Agriculture

16 pages, 1546 KiB

Open AccessArticle

Assessing Fire Risks in Agricultural Balers: A Comprehensive Study

by María Videgain-Marco, Carlos Ayudán-Ibarz, Mariano Vidal-Cortés, Antonio Boné-Garasa and Francisco Javier García-Ramos

Agriculture 2025, 15(8), 908; https://doi.org/10.3390/agriculture15080908 - 21 Apr 2025

Viewed by 138

Abstract

Agricultural machinery, particularly balers, plays a crucial role in forage management. These machines are prone to fire incidents caused by mechanical friction, heat buildup, and the accumulation of crop residues, among other contributing factors. Despite their operational importance, fire risks associated with balers [...] Read more.

Agricultural machinery, particularly balers, plays a crucial role in forage management. These machines are prone to fire incidents caused by mechanical friction, heat buildup, and the accumulation of crop residues, among other contributing factors. Despite their operational importance, fire risks associated with balers remain largely understudied. This research aims to identify critical fire risk factors in large square balers through a combined analysis of survey data, temperature monitoring, and residue characterization. A questionnaire survey was conducted among 144 large square baler users to assess fire incidence and potential risk factors. Contingency table analysis and binary logistic regression were applied to identify variables significantly associated with the fire risk. Additionally, temperature data were recorded in six balers during two harvesting seasons, and residue samples were collected and analyzed to assess their ignition potential. Using a rake for windrowing was the only variable significantly associated with increased fire risk, making balers 3.4 times more likely to experience a fire (p = 0.034). Temperature analysis showed that the feeder fork brake (190.6 °C) and hydraulic pump (128.7 °C) were the hottest components, but none of the recorded temperatures exceeded the 250 °C ignition threshold of fine agricultural residues. Residue analysis showed that particles smaller than 250 µm accounted for 39% of the total material, underscoring their potential to contribute to fire propagation. This study highlights the critical influence of raking equipment on fire risk in balers and emphasizes the importance of preventive measures such as enhanced cleaning, real-time temperature monitoring, and improved mechanical design. These findings provide actionable insights for reducing fire hazards in agricultural operations and optimizing baler safety. Full article

(This article belongs to the Section Agricultural Technology)

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22 pages, 13562 KiB

Open AccessArticle

Brassinosteroids Alleviate Ethylene-Induced Copper Oxide Nanoparticle Toxicity and Ultrastructural and Stomatal Damage in Rice Seedlings

by Wardah Azhar, Abdul Salam, Ali Raza Khan, Irshan Ahmad and Yinbo Gan

Agriculture 2025, 15(8), 907; https://doi.org/10.3390/agriculture15080907 - 21 Apr 2025

Viewed by 226

Abstract

Nanoparticle contamination has been associated with adverse impacts on crop productivity. Thus, effective approaches are necessary to ameliorate NP-induced phytotoxicity. The present study aimed to investigate the efficacy of brassinosteroids and ethylene in regulating CuO NPs toxicity in rice seedlings. Therefore, we comprehensively [...] Read more.

Nanoparticle contamination has been associated with adverse impacts on crop productivity. Thus, effective approaches are necessary to ameliorate NP-induced phytotoxicity. The present study aimed to investigate the efficacy of brassinosteroids and ethylene in regulating CuO NPs toxicity in rice seedlings. Therefore, we comprehensively evaluated the crosstalk of 24-Epibrassinolide and ethylene in regulating CuO NP-induced phytotoxicity at the physiological, cellular ultrastructural, and biochemical levels. The results of the study illustrated that exposure to CuO NPs at 450 mg/L displayed a significant decline in growth attributes and induced toxic effects in rice seedlings. Furthermore, the exogenous application of ethylene biosynthesis precursor 1-aminocyclopropane-1-carboxylic acid (ACC) at 20 µM with 450 mg/L of CuO NPs significantly enhanced the reactive oxygen species (ROS) accumulation that led to the stimulation of ultrastructural and stomatal damage and reduced antioxidant enzyme activities (CAT and APX) in rice tissues. On the contrary, it was noticed that 24-Epibrassinolide (BR) at 0.01 µM improved plant biomass and growth, restored cellular ultrastructure, and enhanced antioxidant enzyme activities (CAT and APX) under exposure to 450 mg/L of CuO NPs. In addition, brassinosteroids reduced ROS accumulation and the toxic effects of 450 mg/L of CuO NPs on guard cells and the stomatal aperture of rice seedlings. Interestingly, when 0.01 µM of brassinosteroids, 20 µM of ACC, and 450 mg/L of CuO NPs were applied together, BRs and ethylene showed antagonistic crosstalk under CuO NP stress via partially reducing the ethylene-induced CuO NP toxicity on plant growth, cellular ultrastructure, stomatal aperture, and guard cell and antioxidant enzyme activities (CAT and APX) in rice seedlings. BR supplementation with ACC and CuO NPs notably diminished ACC-induced CuO NPs’ toxic effects on all of the mentioned attributes in rice seedlings. This study uncovered the interesting crosstalk of two main phytohormones under CuO NPs stress, providing basic knowledge to improve crop yield and productivity in CuO NPs-contaminated areas. Full article

(This article belongs to the Section Crop Production)

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27 pages, 8658 KiB

Open AccessArticle

Enhancing Agricultural Sustainability Through Intelligent Irrigation Using PVT Energy Applications: Implementing Hybrid Machine and Deep Learning Models

by Youness El Mghouchi and Mihaela Tinca Udristioiu

Agriculture 2025, 15(8), 906; https://doi.org/10.3390/agriculture15080906 - 21 Apr 2025

Viewed by 160

Abstract

This research focuses on developing an intelligent irrigation solution for agricultural systems utilising solar photovoltaic-thermal (PVT) energy applications. This solution integrates PVT applications, prediction, modelling and forecasting as well as plants’ physiological characteristics. The primary objective is to enhance water management and irrigation [...] Read more.

This research focuses on developing an intelligent irrigation solution for agricultural systems utilising solar photovoltaic-thermal (PVT) energy applications. This solution integrates PVT applications, prediction, modelling and forecasting as well as plants’ physiological characteristics. The primary objective is to enhance water management and irrigation efficiency through innovative digital techniques tailored to different climate zones. In the initial phase, the performance of PVT solutions was evaluated using ANSYS Fluent software R19.2, revealing that scaled PVT systems offer optimal efficiency for PV systems, thereby optimising electrical production. Subsequently, a comprehensive approach combining integral feature selection (IFS) with machine learning (ML) and deep learning (DL) models was applied for reference evapotranspiration (ETo) prediction and water needs forecasting. Through this process, 301 optimal combinations of predictors and best-performing linear models for ETo prediction were identified. Achieving R² values exceeding 0.97, alongside minimal indicators of dispersion, the results indicate the effectiveness and accuracy of the elaborated models in predicting the ETo. In addition, by employing a hybrid deep learning approach, 28 best models were developed for forecasting the next periods of ETo. Finally, an interface application was developed to house the identified models for predicting and forecasting the optimal water quantity required for specific plant or crop irrigation. This application serves as a user-friendly platform where users can input relevant predictors and obtain accurate predictions and forecasts based on the established models. Full article

(This article belongs to the Section Digital Agriculture)

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24 pages, 6029 KiB

Open AccessReview

Synergistic Approaches for Sustainable Remediation of Organic Contaminated Soils: Integrating Biochar and Phytoremediation

by Hao Fang, Cailing Zhou, Dong-Xing Guan, Muhammad Azeem and Gang Li

Agriculture 2025, 15(8), 905; https://doi.org/10.3390/agriculture15080905 - 21 Apr 2025

Viewed by 239

Abstract

Various industrial and agricultural activities have led to significant organic pollution in soil, posing an ongoing threat to both soil ecosystems and human health. Among the available remediation methods, phytoremediation and biochar remediation are recognized as sustainable and low-impact approaches. However, individual remediation [...] Read more.

