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Role of Intercropping, Herbicides and Fungicides in Compensating for the Lack of Crop Rotation in Long-Term Continuous Cropping of Two Potato Cultivars -
Polyploidy Promotes Larger Mango Fruits with Cultivar-Specific Quality Changes -
An Overview of Bacterial Canker in Stone Fruits Caused by Different Pseudomonads: Pseudomonas syringae Species Complex and Related Species
Journal Description
Agriculture
Agriculture
is an international, peer-reviewed, open access journal published semimonthly online.
- Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
- High Visibility: indexed within Scopus, SCIE (Web of Science), GEOBASE, PubAg, AGRIS, RePEc, and other databases.
- Journal Rank: JCR - Q1 (Agronomy) / CiteScore - Q1 (Plant Science)
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 17.4 days after submission; acceptance to publication is undertaken in 2.4 days (median values for papers published in this journal in the first half of 2026).
- Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
- Companion journals for Agriculture include: Poultry, Grasses, Crops, AIPA and Grain Science.
- Journal Cluster of Agricultural Science: Agriculture, Agronomy, Horticulturae, Soil Systems, AgriEngineering, Crops, Seeds, Grasses, Agrochemicals and AI and Precision Agriculture.
Impact Factor:
4.5 (2025);
5-Year Impact Factor:
4.6 (2025)
Latest Articles
DualSlim-YOLO: A Lightweight Detection Model Based on Unmanned Aerial Vehicle Imagery for Cauliflower Seedling Identification and Growth Assessment
Agriculture 2026, 16(17), 1883; https://doi.org/10.3390/agriculture16171883 (registering DOI) - 30 Aug 2026
Abstract
Cauliflower emergence rate and seedling growth are key indicators of field conditions and varietal potential. Traditional manual surveys are unsuitable for continuous monitoring across multiple varieties. This study integrates UAV RGB imagery with the DualSlim-YOLO model to estimate cauliflower emergence rates and monitor
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Cauliflower emergence rate and seedling growth are key indicators of field conditions and varietal potential. Traditional manual surveys are unsuitable for continuous monitoring across multiple varieties. This study integrates UAV RGB imagery with the DualSlim-YOLO model to estimate cauliflower emergence rates and monitor seedling growth. Built on YOLOv11, the model incorporates a lightweight feature extraction structure and an optimized detection-scale configuration. It reduces computational complexity while maintaining detection accuracy, thereby improving the efficiency of cauliflower seedling detection. DualSlim-YOLO achieved P, R, F1-score, mAP@0.5, and mAP@0.5:0.95 of 95.35%, 96.75%, 96.05%, 98.55%, and 86.65%, respectively. The number of parameters was reduced by 38.61%, while the inference speed increased by 22.16%, demonstrating good lightweight performance. Based on this model, UAV images of 171 cauliflower varieties acquired at 7, 21, and 28 d after transplanting were used for seedling detection and emergence rate estimation. In addition, 18 time-series seedling phenotypic traits were extracted, enabling a comprehensive quantitative evaluation of emergence dynamics and early-growth performance across multiple cauliflower varieties. This method effectively screens cauliflower varieties for high emergence rates, rapid emergence, and excellent seedling growth performance. It provides technical support for high-throughput, nondestructive seedling phenotyping and early germplasm screening under field conditions.
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(This article belongs to the Special Issue Unmanned Aerial System for Crop Monitoring in Precision Agriculture)
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Open AccessArticle
The Impact of Rural Population Aging on Food Prices: Empirical Evidence from China
by
Zhen Nie, Zhenzhen Liu, Wen Li, Qiongyao Liu and Jiaxing Pang
Agriculture 2026, 16(17), 1881; https://doi.org/10.3390/agriculture16171881 (registering DOI) - 30 Aug 2026
Abstract
Stabilizing food prices is essential for ensuring food security in an aging society. Using panel data from 30 Chinese provinces spanning 2005 to 2022, this study employs a nonlinear panel model and a Spatial Durbin Model (SDM) to analyze the impact of rural
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Stabilizing food prices is essential for ensuring food security in an aging society. Using panel data from 30 Chinese provinces spanning 2005 to 2022, this study employs a nonlinear panel model and a Spatial Durbin Model (SDM) to analyze the impact of rural population aging on food prices and its spatial spillover effects. This study derives the following findings based on empirical research: (1) Rural population aging exhibits a significant inverted U-shaped relationship with food prices, with an inflection point at approximately 19.03%. Before reaching this point, rural population aging helps facilitate food prices. When the inflection point is passed, rural population aging adversely impacts food prices. This effect is significant in western regions but not in eastern and central regions. (2) Farmland transfer and agricultural technological progress significantly influence this relationship, causing the curve to reverse into a U-shaped pattern, which implies a gradual future increase in food prices. (3) Local rural population aging has a significant U-shaped spillover effect on food prices in neighboring provinces. These findings indicate that China’s rural population aging presents a complex dynamic for food price fluctuations. To address the current changes in the population and capital structure and ensure food security, the government will need to formulate forward-looking policies, further improve socialized agricultural services, and systematically optimize food production models.
