Agriculture

26 pages, 17214 KiB

Open AccessArticle

Polyploid Induction Enhances Secondary Metabolite Biosynthesis in Clausena lansium: Morphological and Metabolomic Insights

by Yu Ding, Liangfang Wu, Hongyao Wei, Zhichun Zhang, Jietang Zhao, Guibing Hu, Yonghua Qin and Zhike Zhang

Agriculture 2025, 15(14), 1566; https://doi.org/10.3390/agriculture15141566 - 21 Jul 2025

Viewed by 480

Abstract

Polyploidy in plants can enhance stress resistance and secondary metabolite production, offering potential benefits for Clausena lansium (L.) Skeel, a medicinally valuable species. However, systematic studies of polyploidy-induced morphological, anatomical, and metabolic changes in this species are lacking. This study aimed to induce [...] Read more.

Polyploidy in plants can enhance stress resistance and secondary metabolite production, offering potential benefits for Clausena lansium (L.) Skeel, a medicinally valuable species. However, systematic studies of polyploidy-induced morphological, anatomical, and metabolic changes in this species are lacking. This study aimed to induce and characterize polyploid C. lansium lines, assess ploidy-dependent variations, and evaluate their impact on bioactive metabolite accumulation. Three cultivars were hybridized, treated with colchicine, and bred, yielding 13 stable polyploid lines confirmed by flow cytometry and chromosome counting. The polyploids exhibited distinct traits, including larger pollen grains, altered leaf margins, increased leaflet numbers, enlarged guard cells with reduced stomatal density, and thicker leaf tissues. Metabolomic analysis revealed that tetraploids accumulated significantly higher levels of flavonoids, alkaloids, and phenolic acids compared to diploids, while triploids showed moderate increases. These findings demonstrate that polyploidization, particularly tetraploidy, enhances C. lansium’s medicinal potential by boosting pharmacologically active compounds. The study expands germplasm resources and supports the development of high-quality cultivars for pharmaceutical applications. Full article

(This article belongs to the Special Issue Fruit Germplasm Resource Conservation and Breeding)

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15 pages, 2631 KiB

Open AccessArticle

Effects on Powdery Mildew and the Mutualistic Fungal Endophyte Epichloë gansuensis When Host Achnatherum inebrians Plants Are Sprayed with Different Fungicides

by Yue Zhu, Keke Cao, Kelin Wu, Michael J. Christensen, Jianxin Cao, Yanzhong Li, Xingxu Zhang and Zhibiao Nan

Agriculture 2025, 15(14), 1565; https://doi.org/10.3390/agriculture15141565 - 21 Jul 2025

Viewed by 356

Abstract

A study was conducted to examine the effects of the spray application of nine antifungal products, including microbial-derived fungicides, plant-derived fungicides, and chemical fungicides, on the grass Achnatherum inebrians that was either host to Epichloë gansuensis (E+) or E. gansuensis-free (E−) and [...] Read more.

A study was conducted to examine the effects of the spray application of nine antifungal products, including microbial-derived fungicides, plant-derived fungicides, and chemical fungicides, on the grass Achnatherum inebrians that was either host to Epichloë gansuensis (E+) or E. gansuensis-free (E−) and that was exposed to Blumeria graminis, the fungal pathogen causing powdery mildew. The Epichloë endophyte is a seed-borne mutualistic biotrophic fungus whose growth is fully synchronized with the host grass. Bl. graminis is a biotrophic pathogen that continually infects leaves and stems via conidia, the formation of appressoria, leading to the presence of haustoria in epidermal cells. Prior to fungicide application, the presence of endophytes significantly increased the resistance of A. inebrians to powdery mildew and was able to increase the chlorophyll content. However, the positive effects of the Epichloë endophyte on the plant were suppressed with the use of some fungicides and the increase in the number of sprays, but the reciprocal relationship between the Epichloë endophyte and the plant was not significantly disrupted. Full article

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

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28 pages, 6011 KiB

Open AccessArticle

Automatic Vibration Balancing System for Combine Harvester Threshing Drums Using Signal Conditioning and Optimization Algorithms

by Xinyang Gu, Bangzhui Wang, Zhong Tang, Honglei Zhang and Hao Zhang

Agriculture 2025, 15(14), 1564; https://doi.org/10.3390/agriculture15141564 - 21 Jul 2025

Viewed by 287

Abstract

The threshing drum, a core component in combine harvesters, experiences significant unbalanced vibrations during high-speed rotation, leading to severe mechanical wear, increased energy consumption, elevated noise levels, potential safety hazards, and higher maintenance costs. A primary challenge is that excessive interference signals often [...] Read more.

The threshing drum, a core component in combine harvesters, experiences significant unbalanced vibrations during high-speed rotation, leading to severe mechanical wear, increased energy consumption, elevated noise levels, potential safety hazards, and higher maintenance costs. A primary challenge is that excessive interference signals often obscure the fundamental frequency characteristics of the vibration, hampering balancing effectiveness. This study introduces a signal conditioning model to suppress such interference and accurately extract the unbalanced quantities from the raw signal. Leveraging this extracted vibration force signal, an automatic optimization method for the balancing counterweights was developed, solving calculation issues inherent in traditional approaches. This formed the basis for an automatic balancing control strategy and an integrated system designed for online monitoring and real-time control. The system continuously adjusts the rotation angles, θ₁ and θ₂, of the balancing weight disks based on live signal characteristics, effectively reducing the drum’s imbalance under both internal and external excitation states. This enables a closed loop of online vibration testing, signal processing, and real-time balance control. Experimental trials demonstrated a significant 63.9% reduction in vibration amplitude, from 55.41 m/s² to 20.00 m/s². This research provides a vital theoretical reference for addressing structural instability in agricultural equipment. Full article

(This article belongs to the Section Agricultural Technology)

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18 pages, 5434 KiB

Open AccessArticle

Design and Experimental Validation of Stem-Clamping-and-Pull-Out-Type Pepper Plug Seedling-Picking Mechanism

by Zhenhua Lin, Xiao Li, Hao Sun, Maile Zhou, Jianjun Yin, Jijia He and Daqing Yin

Agriculture 2025, 15(14), 1563; https://doi.org/10.3390/agriculture15141563 - 21 Jul 2025

Viewed by 247

Abstract

As a core component of a fully automatic pepper transplanter, the performance of the seedling-picking mechanism is of particular significance. However, existing seedling-picking mechanisms have problems such as being prone to damaging the seedling roots and substrate, as well as having poor stability. [...] Read more.

As a core component of a fully automatic pepper transplanter, the performance of the seedling-picking mechanism is of particular significance. However, existing seedling-picking mechanisms have problems such as being prone to damaging the seedling roots and substrate, as well as having poor stability. To develop a highly efficient, stable, and minimally damaging seedling-picking mechanism, this study proposed a design scheme for a stem-clamping-and-pulling-out-type seedling-picking end actuator driven by a non-circular gear system. The specific methods and objectives include the following: (1) designing a differential non-circular gear system to replicate a manual picking trajectory accurately; (2) establishing a kinematic model and developing optimization software to determine the optimal parameter combination; (3) experimentally validating the mechanism’s performance through virtual simulations and bench tests. The bench tests showed that the mechanism could complete two seedling-picking operations per rotation, extracting an entire row (eight plants) in a single rotation at a speed of 30 r/min. The measured angles of the end effector at four key postures were highly consistent with simulation and high-speed camera data, with all key posture errors less than 1°. These results demonstrate the mechanism’s high accuracy, efficiency, and reliability. Full article

(This article belongs to the Section Agricultural Technology)

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24 pages, 73556 KiB

Open AccessArticle

Neural Network-Guided Smart Trap for Selective Monitoring of Nocturnal Pest Insects in Agriculture

by Joel Hinojosa-Dávalos, Miguel Ángel Robles-García, Melesio Gutiérrez-Lomelí, Ariadna Berenice Flores Jiménez and Cuauhtémoc Acosta Lúa

Agriculture 2025, 15(14), 1562; https://doi.org/10.3390/agriculture15141562 - 21 Jul 2025

Viewed by 478

Abstract

Insect pests remain a major threat to agricultural productivity, particularly in open-field cropping systems where conventional monitoring methods are labor-intensive and lack scalability. This study presents the design, implementation, and field evaluation of a neural network-guided smart trap specifically developed to monitor and [...] Read more.

