Journal Description
Agriculture
Agriculture
is an international, scientific peer-reviewed open access journal published monthly online by MDPI.
- Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
- High Visibility: indexed within Scopus, SCIE (Web of Science), PubAg, AGRIS, RePEc, and other databases.
- Journal Rank: JCR - Q1 (Agronomy) / CiteScore - Q2 (Plant Science)
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 17.7 days after submission; acceptance to publication is undertaken in 2.4 days (median values for papers published in this journal in the second half of 2023).
- Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
- Companion journals for Agriculture include: Poultry, Grasses and Crops.
Impact Factor:
3.6 (2022);
5-Year Impact Factor:
3.6 (2022)
Latest Articles
Design and Test of a Grain Cleaning Loss Monitoring Device for Wheat Combine Harvester
Agriculture 2024, 14(5), 671; https://doi.org/10.3390/agriculture14050671 (registering DOI) - 25 Apr 2024
Abstract
As the world’s first large grain crop, wheat in its mechanized harvesting process faces a serious problem, namely, when the combine harvester operating parameters are not set reasonably, it leads to increased losses of wheat kernels to an extent exceeding the prescribed standard,
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As the world’s first large grain crop, wheat in its mechanized harvesting process faces a serious problem, namely, when the combine harvester operating parameters are not set reasonably, it leads to increased losses of wheat kernels to an extent exceeding the prescribed standard, of which the loss of scavenging accounts for a large proportion. Excessive grain harvest loss will not only reduce the quality of the wheat harvest but also adversely affect its yield. Real-time monitoring of losses in the harvesting process is key to the dynamic adjustment of operating parameters to decrease machine harvesting losses. This article proposes a grain cleaning loss monitoring device for combine harvesters suitable for wheat crops. It aims to measure the loss of grain cleaning in the process of wheat harvesting in real time and adjust the operating parameters of the harvester timeously by feeding back the data to the driver in real time, so as to decrease the loss of wheat grains in the process of harvesting and achieve the purpose of reducing the loss of harvest. When the device was tested in the field, the wheat variety was Bainong 4199, the yield per mu was 625.83 kg (one mu is 1/15 of a hectare, or approximately 666.67 m2), the mass of grain was 43.21 g, and the water content was 14.2%. After the test, the monitoring error of the loss monitoring device was within 8%, and the average error rate was 6.69%. The test proves that the monitoring device achieves the expected design effect and meets design requirements. The results of this paper are of significance to the intelligent control system of wheat combine harvesters and provide a reference for research into grain cleaning loss monitoring devices for wheat combine harvesters.
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(This article belongs to the Topic Emerging Agricultural Engineering Sciences, Technologies, and Applications—2nd Edition)
Open AccessReview
Role of Genome Sequences of Major and Minor Millets in Strengthening Food and Nutritional Security for Future Generations
by
Theivanayagam Maharajan, Thumadath Palayullaparambil Ajeesh Krishna, Neenthamadathil Mohandas Krishnakumar, Mani Vetriventhan, Himabindu Kudapa and Stanislaus Antony Ceasar
Agriculture 2024, 14(5), 670; https://doi.org/10.3390/agriculture14050670 (registering DOI) - 25 Apr 2024
Abstract
Millets are small-seeded cereals belonging to the family Poaceae. They are considered to be climate-resilient and future nutritional food cereals for humans. Millets are resistant to biotic and abiotic stressors compared to other major cereals and thrive in low-quality soils with little maintenance
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Millets are small-seeded cereals belonging to the family Poaceae. They are considered to be climate-resilient and future nutritional food cereals for humans. Millets are resistant to biotic and abiotic stressors compared to other major cereals and thrive in low-quality soils with little maintenance and less rainfall. The importance of millets is still not well known to many people due to the lack of popularity and cultivation in semi-arid tropics of Asia and Africa. The United Nations has declared 2023 as the International Year of Millets (IYM 2023) to promote millet cultivation and popularize their health benefits globally. A few years ago, the application of molecular biology was in its infancy in millets due to the unavailability of genome sequences. Genome sequences are available for most of the millets on NCBI and Phytozome databases. In this review, we discuss the details of genome sequences for millets, candidate genes identified from the native genome of millets. The current status of quantitative trait loci and genome-wide association studies in millets are also discussed. The utilization of millet genome sequences in functional genomics research and translating the information for crop improvement will help millet and non-millet cereals survive harsh environments in the future. Such efforts will help strengthen food security and reduce malnutrition worldwide in 2050.
