Agriculture

20 pages, 2746 KB

Open AccessArticle

Contact Ultrasound-Assisted Hot Air Drying of Sichuan Pepper: Drying Characteristics, Microstructure, and Physicochemical Quality Attributes

by Xu Liu, Kaikai Zhang, Bowen Wu, Zepeng Zang, Fangxin Wan, Xiaopeng Huang and Wenli Ma

Agriculture 2026, 16(3), 391; https://doi.org/10.3390/agriculture16030391 - 6 Feb 2026

Viewed by 403

Abstract

Sichuan Pepper is a high-value spice, but traditional drying often degrades its unique flavor and quality. This study investigates the applicability of contact ultrasound-assisted hot air drying (US-HAD) to address these issues. The effects of drying temperature (45, 50, 55 °C), ultrasonic power [...] Read more.

Sichuan Pepper is a high-value spice, but traditional drying often degrades its unique flavor and quality. This study investigates the applicability of contact ultrasound-assisted hot air drying (US-HAD) to address these issues. The effects of drying temperature (45, 50, 55 °C), ultrasonic power (48, 60, 72 W), and frequency (25, 28, 40 kHz) on drying kinetics, effective moisture diffusivity (D_eff), and physicochemical quality were systematically evaluated. Results showed that US-HAD significantly reduced drying time by 20.00–33.33% compared to hot air drying (HAD). The Page model (R² > 0.99) best described the drying kinetics. Ultrasound enhancement increased D_eff (6.55 × 10⁻⁶ to 9.63 × 10⁻⁶ m²/s) by inducing micro-channel formation and stomatal opening, as evidenced by Scanning electron microscopy (SEM). Critically, US-HAD at 50 °C, 60 W, and 28 kHz minimized color degradation (

∆ E

= 18.73), maximized the retention of total phenols and flavonoids, and increased antioxidant activity by 18.62%. GC-MS analysis confirmed better retention of volatile flavor compounds. However, the slight decrease in D_eff at higher temperatures (55 °C) suggests potential surface hardening risks. This study confirms US-HAD as a promising technology for high-quality spice processing, though further research is still needed on the cost-effectiveness of industrial-scale expansion. Full article

(This article belongs to the Section Agricultural Technology)

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25 pages, 795 KB

Open AccessArticle

Drivers of Farmers’ Adoption Intention for Soil Nutrient Analyzers: Roles of Awareness, Perceived Usefulness, and Ease of Use

by Adisak Suvittawat

Agriculture 2026, 16(3), 390; https://doi.org/10.3390/agriculture16030390 - 6 Feb 2026

Viewed by 618

Abstract

Soil nutrient analyzers are integral to precision agriculture, yet their adoption among smallholder farmers remains uneven. This study investigates the behavioral determinants of farmers’ adoption intention toward soil nutrient analyzers by extending the Technology Acceptance Model (TAM) to incorporate technology awareness as an [...] Read more.

Soil nutrient analyzers are integral to precision agriculture, yet their adoption among smallholder farmers remains uneven. This study investigates the behavioral determinants of farmers’ adoption intention toward soil nutrient analyzers by extending the Technology Acceptance Model (TAM) to incorporate technology awareness as an upstream construct. Survey data were collected from smallholder farmers with prior experience using soil nutrient analyzers in Chanthaburi, Kanchanaburi, and Udon Thani provinces in Thailand. Structural equation modeling was employed to examine the direct and indirect effects of technology awareness on adoption intention through perceived usefulness and perceived ease of use. The results reveal that technology awareness exerts a significant direct influence on adoption intention and indirect effects mediated by both perceived usefulness and ease of use. In addition, perceived ease of use positively enhances perceived usefulness, reinforcing farmers’ willingness to adopt the technology. By empirically positioning technology awareness as a foundational driver within an extended TAM framework, this study advances understanding of smallholder farmers’ technology acceptance in precision agriculture. The findings offer practical insights for policymakers, extension services, and technology developers, emphasizing awareness-building initiatives and user-centered design to accelerate the diffusion of soil nutrient analyzers among smallholder farming communities. Full article

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

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14 pages, 1185 KB

Open AccessCommunication

PLF-Mamba: Analyzing Individual Milk Yield Dynamics Under Data Scarcity Using Selective State Space Models

by Jonghyun Kim and Chae-Bong Sohn

Agriculture 2026, 16(3), 389; https://doi.org/10.3390/agriculture16030389 - 6 Feb 2026

Viewed by 432

Abstract

Real-world dairy farming datasets are often noisy (e.g., missing or corrupted sensor signals) and contain only short labeled sequences, making conventional correlation analysis and feature prioritization unreliable. We present a robust learning framework that identifies head-specific informative sensor features and predicts daily milk [...] Read more.

Real-world dairy farming datasets are often noisy (e.g., missing or corrupted sensor signals) and contain only short labeled sequences, making conventional correlation analysis and feature prioritization unreliable. We present a robust learning framework that identifies head-specific informative sensor features and predicts daily milk yield by combining reinforcement learning (RL)-based dynamic feature gating with the Mamba architecture. The RL policy samples a binary feature mask to suppress uninformative or corrupted signals to maximize prediction reward, while the Mamba predictor captures long-range dependencies with linear computational complexity. Experiments using the MMCows dataset demonstrate that the proposed framework achieves an average

R^{2}

of 0.656 and exhibits substantially lower head-wise variance than Transformer-based baselines, indicating robustness to individual heterogeneity. Ablations removing key components show that RL-based gating is essential: removing the gating module (No-RL) collapses (

R^{2} < 0

). Overall, the proposed approach provides a practical solution for digital livestock farming that mitigates noise and data scarcity while improving robustness across heads. Full article

(This article belongs to the Special Issue Machine Learning in Precision Livestock Farming: From Animal Activity Forecasting to Environmental Control)

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14 pages, 1335 KB

Open AccessArticle

Optimizing Defoliant Application Timing to Improve Boll Opening, Fiber Quality, and Yield in Summer-Sown Short-Season Cotton in Hunan, China

by Zhangshu Xie, Zhiling Rong, Yeling Qin, Aiyu Liu and Qiming Wang

Agriculture 2026, 16(3), 388; https://doi.org/10.3390/agriculture16030388 - 6 Feb 2026

Viewed by 408

Abstract

The optimal timing of chemical defoliation is a critical bottleneck in stabilizing yield and fiber quality for short-season cotton, particularly under the intensifying pressure of mechanized global production. Current practices rely heavily on population-level boll opening rates, often overlooking the physiological maturity of [...] Read more.

The optimal timing of chemical defoliation is a critical bottleneck in stabilizing yield and fiber quality for short-season cotton, particularly under the intensifying pressure of mechanized global production. Current practices rely heavily on population-level boll opening rates, often overlooking the physiological maturity of late-season bolls. Here, we investigate the trade-offs between late-boll development and defoliation-induced senescence in short-season summer cotton. Our results demonstrate that defoliation timing based on a specific heat-unit or temporal threshold after flowering—rather than simple visual indicators—is essential for maximizing biological potential. We identified a critical physiological window (43 days post-anthesis) that synergistically optimizes boll weight, seed cotton yield, and fiber micronaire. Beyond this window, delayed defoliation leads to excessive fiber coarsening and reduced spinnability, while earlier application terminates dry matter accumulation prematurely, incurring significant yield penalties. These findings provide a mechanistic basis for synchronizing reproductive maturation with mechanical harvesting requirements. By establishing a precision defoliation framework, this study offers a scalable strategy to enhance the economic sustainability and resource-use efficiency of short-season cotton systems in double-cropping regions globally. Full article

(This article belongs to the Special Issue Analysis of Crop Yield Stability and Quality Evaluation)

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26 pages, 1201 KB

Open AccessReview

Postbiotics in Poultry Nutrition: Mechanisms of Action, Health Benefits and Future Perspectives

by Lucia Biagini, Maria Chiara Muollo, Livio Galosi, Alessandra Roncarati, Danilo De Bellis and Giacomo Rossi

Agriculture 2026, 16(3), 387; https://doi.org/10.3390/agriculture16030387 - 6 Feb 2026

Viewed by 1097

Abstract

In the poultry industry, measures related to combating antimicrobial resistance have accelerated the search for safe and effective alternatives capable of sustaining production while limiting the spread of pathogens in livestock farms. Among these, postbiotics have recently emerged as a promising solution to [...] Read more.

