Agriculture

19 pages, 4867 KiB

Open AccessArticle

Transcriptomic and Metabolomic Analyses Reveal Differences in Flavonoid Synthesis During Fruit Development of Capsicum frutescens pericarp

by Yinxin Yang, Qihang Cai, Xuan Wang, Yanbo Yang, Liping Li, Zhenghai Sun and Weiwei Li

Agriculture 2025, 15(2), 222; https://doi.org/10.3390/agriculture15020222 - 20 Jan 2025

Viewed by 459

Abstract

Capsicum frutescens is a valuable economic crop that is widely cultivated for its unique flavor and rich nutritional content. While some studies have shown differences in flavonoid content among different chili species, the mechanism by which changes in flavonoid composition lead to fruit [...] Read more.

Capsicum frutescens is a valuable economic crop that is widely cultivated for its unique flavor and rich nutritional content. While some studies have shown differences in flavonoid content among different chili species, the mechanism by which changes in flavonoid composition lead to fruit color variations in C. frutescens remains underreported. We performed transcriptomics and widely targeted metabolome sequencing on three different growth stages of the C. frutescens fruit and analyzed the data to better understand the mechanism of color change. Based on previous research on the genes that regulate flavonoid compounds and the MBW complex, we have identified a total of 28 core genes related to flavonoid biosynthesis and 8 genes that may be related to flavonoid synthesis. Through extensive targeted metabolomic analysis, 581 differential metabolites were identified, including 43 flavonoids. Most anthocyanins, flavonols, and flavonoids were found to be more abundant during the immature fruit stage, which we presume is associated with the differential expression of genes involved in flavonoid biosynthesis and regulation. These findings provide a useful reference for understanding flavonoid synthesis and the accumulation of fruits in C. frutescens. Full article

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

► Show Figures

Figure 1

36 pages, 25401 KiB

Open AccessArticle

Analysis of Spatiotemporal Dynamics and Driving Factors of China’s Nationally Important Agricultural Heritage Systems

by Fei Ju, Rui Yang and Chun Yang

Agriculture 2025, 15(2), 221; https://doi.org/10.3390/agriculture15020221 - 20 Jan 2025

Viewed by 527

Abstract

China’s Nationally Important Agricultural Heritage Systems (China-NIAHS) are agricultural systems with deep historical and cultural roots that exhibit temporal continuity and spatial heterogeneity in their formation and distribution. As modern and industrialized agriculture have developed, traditional agricultural systems are facing unprecedented challenges and [...] Read more.

China’s Nationally Important Agricultural Heritage Systems (China-NIAHS) are agricultural systems with deep historical and cultural roots that exhibit temporal continuity and spatial heterogeneity in their formation and distribution. As modern and industrialized agriculture have developed, traditional agricultural systems are facing unprecedented challenges and pressures. This study investigates the spatiotemporal distribution and influencing factors of 196 China-NIAHS sites, categorized into five categories. Using spatial analysis techniques and Geographical Detectors, this study identifies key natural, socioeconomic, and cultural drivers shaping their distribution. The results reveal a predominantly clustered spatial distribution of China-NIAHS, centered around the Yangtze River Basin, with significant influences from population density, tourism development, and industrialization. Historical analysis highlights a west-to-east and northward migration of agricultural activity, driven by political stability and technological advancements. Further findings indicate that the spatial distribution of China-NIAHS is primarily determined by population density, tourism development, and river network density. Population density plays a pivotal role in heritage preservation, tourism development generates economic benefits and facilitates cultural dissemination, and river network density supports the formation and sustainability of heritage sites. Conversely, urbanization and economic development have limited influence, emphasizing the need to prioritize socioeconomic and natural factors in conservation strategies. This study provides a comprehensive understanding of the spatial and temporal dynamics of China-NIAHS, offering valuable insights for sustainable heritage conservation and the strategic integration of natural and socioeconomic factors into modern agricultural policies. These findings deepen the understanding of China-NIAHS, highlighting their role in ecological and cultural sustainability while supporting value assessment, region-specific protection, and sustainable utilization strategies. Full article

(This article belongs to the Special Issue Exploring, Assessing and Utilizing the Multifunctional Value of Agricultural Heritage Systems)

► Show Figures

Figure 1

18 pages, 4423 KiB

Open AccessArticle

A Compliant Active Roller Gripper with High Positional Offset Tolerance for Delicate Spherical Fruit Handling

by Haoran Zhu, Huanhuan Qin, Zicheng Qiu, Xinwen Chen, Jinlin Xue, Xingjian Gu and Mingzhou Lu

Agriculture 2025, 15(2), 220; https://doi.org/10.3390/agriculture15020220 - 20 Jan 2025

Viewed by 487

Abstract

In the field of agricultural robotics, robotic grippers play an indispensable role, directly influencing the rate of fruit damage and handling efficiency. Currently, traditional agricultural robotic grippers face challenges such as high damage rates and high requirements for position control. A robotic gripper [...] Read more.

In the field of agricultural robotics, robotic grippers play an indispensable role, directly influencing the rate of fruit damage and handling efficiency. Currently, traditional agricultural robotic grippers face challenges such as high damage rates and high requirements for position control. A robotic gripper for stable spherical fruit handling with high positional offset tolerance and a low fruit damage rate is proposed in this paper. It adopts a three-finger structure. A flexible active roller is configured at the end of each finger, allowing fruit translation with just a gentle touch. An integrated pressure sensor within the active roller further enhances the gripper’s compliance. To describe the effect of the gripper on the fruit, the interaction model was derived. Taking the tomato as a typical soft and fragile spherical fruit, three experiments were conducted to evaluate the performance of the proposed gripper. The experimental results demonstrated the handling capability of the gripper and the maximum graspable weight reached 2077 g. The average failure rate for the unilateral offset of 9 mm was only 1.33%, and for the bilateral offset of 6-6 mm was 4%, indicating the high positional offset tolerance performance and a low fruit damage rate of the gripper. The preliminary tomato-picking capability of the proposed gripper was also validated in a simplified laboratory scenario. Full article

(This article belongs to the Section Agricultural Technology)

► Show Figures

Figure 1

22 pages, 8463 KiB

Open AccessArticle

Pre-Season Precipitation and Temperature Have a Larger Influence on Vegetation Productivity than That of the Growing Season in the Agro-Pastoral Ecotone in Northern China

by Yuanyuan Zhang, Qingtao Wang, Xueyuan Zhang, Zecheng Guo, Xiaonan Guo, Changhui Ma, Baocheng Wei and Lei He

Agriculture 2025, 15(2), 219; https://doi.org/10.3390/agriculture15020219 - 20 Jan 2025

Viewed by 495

Abstract

Climate change and human activities are reshaping the structure and function of terrestrial ecosystems, particularly in vulnerable regions such as agro-pastoral ecotones. However, the extent to which climate change impacts vegetation growth in these areas remains poorly understood, largely due to the modifying [...] Read more.

Climate change and human activities are reshaping the structure and function of terrestrial ecosystems, particularly in vulnerable regions such as agro-pastoral ecotones. However, the extent to which climate change impacts vegetation growth in these areas remains poorly understood, largely due to the modifying effects of human-induced land cover changes on vegetation sensitivity to climatic variations. This study utilizes satellite-derived vegetation indices, land cover datasets, and climate data to investigate the influence of both land cover and climate changes on vegetation growth in the agro-pastoral ecotone of northern China (APENC) from 2001 to 2022. The results reveal that the sensitivity of vegetation productivity, as indicated by the kernel Normalized Difference Vegetation Index (kNDVI), varies depending on the land cover type to climate change in the APENC. Moreover, ridge regression modeling shows that pre-season climate conditions (i.e., pre-season precipitation and temperature) have a stronger positive impact on growing-season vegetation productivity than growing season precipitation and temperature, while the effect of vapor pressure deficit (VPD) is negative. Notably, the kNDVI exhibits significant positive sensitivity (p < 0.05) to precipitation in 34.12% of the region and significant negative sensitivity (p < 0.05) to VPD in 38.80%. The ridge regression model explained 89.10% of the total variation (R² = 0.891). These findings not only emphasize the critical role of both historical and contemporary climate conditions in shaping vegetation growth but also provide valuable insights into how to adjust agricultural and animal husbandry management strategies to improve regional climate adaptation based on climate information from previous seasons in fragile regions. Full article

(This article belongs to the Section Digital Agriculture)

► Show Figures

Figure 1

14 pages, 9150 KiB

Open AccessArticle

Plant Adaptability to Improved Dredged Sediment

by Shoulong Zhang, Rixiong Mo, Haorong Shi, Yuanzhen Li, Yaoyao Zhou, Chenhao Wang and Guanlong Yu

Agriculture 2025, 15(2), 218; https://doi.org/10.3390/agriculture15020218 - 20 Jan 2025

Viewed by 365

Abstract

Traditional dredged sludge disposal methods are characterized by low resource utilization and high carbon emissions, leading to serious environmental pollution. This study used dredged sludge, composted pig manure, and sawdust as raw materials, and supplemented them with composite biological agents to prepare improved [...] Read more.

