Agriculture

15 pages, 3906 KB

Open AccessArticle

Energy Consumption Assessment of a Tractor Pulling a Five-Share Plow During the Tillage Process

by Jiapeng Wu, Juncheng Hu, Siyuan Chen, Daqing Zhang, Chaoran Sun and Qijun Tang

Agriculture 2025, 15(24), 2619; https://doi.org/10.3390/agriculture15242619 - 18 Dec 2025

Viewed by 324

Reducing the fuel consumption of tractors has consistently been a critical challenge that the agricultural machinery industry must address. To investigate the energy consumption during the plowing process of tractors and enhance their economic efficiency, this study conducted comparative experiments under varying plowing [...] Read more.

Reducing the fuel consumption of tractors has consistently been a critical challenge that the agricultural machinery industry must address. To investigate the energy consumption during the plowing process of tractors and enhance their economic efficiency, this study conducted comparative experiments under varying plowing speeds and depths. In this experiment, the CAN bus protocol was utilized for the collection of engine operational data, such as rotational speed and fuel flow. A GPS positioning system was adopted to measure the plowing speed of the tractor and combined with the data from the tractor coasting test, and then the energy consumption for operating the plow was determined. In addition, a tension sensor was installed on the three-point hitch to measure the horizontal pull force exerted by the five-share plow during plowing, thereby facilitating the calculation of the energy consumption of agricultural machinery. The findings indicate that when the tractor’s plowing speed is maintained at 5.7 km/h, both the average fuel consumption and the fuel consumption per unit area increase as the plowing depth increases. If the plowing depth is fixed at 23 cm, the average fuel consumption rises with an increase in plowing speed, whereas the fuel consumption per unit area decreases. The experimental data show that during the actual tillage operation of the tractor, the brake thermal efficiency of diesel engines ranges from 21.76% to 28.57%. The energy consumed by agricultural implements accounts for only 11.79% to 17.04% of the total fuel energy. The energy consumed in operating the tractor-drawn plow accounts for merely 7.87% to 13.66% of the diesel engine output energy. Approximately 23.24% to 38.69% of the effective power of the diesel engine is lost during the transmission process. This study provides valuable insights for optimizing the performance of tractors during operation. Full article

(This article belongs to the Section Agricultural Technology)

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20 pages, 1476 KB

Open AccessCommunication

Spring Oat Yields in Crop Rotation and Continuous Cropping: Reexamining the Need for Crop Protection When Growing Modern Varieties

by Magdalena Jastrzębska, Marta K. Kostrzewska and Marek Marks

Agriculture 2025, 15(24), 2618; https://doi.org/10.3390/agriculture15242618 - 18 Dec 2025

Viewed by 345

Abstract

Oats are regaining interest because of their nutritional and agro-environmental benefits. Hence, research into increasing oat productivity through sustainable agronomic practices has become increasingly important, especially as new varieties are developed and weather patterns become more unpredictable. The paper presents the effects of [...] Read more.

Oats are regaining interest because of their nutritional and agro-environmental benefits. Hence, research into increasing oat productivity through sustainable agronomic practices has become increasingly important, especially as new varieties are developed and weather patterns become more unpredictable. The paper presents the effects of the cropping system (six-field crop rotation, continuous cropping since 1968), variety (two per six-year period), chemical crop protection (control, herbicide, herbicide plus fungicide), and study year, on spring oat grain yields for two six-year crop rotation cycles (2011–2016, 2017–2022) of a long-term experiment in Poland. The cropping system was the most influential factor. Studies confirmed that growing oats in crop rotation ensures higher productivity than continuous cropping and sustains satisfactory yields in Polish conditions despite yearly weather variability. The cultivated varieties differed in yield levels and degree of yield reduction in response to continuous oat cropping. Only during the 2011–2016 cycle was a decreasing trend in yields observed as continuous cropping was prolonged. Oats grown in crop rotation rarely benefited from chemical protection against weeds and pathogens. In continuous cropping, herbicide and fungicide treatments typically did not mitigate oat yield losses associated with the system, exacerbating them in the 2017–2022 cycle. Among the evaluated agronomic practices, the six-field crop rotation system proved the most reliable yield-enhancing strategy, whereas chemical protection rarely improved oat performance. In individual years, contradictory reactions of the two cultivated varieties to cropping systems and crop protection levels were often noted. Full article

(This article belongs to the Special Issue Innovative Conservation Cropping Systems and Practices—2nd Edition)

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15 pages, 1050 KB

Open AccessArticle

Impact of Tetranychus urticae Herbivory on Aronia melanocarpa Ecotypes: Physiological, Morphological, and Reproductive Responses

by Edyta Górska-Drabik, Katarzyna Golan, Katarzyna Rubinowska and Cezary Sempruch

Agriculture 2025, 15(24), 2617; https://doi.org/10.3390/agriculture15242617 - 18 Dec 2025

Viewed by 269

Abstract

Induced resistance in plants is a promising strategy for pest management, helping to reduce dependence on synthetic pesticides. However, no study has yet examined the interaction between Tetranychus urticae and Aronia melanocarpa, including host acceptance, performance, and antioxidant defence mechanisms. In this [...] Read more.

Induced resistance in plants is a promising strategy for pest management, helping to reduce dependence on synthetic pesticides. However, no study has yet examined the interaction between Tetranychus urticae and Aronia melanocarpa, including host acceptance, performance, and antioxidant defence mechanisms. In this study, host acceptance of T. urticae was evaluated using two A. melanocarpa ecotypes: a non-cultivar (AMe) and the cultivated variety ‘Galicjanka’ (AGe). Leaf morphological traits (trichome density and length) and key life-history parameters of the mite (fecundity, egg development time, and larval duration) were assessed. Mite feeding effects on oxidative stress markers (hydrogen peroxide—H₂O₂; thiobarbituric acid reactive substances—TBARS) and antioxidant enzyme activity (guaiacol peroxidase—GPX ascorbate peroxidase—APX) were analysed by ecotype and infestation duration. Results showed low fecundity and prolonged development, indicating that neither ecotype is a preferred host for T. urticae. Ecotype-dependent differences in acceptance and mite performance suggest that variation in trichome density and biochemical traits may influence susceptibility. Baseline differences in H₂O₂ and TBARS imply a role in constitutive resistance, while their induction, accompanied by increased GPX and APX activity, highlights oxidative stress and antioxidant defences as key components of A. melanocarpa responses to mite attack. Full article

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

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22 pages, 4704 KB

Open AccessArticle

Nitrogen Fertilizer Rates Regulate Source–Sink Dynamics, Post-Anthesis N Translocation, and Yield Production in Spring Wheat on the Loess Plateau, China

by Yafei Chen, Aixia Xu, Zechariah Effah, Xuexue Wei, Yan Zhang, Nana Liu, Pengbin Liu, Khuram Shehzad Khan and Lingling Li

Agriculture 2025, 15(24), 2616; https://doi.org/10.3390/agriculture15242616 - 18 Dec 2025

Viewed by 326

Abstract

One of the main factors influencing wheat productivity is nitrogen (N) management. This study examined the impact of varying N-fertilizer rates on spring wheat yield and N use efficiency by adjusting the “source-sink” relationship between assimilates and N accumulation and transport. The objective [...] Read more.