Full article
(This article belongs to the Special Issue Feature Papers in Genotype Evaluation and Breeding)
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Open AccessArticle
Organic Certification, Online Market Access, and Agricultural Product Prices: Evidence from Chinese Apple Farmers
by
Li Zhang, Dong Liu, Qie Yin and Jundi Liu
Agriculture 2024, 14(5), 669; https://doi.org/10.3390/agriculture14050669 (registering DOI) - 25 Apr 2024
Abstract
Motivated by the increasing interest in sustainable agriculture and the potential benefits associated with organic certification, this study employs a multidimensional fixed-effects model to analyze data derived from onsite surveys conducted among 681 apple farmers in the Loess Plateau region of China to
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Motivated by the increasing interest in sustainable agriculture and the potential benefits associated with organic certification, this study employs a multidimensional fixed-effects model to analyze data derived from onsite surveys conducted among 681 apple farmers in the Loess Plateau region of China to explore the influence of organic certification on absolute and relative agricultural product prices given online market access. The findings indicated a significant increase in apple prices among farmers who held organic certifications and engaged in online market sales, with prices rising by CNY1.60 per half kilogram. Additionally, this study highlights that the amalgamation of organic certification with online market access significantly enhances agricultural product prices by facilitating better dissemination of market information among farmers. Furthermore, this research addresses a critical gap in the existing literature by clarifying the differential impact of organic certification across distinct farmer demographics and geographical regions. The more pronounced positive impact of organic certification on prices observed among cooperative members and farmers in the low-altitude areas is particularly noteworthy. These results underscore the crucial role of online market access in achieving premium effects and price stability for organically certified products.
Full article
(This article belongs to the Section Agricultural Economics, Policies and Rural Management)
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Open AccessArticle
Nectar Production and Three Main Sugars in Nectar of Salvia pratensis and Salvia glutinosa in Correlation with Abiotic Factors
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Katja Malovrh, Blanka Ravnjak, Jože Bavcon and Mitja Križman
Agriculture 2024, 14(5), 668; https://doi.org/10.3390/agriculture14050668 (registering DOI) - 25 Apr 2024
Abstract
Floral nectar is mainly a reward in the form of food for pollinators. Its composition plays an important role when pollinators choose their food. Several studies have shown that the popularity of flowers with nectar is influenced by the concentration and ratio of
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Floral nectar is mainly a reward in the form of food for pollinators. Its composition plays an important role when pollinators choose their food. Several studies have shown that the popularity of flowers with nectar is influenced by the concentration and ratio of sugars. Here, we present the nectar chemical composition with regard to three main sugars and their concentrations in correlation with abiotic factors for the plant species Salvia pratensis L. and Salvia glutinosa L. through their 2023 flowering season. We sampled nectar using microcapillaries at three different times during the day on sites in nature. Our results show that nectar production in both species is the highest at around 12 a.m. The abiotic factor that affects nectar production in both species is the soil temperature, while UVB radiation does not influence nectar production. Air temperature and air humidity affect the nectar production of S. glutinosa, while soil humidity affects nectar production in S. pratensis. The most represented sugar in S. glutinosa nectar is sucrose, while S. pratensis nectar has more glucose and fructose. Our results show that UVB radiation has an effect on the sucrose level, although it does not have any direct effect on nectar productivity.
Full article
(This article belongs to the Section Agricultural Product Quality and Safety)
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Open AccessArticle
Perceived Organizational Support, Inter-Temporal Choice, and Farmer Conservation Tillage Adoption
by
Tong Zhang, Liangming Lang, Nan Zhao, Qian Lu and Bailiang Sun
Agriculture 2024, 14(5), 667; https://doi.org/10.3390/agriculture14050667 (registering DOI) - 25 Apr 2024
Abstract
To solve the problem of the insufficient driving force and low adoption rate of conservation tillage adoption and to enhance the effect of industrial organization in influencing technology diffusion, this paper explored the relationship and the mechanism of perceived organizational support and inter-temporal
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To solve the problem of the insufficient driving force and low adoption rate of conservation tillage adoption and to enhance the effect of industrial organization in influencing technology diffusion, this paper explored the relationship and the mechanism of perceived organizational support and inter-temporal choice in the adoption of conservation tillage by using micro-research data from 725 melon farmers in the Shaanxi and Shanxi provinces in China and by applying the experimental economics method to obtain the inter-temporal choices of the farmers. This paper also analyzed farmers’ risk preferences’ moderating effect on the relationship between inter-temporal choice and conservation tillage. Additionally, it examined the impact of perceived organizational support on the differentiation of different conservation tillage technologies. The study found that perceived organizational support significantly contributes to adopting zero tillage and minimum tillage, and water-saving irrigation. Perceived organizational support was not conducive to farmers’ adoption of furrow and ridge tillage. The impact of perceived organizational support on technology adoption is heterogeneous, depending on the differences in the size of the family’s cultivated land. The inter-temporal choice of farmers significantly impedes the adoption of conservation tillage. The increase in risk preference helps alleviate the hindering effect of inter-temporal choice on farmers’ adoption of conservation tillage. Perceived organizational support can promote the adoption of conservation tillage by reducing farmers’ inter-temporal choices. Inter-temporal choice is an essential mechanism by which perceived organizational support affects the adoption of conservation tillage. Compared with the existing studies, this paper incorporates the technology-attribute-induced inter-temporal choice of farmers into the impact analysis framework and considers the relationship between perceived organizational support, inter-temporal choice, and the adoption of conservation tillage and the mechanism of its action. The findings of the study provide a theoretical basis for the enrichment of incentive mechanisms for the adoption of conservation tillage, which is of great significance for the improvement of the tool for the integration of small farmers in developing countries into the industrial activities of the new agricultural business central bodies and for promoting the diffusion of conservation tillage in agriculture.