Traditional dredged sludge disposal methods are characterized by low resource utilization and high carbon emissions, leading to serious environmental pollution. This study used dredged sludge, composted pig manure, and sawdust as raw materials, and supplemented them with composite biological agents to prepare improved soil. Plant adaptability to the improved soil was comprehensively evaluated using factors such as seed germination index (GI). The alkaline nitrogen content in the improved soil increased by 78.61% compared to the dredged sludge, and the content of other nutrients such as available potassium also increased to varying degrees. Ryegrass seed GI increased by 51.06% in improved soil (IS1) compared to dredged sludge. The main dominant fungi in the improved soil (IS1) were Tausonia, Trichoderma, and Cystoflobasidium, which promote soil nutrient activation and antagonize pathogenic bacteria, making the environment more conducive to plant growth. Dredged sludge was successfully converted into planting soil. Fully utilizing the nitrogen, phosphorus, and other substances enriched in dredged sludge to provide nutrients for plant growth is an efficient method to achieve dredged sludge resource utilization. Full article

(This article belongs to the Section Agricultural Soils)

► Show Figures

Figure 1

17 pages, 1506 KiB

Open AccessArticle

Arsenic Uptake in Durum Wheat (Triticum durum Desf.) as Influenced by Soil Tillage Practices and Fertilization Sources in Mediterranean Environment

by Ilenia Bravo, Mariam Atait, Ilenia Colamatteo, Roberto Mancinelli, Mohamed Allam, Patrizia Papetti and Emanuele Radicetti

Agriculture 2025, 15(2), 217; https://doi.org/10.3390/agriculture15020217 - 20 Jan 2025

Viewed by 489

Abstract

Nowadays, arsenic (As) accumulation in agricultural soils and its transfer in crop yields is representing a growing concern that threatens food safety and security in the Mediterranean environment. Soil tillage and fertilization may increase the accumulation of As in plant tissues; therefore, there [...] Read more.

Nowadays, arsenic (As) accumulation in agricultural soils and its transfer in crop yields is representing a growing concern that threatens food safety and security in the Mediterranean environment. Soil tillage and fertilization may increase the accumulation of As in plant tissues; therefore, there is a need to develop sustainable agronomical practices capable of supporting crop yield while mitigating As accumulation. The current study was carried out through a 7-year experiment with the aim of evaluating the As uptake by different parts of the durum wheat plant. The experimental treatments include the following: (i) three soil tillage practices (plowing, subsoiling, and spading) and (ii) two fertilization methods (mineral and organic). A factorial randomized complete block design with three replications was adopted. The experimental period refers to the 2018/2019, 2019/2020, and 2020/2021 growing seasons. The results suggest that the maximum level of As was found in plant roots and the minimum in wheat kernels. The chemical fertilization as 2020 × Mineral (1.522 mg As kg⁻¹ d.m.) and 2020 × Plowing (1.855 mg As kg⁻¹ d.m.) had the maximum As content in the roots. Conversely, the content of As was at a minimum in the wheat kernels for organic fertilization as 2021 × Organic (0.012 mg As kg⁻¹ d.m.) and subsoiling tillage as 2021 × Subsoiling (0.008 mg As kg⁻¹ d.m.). Moreover, the application of an organic fertilization source as a tool for enhancing the soil organic matter content also significantly decreased the As content. The results suggest that reduced tillage practices and the adoption of organic amendment could be classified as sustainable agronomic practices in agri-food systems, which are able to improve plant quality and assure a safe consumption of wheat kernels. Full article

(This article belongs to the Section Agricultural Soils)

► Show Figures

Figure 1

21 pages, 719 KiB

Open AccessSystematic Review

Extinction Status, Challenges, and Conservation Approaches of South African Indigenous and Village Chickens: A Systematic Review

by Sindisiwe Mbali Sithole, Khathutshelo Agree Nephawe, Takalani Judas Mpofu, Bohani Mtileni, Masindi Lottus Mphaphathi and Jabulani Nkululeko Ngcobo

Agriculture 2025, 15(2), 216; https://doi.org/10.3390/agriculture15020216 - 20 Jan 2025

Viewed by 562

Abstract

South Africa recognizes the value of indigenous breeds such as Potchefstroom Koekoek, Boschveld, Ovambo, Venda, Naked Neck, and nondescript village chickens. Indigenous chickens support sustainable food systems, improve nutrition, and enhance livelihoods in rural communities, thereby contributing to the United Nations’ Sustainable Development [...] Read more.

South Africa recognizes the value of indigenous breeds such as Potchefstroom Koekoek, Boschveld, Ovambo, Venda, Naked Neck, and nondescript village chickens. Indigenous chickens support sustainable food systems, improve nutrition, and enhance livelihoods in rural communities, thereby contributing to the United Nations’ Sustainable Development Goal (SDG) 2 on Zero Hunger. These breeds are not only vital to rural farmers for food production, income generation, and subsistence but also provide rural farmers with cheap nutritious protein such as eggs and meat for household consumption. Moreover, they are preferred by rural farmers because they are relatively affordable to produce, can withstand harsh environmental conditions amid accelerated climate change compared to exotic breeds, and require less/no feed supplementation. However, despite the numerous advantages of keeping these chickens, it has been found that they are mostly in danger of extinction due to evolving production methods that favor exotic breeds. Therefore, understanding their extinction status, different implications for conserving their genetic material, challenges encountered, and future approaches to rescue these breeds remain vital. Hence, the aim of this systematic review was to assess the extinction status, challenges, and conservation approaches for these breeds. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines were utilized to search for suitable articles addressing the objective of the current review. Research articles were grouped and evaluated for eligibility, and the data from the Domestic Animal Diversity Information System database were used. Records such as duplicates of studies addressing origins, phenotypic and genetic diversity, the conservation of indigenous chickens, semen cryopreservation of indigenous chickens, climate change effects on indigenous chickens, and the use of extenders with exotic chickens and other chicken types, reports in other languages, and reports that were inaccessible were excluded. Articles addressing origins, phenotypic and genetic diversity, the conservation of indigenous chickens, semen cryopreservation of indigenous chickens, climate change effects on indigenous chickens, and the use of extenders with indigenous chickens were included in this review. The keywords used to search articles online were as follows: South African indigenous chicken; extension status; conservation; genetic resources; genetic markers; effective population size; inbreeding; and characterization. This systematic review found that there is less information in the Domestic Animal Diversity Information System regarding South African indigenous and village chickens, suggesting a lack of reporting in this system. Moreover, our review confirmed that most South African indigenous chickens are threatened and, hence, require interventions such as assisted reproductive technologies and other strategies in order to improve efficiency. Full article

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

► Show Figures

Figure 1

20 pages, 1243 KiB

Open AccessArticle

Impact of On-Farm Demonstrations on Technology Adoption, Yield, and Profitability Among Small Farmers of Wheat in Pakistan—An Experimental Study

by Nadia Hussain and Keshav Lall Maharjan

Agriculture 2025, 15(2), 214; https://doi.org/10.3390/agriculture15020214 - 20 Jan 2025

Viewed by 603

Abstract

Do the intensive demonstrations result in consistent technology adoption and yield enhancement? While extension methods show significant immediate effects of an intervention, their impact may fade over time. In a government-led natural experiment in Pakistan, a long-lasting adoption of certified seeds, fertilizers, and [...] Read more.

