in supply or demand may lead to price movements that bring negative consequences for food producers or consumers. Factors causing such movements can be of different natures, but substantial changes in the world energy price levels are supposed to be one of the most important. The purpose of the study was to investigate the effect of global energy price shocks on the evolution of food commodities and food consumer prices. Using the World Bank data on the respective price indices, we looked for shocks in these data series by utilizing statistical tools. Having identified three global energy price shocks in the period 2000–2024 induced by the financial crisis of 2008, the COVID-19 pandemic, and the outbreak of war in Ukraine, their influence on the world agricultural commodity prices and food consumer prices was assessed. It was found that the series of energy, food commodity, and food consumer price indices were related in the long term. Also, the occurrence of global energy price shocks to a visible extent translated into global food commodity and food consumer price shocks. Applying various statistical and econometric techniques, including Chow tests and MS-VAR modelling, enables the identification of which breaking points led to regime changes between the analysed variables. The most sensitive to the structural breaking points appeared to be the relation between energy and consumer food prices. This discovery can be considered our major contribution.

Agriculture doi: 10.3390/agriculture16090943

Authors: Magdalena Kapłan Kamil Buczyński

Winter pruning is a key management practice in viticulture that directly affects vine architecture, yield balance, and grape quality. At the same time, it is a highly labor-intensive operation, and the selective identification of appropriate cutting locations remains one of the main challenges limiting the automation of pruning in vineyards. Advances in machine vision provide new opportunities to support the development of robotic pruning systems. The objective of this study was to develop and evaluate a vision-based method for estimating grapevine pruning points and cutting lines using instance segmentation outputs generated by YOLO models. A dataset of 1500 RGB images of dormant grapevines was collected under field conditions in the Nobilis vineyard located in southeastern Poland. Two annotation strategies were implemented to define pruning regions. YOLO-based instance segmentation models were trained and evaluated for detecting cutting-related structures. Based on the predicted segmentation masks, a geometry-based method termed PCAcutSeg-V was developed to estimate class-dependent cutting points and cutting lines using principal component analysis applied to object contours. The results indicate that YOLOv8 and YOLO11 architectures achieved the highest segmentation performance among the evaluated models. The simplified annotation strategy provided more stable geometric inputs for the PCAcutSeg-V method, enabling more reliable estimation of cutting points and cutting lines compared with the extended annotation approach. When combined with the PCAcutSeg-V method, the proposed perception–geometry pipeline achieved high effectiveness in pruning decision estimation. The method was further implemented in a real-time processing pipeline using an RGB camera and an edge computing platform, where it maintained performance consistent with the results obtained from offline image analysis. These findings demonstrate that combining deep learning-based instance segmentation with deterministic geometric reasoning enables accurate and interpretable estimation of grapevine pruning locations and provides a promising foundation for future autonomous pruning systems.

Agriculture doi: 10.3390/agriculture16090942

Authors: Damjana Tomić Aleksandar Marić Danka Dragojlović Branislava Đermanović Jelena Vujetić Bojana Šarić Tea Sedlar

The global wine industry generates approximately 20 million tonnes of organic residues annually, representing a significant environmental and management challenge. While phenolic compounds from winery by-products have been extensively studied, protein and peptide fractions remain underutilised. This review provides a systematic overview of proteins derived from major winery side streams, including grapevine leaves, stems, pomace, seeds, and wine lees, with emphasis on their characterisation and recovery. Conventional and emerging extraction strategies are evaluated, with particular attention to green technologies such as ultrasound-assisted extraction (UAE), pulsed electric fields (PEF), and natural deep eutectic solvents (NADES) in the context of sustainable and resource-efficient processing. Enzymatic hydrolysis is discussed as a key approach for converting complex proteins into bioactive peptides with antioxidant, antimicrobial, and antihypertensive properties. Potential applications in agriculture, plant protection, animal nutrition, and food systems are considered, together with the implications of the EU circular economy regulatory framework. Overall, winery by-products are highlighted as promising nitrogen-rich secondary resources, and the review outlines valorisation pathways supporting nutrient recycling, waste reduction, and the development of a more sustainable agricultural bioeconomy.

Agriculture doi: 10.3390/agriculture16090944

Authors: Yueyi Chen Xin Chen Paravee Maneejuk Woraphon Yamaka

This study examines whether the relationship between provincial fiscal revenue and expenditure measures and grain production in China is nonlinear. Using a balanced panel of 31 provinces from 2007 to 2021, we analyze major revenue-side and expenditure-side fiscal instruments, including the cultivated land occupation tax, value-added tax, agricultural insurance subsidies, agricultural loan interest subsidies, rural minimum living security subsidies, education expenditure, and transportation infrastructure expenditure. To identify regime-dependent changes in estimated associations, we employ panel kink and double-kink regression models with endogenously estimated kink points. The results suggest that the estimated relationships are intensity-dependent rather than constant. The cultivated land occupation tax exhibits a kinked relationship with grain production, with a more positive association beyond a certain level. Agricultural insurance subsidies display a double-kink pattern, with the strongest positive estimated association concentrated in an intermediate range of the subsidy measure. Rural minimum living security subsidies are positively associated with grain production at lower levels, but this association weakens and may become negative after the estimated kink point. Overall, the findings suggest that the relationship between fiscal variables and grain production depends not only on policy direction but also on the levels of the fiscal measures.

Agriculture doi: 10.3390/agriculture16090941

Authors: Qinghui Zheng Zhiyu Zuo Qingqing Dai Haitao Peng Yongqiang Fu Shenghe Zhang Hanping Mao

To improve the harvesting efficiency of mechanized cabbage harvesting and reduce damage, the structural configuration of a cabbage harvester was designed based on the cabbage cultivation pattern, physical morphological parameters, and mechanical harvesting characteristics. The harvester consists of a crawler power chassis, pulling device, crop guiding device, clamping and conveying device, profiling device, root-cutting device, and leaf-stripping and collecting device, which enables simultaneous pulling, conveying, root cutting, outer leaf separation, and collection for two rows of cabbages in a single pass, thereby enhancing harvesting efficiency. The sources of cabbage damage during the harvesting process were analyzed, and dynamic analyses of the key components were performed to determine their structural parameters. Through single-factor experiments and response surface methodology optimization tests, the effects of forward speed, pulling roller rotational speed, clamping and conveying speed, and cutter rotational speed on the harvest qualification rate were evaluated. The optimal working parameter combination of these factors was determined and validated through field harvesting performance tests. The results showed that, under the operating conditions of forward speed 0.4 m/s, pulling roller rotational speed 114 r/min, clamping and conveying speed 0.51 m/s, and cutter rotational speed 338 r/min, the average harvest qualification rate reached 96.4%, and the average damage rate was 3.6%, which is close to the maximum theoretical harvest qualification rate of 96.78% predicted by the optimization model. The field validation tests demonstrated good performance, with all indicators meeting the design requirements and relevant standards, providing theoretical support and reference for the development and improvement of cabbage harvesting machinery.