One of the main factors influencing wheat productivity is nitrogen (N) management. This study examined the impact of varying N-fertilizer rates on spring wheat yield and N use efficiency by adjusting the “source-sink” relationship between assimilates and N accumulation and transport. The objective was to identify the optimal N rate for the region. The field experiment included five N-fertilizer rates: 0 kg ha⁻¹ (N1), 52.5 kg ha⁻¹ (N2), 105.0 kg ha⁻¹ (N3), 157.5 kg ha⁻¹ (N4), and 210.0 kg ha⁻¹ (N5). Results indicated that the yield response was not proportional to N-fertilizer rates, with maximum biomass (6029 kg ha⁻¹) and grain yield (2625 kg ha⁻¹) achieved under N3. N fertilization primarily increased yield by regulating pre-anthesis translocation of assimilate and N. Assimilate translocation peaked at 105 kg N ha⁻¹, increasing by 8.5–133.7% compared to other treatments. With increasing N input, N absorption efficiency and N partial factor productivity declined. The highest N agronomic use efficiency was observed under N3, which was 19.5–176.34% higher than other treatments. Overall, moderate N input (≈105 kg ha⁻¹) optimizes yield and N-use efficiency, offering guidance for sustainable N management in dryland spring wheat production. Full article

(This article belongs to the Section Crop Production)

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28 pages, 3429 KB

Open AccessArticle

Ensuring the Quality of Solid Biofuels from Orchard Biomass Through Supply Chain Optimization: A Case Study on Peach Biomass Briquettes

by Grigore Marian, Tatiana Alexiou Ivanova, Andrei Gudîma, Boris Nazar, Nicolae Daraduda, Leonid Malai, Alexandru Banari, Andrei Pavlenco and Teodor Marian

Agriculture 2025, 15(24), 2615; https://doi.org/10.3390/agriculture15242615 - 18 Dec 2025

Viewed by 296

Abstract

In the Republic of Moldova, orchard biomass represents an important resource for the production of densified solid biofuels, with peach having the highest sustainable energy potential (33.5 ± 6.54 GJ·ha⁻¹). However, the quality of solid biofuels derived from orchard biomass is [...] Read more.

In the Republic of Moldova, orchard biomass represents an important resource for the production of densified solid biofuels, with peach having the highest sustainable energy potential (33.5 ± 6.54 GJ·ha⁻¹). However, the quality of solid biofuels derived from orchard biomass is often constrained by heterogeneity in moisture content, uneven particle size distribution, and inadequate drying or blending practices along the supply chain. Optimizing the solid biofuel supply chain is therefore essential to minimize feedstock variability, ensure consistent densification quality, and reduce production costs. The aim of this study was to improve the process of producing densified solid biofuels from orchard biomass. Specifically, the study investigated how raw material moisture and particle size influence briquette density and durability, and how ternary mixtures of peach biomass, wheat straw, and sunflower residues can be optimized for enhanced energy performance. All experimental determinations were performed using validated methods and calibrated equipment. The results showed that optimal performance is achieved by shredding the biomass with 4–8 mm sieves and maintaining the moisture content between 6 and 14%, resulting in briquettes with the density of 1.00–1.05 g·cm⁻³, ash content below 3–5%, and an energy yield of 18.4–19.2 MJ·kg⁻¹. Ternary diagrams confirmed the decisive role of peach lignocellulosic residues in achieving high density, low ash content, and increased energy yield, while wheat straw and sunflower residues can be used in controlled proportions to diversify resources and reduce costs. These findings provide quantitative insights into how mixture formulation and process parameters influence the briquette quality, contributing to the optimization of solid biofuel supply chains for orchard and agricultural residues. Overall, this study demonstrates that competitive solid biofuels can be produced through careful balancing of mixture composition and optimization of technological parameters, offering practical guidelines for sustainable bioenergy development in regions with abundant orchard residues. Full article

(This article belongs to the Section Agricultural Technology)

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27 pages, 4863 KB

Open AccessArticle

CFD-Based Pre-Evaluation of a New Greenhouse Model for Climate Change Adaptation and High-Temperature Response

by Chanmin Kim, Rackwoo Kim, Heewoong Seok and Jungyu Kim

Agriculture 2025, 15(24), 2614; https://doi.org/10.3390/agriculture15242614 - 18 Dec 2025

Viewed by 413

Abstract

Global warming has intensified heat waves, severely threatening agricultural productivity and food security. In South Korea, heat waves have strengthened since the 1980s, often causing summer cooling demands far exceeding winter heating needs. Controlled-environment horticulture offers a vital alternative to open-field farming, yet [...] Read more.

Global warming has intensified heat waves, severely threatening agricultural productivity and food security. In South Korea, heat waves have strengthened since the 1980s, often causing summer cooling demands far exceeding winter heating needs. Controlled-environment horticulture offers a vital alternative to open-field farming, yet conventional structures such as the Venlo type remain vulnerable to high-temperature stress. This study pre-evaluates the thermal performance of a high-height wide-type greenhouse, developed by the Rural Development Administration, using computational fluid dynamics and compares it with a conventional Venlo-type structure. Simulations under extreme summer conditions (35–45 °C) considered natural ventilation, fogging, fan coil units, and hybrid systems. Thermal indicators, including air and root-zone temperatures, were analyzed to assess crop-sustaining conditions. Results showed that natural ventilation alone failed to maintain suitable environments. The high-height wide-type greenhouse achieved lower and more uniform temperatures than the Venlo type. Fogging and fan coil systems provided moderate cooling, while the hybrid system achieved the greatest reductions. Overall, the high-height wide-type greenhouse, especially when integrated with hybrid cooling, effectively mitigates heat stress and enhances thermal uniformity, providing quantitative guidance for structural selection and cooling-system configuration in greenhouse design under extreme thermal conditions. Full article

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

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2 pages, 126 KB

Open AccessCorrection

Correction: Zhao et al. Validating Data Interpolation Empirical Orthogonal Functions (DINEOF+) Interpolated Soil Moisture Data in the Contiguous United States. Agriculture 2025, 15, 1212

by Haipeng Zhao, Haoteng Zhao and Chen Zhang

Agriculture 2025, 15(24), 2613; https://doi.org/10.3390/agriculture15242613 - 18 Dec 2025

Viewed by 196

Abstract

In the original publication [...] Full article

(This article belongs to the Special Issue Applications of Remote Sensing in Agricultural Soil and Crop Mapping)

5 pages, 164 KB

Open AccessEditorial

How Optical Sensors and Deep Learning Enhance the Production Management in Smart Agriculture

by Jibo Yue, Meiyan Shu, Chengquan Zhou, Haikuan Feng and Fenghua Yu

Agriculture 2025, 15(24), 2612; https://doi.org/10.3390/agriculture15242612 - 17 Dec 2025

Viewed by 359

Abstract

The advent of smart agriculture marks a paradigm shift from experience-driven to data-driven decision-making, fundamentally reshaping centuries-old farming practices [...] Full article

(This article belongs to the Special Issue How Optical Sensors and Deep Learning Enhance the Production Management in Smart Agriculture)

22 pages, 1927 KB

Open AccessArticle

What Is the Future of Agriculture in Small Island Developing States? The Case of Mauritius

by Roshini Brizmohun, Ellen Hillbom, Rajeshreebhye Mahadea-Nemdharry and Ibrahim Wahab

Agriculture 2025, 15(24), 2611; https://doi.org/10.3390/agriculture15242611 - 17 Dec 2025

Viewed by 422

Abstract

Small Island Developing States (SIDS) face ongoing challenges in balancing agricultural sustainability with economic growth due to limited land resources, rapid urbanisation, climate change, and reliance on food imports. This study explores the evolution of land use and the future of agriculture in [...] Read more.