Do the intensive demonstrations result in consistent technology adoption and yield enhancement? While extension methods show significant immediate effects of an intervention, their impact may fade over time. In a government-led natural experiment in Pakistan, a long-lasting adoption of certified seeds, fertilizers, and pesticides/herbicides in post-treatment years were observed by employing difference–indifferences with a fixed effect method on panel data. The intervention increased the technology adoption in terms of certified seeds by 34%, fertilizers by 15 kg/ha, and pesticides/herbicides by 0.22 L/ha among adopters for four years. Similarly, the wheat yield increased by 0.41 tons per hectare, and profit increased by 12% among the treatment group compared to the control group. In view of these findings, this study suggests continuing this supervised method of extension to other crops in Pakistan. Full article

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

► Show Figures

Figure 1

18 pages, 3369 KiB

Open AccessArticle

Exploring the Impact of Citric Acid on Mitigating Sweet Potato Soft Rot and Enhancing Postharvest Quality

by Yixi Chen, Linjiang Pang, Jiacheng Bai, Wenbao Yu, Yueming Zhu, Melvin Sidikie George, Zunfu Lv and Guoquan Lu

Agriculture 2025, 15(2), 215; https://doi.org/10.3390/agriculture15020215 - 19 Jan 2025

Viewed by 700

Abstract

Citric acid (CAC) is a ubiquitous, odorless, and non-toxic food additive. Soft rot, caused by the pathogen Rhizopus stolonifer, is a major postharvest disease affecting sweet potato (Ipomoea batatas (L.) Lam). The main theme of this study is to determine the [...] Read more.

Citric acid (CAC) is a ubiquitous, odorless, and non-toxic food additive. Soft rot, caused by the pathogen Rhizopus stolonifer, is a major postharvest disease affecting sweet potato (Ipomoea batatas (L.) Lam). The main theme of this study is to determine the CAC inhibitory mechanism against Rhizopus stolonifer, the causative agent of sweet potato soft rot. To ascertain the practical applicability of CAC, both in vitro and in vivo methodologies were employed. The aim of the in vitro experiments in this study was to delineate the effects of a 0.5% (w/v) CAC solution on the growth inhibition of Rhizopus stolonifer, encompassing mycelial morphology and colony expansion. In vivo experiments were carried out using “Xinxiang” sweet potato varieties and the application of a 0.5% (w/v) CAC solution as a pretreatment. Specifically, the tissue treated with 0.5% CAC maintained better appearance quality and texture characteristics; peroxidase, β-1,3-glucanase, chitinase, and phenylalanine ammonia-lyase activities were enhanced. Conversely, the same treatment resulted in a downregulation of polyphenol oxidase, catalase, ascorbate peroxidase, cellulase, and polygalactosidase activities. Moreover, CAC treatment was found to maintain elevated levels of total phenolics and flavonoids within the sweet potato tissues. In summary, the study demonstrates that 0.5% CAC fortifies the resistance of sweet potato to soft rot by activating defense-related enzymes, suppressing the activity of cell wall-degrading enzymes, and promoting the accumulation of antimicrobial compounds. These results advocate for the utilization of CAC as a postharvest treatment to mitigate the incidence of sweet potato soft rot. Full article

(This article belongs to the Special Issue Application of Antioxidants and Bioactive Compounds in Agricultural Products)

► Show Figures

Figure 1

20 pages, 5288 KiB

Open AccessArticle

A Study on Multi-Scale Behavior Recognition of Dairy Cows in Complex Background Based on Improved YOLOv5

by Zheying Zong, Zeyu Ban, Chunguang Wang, Shuai Wang, Wenbo Yuan, Chunhui Zhang, Lide Su and Ze Yuan

Agriculture 2025, 15(2), 213; https://doi.org/10.3390/agriculture15020213 - 19 Jan 2025

Viewed by 486

Abstract

The daily behaviors of dairy cows, including standing, drinking, eating, and lying down, are closely associated with their physical health. Efficient and accurate recognition of dairy cow behaviors is crucial for timely monitoring of their health status and enhancing the economic efficiency of [...] Read more.

The daily behaviors of dairy cows, including standing, drinking, eating, and lying down, are closely associated with their physical health. Efficient and accurate recognition of dairy cow behaviors is crucial for timely monitoring of their health status and enhancing the economic efficiency of farms. To address the challenges posed by complex scenarios and significant variations in target scales in dairy cow behavior recognition within group farming environments, this study proposes an enhanced recognition method based on YOLOv5. Four Shuffle Attention (SA) modules are integrated into the upsampling and downsampling processes of the YOLOv5 model’s neck network to enhance deep feature extraction of small-scale cow targets and focus on feature information, while maintaining network complexity and real-time performance. The C3 module of the model was enhanced by incorporating Deformable convolution (DCNv3), which improves the accuracy of cow behavior characteristic identification. Finally, the original detection head was replaced with a Dynamic Detection Head (DyHead) to improve the efficiency and accuracy of cow behavior detection across different scales in complex environments. An experimental dataset comprising complex backgrounds, multiple behavior categories, and multi-scale targets was constructed for comprehensive validation. The experimental results demonstrate that the improved YOLOv5 model achieved a mean Average Precision (mAP) of 97.7%, representing a 3.7% improvement over the original YOLOv5 model. Moreover, it outperformed comparison models, including YOLOv4, YOLOv3, and Faster R-CNN, in complex background scenarios, multi-scale behavior detection, and behavior type discrimination. Ablation experiments further validate the effectiveness of the SA, DCNv3, and DyHead modules. The research findings offer a valuable reference for real-time monitoring of cow behavior in complex environments throughout the day. Full article

(This article belongs to the Section Digital Agriculture)

► Show Figures

Figure 1

18 pages, 1919 KiB

Open AccessArticle

Effect of Biodegradable Mulch and Different Synthetic Mulches on Growth and Yield of Field-Grown Small-Fruited Tomato (Lycopersicon esculentum Mill.)

by Katarzyna Adamczewska-Sowińska, Joanna Bykowy and Janina Jaworska

Agriculture 2025, 15(2), 212; https://doi.org/10.3390/agriculture15020212 - 19 Jan 2025

Viewed by 438

Abstract

Mulching is a widely adopted practice in vegetable cultivation globally. This technique employs various plastic materials, such as polyethylene (PE) film or polypropylene (PP) nonwoven fabric, with an increasing trend toward the use of biodegradable materials. Between 2014 and 2016, field experiments were [...] Read more.

Mulching is a widely adopted practice in vegetable cultivation globally. This technique employs various plastic materials, such as polyethylene (PE) film or polypropylene (PP) nonwoven fabric, with an increasing trend toward the use of biodegradable materials. Between 2014 and 2016, field experiments were conducted to evaluate the performance of the small-fruited tomato Intrigo F1 cultivated using synthetic mulches. The trials, designed as single-factor experiments employing a randomized block layout with three replicates, assessed plant morphological traits, yield, and the biological value of the tomato fruits. Weather conditions and the type of mulch applied had a pronounced influence on the quality of tomato plants and yield. Compared to the control, the use of black, red, and aluminum PE films and brown PP resulted in a 7.2% increase in plant height. All mulching treatments, except white film, increased the lateral spread of the plants by an average of 24.2%. Plants cultivated on red PE film exhibited a 26.4% increase in leaf count with respect to the control. Mulched treatments achieved an average increase of 19.6% in marketable yield. The highest marketable fruit yield was recorded with black nonwoven fabric mulch. Mulching had a significant effect on the chemical composition of tomato fruits. Fruits on biodegradable foil had the most potassium, lycopene, and polyphenols. Full article

(This article belongs to the Special Issue The Impact of Environmental Factors on the Quality of Horticultural Commodities)

► Show Figures

Figure 1

20 pages, 998 KiB

Open AccessArticle

Effects of Dietary Starch Concentration on Milk Production, Nutrient Digestibility, and Methane Emissions in Mid-Lactation Dairy Cows

by Rebecca L. Culbertson, Fabian A. Gutiérrez-Oviedo, Pinar Uzun, Nirosh Seneviratne, Ananda B. P. Fontoura, Brianna K. Yau, Josie L. Judge, Amanda N. Davis, Diana C. Reyes and Joseph W. McFadden

Agriculture 2025, 15(2), 211; https://doi.org/10.3390/agriculture15020211 - 19 Jan 2025

Viewed by 620

Abstract

Our objective was to evaluate the effects of dietary starch concentration on milk production, nutrient digestibility, and methane emissions in lactating dairy cows. Thirty mid-lactation cows were randomly assigned to either a high-neutral-detergent-fiber, low-starch diet (LS; 20.2% starch) or a low-neutral-detergent-fiber, high-starch diet [...] Read more.