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(This article belongs to the Topic Novel Studies in Agricultural Economics and Sustainable Farm Management)
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Open AccessArticle
Corn Leaf Spot Disease Recognition Based on Improved YOLOv8
by
Shixiong Yang, Jingfa Yao and Guifa Teng
Agriculture 2024, 14(5), 666; https://doi.org/10.3390/agriculture14050666 (registering DOI) - 25 Apr 2024
Abstract
Leaf spot disease is an extremely common disease in the growth process of maize in Northern China and its degree of harm is quite significant. Therefore, the rapid and accurate identification of maize leaf spot disease is crucial for reducing economic losses in
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Leaf spot disease is an extremely common disease in the growth process of maize in Northern China and its degree of harm is quite significant. Therefore, the rapid and accurate identification of maize leaf spot disease is crucial for reducing economic losses in maize. In complex field environments, traditional identification methods are susceptible to subjective interference and cannot quickly and accurately identify leaf spot disease through color or shape features. We present an advanced disease identification method utilizing YOLOv8. This method utilizes actual field images of diseased corn leaves to construct a dataset and accurately labels the diseased leaves in these images, thereby achieving rapid and accurate identification of target diseases in complex field environments. We have improved the model based on YOLOv8 by adding Slim-neck modules and GAM attention modules and introducing them to enhance the model’s ability to identify maize leaf spot disease. The enhanced YOLOv8 model achieved a precision (P) of 95.18%, a recall (R) of 89.11%, an average recognition accuracy (mAP50) of 94.65%, and an mAP50-95 of 71.62%, respectively. Compared to the original YOLOv8 model, the enhanced model showcased enhancements of 3.79%, 4.65%, 3.56%, and 7.3% in precision (P), recall (R), average recognition accuracy (mAP50), and mAP50-95, respectively. The model can effectively identify leaf spot disease and accurately calibrate its location. Under the same experimental conditions, we compared the improved model with the YOLOv3, YOLOv5, YOLOv6, Faster R-CNN, and SSD models. The results show that the improved model not only enhances performance, but also reduces parameter complexity and simplifies the network structure. The results indicated that the improved model enhanced performance, while reducing experimental time. Hence, the enhanced method proposed in this study, based on YOLOv8, exhibits the capability to identify maize leaf spot disease in intricate field environments, offering robust technical support for agricultural production.
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(This article belongs to the Section Crop Protection, Diseases, Pests and Weeds)
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BerryNet-Lite: A Lightweight Convolutional Neural Network for Strawberry Disease Identification
by
Jianping Wang, Zhiyu Li, Guohong Gao, Yan Wang, Chenping Zhao, Haofan Bai, Yingying Lv, Xueyan Zhang and Qian Li
Agriculture 2024, 14(5), 665; https://doi.org/10.3390/agriculture14050665 (registering DOI) - 25 Apr 2024
Abstract
With the rapid advancements in computer vision, using deep learning for strawberry disease recognition has emerged as a new trend. However, traditional identification methods heavily rely on manual discernment, consuming valuable time and imposing significant financial losses on growers. To address these challenges,
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With the rapid advancements in computer vision, using deep learning for strawberry disease recognition has emerged as a new trend. However, traditional identification methods heavily rely on manual discernment, consuming valuable time and imposing significant financial losses on growers. To address these challenges, this paper presents BerryNet-Lite, a lightweight network designed for precise strawberry disease identification. First, a comprehensive dataset, encompassing various strawberry diseases at different maturity levels, is curated. Second, BerryNet-Lite is proposed, utilizing transfer learning to expedite convergence through pre-training on extensive datasets. Subsequently, we introduce expansion convolution into the receptive field expansion, promoting more robust feature extraction and ensuring accurate recognition. Furthermore, we adopt the efficient channel attention (ECA) as the attention mechanism module. Additionally, we incorporate a multilayer perceptron (MLP) module to enhance the generalization capability and better capture the abstract features. Finally, we present a novel classification head design approach which effectively combines the ECA and MLP modules. Experimental results demonstrate that BerryNet-Lite achieves an impressive accuracy of 99.45%. Compared to classic networks like ResNet34, VGG16, and AlexNet, BerryNet-Lite showcases superiority across metrics, including loss value, accuracy, precision, F1-score, and parameters. It holds significant promise for applications in strawberry disease identification.
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(This article belongs to the Special Issue Computer Vision and Artificial Intelligence in Agriculture)
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Open AccessArticle
Soil Bacterial Community of Medicinal Plant Rhizosphere in a Mediterranean System
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Yosef Steinberger, Tirza Doniger, Chen Sherman, Mareeswaran Jeyaraman and Itaii Applebaum
Agriculture 2024, 14(5), 664; https://doi.org/10.3390/agriculture14050664 (registering DOI) - 25 Apr 2024
Abstract
Several attempts have been made to evaluate the abundance and distribution of the bacterial community in the rhizosphere of medicinal plants. Many describe information based on an estimation of the community structure and the effects of plant cover in determining microbial community composition.
