Agriculture

23 pages, 21743 KB

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 [...] Read more.

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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29 pages, 2570 KB

Open AccessReview

Hyperprolificacy in Modern Sow Genetics: A Review of the Neonatal, Immunological, and Welfare Costs of Increased Litter Size

by 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 [...] Read more.

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)

22 pages, 4820 KB

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 [...] Read more.

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)

18 pages, 14799 KB

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 [...] Read more.

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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22 pages, 676 KB

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 [...] Read more.

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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27 pages, 1336 KB

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 [...] Read more.

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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36 pages, 6928 KB

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. [...] Read more.

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. Full article

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

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25 pages, 1254 KB

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 [...] Read more.

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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26 pages, 33974 KB

Open AccessArticle

Scenario-Based Energy Demand Analysis of a 100 hp-Class Agricultural Tractor Using Field-Measured Workloads

by 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 [...] Read more.

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. Full article

(This article belongs to the Special Issue Design and Evaluation of Powertrain Systems for Agricultural Vehicles)

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23 pages, 1980 KB

Open AccessArticle

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 [...] Read more.

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. Full article

(This article belongs to the Topic Sustainable Energy Systems)

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35 pages, 3802 KB

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 [...] Read more.

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. Full article

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

25 pages, 9910 KB

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.: [...] Read more.

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. Full article

(This article belongs to the Section Agricultural Soils)

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39 pages, 6467 KB

Open AccessReview

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 [...] Read more.

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. Full article

(This article belongs to the Special Issue Assessing Ecosystem Respiration in Global Carbon Cycle: Digital Application in Agriculture)

26 pages, 1281 KB

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 [...] Read more.

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. Full article

(This article belongs to the Section Agricultural Technology)

23 pages, 12389 KB

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 [...] Read more.

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. Full article

(This article belongs to the Special Issue Feature Papers in Crop Genetics, Genomics and Breeding)

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31 pages, 353 KB

Open AccessArticle

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 [...] Read more.

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)

33 pages, 4112 KB

Open AccessArticle

International Price Transmission in Chinese Grain Futures Markets: Determinants, Channels, and Implications for Food Security

by Zhenpeng Tang, Xiaoqiang Tang, Yi Cai and Gan Wang

Agriculture 2026, 16(17), 1862; https://doi.org/10.3390/agriculture16171862 - 28 Aug 2026

Abstract

Grain price stability is fundamental to global food security, yet the extent to which major grain futures markets contribute to international price discovery and transmit price signals across borders remains insufficiently understood. This study constructs a measurement–mechanism–pathway framework to analyze the international price [...] Read more.

Grain price stability is fundamental to global food security, yet the extent to which major grain futures markets contribute to international price discovery and transmit price signals across borders remains insufficiently understood. This study constructs a measurement–mechanism–pathway framework to analyze the international price transmission dynamics of four grain futures: wheat, rice, corn, and soybean. We apply the Diebold–Yilmaz spillover index, OLS regressions with mediation analysis, and fsQCA. All four crops display predominantly negative net spillover indices, with rice exhibiting the strongest transmission and soybean the weakest. At the domestic level, yield is associated with stronger price transmission through an inventory channel, while the effects of price regulation are asymmetric. Notably, soybean producer subsidies are unexpectedly associated with stronger rather than weaker international price transmission. At the international level, crude oil prices are associated with weaker grain price transmission primarily through the freight cost channel, and speculative capital is associated with reduced transmission capacity through tail-price episodes. Configuration analysis reveals two shared improvement routes, namely capacity building with policy support and risk containment via volatility suppression, together with four commodity-specific pathways. These findings provide systematic evidence and policy insights for mitigating grain price contagion and strengthening food system resilience. Full article

(This article belongs to the Special Issue Price Transmission and Market Dynamics in Agribusiness)

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23 pages, 2502 KB

Open AccessArticle

Property-Dependent Regulation of Phenanthrene Biodegradation by Carbon Nanomaterials in Agricultural Soil: Bioavailability and Indigenous Microbial Responses

by Meng Zhang, Jichao Song, Muqin Jiang, Kaitai Yang, Wei Sha, Liyuan Chen and Haiyun Zhang

Agriculture 2026, 16(17), 1861; https://doi.org/10.3390/agriculture16171861 - 28 Aug 2026

Abstract

Environmentally released carbon nanomaterials can alter polycyclic aromatic hydrocarbon (PAH) attenuation in agricultural soils, yet how their properties influence biodegradation in association with contaminant bioavailability and indigenous microbial responses remains unclear. This study compared nano-biochar (NBC), pristine and hydroxylated multi-walled carbon nanotubes (MWCNTs; [...] Read more.