Our objective was to evaluate the effects of dietary starch concentration on milk production, nutrient digestibility, and methane emissions in lactating dairy cows. Thirty mid-lactation cows were randomly assigned to either a high-neutral-detergent-fiber, low-starch diet (LS; 20.2% starch) or a low-neutral-detergent-fiber, high-starch diet (HS; 25.2% starch) following a 3-week acclimation. The study lasted 8 weeks, with milk sampling and gas measurements conducted weekly during acclimation and at weeks 2, 4, 6, and 8. Blood and fecal samples were collected during acclimation and week 8. Compared with LS cows, HS cows produced 1.9 kg/d more energy-corrected milk (4.45% increase), with higher yields of true protein (+0.13 kg/day), lactose (+0.10 kg/day), and total solids (+0.24 kg/day). Dry matter and organic matter digestibility was 4.2 and 4.3% higher, respectively, in the HS group. The milk fatty acid (FA) profile differed, with LS cows having greater mixed FA content and HS cows showing higher de novo FA content and yield. Although methane production tended to be higher in HS cows (+25 g/day), methane yield decreased by 8.8%. Overall, the HS diet improved milk production, nutrient digestibility, and environmental efficiency by reducing methane yield in dairy cows. Full article

(This article belongs to the Section Farm Animal Production)

► Show Figures

Figure 1

29 pages, 768 KiB

Open AccessArticle

Quantifying the Performance of European Agriculture Through the New European Sustainability Model

by Puiu-Lucian Georgescu, Nicoleta Barbuta-Misu, Monica Laura Zlati, Costinela Fortea and Valentin Marian Antohi

Agriculture 2025, 15(2), 210; https://doi.org/10.3390/agriculture15020210 - 18 Jan 2025

Viewed by 662

Abstract

The study aims to assess the performance of European sustainable agriculture through a new model of agricultural sustainability, addressing a significant gap identified in the literature: the lack of a systematic framework integrating the economic, environmental, and resource efficiency dimensions of agricultural resource [...] Read more.

The study aims to assess the performance of European sustainable agriculture through a new model of agricultural sustainability, addressing a significant gap identified in the literature: the lack of a systematic framework integrating the economic, environmental, and resource efficiency dimensions of agricultural resource use in the context of the EU Common Agricultural Policy and the Green Deal. The research develops four synthetic indicators: ISPAS (Index of Sustainable Agricultural Productivity), IREA (Index of Reduced Emissions from Agriculture), ISAC (Index of Combined Agricultural Sustainability), and IESA (Index of Agricultural Land Area Efficiency), each reflecting complementary aspects of sustainable agricultural performance. The methodology is based on an econometric linear model and a dynamic Arellano–Bond model, which allows the analysis of the temporal relationships between synthetic indicators and agricultural sustainability performance, capturing the inertia effects and structural dynamics of the European agricultural sector. The modeling provides a robust approach to capture the interdependencies between agricultural emission reductions, sustainability mainstreaming, and land use efficiency. The results of the study indicate a superior quality of measurement by applying this integrated framework, highlighting significant relationships between emission reductions, the integration of economic and environmental dimensions, and the optimization of agricultural land use. The analysis also provides valuable policy implications, suggesting concrete directions for adapting European agricultural policies to the structural particularities of Member States. By integrating a dynamic methodological framework and innovative synthetic indicators, this study contributes to a thorough understanding of agricultural sustainability performance and provides a practical tool for underpinning sustainable agricultural policies in the European Union. Full article

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

► Show Figures

Figure 1

25 pages, 5271 KiB

Open AccessArticle

Design and Experimental Research on a Chisel-Type Variable Hierarchical Deep Fertilization Device Suitable for Saline–Alkali Soil

by Nan Xu, Zhenbo Xin, Jin Yuan, Zenghui Gao, Yu Tian, Chao Xia, Xuemei Liu and Dongwei Wang

Agriculture 2025, 15(2), 209; https://doi.org/10.3390/agriculture15020209 - 18 Jan 2025

Viewed by 442

Abstract

In China, there are around 36.7 million hectares of saline–alkali lands that hold utilization potential. Precision fertilization stands as a vital measure for enhancing the quality of saline–alkali soil and promoting a significant increase in crop yields. The performance of the fertilization device [...] Read more.

In China, there are around 36.7 million hectares of saline–alkali lands that hold utilization potential. Precision fertilization stands as a vital measure for enhancing the quality of saline–alkali soil and promoting a significant increase in crop yields. The performance of the fertilization device is a decisive factor in determining the effectiveness of fertilization. To optimize the fertilizer utilization rate in coastal saline–alkali soils and substantially reduce fertilizer waste, it is imperative to transport fertilizers to the deep soil layers and execute layered variable-rate fertilization. In light of this, a chisel-type variable-rate layered electronically controlled deep-fertilization device specifically designed for saline–alkali soils has been developed. Extensive experimental research on its fertilization performance has also been carried out. Drawing on the principles of soil dynamics, this paper meticulously investigates the structures of key components and the operating parameters of the fertilization device. Key parameters such as the penetration angle of the fertilizer shovel, the penetration clearance angle, the curvature of the shovel handle, the angle between the fertilizer baffle and the fertilizer pipe wall, the angle between the fertilizer pipe and the horizontal plane, and the forward speed are precisely determined. Moreover, this study explores the quantitative relationship between the fertilizer discharge amount of the fertilizer applicator and the effective working width. Simultaneously, this research mainly focuses on analyzing the impact of the forward speed on the operational effect of layered and variable-rate fertilization. Through a series of field experiments, it was conclusively determined that the optimal fertilization effect was attained when the forward speed was set at 6 km/h. Under this condition, the average deviation in the fertilization amount was merely 2.76%, and the average coefficients of variation in the fertilizer amount uniformity in each soil layer were 7.62, 6.32, 6.06, and 5.65%, respectively. Evidently, the experimental results not only successfully met the pre-set objectives, but also fully satisfied the design requirements. Undoubtedly, this article can offer valuable methodological references for the research and development of fertilization devices tailored for diverse crops cultivated on saline–alkali lands. Full article

(This article belongs to the Section Agricultural Technology)

► Show Figures

Figure 1

24 pages, 6160 KiB

Open AccessArticle

Transboundary Impacts of NO₂ on Soil Nitrogen Fixation and Their Effects on Crop Yields in China

by Jinhui Xie, Peiheng Yu and Xiangzheng Deng

Agriculture 2025, 15(2), 208; https://doi.org/10.3390/agriculture15020208 - 18 Jan 2025

Viewed by 743

Abstract

Nitrogen dioxide (NO₂) impacts climate, air quality, soil nitrogen fixation, and crop production, yet its transboundary impacts remain unclear. This study combines 15 global datasets to assess nitrogen’s transboundary impacts on crop yields and soil health. We use machine learning to [...] Read more.

