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 - Q1 (Plant Science)
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 20.2 days after submission; acceptance to publication is undertaken in 2.3 days (median values for papers published in this journal in the first half of 2024).
- 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:
3.3 (2023);
5-Year Impact Factor:
3.5 (2023)
Latest Articles
The Effect of Humic Acid Supplementation on Selected Ruminal Fermentation Parameters and Protozoal Generic Distribution in Cows
Agriculture 2024, 14(10), 1663; https://doi.org/10.3390/agriculture14101663 (registering DOI) - 24 Sep 2024
Abstract
The objective of this study was to examine the effect of humic acid (HA) supplementation on the rumen fermentation and protozoal community in the rumen. For this purpose, four ruminally cannulated Simmental cows were randomly assigned in a replicated 4 × 4 Latin
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The objective of this study was to examine the effect of humic acid (HA) supplementation on the rumen fermentation and protozoal community in the rumen. For this purpose, four ruminally cannulated Simmental cows were randomly assigned in a replicated 4 × 4 Latin square design experiment to study the effect of HA dietary supplementation on feed utilization, rumen fermentation, and protozoal community for 84 days. The basal diet (BD) was composed of meadow hay (68.2% of dry matter [DM]), maize silage (17% of DM), and granulated feed mixture (14.9% of DM). There were four treatments, including the BD without additives (control diet, H0), the BD supplemented with 50 g HA/cow/day (H50 treatment), the BD supplemented with 100 g HA/cow/day (H100 treatment), and the BD supplemented with 200 g HA/cow/day (H200 treatment). HA supplementation did not affect the total or individual volatile fatty acid concentrations, the total protozoa, or the ruminal pH. However, HA at the dosage of 50 g/cow/day increased the NH3-N concentration and fecal nitrogen compared to the control (p < 0.001). HA supplementation also significantly impacted the abundance of individual protozoal genera in the rumen. The results of this study suggest that HA has potential in ruminants as a natural feed additive and may play a role in nitrogen metabolism and stabilizing the protozoal community without adverse effects on rumen fermentation.
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(This article belongs to the Section Farm Animal Production)
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Strigolactone Alleviates NaCl Stress by Regulating Antioxidant Capacity and Hormone Levels in Rice (Oryza sativa L.) Seedlings
by
Jianqin Zhang, Naijie Feng, Dianfeng Zheng, Aaqil Khan, Youwei Du, Yaxing Wang, Rui Deng, Jiashuang Wu, Jian Xiong, Zhiyuan Sun, Qicheng Zhang and Mingxin Wang
Agriculture 2024, 14(9), 1662; https://doi.org/10.3390/agriculture14091662 (registering DOI) - 23 Sep 2024
Abstract
Salt stress is a key environmental factor altering rice plant growth. Strigolactones (GR24) play a vital role in responding to various abiotic stresses and regulating plant growth. However, the regulatory mechanisms of SLs on rice seedlings under salt stress have not yet been
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Salt stress is a key environmental factor altering rice plant growth. Strigolactones (GR24) play a vital role in responding to various abiotic stresses and regulating plant growth. However, the regulatory mechanisms of SLs on rice seedlings under salt stress have not yet been clarified. A pot experiment was undertaken to evaluate the effects of GR24 soaking on the rice variety ‘Huanghuazhan’ (salt-sensitive) seedling growth, antioxidant metabolism, and endogenous hormones under NaCl stress. Results showed that NaCl stress significantly inhibited rice growth; disrupted antioxidant enzymes activity; and increased the content of soluble proteins (SPs), proline (Pro), malondialdehyde (MDA) and hydrogen–peroxide (H2O2). GR24 significantly improved photosynthetic pigments and antioxidant–enzyme activities, including superoxide dismutase (SOD), catalase (CAT), peroxidase (POD), and ascorbate–peroxidase (APX); increased SP, ascorbic acid (AsA); and reduced glutathione (GSH) content and MDA, H2O2, and Pro content, resulting in the mitigation of oxidative injury caused by NaCl stress. Moreover, GR24 significantly increased the content of strigolactones (SLs), cytokinin (CTK), auxin (IAA), Gibberellin A3 (GA3), and IAA/ABA and CTK/ABA ratios and decreased the abscisic acid (ABA). Findings indicated that GR24 alleviated oxidative damage caused by NaCl stress by increasing photosynthetic and antioxidant capacity and maintaining the balance of endogenous hormones, thus improving the salt tolerance of rice seedlings.
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(This article belongs to the Section Crop Production)
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Open AccessEditorial
Soil Mechanical Systems and Related Farming Machinery
by
Yongjin Cho and Ju-Seok Nam
Agriculture 2024, 14(9), 1661; https://doi.org/10.3390/agriculture14091661 (registering DOI) - 23 Sep 2024
Abstract
The mechanization of agricultural work has contributed significantly to the improvement of agricultural productivity and reduced production costs [...]