In the poultry industry, measures related to combating antimicrobial resistance have accelerated the search for safe and effective alternatives capable of sustaining production while limiting the spread of pathogens in livestock farms. Among these, postbiotics have recently emerged as a promising solution to overcome the use of traditional in-feed additives. Defined as a preparation of inanimate microorganisms and/or their components that confer a health benefit to the host, postbiotics appear to combine biological effects with improved technological stability. Numerous studies have highlighted their beneficial effects on gut morphology, mucus production, immune modulation, microbiota composition and feed conversion ratio. Moreover, several postbiotic formulations exhibit protective effects against pathogens, suggesting a potential role in disease prevention. Overall, current evidence indicates that postbiotics are a valuable tool for improving poultry health, productivity and food safety while reducing reliance on antibiotics. This review summarises the studies on the use of postbiotics in poultry, providing a framework for their documented benefits. It also aims to highlight the limitations associated with their application and the existing knowledge gaps—particularly regarding mechanisms of action, optimal dosages, and methods of administration—in order to support standardisation and ensure reproducibility within the livestock industry. Full article

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

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23 pages, 1432 KB

Open AccessArticle

The Impact of Common Agricultural Policy Eco-Schemes on Crop Structure Simplification and Crop Diversity in Poland: A Regional Assessment

by Marek Zieliński, Sławomir Juszczyk, Sebastian Jarzebowski, Brigitte Petersen and Alejandro Guzmán Rivera

Agriculture 2026, 16(3), 386; https://doi.org/10.3390/agriculture16030386 - 6 Feb 2026

Cited by 1 | Viewed by 663 | Correction

Abstract

Enhancing crop diversity is a key pillar of the EU’s 2023–2027 CAP eco-schemes, yet Poland’s long-standing crop simplification raises doubts about the policy’s effectiveness. This study assesses the determinants of crop structure and crop diversity in Poland and evaluates whether eco-schemes generate measurable [...] Read more.

Enhancing crop diversity is a key pillar of the EU’s 2023–2027 CAP eco-schemes, yet Poland’s long-standing crop simplification raises doubts about the policy’s effectiveness. This study assesses the determinants of crop structure and crop diversity in Poland and evaluates whether eco-schemes generate measurable improvements at farm and municipal scales. A multilevel approach integrates municipality-level saturation with ecological interventions (eco-schemes, organic farming, and agri-environment–climate measures) with longitudinal data from 192 purposively selected farms across all 16 voivodeships for 2016, 2021, and 2024. Crop diversity is measured using the Shannon–Wiener index (H′), combined with indicators of specialization, farm size, and participation in CAP instruments. Spatial and temporal comparisons reveal that farms engaged in commercial animal production maintain simplified crop structures, which is associated with specialization as a dominant factor in low diversity. Maize share increased steadily from 12.4% to 16.7%, signalling ongoing homogenization, particularly in livestock-intensive regions. Contrary to earlier assumptions, smaller farms did not exhibit higher diversity, suggesting organizational constraints. At the municipal level, greater saturation with eco-schemes and organic farming was associated with higher H′ values, while areas with strong agri-environment–climate presence—often mountainous—showed lower diversity due to biophysical limits. The findings highlight structural barriers that may limit eco-scheme impacts. Full article

(This article belongs to the Special Issue Sustainable Strategies for Enhancing Farmers' Income in Rural Development)

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12 pages, 646 KB

Open AccessArticle

Unlocking the Cassava Value Chain: Assessment of Technical Needs for Sustainable Agro-Processing in Urban and Rural DRC

by Abass Adebayo, Christopher Mutungi, Simon Lukombo, Adeniyi Ogunkoya, Guelord Nsuanda, Pascaline Masheka, Rodrigue Irenge, Benjamin Munganga, Doline Matempa, Sikirou Mouritala, Najimu Adetoro and Abdul-Rasaq Adebowale

Agriculture 2026, 16(3), 385; https://doi.org/10.3390/agriculture16030385 - 6 Feb 2026

Viewed by 1157

Abstract

This study assessed the technical capacity and specific support needs of 28 small, medium, and community cassava processing centers across the Ruzizi Plain, Kinshasa, and Kongo Central Provinces of the Democratic Republic of Congo. A rapid appraisal methodology involving physical visits and direct [...] Read more.

This study assessed the technical capacity and specific support needs of 28 small, medium, and community cassava processing centers across the Ruzizi Plain, Kinshasa, and Kongo Central Provinces of the Democratic Republic of Congo. A rapid appraisal methodology involving physical visits and direct interviews with proprietors and operators was conducted between March and May 2023. Data collection focused on product types, machinery, production capacity, operational status, challenges, and quality management. The study revealed significant technical and infrastructural deficiencies. Key challenges include reliance on inefficient sun-drying, inadequate infrastructure, lack of basic utilities, obsolete machinery, poor local capacity for machine repair, minimal adherence to Good Manufacturing Practices, and inadequate product quality testing, all leading to inconsistent product quality. The study highlights urgent need for investments in efficient drying facilities, equipment upgrades, and capacity building in quality control and business management. By differentiating technical assistance needs based on enterprise scale and product type, this study provides evidence-based recommendations essential for tailoring effective and sustainable intervention strategies to transform the DRC’s cassava processing sector and enhance food security. Full article

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

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23 pages, 5549 KB

Open AccessArticle

A Precision Weeding System for Cabbage Seedling Stage

by Pei Wang, Weiyue Chen, Qi Niu, Chengsong Li, Yuheng Yang and Hui Li

Agriculture 2026, 16(3), 384; https://doi.org/10.3390/agriculture16030384 - 5 Feb 2026

Viewed by 470

Abstract

This study developed an integrated vision–actuation system for precision weeding in indoor soil bin environments, with cabbage as a case example. The system integrates lightweight object detection, 3D co-ordinate mapping, path planning, and a three-axis synchronized conveyor-type actuator to enable precise weed identification [...] Read more.

This study developed an integrated vision–actuation system for precision weeding in indoor soil bin environments, with cabbage as a case example. The system integrates lightweight object detection, 3D co-ordinate mapping, path planning, and a three-axis synchronized conveyor-type actuator to enable precise weed identification and automated removal. By integrating ECA and CBAM attention mechanisms into YOLO11, we developed the YOLO11-WeedNet model. This integration significantly enhanced the detection performance for small-scale weeds under complex lighting and cluttered backgrounds. Based on the optimal model performance achieved during experimental evaluation, the model achieved 96.25% precision, 86.49% recall, 91.10% F1-score, and a mean Average Precision (mAP@0.5) of 91.50% calculated across two categories (crop and weed). An RGB-D fusion localization method combined with a protected-area constraint enabled accurate mapping of weed spatial positions. Furthermore, an enhanced Artificial Hummingbird Algorithm (AHA⁺) was proposed to optimize the execution path and reduce the operating trajectory while maintaining real-time performance. Indoor soil bin tests showed positioning errors of less than 8 mm on the X/Y axes, depth control within ±1 mm on the Z-axis, and an average weeding rate of 88.14%. The system achieved zero contact with cabbage seedlings, with a processing time of 6.88 s per weed. These results demonstrate the feasibility of the proposed system for precise and automated weeding at the cabbage seedling stage. Full article

(This article belongs to the Special Issue Automation Strategy Using Machine Learning in Horticultural Crop Cultivation)

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24 pages, 1155 KB

Open AccessArticle

The Impact of Farmers’ Digital Capability on Large-Scale Farmland Management: Evidence from the Perspective of Farmland Inflow Behavior

by Zhiwen Xiao, Caihua Xu and Jin Yu

Agriculture 2026, 16(3), 383; https://doi.org/10.3390/agriculture16030383 - 5 Feb 2026

Cited by 1 | Viewed by 466

Abstract

This study empirically investigates the impact and underlying mechanisms of farmers’ digital capability (DC) on large-scale farmland management, utilizing micro-survey data from 1144 rural households across five provinces in China: Anhui, Henan, Shaanxi, Hebei, and Shandong. The analysis employs a double machine learning [...] Read more.