Small Island Developing States (SIDS) face ongoing challenges in balancing agricultural sustainability with economic growth due to limited land resources, rapid urbanisation, climate change, and reliance on food imports. This study explores the evolution of land use and the future of agriculture in Mauritius from 2002 to 2022, using satellite imagery, policy reviews, and stakeholder interviews. Findings show a 9% decrease in agricultural and non-agricultural vegetation cover, alongside a doubling of built-up areas from 10% to 20%, indicating continued land conversion pressures. The analysis highlights major barriers to agricultural sustainability, including declining food self-sufficiency, an ageing farming population, and slow movements towards sustainable practices caused by low profitability and weak institutional support. Diverging priorities among government agencies, sugar companies, smallholder farmers, and NGOs further hinder coordinated policy efforts. To address these challenges, the study identifies strategies for aligning economic and environmental goals through integrated land-use planning, boosting productivity, and providing targeted support for sustainable ecological farming systems. Policy recommendations include protecting agricultural land, encouraging agroecological practices, alleviating labour shortages, and promoting multi-stakeholder engagement within policy development. Overall, this research enhances understanding of land-use dynamics and agricultural resilience in SIDS, offering practical insights for policymakers and practitioners working towards sustainable food systems amid spatial and climatic constraints. Full article

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

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19 pages, 1893 KB

Open AccessArticle

Soil Respiration in Traditional Mediterranean Olive Groves: Seasonal Dynamics, Spatial Variability, and Controlling Factors

by Evangelina Pareja-Sánchez, Roberto García-Ruiz, Gustavo Sanchez, Xim Cerdá, Elena Angulo, Ramón C. Soriguer and Joaquín Cobos

Agriculture 2025, 15(24), 2610; https://doi.org/10.3390/agriculture15242610 - 17 Dec 2025

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Abstract

Understanding soil respiration (Rs) dynamics in Mediterranean olive groves is crucial for quantifying carbon fluxes under climate change. Soil respiration represents the combined CO₂ efflux from root metabolic activity and microbial decomposition of soil organic matter, processes strongly controlled by soil moisture, [...] Read more.

Understanding soil respiration (Rs) dynamics in Mediterranean olive groves is crucial for quantifying carbon fluxes under climate change. Soil respiration represents the combined CO₂ efflux from root metabolic activity and microbial decomposition of soil organic matter, processes strongly controlled by soil moisture, temperature, and the quantity and quality of organic matter inputs in semi-arid Mediterranean environments. This study quantified the seasonal and spatial variability of Rs in a traditional rainfed olive orchard planted at a spacing of 11 m between rows and 9 m between trees (≈101 trees ha⁻¹). Continuous measurements were conducted in two contrasting zones, under-canopy (UC) and inter-row (IR), using automated soil CO₂ flux chambers. Annual Rs reached 3.68 Mg CO₂ ha⁻¹ y⁻¹ in UC and 2.21 Mg CO₂ ha⁻¹ y⁻¹ in IR, with substantially higher emissions per unit area beneath the canopy. However, due to its larger surface proportion, the IR zone contributed more to the orchard scale CO₂ budget. Soil water content emerged as the dominant environmental driver of Rs, moderating or suppressing the temperature response during dry periods. These findings highlight the importance of explicitly considering microsite heterogeneity when assessing soil CO₂ efflux and designing sustainable carbon-management strategies in Mediterranean olive agroecosystems. Full article

(This article belongs to the Section Agricultural Soils)

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18 pages, 3368 KB

Open AccessArticle

Development of an Innovative Mechanical–Aeraulic Device for Sustainable Vector Control of Nymphs of Philaenus spumarius

by Francesco Paciolla, Alessia Farella, Gerardo Betrò, Annalisa Milella and Simone Pascuzzi

Agriculture 2025, 15(24), 2609; https://doi.org/10.3390/agriculture15242609 - 17 Dec 2025

Viewed by 338

Abstract

Several management strategies based on different approaches have been proposed to contain the spread of the pest Xylella fastidiosa, but novel, effective, and sustainable physical methods are still needed. The present study is focused on the design, construction, and testing of an [...] Read more.

Several management strategies based on different approaches have been proposed to contain the spread of the pest Xylella fastidiosa, but novel, effective, and sustainable physical methods are still needed. The present study is focused on the design, construction, and testing of an innovative mechanical–aeraulic device which implements a physical vector control strategy against the nymphs of Philaenus spumarius. The developed machine generates an airstream with proper temperature, shape, and velocity to impact the nymphs sheltered in the protective white “spittle” and cause their impairment or death. The machine generates a hot airflow with a temperature of 71.9 °C at 10 cm and 65.4 °C at 30 cm and a speed of 8.6 m s⁻¹ at 10 cm to 6.2 m s⁻¹ at 30 cm from the central axis of the outlet section. The area affected by the hot airflow was 2.65 m², and the recorded mean temperature of the vegetation in this area was 60.2 ± 2 °C. The mean mortality rate of nymphs of Philaenus spumarius reached by using the developed machine was 84.3%. Full article

(This article belongs to the Section Agricultural Technology)

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18 pages, 3498 KB

Open AccessArticle

Improved Estimation of Cotton Aboveground Biomass Using a New Developed Multispectral Vegetation Index and Particle Swarm Optimization

by Guanyu Wu, Mingyu Hou, Yuqiao Wang, Hongchun Sun, Liantao Liu, Ke Zhang, Lingxiao Zhu, Xiuliang Jin, Cundong Li and Yongjiang Zhang

Agriculture 2025, 15(24), 2608; https://doi.org/10.3390/agriculture15242608 - 17 Dec 2025

Viewed by 265

Abstract

Accurate and rapid estimation of aboveground biomass (AGB) in cotton is crucial for precise agricultural management. However, current AGB estimation methods are limited by data homogeneity and insufficient model accuracy, which fail to comprehensively reflect the cotton growth status. This study introduces a [...] Read more.

Accurate and rapid estimation of aboveground biomass (AGB) in cotton is crucial for precise agricultural management. However, current AGB estimation methods are limited by data homogeneity and insufficient model accuracy, which fail to comprehensively reflect the cotton growth status. This study introduces a novel approach by coupling cotton canopy Soil and Plant Analyzer Development (SPAD) values with multispectral (MS) data to achieve precise estimation of cotton AGB. Two experimental treatments, involving varied nitrogen fertilizer rates and organic manure applications, were conducted from 2022 to 2023. MS data from UAVs were collected across multiple cotton growth stages, while AGB and canopy SPAD values were synchronously measured. Using the coefficient of variation method, SPAD values were coupled with existing vegetation indices to develop a novel vegetation index termed CGSI_VI. Moreover, the applicability of various machine learning algorithms—including Random Forest Regressor (RFR), eXtreme Gradient Boosting (XGBoost), Categorical Boosting (CatBoost), Particle Swarm Optimization-XGBoost (PSO-XGBoost), and Particle Swarm Optimization-CatBoost (PSO-CatBoost)—was evaluated for inverting cotton AGB. The results indicated that, compared to the original vegetation indices, the correlation between the improved vegetation index (CGSI_VI) and AGB was enhanced by 13.60% overall, with the CGSI_CIre exhibiting the highest correlation with cotton AGB (R² = 0.87). The overall AGB estimation accuracy across different growth stages, spanning the entire growth period, ranged from 0.768 to 0.949, peaking during the flowering stage. Furthermore, when the CGSI_VI was used as an input parameter in comparisons of different machine learning algorithms, the PSO-XGBoost algorithm demonstrated superior estimation accuracy across the entire growth stage and within individual growth stages. This high-throughput crop phenotyping analysis method enables rapid and accurate estimation. It reveals the spatial heterogeneity of cotton growth status, thereby providing a powerful tool for accurately identifying growth differences in the field. Full article

