Agriculture

25 pages, 6738 KB

Open AccessArticle

Scaled DEM Modeling of Rice Straw Compression: Parameter Calibration, Experimental Validation, and Efficiency Improvement

by Han Tang, Luan Liu, Fudong Xu, Changsu Xu, Shuhong Zhao and Dongtao Li

Agriculture 2026, 16(9), 1016; https://doi.org/10.3390/agriculture16091016 - 6 May 2026

Viewed by 756

Abstract

The modeling accuracy of rice straw remains limited, and discrete element method (DEM) simulations of its compression are computationally intensive. To address these challenges, this study systematically investigated the physical characteristics of rice straw and proposed an innovative DEM and parameter calibration approach. [...] Read more.

The modeling accuracy of rice straw remains limited, and discrete element method (DEM) simulations of its compression are computationally intensive. To address these challenges, this study systematically investigated the physical characteristics of rice straw and proposed an innovative DEM and parameter calibration approach. Uniaxial compression tests were conducted on individual straw stalks, and key DEM parameters were systematically calibrated using Plackett–Burman experiments, steepest ascent trials, and Central Composite design. The calibrated parameters were validated against single-straw compression tests, showing a relative error of only 1.9% between simulated and measured peak loads, indicating high model fidelity. Building on this foundation, vibration-assisted compression bench tests were performed on bulk straw, further validating the scaled-up DEM and its parameters. The evolution of normal forces and porosity during compression was analyzed by comparing experimental results with simulations, confirming the model’s accuracy in capturing straw compaction behavior. Finally, a comparison of computational efficiency between the scaled-up and original DEMs revealed that the scaled-up model reduced computation time by approximately 67.4% and 65.2%, respectively, significantly improving simulation efficiency. This study provides a robust methodology for modeling flexible agricultural fibers and establishes a foundation for efficient numerical simulation of straw compression. Full article

(This article belongs to the Section Agricultural Technology)

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19 pages, 4042 KB

Open AccessArticle

Comparative Evaluation of Machine Learning Models for Predicting Leaf Gas Exchange Traits from Hyperspectral Reflectance

by Zhipeng Ren, Haoze Zhang, Wei Cai, Zehao Liu, Tao Ma and Wenzhi Zeng

Agriculture 2026, 16(9), 1015; https://doi.org/10.3390/agriculture16091015 - 6 May 2026

Cited by 1 | Viewed by 829

Abstract

Hyperspectral remote sensing has been successfully used to retrieve parameters such as chlorophyll and nitrogen content. However, effective models for inverting dynamic physiological processes like gas exchange are lacking, and the predictive accuracy and applicable limits of such inversions remain unclear. In a [...] Read more.

Hyperspectral remote sensing has been successfully used to retrieve parameters such as chlorophyll and nitrogen content. However, effective models for inverting dynamic physiological processes like gas exchange are lacking, and the predictive accuracy and applicable limits of such inversions remain unclear. In a controlled water and nitrogen stress experiment, 350–1150 nm leaf reflectance spectra were obtained along with simultaneous measurements of 12 physiological parameters. PLSR, RF, XGBoost, and LightGBM models were constructed, and SHAP was utilized for model interpretation. The results showed that predictive accuracies could be categorized into high, medium, and low tiers (R² approximately 0.8, 0.5, and <0.3, respectively), corresponding to leaf water status and vapor pressure, E and Fm′, and g_sw and Fs. LightGBM performed best for six high-tier water-related parameters (R² = 0.75–0.81), while PLSR achieved the best performance for the medium-tier parameters E (R² = 0.49) and Fm′ (R² = 0.51). However, all models failed to predict g_sw, suggesting that the relevant signal in the 350–1150 nm range is either absent or too weak to detect in our dataset. This study outlines the practical limits of estimating dynamic photosynthetic processes using VNIR spectra, offering a reference for future sensor configuration and model development. Full article

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

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24 pages, 2041 KB

Open AccessArticle

EUDR: Identification of Agri-Environmental Risk Drivers of Financial Risks and Implementation Readiness in Eastern European Countries

by Maksym W. Sitnicki, Nataliia Prykaziuk, Diana Stelmakh, Olena Pimenowa, Sergiusz Pimenow and Marek Wigier

Agriculture 2026, 16(9), 1014; https://doi.org/10.3390/agriculture16091014 - 6 May 2026

Cited by 2 | Viewed by 869

Abstract

The EU Regulation on deforestation-free products (EUDR) introduces a new regulatory framework in which the agri-environmental characteristics of production become a prerequisite for access to the European Union market. In this paper, the EUDR is conceptualized as a regulatory framework that renders pre-existing [...] Read more.