Nitrogen dioxide (NO₂) impacts climate, air quality, soil nitrogen fixation, and crop production, yet its transboundary impacts remain unclear. This study combines 15 global datasets to assess nitrogen’s transboundary impacts on crop yields and soil health. We use machine learning to develop yield prediction models for major grain crops (maize, rice, soybean, and wheat) affected by NO₂. Our findings indicate stable soil nitrogen fixation in China from 2015 to 2020, although overgrazing and deforestation may cause declines. Increasing soil total nitrogen content by 0.62–2.1 g/kg can reduce NO₂ by 10–30%. Our research indicates that the current agricultural environments for major grain crops (58.5–94.2%) have already exceeded the NO₂ concentration range that crops can tolerate, particularly in regions near northern urban clusters. This highlights the need for regional interventions, such as precision nitrogen fertilizer management, to enhance both soil nitrogen fixation and crop yields. Scenario analysis suggests that NO₂ control can boost maize and rice yields in a greener context, while increasing total nitrogen content improves wheat and soybean yields. This provides a solution for advancing sustainable agriculture by linking nitrogen cycle management with improved crop yields and environmental sustainability. Full article

(This article belongs to the Special Issue Current Prospects of Social-Ecologically More Sustainable Agriculture and Urban Agriculture)

► Show Figures

Figure 1

23 pages, 6569 KiB

Open AccessArticle

Relationship Between Soil Aggregate Stability and Associated Carbon and Nitrogen Changes Under Different Ecological Construction Measures in the Karst Region of Southwest China

by Meiting Li, Keqin Wang, Xiaoyi Ma, Mingsi Fan, Biyu Li and Yali Song

Agriculture 2025, 15(2), 207; https://doi.org/10.3390/agriculture15020207 - 18 Jan 2025

Viewed by 465

Abstract

As the fundamental unit of soil structure, soil aggregates play a crucial role in enhancing soil carbon and nitrogen storage, thereby supporting soil fertility and overall health, particularly in fragile karst regions. This study aims to quantify the effects of various ecological construction [...] Read more.

As the fundamental unit of soil structure, soil aggregates play a crucial role in enhancing soil carbon and nitrogen storage, thereby supporting soil fertility and overall health, particularly in fragile karst regions. This study aims to quantify the effects of various ecological construction measures on soil aggregate stability, including focusing on geometric mean diameter (GMD), mean weight diameter (MWD), and K values, as well as aggregate-related organic carbon (SOC) and total nitrogen (TN), soil mechanical composition, and aggregate content. The ecological construction measures examined include plantation forests (Y7th–rgl), restored forests (Y6th–zr), fruit forests (Y6th–jgl), and contour reverse slope terraces (Y1th–crt). Compared to sloping farmland, contour reverse slope terraces, with their distinctive priority induction function, significantly increased the content of medium-fine particle aggregates, greater than 87%. Among the ecological construction measures, plantation forests exhibited the highest aggregate stability, with an average increase ranging from 8% to 157%. Notably, microaggregates, regardless of size, possessed the highest carbon and nitrogen contents, contributing significantly to soil carbon and nitrogen pools. Furthermore, both plantation and contour reverse slope terrace treatments demonstrated an equal contribution of carbon and nitrogen across all aggregate sizes. The partial least squares path modeling (PLS-PM) analysis indicates that land use type and the content of carbon and nitrogen pools are the primary factors influencing soil aggregate stability. These findings suggest that plantations are particularly effective in enhancing soil and water conservation in fragile karst areas, while the contour reverse slope terrace method shows potential for stabilizing soil structure over extended time scales due to its unique “preferential entrainment” function. Full article

(This article belongs to the Section Agricultural Soils)

► Show Figures

Figure 1

25 pages, 9852 KiB

Open AccessArticle

Design and Optimization of Power Harrow Soil Crushing Components for Coastal Saline–Alkali Land

by Nan Xu, Zhenbo Xin, Jin Yuan, Zenghui Gao, Yu Tian, Chao Xia, Xuemei Liu and Dongwei Wang

Agriculture 2025, 15(2), 206; https://doi.org/10.3390/agriculture15020206 - 18 Jan 2025

Viewed by 435

Abstract

In China, there are approximately 36.7 million hectares of available saline–alkali land. The quality of land preparation significantly influences the yield of crops grown in saline–alkali soil. However, saline–alkali soil is highly compacted, and, currently, the market lacks land-preparation products specifically tailored to [...] Read more.

In China, there are approximately 36.7 million hectares of available saline–alkali land. The quality of land preparation significantly influences the yield of crops grown in saline–alkali soil. However, saline–alkali soil is highly compacted, and, currently, the market lacks land-preparation products specifically tailored to the unique characteristics of saline–alkali land. The soil crushing performance of existing power harrows fails to meet the requirements for high-quality land preparation, thus affecting crop planting yields. Consequently, it is imperative to conduct research on the design and performance improvement of the soil crushing components of power harrows for saline–alkali land. This paper centers on the key soil crushing component, the harrow blade, and conducts research from the perspectives of kinematics and dynamics. Initially, the ranges of key structural and motion parameters are determined, such as the angle of the harrow blade cutting edge, the thickness of the of the harrow blade cutting edge, and the ratio of the circumferential speed to the forward speed. Subsequently, through simulation tests integrating the Discrete Element Method (DEM) and the Box–Behnken Design (BBD), the optimal parameter combination is identified. The impact of the forward speed and the rotational speed of the vertical-shaft rotor on soil disturbance is analyzed. The relationship between soil disturbance and soil heaping is explored, and an optimal forward speed of around 6 km/h is determined. Field tests are conducted to verify the cause of soil heaping. The test results show that the soil crushing rates are all above 85%, with an average soil crushing rate of 88.66%. These test results have achieved the predetermined objectives and meet the design requirements. Full article

(This article belongs to the Section Agricultural Technology)

► Show Figures

Figure 1

19 pages, 16555 KiB

Open AccessArticle

WED-YOLO: A Detection Model for Safflower Under Complex Unstructured Environment

by Zhenguo Zhang, Yunze Wang, Peng Xu, Ruimeng Shi, Zhenyu Xing and Junye Li

Agriculture 2025, 15(2), 205; https://doi.org/10.3390/agriculture15020205 - 18 Jan 2025

Viewed by 462

Abstract

Accurate safflower recognition is a critical research challenge in the field of automated safflower harvesting. The growing environment of safflowers, including factors such as variable weather conditions in unstructured environments, shooting distances, and diverse morphological characteristics, presents significant difficulties for detection. To address [...] Read more.

Accurate safflower recognition is a critical research challenge in the field of automated safflower harvesting. The growing environment of safflowers, including factors such as variable weather conditions in unstructured environments, shooting distances, and diverse morphological characteristics, presents significant difficulties for detection. To address these challenges and enable precise safflower target recognition in complex environments, this study proposes an improved safflower detection model, WED-YOLO, based on YOLOv8n. Firstly, the original bounding box loss function is replaced with the dynamic non-monotonic focusing mechanism Wise Intersection over Union (WIoU), which enhances the model’s bounding box fitting ability and accelerates network convergence. Then, the upsampling module in the network’s neck is substituted with the more efficient and versatile dynamic upsampling module, DySample, to improve the precision of feature map upsampling. Meanwhile, the EMA attention mechanism is integrated into the C2f module of the backbone network to strengthen the model’s feature extraction capabilities. Finally, a small-target detection layer is incorporated into the detection head, enabling the model to focus on small safflower targets. The model is trained and validated using a custom-built safflower dataset. The experimental results demonstrate that the improved model achieves Precision (P), Recall (R), mean Average Precision (mAP), and F₁ score values of 93.15%, 86.71%, 95.03%, and 89.64%, respectively. These results represent improvements of 2.9%, 6.69%, 4.5%, and 6.22% over the baseline model. Compared with Faster R-CNN, YOLOv5, YOLOv7, and YOLOv10, the WED-YOLO achieved the highest mAP value. It outperforms the module mentioned by 13.06%, 4.85%, 4.86%, and 4.82%, respectively. The enhanced model exhibits superior precision and lower miss detection rates in safflower recognition tasks, providing a robust algorithmic foundation for the intelligent harvesting of safflowers. Full article

(This article belongs to the Special Issue Cutting-Edge Technology in Agricultural Robotics: Sensing and Actuation)

► Show Figures

Figure 1

21 pages, 2661 KiB

Open AccessReview

Progress in Elucidating the Mechanism of Selenium in Mitigating Heavy Metal Stress in Crop Plants

by Shuqing Jia, Qing Guan, Yulong Niu, Ye Wang, Linling Li and Hua Cheng

Agriculture 2025, 15(2), 204; https://doi.org/10.3390/agriculture15020204 - 18 Jan 2025

Viewed by 454

Abstract

In the context of rapid industrialization and agricultural modernization, the issue of heavy metal (HM) pollution has surfaced as a critical concern, posing a substantial threat to human health and having a profound impact on agricultural cultivation. Selenium (Se), a beneficial micronutrient for [...] Read more.