Agriculture doi: 10.3390/agriculture16090940

Authors: Bin Li Minxi Li Hongsheng Ren Chuandong Liu Guilan Peng Zhiheng Zeng

In response to the subjective issues, inconsistent quality standards, high labor intensity and low sorting efficiency during the drying process of green pepper, an improved YOLOv11 algorithm was proposed for quality detection. A multi-scale edge enhancement module (MEEM) is introduced into the backbone network, replacing the original basic C3K2 module with C3K2-MEEM to enhance the extraction of detailed features in images of dried green Sichuan pepper and prevent missed detections, false detections, and boundary confusion. The LRSA module is integrated into the 10th layer of the backbone network to improve the clarity of the tumor-like texture of the Sichuan pepper and reduce the influence of impurities, automatically allocating attention based on feature similarity to preserve local information. In the neck layer, the DPCF module is added to the FPN+PAN feature fusion stage to achieve multi-scale feature collaboration, meeting the detection requirements of dried green Sichuan pepper. The results show that the accuracy recall rate, mean average precision, and model size of the improved MLD-YOLOv11 algorithm are 92.1%, 96.6%, 95.6%, and 11.06 MB, respectively. Compared with the training results of the original YOLOv11 model, the average accuracy of the improved model has increased by 2.2 percentage points, and GFLOPs have definitely decreased by 2 G, with parameter reduction of approximately 3.10%. Compared with other mainstream models, the MLD-YOLOv11 model has significant advantages in terms of mean average precision, model size, and floating point operations per second, making it more suitable for industrial applications and providing an efficient, accurate, and lightweight solution for the quality detection of dried green Sichuan pepper.

Agriculture doi: 10.3390/agriculture16090939

Authors: Andrzej Czyżewski Ryszard Kata Anna Matuszczak

This article analyses budgetary expenditures on agriculture and rural development in Poland in 2004–2025, i.e., after Poland’s accession to the European Union (EU). The study examines the size, real dynamics, and structure of total agricultural budget expenditures, including both national budgetary funds and EU funds allocated through the instruments of the Common Agricultural Policy (CAP). The analysis assesses the importance of EU budget funds for the level and structure of public expenditures on agriculture and rural development in Poland and attempts to determine the relationship between national and EU funds. The study employed time series analysis, structural analysis, and an analysis of the interdependence of variables (i.e., correlation and multiple regression). It was found that during the 22 years of EU membership, budgetary expenditures on agriculture, agricultural markets, and rural development in Poland were strongly determined by the volume of European funds, which accounted for the sharp increase in Poland’s agricultural budget compared with the pre-accession period. Compared with 2003 levels, expenditure rose by an average of 162% in nominal terms and 129% in real terms. EU funds also acted as a stabilising factor for the size of this budget throughout the analysed period. The proportion of European funds in Poland’s agricultural budget (PAB) rose sharply in the early years of Poland’s EU membership (2004–2011), increasing from 20.1% to 48.7%. However, it remained relatively stable in subsequent years, averaging 47.8%. Nevertheless, the appreciation of the Polish zloty against the euro caused the real value of these expenditures to decline, a trend that became apparent from 2017 onwards. This resulted in the need to increase expenditures from the national budget and led to national funds assuming a greater share of the financial burden of supporting agriculture. Between 2017 and 2025, the share of EU funds in the PAB fell from 43% to 33.1% (averaging 40.3%). The structure of expenditures within the CAP evolved over time as a result of changes in CAP priorities, although farmers’ income support as well as assistance for the modernization and improvement of the competitiveness of Polish agriculture remained key objectives.

Agriculture doi: 10.3390/agriculture16090938

Authors: Dawei Shi Wei Wang Qichang Yang Sen Wang Yuexuan He Yanhua Hou Chunlei Zhu Rui Li Yameng Jiang

Aiming at the problems of uneven radiation distribution and difficult regulation in double-film multi-span greenhouses in the Gobi Desert, a spatiotemporal simulation model of the radiation environment based on the coupling of Rhino–Grasshopper and Radiance was constructed in this study. Parametric simulation and multi-objective optimization were adopted to significantly improve the solar radiation capture and distribution uniformity inside the greenhouse, providing a scientific basis for greenhouse design in the Gobi area. The results show that the model has high accuracy (R2 > 0.98), and the radiation inside the greenhouse presents a distribution pattern of “higher in the northeast, lower in the southwest, higher in the upper layer and lower in the lower layer”. The optimal orientation is 1° west of south, and the optimal configuration is 8 m span, 5 m eave height, and 30° roof slope. This study can provide quantitative support for the structural design, planting layout and energy-saving regulation of double-film multi-span greenhouses in arid desert areas, and has important practical value for promoting the efficient and sustainable development of facility agriculture in the Gobi Desert.

Agriculture doi: 10.3390/agriculture16090937

Authors: Beatriz Silvério dos Santos Matheus Ribeiro Brambilla Roberta Possas De Souza Gabriela da Silva Raqueti Mariana Bocchi da Silva Beatriz Gonçalves Pereira Costa Tiely Sakurai Jailson Vieira Aguilar Liliane Santos de Camargos

When present in excess in the environment, nickel (Ni) can bioaccumulate along the food chain, and become toxic to plants and animals. Phytoremediation represents a sustainable alternative, using plants for soil decontamination. This study aimed to evaluate the growth and phytoremediation potential of four Crotalaria species, cultivated in Ni-contaminated soil. The study was conducted in a greenhouse, under a randomized block design, and a 4 × 5 factorial scheme, containing four species (C. juncea, C. spectabilis, C. breviflora, and C. ochroleuca) and five Ni treatments (0, 35, 70, 140, and 280 mg kg−1). When Ni concentration reached 70 mg kg−1, shoot dry mass decreased by approximately 52% in C. juncea, 53% in C. ochroleuca, 81% in C. breviflora, and 46% in C. spectabilis, compared to the control. C. juncea, C. ochroleuca, and C. breviflora maintained satisfactory growth at 35 mg kg−1 and, for C. breviflora, this concentration increased root dry mass. All species showed high Ni translocation to the shoot, indicating potential for phytoextraction. The concentrations observed did not reach the threshold commonly used to define hyperaccumulator plants (>1000 mg kg−1 dry mass). However, in C. spectabilis, the highest Ni dose led to an increase in root translocation and reduced shoot translocation. Therefore, Crotalaria species demonstrate potential for Ni phytoremediation, although they differ in strategies regarding growth, accumulation, and Ni mobilization.