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(This article belongs to the Section Agricultural Economics, Policies and Rural Management)
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Open AccessArticle
Two-Layer Conditional Prediction of Soil Electrical Conductivity Assisted by Post-Irrigation Soil Moisture Trajectories in Farmland of the Bachu Irrigation District
by
Pengfei Xu, Zhiguo Wang, Qingyong Bian and Liang Ma
Agriculture 2026, 16(17), 1880; https://doi.org/10.3390/agriculture16171880 (registering DOI) - 30 Aug 2026
Abstract
Using multi-depth continuous observations from nine farmland sites in the Bachu irrigation district, Xinjiang (November 2024–April 2026), this study developed a two-layer conditional prediction model to test whether predicted soil-moisture trajectories improve apparent electrical conductivity (EC) prediction beyond a persistence benchmark. Four prediction
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Using multi-depth continuous observations from nine farmland sites in the Bachu irrigation district, Xinjiang (November 2024–April 2026), this study developed a two-layer conditional prediction model to test whether predicted soil-moisture trajectories improve apparent electrical conductivity (EC) prediction beyond a persistence benchmark. Four prediction windows (0–1, 1–3, 3–7, and 7–15 d) were evaluated using time-forward validation under observed ERA5 forcing, paired ablation, SHAP, and post-hoc meteorological-deficit linkage analysis. For EC20, the R2 values were 0.978, 0.923, 0.727, and −1.376, with corresponding Skill values of −0.001, 0.277, 0.540, and 0.635; absolute performance at 7–15 d remained unreliable. EC40 achieved R2 of 0.943–0.987, with Skill of 0.029–0.325, and EC60 achieved R2 of 0.737–0.974, with Skill of 0.065–0.177. Ablation showed the clearest gain for EC20 at 3–7 d (ΔR2 = 0.193; ΔSkill = 0.325), whereas most other combinations showed no consistent improvement. At 0–1 d, SHAP contributions of predicted moisture trajectories to EC20, EC40, and EC60 were 39.2%, 37.6%, and 26.8%, respectively. Meteorological-deficit linkage responses varied by depth and horizon but were generally limited. Overall, trajectory benefits were depth- and horizon-dependent and reflected model dependence rather than causal water–salt mechanisms. The framework is currently applicable mainly to monitored, unfrozen post-irrigation periods without additional wetting recharge.
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(This article belongs to the Section Agricultural Water Management)
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Open AccessArticle
Effects of Strip Configurations on Canopy Photosynthetic Performance and Resource Use Efficiency of Winter-Seeded Spring Wheat Relay Intercropped with Sunflower in the Hetao Irrigation District
by
Xuede Luan, Fan Xia, Rui Chen, Mengyuan Li, Min Xie, Qi Gao and Yongping Zhang
Agriculture 2026, 16(17), 1879; https://doi.org/10.3390/agriculture16171879 (registering DOI) - 30 Aug 2026
Abstract
The traditional spring wheat–sunflower relay intercropping system in the Hetao Irrigation District of Inner Mongolia is constrained by restrictions on sowing time, relatively low resource use efficiency, and suboptimal strip configurations. Based on the winter-seeding technique for spring wheat, this study established an
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The traditional spring wheat–sunflower relay intercropping system in the Hetao Irrigation District of Inner Mongolia is constrained by restrictions on sowing time, relatively low resource use efficiency, and suboptimal strip configurations. Based on the winter-seeding technique for spring wheat, this study established an annual double-cropping system of winter-seeded spring wheat relay intercropped with sunflower. The objectives were to evaluate crop photosynthetic performance, grain yield, resource use efficiency, and economic benefits under different strip configurations and to identify a suitable strip arrangement. A two-year fixed-site field experiment was conducted from 2023 to 2025. Four winter-seeded spring wheat/sunflower relay-intercropping treatments (W9S2, W9S4, W18S2, and W18S4) were compared with sole-cropped winter-seeded spring wheat and sole-cropped sunflower. Relay intercropping increased leaf area index, SPAD values, and the net photosynthetic rate of both crops at key growth stages and also improved grain yield and resource use efficiency. Among the strip configurations, W18S2 showed the best overall performance. Its two-year average grain yields of wheat and sunflower were 13.2% and 32.2% higher, respectively, than those of the corresponding sole-cropping treatments. The land equivalent ratio and nitrogen uptake equivalent ratio of all relay-intercropping treatments were greater than 1, with the highest values observed under W18S2. In addition, W18S2 had higher light use efficiency, water use efficiency, and nitrogen partial factor productivity than the sole-cropping treatments and the other relay-intercropping configurations. The two-year average net profit of W18S2 was 46.8% and 8.0% higher than that of sole-cropped wheat and sole-cropped sunflower, respectively. Overall, the superior performance of W18S2 was associated with a more favorable canopy structure and photosynthetic performance, greater dry matter accumulation, and coordinated improvements in grain yield, resource use efficiency, and economic benefits. These findings provide a reference for the high-yield and resource-efficient cultivation of winter-seeded spring wheat relay intercropped with sunflower in the Hetao Irrigation District.
Full article
(This article belongs to the Topic Advances in Cultivation Techniques for Increasing Crop Yield)
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Open AccessArticle
Integrated Analysis of Metabolome and Transcriptome Provides New Insights into the Genetic Basis Underlying the Regulation of α-Linolenic Acid Biosynthesis in Perilla frutescens Seeds
by
Yukun Wang, Yuan Yuan, Yunna Zhu, Jianguo Liu and Hong Ye
Agriculture 2026, 16(17), 1878; https://doi.org/10.3390/agriculture16171878 (registering DOI) - 30 Aug 2026
Abstract
Perilla (Perilla frutescens) is an important oil-bearing crop rich in α-linolenic acid (ALA), and seed oil quality varies greatly among different germplasms. However, the molecular and metabolic mechanisms underlying genotypic differences in ALA accumulation remain unclear. In this study, four Perilla
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Perilla (Perilla frutescens) is an important oil-bearing crop rich in α-linolenic acid (ALA), and seed oil quality varies greatly among different germplasms. However, the molecular and metabolic mechanisms underlying genotypic differences in ALA accumulation remain unclear. In this study, four Perilla varieties with distinct seed phenotypic traits were used to investigate the variations in seed quality, metabolome, and transcriptome. Significant genotypic differences were observed in seed color, thousand-grain weight, and oil content. QO8 showed the highest seed oil content, while QS5 and QO10 exhibited relatively lower oil accumulation levels. Metabolome analysis revealed that lipid metabolism was the dominant metabolic category in Perilla seeds. Multiple differentially accumulated metabolites (DAMs), including ALA, stearic acid, traumatic acid, and 10-OPDA, displayed genotype-specific accumulation patterns. KEGG enrichment demonstrated that α-linolenic acid metabolism and unsaturated fatty acid biosynthesis were the most significantly divergent pathways among different Perilla germplasms. Transcriptome analysis identified numerous differentially expressed genes (DEGs) involved in fatty acid and ALA biosynthesis, such as FAD2, LOX, AOS, AOC, OPR, KAT, ECH, and ACOX. Integrated transcriptome and metabolome analysis further confirmed that the differential expression of structural genes altered the metabolic flux of the ALA and downstream jasmonic acid pathway, resulting in varied accumulation of core lipid intermediates. In addition, WRKY and MYB transcription factors were identified as key upstream regulators that positively or negatively modulated ALA metabolic homeostasis. This study systematically clarified the phenotypic, metabolic, and transcriptional differences in seeds of different Perilla varieties and revealed the core regulatory network of ALA biosynthesis. These findings provide valuable candidate genes and a theoretical foundation for elucidating the molecular mechanism of high ALA accumulation and quality improvement in Perilla seeds.