Insect pests remain a major threat to agricultural productivity, particularly in open-field cropping systems where conventional monitoring methods are labor-intensive and lack scalability. This study presents the design, implementation, and field evaluation of a neural network-guided smart trap specifically developed to monitor and selectively capture nocturnal insect pests under real agricultural conditions. The proposed trap integrates light and rain sensors, servo-controlled mechanical gates, and a single-layer perceptron neural network deployed on an ATmega-2560 microcontroller by Microchip Technology Inc. (Chandler, AZ, USA). The perceptron processes normalized sensor inputs to autonomously decide, in real time, whether to open or close the gate, thereby enhancing the selectivity of insect capture. The system features a removable tray containing a food-based attractant and yellow and green LEDs designed to lure target species such as moths and flies from the orders Lepidoptera and Diptera. Field trials were conducted between June and August 2023 in La Barca, Jalisco, Mexico, under diverse environmental conditions. Captured insects were analyzed and classified using the iNaturalist platform, with the successful identification of key pest species including Tetanolita floridiana, Synchlora spp., Estigmene acrea, Sphingomorpha chlorea, Gymnoscelis rufifasciata, and Musca domestica, while minimizing the capture of non-target organisms such as Carpophilus spp., Hexagenia limbata, and Chrysoperla spp. Statistical analysis using the Kruskal–Wallis test confirmed significant differences in capture rates across environmental conditions. The results highlight the potential of this low-cost device to improve pest monitoring accuracy, and lay the groundwork for the future integration of more advanced AI-based classification and species recognition systems targeting nocturnal Lepidoptera and other pest insects. Full article

(This article belongs to the Special Issue Design and Development of Smart Crop Protection Equipment)

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16 pages, 2687 KiB

Open AccessArticle

Cloning and Functional Validation of the Candidate Gene LuWRKY39 Conferring Resistance to Septoria linicola (Speg.) Garassini from Flax

by Si Chen, Hongmei Yuan, Guangwen Wu, Xue Yang, Dandan Liu, Le Chen, Jing Chen, Yan Liu, Weiping Yin, Cen Li, Linlin Wu, Jun Ma, Daolin Bian and Liguo Zhang

Agriculture 2025, 15(14), 1561; https://doi.org/10.3390/agriculture15141561 - 21 Jul 2025

Viewed by 371

Abstract

WRKY transcription factors play key roles in plant immune responses, including resistance to fungal pathogens. In the present study, we identified a flax resistance-related gene Lus10021999, named LuWRKY39. Here, to identify the role of WRKY transcription factor in resistance of flax against [...] Read more.

WRKY transcription factors play key roles in plant immune responses, including resistance to fungal pathogens. In the present study, we identified a flax resistance-related gene Lus10021999, named LuWRKY39. Here, to identify the role of WRKY transcription factor in resistance of flax against Septoria linicola, we cloned and analyzed the gene LuWRKY39 via homologous cloning using bioinformatics methods and localized the encoded protein. Quantitative real-time PCR (qRT-PCR) was used to explore the response of this gene to S. linicola. The results showed that the gene that is 948 bp long exhibited the closest genetic relationship to WRKY in castor (Ricinus communis), as revealed by phylogenetic analysis, and the encoded protein was localized in the nucleus. The LuWRKY39 gene showed higher expression levels in resistant flax materials than in susceptible ones, and higher in roots and stems than in leaves. Furthermore, gene expression showed an upward trend following treatment with salicylic acid (SA) and methyl jasmonate (MeJA), indicating that LuWRKY39 is involved in the regulation of SA and JA signals. By silencing LuWRKY39 in flax using virus-induced gene silencing (VIGS), the processed plants were more sensitive to S. linicola than untreated plants. Gene expression analysis and disease index statistics confirmed that the silenced plants were more susceptible, highlighting the crucial role of LuWRKY39 in flax disease resistance. This study provides a foundation for functional investigations of WRKY genes in flax and the identification of disease resistance genes. Full article

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

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17 pages, 3987 KiB

Open AccessArticle

Predicting Winter Ammonia and Methane Emissions from a Naturally Ventilated Dairy Barn in a Cold Region Using an Adaptive Neural Fuzzy Inference System

by Hualong Liu, Xin Wang, Tana, Tiezhu Xie, Hurichabilige, Qi Zhen and Wensheng Li

Agriculture 2025, 15(14), 1560; https://doi.org/10.3390/agriculture15141560 - 21 Jul 2025

Viewed by 293

Abstract

This study aims to characterize the emissions of ammonia (NH₃) and methane (CH₄) from naturally ventilated dairy barns located in cold regions during the winter season, thereby providing a scientific basis for optimizing dairy barn environmental management. The target [...] Read more.

This study aims to characterize the emissions of ammonia (NH₃) and methane (CH₄) from naturally ventilated dairy barns located in cold regions during the winter season, thereby providing a scientific basis for optimizing dairy barn environmental management. The target barn was selected at a commercial dairy farm in Ulanchab, Inner Mongolia, China. Environmental factors, including temperature, humidity, wind speed, and concentrations of NH₃, CH₄, and CO₂, were monitored both inside and outside the barn. The ventilation rate and emission rate were calculated using the CO₂ mass balance method. Additionally, NH₃ and CH₄ emission prediction models were developed using the adaptive neural fuzzy inference system (ANFIS). Correlation analyses were conducted to clarify the intrinsic links between environmental factors and NH₃ and CH₄ emissions, as well as the degree of influence of each factor on gas emissions. The ANFIS model with a Gaussian membership function (gaussmf) achieved the highest performance in predicting NH₃ emissions (R² = 0.9270), while the model with a trapezoidal membership function (trapmf) was most accurate for CH₄ emissions (R² = 0.8977). The improved ANFIS model outperformed common models, such as multilayer perceptron (MLP) and radial basis function (RBF). This study revealed the significant effects of environmental factors on NH₃ and CH₄ emissions from dairy barns in cold regions and provided reliable data support and intelligent prediction methods for realizing the precise control of gas emissions. Full article

(This article belongs to the Topic Greenhouse Gas Emission Reductions and Carbon Sequestration in Agriculture)

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16 pages, 2387 KiB

Open AccessArticle

The Impacts of Feeding a Reduced Energy and Lysine Balance in Lactation on Sow Body Composition, Litter Growth, and Markers of Subsequent Reproductive Performance

by Tracy L. Muller, Kate J. Plush, John R. Pluske, Darryl N. D’Souza, David W. Miller and Robert J. Van Barneveld

Agriculture 2025, 15(14), 1559; https://doi.org/10.3390/agriculture15141559 - 21 Jul 2025

Viewed by 347

Abstract

This experiment examined whether multiparous sows fed a diet lower in energy and lysine at a reduced feed allowance would still mobilise fat and (or) protein to support piglet growth and negatively impact subsequent reproductive performance. A total of 152 multiparous sows was [...] Read more.