The EU Regulation on deforestation-free products (EUDR) introduces a new regulatory framework in which the agri-environmental characteristics of production become a prerequisite for access to the European Union market. In this paper, the EUDR is conceptualized as a regulatory framework that renders pre-existing agri-environmental risk drivers economically relevant and, in cases of non-compliance, may translate them into financial risks for agricultural businesses through identifiable transmission channels. The study aims to identify these risk drivers and to assess the institutional and technical readiness of Eastern European countries to implement the Regulation’s requirements. The methodological approach combines an analysis of trade exposure to the EU market, an assessment of countries’ spatial and digital capacities, and the construction of an Institutional and Technical Readiness Index for EUDR implementation. The results indicate an asymmetric impact of the Regulation across the region, driven by cross-country differences in the availability of geospatial data, the maturity of digital traceability systems, and the effectiveness of institutional coordination. The findings further show that broad indicators of digital trade facilitation are insufficient to explain variation in readiness to comply with EUDR requirements. Overall, the study identifies the key institutional and technical constraints shaping EUDR implementation readiness and demonstrates how these constraints translate into financial risks along agricultural supply chains. Full article

(This article belongs to the Special Issue Agri-Environmental Risk Assessment and Management for Sustainable Rural Development)

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17 pages, 3082 KB

Open AccessArticle

Digitization of Field Rice Leaf Greenness (LCC 3 and 4) Using Drone-Based Remote Sensing and Machine Learning

by Piyumi P. Dharmaratne, Arachchige S. A. Salgadoe, Sujith S. Ratnayake, Danny Hunter, Upul K. Rathnayake and Aruna J. K. Weerasinghe

Agriculture 2026, 16(9), 1013; https://doi.org/10.3390/agriculture16091013 - 6 May 2026

Viewed by 726

Abstract

Precision monitoring of crops using drone or unmanned aerial vehicle (UAV) technology is rapidly growing as a climate-smart agriculture practice in rice farming systems in Sri Lanka and globally. In rice fields, the Leaf Color Chart (LCC) is traditionally used for manual comparison [...] Read more.

Precision monitoring of crops using drone or unmanned aerial vehicle (UAV) technology is rapidly growing as a climate-smart agriculture practice in rice farming systems in Sri Lanka and globally. In rice fields, the Leaf Color Chart (LCC) is traditionally used for manual comparison of a leaf to the standard LCC categories in the field to determine the fertilizer condition of the plant. However, this lacks autonomous monitoring, rapid monitoring of larger fields, scalability, and the digital transformation of the scores with sprayer drones for targeted fertilizer application. Drones with multispectral cameras could pose a greater rapid and digitalized solution for delineation of leaf color instead of LCC, in the field. Thus, this paper presents a novel attempt of digitization of conventional LCC levels 3 and 4, rice plant leaf greenness levels in the field, with classification and production of a spatial map using drone multispectral images and machine learning algorithms. The experimental setup consisted of ground sampling of LCC levels 3 and 4 from farmer fields and acquisition of drone imagery data above the field with a DJI Phantom 4 Multispectral UAV, from which fifteen vegetation indices related to crop spectra were extracted. The vegetation indices were then employed for training (70%) and testing (30%) with machine learning algorithms: Random Forest (RF), as well as SVM-linear and SVM-RBF, focusing on LCC 3–4 class classification. The results showed good classification performance, with the RF algorithm reporting a test accuracy of 98.2%, outperforming SVM-linear (82.5%) and SVM-RBF (87.5%). The RF model outputs SR, EVI, MSR, NDVI, and TCARI as feature importance indices for the classification of LCC levels 3 and 4 in the rice field. The findings of this proposed method greatly encourage the adaptation of drone technology for real-time monitoring of rice leaf fertilizer levels linked to LCC levels three and four, and spatial identification of the zones across the field. This imposes greater advancement towards climate-smart rice cultivation, targeted fertilizer application and rice field landscape pattern change analysis, underpinning the importance of field digitization. Full article