Full article
(This article belongs to the Special Issue Genetic Diversity Assessment and Breeding of Ornamental Crops)
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Open AccessReview
Hyperprolificacy in Modern Sow Genetics: A Review of the Neonatal, Immunological, and Welfare Costs of Increased Litter Size
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Vasileios G. Papatsiros, Georgios I. Papakonstantinou and Nikolaos Tsekouras
Agriculture 2026, 16(17), 1877; https://doi.org/10.3390/agriculture16171877 (registering DOI) - 29 Aug 2026
Abstract
Over the past two decades, genetic selection has increased average total litter size in commercial sow herds from approximately 9–10 piglets to more than 14 piglets per farrowing, an achievement that has delivered clear economic benefit but has been accompanied by a parallel
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Over the past two decades, genetic selection has increased average total litter size in commercial sow herds from approximately 9–10 piglets to more than 14 piglets per farrowing, an achievement that has delivered clear economic benefit but has been accompanied by a parallel rise in pre-weaning mortality (PWM), which is now commonly reported in the range of 12–20% and, by some indicative estimates, is trending upward even in well-managed herds. This review synthesizes the veterinary and reproductive-physiology literature on hyperprolificacy in sows, examining its downstream consequences for individual piglet birth weight, farrowing duration, colostrum access, and passive immunoglobulin G (IgG) transfer. Attention is given to the biological mechanism by which litter size dilutes colostral IgG, including vaccine-induced maternally derived antibody (MDA) against porcine reproductive and respiratory syndrome virus (PRRSV) and porcine circovirus type 2 (PCV2), and to the strength of the supporting evidence with regard to each pathogen, which differs considerably. This evidence is considerably stronger for PCV2, where maternal vaccination has a directly demonstrated effect on offspring antibody titres, than for PRRSV, where litter-size-specific dilution of maternally derived antibody has not yet been directly measured and remains an inferred, biologically plausible mechanism rather than a demonstrated one. The review further appraises management interventions including cross-fostering, split suckling, nurse sows, immunoglobulin supplementation, and structured neonatal triage, together with their documented trade-offs and considers the animal-welfare dimension of continued genetic selection for litter size. A dedicated section evaluates the current state of precision livestock farming (automated farrowing and crushing surveillance, computer-vision piglet weighing, and genomic selection for litter uniformity and robustness), concluding that these tools are promising but largely still at the research or early-adoption stage. We conclude that inadequate transfer of passive immunity behaves as an independent risk factor for mortality, separate from birth weight, and that management responses should be viewed as necessary complements to, rather than substitutes for, a re-balancing of genetic selection indices toward piglet survivability.
Full article
(This article belongs to the Special Issue Enhancing Piglet Health, Welfare, and Pre‑Weaning Survival in Hyperprolific Sow Systems)
Open AccessArticle
Non-Destructive Detection of Nutritional Elements in Fresh Tea Leaves Using Hyperspectral Technology Combined with a Multi-Stage Feature Selection Strategy
by
Yang Guo, Bo Zhou, Jianlong Li, Jiaming Chen, Zhirui Yan, Jinchi Tang and Yiyong Chen
Agriculture 2026, 16(17), 1876; https://doi.org/10.3390/agriculture16171876 (registering DOI) - 29 Aug 2026
Abstract
This study addresses two key challenges in tea nutrient analysis: the limited range of detectable nutrient elements in tea gardens and the interference caused by moisture in fresh tea leaves during spectral data acquisition. To overcome these issues, hyperspectral technology combined with effective
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This study addresses two key challenges in tea nutrient analysis: the limited range of detectable nutrient elements in tea gardens and the interference caused by moisture in fresh tea leaves during spectral data acquisition. To overcome these issues, hyperspectral technology combined with effective spectral intelligent processing algorithms was used to develop quantitative, non-destructive prediction models for four essential nutrients—nitrogen, phosphorus, potassium and carbon—in fresh tea leaves. This study utilises EPO to address the issue of moisture interference in the spectra of fresh tea leaves, and combines it with SG for spectral data processing, namely SG-EPO. Through comparative analysis with traditional pre-processing algorithms, this method was found to effectively reduce moisture interference in fresh tea leaves and enhance prediction accuracy (R2). Finally, based on a multi-stage feature selection strategy involving SG-EPO-VCPA-IRIV-SVM_RFE and SG-EPO-BOSS-SVM_RFE, and in combination with three machine learning models—XGBoost, BP and SVR—quantitative prediction models were developed. The results indicated that the R2 for nitrogen is 0.896; phosphorus, 0.954; potassium, 0.913; and carbon, 0.928. The RMSEP values for N, P, K, and C were 0.062, 0.075, 0.438, and 0.157, respectively. Using this model, nitrogen, phosphorus, potassium and carbon contents were rapidly predicted in tea leaves after the exogenous application of GABA at different concentrations, enabling an assessment of the effects of exogenous GABA application on these nutrient levels. Furthermore, the Shapley Additive Explanation method was employed to identify the feature wavelengths that had the greatest contribution to the XGBoost model, effectively explaining the information underlying the improved model predictions regarding the correlation between spectral and chemical values. Finally, the accuracy of the predictions was confirmed using 20 samples from independent data, demonstrating that the proposed model can achieve rapid, non-destructive detection of multiple nutrient elements in fresh tea leaves under in situ conditions in tea plantations.