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Several attempts have been made to evaluate the abundance and distribution of the bacterial community in the rhizosphere of medicinal plants. Many describe information based on an estimation of the community structure and the effects of plant cover in determining microbial community composition. The ability of plants to specifically shape their microbial community in general and medicinal plants in particular is largely unknown. With the arrival of molecular biology, understanding the microbial community’s composition, diversity, and function became possible. We hypothesized that microbial communities associated with medicinal shrubs would differ from each other. To test this hypothesis, we characterized the soil microbial composition under each of five Mediterranean medicinal plants, differentiated by their medicinal use and ecophysiological adaptation, namely, Salvia fruticosa, Pistacia lentiscus, Myrtus communis, Origanum syriacum, and Teucrium capitatum, and an open-space bare soil between the plants, inhabiting natural ecosystems characterized by similar climatic conditions typical of a Mediterranean environment. The results demonstrated the importance of plant ecophysiological adaptations, which play an important role in determining microbial community composition and functional diversity. The intensity of a plant’s response to its surroundings can have either positive or negative effects that will determine the microbial community composition and interactions among the belowground parts. A total of 11 phyla, 21 orders, and 409 genera were found in the soil rhizosphere in the vicinity of the four plants and open space samples. The distinguishing attributes of each shrub trigger and stimulate the microbial community’s rhizosphere. This results in distinct patterns of bacterial diversity and functionality between the different shrubs and the control. The rhizosphere bacterial community composition differed between the plants in a PERMANOVA test, but there was little difference in terms of phyla and order relative abundances. This study shows how five medicinal plants, coexisting in a common habitat, impact the bacterial community. The noticeable shift in bacterial composition further supports our discovery that root exudates effectively govern the makeup of soil bacterial communities.
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(This article belongs to the Section Agricultural Soils)
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Open AccessReview
Pleurotus ostreatus Mushroom: A Promising Feed Supplement in Poultry Farming
by
Gréta Törős, Hassan El-Ramady, Áron Béni, Ferenc Peles, Gabriella Gulyás, Levente Czeglédi, Mahendra Rai and József Prokisch
Agriculture 2024, 14(5), 663; https://doi.org/10.3390/agriculture14050663 (registering DOI) - 25 Apr 2024
Abstract
Pleurotus ostreatus (Jacq. ex Fr.) P. Kumm mushrooms are cultivated on diverse by-products based on substrates that hold promise for mitigating antibiotic usage in the poultry industry and reducing environmental pollution. By incorporating agricultural by-products into mushroom cultivation, the functionality of the mushroom
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Pleurotus ostreatus (Jacq. ex Fr.) P. Kumm mushrooms are cultivated on diverse by-products based on substrates that hold promise for mitigating antibiotic usage in the poultry industry and reducing environmental pollution. By incorporating agricultural by-products into mushroom cultivation, the functionality of the mushroom products can be increased, then the final product can be a more effective feed supplement. After mushroom cultivation, spent mushroom substrate (SMS) can be valorized, due to the presence of huge amounts of bioactive compounds like β-glucan, chitin, polyphenols, and flavonoids related to mycelia. As a prebiotic and antimicrobial feed supplement, these mushrooms positively influence gut microbiota, intestinal morphology, and thus overall poultry well-being. This article underscores the potential of solid-state fermentation (SSF) to enhance the bioactivity of oyster mushrooms and their derivatives, offering a cost-effective and efficient strategy for transforming unconventional feeding materials. Moreover, it emphasizes broader implications, including the reduction of antibiotic dependence in poultry farming, highlighting the promising integration of oyster mushrooms and their derivatives for sustainable and environmentally conscious poultry production.
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(This article belongs to the Special Issue Effects of Feed Additives on Growth Performance, Intestinal Health and Resilience of Poultry)
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Spatio-Temporal Evolution of Olive Tree Water Status Using Land Surface Temperature and Vegetation Indices Derived from Landsat 5 and 8 Satellite Imagery in Southern Peru
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Javier Alvaro Quille-Mamani, German Huayna, Edwin Pino-Vargas, Samuel Chucuya-Mamani, Bertha Vera-Barrios, Lia Ramos-Fernandez, Jorge Espinoza-Molina and Fredy Cabrera-Olivera
Agriculture 2024, 14(5), 662; https://doi.org/10.3390/agriculture14050662 (registering DOI) - 25 Apr 2024
Abstract
Land surface temperature (LST) and its relationship with vegetation indices (VIs) have proven to be effective for monitoring water stress in large-scale crops. Therefore, the objective of this study is to find an appropriate VI to analyse the spatio-temporal evolution of olive water
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Land surface temperature (LST) and its relationship with vegetation indices (VIs) have proven to be effective for monitoring water stress in large-scale crops. Therefore, the objective of this study is to find an appropriate VI to analyse the spatio-temporal evolution of olive water stress using LST images and VIs derived from Landsat 5 and 8 satellites in the semi-arid region of southern Peru. For this purpose, VIs (Normalised Difference Vegetation Index (NDVI), Enhanced Vegetation Index 2 (EVI2) and Soil Adjusted Vegetation Index (SAVI)) and LST were calculated. The information was processed in Google Earth Engine (GEE) for the period 1985 to 2024, with an interval of every five years for the summer season. The triangle method was applied based on the LST-VIs scatterplot analysis, a tool that establishes wet and dry boundary conditions for the Temperature Vegetation Dryness Index (TVDI). The results indicated a better appreciation of olive orchard water stress over time, with an average of 39% drought (TVDINDVI and TVDISAVI), 24% severe drought (TVDINDVI) and 25% (TVDISAVI) of the total area, compared to TVDIEVI2, which showed 37% drought and 16% severe drought. It is concluded that TVDINDVI and TVDISAVI provide a better visualisation of the water stress map of the olive crop and offer a range of options to address current and future problems in water resource management in the olive sector in semi-arid areas of southern Peru.