Agriculture doi: 10.3390/agriculture16090936

Authors: Yuanyi Liu Xuejiao Wang Qianqian He Gen Wang Zhenyou Wu Qi Liu Ming Du Yiping Zhao Gerelchimeg Bou Dongyi Bai Manglai Dugarjaviin Xinzhuang Zhang

Severe winter nutritional deficiencies may impair reproductive performance in Mongolian mares, yet optimal protein requirements during late gestation remain undefined. This study aimed to determine the effects of varying protein levels in complementary feed on gestational performance, physiology, and gut health. Seventeen late-gestating mares were assigned to three isocaloric diets differing in crude protein (CP)—high (HCP, 13.25%), medium (MCP, 12.04%), and low (LCP, 10.85%)—for 40 days. Statistical analysis was conducted using one-way ANOVA followed by Tukey’s HSD post hoc test. Mares fed the MCP diet tended to show more favorable growth performance and nutrient digestibility relative to the HCP group (p < 0.05). Blood analysis suggested that MCP mares had comparatively lower serum creatinine and creatine kinase concentrations, along with higher antioxidant capacity (catalase) and interleukin-1β levels (p < 0.001). Fecal microbiota sequencing showed that MCP was associated with comparatively higher microbial diversity, while HCP was characterized by enrichment of Proteobacteria, and LCP by enrichment of Bacteroidetes. Metabolomics identified 533 differential metabolites linked to protein metabolism. The MCP diet may help balance immune function, antioxidant status, and microbial homeostasis. These findings suggest that a complementary feed containing 12.04% CP may be associated with favorable effects on maternal health-related indicators in late-gestating Mongolian mares during winter.

Agriculture doi: 10.3390/agriculture16090935

Authors: Zhen-Ying Xu Rui-Xue Ren Jia-Yi Mao Yun Yu Jin Chen Ying-Jun Lei Li-Ling Han Wei Fan Chao Chen Yun Wang

As complex agricultural machinery, traditional combine harvesters face numerous challenges during operation due to their reliance on manual observation. To meet the demands of modern agriculture, intelligent combine harvesters have emerged. Intelligent sensing uses multi-sensor fusion and deep learning to monitor crop lodging, feed rate, loss rate, and impurity content. Under suboptimal conditions, multi-source fusion strategies improve perception reliability. Information processing and decision-making enable dynamic optimization of operational parameters and reduce harvest losses. Multi-machine coordination transforms single-machine operations into fleet control, while remote monitoring leverages a cloud edge collaboration architecture to enable status visualization, remote control, and predictive maintenance for faults. Unmanned operations utilize high-precision positioning and intelligent path planning to improve fleet efficiency and field coverage. However, the field still faces common challenges, including insufficient real-time processing capabilities for multi-source heterogeneous data, poor adaptability to complex agronomic scenarios, and limited economic feasibility. In this review, we examine the complete technology chain, which includes intelligent perception, intelligent decision-making and coordination, remote monitoring, and unmanned operations. We conduct a comparative analysis of the current state of these systems and the challenges they face, providing a systematic reference for future research and industrial applications.

Agriculture doi: 10.3390/agriculture16090934

Authors: Daniela Soares Sabrija Čadro Marko Ivanišević Dženan Vukotić João Rolim Teresa A. Paço Paula Paredes

This study assesses the impacts of climate change (CC) on maize production in Bosnia and Herzegovina, comparing ten maize-producing municipalities and using Gradiška as a case study. Agroclimatic indicators and ISAREG-based soil water balance simulations were used to evaluate regional suitability for future maize production. Projections indicate substantial increases in average temperatures of 2 to 6 Celsius by the end of the century, depending on the RCP scenario, together with important reductions in accumulated mean precipitation, particularly during summer. Rising temperatures accelerate maize phenology, shortening growth cycles and enabling double-cropping opportunities for short-season cycles. Medium-season cycles may become feasible in most regions, while long-season cycles remain constrained in high-altitude areas due to thermal requirements. Rainfed maize in Gradiška is expected to face increased relative evapotranspiration deficits under future ‘hot & dry’ conditions, with potential relative yield losses due to water deficit of up to 12%. Irrigated maize shows a variation in irrigation requirements from −26% to +8% relative to the baseline, which reflects the combined effect of a shortened crop growth cycle under higher temperatures and increased evapotranspiration demand under drier conditions. Regions with high soil water-holding capacity are the most resilient, while areas with shallow soils or Mediterranean climates are more vulnerable under future conditions. The findings underscore the need for agronomic adaptation measures to the projected CC impacts, including supplemental irrigation, drought-tolerant cultivars, and potential adjustment of sowing.

Agriculture doi: 10.3390/agriculture16090933

Authors: Zhou Zhang Wei Zhao Jing Jin Fuzhong Li Svitlana Pavlova

Point cloud semantic segmentation is a pivotal technology for realizing non-contact body measurement and refined management of livestock. However, processing sheep point clouds in smart livestock scenarios presents specific challenges, primarily due to non-rigid posture deformations and severe background interference. To address these issues, this paper proposes a novel symmetric encoder–decoder architecture named Local–Global Aggregation Network (LGA-Net), which achieves high-precision parsing of sheep point clouds by constructing a dual-scale feature aggregation mechanism. First, a Dual Attention Aggregation (DAA) module is designed to jointly encode geometric and color features, significantly enhancing the network’s ability to capture fine-grained local boundaries, such as sheep ears and hooves. Second, a Global Semantic Relation (GSR) module is introduced, utilizing spatial occupancy ratios to establish long-range dependencies, thereby effectively resolving semantic ambiguity caused by posture variations. Furthermore, a plug-and-play Dual-domain Feature Enhancement (DFE) module is proposed. By fusing bilinear interactions between explicit 3D space and implicit feature space, the DFE module constructs a high-pass filtering mechanism to suppress low-frequency background noise. Extensive experiments on a self-constructed point cloud dataset involving two semantic classes (Sheep and Fence) demonstrate that LGA-Net achieves a mIoU of 97.3%, an OA of 99.0%, and a mAcc of 97.8%. These results indicate that the proposed method outperforms existing mainstream algorithms in both segmentation accuracy and robustness. This study not only proposes a feasible solution for precise sheep extraction under the tested experimental conditions, but also provides solid technical support for subsequent automated body measurement and behavior analysis.

Agriculture doi: 10.3390/agriculture16090932

Authors: Mei Xu Mingyue Di Wenshuai Zeng Xuanyue Li Dong Xu Zhanlin Ma Yanxin Wang Mengjian Liu Yong Chen

This study was conducted to investigate the effects of dietary supplementation with rumen-protected arginine (RP-Arg) on growth performance, rumen fermentation parameters, microbial diversity, and blood physiological and biochemical indices in fattening Altay sheep. A total of 24 healthy, 6-month-old Altay male lambs were randomly assigned to three groups, with eight replicates per group. The control group received a basal diet, while the experimental groups were supplemented with either 0.50% or 1.00% RP-Arg on a dry matter basis, respectively. The results indicated that RP-Arg supplementation had no significant effect on feed intake, growth performance, or slaughter performance of the lambs (p > 0.05), whereas backfat thickness decreased linearly (p < 0.05). With increasing RP-Arg levels, serum low-density lipoprotein cholesterol, leptin, and catalase activity increased linearly (p < 0.05), while blood ammonia, alanine aminotransferase, and Ig M exhibited a significant quadratic increase (p < 0.05). RP-Arg supplementation led to a linear decrease in ruminal propionate and valerate concentrations (p < 0.05). Analysis of bacterial diversity revealed that the class Vampirivibrionia and the order Gastranaerophilales were biomarkers for the 0.50% RP-Arg group, while several taxa within the phyla Proteobacteria and Thermoplasmatota served as biomarkers for the 1.00% RP-Arg group. In summary, although supplementation of a forage-based diet with RP-Arg partially modified rumen microbial composition and fermentation profile, and regulated several blood biochemical parameters, it did not translate into any beneficial effects on growth performance. Larger-scale studies are therefore warranted to further elucidate the role of RP-Arg in fattening lambs.