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

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25 pages, 2038 KB

Open AccessArticle

Kinetic Approach to Evaluating the Antifungal Performance of Dried Garlic for Application as Natural Agents in Food Preservation

by Haura Jilan Muthiah, Agnieszka Drożdżyńska and Jolanta Wawrzyniak

Agriculture 2026, 16(9), 1012; https://doi.org/10.3390/agriculture16091012 - 6 May 2026

Viewed by 706

Abstract

Food deterioration is largely driven by microbial activity, particularly by fungi producing mycotoxins exhibiting mutagenic and carcinogenic effects. Garlic (Allium sativum L.), valued for its antimicrobial and anti-inflammatory properties, is widely recognized as a natural food preservative; however, the high moisture content [...] Read more.

Food deterioration is largely driven by microbial activity, particularly by fungi producing mycotoxins exhibiting mutagenic and carcinogenic effects. Garlic (Allium sativum L.), valued for its antimicrobial and anti-inflammatory properties, is widely recognized as a natural food preservative; however, the high moisture content and intense respiration of freshly harvested garlic accelerate enzymatic degradation of its bioactive compounds, making post-harvest processing essential to preserve its functional properties. This study evaluated the preservative potential of convectively dried garlic (50–90 °C) by testing the antifungal activity of its extracts (6.3–0.8%) against Aspergillus parasiticus, while a modeling approach was employed to quantitatively describe this phenomenon. The antioxidant activity and rehydration capacity were also analyzed. The results demonstrated that both drying temperature and extract concentration significantly influenced fungal growth kinetics. The strongest inhibition was observed for extracts from raw garlic and garlic dried at 50 °C, whereas extracts from samples dried at 70–90 °C only partially suppressed the microbial activity. Predictive modeling accurately described fungal growth (MAE = 1.9, R² = 0.995), enabling its application in optimizing food preservation strategies. Antioxidant activity was highest in raw garlic, decreased significantly in garlic dried at 50 °C, and then increased progressively with rising drying temperature. The study highlights the need to maintain a balance in drying conditions that ensures efficient drying kinetics while preserving bioactive, functional, and antifungal properties. Full article

(This article belongs to the Section Agricultural Product Quality and Safety)

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20 pages, 4158 KB

Open AccessArticle

Effect of Cultivation Conditions on Selected Physical Properties of Fruits in New Polish Biotypes of Cornus mas L.

by Anna Bieniek, Natalia Bielska, Arkadiusz Bieniek and Ewa Dragańska

Agriculture 2026, 16(9), 1011; https://doi.org/10.3390/agriculture16091011 - 6 May 2026

Viewed by 714

Abstract

Cornelian cherry (Cornus mas L.) is a relatively underutilized orchard species that is well suited for organic cultivation. Due to the health-promoting properties of its fruit, cornelian cherry attracts increasing interest from both consumers and the processing industry. The fruit has a [...] Read more.

Cornelian cherry (Cornus mas L.) is a relatively underutilized orchard species that is well suited for organic cultivation. Due to the health-promoting properties of its fruit, cornelian cherry attracts increasing interest from both consumers and the processing industry. The fruit has a wide range of applications in the food, pharmaceutical, and cosmetic industries. This study analyzed the impact of weather conditions in northeastern Poland on the yield and physical properties of the fruits and seeds of 22 of cornelian cherry biotypes. The fruit of the new Polish biotypes differed in harvest time, yield, and morphological traits. These characteristics were influenced by regional weather conditions, including temperature and precipitation. The results confirm that temperatures in April, August, and September, as well as precipitation in September, negatively affected the yield of the evaluated cornelian cherry biotypes. Mean annual temperature was significantly positively correlated with seed weight, length, and width. These biotypes provide a strong foundation for developing new cultivars that are adapted to northeastern Poland and other regions with a similar climate. The fruits of these biotypes may be used to develop innovative food products and may have potential applications in the pharmaceutical and cosmetic industries. Full article

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

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27 pages, 1848 KB

Open AccessArticle

The Dual Impacts of Agricultural Labor Aging on Grain Production Efficiency and Eco-Efficiency in China: An Analysis of the Mitigation Mechanism of Dual-Level Social Networks

by Yankang Hu, Xinglong Yang and Lei Zhang

Agriculture 2026, 16(9), 1010; https://doi.org/10.3390/agriculture16091010 - 4 May 2026

Viewed by 1057

Abstract

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) [...] Read more.