Various industrial and agricultural activities have led to significant organic pollution in soil, posing an ongoing threat to both soil ecosystems and human health. Among the available remediation methods, phytoremediation and biochar remediation are recognized as sustainable and low-impact approaches. However, individual remediation methods often have limitations, such as plant susceptibility to adverse soil conditions and the desorption of pollutants from biochar. Therefore, integrating biochar with phytoremediation for the remediation of organic-contaminated soils provides a complementary approach that addresses the drawbacks of applying each method alone. The key mechanism of this combined technology lies in the ability of biochar to enhance plant resilience, plant absorption of pollutants, and the degradation capacity of rhizosphere microorganisms. Simultaneously, plants can completely degrade pollutants adsorbed by biochar or present in the soil, either directly or indirectly, through root exudates. This review systematically explores the mechanisms underlying the interactions between biochar and phytoremediation, reviews the progress of their application in the remediation of organic-contaminated soils, and discusses the associated challenges and prospects. Full article

(This article belongs to the Special Issue Risk Assessment and Remediation of Agricultural Soil Pollution)

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15 pages, 3328 KiB

Open AccessArticle

AGRARIAN: A Hybrid AI-Driven Architecture for Smart Agriculture

by Michael C. Batistatos, Tomaso de Cola, Michail Alexandros Kourtis, Vassiliki Apostolopoulou, George K. Xilouris and Nikos C. Sagias

Agriculture 2025, 15(8), 904; https://doi.org/10.3390/agriculture15080904 - 21 Apr 2025

Viewed by 166

Abstract

Modern agriculture is increasingly challenged by the need for scalable, sustainable, and connectivity-resilient digital solutions. While existing smart farming platforms offer valuable insights, they often rely heavily on centralized cloud infrastructure, which can be impractical in rural or remote settings. To address this [...] Read more.

Modern agriculture is increasingly challenged by the need for scalable, sustainable, and connectivity-resilient digital solutions. While existing smart farming platforms offer valuable insights, they often rely heavily on centralized cloud infrastructure, which can be impractical in rural or remote settings. To address this gap, this paper presents AGRARIAN, a hybrid AI-driven architecture that combines IoT sensor networks, UAV-based monitoring, satellite connectivity, and edge-cloud computing to deliver real-time, adaptive agricultural intelligence. AGRARIAN supports a modular and interoperable architecture structured across four layers—Sensor, Network, Data Processing, and Application—enabling flexible deployment in diverse use cases such as precision irrigation, livestock monitoring, and pest forecasting. A key innovation lies in its localized edge processing and federated AI models, which reduce reliance on continuous cloud access while maintaining analytical performance. Pilot scenarios demonstrate the system’s ability to provide timely, context-aware decision support, enhancing both operational efficiency and digital inclusion for farmers. AGRARIAN offers a robust and scalable pathway for advancing autonomous, sustainable, and connected farming systems. Full article

(This article belongs to the Special Issue Computational, AI and IT Solutions Helping Agriculture)

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18 pages, 7147 KiB

Open AccessArticle

Intercropping Forage Mulberry Benefits Nodulation and Growth of Soybeans

by Xinjie Feng, Minghui Zhong, Xuexian Zhao, Xiuli Zhang, Yanbo Hu and Huihui Zhang

Agriculture 2025, 15(8), 902; https://doi.org/10.3390/agriculture15080902 - 21 Apr 2025

Viewed by 192

Abstract

In northern China, intercropping soybeans with forage mulberry (Morus alba L.) enhances soybean yields through the optimization of natural resource use. However, the mechanisms underlying these improvements remain largely unknown. The aim was to explore the effects of this intercropping on soybean [...] Read more.

In northern China, intercropping soybeans with forage mulberry (Morus alba L.) enhances soybean yields through the optimization of natural resource use. However, the mechanisms underlying these improvements remain largely unknown. The aim was to explore the effects of this intercropping on soybean growth and yield. We used transcriptomics, redundancy analysis, and structural equation modeling to evaluate soybean growth, yield, and nodulation; results showed that intercropping did not adversely affect plant height or stem diameter but increased chlorophyll content, photosynthetic rate, leaf area, and yield of soybean. It also increased soil available phosphorus, soil available potassium and soil water content, while reducing soil available nitrogen and the pH value. It promoted P and organic acid metabolism, transporter activity, and key-gene expression. Redundancy analysis strikingly reveals that intercropping is positively correlated with yield, gene expression and soil properties. Meanwhile, structural equation modeling analysis demonstrates that the content of available phosphorus, available potassium, and water in rhizosphere soil are positively correlated with soybean nodulation. Additionally, nodulation traits can directly enhance nitrogen metabolism, which subsequently boosts photosynthesis and ultimately exerts an indirect positive influence on soybean yield. Furthermore, intercropping soybeans with forage mulberry did not induce shade stress on the above-ground portion of soybeans but promoted its growth and nodulation. Full article

(This article belongs to the Section Crop Production)

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26 pages, 5464 KiB

Open AccessArticle

An Innovative Indoor Localization Method for Agricultural Robots Based on the NLOS Base Station Identification and IBKA-BP Integration

by Jingjing Yang, Lihong Wan, Junbing Qian, Zonglun Li, Zhijie Mao, Xueming Zhang and Junjie Lei

Agriculture 2025, 15(8), 901; https://doi.org/10.3390/agriculture15080901 - 21 Apr 2025

Viewed by 212

Abstract

This study proposes an innovative indoor localization algorithm based on the base station identification and improved black kite algorithm–backpropagation (IBKA-BP) integration to address the problem of low positioning accuracy in agricultural robots operating in agricultural greenhouses and breeding farms, where the Global Navigation [...] Read more.

This study proposes an innovative indoor localization algorithm based on the base station identification and improved black kite algorithm–backpropagation (IBKA-BP) integration to address the problem of low positioning accuracy in agricultural robots operating in agricultural greenhouses and breeding farms, where the Global Navigation Satellite System is unreliable due to weak or absent signals. First, the density peaks clustering (DPC) algorithm is applied to select a subset of line-of-sight (LOS) base stations with higher positioning accuracy for backpropagation neural network modeling. Next, the collected received signal strength indication (RSSI) data are processed using Kalman filtering and Min-Max normalization, suppressing signal fluctuations and accelerating the gradient descent convergence of the distance measurement model. Finally, the improved black kite algorithm (IBKA) is enhanced with tent chaotic mapping, a lens imaging reverse learning strategy, and the golden sine strategy to optimize the weights and biases of the BP neural network, developing an RSSI-based ranging algorithm using the IBKA-BP neural network. The experimental results demonstrate that the proposed algorithm can achieve a mean error of 16.34 cm, a standard deviation of 16.32 cm, and a root mean square error of 22.87 cm, indicating its significant potential for precise indoor localization of agricultural robots. Full article

(This article belongs to the Section Digital Agriculture)

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20 pages, 9259 KiB

Open AccessArticle

ARIMA-Kriging and GWO-BiLSTM Multi-Model Coupling in Greenhouse Temperature Prediction

by Wei Zhou, Shuo Liu, Junxian Guo, Na Liu, Zhenglin Li and Chang Xie

Agriculture 2025, 15(8), 900; https://doi.org/10.3390/agriculture15080900 - 21 Apr 2025

Viewed by 214

Abstract

Accurate prediction of greenhouse temperatures is essential for developing effective environmental control strategies, as the precision of minimum temperature data acquisition significantly impacts the reliability of predictive models. Traditional monitoring methods face inherent challenges due to the conflicting demands of temperature-field uniformity assumptions [...] Read more.

Accurate prediction of greenhouse temperatures is essential for developing effective environmental control strategies, as the precision of minimum temperature data acquisition significantly impacts the reliability of predictive models. Traditional monitoring methods face inherent challenges due to the conflicting demands of temperature-field uniformity assumptions and the costs associated with sensor deployment. This study introduces an ARIMA-Kriging spatiotemporal coupling model, which combines temperature time-series data with sensor spatial coordinates to accurately determine minimum temperatures in greenhouses while reducing hardware costs. Utilizing the high-quality data processed by this model, this study proposes and constructs a novel Grey Wolf Optimizer and Bidirectional Long Short-Term Memory (GWO-BiLSTM) temperature prediction framework, which combines a Grey Wolf Optimizer (GWO)-enhanced algorithm with a Bidirectional Long Short-Term Memory (BiLSTM) network. Across different prediction horizons (10 min and 30 min intervals), the GWO-BiLSTM model demonstrated superior performance with key metrics reaching a coefficient of determination (R²) of 0.97, root mean square error (RMSE) of 0.79–0.89 °C (41.7% reduction compared to the PSO-BP model), mean absolute percentage error (MAPE) of 4.94–8.5%, mean squared error (MSE) of 0.63–0.68 °C, and mean absolute error (MAE) of 0.62–0.65 °C, significantly outperforming the BiLSTM, LSTM, and PSO-BP models. Multi-weather validation confirmed the model’s robustness under rainy, snowy, and overcast conditions, maintaining R² ≥ 0.95. Optimal prediction accuracy was observed in clear weather (RMSE = 0.71 °C), whereas rainy/snowy conditions showed a 42.9% improvement in MAPE compared to the PSO-BP model. This study provides reliable decision-making support for precise environmental regulation in facility greenhouse environments, effectively advancing the intelligent development of agricultural environmental control systems. Full article