In the context of rapid industrialization and agricultural modernization, the issue of heavy metal (HM) pollution has surfaced as a critical concern, posing a substantial threat to human health and having a profound impact on agricultural cultivation. Selenium (Se), a beneficial micronutrient for crop growth and development, exerts numerous beneficial effects, including facilitating photosynthesis, enhancing physiological attributes, improving nutritional quality, strengthening antioxidant systems, and modulating the expression of stress-responsive genes. Notably, Se plays a pivotal role in alleviating HM stress in crops and effectively mitigating the accumulation of HMs in edible plant parts. This study investigates the physiological and molecular mechanisms underlying Se’s capacity to alleviate HM stress in crops. Additionally, we discuss the application of Se-enriched fertilizers in agricultural practices, as well as the influence of environmental factors on their effectiveness. Our objective is to contribute to sustainable agricultural development and the production of safe, high-quality agricultural products, thereby providing valuable insights for the development of Se-functional industries and guiding agricultural practices in regions affected by HM pollution. Full article

(This article belongs to the Special Issue Biostimulants for Crop Growth and Abiotic Stress Mitigation)

► Show Figures

Graphical abstract

23 pages, 3676 KiB

Open AccessArticle

Accumulation and Transport of Cd, Pb, As, and Cr in Different Maize Varieties in Southwest China

by Qi Liu, Sheng Wang, Jijiang Zhou, Li Bao, Wenbing Zhou and Naiming Zhang

Agriculture 2025, 15(2), 203; https://doi.org/10.3390/agriculture15020203 - 18 Jan 2025

Viewed by 343

Abstract

The southwestern region of China is one of the major maize (Zea mays L.)-producing areas and a concentrated zone of farmland contaminated by heavy metals (HMs). Selection of maize varieties with low accumulation of HMs under complex HM pollution conditions is one [...] Read more.

The southwestern region of China is one of the major maize (Zea mays L.)-producing areas and a concentrated zone of farmland contaminated by heavy metals (HMs). Selection of maize varieties with low accumulation of HMs under complex HM pollution conditions is one the most feasible and effective ways for safe utilization of HM-polluted farmland. In this study, we conducted field experiments to investigate the differences in biological traits among 28 local maize varieties under combined soil pollution with Cd, Pb, As, Cr, and Hg. We analyzed the absorption, accumulation, and transport characteristics of Cd, Pb, As, and Cr in various parts of the maize plant (Hg was not detected in any part of maize plants) and explored the relationships of HM contents in different parts of maize with soil HM contents through cluster analysis, correlation analysis, and principal component analysis. The results indicated that among different biological traits of maize, root length, root dry weight, and plant height were the most significantly influenced by soil HM content, while stem dry weight was the least affected. The accumulation capacity of various maize parts for HMs followed the order of grains < stems < cobs < leaves < roots, while the transport capacity followed the order of root–grain < root–stem < cob–grain < stem–cob < stem–leaf. In addition, the accumulation capacity of maize grains for HMs followed the order of As < Cr < Pb < Cd. Different HMs exhibited synergistic effects in various maize parts, except for the stem, particularly in the grains. A synchronous transport mechanism was observed for As and other HMs in different parts. The accumulation of HMs in maize was primarily derived from human activities such as the extraction, storage, and smelting of non-ferrous metals, while the HMs in soil parent material and weathering products played a secondary role. The yield of the tested maize varieties ranged from 7377.6 to 11,037.0 kg·hm⁻², with M5 (Haoyu 1511) achieving the highest yield. M2, M4, M5, M9, M10, M21, and M25–28 were identified as suitable varieties with low Cd, Pb, As, and Cr accumulation for popularization in HM-contaminated soils in southwestern China due to their low accumulation of HMs. Full article

(This article belongs to the Section Agricultural Soils)

► Show Figures

Figure 1

13 pages, 2062 KiB

Open AccessArticle

Evaluating Urban Sewage Sludge Distribution on Agricultural Land Using Interpolation and Machine Learning Techniques

by Andrea Lazzari, Simone Giovinazzo, Giovanni Cabassi, Massimo Brambilla, Carlo Bisaglia and Elio Romano

Agriculture 2025, 15(2), 202; https://doi.org/10.3390/agriculture15020202 - 17 Jan 2025

Viewed by 642

Abstract

The European Union promotes the development of a sustainable approach to solid waste management and disposal. Sewage sludge (SWS) is a good example of this economic model because it has fertilizing and soil-conditioning characteristics. This study employed a conventional manure spreader to evaluate [...] Read more.

The European Union promotes the development of a sustainable approach to solid waste management and disposal. Sewage sludge (SWS) is a good example of this economic model because it has fertilizing and soil-conditioning characteristics. This study employed a conventional manure spreader to evaluate the distribution of SWS on agricultural land. Various interpolation methods and machine learning models were employed to analyze the spatial distribution patterns of the sludge. Data were collected from 15 sampling trays across a controlled field during three separate trials. Statistical analysis using ANOVA highlighted significant variations in sludge quantities along the longitudinal axis but not along the latitudinal one. Interpolation methods, such as spline, cubic spline, and inverse distance weighting (IDW) were used to model the distribution, while machine learning models (k-nearest neighbors, random forest, neural networks) classified spatial patterns. Different performance metrics were calculated for each model. Among the interpolation methods, the IDW model combined with neural networks achieved the highest accuracy, with an MCC of 0.9820. The results highlight the potential for integrating advanced techniques into precision agriculture, improving application efficiency and reducing environmental impact. This approach provides a solid basis for optimizing the operation of agricultural machinery and supporting sustainable waste management practices. Full article

(This article belongs to the Section Agricultural Technology)

► Show Figures

Figure 1

22 pages, 3979 KiB

Open AccessArticle

Nutrient Formulation—A Sustainable Approach to Combat PRSV and Enhance Productivity in Papaya

by Kavitha Chinnasamy, Naveen Kumar Krishnan, Moganapathi Balasubramaniam, Reena Balamurugan, Pugalendhi Lakshmanan, Kalarani M. Karuppasami, Manoranjitham S. Karuppannan, Elaiyabharathi Thiyagarajan, Senthil Alagarswamy and Saraladevi Muthusamy

Agriculture 2025, 15(2), 201; https://doi.org/10.3390/agriculture15020201 - 17 Jan 2025

Viewed by 459

Abstract

Papaya (Carica papaya L.) is a highly nutritious fruit crop cultivated commercially in the tropical and subtropical regions of the world. Being a shallow rooted fruit crop, it requires frequent application of nutrients. Papaya is highly remunerative due to its high productivity [...] Read more.

Papaya (Carica papaya L.) is a highly nutritious fruit crop cultivated commercially in the tropical and subtropical regions of the world. Being a shallow rooted fruit crop, it requires frequent application of nutrients. Papaya is highly remunerative due to its high productivity and responds positively to nutrient application. Papaya Ring Spot Virus (PRSV) is a major threat to papaya production, which causes severe yield loss and reduces fruit quality. To combat PRSV and enhance productivity, a nutrient formulation was developed by combining organic, inorganic nutrient sources with biocontrol agents to improve the health and vigor of the plants. Experiments were conducted to standardize the application time and evaluate the efficacy of nutrient formulation in enhancing yield, and to combat papaya ring spot virus (PRSV) incidence in papaya from January 2021 to December 2023 at Tamil Nadu Agricultural University, Coimbatore, Tamil Nadu, India. The results revealed that foliar application of nutrient formulation at monthly intervals from the 3rd to the 7th month after planting (MAP) along with regular application of recommended dose of fertilizers (RDF) at bimonthly intervals from the 3rd MAP significantly increased the yield (37.79% and 30.57% in TNAU Papaya CO 8 and Red Lady, respectively) and reduced PRSV disease incidence (22.49% in TNAU Papaya CO 8 and 16.53% in Red Lady). Metabolomics study indicates that foliar spray of nutrient formulation enhanced the activators and precursors of defense enzymes, viz., peroxidase (PO), polyphenol oxidase (PPO), phenyl ammonia lyase (PAL), catalase (CAT) and nitrate reductase (NRase) in the sprayed plants over unsprayed control. Therefore, the sprayed plants exhibited tolerance to PRSV incidence by maintaining vigor and induced systemic resistance by the defense enzymes. Full article

(This article belongs to the Special Issue Foliar Fertilization for Sustainable Crop Production)

► Show Figures

Figure 1

15 pages, 705 KiB

Open AccessArticle

Characterization of the Pore Network of a Cohesive Oxisol Through Morphological and Pore Complexity Analyses

by Jocenei A. T. de Oliveira, Thaís N. Pessoa, José V. Gaspareto, Adolfo N. D. Posadas, André L. F. Lourenço, Paulo L. Libardi and Luiz F. Pires

Agriculture 2025, 15(2), 200; https://doi.org/10.3390/agriculture15020200 - 17 Jan 2025

Viewed by 458

Abstract

Cohesive Oxisols are a type of soil common in the Coastal Plateau in Brazil. These soils represent a challenge for agriculture and their study is fundamental to better land use. There have been a few studies on the porous system of cohesive soils [...] Read more.