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. Full article

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

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24 pages, 11848 KB

Open AccessArticle

Optimization of Stevia Residue Fermentation Process via Response Surface Methodology and Evaluation of Its Effects on Laying Hens

by Fumeng He, Binghua Qin, Yongqi Wang, Md. Abul Kalam Azad, Yanzhong Feng, Xiangfeng Kong and Fenglan Li

Agriculture 2026, 16(9), 1009; https://doi.org/10.3390/agriculture16091009 - 4 May 2026

Viewed by 1187

Abstract

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 [...] Read more.

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. Full article

(This article belongs to the Section Farm Animal Production)

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16 pages, 283 KB

Open AccessArticle

Alpha-Chloralose Bait Formulations and Their Laboratory and Field Efficacy in Common Vole (Microtus arvalis) Trials

by Radek Aulicky, Marcela Frankova, Tereza Radostna, Pavel Fousek, Jana Bowers, Hana Vokralova and Vaclav Stejskal

Agriculture 2026, 16(9), 1008; https://doi.org/10.3390/agriculture16091008 - 4 May 2026

Viewed by 1314

Abstract

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 [...] Read more.

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. Full article

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

20 pages, 922 KB

Open AccessArticle

The Impact and Driving Mechanism of the “Three Rights Separation” Reform on the Ecological Efficiency of Cultivated Land Use: A Case Study of China

by Weijuan Li, Jinyong Guo and Tian Xie

Agriculture 2026, 16(9), 1007; https://doi.org/10.3390/agriculture16091007 - 4 May 2026

Viewed by 870

Abstract

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 [...] Read more.

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. Full article

(This article belongs to the Special Issue Agroecological Transition in Sustainable Food Systems)

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21 pages, 2676 KB

Open AccessArticle

Split Nitrogen Application Timing Steers Rhizosphere Nitrifiers and Nitrogen Utilization in Wheat

by Shuang Guo, Guanghui Yang, Wei Wu, Shuangshuang Liu, Yang Wang, Weiming Wang, Huasen Xu and Cheng Xue

Agriculture 2026, 16(9), 1006; https://doi.org/10.3390/agriculture16091006 - 3 May 2026

Viewed by 1228

Abstract

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 [...] Read more.

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. Full article

(This article belongs to the Section Crop Production)

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29 pages, 2970 KB

Open AccessArticle

What Configurations Shape Sustainable Growth Capability in Agribusiness? Evidence from an fsQCA of A-Share-Listed Traditional Chinese Medicine Firms

by Han Chen, Yani Guo, Tingchang Zheng, Yuxuan Ji, Xinyu Wu, Shuisheng Fan and Liyu Mao

Agriculture 2026, 16(9), 1005; https://doi.org/10.3390/agriculture16091005 - 3 May 2026

Viewed by 1372

Abstract

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 [...] Read more.

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. Full article

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

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26 pages, 2936 KB

Open AccessArticle

Design, Optimization, and Field Evaluation of an Automatic Steering System for Agricultural Tractors Using Metaheuristic PID Tuning

by Ali Karamolachab, Saman Abdanan Mehdizadeh and Yiannis Ampatzidis

Agriculture 2026, 16(9), 1004; https://doi.org/10.3390/agriculture16091004 - 3 May 2026

Viewed by 2296

Abstract

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, [...] Read more.

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. Full article

(This article belongs to the Special Issue Agricultural Tractors: Evolutionary Trends, Current and Future Challenges, and Opportunities)

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21 pages, 8078 KB

Open AccessArticle

Validating a Multisensor Fusion-Based Adaptive Fuzzy Controller for Capsicum Greenhouses

by Deepashri Kogali Math, James Satheesh Kumar, Santhosh Krishnan Venkata and Bhagya Rajesh Navada

Agriculture 2026, 16(9), 1003; https://doi.org/10.3390/agriculture16091003 - 3 May 2026

Viewed by 1240

Abstract

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 [...] Read more.

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. Full article

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

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41 pages, 12036 KB

Open AccessArticle

Return Flow Compensation Reshapes Water Savings and Carbon–Water Synergy in Cold-Region Paddy Systems

by Jing Wang, Ennan Zheng, Tao Liu, Zhe Xing and Zhenjiang Si

Agriculture 2026, 16(9), 1002; https://doi.org/10.3390/agriculture16091002 - 2 May 2026

Viewed by 1250

Abstract

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 [...] Read more.