This experiment examined whether multiparous sows fed a diet lower in energy and lysine at a reduced feed allowance would still mobilise fat and (or) protein to support piglet growth and negatively impact subsequent reproductive performance. A total of 152 multiparous sows was allocated in a 2 × 2 factorial design with the respective factors being diet type fed in lactation (gestation, 13.0 MJ digestible energy (DE)/kg, 0.42 g standardised ileal digestible (SID) lysine/MJ DE; or lactation, 14.3 MJ DE/kg, 0.62 g SID lysine/MJ DE) and feed allowance (ad libitum or 7.5 kg/d, ~15% reduction on ad libitum intake). Body composition was estimated on the day after farrowing (day 2) and at weaning (day 21). Blood was collected on days 2, 21 and at standing heat, for the analysis of insulin and insulin-like growth factor 1 (IGF-1). Diet type did not alter (p > 0.05) bodyweight or P2 backfat depth change in lactation, estimated body fat and protein changes, litter growth, or subsequent total piglets born. Ad libitum-fed sows showed a significant gain in girth compared to sows offered 7.5 kg/d (2.9 versus −0.4 mm, p = 0.015) and had a tendency for a shorter wean-to-service interval (p < 0.10). Sows fed the lactation diet had higher insulin concentrations at weaning (p < 0.05), but levels were the same (p > 0.10) by heat detection; IGF-1 concentrations remained unaffected. These data indicate that imposing a calculated negative energy and lysine balance on lactating sows had a limited impact on lactation or subsequent reproductive performance, supporting the notion that the modern sow may be more resilient to nutritional impositions than has been historically reported. Full article

(This article belongs to the Special Issue Effects of Dietary Interventions on Monogastric Animal Production)

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24 pages, 4669 KiB

Open AccessArticle

Optimizing the Design of Soil-Mixing Blade Structure Parameters Based on the Discrete Element Method

by Huiling Ding, Qiaofeng Wang, Mengyang Wang, Chao Zhang, Han Lin, Xin Jin, Haizhou Hong and Fengkui Dang

Agriculture 2025, 15(14), 1558; https://doi.org/10.3390/agriculture15141558 - 21 Jul 2025

Viewed by 267

Abstract

A multi-parameter optimization-based design method for soil-mixing blades was proposed to address the issue of excessive straw residue in the seeding layer after maize straw incorporation. A discrete element model simulating the interaction between the soil-mixing blades, soil, and corn straw was established. [...] Read more.

A multi-parameter optimization-based design method for soil-mixing blades was proposed to address the issue of excessive straw residue in the seeding layer after maize straw incorporation. A discrete element model simulating the interaction between the soil-mixing blades, soil, and corn straw was established. The key structural parameters included the bending line angle (α), bending angle (β), side angle (δ), tangential edge height (h), and bending radius (r); the straw burial rate (Y₁) and straw percentage in the seeding layer (Y₂) were selected as evaluation indicators. Single-factor experiments determined the significance level (p < 0.05) and the parameter range. A Box–Behnken response surface design, combined with analysis of variance (ANOVA), was employed to elucidate the influence patterns of the structural parameters and their interactions regarding straw burial performance. Multi-objective optimization yielded an optimal parameter combination: α = 55°, β = 100.01°, δ = 130°, h = 40.05 mm, and r = 28.67 mm. The simulation results demonstrated that this configuration achieved a Y₁ of 96.04% and reduced Y₂ to 35.25%. Field validation tests recorded Y₁ and Y₂ values of 96.54% and 34.13%, respectively. This study quantitatively elucidated the relationship between soil-mixing blade parameters and straw spatial distribution, providing a theoretical foundation for optimizing straw incorporation equipment. Full article

(This article belongs to the Section Agricultural Technology)

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23 pages, 5310 KiB

Open AccessArticle

Prediction of the Calorific Value and Moisture Content of Caragana korshinskii Fuel Using Hyperspectral Imaging Technology and Various Stoichiometric Methods

by Xuehong De, Haoming Li, Jianchao Zhang, Nanding Li, Huimeng Wan and Yanhua Ma

Agriculture 2025, 15(14), 1557; https://doi.org/10.3390/agriculture15141557 - 21 Jul 2025

Viewed by 314

Abstract

Calorific value and moisture content are the key indices to evaluate Caragana pellet fuel’s quality and combustion characteristics. Calorific value is the key index to measure the energy released by energy plants during combustion, which determines energy utilization efficiency. But at present, the [...] Read more.

Calorific value and moisture content are the key indices to evaluate Caragana pellet fuel’s quality and combustion characteristics. Calorific value is the key index to measure the energy released by energy plants during combustion, which determines energy utilization efficiency. But at present, the determination of solid fuel is still carried out in the laboratory by oxygen bomb calorimetry. This has seriously hindered the ability of large-scale, rapid detection of fuel particles in industrial production lines. In response to this technical challenge, this study proposes using hyperspectral imaging technology combined with various chemometric methods to establish quantitative models for determining moisture content and calorific value in Caragana korshinskii fuel. A hyperspectral imaging system was used to capture the spectral data in the 935–1720 nm range of 152 samples from multiple regions in Inner Mongolia Autonomous Region. For water content and calorific value, three quantitative detection models, partial least squares regression (PLSR), random forest regression (RFR), and extreme learning machine (ELM), respectively, were established, and Monte Carlo cross-validation (MCCV) was chosen to remove outliers from the raw spectral data to improve the model accuracy. Four preprocessing methods were used to preprocess the spectral data, with standard normal variate (SNV) preprocessing performing best on the quantitative moisture content detection model and Savitzky–Golay (SG) preprocessing performing best on the calorific value detection method. Meanwhile, to improve the prediction accuracy of the model to reduce the redundant wavelength data, we chose four feature extraction methods, competitive adaptive reweighted sampling (CARS), successive pojections algorithm (SPA), genetic algorithm (GA), iteratively retains informative variables (IRIV), and combined the three models to build a quantitative detection model for the characteristic wavelengths of moisture content and calorific value of Caragana korshinskii fuel. Finally, a comprehensive comparison of the modeling effectiveness of all methods was carried out, and the SNV-IRIV-PLSR modeling combination was the best for water content prediction, with its prediction set determination coefficient

(R_{P}^{2})

, root mean square error of prediction (RMSEP), and relative percentage deviation (RPD) of 0.9693, 0.2358, and 5.6792, respectively. At the same time, the moisture content distribution map of Caragana fuel particles is established by using this model. The SG-CARS-RFR modeling combination was the best for calorific value prediction, with its

R_{P}^{2}

, RMSEP, and RPD of 0.8037, 0.3219, and 2.2864, respectively. This study provides an innovative technical solution for Caragana fuel particles’ value and quality assessment. Full article

(This article belongs to the Section Agricultural Technology)

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15 pages, 748 KiB

Open AccessArticle

The Influence of Sowing Date and Seeding Density on the Yield of Soybean Glycine max (L.) Merrill

by Elżbieta Radzka, Katarzyna Rymuza and Paweł Cała

Agriculture 2025, 15(14), 1556; https://doi.org/10.3390/agriculture15141556 - 21 Jul 2025

Viewed by 402

Abstract

The current study aimed to determine the optimum agronomic conditions—specifically sowing date and seeding density—for soybean cultivation in a temperate climate. A field experiment was conducted to evaluate three sowing dates based on soil temperature (S1—9 °C, S2—12 °C, S3—15 °C) and three [...] Read more.

The current study aimed to determine the optimum agronomic conditions—specifically sowing date and seeding density—for soybean cultivation in a temperate climate. A field experiment was conducted to evaluate three sowing dates based on soil temperature (S1—9 °C, S2—12 °C, S3—15 °C) and three seeding densities (D1—50, D2—70, D3—90 seeds·m⁻²). A field experiment was conducted in the years 2017–2019 in eastern Poland (Central Europe). Yields were strongly influenced by weather conditions. In 2019, the average yield was 2.61 Mg·ha⁻¹, making it the most favorable year, whereas 2018 was the least favorable, with an average yield of 1.41 Mg·ha⁻¹. Seeding density also affected soybean yields—the highest yield was obtained at the medium density (D2—2.36 Mg∙ha⁻¹). On the other hand, the highest thousand seed weight (159.30 g·m⁻²) was achieved at the lowest density (D1). Plant height and pod length depended on the sowing date. The tallest plants (69.96 cm) and the longest pods (4.55 cm) were obtained with early sowing (S1). The number of seeds per pod ranged from 1.8 to 2.7, with the highest values recorded in 2017, mainly with early sowing (S1) and low density (D1). It is recommended that sowing strategies be flexibly adjusted to the meteorological conditions of a given season. The findings indicate that appropriate selection of sowing parameters can significantly enhance the efficiency and stability of soybean yields under the variable climatic conditions of Poland. Full article

(This article belongs to the Special Issue Sustainable Management of Legume Crops)

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14 pages, 360 KiB

Open AccessArticle

Efficiency Analysis of Sheep Farms in Cyprus

by Sokratis Sokratous, Athanasios Ragkos, Georgios Arsenos and Alexandros Theodoridis

Agriculture 2025, 15(14), 1555; https://doi.org/10.3390/agriculture15141555 - 20 Jul 2025

Viewed by 537

Abstract

In this study, an empirical analysis was applied to measure the efficiency level of dairy farms in Cyprus and estimate the capacity of sheep farmers to support the increasing demand for halloumi cheese. Data Envelopment Analysis was used on data from 50 dairy [...] Read more.