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(This article belongs to the Section Digital Agriculture)
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Transcriptomic Analysis of Melatonin-Mediated Salt Stress Response in Germinating Alfalfa
by
Zirui Liu, Xiangling Ren, Wenxuan Zhu, Yingao Li, Guoming Li, Caifeng Liu, Defeng Li, Yinghua Shi, Chengzhang Wang, Xiaoyan Zhu and Hao Sun
Agriculture 2024, 14(5), 661; https://doi.org/10.3390/agriculture14050661 (registering DOI) - 24 Apr 2024
Abstract
Salt stress poses a significant threat to crop yields worldwide. Melatonin (MT), an endogenous hormone synthesized in plants, has emerged as a crucial player in plant responses to various abiotic stresses, including drought, salinity, heat, and cold. However, the precise molecular mechanisms underlying
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Salt stress poses a significant threat to crop yields worldwide. Melatonin (MT), an endogenous hormone synthesized in plants, has emerged as a crucial player in plant responses to various abiotic stresses, including drought, salinity, heat, and cold. However, the precise molecular mechanisms underlying MT-mediated abiotic stress responses remain incompletely understood. To elucidate the key genes and pathways involved in MT-mediated alleviation of salt stress, we conducted physiological, biochemical, and transcriptomic analyses on alfalfa seedlings. Our results demonstrated that alfalfa seedlings treated with melatonin exhibited higher germination rates, longer bud lengths, and greater fresh weights compared to those subjected to salt stress alone. Furthermore, the levels of malondialdehyde (MDA) and superoxide anion (O2−) were reduced, while the activities and contents of antioxidant enzymes such as superoxide dismutase (SOD), peroxidase (POD), and glutathione (GSH) increased in response to melatonin treatment. Transcriptome analysis revealed 2181 differentially expressed genes (DEGs) in the salt-treated group, with 780 upregulated and 1401 downregulated genes. In contrast, the MT-treated group exhibited 4422 DEGs, including 1438 upregulated and 2984 downregulated genes. Functional annotation and pathway enrichment analysis indicated that DEGs were primarily involved in the biosynthesis of flavonoids, isoflavones, plant hormones, glutathione (GSH), soluble sugars, and other substances, as well as in ABC transporter and MAPK signaling pathways. Notably, the MT-treated group showed greater enrichment of DEGs in these pathways, suggesting that MT mitigates salt stress by modulating the expression of genes related to phytohormones and antioxidant capacity. Overall, our findings provide valuable insights into the molecular mechanisms underlying MT-mediated salt tolerance in alfalfa, with important implications for breeding salt-tolerant alfalfa and other crops.
Full article
(This article belongs to the Special Issue Responses and Tolerance to Abiotic Stress in Forage and Turf Grasses)
Open AccessArticle
Effects of Different Natural Drying Methods on Drying Characteristics and Quality of Diaogan apricots
by
Qiaonan Yang, Can Hu, Jie Li, Hongwei Xiao, Wenwen Jia, Xufeng Wang, Xiangjuan Liu, Ziya Tang, Bingzhou Chen, Xiaokang Yi and Xibing Li
Agriculture 2024, 14(5), 660; https://doi.org/10.3390/agriculture14050660 (registering DOI) - 24 Apr 2024
Abstract
Drying is one of the best methods to preserve the quality of fresh fruits and prolong their shelf life. This study focuses on Prunus armeniaca L. cv. ‘Diaogan’ (commonly known as Diaogan apricot) sourced from Xinjiang, China to explore the impact of
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Drying is one of the best methods to preserve the quality of fresh fruits and prolong their shelf life. This study focuses on Prunus armeniaca L. cv. ‘Diaogan’ (commonly known as Diaogan apricot) sourced from Xinjiang, China to explore the impact of two natural drying methods (shade drying and open-air drying in the rocky desert) on the drying kinetics, color, textural characteristics, microstructure, chemical properties, and antioxidant capacity of Diaogan apricots. The experimental results indicate that throughout the natural drying process, the time required for open-air drying in the rocky desert was reduced by 26.47% compared to shade drying. The L*, a*, and b* values of the shade- and ventilation-dried Diaogan apricots were higher than those sun-dried in the rocky desert, exhibiting a lower color difference (ΔE) than apricots dried through rocky desert sun drying. Specifically, the ΔE for shade-dried Diaogan apricots was 19.66 ± 0.24. The Diaogan apricots dried in the rocky desert exhibited greater hardness, lower elasticity, stronger adhesiveness, and higher chewiness compared to those dried in the shade, with the hardness, adhesiveness, and chewiness being, respectively, 14.71%, 18.89%, and 35.79% higher. Scanning electron microscopy (SEM) observations revealed that the high temperatures experienced during open-air drying in the rocky desert caused rapid dehydration of the Diaogan apricot’s skin, leading to clogging and crust formation in the flesh pores, along with deformation or tearing of the tissue structure, ultimately resulting in poor rehydration ability. After drying, there was a significant increase in the soluble solids in the Diaogan apricots, whereas titratable acidity, total phenols, ascorbic acid, and antioxidant capacity were significantly decreased (p < 0.05). In summary, the quality of dried Diaogan apricots post-drying is dependent on the natural drying method employed, with shade drying resulting in superior quality of Diaogan apricots compared to open-air drying in the rocky desert. This study offers fundamental data and serves as a theoretical reference for the industrialized production of apricots.