Full article
(This article belongs to the Section Artificial Intelligence and Digital Agriculture)
Open AccessArticle
An Investigation into the Effects of Graphene and Cellulase Preparation on the Fermentation Quality and Bacterial Community Structure of Mulberry Silage
by
Yifan Chen, Zhumei Du, Yunhua Zhang, Siran Wang and Xuebing Yan
Agriculture 2026, 16(17), 1875; https://doi.org/10.3390/agriculture16171875 (registering DOI) - 29 Aug 2026
Abstract
Developing efficient utilization approaches for unconventional feed resources is critical for sustainable livestock production. Mulberry (Morus alba L.) is a woody forage resource with high nutritional value. However, its inherent lignocellulosic barrier hinders high-quality fermentation during natural ensiling without exogenous additives. In
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Developing efficient utilization approaches for unconventional feed resources is critical for sustainable livestock production. Mulberry (Morus alba L.) is a woody forage resource with high nutritional value. However, its inherent lignocellulosic barrier hinders high-quality fermentation during natural ensiling without exogenous additives. In this study, mature mulberry was ensiled under 8 treatments: a blank control (without any exogenous additives), 6 graphene treatments (G5, G10, G20, G25, G50, G75) with final graphene concentrations of 5, 10, 20, 25, 50, and 75 mg/L respectively, and a cellulase treatment (AC, Acremonium cellulolyticus). Four biological replicates were prepared for each treatment, and fermentation quality, chemical composition, and bacterial community structure were determined after 60 days of ensiling. Low-dose graphene treatments (G5 and G10) showed no significant difference in fermentation quality compared with the control. Across the G20–G75 gradient, silage pH decreased and then increased with rising graphene dosage, while lactic acid content exhibited the opposite trend. The G50 treatment achieved optimal fermentation performance, characterized by high lactic acid accumulation (2.84% DM), a low pH (4.13), and a low ammonia nitrogen/total nitrogen ratio (15.85%). The neutral detergent fiber content of the G50 treatment was comparable to that of the AC treatment. The relative abundance of Lactiplantibacillus plantarum increased with graphene concentration, with the minimum value observed in G5 and the maximum in G50. This study demonstrated that 50 mg/L graphene alone effectively alleviated the fermentation barrier of woody forage silage, with fermentation performance comparable to or even superior to that of cellulase treatment. These findings provide new insights and a theoretical basis for the application of functional nanomaterials in the livestock industry.
Full article
(This article belongs to the Section Farm Animal Production)
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Open AccessReview
Agricultural Use of Cultivated Peatlands in Hokkaido, Northern Japan: Development History, Land Subsidence, Greenhouse Gas Emissions, and Sustainable Management
by
Arata Nagatake, Mariko Shimizu and Ryusuke Hatano
Agriculture 2026, 16(17), 1874; https://doi.org/10.3390/agriculture16171874 (registering DOI) - 29 Aug 2026
Abstract
Draining peatlands for agricultural purposes accelerates land subsidence, greenhouse gas emissions, and the degradation of surrounding wetlands. To achieve sustainable peatland agriculture, land management must consider not only crop productivity but also the global environment. Peatlands account for approximately 1% of Japan’s land
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Draining peatlands for agricultural purposes accelerates land subsidence, greenhouse gas emissions, and the degradation of surrounding wetlands. To achieve sustainable peatland agriculture, land management must consider not only crop productivity but also the global environment. Peatlands account for approximately 1% of Japan’s land area, with about 61% of that 1% located in Hokkaido. This review summarizes the history of agricultural land use on peatlands in Japan and efforts to address land subsidence, greenhouse gas emissions, and the degradation of wetlands surrounding farmland, focusing primarily on case studies from Hokkaido. To allow peatlands to be used for agriculture, drainage, and mineral soil dressing have been carried out. The drying, shrinkage, consolidation, and decomposition of peat resulting from drainage cause land subsidence. Paddy rice cultivation and cyclic irrigation are land management methods that balance the mitigation of land subsidence with food production. Drainage from farmland degrades the vegetation of any surrounding wetlands. On forage-harvesting farmland, buffer zones are established between the farmland and any surrounding wetlands to mitigate the degradation of these wetlands. Lowering the groundwater level increases CO2 and N2O emissions, while raising it increases CH4 emissions. A global meta-analysis has reported that maintaining the groundwater level between −20 cm and −40 cm results in the lowest total greenhouse gas emissions. However, data on greenhouse gas emissions from peatlands used for agricultural purposes with mineral soil coverage in Japan and the reduction in such emissions are limited. In Hokkaido, the introduction of groundwater level control systems has recently been progressing; the challenge of verifying the effectiveness of subsidence control and peat decomposition control through subsurface irrigation on fields other than paddy fields remains.
Full article
(This article belongs to the Special Issue The Impact of Land Use and Climate Change on Cultivated Peatlands)
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Open AccessArticle
Life Cycle Greenhouse Gas Balances and Economic Trade-Offs of Oil Palm-Cassava Intercropping: A 25-Year Retrospective Assessment
by
Jittima Prasara-A, Pornpimon Boonkum, Charongpun Musikavong and Shabbir H. Gheewala
Agriculture 2026, 16(17), 1873; https://doi.org/10.3390/agriculture16171873 (registering DOI) - 29 Aug 2026
Abstract
Sustainable agriculture in Southeast Asia requires balancing economic viability with climate mitigation. This study investigated whether integrated intercropping can mitigate early-stage economic “dead zones” in perennial crops while simultaneously enhancing long-term carbon sequestration. A 25-year bio-economic simulation in Thailand compared three scenarios: oil
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Sustainable agriculture in Southeast Asia requires balancing economic viability with climate mitigation. This study investigated whether integrated intercropping can mitigate early-stage economic “dead zones” in perennial crops while simultaneously enhancing long-term carbon sequestration. A 25-year bio-economic simulation in Thailand compared three scenarios: oil palm monoculture (OPM), cassava monoculture (CM), and cassava-oil palm intercropping (COPI) during the initial 5-year establishment phase. Secondary national data were analyzed to quantify crop yields, carbon footprint, carbon sequestration, and inclusive income (incorporating crop revenues, self-employment wages, and potential carbon credits). Results demonstrate that COPI and OPM achieve identical accumulated carbon sequestration (−389.50 tCO2eq/ha with the same number of palm plants, with carbon footprints of 65.07 and 63.57 tCO2eq/ha, respectively (CM: 30.78 tCO2eq/ha)). Economically, COPI successfully bridges early-stage cash deficits, achieving the highest cumulative inclusive income (2.95 × 106 THB/ha) and commercial profit (2.93 ×106 THB/ha), outperforming OPM (2.78 × 106 THB/ha and 2.77 × 106 THB/ha) and CM (2.91 × 106 THB/ha for both). Although OPM yields a slightly higher net cash flow (0.77 × 106 THB/ha vs. COPI’s 0.74 × 106 THB/ha), COPI optimizes smallholder livelihood stability via retained household self-employment wages. Overall, integrated intercropping improves smallholder climate resilience and financial stability, providing a scalable model for sustainable tropical agriculture.