(This article belongs to the Section Digital Agriculture)

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23 pages, 718 KiB

Open AccessArticle

Assessment of Technical and Eco-Efficiency of Dairy Farms in the Republic of Serbia: Towards the Implementation of a Circular Economy

by Tihomir Novaković, Dragana Novaković, Dragan Milić, Mirela Tomaš Simin, Maja Radišić, Mladen Radišić, Srboljub Nikolić and Milan Mihajlović

Agriculture 2025, 15(8), 899; https://doi.org/10.3390/agriculture15080899 - 21 Apr 2025

Viewed by 108

Abstract

Efforts to improve agricultural sustainability have increasingly focused on enhancing productivity while minimizing environmental impact. In the Republic of Serbia, dairy farming remains a critical sector due to its dual role in food production and environmental pressure. This study aims to evaluate the [...] Read more.

Efforts to improve agricultural sustainability have increasingly focused on enhancing productivity while minimizing environmental impact. In the Republic of Serbia, dairy farming remains a critical sector due to its dual role in food production and environmental pressure. This study aims to evaluate the technical and eco-efficiency of dairy farms in the Republic of Serbia using FADN data and the Stochastic Frontier Analysis (SFA) method. Specifically, the SFA methodology was applied, which enables a separate assessment of time-invariant and time-variant efficiency, with the aim of clearly identifying the factors that shape milk production in the Republic of Serbia. It was found that the technical efficiency for the 2015–2023 period was at a level of 58.7%, while the eco-efficiency was estimated to be 13.1%. Observing the relationship between the estimated technical and eco-efficiency, it can be concluded that they share similar mechanisms for improvement. In both cases, time-invariant inefficiency dominated, indicating that factors under the control of farms, such as the characteristics of agricultural producers and farms, play a key role in shaping production efficiency. In this context, adopting circular economy principles, such as nutrient recycling, the use of renewable energy, and optimized input utilization, offers an additional opportunity to enhance both economic and environmental performance. Full article

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

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17 pages, 3375 KiB

Open AccessArticle

Cover Crops for Carbon Mitigation and Biodiversity Enhancement: A Case Study of an Olive Grove in Messinia, Greece

by Ioanna Michail, Christos Pantazis, Stavros Solomos, Michail Michailidis, Athanassios Molassiotis and Vasileios Gkisakis

Agriculture 2025, 15(8), 898; https://doi.org/10.3390/agriculture15080898 - 21 Apr 2025

Viewed by 136

Abstract

Land desertification is becoming increasingly significant for the Mediterranean basin, particularly due to the rising pressures on agricultural land. Regarding the olive grove sector, intensive farming methods can have detrimental effects on the provision of various agroecosystem services. Conversely, agroecological approaches, such as [...] Read more.

Land desertification is becoming increasingly significant for the Mediterranean basin, particularly due to the rising pressures on agricultural land. Regarding the olive grove sector, intensive farming methods can have detrimental effects on the provision of various agroecosystem services. Conversely, agroecological approaches, such as reduced tillage/no tillage and the use of cover crops, can help mitigate soil degradation and enhance soil arthropod biodiversity. Herein, an experiment was conducted in a hilly olive grove in southern Peloponnese, a key olive production area in Greece. Different soil treatments were implemented across nine plots (three plots per treatment), including the following: (i) the use of a cover crop mixture (Pisum sativum, Vicia faba, Hordeum vulgare), (ii) herbicide application, and (iii) spontaneous vegetation (control). A comprehensive survey was performed at the plot level for monitoring carbon sequestration and ground-dwelling arthropod diversity. The results indicated that cover crops had a positive impact on soil fertility and structure, leading to an increase in total biomass production per plot, while also contributing to the preservation of key soil arthropod populations when compared to treatments that resulted in bare soil. The findings from this in situ study are meant to be integrated into the frames of a long-term monitoring process in order to be used for climate change mitigation and biodiversity management models, enhancing the resilience and regeneration of degraded land. Full article

(This article belongs to the Section Agricultural Soils)

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25 pages, 1107 KiB

Open AccessArticle

Impact of Peas (Pisum Sativum L.) as a Sustainable Source of Protein in Growing Pigs’ Diets on Production Efficiency, Nitrogen Metabolism and Gastrointestinal Tract Health

by Tatiana Dumitra Panaite, Gabriela Maria Cornescu, Elvira Gagniuc, Ana Elena Cismileanu, Claudiu Gal, Mihaela Dumitru and Smaranda Mariana Toma

Agriculture 2025, 15(8), 897; https://doi.org/10.3390/agriculture15080897 - 20 Apr 2025

Viewed by 209

Abstract

This pilot study evaluated the effects of dietary pea inclusion as a sustainable and nutritional alternative protein source on growth performance, nitrogen balance, digestibility, and intestinal health on nine castrated male Topigs hybrid pigs (three pigs/group), with an initial average weight of 20 [...] Read more.

This pilot study evaluated the effects of dietary pea inclusion as a sustainable and nutritional alternative protein source on growth performance, nitrogen balance, digestibility, and intestinal health on nine castrated male Topigs hybrid pigs (three pigs/group), with an initial average weight of 20 ± 2.5 kg, for 45 experimental days. To conduct this digestibility pilot study, the pigs were kept individually in metabolic cages. Three experimental groups were compared: T₀ (control), T₁₀ (10% pea inclusion), and T₂₀ (20% pea inclusion). Growth performance parameters, such as the feed conversion ratio (FCR), daily feed intake (DFI), and dry matter intake (DMI), were significantly higher in the T₁₀ and T₂₀ groups compared to T₀ (p < 0.05). Nitrogen retention was significantly higher in the T₁₀ group (p = 0.042) compared to the T₀ group only. Biochemical markers, such as the total bilirubin (T-Bil) and uric acid (UA) levels, were significantly higher in T₂₀ compared to T₀ (p < 0.05). The short-chain fatty acids (SCFAs) increased significantly in the ceca and ilea of the T₁₀ and T₂₀ groups compared to T₀, with higher levels of acetic acid (C2) and butyric acid (C4). A positive effect on Lactobacillus populations was observed in both the ileum and cecum in the T₁₀ and T₂₀ groups (p < 0.05). Intestinal morphology analysis revealed that the villus width, villus area, and crypt depth were significantly increased in the jejuna and ilea of both pea-fed groups. The N retention, SCFA concentration, and Lactobacillus population from the ileal and cecal segments showed a strong correlation. These findings suggest that the dietary inclusion of peas positively impacts growth performance, nitrogen retention, and intestinal health, with enhanced microbial populations and improved gut morphology. Full article

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

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16 pages, 3816 KiB

Open AccessArticle

Research on Axial-Flow Corn-Threshing Technology for High-Throughput Conditions

by Lin Niu, Pengxuan Guan, Xinxin Wang, Yang Wang and Duanyang Geng

Agriculture 2025, 15(8), 896; https://doi.org/10.3390/agriculture15080896 - 20 Apr 2025

Viewed by 91

Abstract

To address the problems of corn harvesting in the Yellow Huaihai region with high moisture content, such as grain damage and high failure rate, a wider and taller ripple block threshing element was designed by combining the threshing principles of different threshing elements [...] Read more.