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(This article belongs to the Special Issue Agricultural Products Processing and Quality Detection)
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Using Cover Crops as Means of Controlling Weeds and Reducing the Applied Quantity of Glyphosate-Based Herbicide in No-Till Glyphosate Tolerant Soybean and Corn
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Jérôme Bernier Brillon, Marc Lucotte, Ariane Bernier, Myriam Fontaine and Matthieu Moingt
Agriculture 2024, 14(5), 659; https://doi.org/10.3390/agriculture14050659 - 24 Apr 2024
Abstract
Weeds represent a serious drawback affecting the productivity of field crops worldwide. While the most common approach to control weeds in no-till practices is the use of glyphosate-based herbicides (GBHs), reducing their use represents a major challenge. This two-year field study aims to
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Weeds represent a serious drawback affecting the productivity of field crops worldwide. While the most common approach to control weeds in no-till practices is the use of glyphosate-based herbicides (GBHs), reducing their use represents a major challenge. This two-year field study aims to evaluate whether the use of cover crops (CC) in transgenic soybean and corn productions can (1) help control weeds and (2) reduce the amount of GBH needed for managing weeds. Sampling was carried out in 32 experimental field plots (four crop managements with four replicates on both crops). Crop managements consisted of GBH applications at rates of 0.84, 1.67, and 3.3 L ha−1 in plots in direct seeding with CC (DSCC) and at rates of 3.3 L ha−1 in plots without CC (DS). Weed cover rates, plant parameters (fresh and dry weights and heights), grain yields, water, and cation contents in soil were considered as indicators of interspecific competition. Results obtained in both years show that it is possible to reduce GBH use by 50% in plots with CC compared to plots without CC using a rate of GBH application of 3.33 L ha−1 (DS 3.3). However, weeds had a large impact on water content in soil, which was reflected by smaller plants and lower yields in plots with only 0.84 L ha−1 of GBH applied. In the context of the study, the use of CCs seems to facilitate the development of more sustainable agriculture while reducing the quantities of GBH generally used.
Full article
(This article belongs to the Special Issue Benefits and Challenges of Cover Crops in Agricultural Systems)
Open AccessArticle
Heterogeneity of Intramuscular, Intermuscular, and Subcutaneous Fat in Laiwu Pigs: Insights from Targeted Lipidomics and Transcriptomics
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Jian Xu, Tianwen Wu, Sin Man Lam, Guanghou Shui, Shulin Yang, Yanfang Wang and Cong Tao
Agriculture 2024, 14(5), 658; https://doi.org/10.3390/agriculture14050658 - 24 Apr 2024
Abstract
In the livestock industry, an excessive accumulation of subcutaneous fat diminishes the proportion of lean meat, while elevated intramuscular fat (IMF) content is associated with enhanced meat quality. However, the heterogeneity of various fat depots in pigs remains incompletely understood. Comprehensive tissue section,
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In the livestock industry, an excessive accumulation of subcutaneous fat diminishes the proportion of lean meat, while elevated intramuscular fat (IMF) content is associated with enhanced meat quality. However, the heterogeneity of various fat depots in pigs remains incompletely understood. Comprehensive tissue section, lipidomic, and transcriptomic analyses indicated that the maturity of IMF was significantly less than that of both intermuscular and subcutaneous fats. We identified 467 lipids across 29 lipid classes in total, revealing that IMF exhibits unique lipid composition and transcriptional profiles. More importantly, several lipids, including GalCer, S1P, CL, AcCa, PC-O, PE-O, and sulfatide, are highly enriched in intramuscular fat and may play pivotal roles in neuromodulation, mitochondrial function, lipogenesis, and membrane signaling. In conclusion, we unveiled unique lipid composition and molecular regulatory pathways of porcine IMF, offering new insights for the synergistic breeding that aims at optimizing pig backfat thickness and IMF content.