Full article
(This article belongs to the Section Ecosystem, Environment and Climate Change in Agriculture)
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Open AccessArticle
Standardised Livestock Manure Valorisation Potential
by
Fernando Mata, Joana Santos, Meirielly Jesus, Pedro Vaz, Gustavo Paixão, Joaquim Cerqueira and José Araújo
Agriculture 2026, 16(17), 1872; https://doi.org/10.3390/agriculture16171872 (registering DOI) - 29 Aug 2026
Abstract
Livestock manure is both an environmental burden and potential feedstock for the circular bioeconomy and sustainable biorefinery systems. This study estimated the theoretical potential of livestock manure valorisation using a balanced 50-country panel from 2000 to 2023, with illustrative scenario projections to 2050.
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Livestock manure is both an environmental burden and potential feedstock for the circular bioeconomy and sustainable biorefinery systems. This study estimated the theoretical potential of livestock manure valorisation using a balanced 50-country panel from 2000 to 2023, with illustrative scenario projections to 2050. Livestock stock data and population data were combined with species-specific coefficients to estimate manure production, standardised theoretical resource CH4 potential, standardised theoretical resource gross methane energy potential, standardised theoretical resource nitrogen and phosphorus potential, and the recoverable-CH4 CO2e value. Country rankings, species contribution analysis, k-means clustering, principal component analysis and ARIMA-based scenario analysis were used to compare manure-resource indicators. Between 2000 and 2023, total estimated manure production increased from 29.25 to 33.18 Gt, while standardised theoretical resource gross methane energy potential increased from 3396.6 to 3977.8 TWh. Standardised theoretical resource nitrogen, standardised theoretical resource phosphorus and recoverable-CH4 CO2e value also increased, whereas mean standardised theoretical resource gross methane energy potential per capita declined. In 2023, India, Brazil, China, the USA and Pakistan had the greatest total standardised theoretical resource gross methane energy potential, while Uruguay, New Zealand, Paraguay, Ireland and Argentina had the highest per capita gross methane energy potential. Cattle dominated the estimated manure resource, contributing 76.1% of total manure production. The 2050 scenario values were derived from an exploratory ARIMA trajectory based on 24 annual observations and should be interpreted as model-dependent sensitivity outputs, not as strong long-term forecasts. Under low, medium and high illustrative adoption assumptions, scenario-adjusted 2050 values were 8.04, 5.81, and 2.28 Gt CO2e, respectively. The study provides standardised theoretical manure-resource indicators for comparative screening, rather than country-specific feasibility estimates or implementation forecasts.
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(This article belongs to the Section Ecosystem, Environment and Climate Change in Agriculture)
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Open AccessArticle
Effects of Different Cultivation Treatments on Tuber Yield, Nitrogen Compound Accumulation, and Natural Storage Losses in Chip Potatoes
by
Katarzyna Brążkiewicz, Jarosław Pobereżny, Elżbieta Wszelaczyńska, Bożena Bogucka and Agnieszka Pszczółkowska
Agriculture 2026, 16(17), 1871; https://doi.org/10.3390/agriculture16171871 (registering DOI) - 29 Aug 2026
Abstract
The yield, consumer safety, and storage stability of potato tubers depend on the interaction between the genotypic characteristics of the cultivar, its intended use, the cultivation technology applied, and storage conditions. The aim of this study was to comprehensively assess the effects of
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The yield, consumer safety, and storage stability of potato tubers depend on the interaction between the genotypic characteristics of the cultivar, its intended use, the cultivation technology applied, and storage conditions. The aim of this study was to comprehensively assess the effects of seed potato dressing with a fungicide and a biostimulant, applied individually or in combination, on total and starch yield, the content of undesirable nitrogen compounds, and the storage stability of tubers. A field experiment was conducted over three growing seasons (2021–2023) at the Agricultural Experimental Station of the University of Warmia and Mazury in Olsztyn, using a randomized split-block design with three replications. The field experiment was conducted over three growing seasons (2021–2023) at the Agricultural Experiment Station in Tomaszkowo (53°42′ N, 20°26′ E). Three potato cultivars intended for chip processing were evaluated using a randomized split-block design with three replications. The storage experiment and laboratory analyses were conducted at Bydgoszcz University of Science and Technology. Analyses were performed immediately after harvest and after six months of storage under controlled conditions (8 °C and 95% relative humidity). The novelty lies in the comprehensive evaluation of the effects of fungicide and biostimulant seed treatments on potato yield, starch production, nitrate and nitrite accumulation, and storage losses. Potato genotype had a significant effect on tuber yield and the proportion of marketable tuber yield. The highest total and marketable tuber yields were obtained from the cultivar with the longest growing season. The study demonstrated variation in total tuber yield, marketable tuber yield, and the proportion of marketable tuber yield depending on the study year, reflecting differences in meteorological conditions among growing seasons. The cultivation technology did not significantly affect total tuber yield. Numerically, the highest total tuber yield (35.81 t ha−1) was recorded following the combined application of fungicide and biostimulant, while the highest marketable tuber yield was observed after treatment with fungicide (23.40 t ha−1). The potato cultivars intended for chip processing were characterized by low nitrate and nitrite contents (49.56 and 0.49 mg kg−1 FM, respectively), not exceeding 200 mg kg−1 limit for food intended for children. After six months of storage, the contents of these harmful nitrogen compounds decreased by an average of 8%, while natural storage losses remained low, averaging 3%. The effects of the cultivation factors applied during the growing season on nitrate and nitrite contents after storage were consistent with the trends observed immediately after harvest. These findings indicate that the cultivation technology evaluated in this study can be recommended for the production of potatoes intended for chip processing. However, further research involving a larger number of cultivars, including those intended for French fry processing and table use, is needed to confirm the broader applicability of these results.