In this study, an empirical analysis was applied to measure the efficiency level of dairy farms in Cyprus and estimate the capacity of sheep farmers to support the increasing demand for halloumi cheese. Data Envelopment Analysis was used on data from 50 dairy sheep farms in Cyprus, which operate under extensive, semi-intensive, and intensive systems. The main features of the most efficient farms are presented, and a comparative financial analysis is implemented between the efficient and less efficient farms. The results indicate room for improvement in extensive and semi-intensive dairy sheep farming and verify that the transition that takes place in sheep farming towards more intensive systems constitutes the optimal approach. The most efficient farms operate under semi-intensive and intensive dairy sheep farming and achieve higher milk yields than the farms operating under extensive systems. Feeding constitutes the main cost driver, exceeding 60% in both efficient and inefficient farms, while labor wages and fixed capital cost varies between 25% and 30% of the total production cost for both efficiency groups. The findings indicate that the farms should utilize economies of scale to reduce production costs and utilize fixed capital endowments at full capacity. Full article

(This article belongs to the Special Issue Productivity and Efficiency of Agricultural and Livestock Systems)

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20 pages, 3953 KiB

Open AccessArticle

Straw Returning Combined with Application of Sulfur-Coated Urea Improved Rice Yield and Nitrogen Use Efficiency Through Enhancing Carbon and Nitrogen Metabolism

by Guangxin Zhao, Kaiyu Gao, Ming Gao, Xiaotian Xu, Zeming Li, Xianzhi Yang, Ping Tian, Xiaoshuang Wei, Zhihai Wu and Meiying Yang

Agriculture 2025, 15(14), 1554; https://doi.org/10.3390/agriculture15141554 - 19 Jul 2025

Viewed by 417

Abstract

Straw returning inhibits tillering at the early stage of rice growth and thus affects grain yield. Sulfur-coated urea (SCU) has been expected to increase nitrogen use efficiency (NUE) and yield, save labor input, and reduce environmental pollution in crop production. Nevertheless, the sulfur [...] Read more.

Straw returning inhibits tillering at the early stage of rice growth and thus affects grain yield. Sulfur-coated urea (SCU) has been expected to increase nitrogen use efficiency (NUE) and yield, save labor input, and reduce environmental pollution in crop production. Nevertheless, the sulfur coatings of SCU are easy to break and then shorten the nutrient release cycle. Whether there was a complementary effect between straw returning and SCU in NUE and grain yield had remained elusive. To investigate the effects of straw returning combined with the application of SCU on NUE and rice yield, a two-year field experiment was conducted from 2022 to 2023 with three treatments (straw returning combined with conventional urea (SRU), no straw returning combined with SCU (NRS), straw returning combined with SCU (SRS)). We found that straw returning combined with the application of SCU increased rice yield and NUE significantly. Compared with SRU and NRS, SRS treatments significantly increased grain yield by 14.61–16.22%, and 4.14–7.35%, respectively. Higher effective panicle numbers per m² and grain numbers per panicle were recorded in NRS and SRS treatments than SRU. SRS treatment increased nitrogen recovery efficiency by 79.53% and 22.97%, nitrogen agronomic efficiency by 18.68% and 17.37%, and nitrogen partial factor productivity by 10.51% and 9.81% compared with SRU and NRS treatment, respectively. The enhanced NUE in SRS was driven by higher leaf area index, SPAD value, net photosynthetic rate, carbon metabolic enzyme (RuBP and SPS) activity, nitrogen metabolic enzyme (NR, GS, and GOGAT) activity, sucrose and nitrogen content in leaves, and nitrogen accumulation in plant during grain filling. Moreover, the improved yield in SRS was closely related to superior NUE. In conclusion, straw returning combined with application of SCU boosted grain yield and NUE via enhanced carbon–nitrogen metabolism during the late growth period in rice. Full article

(This article belongs to the Special Issue Effects of Crop Management on Yields)

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14 pages, 10677 KiB

Open AccessArticle

A Seed Vigor Test Through a Biospeckle Laser: A Comparison of Local and Global Analyses

by Bruno Vicentini, Roberto Alves Braga, José Luís Contado, José Eduardo da Silva Gomes and Rolando de Jesus Gonzalez-Peña

Agriculture 2025, 15(14), 1553; https://doi.org/10.3390/agriculture15141553 - 19 Jul 2025

Viewed by 376

Abstract

Seed vigor testing traditionally requires large sample sizes and extended durations. The biospeckle laser (BSL) technique offers a faster, image-based alternative for seed analysis though the standardization of set protocols. This study evaluated the efficiency of local and global BSL analyses in bean [...] Read more.

Seed vigor testing traditionally requires large sample sizes and extended durations. The biospeckle laser (BSL) technique offers a faster, image-based alternative for seed analysis though the standardization of set protocols. This study evaluated the efficiency of local and global BSL analyses in bean seeds (Phaseolus vulgaris L.). Two groups of seeds (872 in total) were classified into high- and low-vigor seeds using the emergence test over 800 samples. The BSL test was then applied to 72 seeds (36 per group), analyzing biological activity locally (vascular and embryonic areas) and globally (whole image). BSL analysis detected significant differences between the groups (p < 0.05). Among the methods, the local analysis of the embryonic axis was most effective (F = 44.252, p = 0.000), showing a clearer distinction than the global analysis (F = 19.484, p = 0.000). The vascular area analysis did not yield significant results. These findings highlight the efficiency of the local BSL analysis at the embryonic axis for vigor tests compared to the global analysis. However, it was observed that the selected point in the local analysis affects the reliability of the vigor test. It was a relevant step toward standardization demanding additional tests in other species and varieties. Full article

(This article belongs to the Special Issue Optics and Image Analysis in Modern Agriculture: Transforming Practices and Unveiling Opportunities)

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27 pages, 15353 KiB

Open AccessArticle

Drought Evolution in the Yangtze and Yellow River Basins and Its Dual Impact on Ecosystem Carbon Sequestration

by Yuanhe Yu, Huan Deng, Shupeng Gao and Jinliang Wang

Agriculture 2025, 15(14), 1552; https://doi.org/10.3390/agriculture15141552 - 19 Jul 2025

Viewed by 309

Abstract

As an extreme event driven by global climate change, drought poses a severe threat to terrestrial ecosystems. The Yangtze River Basin (YZRB) and Yellow River Basin (YRB) are key ecological barriers and economic zones in China, holding strategic importance for exploring the evolution [...] Read more.