This study empirically investigates the impact and underlying mechanisms of farmers’ digital capability (DC) on large-scale farmland management, utilizing micro-survey data from 1144 rural households across five provinces in China: Anhui, Henan, Shaanxi, Hebei, and Shandong. The analysis employs a double machine learning model (DML). The results demonstrate that DC is positively related to farmers’ farmland inflow, thereby facilitating the realization of large-scale land management. Mechanism analysis reveals that farmers’ DC affects large-scale farmland management by expanding the transaction radius and improving agricultural production efficiency. Heterogeneity analysis indicates that the positive effect of DC on farmland inflow is more pronounced when farmers possess advantages in human capital, income levels, business entity characteristics, and natural endowments. This finding suggests that the impact of farmers’ DC on large-scale farmland management is not yet inclusive. Accordingly, the government should actively construct a cultivation system for farmers’ DC, build an inclusive digital service platform for farmland transfer, help farmers bridge the digital divide, and further unleash digital dividends. In future research, we will conduct follow-up surveys on fixed farmer households to expand the survey scope, optimize the measurement of key variables, and carry out comparative analyses across different institutional contexts, thereby providing a more systematic scientific basis for the development of agricultural modernization driven by digital empowerment. Full article

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

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24 pages, 525 KB

Open AccessArticle

A Deductive Ex-Ante Framework for Assessing Risks and Benefits of the EU–Mercosur Agreement for Agri-Food Producers and Processors

by Agnieszka Bezat and Włodzimierz Rembisz

Agriculture 2026, 16(3), 382; https://doi.org/10.3390/agriculture16030382 - 5 Feb 2026

Viewed by 494

Abstract

In the absence of ex-post empirical evidence on the implementation effects of the EU-Mercosur agreement, assessments of expected risks and benefits for the agri-food sector must rely on ex-ante reasoning rather than statistical identification. This paper develops a deductive ex-ante framework to assess [...] Read more.

In the absence of ex-post empirical evidence on the implementation effects of the EU-Mercosur agreement, assessments of expected risks and benefits for the agri-food sector must rely on ex-ante reasoning rather than statistical identification. This paper develops a deductive ex-ante framework to assess how partial market integration under EU–Mercosur may affect the prices and profitability of two groups: agri-food processors and agricultural producers. Methodologically, we formalize a two-market setting (final food products and agricultural raw materials) and derive comparative-statics implications for microeconomic profitability indicators that guide agents’ choices. The main propositions are as follows. First, the integration of the sourcing base for processors is likely to increase the relative profitability of processing by improving the ratio of output to raw-material inputs and, crucially, by widening the price wedge between final food prices and agricultural input prices. Second, the same mechanism implies that agricultural producers in the EU face greater downside risk, as increased competition on the raw-material market tends to depress farm-gate prices; the resulting revenue effect is unlikely to be fully offset by higher sales volumes in the short run. Third, these asymmetric effects rationalize the divergence of perceived risks and benefits across processors and farmers, even when both operate within the same integrated market environment. In addition, we highlight a complementary risk channel: market integration can affect not only price levels but also price volatility in raw-material markets, which may further increase downside risk for farms. The proposed framework provides a disciplined basis for scenario and simulation analyses relevant to agricultural and trade policy, and yields testable predictions for future ex-post evaluation. Full article

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

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15 pages, 2547 KB

Open AccessArticle

Protein-Rich Supplements Improved the Agronomic and Nutritional Quality of Stropharia rugosoannulata

by Wei-Wei Zhang, Ya-Jing Zhao, Qing-Jun Chen, Xi-Shan Gong, Ding-Gao Xu, Jia-Shu Li, Nian-Zu Li, Shu-Ning You and Guo-Qing Zhang

Agriculture 2026, 16(3), 381; https://doi.org/10.3390/agriculture16030381 - 5 Feb 2026

Viewed by 426

Abstract

Stropharia rugosoannulata is efficiently cultivated using agricultural and forestry wastes, such as sawdust and straw, and has gained popularity in China for its rich nutrition and excellent taste. However, traditional cultivation methods, which lack nitrogen supplementation, often result in low yields and poor [...] Read more.

Stropharia rugosoannulata is efficiently cultivated using agricultural and forestry wastes, such as sawdust and straw, and has gained popularity in China for its rich nutrition and excellent taste. However, traditional cultivation methods, which lack nitrogen supplementation, often result in low yields and poor fruiting body quality. This study evaluated the effects of protein-rich supplements (PRSs)—feather meal (FM), soybean meal (SM), and their mixture (FS)—on substrate properties, yield, and nutritional quality. PRS significantly increased substrate total nitrogen (TN), reduced the C/N ratio, and improved fruiting body yield, with FM achieving the highest yield (6.80 kg·m⁻²). Moreover, FM and FS significantly enhanced the contents of crude fat, crude fiber, crude protein, crude polysaccharides, total amino acids (TAAs), essential amino acids (EAAs), and umami amino acids (p < 0.05). Additionally, FS significantly enhanced antioxidant activity and 1-Diphenyl-2-picrylhydrazyl (DPPH) radical scavenging capacity of crude polysaccharides (p < 0.05). These findings demonstrate the potential of PRS to optimize S. rugosoannulata cultivation, offering a cost-effective strategy to improve commercial production. Full article

(This article belongs to the Special Issue Edible and Medicinal Mushrooms: Molecular Biology, Cultivation, Active Compounds, Preservation and Processing)

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17 pages, 5801 KB

Open AccessArticle

Assessing the Sustainability of Crop Yield and Soil Quality in a Rice (Oryza sativa L.)–Wheat (Triticum aestivum L.) System Under Climate Change: An 18-Year Fertilization and Straw Management Study

by Dandan Zhu, Zhiyi Zhang, Fulin Zhang, Ying Xia, Dongbi Liu, Xianpeng Fan, Chengfan Ni and Maoqian Wu

Agriculture 2026, 16(3), 380; https://doi.org/10.3390/agriculture16030380 - 5 Feb 2026

Viewed by 561

Abstract

Straw return plays a pivotal role in sustaining soil fertility and crop production, but the interaction between straw return and consecutive fertilizer applications on yield sustainability and soil quality under climate change are unclear. Therefore, a long-term field experiment (2005–2022) was conducted to [...] Read more.

Straw return plays a pivotal role in sustaining soil fertility and crop production, but the interaction between straw return and consecutive fertilizer applications on yield sustainability and soil quality under climate change are unclear. Therefore, a long-term field experiment (2005–2022) was conducted to examine how straw return and fertilizer application improve soil properties, increase crop production, enhance the ability to resist climatic changes, and thus improve yield sustainability in a rice (Oryza sativa L.)–wheat (Triticum aestivum L.) cropping system. This study established five treatments, including the control, NPK treatment, S treatment, NPK + 1/2S treatment, and NPK + S treatment. Compared with the control, the treatments involving chemical fertilization combined with straw return increased on average rice and wheat yield by 52.9% and 95.4%, respectively, with higher values of the sustainable yield index (SYI) and lower values of the coefficient of variance (CV) for the two crops. Moreover, the treatments that combined chemical fertilization with straw return improved soil quality by increasing soil organic matter (SOM), total N, total P, and available K contents and presented a higher soil quality index (SQI) value compared to the other three treatments. The crop yield, SYI, and apparent nutrient balance increased with increasing SQI. The SOM and AP were identified as the most crucial soil fertility indices, exerting a significant impact on crop yields. Meanwhile, precipitation emerged as the key meteorological factor restricting the yield of winter wheat. The PLS-SEM suggested that fertilizer application, climatic conditions, and soil properties strongly influenced crop yield, and the magnitude of this influence varies between rice and wheat. In conclusion, the long-term fertilization combined with straw return represents an effective strategy to safeguard the sustainability of crop yields under climate change. Full article

(This article belongs to the Section Agricultural Systems and Management)

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14 pages, 3167 KB

Open AccessArticle

Overdosing a Commercial Inoculant with Pediococcus pentosaceus, Lentilactobacillus buchneri, and Lentilactobacillus hilgardii Does Not Improve Acetic Acid Synthesis or Alfalfa Silage Aerobic Stability

by Vida Vertuš, Kristina Kljak, Mirna Mrkonjić Fuka, Manuela Zadravec and Marija Duvnjak

Agriculture 2026, 16(3), 379; https://doi.org/10.3390/agriculture16030379 - 5 Feb 2026

Viewed by 474

Abstract

During feedout, silage is exposed to air, promoting the growth of aerobic microorganisms that degrade its quality. Obligate heterofermentative lactic acid bacteria (LAB) can produce acetic acid, which enhances aerobic stability. Higher inoculation rates may further increase acid production. The goal of this [...] Read more.