(This article belongs to the Special Issue Unmanned Aerial System for Crop Monitoring in Precision Agriculture)

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22 pages, 6589 KB

Open AccessArticle

Research on Variable-Rate Spray Control System Based on Improved ANFIS

by Derui Bao, Changxi Liu, Yufei Li, Hang Shi, Chuang Yan, Hang Xue and Jun Hu

Agriculture 2025, 15(24), 2607; https://doi.org/10.3390/agriculture15242607 - 17 Dec 2025

Viewed by 303

Abstract

To optimize the flow stability and improve application accuracy of the PWM intermittent variable-rate spraying system, which suffers from insufficient flow stability and response delays during changes in travel speed, this study proposes an intelligent control method based on an improved Adaptive Neural [...] Read more.

To optimize the flow stability and improve application accuracy of the PWM intermittent variable-rate spraying system, which suffers from insufficient flow stability and response delays during changes in travel speed, this study proposes an intelligent control method based on an improved Adaptive Neural Fuzzy Inference System (ANFIS). Flow characteristic data of the solenoid valve were collected under four pressure conditions (0.2–0.5 MPa), drive frequencies (5–20 Hz), and duty cycles (10–90%) using an indoor test system. An ANFIS controller architecture was constructed with target flow rate and actual travel speed as input variables and PWM frequency-duty cycle combinations as output variables. This controller enhances the traditional single-output mode of ANFIS by achieving multi-output collaborative optimization through shared premise parameters, thereby strengthening the system’s nonlinear modeling and control capabilities. To validate the system’s practical performance, a field simulation test platform based on a spraying robot was constructed. By analyzing preset prescription map information, the system achieved precise variable-rate spraying operations during movement. Test results demonstrate that the steady-state error remains within 5.03% under various speed-varying conditions. This research provides a high-precision intelligent control solution for variable-rate spraying systems, holding significant implications for reducing pesticide application rates and advancing precision agriculture. Full article

(This article belongs to the Special Issue Perception, Decision-Making, and Control of Agricultural Robots)

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14 pages, 5353 KB

Open AccessArticle

Comparative Analysis of Chloroplast Genomes in Sansevieria Reveals Phylogenetic Relationships and High Variability Molecular Markers

by Zhigang Hao, Hua Kong, Xiaojun Lv, Xiaoxi Du, Hui Zhao and Jinghua Lu

Agriculture 2025, 15(24), 2606; https://doi.org/10.3390/agriculture15242606 - 17 Dec 2025

Viewed by 339

Abstract

Sansevieria, a perennial herb known for its ornamental and medicinal value, has many varieties due to its leaf size and stripe color. However, it is very difficult to distinguish them during the seedling stage. In this study, we conducted chloroplast genome sequencing [...] Read more.

Sansevieria, a perennial herb known for its ornamental and medicinal value, has many varieties due to its leaf size and stripe color. However, it is very difficult to distinguish them during the seedling stage. In this study, we conducted chloroplast genome sequencing analysis on 10 cultivars of Sansevieria trifasciata. The chloroplast genomes exhibited a typical quadripartite circular structure (154.2–158.7 kb), encoding 113 functional genes with highly conserved gene order. Phylogenetic analysis supported the evolutionary linkage between Sansevieria and Dracaena. Dynamic inverted repeats (IR) boundary expansions/contractions, particularly species-specific patterns in ndhF and rps19 gene distributions across IR junctions, indicating its adaptive divergence. We also discovered the trnT-psbD marker, which is a deletion marker developed from hypervariable regions and can effectively distinguish closely related species. This work provides critical molecular tools and theoretical foundations for germplasm identification, phylogenetic reconstruction, and chloroplast genome evolution in Sansevieria, and also promotes taxonomic revisions in Asparagaceae. Full article

(This article belongs to the Section Crop Genetics, Genomics and Breeding)

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25 pages, 6475 KB

Open AccessArticle

Fine-Resolution Multivariate Drought Analysis for Southwestern Türkiye Under SSP3-7.0 Scenario

by Cemre Yürük Sonuç, Nisa Yaylacı, Burkay Keske, Nur Kapan, Levent Başayiğit and Yurdanur Ünal

Agriculture 2025, 15(24), 2605; https://doi.org/10.3390/agriculture15242605 - 17 Dec 2025

Viewed by 483

Abstract

The ramifications of climate change, which are projected to lead to increased drought, desertification, and water scarcity, are expected to have a significant impact on the agricultural sector of Türkiye, particularly in the Mediterranean coastal regions. This study presents an extensive evaluation of [...] Read more.

The ramifications of climate change, which are projected to lead to increased drought, desertification, and water scarcity, are expected to have a significant impact on the agricultural sector of Türkiye, particularly in the Mediterranean coastal regions. This study presents an extensive evaluation of potential agricultural drought conditions in southwestern Türkiye, using a high-resolution, convection-permitting (0.025°) modeling approach. We employ a single, physically consistent model chain, dynamically downscaling the CMIP6 MPI-ESM-HR Earth System Model with the COSMO-CLM regional climate model at a convection-permitting (CP) resolution (0.025°) under IPCC Shared Socioeconomic Pathways SSP3-7.0, reflecting a high-emission scenario with regional socioeconomic challenges. Southwestern Türkiye, situated at the intersection of the Mediterranean and continental climates, hosts rare climatic and ecological conditions that sustain a highly productive and diverse agricultural system. This region forms the backbone of Türkiye’s agricultural economy but is increasingly vulnerable to climate variability and fluctuations that threaten its agricultural stability and resilience. Our study employs a novel approach that utilizes multivariate assessment of agricultural drought in the Mediterranean Region by integrating precipitation, soil moisture, and temperature variables from 2.5 km resolution climate simulations. Agricultural drought conditions were evaluated using the Standardized Precipitation Index (SPI), the Standardized Soil Moisture Index (SSI), and the Standardized Temperature Index (STI), derived by normalizing respective climate variables from climate simulations spanning from 1995 to 2014 for the historical period, from 2040 to 2049 and from 2070 to 2079 for future projections. CP climate simulations (CPCSs) exhibit a modest warm and dry bias during all seasons but slightly wetter conditions during summer when compared with station observations. Correlations between indices indicate that soil moisture variations in the future will become more sensitive to changes in temperature rather than precipitation. Results from this specific model chain reveal that the probability of compound events where precipitation and soil moisture deficits coincide with anomalously high temperatures will rise for all threshold levels under the SSP3-7.0 scenario towards the end of the century. For the most severe conditions (|Z| > 1.2), the compound likelihood increases to about 3%, highlighting the enhanced occurrence of rare events in a changing climate. These findings, conditional on the model and scenario used, provide a high-resolution, physically grounded perspective on the potential intensification of agricultural drought regimes. Full article

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

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24 pages, 1008 KB

Open AccessArticle

Rural Development Strategies in Border Areas: The Case of Sierra de San Pedro—Los Baldíos (Extremadura, Spain)

by Francisco Javier Castellano-Álvarez, Alejandro Jorge Márquez Mateo and María Durán-Pacheco

Agriculture 2025, 15(24), 2604; https://doi.org/10.3390/agriculture15242604 - 16 Dec 2025

Viewed by 453

Abstract

Taking as a reference a region located on the border between Spain and Portugal, this paper analyses how European rural development programs take into account this borderline nature in order to implement their development strategies. The case study methodology allows for an in-depth [...] Read more.