As an extreme event driven by global climate change, drought poses a severe threat to terrestrial ecosystems. The Yangtze River Basin (YZRB) and Yellow River Basin (YRB) are key ecological barriers and economic zones in China, holding strategic importance for exploring the evolution of drought patterns and their ecological impacts. Using meteorological station data and Climatic Research Unit Gridded Time Series (CRU TS) data, this study analyzed the spatiotemporal characteristics of drought evolution in the YZRB and YRB from 1961 to 2021 using the standardized precipitation evapotranspiration index (SPEI) and run theory. Additionally, this study examined drought effects on ecosystem carbon sequestration (CS) at the city, county, and pixel scales. The results revealed the following: (1) the CRU data effectively captured precipitation (annual r = 0.94) and temperature (annual r = 0.95) trends in both basins, despite significantly underestimating winter temperatures, with the optimal SPEI calculation accuracy found at the monthly scale; (2) both basins experienced frequent autumn–winter droughts, with the YRB facing stronger droughts, including nine events which exceeded 10 months (the longest lasting 25 months), while the mild droughts increased in frequency and extreme intensity; and (3) the drought impacts on CS demonstrated a significant threshold effect, where the intensified drought unexpectedly enhanced CS in western regions, such as the Garzê Autonomous Prefecture in Sichuan Province and Changdu City in the Xizang Autonomous Region, but suppressed CS in the midstream and downstream plains. The CS responded positively under weak drought conditions but declined once the drought intensity surpassed the threshold. This study revealed a nonlinear relationship between drought and CS across climatic zones, thereby providing a scientific foundation for enhancing ecological resilience. Full article

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

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21 pages, 8976 KiB

Open AccessArticle

Design and Parameter Optimization of Drum Pick-Up Machine Based on Archimedean Curve

by Caichao Liu, Feng Wu, Fengwei Gu, Man Gu, Jingzhan Ni, Weiweng Luo, Jiayong Pei, Mingzhu Cao and Bing Wang

Agriculture 2025, 15(14), 1551; https://doi.org/10.3390/agriculture15141551 - 19 Jul 2025

Viewed by 277

Abstract

Stones in farmland soil affect the efficiency of agricultural mechanization and the efficient growth of crops. In order to solve the problems of traditional stone pickers, such as large soil disturbance, high soil content and low picking rate, this paper introduces the Archimedean [...] Read more.

Stones in farmland soil affect the efficiency of agricultural mechanization and the efficient growth of crops. In order to solve the problems of traditional stone pickers, such as large soil disturbance, high soil content and low picking rate, this paper introduces the Archimedean curve with constant radial expansion characteristics into the design of the core working parts of the drum picker and designs a new type of drum stone picker. The key components such as spiral blades, rollers, and scrapers were theoretically analyzed, the structural parameters of the main components were determined, and the reliability of the spiral blades was checked using ANSYS Workbench software. Through the preliminary stone-picking performance test, the forward speed of the stone picker, the rotation speed of the drum, and the starting sliding angle of the spiral blade were determined as the test influencing factors. The picking rate and soil content of the stone picker were determined as the test indicators. The response surface test was carried out in the Design-Expert13.0 software. The results show that, when the forward speed of the stone picker is 0.726 m/s, the drum speed is 30 rpm, and the initial sliding angle of the spiral blade is 26.214°, the picking rate is 91.458% and the soil content is 3.513%. Field tests were carried out with the same parameters, and the picking rate was 91.42% and the soil content was 3.567%, with errors of 0.038% and 0.054% compared with the predicted values, indicating that the stone picker meets the field operation requirements. These research results can provide new ideas and technical paths for improving the performance of pickers and are of great value in promoting the development of advanced harvesting equipment and the efficient use of agricultural resources. Full article

(This article belongs to the Section Agricultural Technology)

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34 pages, 16612 KiB

Open AccessArticle

Identification of Optimal Areas for the Cultivation of Genetically Modified Cotton in Mexico: Compatibility with the Center of Origin and Centers of Genetic Diversity

by Antonia Macedo-Cruz

Agriculture 2025, 15(14), 1550; https://doi.org/10.3390/agriculture15141550 - 19 Jul 2025

Viewed by 441

Abstract

The agricultural sector faces significant sustainability, productivity, and environmental impact challenges. In this context, geographic information systems (GISs) have become a key tool to optimize resource management and make informed decisions based on spatial data. These data support planning the best cotton planting [...] Read more.

The agricultural sector faces significant sustainability, productivity, and environmental impact challenges. In this context, geographic information systems (GISs) have become a key tool to optimize resource management and make informed decisions based on spatial data. These data support planning the best cotton planting and harvest dates based on agroclimatic conditions, such as temperature, precipitation, and soil type, as well as identifying areas with a lower risk of water or thermal stress. As a result, cotton productivity is optimized, and costs associated with supplementary irrigation or losses due to adverse conditions are reduced. However, data from automatic weather stations in Mexico are scarce and incomplete. Instead, grid meteorological databases (DMM, in Spanish) were used with daily temperature and precipitation data from 1983 to 2020 to determine the heat units (HUs) for each cotton crop development stage; daily and accumulated HU; minimum, mean, and maximum temperatures; and mean annual precipitation. This information was used to determine areas that comply with environmental, geographic, and regulatory conditions (NOM-059-SEMARNAT-2010, NOM-026-SAG/FITO-2014) to delimit areas with agricultural potential for planting genetically modified (GM) cotton. The methodology made it possible to produce thirty-four maps at a 1:250,000 scale and a digital GIS with 95% accuracy. These maps indicate whether a given agricultural parcel is optimal for cultivating GM cotton. Full article

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

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22 pages, 9981 KiB

Open AccessArticle

Design and Experiment of Autonomous Shield-Cutting End-Effector for Dual-Zone Maize Field Weeding

by Yunxiang Li, Yinsong Qu, Yuan Fang, Jie Yang and Yanfeng Lu

Agriculture 2025, 15(14), 1549; https://doi.org/10.3390/agriculture15141549 - 18 Jul 2025

Viewed by 340

Abstract

This study presented an autonomous shield-cutting end-effector for maize surrounding weeding (SEMSW), addressing the challenges of the low weed removal rate (WRR) and high seedling damage rate (SDR) in northern China’s 3–5 leaf stage maize. The SEMSW integrated seedling positioning, robotic arm control, [...] Read more.

This study presented an autonomous shield-cutting end-effector for maize surrounding weeding (SEMSW), addressing the challenges of the low weed removal rate (WRR) and high seedling damage rate (SDR) in northern China’s 3–5 leaf stage maize. The SEMSW integrated seedling positioning, robotic arm control, and precision weeding functionalities: a seedling positioning sensor identified maize seedlings and weeds, guiding XYZ translational motions to align the robotic arm. The seedling-shielding anti-cutting mechanism (SAM) enclosed crop stems, while the contour-adaptive weeding mechanism (CWM) activated two-stage retractable blades (TRWBs) for inter/intra-row weeding operations. The following key design parameters were determined: 150 mm inner diameter for the seedling-shielding disc; 30 mm minimum inscribed-circle for retractable clamping units (RCUs); 40 mm ground clearance for SAM; 170 mm shielding height; and 100 mm minimum inscribed-circle diameter for the TRWB. Mathematical optimization defined the shape-following weeding cam (SWC) contour and TRWB dimensional chain. Kinematic/dynamic models were introduced alongside an adaptive sliding mode controller, ensuring lateral translation error convergence. A YOLOv8 model achieved 0.951 precision, 0.95 mAP50, and 0.819 mAP50-95, striking a balance between detection accuracy and localization precision. Field trials of the prototype showed 88.3% WRR and 2.2% SDR, meeting northern China’s agronomic standards. Full article

(This article belongs to the Special Issue Innovative Design and Application of Modern Agricultural Machinery Systems in Cropping Systems)

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13 pages, 1746 KiB

Open AccessArticle

Calibration of DEM Parameters and Microscopic Deformation Characteristics During Compression Process of Lateritic Soil with Different Moisture Contents

by Chao Ji, Wanru Liu, Yiguo Deng, Yeqin Wang, Peimin Chen and Bo Yan

Agriculture 2025, 15(14), 1548; https://doi.org/10.3390/agriculture15141548 - 18 Jul 2025

Viewed by 398

Abstract

Lateritic soils in tropical regions feature cohesive textures and high specific resistance, driving up energy demands for tillage and harvesting machinery. However, current equipment designs lack discrete element models that account for soil moisture variations, and the microscopic effects of water content on [...] Read more.