Full article
(This article belongs to the Section Crop Production)
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Open AccessArticle
Scenario-Based Energy Demand Analysis of a 100 hp-Class Agricultural Tractor Using Field-Measured Workloads
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Seung-Min Baek, Namdoo Kim, Wan-Soo Kim, Hyeon-Ho Jeon and Yong-Joo Kim
Agriculture 2026, 16(17), 1870; https://doi.org/10.3390/agriculture16171870 (registering DOI) - 29 Aug 2026
Abstract
This study investigated the energy characteristics of a 100 hp-class agricultural tractor under representative agricultural operations using field-measured workload data and a scenario-based energy analysis framework. Six representative operations, including moldboard plowing, subsoiling, rotary tillage, baler operation, transport operation, and loader operation, were
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This study investigated the energy characteristics of a 100 hp-class agricultural tractor under representative agricultural operations using field-measured workload data and a scenario-based energy analysis framework. Six representative operations, including moldboard plowing, subsoiling, rotary tillage, baler operation, transport operation, and loader operation, were analyzed to evaluate operation-level energy characteristics under realistic agricultural conditions. The results showed that tractor energy demand varied substantially depending on the workload characteristics of each task. Traction-intensive operations exhibited sustained high-power demand, whereas rotary tillage showed the highest specific energy consumption (SEC) because of continuous power take-off (PTO)-driven operation. Utility-oriented operations generally exhibited lower SEC values than traction- and PTO-intensive operations. Scenario-based analysis further demonstrated that workload composition strongly influenced annual energy use (AEU). The traction-intensive scenario exhibited the highest AEU, whereas the utility-oriented scenario showed the lowest cumulative annual energy demand. Sensitivity analysis revealed that annual operating hours had an approximately proportional influence on AEU across all scenarios. The proposed framework provides a practical basis for evaluating workload-dependent tractor energy characteristics and offers useful insights for future agricultural tractor electrification strategies.
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(This article belongs to the Special Issue Design and Evaluation of Powertrain Systems for Agricultural Vehicles)
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Enabling Cooperative Dispatch of Heterogeneous Agricultural Microgrids Through Trusted-Node Coordination
by
Jue Han, Fangyuan Li, Zhengqi Li, Xuke Zuo and Yanhong Liu
Agriculture 2026, 16(17), 1869; https://doi.org/10.3390/agriculture16171869 (registering DOI) - 29 Aug 2026
Abstract
Driven by rural energy decarbonization and the electrification of agricultural production, agricultural microgrids (agri-microgrids) have become a critical paradigm for accommodating distributed renewable generation and volatile farming loads. However, agri-microgrids usually face acute cost sensitivity. Coordinated operation of autonomous agri-microgrids offers a promising
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Driven by rural energy decarbonization and the electrification of agricultural production, agricultural microgrids (agri-microgrids) have become a critical paradigm for accommodating distributed renewable generation and volatile farming loads. However, agri-microgrids usually face acute cost sensitivity. Coordinated operation of autonomous agri-microgrids offers a promising solution. Yet coordinating heterogeneous energy resources to exploit temporal complementarity while fairly allocating costs remains a key challenge. Information asymmetry, the lack of trusted node, and the computational complexity of revenue allocation impede cooperative dispatch of multi-microgrids.This paper proposes a decentralized game-theoretic framework for cooperative multi-microgrid dispatch. Firstly, a distributed node information collection algorithm is designed to acquire necessary data while preserving local privacy. Secondly, a trusted-node election method is proposed to enable reliable coalition profit calculation without external authorities or predefined centralized coordinators. Then, an enhanced Shapley value-based revenue allocation strategy, which reduces the computational complexity, is presented. Finally, case studies verify the effectiveness of the proposed algorithms in reducing operational costs and promoting green energy coordination among agri-microgrids.
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(This article belongs to the Topic Sustainable Energy Systems)
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Open AccessArticle
CitraNav: A Lightweight Navigation Method Using Spatiotemporal Information Voxel Mapping and Model Predictive Path Integral Control for Complex Orchards
by
Hao Yu, Hewen Tan, Baidong Zhao, Bowen Xia, Jiaqin Yin, Ze Chen and Huanyu Liu
Agriculture 2026, 16(17), 1868; https://doi.org/10.3390/agriculture16171868 - 28 Aug 2026
Abstract
Canopy occlusion, dynamic vegetation, structural degeneracy, and implicit terrain risks make stable localization and task-adaptive planning difficult for resource-constrained orchard robots. This paper proposes CitraNav, a lightweight navigation method for global navigation satellite system (GNSS)-denied orchards. It separates stable geometric evidence for localization
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Canopy occlusion, dynamic vegetation, structural degeneracy, and implicit terrain risks make stable localization and task-adaptive planning difficult for resource-constrained orchard robots. This paper proposes CitraNav, a lightweight navigation method for global navigation satellite system (GNSS)-denied orchards. It separates stable geometric evidence for localization from short-lived semantic evidence for planning, preventing semantic observations from accumulating in the global map. For localization, a hierarchical voxel map selects its resolution according to local structure and light detection and ranging (LiDAR) sampling characteristics, while cross-frame reliability and observability constraints suppress updates from transient vegetation and weakly observable directions. For planning, synchronized color and depth observations form a local semantic risk point cloud. A model predictive path integral (MPPI) planner combines task-dependent semantic costs with exact-footprint collision checking against currently detected obstacles. In simulation, CitraNav achieved a mean translational localization root mean square error (RMSE) of 0.075 m. Compared with geometric point-cloud planning, semantic planning reduced the collision rate by 71.4% and increased weed coverage 4.72-fold. Across 14 real-world sequences spanning farm-road, lawn, forest, and orchard environments, CitraNav achieved mean translational and heading RMSEs of 0.151 m and 1.13°, respectively, while using 72.3–87.4% fewer geometric map cells than the comparison methods. The complete perception–planning pipeline operated at 20.3–32.7 frames per second on an edge platform. These results suggest that CitraNav offers a balanced approach to localization stability, task-adaptive planning, and computational efficiency in complex orchard navigation.