Agriculture doi: 10.3390/agriculture16090931

Authors: Marco Vinicio Rodríguez-Deméneghi Gael Francisco García-Merino Noé Aguilar-Rivera Fabiola Hernández-Ramírez María Elena Montes-Ayala

Vanilla (Vanilla planifolia Jacks. ex Andrews) is a tropical orchid of high economic value, with an annual production of 8000 to 10,000 t and a market exceeding 800 million USD in over 40 countries. In vitro propagation has strengthened the innovation, production, and conservation of this species. Bibliometrics, as a quantitative approach, systematically examines the patterns, dynamics, and evolutionary trends of scientific production. A systematic search was conducted in Scopus and Web of Science until December 2025, using the terms “vanilla” and “micropropagation”. A total of 53 documents were identified in Scopus (1997–2025) and 39 in Web of Science (2000–2025). The evaluated indicators included: year of publication, country of origin, language, areas, main categories, document typology, authorship, and keyword distribution. VOSviewer was used for keyword analysis to identify author collaboration networks and emerging trends. The years with the most information were 2024 and 2025, with Mexico and India standing out prominently. The main thematic areas were Agricultural and Biological Sciences, and the role of researcher Ramírez-Mosqueda was highlighted. The keywords with the highest correlation and impact were bioreactors, vanillin, and cryopreservation. This bibliometric study provides a comprehensive perspective on scientific production related to vanilla micropropagation. The results highlight the multidisciplinary nature of biotechnology applied to this crop, integrating contributions from various areas of knowledge for the benefit of the main actors in the value chain.

Agriculture doi: 10.3390/agriculture16090930

Authors: Junxing Zhang Mingyue Wang Chaocang Chen Chen Ye Shijun Zhong Linmei Deng Lifen Luo Haijiao Liu Shusheng Zhu Min Yang

Negative plant–soil feedback (NPSF) drives yield decline in monocropping systems, yet how intraspecific competition modulates NPSF across planting densities remains unclear. We conducted a two-stage plant–soil feedback experiment using five crops (Triticum aestivum L., Zea mays L., Solanum lycopersicum L., Cucumis sativus L., and Panax notoginseng (Burkill) F.H. Chen) with contrasting NPSF intensities under four planting densities (30 × 30 to 8 × 8 cm). Crops with stronger NPSF (P. notoginseng) showed pronounced density-dependent biomass reductions, whereas those with moderate (S. lycopersicum, C. sativus) or low (Z. mays, T. aestivum) NPSF were largely density-insensitive. Given its sensitivity, P. notoginseng was used to explore mechanisms. High-density planting (8 × 8 cm) intensified NPSF, reducing seedling survival by 88.54% and biomass by 56.08% compared with low-density controls (30 × 30 cm). Microbiome profiling showed enrichment of pathogenic Fusarium spp. and depletion of beneficial Humicola spp. under high density. Metabolomic analysis identified linoleic acid and oleamide as key root exudates upregulated under high-density stress, which selectively stimulated Fusarium growth as preferred carbon sources. Collectively, these results reveal a density-dependent feedback in which intensified competition reshapes root exudation, promotes pathogen proliferation, and suppresses beneficial taxa, thereby amplifying NPSF. This provides mechanistic insights into microbially mediated NPSF under density stress and highlights the importance of optimizing planting density to sustain crop productivity.

Agriculture doi: 10.3390/agriculture16090929

Authors: Meiqiu Jiang Mingfu Gao Weichao Yang Hao Sun Hui Xu

Drought stress severely restricts agricultural productivity. Effective drought mitigation requires both improved rhizosphere water retention and enhanced nutrient availability. Poly-γ-glutamic acid (PGA) was expected to enhance water retention, while residue after evaporation (RAE) of 2-keto-L-gulonic acid fermentation was expected to supply labile carbon and promote nutrient mobilization. We hypothesized that their combined application would synergistically optimize the rhizosphere environment and enhance maize seedlings’ resistance to drought. A pot experiment was conducted to evaluate the growth of maize under simulated drought conditions, containing four treatments: control (C), RAE alone (R), PGA alone (P), and their combination (M). Results demonstrated that the M treatment synergistically promoted maize seedling growth, increasing the seedling growth index by 125% compared to the control. Co-application also synergistically enhanced the accumulation of osmotic adjustment substances (proline, soluble proteins, and soluble sugars) and ascorbic acid content, while reducing malondialdehyde (MDA) level. Furthermore, the M treatment markedly increased soil ammonium nitrogen and total organic carbon, thereby improving soil moisture and optimizing the rhizosphere conditions. Mantel analysis revealed that the M treatment restructured soil bacterial communities and enzyme activities by enhancing nutrient and organic carbon availability, which subsequently improved overall soil properties. These findings suggest that co-application of PGA and RAE improves maize seedling drought resilience and soil nutrient supply, offering a promising and economically viable strategy for sustainable agriculture in drought-prone regions by valorizing industrial by-products.

Agriculture doi: 10.3390/agriculture16090925

Authors: Aya Momose Mia Ann Fosco Shiho Kagami Masaaki Yamada Ryosuke Fujinuma

Cover crops are crucial in conservation agriculture for preventing soil erosion. For Citrus unshiu production, rattail fescue (Vulpia myuros (L.) C.C. Gmel) is a popular cover crop because its growth season differs from the citrus season, minimizing nutrient competition. However, no studies have examined its effects on the seasonal concentrations of flavonoids and monoterpenes in citrus peels, which are often used as medical ingredients. In this study, our aim is to determine the effects of cover crops on the sugar content and medicinal properties of unripe citrus fruit during the growing season. Samples collected in 2022 were examined for the effects of cover crops on the sugar concentration of fresh pulp. In addition, samples were taken from three randomly selected trees in each cover crop treatment (0, 50, and 100% area coverage) at the thinning (July, August, and September) of 2023 and 2024 to analyze hesperidin and d-limonene concentrations using standard methods. The results showed that cover crops reduced the sugar concentration of fresh pulp but had no impact on hesperidin concentrations across all thinning events and had inconsistent effects on the d-limonene concentration. Hence, while the use of rattail fescue might negatively affect the sugar concentration of mature Citrus unshiu, the use of premature fruits for medical ingredients could compensate for this loss.