To address the problems of corn harvesting in the Yellow Huaihai region with high moisture content, such as grain damage and high failure rate, a wider and taller ripple block threshing element was designed by combining the threshing principles of different threshing elements and analyzing the effects of the overall layout and parameters of the element on the threshing process. The threshing element can improve the collision attitude between the corn and the element and prioritize part of the corn kernels falling off during the collision, which makes the subsequent threshing smoother and realizes a low crushing rate of corn in the process of corn detachment. The different stages of the corn-threshing process were analyzed, a threshing simulation test was carried out, and the threshing force of the intact corn on the top side was measured to be 42.86 N; the closer the kernel was to the position of the dislodged kernel, the more the dislodging force was gradually reduced, with a minimum of 2.09 N, which verified that it was difficult to dislodge the kernel when the ear was intact and that the difficulty of dislodging the kernel around the kernel decreased as the corn was dislodged. Full article

(This article belongs to the Section Agricultural Technology)

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20 pages, 14184 KiB

Open AccessArticle

Effects of Rare Earth Element-Rich Biochar on Soil Quality and Microbial Community Dynamics of Citrus grandis (L.) Osbeck. cv. Guanximiyou

by Zhiqi Chen, Liujun Feng, Zhiqiang Chen, Zhibiao Chen, Jie Wu and Qiang Lin

Agriculture 2025, 15(8), 895; https://doi.org/10.3390/agriculture15080895 - 20 Apr 2025

Viewed by 126

Abstract

Rare earth elements (REEs) are key resources of strategic importance, but pollution has increased due to uncontrolled mining. Although heavy metal hyperaccumulating plants are environmentally friendly, they require strict control during post-treatment, or they may cause secondary pollution. Therefore, their safe disposal plays [...] Read more.

Rare earth elements (REEs) are key resources of strategic importance, but pollution has increased due to uncontrolled mining. Although heavy metal hyperaccumulating plants are environmentally friendly, they require strict control during post-treatment, or they may cause secondary pollution. Therefore, their safe disposal plays a key role in the ecological restoration of REE mines. In this study, rare earth element (REE)-rich biochar was produced by pyrolyzing the REE hyperaccumulator Dicranopteris pedata. This biochar was then applied to the Citrus grandis (L.) Osbeck. cv. Guanximiyou soil amendment experiment to evaluate its effects on soil physicochemical properties and microbial indicators. Four treatments were established: CK (0% REE-rich biochar), BC1 (1% REE-rich biochar), BC3 (3% REE-rich biochar), and BC5 (5% REE-rich biochar). The BC5 treatment decreased soil REE bioavailability, thereby preventing REE pollution. The BC5 treatment also demonstrated the highest efficacy in improving soil total organic carbon (229.11%), total nitrogen (53.92%), total phosphorus (55.61%), total potassium (55.50%), available nitrogen (14.76%), available phosphorus (46.79%), and available potassium (159.42%) contents compared to CK. Furthermore, soil enzyme activities were significantly increased by BC5 treatment (p < 0.05). At the bacterial phylum level of classification, the bacterial diversity index (Chao1 and Shannon) exhibited elevated levels under BC5 conditions. Furthermore, the Chao1 index of fungal diversity exhibited a substantial augmentation of 55.67% (p < 0.05) in the BC5 treatment in comparison to the CK, and also significantly higher than the other treatments (p < 0.05). Our study showed that the composition of soil microorganisms was altered by REE-rich biochar. Proteobacteria, Acidobacteria, Actinobacteriota, and Chloroflexi are dominant among bacteria, while Ascomycota is dominant among fungi. Mantel and redundancy analyses showed that the most important environmental factor affecting the structure of soil microbial communities was pH, especially in the case of bacteria. In summary, this study showed that the application of 5% REE-rich biochar provided the best improvement in soil physicochemical properties and microbial diversity. These findings highlight its potential for soil remediation and provide new ideas for recycling heavy metal hyperaccumulating plant waste. Full article

(This article belongs to the Section Agricultural Soils)

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22 pages, 1858 KiB

Open AccessReview

Biochar as a Feedstock for Sustainable Fertilizers: Recent Advances and Perspectives

by Marcela Granato Barbosa dos Santos, Andressa Blasi Paiva, Rhaila da Silva Rodrigues Viana, Keiji Jindo and Cícero Célio de Figueiredo

Agriculture 2025, 15(8), 894; https://doi.org/10.3390/agriculture15080894 - 20 Apr 2025

Viewed by 232

Abstract

The increase in the world population exerts significant pressure on expanding global agricultural production. To achieve this, the use of fertilizers is fundamental. However, highly soluble traditional chemical fertilizers can be easily leached and volatilized, causing environmental damage. Therefore, reducing the use of [...] Read more.

The increase in the world population exerts significant pressure on expanding global agricultural production. To achieve this, the use of fertilizers is fundamental. However, highly soluble traditional chemical fertilizers can be easily leached and volatilized, causing environmental damage. Therefore, reducing the use of these fertilizers and developing new and smart fertilizers is crucial. Biochar, a solid and carbon-rich pyrolysis product, has been studied both as a standalone fertilizer and as a raw material for sustainable fertilizers. Recently, a wide variety of materials and techniques have been used in the production of biochar-based fertilizers (BBFs) and need to be grouped and critically evaluated. Thus, this study aimed to conduct a literature review on new biochar-based fertilizers, involving different routes for biochar-based fertilizer synthesis and their effects on various crops. Recent results indicate the growing interest in nanomaterials and microbial processes for producing new fertilizers. Most assessed studies use biochar to produce slow-release fertilizers. The results also indicate that these new biochar-based fertilizers increase crop yields and reduce the leaching and volatilization of nutrients in soil, demonstrating significant potential as an alternative to traditional fertilizers. Therefore, the agricultural use of biochar holds environmental importance by reducing the negative impacts caused by the use of highly soluble traditional fertilizers. However, long-term field experiments and the economic feasibility of BBF production routes must be carefully studied. Full article

(This article belongs to the Section Agricultural Soils)

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21 pages, 3394 KiB

Open AccessArticle

Assessment of Integrated BMPs for Subbasin-Scale Soil Erosion Reduction Considering Spatially Distributed Farmland Characteristics

by Jimin Lee, Seoro Lee, Woon Ji Park, Minhwan Shin and Kyoung Jae Lim

Agriculture 2025, 15(8), 893; https://doi.org/10.3390/agriculture15080893 - 20 Apr 2025

Viewed by 178

Abstract

Recent climate change has intensified extreme rainfall events, exacerbating soil erosion and agricultural nonpoint source pollution in South Korea’s steeply sloped farmlands. This study assessed soil erosion reduction measures by applying individual Best Management Practices (BMPs) in cropland and expanding upon existing management [...] Read more.

Recent climate change has intensified extreme rainfall events, exacerbating soil erosion and agricultural nonpoint source pollution in South Korea’s steeply sloped farmlands. This study assessed soil erosion reduction measures by applying individual Best Management Practices (BMPs) in cropland and expanding upon existing management efforts through the implementation of additional BMPs aimed at further reducing soil erosion. Furthermore, priority management areas were identified based on soil erosion reduction efficiency within subbasins. For this evaluation, the Soil and Water Assessment Tool (SWAT) was employed, with a spatially distributed Hydrological Response Unit (SD-HRU) module and calibrated Modified Universal Soil Loss Equation (MUSLE) parameters tailored to Korean watershed conditions. Scenarios 1 and 2 were implemented in the study area to evaluate BMP effectiveness in controlling soil erosion and suspended sediment (SS) loads. Scenario 1 applied a set of BMPs already in place, while Scenario 2 involved the addition of supplementary BMPs to enhance soil erosion control. Scenario 1 resulted in a 34.6% reduction in annual soil erosion and a 35.0% decrease in SS concentration, whereas Scenario 2 achieved a 59.3% reduction in soil erosion and a 57.3% decrease in SS concentration. Subbasin-scale evaluations revealed considerable spatial variability in erosion control efficiency, ranging from 1.3% to 70.5%, highlighting the necessity for spatially targeted management strategies. These results underscore the importance of employing spatially adaptive BMP approaches and offer practical guidance for enhancing watershed sustainability, particularly in regions vulnerable to extreme hydrometeorological events. 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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20 pages, 3586 KiB

Open AccessArticle

Nitrogen Fertiliser Reduction at Different Rice Growth Stages and Increased Density Improve Rice Yield and Quality in Northeast China

by Wenjun Dong, Yuhan Zhang, Frederick Danso, Jun Zhang, Ao Tang, Youhong Liu, Kai Liu, Ying Meng, Lizhi Wang, Zhongliang Yang and Feng Jiao

Agriculture 2025, 15(8), 892; https://doi.org/10.3390/agriculture15080892 - 20 Apr 2025

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Abstract

Rice yield and quality decline due to excessive fertiliser use is problematic in China. To increase rice grain filling and improve rice yield and quality, a nitrogen reduction and density increase study in 2023 and 2024 was imposed on a long-term experimental field. [...] Read more.