Lateritic soils in tropical regions feature cohesive textures and high specific resistance, driving up energy demands for tillage and harvesting machinery. However, current equipment designs lack discrete element models that account for soil moisture variations, and the microscopic effects of water content on lateritic soil deformation remain poorly understood. This study aims to calibrate and validate discrete element method (DEM) models of lateritic soil at varying moisture contents of 20.51%, 22.39%, 24.53%, 26.28%, and 28.04% by integrating the Hertz–Mindlin contact mechanics with bonding and JKR cohesion models. Key parameters in the simulations were calibrated through systematic experimentation. Using Plackett–Burman design, critical factors significantly affecting axial compressive force—including surface energy, normal bond stiffness, and tangential bond stiffness—were identified. Subsequently, Box–Behnken response surface methodology was employed to optimize these parameters by minimizing deviations between simulated and experimental maximum axial compressive forces under each moisture condition. The calibrated models demonstrated high fidelity, with average relative errors of 4.53%, 3.36%, 3.05%, 3.32%, and 7.60% for uniaxial compression simulations across the five moisture levels. Stress–strain analysis under axial loading revealed that at a given surface displacement, both fracture dimensions and stress transfer rates decreased progressively with increasing moisture content. These findings elucidate the moisture-dependent micromechanical behavior of lateritic soil and provide critical data support for DEM-based design optimization of soil-engaging agricultural implements in tropical environments. Full article

(This article belongs to the Section Agricultural Technology)

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17 pages, 11610 KiB

Open AccessArticle

Exploring the Impact of Species Participation Levels on the Performance of Dominant Plant Identification Models in the Sericite–Artemisia Desert Grassland by Using Deep Learning

by Wenhao Liu, Guili Jin, Wanqiang Han, Mengtian Chen, Wenxiong Li, Chao Li and Wenlin Du

Agriculture 2025, 15(14), 1547; https://doi.org/10.3390/agriculture15141547 - 18 Jul 2025

Viewed by 299

Abstract

Accurate plant species identification in desert grasslands using hyperspectral data is a critical prerequisite for large-scale, high-precision grassland monitoring and management. However, due to prolonged overgrazing and the inherent ecological vulnerability of the environment, sericite–Artemisia desert grassland has experienced significant ecological degradation. [...] Read more.

Accurate plant species identification in desert grasslands using hyperspectral data is a critical prerequisite for large-scale, high-precision grassland monitoring and management. However, due to prolonged overgrazing and the inherent ecological vulnerability of the environment, sericite–Artemisia desert grassland has experienced significant ecological degradation. Therefore, in this study, we obtained spectral images of the grassland in April 2022 using a Soc710 VP imaging spectrometer (Surface Optics Corporation, San Diego, CA, USA), which were classified into three levels (low, medium, and high) based on the level of participation of Seriphidium transiliense (Poljakov) Poljakov and Ceratocarpus arenarius L. in the community. The optimal index factor (OIF) was employed to synthesize feature band images, which were subsequently used as input for the DeepLabv3p, PSPNet, and UNet deep learning models in order to assess the influence of species participation on classification accuracy. The results indicated that species participation significantly impacted spectral information extraction and model classification performance. Higher participation enhanced the scattering of reflectivity in the canopy structure of S. transiliense, while the light saturation effect of C. arenarius was induced by its short stature. Band combinations—such as Blue, Red Edge, and NIR (BREN) and Red, Red Edge, and NIR (RREN)—exhibited strong capabilities in capturing structural vegetation information. The identification model performances were optimal, with a high level of S. transiliense participation and with DeepLabv3p, PSPNet, and UNet achieving an overall accuracy (OA) of 97.86%, 96.51%, and 98.20%. Among the tested models, UNet exhibited the highest classification accuracy and robustness with small sample datasets, effectively differentiating between S. transiliense, C. arenarius, and bare ground. However, when C. arenarius was the primary target species, the model’s performance declined as its participation levels increased, exhibiting significant omission errors for S. transiliense, whose producer’s accuracy (PA) decreased by 45.91%. The findings of this study provide effective technical means and theoretical support for the identification of plant species and ecological monitoring in sericite–Artemisia desert grasslands. Full article

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

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19 pages, 4026 KiB

Open AccessArticle

The Fusion of Focused Spectral and Image Texture Features: A New Exploration of the Nondestructive Detection of Degeneration Degree in Pleurotus geesteranus

by Yifan Jiang, Jin Shang, Yueyue Cai, Shiyang Liu, Ziqin Liao, Jie Pang, Yong He and Xuan Wei

Agriculture 2025, 15(14), 1546; https://doi.org/10.3390/agriculture15141546 - 18 Jul 2025

Viewed by 335

Abstract

The degradation of edible fungi can lead to a decrease in cultivation yield and economic losses. In this study, a nondestructive detection method for strain degradation based on the fusion of hyperspectral technology and image texture features is presented. Hyperspectral and microscopic image [...] Read more.

The degradation of edible fungi can lead to a decrease in cultivation yield and economic losses. In this study, a nondestructive detection method for strain degradation based on the fusion of hyperspectral technology and image texture features is presented. Hyperspectral and microscopic image data were acquired from Pleurotus geesteranus strains exhibiting varying degrees of degradation, followed by preprocessing using Savitzky–Golay smoothing (SG), multivariate scattering correction (MSC), and standard normal variate transformation (SNV). Spectral features were extracted by the successive projections algorithm (SPA), competitive adaptive reweighted sampling (CARS), and principal component analysis (PCA), while the texture features were derived using gray-level co-occurrence matrix (GLCM) and local binary pattern (LBP) models. The spectral and texture features were then fused and used to construct a classification model based on convolutional neural networks (CNN). The results showed that combining hyperspectral and image texture features significantly improved the classification accuracy. Among the tested models, the CARS + LBP-CNN configuration achieved the best performance, with an overall accuracy of 95.6% and a kappa coefficient of 0.96. This approach provides a new technical solution for the nondestructive detection of strain degradation in Pleurotus geesteranus. Full article

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

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16 pages, 2433 KiB

Open AccessArticle

A Single-Cell Assessment of Intramuscular and Subcutaneous Adipose Tissue in Beef Cattle

by Mollie M. Green, Hunter R. Ford, Alexandra P. Tegeler, Oscar J. Benitez, Bradley J. Johnson and Clarissa Strieder-Barboza

Agriculture 2025, 15(14), 1545; https://doi.org/10.3390/agriculture15141545 - 18 Jul 2025

Viewed by 1826

Abstract

Deposition of intramuscular fat (IM), also known as marbling, is the deciding factor of beef quality grade in the U.S. Defining molecular mechanisms underlying the differential deposition of adipose tissue in distinct anatomical areas in beef cattle is key to the development of [...] Read more.

Deposition of intramuscular fat (IM), also known as marbling, is the deciding factor of beef quality grade in the U.S. Defining molecular mechanisms underlying the differential deposition of adipose tissue in distinct anatomical areas in beef cattle is key to the development of strategies for marbling enhancement while limiting the accumulation of excessive subcutaneous adipose tissue (SAT). The objective of this exploratory study was to define the IM and SAT transcriptional heterogeneity at the whole tissue and single-nuclei levels in beef steers. Longissimus dorsi muscle samples (9–11th rib) were collected from two finished beef steers at harvest to dissect matched IM and adjacent SAT (backfat). Total RNA from IM and SAT was isolated and sequenced in an Illumina NovaSeq 6000. Nuclei from the same samples were isolated by dounce homogenization, libraries generated with 10× Genomics, and sequenced in an Illumina NovaSeq 6000, followed by analysis via Cell Ranger pipeline and Seurat in RStudio (v4.3.2) By the expression of signature marker genes, single-nuclei RNA sequencing (snRNAseq) analysis identified mature adipocytes (AD; ADIPOQ, LEP), adipose stromal and progenitor cells (ASPC; PDGFRA), endothelial cells (EC; VWF, PECAM1), smooth muscle cells (SMC; NOTCH3, MYL9) and immune cells (IMC; CD163, MRC1). We detected six cell clusters in SAT and nine in IM. Across IM and SAT, AD was the most abundant cell type, followed by ASPC, SMC, and IMC. In SAT, AD made up 50% of the cellular population, followed by ASPC (31%), EC (14%), IMC (1%), and SMC (4%). In IM depot, AD made up 23% of the cellular population, followed by ASPC at 19% of the population, EC at 28%, IMC at 7% and SMC at 12%. The abundance of ASPC and AD was lower in IM vs. SAT, while IMC was increased, suggesting a potential involvement of immune cells on IM deposition. Accordingly, both bulk RNAseq and snRNAseq analyses identified activated pathways of inflammation and metabolic function in IM. These results demonstrate distinct transcriptional cellular heterogeneity between SAT and IM depots in beef steers, which may underly the mechanisms by which fat deposits in each depot. The identification of depot-specific cell populations in IM and SAT via snRNAseq analysis has the potential to reveal target genes for the modulation of fat deposition in beef cattle. Full article