During feedout, silage is exposed to air, promoting the growth of aerobic microorganisms that degrade its quality. Obligate heterofermentative lactic acid bacteria (LAB) can produce acetic acid, which enhances aerobic stability. Higher inoculation rates may further increase acid production. The goal of this study was to evaluate the aerobic stability of alfalfa silage (Medicago sativa L.) with increasing inoculant rates. Treatments included a control without inoculant (CON), the standard inoculation rate (SIC 1.0), 1.5× the standard rate (SIC 1.5), and 2.0× the standard rate (SIC 2.0). The inoculant contained Pediococcus pentosaceus, Lentilactobacillus buchneri, and Lentilactobacillus hilgardii with xylanase and beta-glucanase enzymes. Silages were prepared in five replicates per treatment (four for SIC 1.0) and aerated for seven days, during which fermentation characteristics and microbial populations were evaluated. Lactic acid was threefold higher in CON and SIC 2.0 than in SIC 1.0 and SIC 1.5 (p = 0.004), indicating unexpected homofermentative activity in SIC 2.0. All inoculated silages had greater acetic acid (38–51 g/kg DM) and propionic acid (0.83–4.05 g/kg DM) than CON (p < 0.001), but the highest acetic acid concentrations were observed in SIC 1.0 rather than at higher inoculant rates. Inoculation resulted in higher LAB counts (p < 0.001) and stable aerobic conditions; however, increasing the inoculant rate above the manufacturer’s recommendation did not enhance aerobic stability or acetic acid production. These results highlight that optimal inoculant dosing, rather than higher application rates, is critical for effective alfalfa silage preservation. Full article

(This article belongs to the Special Issue Assessment of Nutritional Value of Animal Feed Resources)

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20 pages, 393 KB

Open AccessArticle

Effects of Dietary Cauliflower Leaf Meal Supplementation on Growth Performance, Nutrient Utilization, Rumen Fermentation, and Methane Emission in Goats

by Ashvini Pundalik Bansod, Subodh Kumar Saha, Mani Saminathan, Rajeshwar Manohar Khandare, Sobharani Vineetha, Madhulina Maity, Theerthesh Mahesh and Hari Om Pandey

Agriculture 2026, 16(3), 378; https://doi.org/10.3390/agriculture16030378 - 5 Feb 2026

Viewed by 745

Abstract

Feed stress is a very critical factor impacting livestock health and productivity. One of the major contributors to quantitative feed deficiency is the continued adherence to conventional diets and feeding practices, which renders livestock populations vulnerable to environment-induced scarcity events as well as [...] Read more.

Feed stress is a very critical factor impacting livestock health and productivity. One of the major contributors to quantitative feed deficiency is the continued adherence to conventional diets and feeding practices, which renders livestock populations vulnerable to environment-induced scarcity events as well as shortages arising from supply-chain bottlenecks. These challenges occur in the face of the ever-expanding demand from a continuously growing livestock population. In a world increasingly experiencing qualitative and quantitative resource constraints due to rising demand and increasing pollutant concentrations in the environment, conventional dietary compositions require timely modification and supplementation with alternative feed ingredients. These may include the hitherto unutilized by-products of agricultural production, which are often discarded as agricultural waste, in order to mitigate the stress induced by feed availability shortfalls. Cauliflower leaf meal is one such by-product whose suitability as a feed supplement was evaluated in the present study, with results that can be reliably described as promising. The present study assessed the impact of dried cauliflower leaf meal (CLM) on growth performance, nutrient utilization, rumen fermentation, and methane emission in goats. Fifteen non-descript male goats, aged 6–8 months, were randomly allocated into three groups of five animals each and housed separately in identical pens within the same shed for the duration of the experiment. Three dietary treatments were administered: T0 (control; concentrate, hybrid Napier, and wheat straw); T20 (20% replacement of wheat bran with CLM in the concentrate, along with hybrid Napier and wheat straw); and T30 (30% replacement of wheat bran with CLM in the concentrate, along with hybrid Napier and wheat straw). The results indicated that the goats in all groups achieved a similar body-weight gain with a comparable dry-matter intake (DMI). The feed conversion ratio (FCR), nutrient digestibility, and mineral balance were also comparable across treatments. However, the methane emission rate was significantly lower (p < 0.05) in the T30 group compared with the other groups. CLM supplementation did not cause deviations in rumen pH, NH₃-N concentration, volatile fatty acid production, or bacterial and protozoal populations. The hematological parameters remained unaffected by the increased dietary inclusion of CLM, while both cell-mediated and humoral immune responses showed an improvement in the CLM-fed groups. Notable reductions in methane emission were observed in goats fed diets containing 20–30% dried CLM, highlighting the positive environmental implications of such a dietary inclusion. Full article

(This article belongs to the Special Issue Valorization of Agri-Food Waste Bioresources for Sustainable Livestock Feeding—2nd Edition)

23 pages, 721 KB

Open AccessArticle

Managing Business Models for Achieving Sustainable Transition in the Dairy Industry: A Multi-Case Analysis from Spain

by Samir Mili and Siwar Chouk

Agriculture 2026, 16(3), 377; https://doi.org/10.3390/agriculture16030377 - 5 Feb 2026

Viewed by 1077

Abstract

It is largely acknowledged that the dairy industry faces momentous challenges to make progress toward major environmental goals in balance with economic and social sustainability. This study addresses this concern by examining the processes of sustainability transition in the dairy industry in Spain. [...] Read more.

It is largely acknowledged that the dairy industry faces momentous challenges to make progress toward major environmental goals in balance with economic and social sustainability. This study addresses this concern by examining the processes of sustainability transition in the dairy industry in Spain. In particular, we analyzed the process of shifting from the classical, purely economic-driven business models toward more sustainable business models and also integrating environmental and social concerns. We provide a conceptual model for assessing sustainability transformation in the dairy industry and test the applicability of this model using a combination of evidence from the literature and primary information. Primary data were obtained through a dedicated questionnaire addressed to four dairy companies purposefully selected as illustrative case studies. The findings suggest that sustainability goals in the dairy industry can be represented appropriately through the proposed framework both at the sector and company levels, facilitating the identification of concrete business areas better suited for potential innovations and improvements in terms of sustainable value creation and delivery. The results also reveal the need for activity-specific assessments and a more-focused approach to sustainability practices, including the development of more comprehensive sustainability metrics and measurement methods specifically tailored to the dairy industry. Full article

(This article belongs to the Special Issue Building Resilience Through Sustainable Agri-Food Supply Chains)

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17 pages, 1721 KB

Open AccessArticle

Differential Responses of Soil Phosphorus Availability to Variations in Repeated Drying–Rewetting Cycles Under Different Land-Use Types in the Semi-Arid Loess Plateau of China

by Yan Hu and Meng Kong

Agriculture 2026, 16(3), 376; https://doi.org/10.3390/agriculture16030376 - 5 Feb 2026

Viewed by 394

Abstract

Soil phosphorus (P) deficiency is an important factor limiting plant growth in the semi-arid Loess Plateau region in China. The topsoils in this area undergo repeated drying–rewetting (DRW) cycles, which can influence soil P availability, a process that may become more pronounced due [...] Read more.