Taking as a reference a region located on the border between Spain and Portugal, this paper analyses how European rural development programs take into account this borderline nature in order to implement their development strategies. The case study methodology allows for an in-depth analysis of the investments implemented and the assessments of the entrepreneurs who carry them out. The results show the relevance of tourism projects within the investments made; however, the paradox is that it is precisely this type of project, and especially those aimed at creating rural accommodation, which have the highest percentage of failed investments. The results confirm the growing relevance of ‘non-productive’ actions led by local entities and aimed at the provision of public services. The interviews with the promoters show that, with the exception of some of the agricultural valorization actions, the vast majority of the projects carried out lack a cross-border vision. The development strategy of this county is not substantially different from that implemented by any other county. This is an interesting lesson since, if the same were happening in other border territories, the development strategies implemented would ignore the specific potentialities of this type of border region. Full article

(This article belongs to the Special Issue Economic Development of Rural Areas in Border Territories: Threats and Opportunities)

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24 pages, 30028 KB

Open AccessArticle

Temporal and Spatial Changes in Soil Drought and Identification of Remote Correlation Effects

by Weiran Luo, Jianzhong Guo, Ziwei Li, Ning Li, Fei Wang, Hexin Lai, Ruyi Men, Rong Li, Mengting Du, Kai Feng, Yanbin Li, Shengzhi Huang and Qingqing Tian

Agriculture 2025, 15(24), 2603; https://doi.org/10.3390/agriculture15242603 - 16 Dec 2025

Viewed by 336

Abstract

Under the extensive influence of the monsoon climate, droughts in the Yangtze River Basin (YRB) occur frequently and pose a serious threat to grain security. To better understand the evolution and drivers of soil drought, this study employed remote sensing-based soil moisture and [...] Read more.

Under the extensive influence of the monsoon climate, droughts in the Yangtze River Basin (YRB) occur frequently and pose a serious threat to grain security. To better understand the evolution and drivers of soil drought, this study employed remote sensing-based soil moisture and atmospheric circulation data from 2000 to 2022. It assessed the spatiotemporal characteristics of soil drought across the YRB and its sub-basins, identified the main mutation points and types, and quantified the relative contributions of climatic and circulation factors. The results show that: (1) the most severe soil drought month occurred in August 2022 (Standardized Soil Moisture Index SSMI = –1.69), with two major mutation points in May 2011 (“decrease to increase”) and June 2019 (“increase to decrease”); (2) drought mutations were mainly categorized as “interrupted decrease” (9 sub-basins) and “increase to decrease” (1 sub-basin), most occurring after 2010; (3) the year 2022 experienced the most severe annual drought (SSMI = –0.94), with extreme drought covering 39.36% of the basin in August; (4) precipitation (PC) was the dominant climatic factor influencing drought (percentage area of significant coherence PASC = 15.48%), while the Interannual Pacific Oscillation (IPO), Pacific Decadal Oscillation (PDO), and Dipole Mode Index (DMI) all showed significant remote-correlation effects, with mean Shapley additive explanations (SHAP) values of 0.138, 0.111, and 0.090, respectively. This study clarifies the spatiotemporal patterns and drivers of soil drought in the YRB, providing a scientific basis for improved drought monitoring and agricultural risk management. Full article

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

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19 pages, 3072 KB

Open AccessArticle

Microtopography-Driven Soil Loss in Loess Slopes Based on Surface Heterogeneity with BPNN Prediction

by Lin Chen, Yiting Song, Jie Lin, Qinqian Meng and Jian Wang

Agriculture 2025, 15(24), 2602; https://doi.org/10.3390/agriculture15242602 - 16 Dec 2025

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Abstract

Microtopography regulates soil erosion by shaping surface heterogeneity, but the mechanism of loess slope soil loss remains insufficiently quantified. This study combined laboratory rainfall simulations and machine learning to investigate how tillage-induced microtopography modulates soil loss through surface heterogeneity and hydrodynamic processes. Simulations [...] Read more.

Microtopography regulates soil erosion by shaping surface heterogeneity, but the mechanism of loess slope soil loss remains insufficiently quantified. This study combined laboratory rainfall simulations and machine learning to investigate how tillage-induced microtopography modulates soil loss through surface heterogeneity and hydrodynamic processes. Simulations used loess soil (silty loam) with a 5° slope, 60 mm/h rainfall intensity, and 5–30 min rainfall durations (RD). Results indicated that the mean weight diameter (MWD) and aggregate stability index (ASI) of structural, transition, and depositional crusts under micro-terrain decreased by 36~65% and 41~60%, respectively, while the fractal dimension (D) increased by 10~19%. Negative relationships were observed between ASI/MWD and D (R² = 0.83~0.98). Horizontal cultivation (T_HC, surface roughness [SR] = 1.76, average depression storage [ADS] = 2.34 × 10⁻² m³) delayed runoff connectivity and reduced cumulative soil loss (LS) by 42–58% compared to hoeing cultivation (T_HE, SR = 1.47, ADS = 3.23 × 10⁻⁴ m³). Abrupt hydrodynamic transitions occurred at 10 min RD (T_HE) and 15 min RD (artificial digging [T_AD]), driven by trench connectivity and depression overflow. LS exhibited a significant positive correlation with D and RD and was inversely correlated with ASI, MWD, and SR. A three-hidden-layer BPNN exhibited high predictive accuracy for LS (mean square error = 0.07), verifying applicability in complex scenarios with significant microtopographic heterogeneity and multi-factor coupling. This study demonstrated that surface roughness and depression storage were the dominant microtopographic controls on loess slope soil loss. BPNN provided a reliable tool for soil loss prediction in heterogeneous microtopographic systems. The findings provide critical insights into optimizing tillage-based soil conservation strategies for sloping loess farmlands. Full article

(This article belongs to the Special Issue Advancements in Best Management Practices for Enhancing Soil Health and Water Quality)

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30 pages, 4667 KB

Open AccessArticle

Cross-Hedging Mexican Lemon Prices with US Agricultural Futures: Evidence from the Surplus Efficient Frontier

by Oscar V. De la Torre-Torres, José Álvarez-García and María de la Cruz del Río-Rama

Agriculture 2025, 15(24), 2601; https://doi.org/10.3390/agriculture15242601 - 16 Dec 2025

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Abstract

This paper tested the use of the surplus efficient frontier (a minimum tracking error portfolio selection method) to select the optimal hedging portfolio that replicates the best Mexican #4 lemon price in a t + 1 and t + 4 week hedging scenario. [...] Read more.