Rice yield and quality decline due to excessive fertiliser use is problematic in China. To increase rice grain filling and improve rice yield and quality, a nitrogen reduction and density increase study in 2023 and 2024 was imposed on a long-term experimental field. The four treatments adopted for the study were normal nitrogen and normal density (CK), normal nitrogen and increased density (NN+ID), reduced nitrogen in panicle fertiliser and increased density (RPN+ID), and reduced nitrogen in basal fertiliser and increased density (RBN+ID). RPN+ID and RBN+ID, respectively, produced a 3.0% and 5.1% higher yield than CK in both years. The mean grain filling rate (Va) of superior grains in RBN+ID increased by 12.5%, while the mean grain filling rate (Va) of inferior grains in the RPN+ID treatment increased by 4.2% with respect to CK. RPN+ID caused 0.4%, 9.6%, and 13.3% decline in the brown rice rate, chalkiness degree, and chalkiness rate, respectively, while RBN+ID triggered 0.4%, 7.2%, and 11.0% decline in the brown rice rate, chalkiness degree, and chalkiness rate, respectively. RPN+ID stimulated 4.2% and 3.1% increases in flavour and straight-chain amylose values, respectively. Whereas a 20% reduction in basal nitrogen fertiliser and a 32% increase in density improved the yield and appearance quality of rice, a 20% reduction in nitrogen fertiliser at the panicle stage and a 32% increase in density promoted a higher steaming flavour quality. Therefore, an appropriate reduction in nitrogen fertiliser while simultaneously increasing rice density has a significant impact on rice quality, fertiliser pollution reduction, and is a theoretical basis for rice yield and quality improvement in Northeast China. Full article

(This article belongs to the Special Issue Effect of Cultivation Practices on Crop Yield and Quality)

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12 pages, 2508 KiB

Open AccessArticle

Approach to Selenium Application in Different Soil Concentrations for Encouraged Yield, Distribution, and Biofortification of Common Buckwheat Seeds (Fagopyrum esculentum Moench)

by Alexandra Zapletalová, Marek Kolenčík, Ladislav Ducsay, Mária Vicianová, Tomáš Vician, Ivan Černý and Rastislav Bušo

Agriculture 2025, 15(8), 891; https://doi.org/10.3390/agriculture15080891 - 19 Apr 2025

Viewed by 207

Abstract

The soil application of essential trace elements, such as selenium and its various agrochemical species, presents a real challenge for modern agriculture. However, unknown exceeding threshold concentrations could target potential toxicity within the soil–plant–organism. When applied at optimal levels and combined with the [...] Read more.

The soil application of essential trace elements, such as selenium and its various agrochemical species, presents a real challenge for modern agriculture. However, unknown exceeding threshold concentrations could target potential toxicity within the soil–plant–organism. When applied at optimal levels and combined with the common buckwheat—a crop of the future known for its high nutritional value—this poses a novel academic approach. Therefore, the aim of this research is to examine the effect of three concentrations (150, 300, and 600 g/ha) of selenium species (sodium selenite and sodium selenate) on mobility and distribution within the common buckwheat plant, including its impact on the biofortification. The research was carried out during the 2022 and 2023 seasons through pot experiments in semi-regulated conditions located in the Central European agronomic region. Following manual harvesting, chemical analysis was conducted using methods such as atomic absorption spectroscopy (AAS) and inductively coupled plasma mass spectrometry (ICP-MS), along with yield determination. The results confirmed the positive effect of Se⁶⁺ 150 g/ha and Se⁴⁺ 150 g/ha and 300 g/ha on seed yield. Oppositely, Se⁶⁺ 600 g/ha caused a decrease in seed yield of 23.87%. For biofortification of common buckwheat is most suitable Se⁶⁺ in a dose of 150 g/ha, where the Se content in seeds, 3.30 ± 0.46 mg/kg, was achieved. The soil fertility index, based on PCA, indicated that Se⁶⁺ at 150 g/ha exhibited the highest biofortification efficiency without compromising yield. Full article

(This article belongs to the Section Agricultural Soils)

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18 pages, 2050 KiB

Open AccessArticle

Influence of Epiphytic Microorganisms on Silage Quality and Aerobic Exposure Characteristics of Grass Pastures

by Qi Yan, Hao Ding, Chenghuan Qin, Qichao Gu, Xin Gao, Yongqi Tan, Deshuang Wei, Yiqiang Li, Nanji Zhang, Ruizhanghui Wang, Bo Lin and Caixia Zou

Agriculture 2025, 15(8), 890; https://doi.org/10.3390/agriculture15080890 - 19 Apr 2025

Viewed by 180

Abstract

In this study, we investigated whether epiphytic microorganisms of fresh forage affect silage quality and aerobic exposure of silage by determining the changes in chemical composition, fermentation characteristics and microbial population of two grass forages (sugarcane tops and corn stover) under aerobic exposure [...] Read more.

In this study, we investigated whether epiphytic microorganisms of fresh forage affect silage quality and aerobic exposure of silage by determining the changes in chemical composition, fermentation characteristics and microbial population of two grass forages (sugarcane tops and corn stover) under aerobic exposure treatments (fresh, end-of-storage and aerobic exposure periods). There were nine replicates for each of the two forage silages. The total silage time was 60 days, after which the cellar was opened for a 12-day period for aerobic exposure measurements. At the end of ensiling, the lactic acid content of corn stover silage (116.78 g/kg DM) was significantly higher than that of sugarcane top silage (16.07 g/kg DM; p < 0.01), and the corn stover (3.53) had a significantly lower pH than sugarcane tops (4.46) (p < 0.01). Weissella was the most abundant epiphytic lactic acid bacteria (LAB) in sugarcane tops and corn stover (19.08% and 11.15%, respectively). The relative abundance of epiphytic Pediococcus was higher in sugarcane tops (0.17%) than in corn stover (0.09%; p < 0.05). The relative abundance of Pediococcus was significantly higher in sugarcane top silage (2.24%) than in corn stover silage during the aerobic exposure period (p < 0.01). The acetic acid content of corn stover silage was significantly reduced during aerobic exposure (p < 0.01) due to the abundance of Paenibacillus (62.38%). The fungal genus Candida affected the aerobic exposure of sugarcane top (37.88%) and corn stover silage (73.52%). In summary, Weissella was the genus of lactic acid bacteria present in the highest abundance in sugarcane tops and corn stover, favoring early and rapid acidification. In addition, Candiada, which consumes organic acids in large numbers, was the fungal genus that influenced the aerobic exposure of sugarcane top silage versus corn stover silage. Full article

(This article belongs to the Special Issue Silage Preparation, Processing and Efficient Utilization—2nd Edition)

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15 pages, 495 KiB

Open AccessArticle

Evaluating Maturity Index I_AD for Storability Potential in Mid-Season and Late-Season Apple Cultivars in the Light of Climate Change

by Joakim Sjöstrand, Ibrahim Tahir, Henrik Stridh and Marie E. Olsson

Agriculture 2025, 15(8), 889; https://doi.org/10.3390/agriculture15080889 - 19 Apr 2025

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Abstract

Reducing food losses in apple production is becoming increasingly important, as the effects of climate change constitute a challenge to food production. Improving methods for determining fruit maturity at harvest leading to the longest storability is crucial, thereby facing more unpredictable seasonal weather [...] Read more.

Reducing food losses in apple production is becoming increasingly important, as the effects of climate change constitute a challenge to food production. Improving methods for determining fruit maturity at harvest leading to the longest storability is crucial, thereby facing more unpredictable seasonal weather conditions. In addition, the increasing temperature is affecting common maturity indices differently; thus, present practice may not be valid. In this study, a non-destructive, time-efficient method was used, tentatively indicating maturity. This study was performed during three climate-diverse years, reflecting more irregular climate conditions. Mid- to late-season cultivars ‘Frida’, ‘Ingrid Marie’, ‘Rubinstar’, and ‘Elise’ were harvested at different pre-determined I_AD (index of absorbance difference) intervals and stored for five months. Correlations between I_AD values at harvest and total losses after storage were found for all cultivars and years, while only a few correlations related to firmness after storage were found. Although a strong effect of year was related to correlations between I_AD and different quality parameters, no noticeably general differences could be found between the exceptionally warm year in comparison to the other investigated years. I_AD, as a maturity index, thus, seems to be resilient to changing temperatures and can be used as a complementary maturity index. Full article

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

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16 pages, 1489 KiB

Open AccessArticle

Sward Diversity Modulates Soil Carbon Dynamics After Ploughing Temporary Grassland

by Hendrik P. J. Smit, Hanna Anders, Christof Kluß, Friedhelm Taube, Ralf Loges and Arne Poyda

Agriculture 2025, 15(8), 888; https://doi.org/10.3390/agriculture15080888 - 19 Apr 2025

Viewed by 138

Abstract

Grasslands are crucial for sequestering carbon underground, but disturbances like ploughing can lead to significant soil organic carbon (SOC) loss as CO₂, a potent greenhouse gas. Thus, managed grasslands should be maintained to minimize GHG emissions. A field study was carried [...] Read more.