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(This article belongs to the Section Artificial Intelligence and Digital Agriculture)
Open AccessArticle
Organic Amendments Regulate Heavy Metal Uptake, Greenhouse Gas Emissions and Carbon Sequestration in a Contaminated Rice–Vegetable Rotation System
by
Junjiang Li, Bo Gao, Xingfeng Zhang, Jie Zhang, Haochen Yu and Junjie Huang
Agriculture 2026, 16(17), 1867; https://doi.org/10.3390/agriculture16171867 - 28 Aug 2026
Abstract
Organic amendments (biochar, manure, and straw) are widely used as soil-applied functional materials in polluted soils; however, integrated comparative assessments within crop rotation systems remain limited. We established a rice (Oryza sativa L.: Hanyou 3015 and Yangtaiyou 128)–celery (Apium graveolens L.:
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Organic amendments (biochar, manure, and straw) are widely used as soil-applied functional materials in polluted soils; however, integrated comparative assessments within crop rotation systems remain limited. We established a rice (Oryza sativa L.: Hanyou 3015 and Yangtaiyou 128)–celery (Apium graveolens L.: Queen Celery) rotation system on farmland contaminated with heavy metals (HMs). Biochar (B), manure (M), and straw (S) were applied to assess HM dynamics, greenhouse gas emissions (CO2, CH4 and N2O), and overall system responses. B showed limited but generally stabilizing effects on crop performance and greenhouse gas emissions in the rice–celery rotation system; however, it significantly reduced Cd, Pb, and Zn uptake in celery during the later stages of the rotation. Although M enhanced soil N transformation and microbial biomass C, increased yield by 50%, and improved total system carbon sequestration, the associated risk of heavy metal accumulation during the initial rice phase should be considered in agricultural management. S increased rice and celery yields, reduced Pb and Zn accumulation in edible parts, and enhanced carbon sequestration in both crops and soil during the celery phase. These results highlight amendment-specific functions and associated trade-offs in the management of contaminated soils.
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(This article belongs to the Section Agricultural Soils)
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Research Status and Future Perspectives on Soil Microbial Respiration in Agricultural Ecosystems Under Climate Change
by
Jiarong Hou, Tongde Chen, Fengqiuli Zhang, Boxin Zeng, Xingshuai Mei and Yiping Zhao
Agriculture 2026, 16(17), 1866; https://doi.org/10.3390/agriculture16171866 - 28 Aug 2026
Abstract
Climate change is altering soil organic carbon stocks and the associated carbon fluxes of cropland ecosystems—including organic matter mineralization, microbial respiration rates, and CO2 emissions—through shifts in temperature and moisture regimes. Ecosystem respiration, the main pathway linking terrestrial carbon pools to atmospheric
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Climate change is altering soil organic carbon stocks and the associated carbon fluxes of cropland ecosystems—including organic matter mineralization, microbial respiration rates, and CO2 emissions—through shifts in temperature and moisture regimes. Ecosystem respiration, the main pathway linking terrestrial carbon pools to atmospheric CO2, directly governs the carbon source–sink balance of croplands. As integral components of the agroecosystem, soil microorganisms directly participate in ecosystem respiration and organic carbon transformation: they contribute to heterotrophic respiration through the decomposition of organic matter, while also synthesizing new organic compounds, forming microbial biomass, and promoting organic carbon stabilization, with their community composition and metabolic activity adjusting to changing environmental conditions. To synthesize research progress and clarify how the field has evolved over the past three decades, we analyzed 290 publications (1991–2025) from the Web of Science Core Collection, combining bibliometric tools (CiteSpace 7.0, VOSviewer 1.6.20) with a structured evidence synthesis to map the research landscape, knowledge structure, hotspot evolution, and mechanistic understanding of the microbial processes underlying cropland ecosystem respiration. Publication output has grown steadily, led by China (161 publications; 55.5%) and the United States (47; 16.2%), which together account for 71.7% of the sample. The knowledge structure has coalesced around five core themes (ecosystem respiration, soil microbial communities, soil organic carbon, carbon cycling, and agricultural management), corresponding to 14 major thematic clusters (Q = 0.668, S = 0.778). Rather than strictly sequential stages, these thematic areas developed largely in parallel, with a gradual shift in research emphasis over time: early work centered on fundamental carbon-cycle processes, including soil respiration flux, organic matter decomposition, and CO2 release, whereas later research increasingly emphasized microbial community structure, functional mechanisms, carbon use efficiency, soil organic carbon stabilization, carbon sequestration, fungal communities, and ecological stoichiometry. The responses of cropland respiration to climate change are context-dependent: under specific conditions their direction and magnitude may be dominated by a single limiting factor, whereas overall they emerge from the coordinated interplay of temperature, moisture, substrate supply, and agricultural management, within which microbial processes play a central but still incompletely resolved role. Future research should prioritize long-term in situ observations, multi-factor coupling experiments, and functional validation of microbial processes, and integrate microbial mechanisms into ecosystem models to strengthen predictions of cropland carbon cycling and support agricultural emission reduction, carbon sequestration, and sustainable management.