Agriculture doi: 10.3390/agriculture16090928

Authors: Binbin Liu Xin Liu Xinying Liu Wanqin She Qiying Sun Qingming Li

To investigate the thermal environments of three large-span plastic tunnels with different orientations and shapes (two east–west-oriented asymmetrical tunnels, WE15-5 and WE13-7, and one north–south-oriented symmetrical tunnel, NS10-10) under summer high-temperature and winter low-temperature conditions, we continuously monitored the air and soil temperature and conducted a comparative analysis of both under typical weather conditions. Computational fluid dynamics (CFD) simulations were used to further analyze the temperature and airflow fields. The results showed that, in summer, NS10-10 exhibited a superior ventilation and cooling performance with the most uniform temperature distribution, making it more suitable for summer crop cultivation. In winter, WE13-7 demonstrated optimal insulation and heat retention, with the highest minimum air temperatures and best daylighting capacity. CFD model validation showed a good agreement with the measured data (RMSE: 0.73–0.85 °C). These findings provide structural optimization recommendations for large-span plastic tunnels in different seasons.

Agriculture doi: 10.3390/agriculture16090927

Authors: Woraphon Yamaka Nuttaphong Kaewtathip Wiranya Puntoon Roengchai Tansuchat Paravee Maneejuk

This study examines the relationship between major government support programs and farm-level technical efficiency in Thailand’s sticky rice sector. While existing studies have extensively analyzed rice efficiency, limited attention has been given to distinguishing the efficiency implications of different policy instruments or to modeling dependence between stochastic shocks and inefficiency. Methodologically, we employ a copula-based stochastic frontier efficiency effects model that jointly estimates production and inefficiency determinants while allowing for flexible dependence between noise and inefficiency components. Empirically, we use primary survey data from 429 farmers in Northern Thailand. The results indicate that participation in the debt moratorium program is positively associated with technical efficiency, whereas the widely implemented 1000-baht-per-rai subsidy is negatively associated with efficiency. The cost-reduction program exhibits no statistically significant association. The mean technical efficiency is 0.458, with a distribution concentrated at both low and high efficiency levels, indicating substantial heterogeneity across farmers.

Agriculture doi: 10.3390/agriculture16090926

Authors: Yunkun Cheng Yiling Xing Lei Xie Wanlong He Jinjin Ding Haiyan Zhang Xiaomei Liu Hongwei Geng

Pre-harvest sprouting (PHS) in wheat is a significant global challenge influenced by climate. This study aimed to decipher the genetic underpinnings of PHS and identify resistance genes using 309 recombinant inbred lines (RILs) derived from the “Berkut” × “Worrakatta” cross. Methods: Phenotypic assessment of PHS traits was performed using the whole-spike sprouting method across various environments, complemented by quantitative trait loci (QTL) analysis employing a wheat 50 K SNP chip. Results showed high PHS rates in both parental lines across multiple environments. Progeny exhibited substantial variation in PHS rates, with coefficients of variation ranging from 0.16 to 0.19 and phenotypic variation ranging from 23.92% to 100%, suggesting pronounced transgressive segregation. Nine QTLs associated with PHS were identified on chromosomes 1AL, 1DL, 2AL, 2AS, 2BS, 3DS, 4BL, and 7BL. These loci accounted for 2.67% to 6.39% of the phenotypic variation. Notably, the enhancer alleles at four loci—1DL, 2BS, 4BL, and 7BL—originated from “Worrakatta”, and “Berkut” contributed the enhancer alleles at the remaining five loci. Two QTLs, QPHS.xjau-1AL.1 and QPHS.xjau-1AL.2, were stable across multiple environments. Specifically, QPHS.xjau-1AL.1 was present in three environments and explained 3.86% to 6.39% of the phenotypic variation, while QPHS.xjau-1AL.2 appeared in one environment under average conditions, explaining 2.67% to 4.87% of the variation. Our study also identified eight candidate genes associated with wheat PHS, including those encoding Myb transcription factors that influence flavonoid biosynthesis and grain color, as well as genes involved in stress response and gibberellin biosynthesis, which are crucial for plant growth and development. These genes represent vital targets for enhancing wheat PHS resistance.

Agriculture doi: 10.3390/agriculture16090924

Authors: Andie Alexander Gonzales Diaz Fumin Wang Honglin Feng

Aphids are major agricultural pests worldwide, causing crop damage both through direct piercing-sucking feeding and the transmission of plant viruses. Their multistage life cycle, unique developmental physiology, plasticity in developing pesticide resistance, and multifaceted interactions with host plants and bacterial endosymbionts make effective control particularly challenging. In this review, we summarize the current toolbox available for aphid control across major crop systems, including chemical pesticides, biological agents, plant resistance, cultural practices, biorational control, and emerging strategies such as RNA interference (RNAi) and symbiosis-targeted approaches. Rather than providing an exhaustive survey of the literature, we draw on conceptual and illustrative studies to critically evaluate the strengths and limitations of each control strategy. Finally, we outline future directions for aphid control, highlighting the potential of modern technologies, such as artificial intelligence (AI), synthetic biology, data-driven analytics, and CRISPR-based genome editing, to expand and improve existing control options.

Agriculture doi: 10.3390/agriculture16090921

Authors: Szymon Piekarz Tomasz Płociniczak Magdalena Noszczyńska

Microplastics (MPs), defined as plastic particles ranging in size from 0.1 μm to 5 mm, have gained significant scientific attention worldwide due to their widespread occurrence and potential risks for human health and the environment. MPs can accumulate in water and soil, affecting organisms across multiple trophic levels and negatively impacting agricultural productivity and animal husbandry. Agricultural practices, such as plastic mulching, compost, and sewage sludge application, contribute to environmental plastic contamination, while irrigation and wastewater reuse facilitate their transport and deposition across ecosystems. Given the limited efficiency and high costs of physicochemical remediation methods, microbial biodegradation has attracted growing attention as a potentially sustainable strategy. This review focuses primarily on the metabolic potential of bacteria and fungi and the mechanisms underlying MP degradation. In the context of environmental safety, such studies are of particular importance. Under optimal laboratory conditions, reported microbial degradation efficiencies varied with microplastic type, microbial strain(s), and experimental conditions, ranging from 4% to >97%. Moreover, the literature review identifies key barriers to practical application, including environmental variability and the limited transferability of laboratory findings to field settings. Future research should therefore prioritize testable, application-oriented approaches. Addressing these gaps is essential to developing effective microbial degradation strategies for mitigating microplastic pollution.