Soil phosphorus (P) deficiency is an important factor limiting plant growth in the semi-arid Loess Plateau region in China. The topsoils in this area undergo repeated drying–rewetting (DRW) cycles, which can influence soil P availability, a process that may become more pronounced due to climate change. However, little is known about how soil P availability responds to DRW cycles under different land-use types. To investigate this issue, we conducted three 120-day soil culture experiments to investigate the direction and magnitude of soil available P and the responses of its influencing factors to repeated DRW cycles and their frequency and intensity under three typical land-use types (cropland, grassland, and shrubland) in Gansu Province, North-western China. The results showed that the available P concentration of cropland, grassland, and shrubland soils after repeated DRW cycles significantly decreased by 8.9%, 11.5%, and 14.2%, respectively, compared with a constant humidity control. With increasing intensity of the DRW cycles, the available P concentration of grassland and shrubland soils significantly increased by 14.3% and 15.5%, respectively, while in cropland soil P significantly decreased by 10.4%. Compared with low-frequency DRW cycles, high-frequency DRW cycles significantly reduced the available P concentration by 6.4% in grassland soil and increased it by 9.8% in shrubland soil but had no significant effect in cropland soil. Overall, the responses of soil P availability to repeated DRW cycles vary among different land-use types, and the magnitude of the soil P availability response to repeated DRW cycles depended strongly on soil microorganism biomass, phosphatase activity, and the initial soil properties, being more pronounced in grassland and shrubland soils than in cropland soils. It is therefore essential to consider land-use type when studying the effects of DRW on soil P cycling in semi-arid regions, especially in the context of climate change. Full article

(This article belongs to the Section Agricultural Soils)

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26 pages, 48917 KB

Open AccessArticle

A Low-Cost Framework for 3D Phenotyping of Sugarcane via Instance Segmentation and 3D Gaussian Splatting

by Yan Chen, Xiyao Huang, Fen Liao, Hengyi Li, Jinxin Chen and Xiangyu Lu

Agriculture 2026, 16(3), 375; https://doi.org/10.3390/agriculture16030375 - 5 Feb 2026

Viewed by 538

Abstract

Sugarcane is an important economic crop, and key phenotypic traits such as plant height and leaf area play a crucial role in yield potential assessment and breeding selection. However, the quantification of these traits currently relies mainly on inefficient and destructive manual measurements, [...] Read more.

Sugarcane is an important economic crop, and key phenotypic traits such as plant height and leaf area play a crucial role in yield potential assessment and breeding selection. However, the quantification of these traits currently relies mainly on inefficient and destructive manual measurements, making it difficult to achieve continuous monitoring of plant growth. To address this limitation, this study integrates a YOLOv8x-seg instance segmentation model with 3D Gaussian Splatting (3DGS) and proposes a non-contact, high-precision 3D phenotyping method based on low-cost data acquisition using a smartphone. Multi-view RGB images are first processed using YOLOv8x-seg to extract plant foreground masks, which are then used as inputs for 3DGS-based reconstruction to generate 3D models. Plant height is automatically measured from the reconstructed models, while leaf area extraction involves a semi-automatic workflow combining image processing and manual steps. Experimental results demonstrate that the proposed approach enables accurate trait estimation, achieving a coefficient of determination (

R^{2}

) of 0.9644 for plant height estimation (evaluated on a subset of 15 plants, with a mean absolute percentage error of approximately 1.5%) and an

R^{2}

of 0.8551 for leaf area estimation (validated on 10 plants). Ground-truth plant height was measured using a telescopic measuring rod, and leaf area was determined through destructive measurement with a leaf area meter (LI-COR Model LI-3000A). Ground-truth plant height values were obtained using a telescopic measuring rod, and leaf area was determined through destructive measurement with a leaf area meter (LI-COR Model LI-3000A). This method demonstrates the feasibility of using consumer-grade devices for high-fidelity 3D phenotyping and offers an effective approach for high-throughput sugarcane breeding applications. Full article

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

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20 pages, 679 KB

Open AccessArticle

Assessing the Resilience of Regenerative Agricultural Systems to Climate Change: A Scenario-Based Systemic Analysis Framework

by Ana-Maria Nicolau, Augustin Semenescu and Petruţa Petcu

Agriculture 2026, 16(3), 374; https://doi.org/10.3390/agriculture16030374 - 5 Feb 2026

Viewed by 805

Abstract

Regenerative agriculture (RA) offers a critical pathway for climate change mitigation and adaptation, yet its implementation is often hindered by conceptual ambiguity and a lack of standardized assessment frameworks. This study employs a comparative systemic analysis, integrated with a Failure Mode and Effects [...] Read more.

Regenerative agriculture (RA) offers a critical pathway for climate change mitigation and adaptation, yet its implementation is often hindered by conceptual ambiguity and a lack of standardized assessment frameworks. This study employs a comparative systemic analysis, integrated with a Failure Mode and Effects Analysis (FMEA) framework, to evaluate the resilience of medium-sized RA farms (50–200 ha)—a segment representing the professional backbone of European agriculture—under varying infrastructural and policy conditions. By synthesizing recent standardized metrics from the global literature, the research constructs three operational contexts: Context A (Integrated High-Performance), characterized by robust support and digital monitoring; Context B (Transitional/Fragmented), reflecting partial adoption with limited resources; and Context C (Maladaptive), representing systemic barriers. The results reveal a significant “Resilience Gap” between theoretical potential and practical reality. Specifically, the analysis identifies that ecological practices alone (e.g., cover cropping, no-till) are insufficient to guarantee economic resilience without the support of Monitoring, Reporting, and Verification (MRV) systems. In transitional contexts, the inability to verify ecosystem services prevents farmers from accessing financial buffers, rendering the system vulnerable to climate shocks. This study concludes that enhancing RA resilience requires a paradigmatic shift from practice-based subsidies to outcome-based incentives, underpinned by accessible MRV technologies and standardized socio-economic indicators. Full article

(This article belongs to the Section Agricultural Systems and Management)

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16 pages, 19223 KB

Open AccessArticle

Genome-Wide Identification of the MADS-Box Family Reveals Transcriptional Regulation Underlying Heat Stress Response in Pearl Millet

by Zhiyao Zhou, Yarong Jin, Dan Yang, Chunli Mao, Jie Zhu, Wei Luo, Yun Zhong, Yuheng Li, Qinglin Li, Ruiming Yang, Haidong Yan and Linkai Huang

Agriculture 2026, 16(3), 373; https://doi.org/10.3390/agriculture16030373 - 4 Feb 2026

Viewed by 634

Abstract

Pearl millet, an African-origin crop with exceptional heat tolerance, maintains normal flowering and seed production even under extremely high temperatures. The MADS-box transcription factor family plays a central role not only in floral organs, but also in abiotic stress responses. However, its specific [...] Read more.

Pearl millet, an African-origin crop with exceptional heat tolerance, maintains normal flowering and seed production even under extremely high temperatures. The MADS-box transcription factor family plays a central role not only in floral organs, but also in abiotic stress responses. However, its specific function in pearl millet’s heat stress response remains unclear. In this study, a total of 63 MADS-box genes were identified. These genes were classified into five subfamilies and distributed across seven chromosomes, with chromosome 6 containing the highest number (12 genes). Additionally, expression analysis revealed that 53 MADS-box genes exhibited increased expression levels following heat stress under high-temperature conditions. Differential expression analysis identified five key MADS-box genes responding to heat stress. Further analysis of their expression trends using qRT-PCR revealed that the expression levels of these genes first increased and then decreased after heat stress treatment, with differences in the timing of peak expression among different genes. PMA1G07218.1 was selected for further functional characterization, which exhibited a significant response to heat stress treatment and reached a peak at 6 h. Subcellular localization analysis confirmed that the encoded protein is exclusively nuclear-localized. Through the yeast one-hybrid method (Y1H), we found that PMA1G07218.1 interacts by binding to the AG cis-acting element of F-box gene PMA1G04890.1. These findings provide valuable insight into the role of MADS-box genes in the high-temperature stress response of pearl millet, highlighting PMA1G07218.1 as a promising candidate for enhancing thermotolerance in this species. Full article

(This article belongs to the Special Issue Molecular Mechanisms and Breeding Techniques of Forage Crops)

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23 pages, 9619 KB

Open AccessArticle

Quantifying Feed-to-Manure Transfer of Heavy Metals and Nutrients for Precision Pig Production in China

by Tao Zhang, Lijun Liu, Jie Feng, Chunlai Hong, Weiping Wang, Rui Guo, Weijing Zhu, Leidong Hong, Yanlai Yao and Fengxiang Zhu

Agriculture 2026, 16(3), 372; https://doi.org/10.3390/agriculture16030372 - 4 Feb 2026

Viewed by 563

Abstract

Intensive pig production systems in China face dual challenges of heavy metal (HM) contamination and nutrient overloading from manure. However, stage-specific quantitative relationships between diet and excretion remain poorly characterized, hindering targeted mitigation. To address this, we conducted a comprehensive farm survey in [...] Read more.