Full article
(This article belongs to the Special Issue Current Research and Strategies for Improving Farm Animal Meat Quality)
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A Genome-Wide Comparative Analysis of AUX1/LAX, PIN, and ABCB Genes Reveals Their Roles in Cucumber Fruit Curving
by
Ke Lu, La Zhang, Lianxue Fan, Xiuyan Zhou and Shengnan Li
Agriculture 2024, 14(5), 657; https://doi.org/10.3390/agriculture14050657 - 24 Apr 2024
Abstract
Auxin transport is regulated by the AUX1/LAX, PIN, and ABCB gene families, controlling the distribution of auxin and ultimately fruit curving in cucumbers. However, studies on the differential expression of these auxin transporters and their roles in fruit curving are limited.
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Auxin transport is regulated by the AUX1/LAX, PIN, and ABCB gene families, controlling the distribution of auxin and ultimately fruit curving in cucumbers. However, studies on the differential expression of these auxin transporters and their roles in fruit curving are limited. In this study, we identified 36 auxin transporters from cucumber, including CsLAX1–7, CsPIN1–10, and CsABCB1–19. Basic characteristic analysis revealed that all CsLAX proteins were conservative, and a C-terminal NPNTY motif was found in CsPIN1–4/7–10. CsABCB1/5/11/14/17 were categorized as half-size transporters. Phylogenetic analysis revealed a genetic relationship between auxin transporters in Arabidopsis and cucumber. Exogenous auxin treatment on fruits and qPCR analysis indicated that differential expression patterns of auxin transporters control cucumber fruit curving. Co-expression analysis indicated that CsPIN1 and CsLAX2 were substantially negatively correlated, and they displayed opposite expression patterns in curved fruits. A proposed model suggested that CsLAX2 transports extracellular auxin to the convex side of the fruit; however, CsPIN1 inhibits auxin efflux at the same location. This leads to uneven auxin distribution that results in cucumber fruit curving.
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(This article belongs to the Special Issue Agronomic Practices for Improving Growth, Quality, and Yield of Vegetables)
Open AccessReview
Nano-Food Farming Approaches to Mitigate Heat Stress under Ongoing Climate Change: A Review
by
Hassan El-Ramady, József Prokisch, Mohammed E. El-Mahrouk, Yousry A. Bayoumi, Tarek A. Shalaby, Eric C. Brevik and Svein Ø. Solberg
Agriculture 2024, 14(5), 656; https://doi.org/10.3390/agriculture14050656 - 24 Apr 2024
Abstract
Increased heat stress is a common feature of global climate change and can cause adverse impacts on crops from germination through maturation and harvest. This review focuses on the impacts of extreme heat (>35 °C) on plants and their physiology and how they
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Increased heat stress is a common feature of global climate change and can cause adverse impacts on crops from germination through maturation and harvest. This review focuses on the impacts of extreme heat (>35 °C) on plants and their physiology and how they affect food and water security. The emphasis is on what can be done to minimize the negative effects of heat stress, which includes the application of various materials and approaches. Nano-farming is highlighted as one promising approach. Heat is often combined with drought, salinity, and other stresses, which together affect the whole agroecosystem, including soil, plants, water, and farm animals, leading to serious implications for food and water resources. Indeed, there is no single remedy or approach that can overcome such grand issues. However, nano-farming can be part of an adaptation strategy. More studies are needed to verify the potential benefits of nanomaterials but also to investigate any negative side-effects, particularly under the intensive application of nanomaterials, and what problems this might create, including potential nanotoxicity.
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(This article belongs to the Section Ecosystem, Environment and Climate Change in Agriculture)
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Open AccessArticle
Spatial Analysis of Intercity Migration Patterns of China’s Rural Population: Based on the Network Perspective
by
Yihu Zhou, Huiguang Chen and Tingting Fang
Agriculture 2024, 14(5), 655; https://doi.org/10.3390/agriculture14050655 - 24 Apr 2024
Abstract
Since entering the 21st century, many developing countries around the world have begun to enter a stage of rapid urbanization; large-scale “rural-urban” population migration has become a typical social phenomenon in these countries. Against this backdrop, this paper aims to elucidate the spatial
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Since entering the 21st century, many developing countries around the world have begun to enter a stage of rapid urbanization; large-scale “rural-urban” population migration has become a typical social phenomenon in these countries. Against this backdrop, this paper aims to elucidate the spatial migration characteristics of rural populations and to discuss future rural–urban development strategies. For this purpose, this paper takes China as a case and employs methods such as spatial autocorrelation analysis, hotspot analysis, and network analysis to construct an intercity migration network of rural migrants and analyze its spatial characteristics and internal structure. The results indicate that the migration pattern of the rural population exhibits notable spatial clustering features. Cities in the eastern and central regions are, respectively, hotspots for the inflow and outflow of rural populations, with internal migration dominating in western cities and relatively inactive rural population movements in northeastern cities. Municipalities directly under the central government, sub-provincial cities, and provincial capitals show a significant tendency to attract rural populations, while prefecture-level and county-level cities mainly radiate rural populations outward. Cities nationwide form seven major clusters in the migration network, and these clusters exhibit distinct structural characteristics. Rural population migration is influenced by various factors. In the future, considerations should focus on the county as the primary unit, attracting rural populations for local employment, and promoting rural revitalization and agriculture development. The findings of this paper are of reference significance not only to China but also to many developing countries with similar national conditions in the world.