Grasslands are crucial for sequestering carbon underground, but disturbances like ploughing can lead to significant soil organic carbon (SOC) loss as CO₂, a potent greenhouse gas. Thus, managed grasslands should be maintained to minimize GHG emissions. A field study was carried out to investigate how varying sward diversity influences soil respiration following the ploughing of temporary grassland. This study investigated the extent of CO₂ emissions from different species mixtures immediately after ploughing, as well as C losses when straw was added to plots, over a 142-day period. The species mixture treatments consisted of a binary mixture (BM), a tertiary mixture (TM), and a complex mixture (CM), which were compared to two bare plot treatments, one of which was also ploughed. The highest CO₂ flux occurred immediately after ploughing and was observed in the BM treatment (1.99 kg CO₂-C ha⁻¹ min⁻¹). Accumulated CO₂ emissions ranged from 0.4 to 14.8 t CO₂ ha⁻¹. The ploughing effect on CO₂ emissions was evident for bare soils, as ploughing increased soil aeration, which enhanced microbial activity and accelerated the decomposition rate of soil organic matter. However, different mixtures did not affect the C turnover rate. Adding straw to treatments resulted in 43% higher CO₂ emissions compared to bare plots. The BM treatment likely induced a higher priming effect, suggesting that the incorporated straw, under different sward residues, influenced CO₂ emissions more than the mechanical disturbance caused by ploughing. Findings suggest that using complex species mixtures can be recommended as a strategy to reduce CO₂ emissions from incorporated biomass and minimize the priming effect of native soil carbon. Full article

(This article belongs to the Special Issue Research on Soil Carbon Dynamics at Different Scales on Agriculture)

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10 pages, 241 KiB

Open AccessArticle

Precision Feeding in Lactating Sows Improves Growth Performance and Carcass Quality of Their Progeny

by María Aparicio-Arnay, Natalia Yeste-Vizcaíno, Nerea Soria, Jorge Cambra, Beatriz Isabel, Carlos Piñeiro and Antonio Gonzalez-Bulnes

Agriculture 2025, 15(8), 887; https://doi.org/10.3390/agriculture15080887 - 18 Apr 2025

Viewed by 277

Abstract

The use of electronic sow feeders (ESFs) during lactation has been associated with weaning of heavier piglets when compared to traditional feeders, with a lower amount of sow feed per kg of weaned piglet, improved welfare of the sow, and no negative effects [...] Read more.

The use of electronic sow feeders (ESFs) during lactation has been associated with weaning of heavier piglets when compared to traditional feeders, with a lower amount of sow feed per kg of weaned piglet, improved welfare of the sow, and no negative effects on body condition or metabolic traits at weaning or subsequent reproductive yields. However, there have been no studies assessing the possible effects of ESF use on the lifelong development of the progeny. This study reveals that piglets weaned from sows fed with ESFs were heavier than those from sows fed with traditional feeders (5.91 ± 1.45 vs. 5.58 ± 1.23 kg, p < 0.005), with a lower amount of feed per kg of weaned piglet (2.41 ± 0.42 vs. 1.88 ± 0.28 kg, p < 0.0005). Subsequent differences in body weight increased due to a higher average daily weight gain during both the periods of nursery (0.332 ± 0.92 vs. 0.312 ± 0.80 kg/day, p < 0.01) and growing–finishing (0.921 ± 0.11 vs. 0.871 ± 0.09 kg/day, p < 0.001). Finally, the weights of the carcasses and primal pork pieces (ham, shoulder, loin, and belly) were also higher in pigs from sows fed with ESFs (p < 0.001 for all). Full article

(This article belongs to the Special Issue Recent Progress in Swine Nutrition and Meat Quality)

18 pages, 9793 KiB

Open AccessArticle

Analytical Methods for Wind-Driven Dynamic Behavior of Pear Leaves (Pyrus pyrifolia)

by Yunfei Wang, Weidong Jia, Shiqun Dai, Mingxiong Ou, Xiang Dong, Guanqun Wang, Bohao Gao and Dengjun Tu

Agriculture 2025, 15(8), 886; https://doi.org/10.3390/agriculture15080886 - 18 Apr 2025

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Abstract

The fluttering of leaves under wind fields significantly impacts the efficiency and precision of agricultural spraying. However, existing spraying technologies often overlook the complex mechanisms of wind–leaf interactions. This study integrates the fine-tuned Segment Anything Model 2 with multi-dimensional dynamic behavior analysis to [...] Read more.

The fluttering of leaves under wind fields significantly impacts the efficiency and precision of agricultural spraying. However, existing spraying technologies often overlook the complex mechanisms of wind–leaf interactions. This study integrates the fine-tuned Segment Anything Model 2 with multi-dimensional dynamic behavior analysis to provide a systematic approach for investigating leaf fluttering under wind fields. First, a segmentation algorithm based on Principal Component Analysis was employed to eliminate background interference in leaf fluttering data. The results showed that the segmentation algorithm achieved an Intersection over Union (IoU) ranging from 98.2% to 98.7%, with Precision reaching 99.0% to 99.5%, demonstrating high segmentation accuracy and reliability. Building on this, experiments on leaf segmentation and tracking in dynamic scenarios were conducted using the SAM2-FT model. The results indicated that SAM2-FT effectively captured the dynamic behavior of leaves by integrating spatiotemporal information, achieving Precision and AP50/% values exceeding 97%. Its overall performance significantly outperformed mainstream YOLO-series models. In the analysis of dynamic response patterns, the Hilbert transform and time-series quantification methods were introduced to reveal the amplitude, frequency, and trajectory characteristics of a leaf fluttering under wind fields across three dimensions: area, inclination angle, and centroid. This comprehensive analysis highlights the dynamic response characteristics of leaves to wind field perturbations. Full article

(This article belongs to the Section Agricultural Technology)

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27 pages, 1216 KiB

Open AccessArticle

Measurement of Production Efficiency and Analysis of Influencing Factors in Major Sugarcane-Producing Regions of China

by Chuanmin Yan, Xingqun Li, Lei Zhan, Zhizhuo Li and Jun Wen

Agriculture 2025, 15(8), 885; https://doi.org/10.3390/agriculture15080885 - 18 Apr 2025

Viewed by 149

Abstract

Enhancing production efficiency in major sugarcane-producing regions is of strategic significance for ensuring the security of China’s sugar industry and promoting its industrial upgrading. Using the DEA–Malmquist–Tobit modeling framework, this study dynamically evaluates production efficiency from 2011 to 2023, spanning China’s 12th to [...] Read more.

Enhancing production efficiency in major sugarcane-producing regions is of strategic significance for ensuring the security of China’s sugar industry and promoting its industrial upgrading. Using the DEA–Malmquist–Tobit modeling framework, this study dynamically evaluates production efficiency from 2011 to 2023, spanning China’s 12th to 14th Five-Year Plan periods, with a focus on the primary sugarcane-producing regions: Guangdong, Guangxi, Yunnan, and Hainan. Results indicate a U-shaped fluctuation in national comprehensive technical efficiency, with a historical low in 2022 due to a collapse in scale efficiency, pinpointing scale management as the central constraint. Regionally, Guangdong consistently maintained optimal dual efficiency. Yunnan stabilized its efficiency through rigid policy mechanisms. Guangxi experienced setbacks due to competition between eucalyptus and sugarcane cultivation, while Hainan faced a precipitous decline in scale efficiency following industry exits. Total factor productivity (TFP) analysis revealed that stagnation in technological advancement was the primary cause of productivity decline, leading to asynchronous regional technology diffusion and subsequent reliance on scale adjustments. During the 12th Five-Year Plan, Hainan led in TFP growth but experienced a sharp downturn in the 13th period due to policy tightening. In contrast, Guangdong achieved notable TFP growth in the 14th period through technological breakthroughs, whereas Yunnan lagged behind Guangxi due to technological inertia. Analysis of the driving mechanisms showed that urbanization rates significantly boosted efficiency through intensified land use. Full article

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

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14 pages, 8224 KiB

Open AccessArticle

Construction of an SNP Fingerprinting Database and Population Genetic Analysis of Auricularia heimuer

by Kaisheng Shao, Qiuyu Feng, Fangjie Yao, Lixin Lu, Ming Fang, Xiaoxu Ma and Xu Sun

Agriculture 2025, 15(8), 884; https://doi.org/10.3390/agriculture15080884 - 18 Apr 2025

Viewed by 176

Abstract

Auricularia heimuer is the second most widely cultivated edible fungus in China, with significant food and medicinal value, and is highly popular throughout Asia and globally. However, the differentiation of A. heimuer is simple, as its morphology is characterized by a small “black [...] Read more.