Intensive pig production systems in China face dual challenges of heavy metal (HM) contamination and nutrient overloading from manure. However, stage-specific quantitative relationships between diet and excretion remain poorly characterized, hindering targeted mitigation. To address this, we conducted a comprehensive farm survey in the southern water network region—a major pig production hub in China—collecting 93 paired feed and manure samples from piglets, finishing pigs, and sows across 32 large-, medium-, and small-scale farms. The results revealed that essential trace elements (Cu, Zn, Fe, Mn) in feed exceeded safety guidelines by 3–19-fold, while toxic metals (As, Hg, Pb, Cd, Cr) remained below hygienic limits. Notably, Cu and Zn concentrations in manure significantly surpassed organic fertilizer standards, with piglet manure showing the highest exceedance rates (69–91%). Strong linear correlations (Pearson’s r = 0.360–0.766) were found between feed additives (Cu, Zn, As, Pb, Cd, Cr) and their excretion in manure, with Cu and Zn exhibiting the strongest relationships, especially in piglets. Feed crude protein (CP) and phosphorus (P) levels positively influenced nitrogen (N) and P excretion (r = 0.389–0.860), particularly in finishing pigs. Scenario analysis demonstrated that aligning Cu and Zn supplementation with safety guidelines could reduce HM excretion by 50–67%, while low-CP diets and precision P feeding lowered N and P losses by 10.2–10.8% and reduced feed costs by 4.1%. These findings highlight the potential of dietary interventions to mitigate environmental risks without compromising productivity, offering actionable strategies for sustainable pig production and revised feed regulations. This study provides quantitative, stage-specific evidence linking feed formulation to excretion patterns, addressing critical knowledge gaps in feed-to-manure transfer mechanisms and supporting the development of precision feeding standards and integrated manure management systems to decouple livestock intensification from environmental degradation. Full article

(This article belongs to the Section Farm Animal Production)

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17 pages, 3304 KB

Open AccessArticle

Research on Marginal Effects of Dry Matter Accumulation and Extinction Coefficient in Maize–Soybean Intercropping Composite Population

by Shiwei Yang, Jiying Sun, Zhaoran Wang, Jie Li, Mao Xu and Guixin Fan

Agriculture 2026, 16(3), 371; https://doi.org/10.3390/agriculture16030371 - 4 Feb 2026

Viewed by 466

Abstract

Maize–soybean intercropping can improve land use efficiency and increase crop yields, thereby contributing to sustainable agricultural development. This study aimed to investigate the marginal effects of intercropping on dry matter accumulation and the extinction coefficient (K) of maize and soybean canopies, thereby providing [...] Read more.

Maize–soybean intercropping can improve land use efficiency and increase crop yields, thereby contributing to sustainable agricultural development. This study aimed to investigate the marginal effects of intercropping on dry matter accumulation and the extinction coefficient (K) of maize and soybean canopies, thereby providing theoretical guidance for efficient resource utilization and the realization of high-yield and high-efficiency maize–soybean intercropping systems. This experiment employed maize variety Jincheng 316 and soybean variety Heinong 531. Two intercropping treatments (S4M4: four rows soybean alternating with four rows maize; S6M4: six rows soybean alternating with four rows maize) and two sole cropping controls (M: sole maize; S: sole soybean) tested the marginal effects of different intercropping patterns on crop dry matter accumulation, SPAD, and K. Combined with analyses of yield, land equivalent ratio (LER), and intercropping advantage (IA), we determined the optimal row ratio configuration for intercropping. The results showed that, compared with monocropped maize, the leaf SPAD at the R1 stage and grain dry matter accumulation at the R6 stage under S4M4 and S6M4 treatments increased by 17.28%/20.12% and 8.07%/5.35%, respectively, while K values decreased by 21.80% and 14.37%. For soybean, relative to monocropping, the R4 leaf SPAD and R8 grain dry matter accumulation under S4M4 and S6M4 were elevated by 23.87%/19.40% and 26.66%/13.56%, respectively, with corresponding K values reductions of 21.94% and 21.82%. Moreover, S4M4 exhibited a 51.67% higher IA and a 9.48% higher LER than S6M4. In summary, maize–soybean intercropping significantly boosts dry matter accumulation and resource use efficiency, with the S4M4 configuration exhibiting the most distinct advantages. Full article

(This article belongs to the Section Crop Production)

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24 pages, 831 KB

Open AccessArticle

Genetic Diversity and Dissection of Agronomic Traits in Durum Wheat Grown Under Contrasting Environments in Algeria

by Hassiba Bekaddour, Nadjat Benkherbache, Justyna Milc, Giovanni Caccialupi, Federica Caradonia, Enrico Francia, Anna Paola Minervini, Chafika Djenadi, Abdelkader Benbelkacem and Francesca Taranto

Agriculture 2026, 16(3), 370; https://doi.org/10.3390/agriculture16030370 - 4 Feb 2026

Viewed by 825

Abstract

Durum wheat productivity in Mediterranean regions faces growing challenges from drought and heat stress. Understanding the genetic architecture of diverse germplasm is therefore essential to support pre-breeding efforts and enhance stress adaptation. In this context, 125 durum wheat genotypes were evaluated for agro-morphological [...] Read more.

Durum wheat productivity in Mediterranean regions faces growing challenges from drought and heat stress. Understanding the genetic architecture of diverse germplasm is therefore essential to support pre-breeding efforts and enhance stress adaptation. In this context, 125 durum wheat genotypes were evaluated for agro-morphological traits across two contrasting Algerian locations over two growing seasons. A subset of 94 genotypes, selected on the basis of phenotypic characterization, was genotyped using the Illumina 7K SNP array. Population structure analysis revealed two to four subgroups, with linkage disequilibrium decaying at 4.09 Mb. Genome-wide association analysis identified 27 distinct significant SNPs associated with eight traits, with most associations detected for spike length, thousand-kernel weight, and plant height. The marker TGWA25K-TG0010 on chromosome 4A showed pleiotropic effects on plant height and peduncle length and co-localized with the Dwarf8 and gibberellic-acid-insensitive genes. Additionally, wsnp_Ex_c2033_3814035 on chromosome 2A was associated with heading earliness and the number of fertile spikelets per spike, and wsnp_Ku_c51039_56457361 on chromosome 5A with plant height and peduncle length in a single site and season. Several other environment-specific associations were also identified. These results support future studies in which the identified markers may be deployed in breeding strategies aimed at improving yield stability and stress adaptability in durum wheat under Algerian conditions. Full article

(This article belongs to the Special Issue Breeding for Abiotic Stress Resistance in Crops: Biotechnology and Bioinformatics)

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14 pages, 342 KB

Open AccessArticle

Analysis of Sustainable Vegetable Production in Guangdong Province, China, Based on the Carbon Footprint

by Xialing Chu, Linxiu Zheng, Jie Li and Pengfei Cheng

Agriculture 2026, 16(3), 369; https://doi.org/10.3390/agriculture16030369 - 4 Feb 2026

Cited by 2 | Viewed by 503

Abstract

Climate change induced by greenhouse gas emissions is currently one of the most important challenges of the world. Against this backdrop, we deeply explore the temporal variation characteristics of vegetable production in Guangdong Province, a major province of China from the carbon footprint [...] Read more.