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(This article belongs to the Special Issue Depopulation of Rural Areas: Social, Economic, and Environmental Issues)
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Open AccessArticle
Enhancing Predictive Accuracy in European Agricultural Tractor Residual Value Estimation: A Double Square Root Regression Reappraisal
by
Ivan Herranz-Matey and Luis Ruiz-Garcia
Agriculture 2024, 14(5), 654; https://doi.org/10.3390/agriculture14050654 - 23 Apr 2024
Abstract
Determining the residual value of tractors is imperative for comprehensive cost analyses within the agricultural machinery sector. Despite numerous studies offering various models and independent variables, the double square root regression approach, originally developed by Cross and Perry and adapted by ASABE for
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Determining the residual value of tractors is imperative for comprehensive cost analyses within the agricultural machinery sector. Despite numerous studies offering various models and independent variables, the double square root regression approach, originally developed by Cross and Perry and adapted by ASABE for North American contexts, has been widely utilized. However, factors such as the complexity of OEM portfolios, steep price increases due to compliance with diesel emission regulations, and limited data availability in Europe and its market specificities necessitate improvements in predictive accuracy. This study evaluates different tractor cohort alternatives beyond engine horsepower to enhance predictive robustness. Incorporating brand and powertrain type alongside engine power significantly improved model performance and exhibited the strongest robustness, as evidenced by reduced the root mean square error (RMSE) and increased R-squared values. These findings contribute to the refinement of tractor residual value estimation models, offering valuable insights for stakeholders in the agricultural machinery industry.
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(This article belongs to the Section Agricultural Technology)
Open AccessArticle
Optimizing Efficiency of Tea Harvester Leaf-Collection Pipeline: Numerical Simulation and Experimental Validation
by
Zhe Du, Liyuan Zhang, Xinping Li, Xin Jin and Fan Yu
Agriculture 2024, 14(5), 653; https://doi.org/10.3390/agriculture14050653 - 23 Apr 2024
Abstract
To address the challenges of missed and disorderly picking in tea harvesters, this study focused on the leaf-collection pipeline and utilized Fluent simulation 19.0 software. A single-factor test identified key parameters affecting airflow velocity. An orthogonal test evaluated the main pipe taper, number
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To address the challenges of missed and disorderly picking in tea harvesters, this study focused on the leaf-collection pipeline and utilized Fluent simulation 19.0 software. A single-factor test identified key parameters affecting airflow velocity. An orthogonal test evaluated the main pipe taper, number of branch pipes, and branch pipe outlet diameter, with average outlet wind speed and wind speed non-uniformity as indicators. The optimal parameters were a main pipe taper of 25.5 mm, 10 branch pipes, and an inner diameter of 17.10 mm for the outlet, resulting in 10.73 m/s average wind speed and 8.24% non-uniformity. Validation tests showed errors under 1%. Further optimization on the internal structure’s extension length led to 11.02 m/s average wind speed and 8.04% non-uniformity. Field experiments demonstrated a 3.40% stalk leakage rate and 90.36% bud leaf integrity rate; the optimized structure of the leaf-collecting pipeline significantly improved the uniformity of airflow and the picking efficiency. These findings offer valuable insights and practical benefits for enhancing the efficiency of tea harvesters.
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(This article belongs to the Special Issue Smart Mechanization and Automation in Agriculture)
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Open AccessArticle
Opportunity of the NEGFRY Decision Support System for the Sustainable Control of Potato Late Blight in A Limia (NW of Spain)
by
Laura Meno, Olga Escuredo and M. Carmen Seijo
Agriculture 2024, 14(5), 652; https://doi.org/10.3390/agriculture14050652 - 23 Apr 2024
Abstract
The NEGFRY system is presented in this research work as a novelty strategy for the control of potato late blight in A Limia (NW Spain). The aim was to analyse the number of fungicide applications established by NEGFRY (Decision Support System, DSS) with
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The NEGFRY system is presented in this research work as a novelty strategy for the control of potato late blight in A Limia (NW Spain). The aim was to analyse the number of fungicide applications established by NEGFRY (Decision Support System, DSS) with respect to the routine calendars of this potato production area. This approach is in accordance with the requirements imposed by European policies, participating in more profitable and environmentally friendly agriculture. For this purpose, the relationships between the pathogen and the environmental conditions and epidemiological parameters were analysed in different plots compared to late blight infection in both Routine and DSS strategies. In addition, economic and environmental impacts of fungicide sprays were also analysed to check the adaptability of the decision support system to late blight in the area. Results confirmed that it is possible to reduce sprays following the NEGFRY model by more than 50% compared with Routine applications. Therefore, NEGFRY is a promising strategy to achieve lower footprint potato yields through a reduction in applied pesticides and water, lower gas emissions and less soil compaction due to a reduction in the number of tractor passes over the soil. The commitment to this strategy contributes to improving the economy of farmers, the health of the biodiversity, the environment and consumers, as well as to comply with demands of global economies in terms of more sustainable and resilient agriculture.
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(This article belongs to the Section Crop Protection, Diseases, Pests and Weeds)
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