Environmentally released carbon nanomaterials can alter polycyclic aromatic hydrocarbon (PAH) attenuation in agricultural soils, yet how their properties influence biodegradation in association with contaminant bioavailability and indigenous microbial responses remains unclear. This study compared nano-biochar (NBC), pristine and hydroxylated multi-walled carbon nanotubes (MWCNTs; 4–6 nm and >50 nm) in phenanthrene-contaminated soil, using raw biochar (RBC) as parent reference material. NBC showed the strongest promotion, reaching 68.17% biodegradation at 60 d and a maximum rate of 3.00 mg/kg/d, compared with 58.31% and 2.00 mg/kg/d in the unamended phenanthrene-spiked control. RBC exerted a weaker positive effect, suggesting biochar nanosizing favored biodegradation, accompanied by moderate bioavailability reduction and stimulation of microbial abundance, enzyme activity and diversity. In contrast, MWCNTs inhibited biodegradation, with reduced β-HPCD-extractable phenanthrene, suppressed polyphenol oxidase activity and more pronounced community shifts, while higher abundance of PAH-degradation gene nidA did not correspond to enhanced biodegradation. Pristine MWCNTs showed the lowest initial β-HPCD-extractable phenanthrene and biodegradation rates, whereas small-diameter MWCNTs most strongly limited final biodegradation extent, consistent with greater surface reactivity and intensified cell-contact stress. Hydroxylated MWCNTs exhibited weaker inhibition than pristine counterparts. These findings highlight the importance of material properties in shaping PAH fate and microbial ecology in agricultural soils. Full article

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

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28 pages, 24184 KB

Open AccessArticle

A Yield-Constrained Machine Learning Framework for Multi-Scenario Heat Hazard Assessment of Single-Cropping Rice in the Middle and Lower Reaches of the Yangtze River

by Zecheng Cui, Dan Chen, Sicheng Wei, Ying Guo, Ziyuan Zhou, Zhijun Tong, Xingpeng Liu, Jiquan Zhang and Chunli Zhao

Agriculture 2026, 16(17), 1860; https://doi.org/10.3390/agriculture16171860 - 28 Aug 2026

Abstract

Rice is a staple grain crop central to China’s food security. As the core production region of single-cropping rice, the middle and lower reaches of the Yangtze River face escalating high daytime and nighttime temperatures and compound drought–heat stress amid global warming. The [...] Read more.

Rice is a staple grain crop central to China’s food security. As the core production region of single-cropping rice, the middle and lower reaches of the Yangtze River face escalating high daytime and nighttime temperatures and compound drought–heat stress amid global warming. The accurate assessment of heat hazards is therefore pivotal for regional yield stability and disaster mitigation. Based on meteorological, remote-sensing, and soil data, together with county-level rice yield statistics from 150 major producing counties spanning 1991 to 2024 (5009 county-year calibration units), we first constructed a composite heat damage index (CHI) by integrating daytime harmful accumulated temperature (Ha), nighttime harmful accumulated temperature (HNa), and the Vegetation Health Index (VHI). We then implemented a gradient boosting decision tree (GBDT) machine learning framework in which yield loss was imposed as a physical constraint. This framework was benchmarked against convolutional neural network (CNN), random forest (RF), and support vector machine (SVM) models, with the Shapley additive explanations (SHAP) method used for attribution analysis and an independent temporal partitioning strategy applied for model validation. The results indicate the following: (1) compared to the single daytime heat damage index, the CHI elevated the yield correlation coefficient from 0.52 to 0.63; (2) with yield constraint calibration, the model attained a balanced accuracy of 92.6% and 94.0% consistency with historical disaster records; (3) regional heat hazard presents a spatial pattern of “high in inland areas and low in coastal areas,” with the heading–flowering stage as the critical sensitive period; and (4) high nighttime temperature accounts for approximately 20% of the model’s relative importance, with higher discriminative sensitivity for high-grade hazards, while the amplifying effect of water deficit on heat stress maintains a stable relative importance of around 16%. In this study, the coupled optimization of traditional assessment paradigms and data-driven approaches is achieved, providing a methodological reference for refined growth stage–specific heat hazard assessment. Its cross-regional portability and independent predictive validity require further validation. Full article

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

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