Cohesive Oxisols are a type of soil common in the Coastal Plateau in Brazil. These soils represent a challenge for agriculture and their study is fundamental to better land use. There have been a few studies on the porous system of cohesive soils on the micrometer scale. Our study aimed to provide a detailed analysis of the pore complexity of the cohesive horizon of a Brazilian Oxisol using 3D images (volumetric data reconstructed by 2D CT slices) and to correlate these parameters with soil physical–hydric attributes. For this purpose, images with two different resolutions were analyzed from multifractal, lacunarity, and entropy analyses. Additionally, a characterization of hydraulic properties was carried out based on a soil water retention curve (SWRC). No differences were observed between the resolutions for the different physical parameters analyzed. The lacunarity analysis showed a greater homogeneity of the pore system with pores grouped in clusters. The multifractal analysis showed fractal characteristics for the cohesive horizon, suggesting a more homogeneous pore distribution. The main results obtained from the SWRC showed a low available water content due to the predominance of ultramicropores. Overall, the results show a less complex pore system, indicating the presence of pores of small sizes, affecting the water retention and conduction through the soil. Full article

(This article belongs to the Section Agricultural Soils)

► Show Figures

Figure 1

17 pages, 6799 KiB

Open AccessArticle

Characterization of PHT Genes in ‘duli’ (Pyrus betulifolia Bunge) and Expression Analysis of PbPHTs in Response to Plant Growth Regulators, P, and Salt Stress

by Shuai Yuan, Weilong Zhang and Yuxing Zhang

Agriculture 2025, 15(2), 199; https://doi.org/10.3390/agriculture15020199 - 17 Jan 2025

Viewed by 393

Abstract

The phosphate transporter (PHT) family plays an important role in the uptake and transport of P elements in plants. A total of 158 PbPHTs were identified from the genome of ‘duli’ (Pyrus betulifolia Bunge) in this study, including 70 PbPHT1s, [...] Read more.

The phosphate transporter (PHT) family plays an important role in the uptake and transport of P elements in plants. A total of 158 PbPHTs were identified from the genome of ‘duli’ (Pyrus betulifolia Bunge) in this study, including 70 PbPHT1s, 2 PbPHT2s, 70 PbPHT3s, 12 PbPHT4s, and 4 PbPHT5s. Among the 158 PHT genes, 150 were localized to 17 ‘duli’ chromosomes. Gene duplication analysis identified 18 tandemly duplicated gene pairs. The promoter analysis showed that there were a large number of cis-acting elements related to phytohormones, growth, development, stress, and light response in PbPHTs. qRT-PCR analysis revealed that most PHT genes in ‘duli’ were highly expressed in the fruits, flowers, leaves, stems, and roots, and 15 PbPHT genes were responsive to 5 μM, 0.5 mM, 5 mM H₂PO₄, NaCl, GR24 (synthetic SL analog), GA3 (gibberellin 3), ABA (abscisic acid), and IAA (indole-3-acetic acid). GR24, GA3, IAA, and 5 mM KH₂PO₄ treatments could increase the concentration, absorption, transport, and distribution of P elements in the rhizomes and leaves of ‘duli’, but 5 μM KH₂PO₄, NaCl, and ABA had the opposite effect. This study therefore provides a list of PbPHT genes with substantial roles in abiotic stress response, as well as important information to understand the functional characteristics of PbPHT during ‘duli’ abiotic stress tolerance, and explores the function of PbPHTs in exogenous hormones, phosphorus, and salt stress in the future. Full article

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

► Show Figures

Figure 1

23 pages, 10414 KiB

Open AccessArticle

Instance Segmentation and 3D Pose Estimation of Tea Bud Leaves for Autonomous Harvesting Robots

by Haoxin Li, Tianci Chen, Yingmei Chen, Chongyang Han, Jinhong Lv, Zhiheng Zhou and Weibin Wu

Agriculture 2025, 15(2), 198; https://doi.org/10.3390/agriculture15020198 - 17 Jan 2025

Viewed by 447

Abstract

In unstructured tea garden environments, accurate recognition and pose estimation of tea bud leaves are critical for autonomous harvesting robots. Due to variations in imaging distance, tea bud leaves exhibit diverse scale and pose characteristics in camera views, which significantly complicates the recognition [...] Read more.

In unstructured tea garden environments, accurate recognition and pose estimation of tea bud leaves are critical for autonomous harvesting robots. Due to variations in imaging distance, tea bud leaves exhibit diverse scale and pose characteristics in camera views, which significantly complicates the recognition and pose estimation process. This study proposes a method using an RGB-D camera for precise recognition and pose estimation of tea bud leaves. The approach first constructs an for tea bud leaves, followed by a dynamic weight estimation strategy to achieve adaptive pose estimation. Quantitative experiments demonstrate that the instance segmentation model achieves an mAP@50 of 92.0% for box detection and 91.9% for mask detection, improving by 3.2% and 3.4%, respectively, compared to the YOLOv8s-seg instance segmentation model. The pose estimation results indicate a maximum angular error of 7.76°, a mean angular error of 3.41°, a median angular error of 3.69°, and a median absolute deviation of 1.42°. The corresponding distance errors are 8.60 mm, 2.83 mm, 2.57 mm, and 0.81 mm, further confirming the accuracy and robustness of the proposed method. These results indicate that the proposed method can be applied in unstructured tea garden environments for non-destructive and precise harvesting with autonomous tea bud-leave harvesting robots. Full article

(This article belongs to the Section Agricultural Technology)

► Show Figures

Figure 1

17 pages, 8773 KiB

Open AccessArticle

Foliar Application and Translocation of Radiolabeled Zinc Oxide Suspension vs. Zinc Sulfate Solution by Soybean Plants

by Anita Beltrame, João Paulo Rodrigues Marques, Mariana Ayres Rodrigues, Eduardo de Almeida, Márcio Arruda Bacchi, Elisabete Aparecida De Nadai Fernandes, Rafael Otto and Hudson Wallace Pereira de Carvalho

Agriculture 2025, 15(2), 197; https://doi.org/10.3390/agriculture15020197 - 17 Jan 2025

Viewed by 898

Abstract

The present study employed a ⁶⁵Zn radioactive isotope as a tracer to investigate the foliar uptake and distribution patterns of ZnO concentrated suspension- and ZnSO₄ solution-sprayed on soybean plant leaves. The radiolabeled foliar treatments were sprayed on the leaves at V4 [...] Read more.