Agriculture doi: 10.3390/agriculture16090923

Authors: Gao Peng Libo Liu Qiqi Tan

Knowledge of the influence of grassland-to-cropland conversion on subsoil carbon (C) and nitrogen (N) stocks and the effect of soil properties on subsoil C and N stocks after grassland cultivation remain poorly understood. Furthermore, soil C and N changes retain a biological coupling under global changes; however, whether the coupling between soil C and N stocks can be disrupted by long-term grassland cultivation remains largely unknown. Here, we explored changes in soil C and N stocks at three soil depths (0–10, 10–30, and 30–50 cm) across a grassland cultivation chronosequence of 50 years in a semiarid agro-pastoral ecotone in northern China. Our results showed that soil C and N stocks in the 0–10 cm soil layer exhibited a valley-shaped pattern with increasing cultivation duration, reaching the lowest value at 20 years of grassland cultivation. For the 10–30 cm and 30–50 cm soil layers, soil C and N stocks within 10 years of grassland cultivation were higher than those in native grassland. Soil C and N stocks bottomed out at 20 years of grassland cultivation and then increased with the duration of grassland cultivation. Cultivation duration had no direct effect on soil C and N stocks across soil depths but exerted an indirect influence by affecting soil properties. Soil properties mainly drove variations in C and N stocks in soil, which strengthened with soil depth. Soil C and N stocks in the 0–10 cm soil layer showed a positive correlation with soil pH and soil clay and silt contents and were negatively related to soil sand content. Soil C and N stocks in the 10–30 and 30–50 cm soil layers were only positively correlated with soil clay content. These indicate that soil clay plays a vital role in regulating variations in C and N stocks in topsoil and subsoil with the duration of grassland cultivation. Moreover, soil C stocks in the three soil layers exhibited a significant correlation with soil N stocks. This reveals that the coupled correlation between soil C and N stocks still remains under long-term grassland cultivation.

Agriculture doi: 10.3390/agriculture16090922

Authors: Ziqi Shen Can Qian Yifan Liu Tingting Ren Yinlong Zhang Jianming Xue Honghua Ruan Hu Cheng

Hydrochar application to soil inevitably releases hydrochar-derived dissolved organic matter (HDOM), yet its specific impact on soil microbial communities, independent of the hydrochar solid matrix, remains poorly understood. This study investigated, for the first time, the dose-dependent effects of HDOM on bacterial communities in three distinct soil types (red, yellow-brown, and black soils). A concentration gradient, including undiluted stock solution and 10-, 100-, and 1000-fold dilutions with ultrapure water, was established to test for hormesis-like responses. High-throughput 16S rRNA gene sequencing revealed that HDOM induced profound, soil-specific shifts in bacterial community structure. The application of HDOM induced the emergence of numerous specific bacterial taxa, with unique ASVs reaching up to 15,372. However, no significant changes were observed in microbial community richness or evenness (alpha diversity). Drastic shifts in beta diversity were evident only in red soil and yellow-brown soil, and exclusively under the undiluted HDOM treatment. At the phylum level, HDOM application did not alter the dominant bacterial types (top 10 phyla); however, their relative abundances were jointly regulated by both HDOM dose and soil type. Significant HDOM-induced changes in key bacterial biomarkers were primarily detected in red soil (e.g., phylum Elusimicrobia, class Fimbriimonadia, and family Alicyclobacillaceae) and yellow-brown soil (e.g., phylum Proteobacteria, class Alphaproteobacteria, and family Rhizobiaceae), while in black soil, such changes were observed only under the undiluted HDOM treatment (e.g., species Streptomyces rochei). Predictive functional profiling suggested limited impact on major metabolic pathways, with soil type remaining the primary determinant. These findings demonstrate that HDOM exerts a direct, dose-dependent, and soil-specific influence on bacterial communities, providing key insights into the environmental behavior of hydrochar and guiding its safe application.

Agriculture doi: 10.3390/agriculture16090920

Authors: Sensen Shi Quanming Liu Zhiyuan Yan

Fine-scale crop type information is essential for agricultural monitoring, irrigation management, and food security assessment. This study mapped three major crops—wheat, corn, and sunflower—in the Hetao Irrigation District, China, using multi-temporal Sentinel-2 optical imagery and Sentinel-1 SAR observations at the parcel scale. A multi-source feature set, including spectral bands, vegetation and red-edge indices, moisture-related variables, radar backscatter coefficients, and derived radar features, was constructed from the full growing season. An LSTM network was used to learn temporal representations of crop phenological dynamics, and the resulting embeddings were then combined with traditional machine learning classifiers, including Random Forest (RF), Support Vector Machine (SVM), and Extreme Gradient Boosting (XGBoost), for final classification. The results show that the hybrid framework substantially improves classification performance compared with the corresponding non-LSTM classifiers. Among all tested models, XGBoost + LSTM achieved the best performance, with an overall accuracy of 93.61%, a Kappa coefficient of 91.66%, and a mean IoU of 87.41%. The class-wise F1-scores were 85.61% for wheat, 97.22% for corn, and 87.27% for sunflower. Additional experiments further confirmed the advantages of parcel-based aggregation in improving spatial consistency and reducing mixed-field noise. The proposed framework provides a promising parcel-scale workflow for crop type mapping in fragmented irrigation districts, while its transferability across years and regions still requires further validation.

Agriculture doi: 10.3390/agriculture16090918

Authors: Muhammad Irfan Sharif Yong Zhong Muhammad Zaheer Sajid Francesco Marinello

Plant disease diagnosis in real-world agricultural environments is challenged by data scarcity, domain shift, privacy constraints, and limited edge-device resources. This paper proposes FMEL-FSDA, a Federated Multimodal Edge Learning framework with Few-Shot Domain Adaptation for robust field-based plant disease recognition. The framework integrates attention-based RGB–text feature fusion, privacy-preserving federated learning, rapid few-shot personalization, and uncertainty-aware inference within an edge-efficient architecture. Federated training enables collaborative learning across distributed farms without sharing raw data, while few-shot adaptation allows fast deployment to new regions using only 1–10 labeled samples per class. Experiments on the PlantWild in-the-wild dataset show that FMEL-FSDA outperforms centralized, federated, and few-shot baselines, achieving 93.78% accuracy, 93.33% F1-score, and 0.97 AUC. The model maintains strong performance under privacy mechanisms such as gradient perturbation and secure aggregation, reduces communication overhead by up to 4×, and supports low-latency edge inference. Uncertainty estimation and Grad-CAM-based explainability further enhance reliability by identifying low-confidence cases and highlighting disease-relevant regions. Overall, FMEL-FSDA offers a scalable, privacy-aware, and field-ready solution for intelligent plant disease diagnosis in precision agriculture.