This paper tested the use of the surplus efficient frontier (a minimum tracking error portfolio selection method) to select the optimal hedging portfolio that replicates the best Mexican #4 lemon price in a t + 1 and t + 4 week hedging scenario. Using data on the nine most traded agricultural futures in the US from January 2000 to February 2025, we tested hedging effectiveness across 502 futures portfolios in a weekly backtest. The results suggest that a corn and wheat portfolio increases the hedging effectiveness of the lemon price by 0.7033 or 70.33%. A result that, including the impact of trading fees and taxes, leads to a reduction in income risk to a lemon seller in a t + 1 week hedging horizon. The results suggest that a public or private financial institution could take a short position in such a portfolio to provide a hedge at a price that finances the spot/future price difference at minimum cost to Mexican taxpayers. Full article

(This article belongs to the Special Issue Price and Trade Dynamics in Agricultural Commodity Markets)

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18 pages, 3213 KB

Open AccessArticle

Design and Experimental Study of an Extraction Force Measurement System for Densely Planted Cotton Stalks

by Xingwang Wang, Xiangyu Wang, Jie Fang, Junhua Chen, Weixin Chen and Xueyong Chen

Agriculture 2025, 15(24), 2600; https://doi.org/10.3390/agriculture15242600 - 16 Dec 2025

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Abstract

The study of cotton stalk extraction resistance provides important parameters for the design of cotton stalk harvesting machinery. To investigate the effects of soil moisture content, cotton stalk diameter, and extraction angle on the extraction force of densely planted cotton stalks, this paper [...] Read more.

The study of cotton stalk extraction resistance provides important parameters for the design of cotton stalk harvesting machinery. To investigate the effects of soil moisture content, cotton stalk diameter, and extraction angle on the extraction force of densely planted cotton stalks, this paper designs a real-time measurement system based on virtual instrument technology and conducts field tests. The tests were carried out in cotton fields at the First Farm in Aral City, Xinjiang, using the cotton variety “Xiulu Zhong 70”. Single-factor experiments were conducted with extraction angle and stalk diameter as influencing factors. A combined three-factor experiment was performed under the following conditions: soil moisture contents of 21.87% and 26.32%; extraction angles of 25°, 30°, and 35°; and cotton stalk diameters of 8.50–9.00 mm, 10.00–10.50 mm, and 11.50–12.00 mm. The results show that the minimum extraction force is required when the extraction angle is 30°. Soil moisture content significantly affects the extraction force, which increases with stalk diameter. The combined test results indicate that the order of significance of the three factors is as follows: cotton stalk diameter (A), extraction angle (B), and soil moisture content (C). The optimal combination is A₁B₁C₂, corresponding to a diameter of 8.50–9.00 mm, an extraction angle of 35°, and a soil moisture content of 26.32%. Based on comprehensive analysis, the recommended extraction angle range is 30–35°. The proposed system can efficiently complete cotton stalk extraction force tests, and the collected data provide valuable references for the design of cotton stalk harvesting machinery. By appropriately selecting the extraction angle and conducting harvesting under suitable soil moisture conditions, it is possible to reduce power consumption and improve production efficiency. Full article

(This article belongs to the Section Agricultural Technology)

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24 pages, 4961 KB

Open AccessArticle

U-PKAN: A Dual-Module Kolmogorov–Arnold Network for Agricultural Plant Disease Detection

by Dejun Xi, Baotong Zhang and Yi-Jia Wang

Agriculture 2025, 15(24), 2599; https://doi.org/10.3390/agriculture15242599 - 16 Dec 2025

Viewed by 326

Abstract

Crop diseases and pests have a significant impact on planting costs and crop yields and, in severe cases, can threaten food security and farmers’ incomes. Currently, most researchers employ various deep learning methods, such as the YOLO series algorithms and U-Net and its [...] Read more.

Crop diseases and pests have a significant impact on planting costs and crop yields and, in severe cases, can threaten food security and farmers’ incomes. Currently, most researchers employ various deep learning methods, such as the YOLO series algorithms and U-Net and its variants, for the detection of agricultural plant diseases. However, the existing algorithms suffer from insufficient interpretability and are limited to linear modeling, which can lead to issues such as trust crises in current technologies, restricted applications and difficulties in tracing and correcting errors. To address these issues, a dual-module Kolmogorov–Arnold Network (U-PKAN) is proposed for agricultural plant disease detection in this paper. A KAN encoder–decoder structure is adopted to construct the network. To ensure the network fully extracts features, two different modules, namely Patchembed-KAN (P-KAN) and Decoder-KAN (D-KAN), are designed. To enhance the network’s feature fusion capability, a KAN-based symmetrical structure for skip connections is designed. The proposed method places learnable activation functions on weights, enabling it to achieve higher accuracy with fewer parameters. Moreover, it can reveal the compositional structure and variable dependencies of synthetic datasets through symbolic formulas, thus exhibiting excellent interpretability. A field corn disease image dataset was collected and constructed. Additionally, the performance of the U-PKAN model was verified using the open plant disease dataset PlantDoc and a gear pitting dataset. To better understand the performance differences between different methods, U-PKAN was compared with U-KAN, U-Net, AttUNet, and U-Net++ models for performance benchmarking. IoU and the Dice coefficient were chosen as evaluation metrics. The experimental results demonstrate that the proposed method achieves faster convergence and higher segmentation accuracy. Overall, the proposed method demonstrates outstanding performance in aspects such as function approximation, global perception, interpretability and computational efficiency. Full article

(This article belongs to the Special Issue Emerging Technologies in Crop Protection: Advanced Methods and Machinery)

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21 pages, 1755 KB

Open AccessArticle

Analysis on Economic Improvement Based on Energy Efficiency of Agricultural Tractors in South Korea During a Decade

by Wan-Tae Im, In-Seok Hwang, Moon-Kyung Jang, Jung-Hoon Kim, Tae-Ho Han, Young-Tae Kim, Youn-Koo Kang, Ju-Seok Nam and Chang-Seop Shin

Agriculture 2025, 15(24), 2598; https://doi.org/10.3390/agriculture15242598 - 16 Dec 2025

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Abstract

In recent years, the rapidly changing environment and climate have emphasized the need for sustainable development, particularly in the agricultural sector. Tractors are the most widely used machines in agriculture, making their energy efficiency crucial not only for environmental protection but also for [...] Read more.

In recent years, the rapidly changing environment and climate have emphasized the need for sustainable development, particularly in the agricultural sector. Tractors are the most widely used machines in agriculture, making their energy efficiency crucial not only for environmental protection but also for reducing farming costs and enhancing economic sustainability. This study applies Yeo–Johnson data transformation to normalize the discretized data of 111 tractor models, enabling the classification of agricultural tractors based on energy efficiency. Tractors were categorized into five classes according to energy efficiency, and the upper limit of each class was used to quantify the rate of improvement in energy efficiency. Furthermore, a comparative analysis between the classification model from 2006 to 2010 and that from 2016 to 2020 demonstrated that the latter exhibits superior energy consumption efficiency. Specifically, the 2016–2020 model showed an improvement in energy efficiency ranging from approximately 20.57% to 54.86% across all power categories, with higher-rated power tractors achieving greater improvements. This comparison confirms that the energy efficiency of tractors in the latest classification model is further improved, reflecting the substantial technological advancements made over the past decade. Full article

(This article belongs to the Special Issue Soil-Machine Systems and Its Related Digital Technologies Application)

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1 pages, 126 KB

Open AccessCorrection

Correction: Xayyavong et al. Utilization of Giant Mimosa Stalk to Produce Effective Stick Spawn for Reducing Inoculum Costs in Economic Mushroom Farming Systems. Agriculture 2025, 15, 1584

by Orlavanh Xayyavong, Worawoot Aiduang, Kritsana Jatuwong and Saisamorn Lumyong

Agriculture 2025, 15(24), 2597; https://doi.org/10.3390/agriculture15242597 - 16 Dec 2025

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Abstract

Missing Citation [...] Full article

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

16 pages, 7514 KB

Open AccessArticle

Tracking Heavy Metals and Resistance-Related Genes in Agricultural Karst Soils Derived from Various Parent Materials

by Jian Xiao, Chuan Liu, Hanxiang Mei, Changxingzi Gong and Chichao Huang

Agriculture 2025, 15(24), 2596; https://doi.org/10.3390/agriculture15242596 - 16 Dec 2025

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Abstract

Karstic regions are globally distributed, and the soil-forming parent rocks and their weathering process primarily cause elevated geochemical heavy metal (HM) accumulation in karst soils. However, the patterns of HMs, the genes related to resistance, and their interactions in karstic soils developed from [...] Read more.