Auricularia heimuer is the second most widely cultivated edible fungus in China, with significant food and medicinal value, and is highly popular throughout Asia and globally. However, the differentiation of A. heimuer is simple, as its morphology is characterized by a small “black disc”, making it difficult to distinguish among germplasms with highly similar agronomic traits, thus posing challenges for germplasm identification. To address this issue, this study conducted whole-genome resequencing analysis on 150 A. heimuer germplasms. Through filtering 9,589,911 SNPs obtained from 280 G resequencing data, a total of 1,202,947 high-quality SNP sites were identified. Based on these high-quality SNPs, population structure analysis, principal component analysis (PCA), and phylogenetic tree analysis revealed that the 150 A. heimuer germplasms could be divided into five groups, with wild strains from the same geographical origin exhibiting significant geographical clustering patterns. This finding underscores the relationship between the genetic diversity of wild A. heimuer and its geographical distribution in China. A further selection of 71 SNP sites was made, and 61 KASP markers were successfully developed using kompetitive allele-specific PCR (KASP) technology, with 54 of them demonstrating good polymorphism. The average values for the polymorphism information content (PIC), minor allele frequency (MAF), gene diversity, and heterozygosity of these core KASP markers were 0.34, 0.35, 0.34, and 0.43, respectively. Based on the 54 core KASP markers, a DNA fingerprinting map of the 150 A. heimuer germplasms was constructed in this study. The findings provide important molecular marker resources and theoretical support for the identification of A. heimuer germplasm, molecular marker-assisted breeding, and the selection of superior varieties. Full article

(This article belongs to the Special Issue Genetics and Breeding of Edible Mushroom)

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17 pages, 416 KiB

Open AccessArticle

Reexamining the Determinants of Organic Food Purchases in Online Contexts: The Dual-Factor Model Perspective

by Ching-Hsuan Yeh and Min-Hsien Yang

Agriculture 2025, 15(8), 883; https://doi.org/10.3390/agriculture15080883 - 18 Apr 2025

Viewed by 208

Abstract

The ever-expanding market has made organic food a popular research topic, with the primary question being what factors facilitate or hinder consumers in making an organic purchase. The most relevant studies have been conducted in an offline context. As selling organic food online [...] Read more.

The ever-expanding market has made organic food a popular research topic, with the primary question being what factors facilitate or hinder consumers in making an organic purchase. The most relevant studies have been conducted in an offline context. As selling organic food online has become a common practice and is underresearched, this study aims to (1) explore the drivers and barriers of online organic food shopping and (2) investigate the shopping behavior of organic food from an omnichannel perspective. The results of partial least square structural equation modeling (PLS-SEM), with 278 valid samples, indicate that trust in organic labels and positive review sentiment significantly contribute to the intention to purchase organic food online, which in turn influences online purchase behaviors. For online shopping behavior, the investigation shows that Taiwanese consumers, on a monthly basis, make an average of 3.22 organic food purchases and spend US$156.44 through offline channels, whereas they make 2.34 purchases of organic food and spend US$114.71 via online channels. Organic vegetables and fruits are the most frequently purchased organic foods. Among online channels, consumers prefer visiting the websites of general grocery stores and specialty stores over social media platforms. Our findings suggest that the determinants of organic food shopping differ between offline and online contexts and reveal interesting behavioral patterns of online organic shopping. Full article

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

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14 pages, 5129 KiB

Open AccessArticle

Mapping for Autonomous Navigation of Agricultural Robots Through Crop Rows Using UAV

by Hasib Mansur, Manoj Gadhwal, John Eric Abon and Daniel Flippo

Agriculture 2025, 15(8), 882; https://doi.org/10.3390/agriculture15080882 - 18 Apr 2025

Viewed by 291

Abstract

Mapping is fundamental to the autonomous navigation of agricultural robots, as it provides a comprehensive spatial understanding of the farming environment. Accurate maps enable robots to plan efficient routes, avoid obstacles, and precisely execute tasks such as planting, spraying, and harvesting. Row crop [...] Read more.

Mapping is fundamental to the autonomous navigation of agricultural robots, as it provides a comprehensive spatial understanding of the farming environment. Accurate maps enable robots to plan efficient routes, avoid obstacles, and precisely execute tasks such as planting, spraying, and harvesting. Row crop navigation presents unique challenges, and mapping plays a crucial role in optimizing routes and avoiding obstacles in coverage path planning (CPP), which is essential for efficient agricultural operations. This study proposes a simple method for using Unmanned Aerial Vehicles (UAVs) to create maps and its application to row crop navigation. A case study is presented to demonstrate the method’s viability and illustrate how the resulting map can be applied in agricultural scenarios. This study focused on two major row crops, namely corn and soybean, but the results indicate that map creation is feasible when the inter-row spaces are not obscured by canopy cover from the adjacent rows. Although the study did not apply the map in a real-world scenario, it offers valuable insights for guiding future research. Full article

(This article belongs to the Special Issue Intelligent Robots for Agriculture: Design, Development and Applications)

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24 pages, 12828 KiB

Open AccessArticle

Red Raspberry Maturity Detection Based on Multi-Module Optimized YOLOv11n and Its Application in Field and Greenhouse Environments

by Rongxiang Luo, Xue Ding and Jinliang Wang

Agriculture 2025, 15(8), 881; https://doi.org/10.3390/agriculture15080881 - 18 Apr 2025

Viewed by 260

Abstract

In order to achieve accurate and rapid identification of red raspberry fruits in the complex environments of fields and greenhouses, this study proposes a new red raspberry maturity detection model based on YOLOv11n. First, the proposed hybrid attention mechanism HCSA (halo attention with [...] Read more.

In order to achieve accurate and rapid identification of red raspberry fruits in the complex environments of fields and greenhouses, this study proposes a new red raspberry maturity detection model based on YOLOv11n. First, the proposed hybrid attention mechanism HCSA (halo attention with channel and spatial attention modules) is embedded in the neck of the YOLOv11n network. This mechanism integrates halo, channel, and spatial attention to enhance feature extraction and representation in fruit detection and improve attention to spatial and channel information. Secondly, dilation-wise residual (DWR) is fused with the C3k2 module of the network and applied to the entire network structure to enhance feature extraction, multi-scale perception, and computational efficiency in red raspberry detection. Concurrently, the DWR module optimizes the learning process through residual connections, thereby enhancing the accuracy and real-time performance of the model. Finally, a lightweight and efficient dynamic upsampling module (DySample) is introduced between the backbone and neck of the network. This module enhances the network’s multi-scale feature extraction capabilities, reduces the interference of background noise, improves the recognition of structural details, and optimizes the spatial resolution of the image through the dynamic sampling mechanism. Reducing network parameters helps the model better capture the maturity characteristics of red raspberry fruits. Experiments were conducted on a custom-built 3167-image dataset of red raspberries, and the results demonstrated that the enhanced YOLOv11n model attained a precision of 0.922, mAP@0.5 of 0.925, and mAP@0.5 of 0.943, respectively, representing improvements of 0.7%, 4.4%, and 4.4%, respectively. At 3.4%, mAP@0.5-0.95 was 0.798, which was 2.0%, 9.8% and 3.7% higher than the original YOLOv11n model, respectively. The mAP@0.5 of unripe and ripe berries was 0.925 and 0.943, which was improved by 0.7% and 4.4%, respectively. The F1-score was enhanced to 0.89, while the computational complexity of the model was only 8.2 GFLOPs, thereby achieving a favorable balance between accuracy and efficiency. This research provides new technical support for precision agriculture and intelligent robotic harvesting. Full article

(This article belongs to the Section Digital Agriculture)

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16 pages, 265 KiB

Open AccessArticle

Evaluation of Scrapie Test Results of Native and Endangered Hungarian Sheep Breeds for Further Breeding

by Eszter Ilona Bácsi, Renáta Klein, András Lévai, Fiona Kenyon and János Oláh

Agriculture 2025, 15(8), 880; https://doi.org/10.3390/agriculture15080880 - 18 Apr 2025

Viewed by 233

Abstract

In this study, we analysed scrapie test results of Hungarian indigenous sheep breeds (Cikta, Tsigai, Dairy Tsigai, Transylvanian Racka, and Hungarian Racka in white and black colour variants) and the endangered Hungarian Merino rams during the period from 2019 to 2023. In Hungary, [...] Read more.