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. Full article

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

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11 pages, 1434 KB

Open AccessArticle

Efficiency of Factor Analysis-Based Selection Indices Under Varying Heritability and Trait-Environment Correlations

by Wanessa Alves Lima Paiva, Brenda Vieira de Oliveira, Camila Ferreira Azevedo, Ana Carolina Campana Nascimento, Diego Jarquin and Moyses Nascimento

Agriculture 2026, 16(9), 1001; https://doi.org/10.3390/agriculture16091001 - 2 May 2026

Viewed by 1560

Abstract

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 [...] Read more.

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. Full article

(This article belongs to the Special Issue Genetic Diversity Assessment and Phenotypic Characterization of Crops—2nd Edition)

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25 pages, 4852 KB

Open AccessArticle

Analysis of Mechanical Operation Processes and Optimization of Key Parameters with Cotton Extra-Wide Film Mulching and Sowing

by Xinyu Chen, Zenglu Shi, Xuejun Zhang, Jinshan Yan, Shaoteng Ma, Duijin Wang, Jian Chen and Yongliang Yu

Agriculture 2026, 16(9), 1000; https://doi.org/10.3390/agriculture16091000 - 1 May 2026

Viewed by 1271

Abstract

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 [...] Read more.

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. Full article

(This article belongs to the Section Agricultural Technology)

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16 pages, 396 KB

Open AccessArticle

What Drives Renewable Energy Adoption in EU Countries? Evidence on the Differential Effects of Economic, Structural and Energy Factors

by Jităreanu Andy-Felix, Mihăilă Mioara, Costuleanu Carmen-Luiza, Mărcuță Alina, Mărcuță Liviu, Tudor Valentina Constanța, Micu Marius Mihai and Arion Iulia Diana

Agriculture 2026, 16(9), 999; https://doi.org/10.3390/agriculture16090999 - 30 Apr 2026

Cited by 1 | Viewed by 1422

Abstract

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 [...] Read more.

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. Full article

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

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12 pages, 1889 KB

Open AccessArticle

Polyploidy Promotes Larger Mango Fruits with Cultivar-Specific Quality Changes

by Marcos Adrián Ruiz-Medina, Águeda M. González-Rodríguez and María José Grajal-Martín

Agriculture 2026, 16(9), 998; https://doi.org/10.3390/agriculture16090998 - 30 Apr 2026

Viewed by 1570

Abstract

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. [...] Read more.

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. Full article

(This article belongs to the Special Issue Conservation and Comprehensive Utilization of Germplasm Resources in Horticultural Crops)

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21 pages, 2975 KB

Open AccessArticle

Diversified Crop Rotation Enhances Soil Health and Microbial Diversity in Successive Maize Cropping on Sodic Soils

by Yule Sun, Haiwen Duan, Lanying Zhang, Shanshan Zhu, Qiang Li, Yang Zhou, Meiying Liu, Jicheng Tai, Yupeng Jing and Xiaofang Yu

Agriculture 2026, 16(9), 997; https://doi.org/10.3390/agriculture16090997 - 30 Apr 2026

Viewed by 1484

Abstract

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 [...] Read more.

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. Full article

(This article belongs to the Section Agricultural Soils)

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20 pages, 30829 KB

Open AccessArticle

Crop-IRM: An Intelligent Recognition and Management System for Organ Characteristics of Crop Germplasm Resources

by Jie Zhang, Chenyao Yang, Hailin Peng, Xintong Wei, Jiaqi Zou, Shiyu Wang, Zhaohong Lu, Xianming Tan and Feng Yang

Agriculture 2026, 16(9), 996; https://doi.org/10.3390/agriculture16090996 - 30 Apr 2026

Viewed by 1737

Abstract

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 [...] Read more.

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. Full article

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

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20 pages, 2155 KB

Open AccessArticle

Structural Capacity, Food Security-Related Publications, and Crop Production: A Multilevel Global Analysis Across Income Settings

by Andy A. Acosta-Monterrosa, María Cristina Florián-Pérez, Martha Elena Montoya-Vega and Ivan David Lozada-Martinez

Agriculture 2026, 16(9), 995; https://doi.org/10.3390/agriculture16090995 - 30 Apr 2026

Cited by 1 | Viewed by 1168

Abstract

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 [...] Read more.