Karstic regions are globally distributed, and the soil-forming parent rocks and their weathering process primarily cause elevated geochemical heavy metal (HM) accumulation in karst soils. However, the patterns of HMs, the genes related to resistance, and their interactions in karstic soils developed from different parent materials remain unexplored. In this study, 36 field karst soil samples originating from two parent materials were collected, including 19 samples from the residues of the weathering and leaching of carbonate rocks (Car) and 17 samples from Quaternary sediments (Qua). In the Car soils, the levels of As, Cd, Cr, Zn, Cu, Ni, and Pb exceeded the risk screening values for soil contamination of agricultural land set by the Chinese standard GB15618-2018 by 100%, 100%, 94.11%, 64.71%, 64.71%, 47.06%, and 41.18%, respectively, while only 11.76% of As in Qua soils exceeded the risk screening values. The proportion of metal resistance genes (MRGs) and antibiotic resistance genes (ARGs) in Car soils was significantly higher than that in Qua soils. However, HM content had a significantly positive correlation with Nemerow integrated pollution index (NIPI), individual HM-related genes, MRGs, ARGs, and mobile genetic elements (MGEs) in Qua soils, respectively. Although the corresponding correlation was positive in the Car soils, it was not statistically significant. Results demonstrated that microbial activity was more crucial for the accumulation of HMs in Qua soils compared with Car soils. Meanwhile, our in-depth research also provides new perspectives to establish a more rational ecological assessment for the elevated HMs by identifying applicable and valid biomarkers from functional genes, which is vital in contamination monitoring, prevention, and standard establishment in agricultural soils of karst regions. Full article

(This article belongs to the Section Agricultural Soils)

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22 pages, 3088 KB

Open AccessArticle

Stability of Forage Quality Traits in Artificial Meadows Across Greek Environments

by Vasileios Greveniotis, Elisavet Bouloumpasi, Adriana Skendi, Athanasios Korkovelos, Dimitrios Kantas and Constantinos G. Ipsilandis

Agriculture 2025, 15(24), 2595; https://doi.org/10.3390/agriculture15242595 - 15 Dec 2025

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Abstract

Ensuring high-quality forage under Mediterranean conditions requires careful evaluation of genetic resources. Two perennial forage species, cocksfoot (Dactylis glomerata L.) and tall fescue (Festuca arundinacea Schreb.), were evaluated to determine the stability and broad-sense heritability of major forage quality traits across [...] Read more.

Ensuring high-quality forage under Mediterranean conditions requires careful evaluation of genetic resources. Two perennial forage species, cocksfoot (Dactylis glomerata L.) and tall fescue (Festuca arundinacea Schreb.), were evaluated to determine the stability and broad-sense heritability of major forage quality traits across Greek environments. The objective was to identify stable, heritable traits contributing to consistent forage quality under climatic variability. Measured traits included crude protein (CP%), crude fiber (CF%), ash, acid detergent fiber (ADF), neutral detergent fiber (NDF), cellulose, hemicellulose, acid detergent lignin (ADL), digestible dry matter (DDM%), dry matter intake (DMI%), and relative feed value (RFV). Significant genotype × environment (G × E) interactions were observed for most traits, highlighting the importance of multi-environment testing, except for RFV in cocksfoot, which was non-significant. Principal Component Analysis (PCA) helped clarify how these traits covary across environments. The traits Crude Protein, Ash Content, and ADL (on PC1) are largely independent of the traits Cellulose and Hemicellulose (on PC2) in the case of cocksfoot. The pattern of loadings in the case of Tall fescue revealed that hemicellulose represents a completely separate dimension of variation, which is uncorrelated to the rest of the traits that form a unified, highly correlated group. In both cases, the first two PCs explained over 82% of the total variance, separating genotypes and environments. By integrating stability (SI) and heritability (H²) results, Cock2D and T2fes were identified as the most stable and high-performing genotypes across environments. These findings could support breeding strategies for developing resilient forage cultivars with consistent quality and adaptability to Mediterranean environments, thereby enhancing sustainable livestock production. Full article

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

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21 pages, 8620 KB

Open AccessArticle

Hardware-in-the-Loop Simulation Research on Adaptive Control Strategy for Traveling Power of Hydrostatic Harvesters

by Jichen Xie, Wenxing Ma, Zhongshan Wang, Haoji Song and Xin Wang

Agriculture 2025, 15(24), 2594; https://doi.org/10.3390/agriculture15242594 - 15 Dec 2025

Viewed by 234

Abstract

Conventional harvesters usually depend on the operator’s expertise to manually manage the power allocation between the harvesting and traveling system, which results in problems like high subjectivity, labor intensity, and sensitivity to terrain. To overcome issues such as inadequate power and power mismatches [...] Read more.

Conventional harvesters usually depend on the operator’s expertise to manually manage the power allocation between the harvesting and traveling system, which results in problems like high subjectivity, labor intensity, and sensitivity to terrain. To overcome issues such as inadequate power and power mismatches between harvesting and traveling on gentle slopes, this study introduces a hydrostatic four-wheel-drive system featuring a single variable pump paired with two variable motors, improving the vehicle’s capability to handle complex terrains. Building on this system, an adaptive power allocation method for traveling is proposed. This method dynamically adjusts the power distribution between traveling and harvesting according to changing terrain conditions, giving priority to harvesting power while controlling vehicle and engine speeds to avoid engine stalls, thereby enhancing operational quality and efficiency. A model of the full vehicle system is created using Amesim 2410, and a comparation of adaptive control and constant speed control is modeled under a hardware-in-the-loop environment. The simulation results show that the proposed control approach effectively manages power distribution across different slopes and speeds, and avoids engine stalling, providing valuable technical guidance for power coordination control in harvesters working on gentle slopes. Full article

(This article belongs to the Section Agricultural Technology)

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24 pages, 785 KB

Open AccessArticle

Economic and Financial Performance of Smallholder Dairy Farms in the Mexican Highlands: Prospective to 2033

by Nathaniel Alec Rogers-Montoya, Francisco Ernesto Martínez-Castañeda, Nicolás Callejas-Juárez, José Guadalupe Herrera-Haro, Gabriela Berenice Vilchis-Granados, Ariana Cruz-Olayo, Daniel Alonso Domínguez-Olvera, Rodrigo González-López, Monica Elizama Ruiz-Torres, Martha Mariela Zarco-González and Angel Roberto Martínez-Campos

Agriculture 2025, 15(24), 2593; https://doi.org/10.3390/agriculture15242593 - 15 Dec 2025

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Abstract

This study assessed the economic and financial viability of representative smallholder dairy farms (RSDFs) by analyzing two farm types: (1) RSDFs that rely exclusively on family labor and milk receipts, and (2) RSDFs that employ hired labor and obtain income from milk in [...] Read more.