Agriculture doi: 10.3390/agriculture16090919

Authors: Tupthai Norsuwan Kawiporn Chinachanta Thakoon Punyasai Rattanaphon Chaima Pruk Aggarangsi Masaomi Kimura Napat Jakrawatana Yutaka Matsuno

Agrivoltaics (AV) has emerged as an integrated land-use innovation capable of simultaneously addressing food, energy, and water challenges, yet its systemic implications for farming system sustainability remain insufficiently synthesized. This review adopts a farming system dynamics perspective to examine how AV systems reorganize biophysical, ecological, and socio-economic interactions across agroecosystems. Drawing upon agroecological principles, pathways of sustainable intensification and ecological intensification, and resource-loop strategies in circular economy, we identify the key elements and cause-and-effect relationships that shape AV system performance. Evidence indicates that the co-location of photovoltaics (PV) structures and crop cultivation generates new system properties, altered light distribution, moderated microclimates, redistributed soil moisture, and diversified production functions that influence productivity, resource-use efficiency, ecological services, and farm resilience. Using causal loop analysis, we conceptualize four central feedback dynamics: (i) PV–crop trade-offs and spatial-sharing relationships; (ii) microclimate modifications and crop physiological responses; (iii) ecological performance and landscape-level interactions; and (iv) circularity loops connecting resource conservation, renewable-energy substitution, soil processes, and material flows. This feedback collectively determines eco-efficiency outcomes, including enhanced land-equivalent productivity, improved water-use efficiency, strengthened regulating services, and reductions in external energy dependence. At the farming-system scale, AV diversifies income streams and stabilizes yields under climatic variability, whereas at the landscape scale, it fosters multifunctionality by supporting regenerative resource flows and ecological resilience. Building on these insights, we propose an integrated framework that links agroecological elements with dynamic feedback structures to guide context-specific AV design, management, and governance. This system-oriented synthesis provides a foundation for future research and policy efforts aimed at optimizing AV as a circular, resilient, and sustainable farming system innovation.

Agriculture doi: 10.3390/agriculture16090915

Authors: Ana Rita de Oliveira Braga Vinicius John Criscian Kellen Amaro de Oliveira Danielli Heiriane Martins Sousa Filipe Eduardo Danielli Danielle Monteiro de Oliveira Newton Paulo de Souza Falcão Cláudia Saramago de Carvalho Marques-dos-Santos

Acidic tropical soils act as strong sinks for phosphorus (P) due to the high adsorption capacity of this nutrient by iron (Fe) and aluminium (Al) minerals. In this study, we investigated the effects of applying acai waste biochar (Euterpe oleracea Mart.) in combination with dolomitic lime on the P dynamics of a Ferralsol with cowpea (Vigna unguiculata (L.) Walp) test crop. Application of 12 t ha−1 of biochar and 75% of the recommended lime rate increased soil pH by 1.77 units, reaching 6.77, and resulted in the lowest C:N ratio (18.99) at 0–5 cm depth. Inorganic P concentrations increased in Resin-Pi (2-fold), NaHCO3-Pi (2-fold), NaOH-Pi (2.89-fold) and HCl-Pi (4-fold) fractions relative to the corresponding treatments without biochar, while NaHCO3-Po decreased markedly, declining from 68% to 9% of the organic P fraction, NaOH-Po showed a less consistent response among treatments. In addition, P recovery in the Resin-Pi fraction increased, reaching 34.91% and 37.36% in the treatments with 12 t ha−1 of biochar and both 75 and 100% liming, respectively. Combined use of alkaline biochar and lime is a practical strategy to raise pH and increase labile and moderately labile inorganic P, and improve P use efficiency in acid Ferralsols. These responses are consistent with a redistribution of P among the assessed fractions and with the absence of detectable short-term effects on arbuscular mycorrhizal fungi (AMF) colonisation and easily extractable glomalin-related soil protein (EE-GRSP) production.

Agriculture doi: 10.3390/agriculture16090917

Authors: Chunhua Ji Guizhen Wang Wenxian Xu Zhengzao Cha Qinghuo Lin Hailin Liu Hongzhu Yang Zhaoyong Shi

Soil health is critical for the sustainability of tropical plantation ecosystems, However, the ecological factors driving productivity gradients remain inadequately understood. This study investigated rubber plantations on Hainan Island with varying yield levels to assess soil health and its underlying ecological mechanisms using a minimum data set (MDS) approach. Twenty-seven soil physical, chemical, and biological indicators were analyzed at two depths (0–20 cm and 20–40 cm). Principal component analysis identified seven key indicators for the MDS: soil organic matter (OM), alkaline-hydrolyzable nitrogen (AN), cation exchange capacity (CEC), dissolved organic carbon (DOC), microbial biomass phosphorus (MBP), acid phosphatase activity (ACP), and microbial diversity (Shannon-Wiener index, SHDI). The soil health indices derived from the MDS showed strong correlations with those generated from the total data set (TDS) (p < 0.001), confirming the reliability of the MDS framework. Overall, soil health levels were rated low to moderate with no significant differences across low-yield plantations (≤900 kg·ha−1), medium-yield plantations (900–1200 kg·ha−1), and high-yield plantations (≥1200 kg·ha−1)., suggesting a decoupling of soil health and rubber productivity under uniform management practices. Random forest analysis identified microbial-driven phosphorus cycling, particularly MBP and ACP, as the primary determinant of soil health across soil layers, with DOC and SHDI also contributing significantly. These findings highlight the critical role of microbial-mediated nutrient cycling in maintaining soil health in rubber plantations and suggest that current management practices prioritize short-term yields over long-term soil ecological stability. Enhancing microbial activity and increasing organic matter inputs may be essential for improving soil health and ensuring the sustainability of rubber production in tropical agroecosystems.

Agriculture doi: 10.3390/agriculture16090916

Authors: Qun Wan Shaohua Zhang Luan Zhang Guodong Yin Jiliang Ma Xiaopeng Hao Yinmei Duan Xuejun Wang Ning Xu Jie Liang Dongxu Xu Changyi Jiang Huijie Zhang

Enhancing technical efficiency in food legume production is essential, since the scope for expanding factor inputs is limited under tightening resource constraints. Higher technical efficiency improves resource allocation, ensures food supply stability, and boosts farm income. To strengthen production performance, using survey data from 817 food legume farm households in five major producing regions of China in 2024, this study employs a two-stage DEA-Tobit model to measure farmers’ technical efficiency in food legume production and to empirically identify its driving factors. The results indicate that: (1) technical efficiency in food legume production shows pronounced regional disparities and substantial within-region heterogeneity; (2) technical efficiency in food legume production improves over time, yet substantial space for efficiency gains remains relative to other staple crops; (3) farm households located at different stages of returns to production inputs show distinct production and management patterns. (4) human capital accumulation, full-time farming status, and participation in food legume cooperative economic organizations exert significant positive effects on technical efficiency. Meanwhile, planting scale exhibits a significant inverted U-shaped relationship with technical efficiency. The findings provide household-level empirical evidence to explain disparities in technical efficiency and identify pathways for improving food legume production.

Agriculture doi: 10.3390/agriculture16080914

Authors: Mahtem Teweldemedhin Mengstu Alper Taner Neluș-Evelin Gheorghiță

The combination of Fourier-transform infrared (FTIR) spectroscopy and machine learning gives a promising result in wheat variety classification. This study aimed to evaluate the contributions of distinct spectral regions and their combinations to classification performance. Out of the full raw spectra of four bread wheat varieties, namely Altindane, Cavus, Flamura-85, and Nevzatbey, 15 spectral datasets were prepared. Artificial Neural Networks (ANN), Support Vector Machines (SVM), Random Forest (RF), and K-Nearest Neighbor (KNN) models were trained and analyzed. The highest classification performance was obtained using spectral regions associated with protein and lipid bands. The highest average accuracy of 0.9895 was shown by the SVM model, while the ANN produced comparable results with lower variability. Additionally, Variable Importance in Projection (VIP) analysis identified the most influential spectral bands in the protein (Amide II, ~1542 cm−1) and carbonyl (1744–1715 cm−1) regions. These findings indicate that classification is driven by chemically meaningful features rather than purely statistical patterns. The approach followed in this study provides an insight that, in FTIR-based classification, when rigorously evaluated using nested cross-validation, spectral region selection can outweigh model complexity. This approach demonstrates strong potential for rapid and non-destructive assessment, especially for real-time applications in grain processing and automated sorting systems.