(This article belongs to the Special Issue Current Research and Strategies for Improving Farm Animal Meat Quality)

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22 pages, 4732 KiB

Open AccessArticle

Improving Winter Wheat Yield Estimation Under Saline Stress by Integrating Sentinel-2 and Soil Salt Content Using Random Forest

by Chuang Lu, Maowei Yang, Shiwei Dong, Yu Liu, Yinkun Li and Yuchun Pan

Agriculture 2025, 15(14), 1544; https://doi.org/10.3390/agriculture15141544 - 18 Jul 2025

Viewed by 379

Abstract

Accurate estimation of winter wheat yield under saline stress is crucial for addressing food security challenges and optimizing agricultural management in regional soils. This study proposed a method integrating Sentinel-2 data and field-measured soil salt content (SC) using a random forest (RF) method [...] Read more.

Accurate estimation of winter wheat yield under saline stress is crucial for addressing food security challenges and optimizing agricultural management in regional soils. This study proposed a method integrating Sentinel-2 data and field-measured soil salt content (SC) using a random forest (RF) method to improve yield estimation of winter wheat in Kenli County, a typical saline area in China’s Yellow River Delta. First, feature importance analysis of a temporal vegetation index (VI) and salinity index (SI) across all growth periods were achieved to select main parameters. Second, yield models of winter wheat were developed in VI-, SI-, VI + SI-, and VI + SI + SC-based groups. Furthermore, error assessment and spatial yield mapping were analyzed in detail. The results demonstrated that feature importance varied by growth periods. SI dominated in pre-jointing periods, while VI was better in the post-jointing phase. The VI + SI + SC-based model achieved better accuracy (R² = 0.78, RMSE = 720.16 kg/ha) than VI-based (R² = 0.71), SI-based (R² = 0.69), and VI + SI-based (R² = 0.77) models. Error analysis results suggested that the residuals were reduced as the input parameters increased, and the VI + SI + SC-based model showed a good consistency with the field-measured yields. The spatial distribution of winter wheat yield using the VI + SI + SC-based model showed significant differences, and average yields in no, slight, moderate, and severe salinity areas were 7945, 7258, 5217, and 4707 kg/ha, respectively. This study can provide a reference for winter wheat yield estimation and crop production improvement in saline regions. Full article

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

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21 pages, 1206 KiB

Open AccessArticle

Evaluation of Olive Mill Waste Compost as a Sustainable Alternative to Conventional Fertilizers in Wheat Cultivation

by Ana García-Rández, Silvia Sánchez Méndez, Luciano Orden, Francisco Javier Andreu-Rodríguez, Miguel Ángel Mira-Urios, José A. Sáez-Tovar, Encarnación Martínez-Sabater, María Ángeles Bustamante, María Dolores Pérez-Murcia and Raúl Moral

Agriculture 2025, 15(14), 1543; https://doi.org/10.3390/agriculture15141543 - 17 Jul 2025

Viewed by 473

Abstract

This study evaluates the agronomic and environmental performance of pelletized compost derived from olive mill waste as a sustainable alternative to mineral fertilizers for cultivating wheat (Triticum turgidum L.) under conventional tillage methods. A field experiment was conducted in semi-arid Spain, employing [...] Read more.

This study evaluates the agronomic and environmental performance of pelletized compost derived from olive mill waste as a sustainable alternative to mineral fertilizers for cultivating wheat (Triticum turgidum L.) under conventional tillage methods. A field experiment was conducted in semi-arid Spain, employing three fertilization strategies: inorganic (MAP + Urea), sewage sludge (SS), and organic compost pellets (OCP), each providing 150 kg N ha⁻¹. The parameters analyzed included wheat yield, grain quality, soil properties, and greenhouse gas (GHG) emissions. Inorganic fertilization yielded the highest productivity and nutrient uptake. However, the OCP treatment reduced grain yield by only 15%, while improving soil microbial activity and enzymatic responses. The SS and OCP treatments showed increased CO₂ and N₂O emissions compared to the control and inorganic plots. However, the OCP treatment also acted as a CH₄ sink. Nutrient use efficiency was greatest under mineral fertilization, though the OCP treatment outperformed the SS treatment. These results highlight the potential of OCP as a circular bio-based fertilizer that can enhance soil function and partially replace mineral inputs. Optimizing application timing is critical to aligning nutrient release with crop demand. Further long-term trials are necessary to evaluate their impact on the soil and improve environmental outcomes. Full article

(This article belongs to the Special Issue Fertilizer Management Strategies for Enhancing the Growth, Yield and Quality in Crops)

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5 pages, 179 KiB

Open AccessEditorial

Leaning on Smart Agricultural Systems for Crop Monitoring

by Adrian Gracia-Romero, Karen Marti-Jerez and Fabio Fania

Agriculture 2025, 15(14), 1542; https://doi.org/10.3390/agriculture15141542 - 17 Jul 2025

Viewed by 426

Abstract

Contemporary precision agriculture and breeding programs are heavily dependent on the evaluation of a high number of experimental plots, usually involving different genotypes, irrigation methods, and managing systems [...] Full article

(This article belongs to the Special Issue Smart Agriculture Sensors and Monitoring Systems for Field Detection)

16 pages, 992 KiB

Open AccessArticle

Relative Growth Rate and Specific Absorption Rate of Nutrients in Lactuca sativa L. Under Secondary Paper Sludge Application and Soil Contamination with Lead

by Elena Ikkonen and Marija Yurkevich

Agriculture 2025, 15(14), 1541; https://doi.org/10.3390/agriculture15141541 - 17 Jul 2025

Viewed by 269

Abstract

Cost-effective methods for improving soil fertility and mitigating the negative impact of heavy metal contamination in agricultural soils are currently under investigation. This study aimed to evaluate the impact of soil lead (Pb) contamination and the application of secondary pulp and paper mill [...] Read more.

Cost-effective methods for improving soil fertility and mitigating the negative impact of heavy metal contamination in agricultural soils are currently under investigation. This study aimed to evaluate the impact of soil lead (Pb) contamination and the application of secondary pulp and paper mill sludge on the relative growth rate (RGR) and its determinants, as well as the specific absorption rate (SAR) of nutrients of Lactuca sativa L. For the 46-day pot experiment, which was carried out in 2022 under controlled conditions at the Karelian Research Centre of RAS, sandy loam soil was used, to which Pb was added at rates of 0, 50, and 250 mg Pb(NO₃)₂ kg⁻¹. Secondary sludge was applied with each watering at concentrations of 0%, 20%, and 40%. RGR values varied significantly, primarily due to changes in net assimilation rate (NAR) rather than specific leaf area. Positive relationships were found between RGR and NAR, and RGR and SAR of nitrogen and phosphorus, but not potassium. Sludge applications can stimulate NAR at early stages of plant growth. For plants grown on soil with the highest Pb concentration studied, secondary sludge reduced root lead content by an average of 35%. Soil contamination with lead increased nutrient SAR by 79 and 39% when applied as 20 and 40% sludge, respectively, while 40% sludge increased nitrogen SAR by 51% but did not change phosphorus and potassium SAR. A sludge-mediated reduction in root Pb content and an increase in NAR suggest that secondary paper sludge may contribute to the remediation of Pb-contaminated soils and reduce the toxicity of heavy metals to plants. The results may help in finding new ways to manage soil fertility, especially for contaminated soils. Full article

(This article belongs to the Section Agricultural Soils)

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18 pages, 4389 KiB

Open AccessArticle

Acoustic Wave Propagation Characteristics of Maize Seed and Surrounding Region with the Double Media of Seed–Soil

by Yadong Li, Caiyun Lu, Hongwen Li, Jin He, Zhinan Wang and Chengkun Zhai

Agriculture 2025, 15(14), 1540; https://doi.org/10.3390/agriculture15141540 - 17 Jul 2025

Viewed by 394

Abstract

When monitoring seed positions in soil using ultrasonic waves, the main challenge is obtaining acoustic wave characteristics at the seed locations. This study developed a three-dimensional ultrasonic model with the double media of seed–soil using the discrete element method to visualize signal variations [...] Read more.