Climate change induced by greenhouse gas emissions is currently one of the most important challenges of the world. Against this backdrop, we deeply explore the temporal variation characteristics of vegetable production in Guangdong Province, a major province of China from the carbon footprint perspective. The aim is to promote the reduction of greenhouse gas emissions from agricultural production and carbon sequestration, as well as sustainable agricultural development. We primarily adopted the carbon emission coefficient provided by Intergovernmental Panel on Climate Change and utilized data from the China Rural Statistical Yearbook and the Guangdong Rural Statistical Yearbook from 1990 to 2022 to analyze the changing characteristics of the carbon footprint of vegetable production in Guangdong Province. In addition, we used the grey prediction model GM (1, 1) to estimate the parameters and test the residual. Then, the carbon emission of vegetable production in Guangdong province was predicted from 2023 to 2060. The research results show that agricultural input is the largest source of carbon emissions, accounting for 51.99–66.55%, followed by farmland soil utilization (33.45–48.01%). Within agricultural input, fertilizers, pesticides, and mulching films are the main sources of carbon emissions. Based on the data from 2011 to 2022, it is predicted that the net carbon emissions of vegetable production in Guangdong Province will continue to decline after 2022. Based on the above findings, it is suggested to promote the sustainable development of the vegetable industry by increasing policy support for the R&D and promotion of green and low-carbon technologies and green vegetable production, reducing agricultural input, and promoting the formation of the low-carbon production concept. Full article

(This article belongs to the Special Issue Agriculture and Global Climate Change: Threats, Challenges and Adaptations)

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19 pages, 2946 KB

Open AccessArticle

LGH-YOLOv12n: Latent Diffusion Inpainting Data Augmentation and Improved YOLOv12n Model for Rice Leaf Disease Detection

by Shaowei Mi, Cheng Li, Kui Fang, Xinghui Zhu and Gang Chen

Agriculture 2026, 16(3), 368; https://doi.org/10.3390/agriculture16030368 - 4 Feb 2026

Cited by 1 | Viewed by 643

Abstract

Detecting rice leaf diseases in real-world field environments remains challenging due to varying lesion sizes, diverse lesion morphologies, complex backgrounds, and the limited availability of high-quality annotated datasets. Existing detection models often suffer from performance degradation under these conditions, particularly when training data [...] Read more.

Detecting rice leaf diseases in real-world field environments remains challenging due to varying lesion sizes, diverse lesion morphologies, complex backgrounds, and the limited availability of high-quality annotated datasets. Existing detection models often suffer from performance degradation under these conditions, particularly when training data lack sufficient diversity and structural realism. To address these challenges, this paper proposes a Latent Diffusion Inpainting (LDI) data augmentation method and an improved lightweight detection model, LGH-YOLOv12n. Unlike conventional diffusion-based augmentation methods that generate full images or random patches, LDI performs category-aware latent inpainting, synthesizing realistic lesion patterns by jointly conditioning on background context and disease categories, thereby enhancing data diversity while preserving scene consistency. Furthermore, LGH-YOLOv12n improves upon the YOLOv12n baseline by introducing GSConv in the backbone to reduce channel redundancy and enhance lesion localization, and integrating Hierarchical Multi-head Attention (HMHA) into the neck network to better distinguish disease features from complex field backgrounds. Experimental results demonstrate that LGH-YOLOv12n achieves an F1 of 86.1% and an mAP@50 of 88.3%, outperforming the YOLOv12n model trained without data augmentation by 3.3% and 5.0%, respectively. Moreover, when trained on the LDI-augmented dataset, LGH-YOLOv12n consistently outperforms YOLOv8n, YOLOv10n, YOLOv11n, and YOLOv12n, with mAP@50 improvements of 4.6%, 5.2%, 1.9%, and 2.1%, respectively. These results indicate that the proposed LDI augmentation and LGH-YOLOv12n model provide an effective and robust solution for rice leaf disease detection in complex field environments. Full article

(This article belongs to the Topic Digital Agriculture, Smart Farming and Crop Monitoring)

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22 pages, 6723 KB

Open AccessArticle

An Enhanced SegNeXt with Adaptive ROI for a Robust Navigation Line Extraction in Multi-Growth-Stage Maize Fields

by Yuting Zhai, Zongmei Gao, Jian Li, Yang Zhou and Yanlei Xu

Agriculture 2026, 16(3), 367; https://doi.org/10.3390/agriculture16030367 - 4 Feb 2026

Viewed by 462

Abstract

Navigation line extraction is essential for visual navigation in agricultural machinery, yet existing methods often perform poorly in complex environments due to challenges such as weed interference, broken crop rows, and leaf adhesion. To enhance the accuracy and robustness of crop row centerline [...] Read more.

Navigation line extraction is essential for visual navigation in agricultural machinery, yet existing methods often perform poorly in complex environments due to challenges such as weed interference, broken crop rows, and leaf adhesion. To enhance the accuracy and robustness of crop row centerline identification, this study proposes an improved segmentation model based on SegNeXt with integrated adaptive region of interest (ROI) extraction for multi-growth-stage maize row perception. Improvements include constructing a Local module via pooling layers to refine contour features of seedling rows and enhance complementary information across feature maps. A multi-scale fusion attention (MFA) is also designed for adaptive weighted fusion during decoding, improving detail representation and generalization. Additionally, Focal Loss is introduced to mitigate background dominance and strengthen learning from sparse positive samples. An adaptive ROI extraction method was also developed to dynamically focus on navigable regions, thereby improving efficiency and localization accuracy. The outcomes revealed that the proposed model achieves a segmentation accuracy of 95.13% and an IoU of 93.86%. The experimental results show that the proposed algorithm achieves a processing speed of 27 frames per second (fps) on GPU and 16.8 fps on an embedded Jetson TX2 platform. This performance meets the real-time requirements for agricultural machinery operations. This study offers an efficient and reliable perception solution for vision-based navigation in maize fields. Full article

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

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18 pages, 1473 KB

Open AccessArticle

Grain Quality and Stability of Advanced Barley Lines and Local Landraces in Mediterranean Conditions

by Vasileios Greveniotis, Elisavet Bouloumpasi, Adriana Skendi, Stylianos Zotis, Dimitrios Kantas and Constantinos G. Ipsilandis

Agriculture 2026, 16(3), 366; https://doi.org/10.3390/agriculture16030366 - 4 Feb 2026

Cited by 2 | Viewed by 680

Abstract

Barley (Hordeum vulgare L.) seed quality traits were evaluated to investigate the relative genetic and environmental contributions to their variation, the stability of genotypes across environments, and the interrelationships among traits. Fifteen genotypes, including classical pedigree-derived lines (G1–G5), PYI-selected lines (G6–G10), YC-selected [...] Read more.

Barley (Hordeum vulgare L.) seed quality traits were evaluated to investigate the relative genetic and environmental contributions to their variation, the stability of genotypes across environments, and the interrelationships among traits. Fifteen genotypes, including classical pedigree-derived lines (G1–G5), PYI-selected lines (G6–G10), YC-selected lines (G11–G12), cultivars (G13–G14), and a local population (G15), were assessed for crude protein content, fat content, ash content, starch content, crude fiber content, carbohydrate content, soluble fraction, and non-starch fraction. Field trials were conducted across six environments under a randomized complete block design with four replications per environment. Combined ANOVA revealed significant differences among genotypes for all evaluated traits, while environmental effects and genotype × environment interactions also contributed significantly to trait variation. Stability analysis using the Stability Index (SI) showed that classical pedigree lines (G1–G5) demonstrated the highest overall stability across most traits. Lines selected via the Plant Yield Index (PYI) and Yielding Coefficient (YC) criteria exhibited greater stability compared to the local population, while cultivars showed intermediate and trait-dependent stability. Broad-sense heritability (H²) was high for all traits (>92%), with crude protein, fat, ash, and crude fiber content showing particularly strong genetic control. Genetic advance (GA) and genetic advance as a percentage of the mean (GA%) indicated a favorable expected response to selection for protein- and fiber-related traits. Traits such as starch content, carbohydrate content, soluble fraction, and non-starch fraction were more strongly influenced by environmental variation, highlighting the need for multi-environment testing. Correlation analysis revealed significant associations among traits, highlighting both trade-offs and coordinated accumulation patterns. Crude protein content was negatively correlated with carbohydrate content, soluble fraction, and non-starch fraction, whereas fat content showed positive correlations with ash content and fiber-related components, indicating potential targets for breeding programs. Overall, advanced barley lines combine high performance and stability, providing material suitable for further breeding under Mediterranean conditions. Full article

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

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16 pages, 472 KB

Open AccessArticle

The Development and Condition of Selected Legume Species Depending on the Rate of Superabsorbent Application Under Conditions of Limited Irrigation

by Katarzyna Czopek

Agriculture 2026, 16(3), 365; https://doi.org/10.3390/agriculture16030365 - 3 Feb 2026

Viewed by 463

Abstract

The aim of the study was to assess the effect of superabsorbents on the condition of selected legume species grown with different watering frequencies. Three two-factor pot experiments were conducted in MICRO-CLIMA phytotrons. The objects of the study were three legume species: faba [...] Read more.