This study assessed the economic and financial viability of representative smallholder dairy farms (RSDFs) by analyzing two farm types: (1) RSDFs that rely exclusively on family labor and milk receipts, and (2) RSDFs that employ hired labor and obtain income from milk in addition to sales of crops and agricultural by-products. A stochastic simulation based on empirical distributions derived from 44 years of historical data was used to project a 10-year horizon. Results indicate a low-to-minimal probability of decapitalization, an overall outlook of economic and financial viability, and a return on assets between 12% and 22%. Net present value (NPV) was positive for all RSDFs except one; however, in every case, NPV was lower than the opening asset value. Under current economic and policy conditions, RSDFs in the highlands of Mexico appear economically and financially viable through 2033. Family labor was associated with stronger economic and financial outcomes among the small-scale dairy farms evaluated. Full article

(This article belongs to the Special Issue Economics of Milk Production and Processing)

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14 pages, 3585 KB

Open AccessArticle

Endosymbiont Communities in Tea Plantation Beetles: A Comparative Study of Composition and Function Across Four Species

by Shi-Yan Xu

Agriculture 2025, 15(24), 2592; https://doi.org/10.3390/agriculture15242592 - 15 Dec 2025

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Abstract

Coleoptera, specifically leaf beetles (Chrysomelidae) and weevils (Curculionidae), are the dominant pests in tea plantations, significantly impacting tea yield and quality. Insect endosymbiont microbial communities play a crucial role in the physiological metabolism and pathogenicity of their hosts. However, there is still a [...] Read more.

Coleoptera, specifically leaf beetles (Chrysomelidae) and weevils (Curculionidae), are the dominant pests in tea plantations, significantly impacting tea yield and quality. Insect endosymbiont microbial communities play a crucial role in the physiological metabolism and pathogenicity of their hosts. However, there is still a lack of understanding regarding the composition and function of these communities in coleopteran pests in tea plantations. This study utilized high-throughput sequencing technology to analyze the composition and function of the endosymbiont microbial communities in four species of coleopteran insects from tea plantations. The results indicated that at the phylum level, the dominant bacteria in both leaf beetles and weevils were Proteobacteria and Firmicutes, while the dominant fungi were Ascomycota and Basidiomycota. At the genus level, the primary dominant bacteria in leaf beetles were Enterobacter and Lactococcus, whereas in weevils, they were Klebsiella, Pantoea, and Cedecea. The dominant fungi in leaf beetles consisted of Mortierella, Fusarium, Cladosporium, Aspergillus, and Penicillium, while those in weevils were Aspergillus, Thelebolus, Cladosporium, and Fusarium. Each species harbored its own distinct set of dominant genera. Furthermore, the abundance profiles of shared and unique bacterial and fungal genera revealed distinct characteristics in leaf beetles versus weevils. Although overall microbial diversity did not differ significantly among the four species, their bacterial community structures varied markedly. Functional prediction indicated ‘Plant Pathogen’ as the predominant type in leaf beetles, contrasting with ‘Membrane Transport’ in weevils. These findings provide a foundation for understanding endosymbionts in tea plantation beetles and their potential interactions with host insects. Full article

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

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20 pages, 4165 KB

Open AccessArticle

Shifts in Bacterial Community Structure and Humus Formation Under the Effect of Applying Compost from the Cooling Stage as a Natural Additive

by Jianxun Ma, Yufan Wang, Xinyu Zhang, Guang Chen, Jihong Wang, Yang Sun, Chunyu Sun and Nyuk Ling Ma

Agriculture 2025, 15(24), 2591; https://doi.org/10.3390/agriculture15242591 - 15 Dec 2025

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Abstract

Humus is the core product and key indicator of compost maturity. How to improve the humus content and accelerate its formation in composting is critical for the improvement of compost quality. This study investigated the effects of adding compost derived from different stages [...] Read more.

Humus is the core product and key indicator of compost maturity. How to improve the humus content and accelerate its formation in composting is critical for the improvement of compost quality. This study investigated the effects of adding compost derived from different stages including thermophilic, cooling, and maturation phases on compost initiation and efficiency in terms of humus formation and microbial community dynamics. The results reveal that adding compost from the cooling stage markedly outperforms the thermophilic and maturation phases, achieving a germination index of 107.22%, a carbon-to-nitrogen ratio of 15.95, a humus content of 91.12 g/kg, a humic acid concentration of 71.49 g/kg, and a polymerization degree of 3.64. EEMs indicated that the cooling-phase additive increased humic-like fluorescence (Region V) at day 35. The abundance and diversity of humifying bacteria were significantly enriched, and the succession of microbial community was accelerated as confirmed by redundancy analysis. This approach also improved compost quality and reduced the overall composting duration, thus suggesting that using compost from the cooling phase as an additive is an effective way to increase the humus content and accelerate the humification, providing a green solution for organic waste recycling and sustainable agricultural development and production. Full article

(This article belongs to the Section Agricultural Soils)

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32 pages, 1831 KB

Open AccessArticle

Energy Transition at the EU Peripheries: Investment of Rural and Urban–Rural Communes in Border Regions of Eastern Poland

by Agnieszka Kozera

Agriculture 2025, 15(24), 2590; https://doi.org/10.3390/agriculture15242590 - 15 Dec 2025

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Abstract

Energy transition has become a priority in public policy; however, knowledge of its progress in peripheral, border regions of Eastern Poland—particularly in rural and urban—rural communes—remains sketchy. Research gaps concern both the scale and intensity of investments co-financed from European Union (EU) funds, [...] Read more.

Energy transition has become a priority in public policy; however, knowledge of its progress in peripheral, border regions of Eastern Poland—particularly in rural and urban—rural communes—remains sketchy. Research gaps concern both the scale and intensity of investments co-financed from European Union (EU) funds, as well as the effect of their locations in relation to the state border and their position in reference to Functional Urban Areas (FUAs) on the level and character of the discussed investment activity. The primary aim of this study was to assess how the location of a border region and its relation to FUAs diversifies the investment activity and level of investment co-financed from EU funds aimed at developing the low-carbon economy in rural and urban–rural communes of the Eastern Macroregion. The analysis was conducted in two complementary dimensions: (i) a comparative nationwide assessment, covering all macroregions of Poland, within the two most recent, completed EU financial frameworks; i.e., the years 2007–2013 and 2014–2020 and (ii) an in-depth analysis of the Eastern Macroregion, with particular attention to rural and urban–rural communes, their affiliation with Functional Urban Areas (FUAs), and the typology defined by the Delimitation of Rural Areas (DRA). The aim of the conducted analyses was to respond to the research hypothesis assuming that “in the Eastern Macroregion the spatial conditions, i.e., the border location and the location in relation to functional urban areas (within an FUA vs. outside an FUA) significantly diversify the investment activity of rural and urban–rural communes aimed at the low-carbon economy co-financed from EU funds”. Empirical studies were conducted based on data from the Ministry of Development Funds and Regional Policy and Statistics Poland, which were processed applying methods of descriptive statistics and statistical inference and also using correspondence analysis. The analyses confirmed that in Eastern Poland the process of energy transition moved from the pilot phase to the common implementation of low-carbon measures, to a considerable extent thanks to the activity of rural and urban–rural communes. The results indicate that spatial factors, particularly location in relation to Functional Urban Areas and population density, significantly diversify intensity of investments in rural and urban–rural communes in the spatial context, whereas no such relationship was found for the investment level per capita. Full article

(This article belongs to the Special Issue Economic Development of Rural Areas in Border Territories: Threats and Opportunities)

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