When monitoring seed positions in soil using ultrasonic waves, the main challenge is obtaining acoustic wave characteristics at the seed locations. This study developed a three-dimensional ultrasonic model with the double media of seed–soil using the discrete element method to visualize signal variations and analyze propagation characteristics. The effects of the compression ratio (0/6/12%), excitation frequency (20/40/60 kHz), and amplitude (5/10/15 μm) on signal variation and attenuation were analyzed. The results show consistent trends: time/frequency domain signal intensity increased with a higher compression ratio and amplitude but decreased with frequency. Comparing ultrasonic signals at soil particles before and after the seed along the propagation path shows that the seed significantly absorbs and attenuates ultrasonic waves. Time domain intensity drops 93.99%, and first and residual wave frequency peaks decrease by 88.06% and 96.39%, respectively. Additionally, comparing ultrasonic propagation velocities in the double media of seed–soil and the single soil medium reveals that the velocity in the seed is significantly higher than that in the soil. At compression ratios of 0%, 6%, and 12%, the sound velocity in the seed is 990.47%, 562.72%, and 431.34% of that in the soil, respectively. These findings help distinguish seed presence and provide a basis for ultrasonic seed position monitoring after sowing. Full article

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

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15 pages, 1650 KiB

Open AccessArticle

Physico-Chemical and Resistance Characteristics of Rosehip Seeds

by Alina-Daiana Ionescu, Gheorghe Voicu, Elena-Madalina Stefan, Gabriel-Alexandru Constantin, Paula Tudor and Gheorghe Militaru

Agriculture 2025, 15(14), 1539; https://doi.org/10.3390/agriculture15141539 - 17 Jul 2025

Viewed by 321

Abstract

Both the pulp and the seeds of rosehip are important for human health. Rosehip seeds are rich in polyunsaturated fats, which support a healthy skin membrane and protect it from inflammatory factors. In order to be used, the seeds require initial processing, mainly [...] Read more.

Both the pulp and the seeds of rosehip are important for human health. Rosehip seeds are rich in polyunsaturated fats, which support a healthy skin membrane and protect it from inflammatory factors. In order to be used, the seeds require initial processing, mainly by grinding. This paper first presents a brief review of the physicochemical properties and the content of bioactive compounds in rosehip (Rosa canina) and its seeds. Original research results on the compression behavior of rosehip seeds are presented below, together with the key values of the most important parameters derived from the analysis. For seeds with a thickness ranging from 1.80 to 3.55 mm, the compressive force at the onset of fracture was recorded to be between 94.4 and 156.0 N, while the force required for complete fracture ranged from 114.0 to 495.0 N (with about 12.5% of values considered outside a normal distribution). Additionally, for these forces, the deformation of the seeds ranged between 0.142 and 0.916 mm at the onset of fracture and between 0.248 and 1.878 mm at complete fracture. For these characteristics, the energy consumed ranged between 0.012 and 0.041 J at the onset of fracture and between 0.017 and 0.322 J at complete breaking. The elasticity of the seeds also ranged between 159.9 and 789.1 N/mm, considering the forces and deformations at the onset of fracture. The results of our study contribute to expanding the database on the mechanical characteristics of rosehip seeds, knowledge of which is essential for the initial processing operations used in the pharmaceutical industry aimed at oil extraction. Full article

(This article belongs to the Section Seed Science and Technology)

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19 pages, 3309 KiB

Open AccessArticle

Harnessing Microbial Agents to Improve Soil Health and Rice Yield Under Straw Return in Rice–Wheat Agroecosystems

by Yangming Ma, Yanfang Wen, Ruhongji Liu, Zhenglan Peng, Guanzhou Luo, Cheng Wang, Zhonglin Wang, Zhiyuan Yang, Zongkui Chen, Jun Ma and Yongjian Sun

Agriculture 2025, 15(14), 1538; https://doi.org/10.3390/agriculture15141538 - 17 Jul 2025

Viewed by 378

Abstract

We clarified the effect of wheat straw return combined with microbial agents on rice yield and soil properties. A field experiment was conducted using hybrid indica rice ‘Chuankangyou 2115’ and five treatments: no wheat straw return (T₁), wheat straw [...] Read more.

We clarified the effect of wheat straw return combined with microbial agents on rice yield and soil properties. A field experiment was conducted using hybrid indica rice ‘Chuankangyou 2115’ and five treatments: no wheat straw return (T₁), wheat straw return alone (T₂), T₂+ microbial agent application (Bacillus subtilis/Trichoderma harzianum = 1:1) (T₃); T₂+ microbial agent application (Bacillus subtilis/Trichoderma harzianum = 3:1) (T₄); T₂+ microbial agent application (Bacillus subtilis/Trichoderma harzianum = 1:3) (T₅). T₂–T₅ significantly increased dry matter accumulation, soil total N, ammonium N, nitrate N, and organic matter, improving yield by 3.81–26.63%. T₃ exhibited the highest yield increases in two consecutive years. At the jointing and heading stages, Penicillium and Saitozyma dominated under T₃ and positively correlated with dry matter, yield, and nitrogen levels. Straw return combined with Bacillus subtilis and Trichoderma harzianum (20 g m⁻² each) enhanced soil nitrogen availability and dry matter accumulation and translocation. Our findings guide efficient straw utilization, soil microbial regulation, and sustainable high-yield rice production. Full article

(This article belongs to the Section Agricultural Soils)

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27 pages, 68526 KiB

Open AccessArticle

Design and Evaluation of a Novel Actuated End Effector for Selective Broccoli Harvesting in Dense Planting Conditions

by Zhiyu Zuo, Yue Xue, Sheng Gao, Shenghe Zhang, Qingqing Dai, Guoxin Ma and Hanping Mao

Agriculture 2025, 15(14), 1537; https://doi.org/10.3390/agriculture15141537 - 16 Jul 2025

Viewed by 345

Abstract

The commercialization of selective broccoli harvesters, a critical response to agricultural labor shortages, is hampered by end effectors with large operational envelopes and poor adaptability to complex field conditions. To address these limitations, this study developed and evaluated a novel end-effector with an [...] Read more.

The commercialization of selective broccoli harvesters, a critical response to agricultural labor shortages, is hampered by end effectors with large operational envelopes and poor adaptability to complex field conditions. To address these limitations, this study developed and evaluated a novel end-effector with an integrated transverse cutting mechanism and a foldable grasping cavity. Unlike conventional fixed cylindrical cavities, our design utilizes actuated grasping arms and a mechanical linkage system to significantly reduce the operational footprint and enhance maneuverability. Key design parameters were optimized based on broccoli morphological data and experimental measurements of the maximum stem cutting force. Furthermore, dynamic simulations were employed to validate the operational trajectory and ensure interference-free motion. Field tests demonstrated an operational success rate of 93.33% and a cutting success rate of 92.86%. The end effector successfully operated in dense planting environments, effectively avoiding interference with adjacent broccoli heads. This research provides a robust and promising solution that advances the automation of broccoli harvesting, paving the way for the commercial adoption of robotic harvesting technologies. Full article

(This article belongs to the Topic New Research on Automated and Efficient Agricultural Machineries)

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Agriculture, Volume 15, Issue 14 (July-2 2025) – 108 articles

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