Agriculture doi: 10.3390/agriculture16080913

Authors: Chenyu Li Xinjun Wang Qingfu Liang Wenli Dong Wanzhi Zhou Yu Huang Rui Qi Shenao Wang Jiandong Sheng

Soil salinization is one of the primary forms of land degradation in arid and semi-arid regions, severely constraining agricultural production in Xinjiang’s oases. Unmanned aerial vehicle (UAV) imagery provides an effective means for precise monitoring of soil salinization, with image spatial resolution being a key factor affecting assessment accuracy. However, traditional single-scale remote sensing monitoring methods rely solely on spectral and textural features at the leaf scale (0.1 m resolution captures leaf-scale characteristics), neglecting the contribution of multi-scale features (single-row canopy scale and single-membrane-covered area scale (6-row crop canopy)) to soil salinity. For instance, 0.5–1 m reflects single-row canopy scale, while 2 m reflects single-membrane-covered area scale. Therefore, this study developed a multi-scale UAV imagery and machine learning framework to enhance soil electrical conductivity prediction accuracy. This study focuses on oasis cotton fields in Shaya County, Xinjiang. Based on UAV multispectral imagery, we resampled data to generate eight datasets at different spatial resolutions: 0.1, 0.5, 1, 1.5, 2, 2.5, 5, and 10 m. For each resolution, we calculated 21 spectral indices and 48 texture features to construct a feature set. At both single and multispatial scales, spectral indices, texture features, and their spectral-texture fusion features were constructed. Combining these with Backpropagation Neural Network (BPNN), Random Forest Regression (RFR), and Extreme Gradient Boosting (XGBoost) models, a soil EC estimation framework was developed. The impact of three feature combination schemes on cotton field soil conductivity estimation using single-scale UAV imagery was compared. The accuracy of soil EC estimation for cotton fields was compared between multi-spatial scale and single-scale UAV image features. The optimal combination strategy for a multi-spatial scale and multiple features was determined. Results indicate that combining spectral and texture features yields the highest estimation accuracy for cotton field soil electrical conductivity in single-scale analysis. Multi-spatial scale image features outperform single-scale image features in estimating cotton field soil electrical conductivity accuracy. By comparing different feature combinations, when integrating 0.5 m spatial-scale spectra (S1, EVI, DVI, NDVI, Int1, SI) with 0.1 m texture features (RE1_ent, R_cor, RE1_cor, G_hom, B_mea, R_con, NIR_con), the XGBoost model achieved the optimal prediction accuracy (R2 = 0.693, RMSE = 0.515 dS/m), outperforming the methods using multiple features at a single scale. This study developed a novel multi-scale image feature fusion technique to construct a machine learning model. This method describes the image characteristics of soil electrical conductivity at different geographical scales, providing a reference approach for the rapid and accurate prediction of soil electrical conductivity in arid regions.

Agriculture doi: 10.3390/agriculture16080912

Authors: Chang-Hyun Baeg Seung-Min Jeong Arrynda Rachma Dyasti Wardani Ji-Yoon Kim Bu-Gil Choi Young-Ho Joo Hye-Seong Kim Yong-Hyun Do Jung-Jun Park Sam-Churl Kim

This study aims to evaluate the blanching process of wasted Undaria pinnatifida as a ruminant feed source by assessing chemical compositions, in vitro nutrient digestibility, rumen fermentation characteristics, greenhouse gas emissions, and rumen microbes. The blanching process was conducted at different temperatures (15 vs. 80 vs. 90 °C) and times (2 vs. 4 min) to assess the chemical and mineral contents. Supplementation levels of U. pinnatifida (0 vs. 0.5 vs. 1 vs. 2%) were observed with the blanching process (non-blanching (NBL) vs. blanching (LOS)). Increasing blanching temperature and time decreased (p < 0.05) dry matter, crude ash, and the mineral contents, including sodium, phosphorus, and arsenic. Moreover, LOS treatment increased (p < 0.01) in vitro dry matter and neutral detergent fiber digestibility, ruminal pH, and the acetate-to-propionate ratio, but reduced (p < 0.01) CH4 (mL/g NDFD). Additionally, 2% of LOS treatment reduced the abundance of protozoa, fungi, fibrolytic microbes, methanogenic archaea, Methanobrevibacter ruminantium, Methanosarcina barkeri, and Methanosphaera stadtmanae (p < 0.01). Therefore, blanching at 80 °C for 2 min improved the nutritional profile by reducing antinutritional minerals. Subsequent in vitro fermentation suggested that supplementing the diet with 0.5–1% of LOS improved digestibility and altered fermentation, potentially reducing methane yield (per NDFD).

Agriculture doi: 10.3390/agriculture16080911

Authors: Tong Liu Shengchao Hu Xinliang Dong Boyuan Lou Wenxin Bian Hongyong Sun Jintao Wang Xiaojing Liu Chengrong Chen Yunying Fang

Biochar amendment holds promise for improving saline soils, yet its efficacy is often constrained by the uncertainty of application rates. In this study, a large field trial and associated statistical modeling were conducted to explore the mechanisms by which biochar affects wheat yield in coastal saline soils of northern China. Results showed that biochar application significantly increased soil organic carbon (SOC) content (R2 = 0.615, p < 0.001) but induced marked spatial heterogeneity across the field, with the coefficient of variation (CV) reaching 30.2%. Given the difficulty of uniformly applying biochar in the field, subplot-level SOC was used as a proxy for effective biochar distribution. Stepwise regression identified soil electrical conductivity (EC) as the dominant yield constraint (standardized coefficient = −0.69), rather than water and nutrients, and a quadratic relationship was observed between SOC and EC. Structural equation modeling (SEM) further suggested a trade-off: SOC was associated with higher yield through reduced bulk density (BD) (path coefficient = −0.603), whereas high SOC levels were also associated with increased EC under this coastal saline field setting (path coefficient = 0.243), thereby indirectly constraining growth. Consequently, the agronomic response showed a threshold-like transition: the peak wheat yield occurred at an SOC threshold of 13.87 g kg−1 (equivalent to 44.41 t ha−1), which exceeded the point of minimum salinity (11.71 g kg−1, equivalent to ~29.90 t ha−1 biochar). These results suggest that the agronomic benefit of biochar in saline soils depends on maintaining application within an estimated beneficial buffering zone.