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(This article belongs to the Special Issue Assessing Ecosystem Respiration in Global Carbon Cycle: Digital Application in Agriculture)
Open AccessArticle
Energy Demand of a 50 kW Battery-Electric Tractor in Farmyard, Transport, and Grassland Operations
by
Julius Ignatz Wendling, Fredrik Regler and Heinz Bernhardt
Agriculture 2026, 16(17), 1865; https://doi.org/10.3390/agriculture16171865 - 28 Aug 2026
Abstract
Reliable data on the energy demand of battery-electric tractors under practical operating conditions remain limited. This study investigated a fully electric tractor prototype with 50 kW nominal traction power during front-loader work, trailer transport, unloaded driving, feed distribution, mowing, and windrowing. Operational and
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Reliable data on the energy demand of battery-electric tractors under practical operating conditions remain limited. This study investigated a fully electric tractor prototype with 50 kW nominal traction power during front-loader work, trailer transport, unloaded driving, feed distribution, mowing, and windrowing. Operational and sensor data were recorded via telemetry. Electrical input power was calculated for the traction, power take-off, and hydraulic drive units from the battery voltage and the respective branch currents, and energy demand was obtained by integrating the one-second power values. Energy demand varied strongly between applications. Front-loader and feeding operations were dominated by hydraulic loads, transport tasks by traction, and mowing by power take-off demand. Mean power demand ranged from approximately 6.6 kW during front-loader operations to 25.7 kW during mowing. Assuming 120 kWh of useable battery capacity, the measured front-loader demand corresponds to a theoretical operating time of about 18 h. During unloaded driving, the tractor required 1.55 kWh km−1, corresponding to a theoretical range of 77 km. Compared with diesel reference values, the measured energy demand was within or below typical ranges. Battery-electric tractors are therefore particularly promising for applications with moderate average loads, although sufficient peak-power capability remains essential.
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(This article belongs to the Section Agricultural Technology)
Open AccessArticle
Transcriptomic and Physiological Profiling of Enhanced Drought Tolerance in a Gamma-Ray-Induced Colored Wheat Mutant
by
Min Jeong Hong, Ryu Jeong Kim, So Jin Park, Chan Seop Ko and Dae Yeon Kim
Agriculture 2026, 16(17), 1864; https://doi.org/10.3390/agriculture16171864 - 28 Aug 2026
Abstract
Drought stress poses a major threat to global wheat (Triticum aestivum L.) productivity by impairing physiological processes and inducing oxidative damage. Mutation breeding provides a valuable approach to generate novel genetic variation and identify stress-tolerant germplasms. In this study, phenotypic, physiological, and
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Drought stress poses a major threat to global wheat (Triticum aestivum L.) productivity by impairing physiological processes and inducing oxidative damage. Mutation breeding provides a valuable approach to generate novel genetic variation and identify stress-tolerant germplasms. In this study, phenotypic, physiological, and transcriptomic analyses were integrated to elucidate the drought adaptation mechanisms of a gamma-ray-induced mutant wheat line, PL6, alongside its wild-type parent, PL1. Under osmotic stress and soil drought conditions, PL6 exhibited an enhanced germination rate and higher photosynthetic efficiency (Fv/Fm). Furthermore, PL6 maintained lower malondialdehyde (MDA) accumulation, which was supported by elevated activities of antioxidant enzymes including SOD, APX, and CAT. Time-series transcriptomic analysis via WGCNA and GSEA revealed that PL6 actively maintains environmental sensing, transmembrane transport, and photosynthetic processes under PEG-induced osmotic stress. Conversely, pathways associated with the cell cycle and DNA metabolism were transiently suppressed. To isolate key regulatory genes without computational bias, a multi-algorithm machine learning framework—combining Random Forest, LightGBM, and LASSO—was applied to variance-stabilizing transformed (VST) expression profiles. This approach successfully identified 45 consensus core drought-responsive genes enriched in targeted protein turnover, redox balance, cell wall restructuring, and lipid metabolism, from which ten representative candidate genes were experimentally validated via qRT-PCR. Collectively, this study demonstrates an effective analytical framework for selection of high-confidence transcripts, providing candidate targets for future targeted gene editing and molecular breeding in wheat.
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(This article belongs to the Special Issue Feature Papers in Crop Genetics, Genomics and Breeding)
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Risk Management and Resilience Enhancement of New-Type Rural Collective Economy Projects in Karst Mountainous Areas: A Case Study of Hechi, Guangxi
by
Huaqing Zhao, Jun Wen and Yining Zhou
Agriculture 2026, 16(17), 1863; https://doi.org/10.3390/agriculture16171863 - 28 Aug 2026
Abstract
To address the overlapping risks and weak agricultural resilience in karst underdeveloped mountainous areas, this study examines 110 new-type rural collective economy projects in Hechi City, Guangxi. Grounded theory is used to qualitatively identify risk factors. The analytic hierarchy process and fuzzy comprehensive
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To address the overlapping risks and weak agricultural resilience in karst underdeveloped mountainous areas, this study examines 110 new-type rural collective economy projects in Hechi City, Guangxi. Grounded theory is used to qualitatively identify risk factors. The analytic hierarchy process and fuzzy comprehensive evaluation are then combined to quantify risk indicator weights and overall risk intensity, clarify how various risks constrain agricultural resilience, and construct risk control pathways to enhance resilience. Findings reveal that risks fall into four categories—systemic, external environmental, operational and management, and financial and capital risks—encompassing ten secondary dimensions. The overall risk level is moderate but clearly stratified. Market price, capital recovery, operational and sales, investment decision-making, and internal governance are relatively high-risk dimensions. Specifically, policy support risk carries the greatest relative importance weight, while natural disaster risk has the lowest current intensity. Guided by prioritizing relatively high-risk areas for targeted reinforcement and routinely consolidating moderate risks, this paper proposes a three-dimensional strategy: targeted risk control, routine foundation consolidation, and multi-dimensional safeguards. This provides theoretical support and practical reference for precise risk governance and synergistic agricultural resilience enhancement in ecologically fragile karst regions.
Full article
(This article belongs to the Special Issue Farming System Resilience in a Changing Climate: Implications for Land Use and Sustainability)
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