The present study employed a ⁶⁵Zn radioactive isotope as a tracer to investigate the foliar uptake and distribution patterns of ZnO concentrated suspension- and ZnSO₄ solution-sprayed on soybean plant leaves. The radiolabeled foliar treatments were sprayed on the leaves at V4 and V8 phenological stages. The radioactivity of ⁶⁵Zn in the leaves, roots, stems, and pods was determined using γ-ray spectrometry. After the first foliar spray, V4, the partition of radiolabeled Zn in plants treated with ZnO and ZnSO₄ was 99.22% and 98.12% in treated leaves, 0.15% and 0.39% in stems, 0.16% and 0.29% in roots, and 0.47% and 1.19% in newly expanded non-treated leaves, respectively. After two sprayings, V4 and V8, the partition of radiolabeled Zn in plants treated with ZnO and ZnSO₄ was 92.56% and 92.18% in treated leaves, 0.92% and 0.70% in stems, 0.52% and 0.39% in roots, 5.60% and 6.15% in newly expanded non-treated leaves, and 0.43% and 0.61% in grains, respectively. The total fraction translocated from the application tissue was 0.79% and 1.91% for ZnO and ZnSO₄, respectively, after 12 days and 8.03% and 8.48% for ZnO and ZnSO₄, respectively, after 72 days. An anatomical analysis revealed that plants cultivated in a nutrition solution with 10% ionic strength had 63% fewer stomata, and the xylem vessels were 63% smaller compared to plants grown in a solution with 100% Zn ionic. One can conclude that after a short period, 12 days, the absorption and translocation of ZnSO₄ was higher and faster than ZnO, and after the long period, 72 days, their performance was similar. Full article

(This article belongs to the Special Issue Mechanisms and Control of Nutrients, Beneficial Elements and Metals Uptake in Crops)

► Show Figures

Figure 1

17 pages, 2041 KiB

Open AccessArticle

LEAF-Net: A Unified Framework for Leaf Extraction and Analysis in Multi-Crop Phenotyping Using YOLOv11

by Ameer Tamoor Khan and Signe Marie Jensen

Agriculture 2025, 15(2), 196; https://doi.org/10.3390/agriculture15020196 - 17 Jan 2025

Viewed by 437

Abstract

Accurate leaf segmentation and counting are critical for advancing crop phenotyping and improving breeding programs in agriculture. This study evaluates YOLOv11-based models for automated leaf detection and segmentation across spring barley, spring wheat, winter wheat, winter rye, and winter triticale. The key focus [...] Read more.

Accurate leaf segmentation and counting are critical for advancing crop phenotyping and improving breeding programs in agriculture. This study evaluates YOLOv11-based models for automated leaf detection and segmentation across spring barley, spring wheat, winter wheat, winter rye, and winter triticale. The key focus is assessing whether a unified model trained on a combined multi-crop dataset can outperform crop-specific models. Results show that the unified model achieves superior performance in bounding box tasks, with mAP@50 exceeding 0.85 for spring crops and 0.7 for winter crops. Segmentation tasks, however, reveal mixed results, with individual models occasionally excelling in recall for winter crops. These findings highlight the benefits of dataset diversity in improving generalization, while emphasizing the need for larger annotated datasets to address variability in real-world conditions. While the combined dataset improves generalization, the unique characteristics of individual crops may still benefit from specialized training. Full article

(This article belongs to the Special Issue Single Leaf Area Models and Leaf Area Index in Agriculture and Its Related Ecosystems)

► Show Figures

Figure 1

34 pages, 8155 KiB

Open AccessReview

Raman Spectroscopy and Its Application in Fruit Quality Detection

by Yong Huang, Haoran Wang, Huasheng Huang, Zhiping Tan, Chaojun Hou, Jiajun Zhuang and Yu Tang

Agriculture 2025, 15(2), 195; https://doi.org/10.3390/agriculture15020195 - 17 Jan 2025

Viewed by 526

Abstract

Raman spectroscopy is a spectral analysis technique based on molecular vibration. It has gained widespread acceptance as a practical tool for the non-invasive and rapid characterization or identification of multiple analytes and compounds in recent years. In fruit quality detection, Raman spectroscopy is [...] Read more.

Raman spectroscopy is a spectral analysis technique based on molecular vibration. It has gained widespread acceptance as a practical tool for the non-invasive and rapid characterization or identification of multiple analytes and compounds in recent years. In fruit quality detection, Raman spectroscopy is employed to detect organic compounds, such as pigments, phenols, and sugars, as well as to analyze the molecular structures of specific chemical bonds or functional groups, providing valuable insights into fruit disease detection, pesticide residue analysis, and origin identification. Consequently, Raman spectroscopy techniques have demonstrated significant potential in agri-food analysis across various domains. Notably, the frontier of Raman spectroscopy is experiencing a surge in machine learning applications to enhance the resolution and quality of the resulting spectra. This paper reviews the fundamental principles and recent advancements in Raman spectroscopy and explores data processing techniques that use machine learning in Raman spectroscopy, with a focus on its applications in detecting fruit diseases, analyzing pesticide residues, and identifying origins. Finally, it highlights the challenges and future prospects of Raman spectroscopy, offering an effective reference for fruit quality detection. Full article

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

► Show Figures

Figure 1

13 pages, 2048 KiB

Open AccessArticle

Agronomic Performance of European Pear Cultivars in Different Training Systems in the Highland Region of Southern Brazil

by Alex Felix Dias, Sabrina Baldissera, Alberto Ramos Luz, Augusto Schütz Ferreira, Bruno Dalazen Machado, Bruno Pirolli, Renaldo Borges de Andrade Júnior, Joel de Castro Ribeiro, Daiana Petry Rufato, Aike Anneliese Kretzschmar, Amauri Bogo and Leo Rufato

Agriculture 2025, 15(2), 194; https://doi.org/10.3390/agriculture15020194 - 16 Jan 2025

Viewed by 514

Abstract

This study aimed to evaluate the vegetative, productive, and fruit quality parameters of the European pear cultivars ‘Rocha’ and ‘Santa Maria’ under the training systems of Tall Spindle, with branches bent at an angle of 45° (Tall Spindle—45°) and 90° (Tall Spindle—90°) to [...] Read more.

This study aimed to evaluate the vegetative, productive, and fruit quality parameters of the European pear cultivars ‘Rocha’ and ‘Santa Maria’ under the training systems of Tall Spindle, with branches bent at an angle of 45° (Tall Spindle—45°) and 90° (Tall Spindle—90°) to the leader, and Bi-axis. The evaluation was conducted over the 2016/2017 to 2022/2023 growing seasons in the highland region of southern Brazil. Both Tall Spindle systems significantly improved the yield and productive efficiency compared to the Bi-axis system, with ‘Santa Maria’ showing superior performance under Tall Spindle—90°. While ‘Rocha’ exhibited no significant differences between Tall Spindle systems, it benefited from better vigor control and reduced biennial bearing when trained under the Bi-axis system. Fruit quality parameters were consistent across training systems, indicating Tall Spindle—90° as an optimal choice for productivity and stability in ‘Santa Maria’. These results emphasize the adaptability and efficiency of training systems for pear orchard management. Full article

(This article belongs to the Section Crop Production)

► Show Figures

Figure 1

16 pages, 6327 KiB

Open AccessArticle

Bacillus velezensis TCS001 Enhances the Resistance of Hickory to Phytophthora cinnamomi and Reshapes the Rhizosphere Microbial Community

by Chenshun Xie, Yuntian Wu, Zhonghao Wu, Hao Cao, Xiaohui Huang, Feng Cui, Shuai Meng and Jie Chen

Agriculture 2025, 15(2), 193; https://doi.org/10.3390/agriculture15020193 - 16 Jan 2025

Viewed by 599

Abstract

Phytophthora cinnamomi causes significant root rot in hickory, leading to substantial yield losses. While Bacillus spp. are recognized as beneficial rhizosphere microorganisms, their application against hickory root rot and their impact on rhizosphere microbial communities remain under-investigated. This study demonstrated that Bacillus velezensis [...] Read more.

Phytophthora cinnamomi causes significant root rot in hickory, leading to substantial yield losses. While Bacillus spp. are recognized as beneficial rhizosphere microorganisms, their application against hickory root rot and their impact on rhizosphere microbial communities remain under-investigated. This study demonstrated that Bacillus velezensis TCS001 significantly inhibited P. cinnamomi ST402 growth in vitro, and achieved 71% efficacy in root rot disease management. Scanning electron microscopy (SEM) revealed that TCS001 fermentation filtrate induced mycelial deformities in P. cinnamomi. An analysis of α and β diversity indicated a significant impact of TCS001 on rhizosphere bacterial community richness and diversity, with minimal effects on the fungal community. Moreover, TCS001 altered the hickory rhizosphere microbiome co-occurrence network. The differential abundance analysis suggests that TCS001 promotes the recruitment of beneficial microbes associated with disease resistance, thereby suppressing disease development. These findings underscore the influence of TCS001 on the hickory rhizosphere microbiome in the presence of pathogens, providing valuable data for future research and the development of effective biocontrol strategies for hickory root rot. Full article

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

► Show Figures

Figure 1

Journal Menu

Journal Browser

Agriculture, Volume 15, Issue 2 (January-2 2025) – 107 articles

Further Information

Guidelines

MDPI Initiatives

Follow MDPI