The aim of the study was to assess the effect of superabsorbents on the condition of selected legume species grown with different watering frequencies. Three two-factor pot experiments were conducted in MICRO-CLIMA phytotrons. The objects of the study were three legume species: faba bean, pea and soybean. The first factor was the superabsorbent (SAP) rate (0, 2, 4, and 6 g·kg⁻¹ of substrate), while the second factor was the watering frequency (the subjects were watered every 1, 3, 6, and 9 days). The study showed that faba bean and pea plants were significantly taller after superabsorbent application (by 17 and 11%, respectively) and developed greater root mass. The application of SAPs at a rate of 6 g·kg⁻¹ increased the dry weight of the underground parts of faba beans and peas (by 56.8% and 85.9%, respectively) compared to the control. The highest SAP dose reduced the Fv/Fm index in soybean and the PI index in faba bean and soybean (by 5 and 29%, respectively). The lowest SPAD index in peas was recorded in the control treatment (without SAPs) and in soybeans at the highest dose of SAPs (6 g·kg⁻¹). In all species, the best results for growth and biomass of the aboveground parts were obtained with daily watering, which increased plant height by an average of 26.5–60.9% and the dry mass of the aboveground parts by 42.6–60.6% compared to less frequent watering. Higher values of the Fv/Fm index were observed in soybean, and higher values of the PI index were observed in faba bean, pea, and soybean in the least frequently watered treatments. In all species studied, the SPAD index was higher under conditions of the greatest water deficit (watering every 9 days) compared to plants watered every 1, 3, and 6 days. Full article

(This article belongs to the Special Issue Advances in the Cultivation and Production of Leguminous Plants—2nd Edition)

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45 pages, 5901 KB

Open AccessArticle

A Crayfish Optimization Algorithm with a Random Perturbation Strategy and Removal Similarity Operation for Color Image Enhancement

by Jiquan Wang, Min Wang, Haohao Song and Jinling Bei

Agriculture 2026, 16(3), 364; https://doi.org/10.3390/agriculture16030364 - 3 Feb 2026

Viewed by 1347

Abstract

Image enhancement can effectively improve the contrast, clarity, and information content of images, thereby improving visual quality. Image enhancement has significant application value in the process of identifying and diagnosing agricultural pests and diseases. This paper proposes a color image enhancement method based [...] Read more.

Image enhancement can effectively improve the contrast, clarity, and information content of images, thereby improving visual quality. Image enhancement has significant application value in the process of identifying and diagnosing agricultural pests and diseases. This paper proposes a color image enhancement method based on color space transformation, converting the image from the RGB space to the HSV space, conducting targeted enhancement on the V channel, and combining adaptive brightness adjustment and Gamma correction to further improve the visual effect. To achieve better enhancement results, this paper designs a crayfish optimization algorithm with a random perturbation strategy and removal similarity operation (COA-RPRS). This algorithm achieves a dynamic balance between exploration and exploitation through an adaptive temperature calculation formula and improves the position update mechanism in the summer escape, competition, and foraging stages, significantly enhancing convergence performance. Moreover, introducing a removal similarity operation and a random perturbation strategy based on Lévy flight effectively maintains population diversity and prevents premature convergence. Experimental verification was conducted on the CEC 2017 test functions, 20 color images, and 10 images of rice pests and diseases, showing that COA-RPRS achieves superior performance compared to eight other comparison algorithms in both global optimization and color image enhancement tasks. These results suggest its potential applicability in supporting intelligent recognition and diagnostic systems for agricultural pest and disease management. Full article

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

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19 pages, 773 KB

Open AccessReview

Bioactive Compounds in Hawthorn Leaves (Crataegus spp.)—Extraction, Functionality, and Future Perspectives: From Waste to Wealth

by Akerke Kulaipbekova, Zhanar Nabiyeva, Elmira Assembayeva, Fuhang Song, Yufang Su, Kairat Bekbayev, Xun Zhu and Nasi Ai

Agriculture 2026, 16(3), 363; https://doi.org/10.3390/agriculture16030363 - 3 Feb 2026

Viewed by 993

Abstract

The transition to a circular bioeconomy enhances the valorization of agricultural by-products. Hawthorn leaves (Crataegus spp.), generated in large quantities from orchard maintenance, represent a promising yet underutilized biomass. This comprehensive narrative review synthesizes recent advances regarding their bioactive compounds, extraction methods, [...] Read more.

The transition to a circular bioeconomy enhances the valorization of agricultural by-products. Hawthorn leaves (Crataegus spp.), generated in large quantities from orchard maintenance, represent a promising yet underutilized biomass. This comprehensive narrative review synthesizes recent advances regarding their bioactive compounds, extraction methods, and applications. A systematic literature search was conducted to identify relevant studies. The analysis reveals that hawthorn leaves are rich in polyphenols (e.g., flavonoids, procyanidins), with their content often exceeding that found in fruits. Modern “green” extraction techniques (e.g., ultrasound- and microwave-assisted) demonstrate superior efficiency in recovering these thermolabile compounds compared to conventional methods. The broad spectrum of associated biological activities—including antioxidant, cardioprotective, neuroprotective, antimicrobial, and insecticidal effects—underpins their potential in nutraceuticals, cosmetics, and functional foods. Crucially, this review highlights the significant promise of hawthorn leaf extracts as a source for developing natural, plant-based biopesticides, aligning with sustainable agriculture and integrated pest management principles. To fully realize this “waste-to-wealth” potential, future research should prioritize the scaling of eco-friendly extraction, field trials for crop protection efficacy, and the standardization of extracts. Full article

(This article belongs to the Special Issue Sustainable Use of Pesticides—2nd Edition)

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20 pages, 1592 KB

Open AccessArticle

Value-Added Diversification in Small Dairy Farms: Economic Efficiency and Strategic Investment

by Nemanja Jalić, Željko Vaško, Črtomir Rozman and Karmen Pažek

Agriculture 2026, 16(3), 362; https://doi.org/10.3390/agriculture16030362 - 3 Feb 2026

Cited by 1 | Viewed by 1083

Abstract

This research was conducted on small farms in Republika Srpska, an entity of Bosnia and Herzegovina. Data were collected through direct interviews on five farms, each with 8–15 dairy cows, which at some point diversified their production from selling raw milk to processing [...] Read more.

This research was conducted on small farms in Republika Srpska, an entity of Bosnia and Herzegovina. Data were collected through direct interviews on five farms, each with 8–15 dairy cows, which at some point diversified their production from selling raw milk to processing and selling fresh cheese. Due to low productivity and limited economies of scale, calculated indicators such as net present value, internal rate of return, and payback period are insufficient to consider traditional milk production economically justified. However, further analysis using Monte Carlo simulations and the real options method demonstrated that diversifying production into cheese processing is economically feasible, as confirmed by the strategic net present value calculated using Black–Scholes and binomial approaches. The results indicate that small, extensive family farms should focus on higher levels of product finalization. Although their production volumes are limited and they are not cost-competitive in raw milk markets, they gain a competitive advantage by adding value through their own labor and selling products via short supply chains. Diversification enables these farms to improve profitability, achieve financial stability, and strengthen market positioning, demonstrating that value addition is essential for the sustainability of small-scale dairy enterprises. Full article

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

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Agriculture, Volume 16, Issue 3 (February-1 2026) – 105 articles

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