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. Full article

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

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22 pages, 8405 KB

Open AccessArticle

Design and Research of a Quadrangular Frustum-Shaped Soil Surface Microtopography Processing Device Based on DEM

by Yan Ma, Zhihao Zhao, Shuangpeng Xie and Xiaohu Jiang

Agriculture 2026, 16(9), 994; https://doi.org/10.3390/agriculture16090994 - 30 Apr 2026

Viewed by 985

Abstract

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 [...] Read more.

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. Full article

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

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26 pages, 3478 KB

Open AccessArticle

Optimising Vegetation Buffers for Soil and Water Conservation in Dryland Cropping Systems: A Modelling Framework Integrating Causal and Process-Based Approaches

by Michael Aliyi Ame, Wei Wei and Gadisa Fayera Gemechu

Agriculture 2026, 16(9), 993; https://doi.org/10.3390/agriculture16090993 - 30 Apr 2026

Cited by 1 | Viewed by 1151

Abstract

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 [...] Read more.

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. Full article

(This article belongs to the Special Issue Soil Management and Interdisciplinary Approaches to Global Challenges)

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40 pages, 3961 KB

Open AccessSystematic Review

Trends, Challenges, and Opportunities of Cañihua (Chenopodium pallidicaule) for Functional Food Development and Sustainable Agriculture: A Bibliometric and Systematic Approach

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

Agriculture 2026, 16(9), 992; https://doi.org/10.3390/agriculture16090992 - 30 Apr 2026

Cited by 1 | Viewed by 1868

Abstract

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 [...] Read more.

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. Full article

(This article belongs to the Special Issue Strategies to Improve the Security and Nutritional Quality of Crop Species—2nd Edition)

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21 pages, 125008 KB

Open AccessArticle

Effects of the Combined Application of Nitrogen, Phosphorus, and Potassium Under Drip Irrigation on the Yield and Quality of Winter Wheat

by Yulei Jiang, Siqi Long, Yuyang Duan, Han Zhang, Guolong Gao, Jie Qiu and Changxing Zhao

Agriculture 2026, 16(9), 991; https://doi.org/10.3390/agriculture16090991 - 30 Apr 2026

Viewed by 958

Abstract

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 [...] Read more.

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. Full article

(This article belongs to the Section Crop Production)

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25 pages, 2547 KB

Open AccessArticle

Straw Retention Enables the Yield and Quality Benefits of Reduced Tillage in Winter Wheat and Spring Barley: A Long-Term Study

by Aušra Sinkevičienė, Vaclovas Bogužas, Vaida Steponavičienė, Alfredas Sinkevičius, Aušra Marcinkevičienė, Marta Wyzińska, Adam Kleofas Berbeć and Rasa Kimbirauskienė

Agriculture 2026, 16(9), 990; https://doi.org/10.3390/agriculture16090990 - 30 Apr 2026

Viewed by 873

Abstract

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 [...] Read more.

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. Full article

(This article belongs to the Section Crop Production)

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17 pages, 1481 KB

Open AccessArticle

The Effects of Two Land Creation Processes Using Modified Phosphogypsum on Soil Properties and Potato Yield and Quality

by Xiang Wang, Jianyang He, Yingmei Li, Xiuling Peng, Ke Yang, Lijuan Wang, Shundi Zhu, Muxi Bai, Yongxiang Zhou and Naiming Zhang

Agriculture 2026, 16(9), 989; https://doi.org/10.3390/agriculture16090989 - 30 Apr 2026

Viewed by 885

Abstract

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 [...] Read more.

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. Full article

(This article belongs to the Topic Sustainability and Innovation in Agriculture for the Food Production of Tomorrow)

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24 pages, 4766 KB

Open AccessReview

Visualization Analysis of Global Trends and Hotspots in Intercropping and Crop Rotation of Medicinal Plants Based on CiteSpace and VOSviewer

by Mei-Chen Zhou, Wan-Ying Guo, Zhi-Lai Zhan, Li-Ping Kang, Xiao-Lin Yang and Tie-Gui Nan

Agriculture 2026, 16(9), 988; https://doi.org/10.3390/agriculture16090988 - 30 Apr 2026

Viewed by 1094

Abstract

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 [...] Read more.

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. Full article

(This article belongs to the Section Crop Production)

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