In this study, we analysed scrapie test results of Hungarian indigenous sheep breeds (Cikta, Tsigai, Dairy Tsigai, Transylvanian Racka, and Hungarian Racka in white and black colour variants) and the endangered Hungarian Merino rams during the period from 2019 to 2023. In Hungary, it is mandatory to perform scrapie testing for every ram intended for breeding. These results were subsequently compared with data from analyses conducted in 2004 and between 2013 and 2015, which served as control samples. The test results were given by the Hungarian Sheep and Goat Breeders’ Association. The employees collected ear cartilage tissue samples during the identification of the lambs using TypiFixTM by Agrobiogen GmBH. We determined the frequencies of alleles, genotypes, and risk groups, and calculated the proportion of each within the studied population. The scrapie test results were evaluated using the SPSS 23 software package and a Chi²-test. Samples were categorised into one of five risk groups (R1 (lowest)–R5 (highest)) based on the degree of resistance observed. In conclusion, we found that there was a significant improvement in scrapie susceptibility for all breeds except the Cikta. However, the potential impact of this improvement on other important traits remains undetermined. Regarding susceptibility to scrapie, the Hungarian Merino is the most resistant group, as 68.8% of the rams in this breed belonged to the R1 risk group, while the Cikta sheep is in the least favourable position, as only 3.3% of the examined individuals belonged to this category. Full article

(This article belongs to the Special Issue Role of Local Breeds in Global Agriculture—Local Food, Regional Identity and Ecosystem Services)

30 pages, 4548 KiB

Open AccessArticle

Effects of Auricularia heimuer Residue Amendment on Soil Quality, Microbial Communities, and Maize Growth in the Black Soil Region of Northeast China

by Ying Wang, Jionghua Wang, Keqing Qian, Yuting Feng, Jiangyan Ao, Yinzhen Zhai, Yu Li, Xiao Li, Bo Zhang and Han Yu

Agriculture 2025, 15(8), 879; https://doi.org/10.3390/agriculture15080879 - 17 Apr 2025

Viewed by 261

Abstract

This study reveals how microbial diversity relates to soil properties in Auricularia heimuer residue–chicken manure composting, presenting sustainable waste recycling solutions. These microbial-straw strategies are adaptable to various agroecological regions, offering flexible residue valorization approaches for local conditions, crops, and resources. This study [...] Read more.

This study reveals how microbial diversity relates to soil properties in Auricularia heimuer residue–chicken manure composting, presenting sustainable waste recycling solutions. These microbial-straw strategies are adaptable to various agroecological regions, offering flexible residue valorization approaches for local conditions, crops, and resources. This study examined the effects of composting Auricularia heimuer residue and chicken manure at three ratios (6:4, 7:3, 8:2) on soil properties, lignocellulose content, enzyme activity, microbial diversity, and maize growth. The compost was mixed into potting soil at different proportions (0:10 to 10:0). During composting, the temperature remained above 50 °C for more than 14 days, meeting safety and sanitation requirements. The composting process resulted in a pH range of 7–8, a stable moisture content of 60%, a color change from brown to gray-brown, the elimination of unpleasant odors, and the formation of loose aggregates. Lignocellulose content steadily decreased, while lignocellulosic enzyme activity and actinomycete abundance increased, indicating suitability for field application. Compared with the control (CK), total nitrogen, total phosphorus, and total potassium in the soil increased by 57.81–77.91%, 4.5–19.28%, and 301.09–577.2%, respectively. Lignin, cellulose, and hemicellulose increased 50.6–83.49%, 59.6–340.33%, and 150.86–310.5%, respectively. The activities of lignin peroxidase, cellulase, and hemicellulase increased by 9.05–36.31%, 6.7–36.66%, and 37.39–52.16%, respectively. Maize root weight, plant biomass, and root number increased by 120.87–138.59%, 117.83–152.86%, and 29.03–75.81%, respectively. In addition, composting increased the relative abundance of actinomycetes while decreasing the abundance of ascomycetes and ascomycetes. The relative abundance of Sphingomonas and Gemmatimonas increased, whereas pathogenic fungi such as Cladosporium and Fusarium decreased. Compost application also enhanced bacterial and fungal diversity, with bacterial diversity indices ranging from 6.744 to 9.491 (B1), 5.122 to 9.420 (B2), 8.221 to 9.552 (B3), and 6.970 to 9.273 (CK). Fungal diversity indices ranged from 4.811 to 8.583 (B1), 1.964 to 9.160 (B2), 5.170 to 9.022 (B3), and 5.893 to 7.583 (CK). Correlation analysis of soil physicochemical properties, lignocellulose content, enzymes, microbial community composition, and diversity revealed that total nitrogen, total phosphorus, total potassium, and lignocellulose content were the primary drivers of rhizosphere microbial community dynamics. These factors exhibited significant correlations with the dominant bacterial and fungal taxa. Additionally, bacterial and fungal diversity increased with the incorporation of Auricularia heimuer residue. In conclusion, this study elucidates the relationships between microbial diversity and soil properties across different proportions of Auricularia heimuer residue and chicken manure composting, offering alternative strategies for waste recycling and sustainable agricultural development. At present, the production of biobiotics using waste culture microorganisms is still in the laboratory research stage, and no expanded experiments have been carried out. Therefore, how to apply waste bacterial bran to the production of biocontrol biotics on a large scale needs further research. Full article

(This article belongs to the Section Agricultural Soils)

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Open AccessArticle

The Simulation of Stomatal Aperture Size on the Upper and Lower Epidermis of Gynura formosana Kitam Leaves Based on Cellular Automata

by Xinlong Shi, Yanbo Song, Xiaojing Shi, Penghui Li, Yun Wang, Liyan Jia and Zhenyu Liu

Agriculture 2025, 15(8), 878; https://doi.org/10.3390/agriculture15080878 - 17 Apr 2025

Viewed by 188

Abstract

Stomata are essential structures in plants for gas exchange, and their opening and closing are influenced by complex external environmental factors. Using Gynura formosana Kitam as the research object, the regulation of stomatal aperture is crucial for ensuring healthy growth. By simulating and [...] Read more.

Stomata are essential structures in plants for gas exchange, and their opening and closing are influenced by complex external environmental factors. Using Gynura formosana Kitam as the research object, the regulation of stomatal aperture is crucial for ensuring healthy growth. By simulating and predicting the variation in stomatal aperture, it is possible to determine whether the stomatal response is adapted to environmental conditions. Furthermore, predicting environmental factors such as light intensity and electric fields can help adjust stomatal apertures to enhance Gynura formosana Kitam’s adaptability to different conditions. To explore the impact of external factors like light and electric fields on stomatal aperture, this study employs a cellular automaton model, selecting a 24 h period to observe the stomatal variation law. By incorporating the multi-faceted influences of the external environment on the stomatal apertures of both the upper and lower epidermis of Gynura formosana Kitam leaves, a simulation model of stomatal opening and closing based on metacellular automata is proposed. Based on the physiological characteristics and opening and closing laws of stomata, the rule changes of stomatal opening and closing under different environmental conditions were defined, and the stomatal development area was divided into several two-dimensional and three-dimensional cellular spatial structures. The grid of cells in the structure with stomatal “open” and “closed” states was regarded as an intelligent agent. For different environments under the law of change and simulation of the law of change for simulation research, the simulation results and the actual results match, and the law is consistent. In order to ensure the accuracy of the simulation model, 100 training fits were carried out and the results were statistically analyzed, and the average error was kept within 0.05. This model effectively predicts the variations in stomatal apertures on the upper and lower epidermis of Gynura formosana Kitam leaves, providing a theoretical basis for implementing precise control and improving the economic benefits of Gynura formosana Kitam cultivation. Full article

(This article belongs to the Section Digital Agriculture)

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Agriculture, Volume 15, Issue 8 (April-2 2025) – 111 articles

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