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(This article belongs to the Special Issue Soil Mechanical Systems and Related Farming Machinery)
Open AccessReview
Fire Impacts on Soil Properties and Implications for Sustainability in Rotational Shifting Cultivation: A Review
by
Noppol Arunrat, Praeploy Kongsurakan, Lemlem Wondwossen Solomon and Sukanya Sereenonchai
Agriculture 2024, 14(9), 1660; https://doi.org/10.3390/agriculture14091660 (registering DOI) - 23 Sep 2024
Abstract
Fire, a prevalent land management tool in rotational shifting cultivation (RSC), has long been debated for its immediate disruption of surface soil, vegetation, and microbial communities. While low-intensity and short-duration slash-and-burn techniques are considered beneficial for overall soil function, the dual nature of
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Fire, a prevalent land management tool in rotational shifting cultivation (RSC), has long been debated for its immediate disruption of surface soil, vegetation, and microbial communities. While low-intensity and short-duration slash-and-burn techniques are considered beneficial for overall soil function, the dual nature of fire’s impact warrants a comprehensive exploration. This review examines both the beneficial and detrimental effects of fire on soil properties within the context of RSC. We highlight that research on soil microbial composition, carbon, and nitrogen dynamics following fire events in RSC is gaining momentum. After fires, soil typically shows decreases in porosity, clay content, aggregation, and cation exchange capacity, while sand content, pH, available phosphorus, and organic nitrogen tend to increase. There remains ongoing debate regarding the effects on bulk density, silt content, electrical conductivity, organic carbon, total nitrogen, and exchangeable ions (K+, Ca2+, Mg2+). Certain bacterial diversity often increases, while fungal communities tend to decline during post-fire recovery, influenced by the soil chemical properties. Soil erosion is a major concern because fire-altered soil structures heighten erosion risks, underscoring the need for sustainable post-fire soil management strategies. Future research directions are proposed, including the use of advanced technologies like remote sensing, UAVs, and soil sensors to monitor fire impacts, as well as socio-economic studies to balance traditional practices with modern sustainability goals. This review aims to inform sustainable land management practices that balance agricultural productivity with ecological health in RSC systems.
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(This article belongs to the Special Issue Feature Review in Agricultural Soils—Intensification of Soil Health)
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Open AccessArticle
Long-Term Minimum Tillage and Straw Retention Promote Macroaggregate Formation, Carbon and Nitrogen Sequestration under Wheat-Maize Rotation in Northern China
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Zhijie Ren, Xiaojie Han, Zhidong Han, Wenzhong Tian, Junhong Li, Junjie Lv, Yuanxin Shen, Yingxin Xie, Geng Ma, Gezi Li, Yanan Zhao and Chenyang Wang
Agriculture 2024, 14(9), 1659; https://doi.org/10.3390/agriculture14091659 (registering DOI) - 22 Sep 2024
Abstract
Conservation tillage is believed to promote soil aggregate stability, carbon (C) and nitrogen (N) sequestration, but the underlying mechanisms remain unclear. In this study, soil samples from an 18-year experiment including conventional tillage with straw removal (CT), deep scarification with straw mulching (DS),
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Conservation tillage is believed to promote soil aggregate stability, carbon (C) and nitrogen (N) sequestration, but the underlying mechanisms remain unclear. In this study, soil samples from an 18-year experiment including conventional tillage with straw removal (CT), deep scarification with straw mulching (DS), and no-tillage with straw mulching (NT) were used to obtain different fractions based on a comprehensive wet-sieving method of aggregate and particle size. The results showed that NT and DS increased soil organic carbon (SOC) and N by 9.3–16.4% and 10.8–25.8%, respectively, in addition to increasing the weight proportion of macroaggregates and the contribution of macroaggregate-associated C and N to total SOC and N. The C change in the total POM accounted for 77.4% and 79.9% of the total SOC increase by NT and DS, while the MAOM only accounted for 29.2% and 25.2%, respectively. Meanwhile, microaggregates-within-macroaggregates accounted for 96.9% and 90.5% of the SOC increase by NT and DS, respectively. The total SOC and N were positively correlated with the C and N of the macroaggregates and subfractions. In conclusion, the formation of macroaggregates drives soil C and N sequestration under conservation tillage, and POM and mM were important functional pools in this process.
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(This article belongs to the Section Agricultural Soils)
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Open AccessArticle
Research on the Energy Management Strategy of a Hybrid Tractor OS-ECVT Based on a Dynamic Programming Algorithm
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Kai Zhang, Xiaoting Deng, Zhixiong Lu and Tao Wang
Agriculture 2024, 14(9), 1658; https://doi.org/10.3390/agriculture14091658 (registering DOI) - 22 Sep 2024
Abstract
The multi-degree-of-freedom characteristics of the planetary gear electronic continuously variable transmission (ECVT) configuration in series-parallel hybrid tractors impose more complex requirements for energy management strategies under variable load conditions. For a high-power hybrid tractor, this paper takes the hybrid tractor output-split (OS)-ECVT configuration
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The multi-degree-of-freedom characteristics of the planetary gear electronic continuously variable transmission (ECVT) configuration in series-parallel hybrid tractors impose more complex requirements for energy management strategies under variable load conditions. For a high-power hybrid tractor, this paper takes the hybrid tractor output-split (OS)-ECVT configuration as the research object and describes the principles of stepless transmission and power-splitting within the configuration. In order to improve the fuel economy of high-power hybrid tractors and the running status of power components, an energy management strategy focused on ploughing conditions based on the Bellman minimum dynamic programming (DP) algorithm is proposed in this paper. Second, equivalent fuel consumption is selected as the performance index for energy-saving control, and the solving principle of the energy management strategy based on the dynamic programming algorithm is established to facilitate the resolution process of the energy management strategy. Finally, the energy-saving control simulation is completed under ploughing conditions. The results show that compared with the energy management strategy based on the optimal operating line (OOL), the energy management strategy based on DP fully utilizes the benefits of low-cost electric energy and enables the hybrid power system to have a wider range of stepless transmission performance. In addition, the hybrid power system has the advantages of enhanced decoupling of speed and torque, higher efficiency, and more economical secondary energy conversion. As a result, the whole machine has enhanced power-split performance, greatly improving the running conditions of the power components. The equivalent fuel consumption values of the energy management strategies based on DP and OOL are about 3.1238 L and 4.2713 L, respectively. The equivalent fuel consumption based on DP is reduced by about 26.87%, which effectively improves the fuel efficiency of hybrid tractors.
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(This article belongs to the Special Issue From Planting to Harvesting: The Role of Agricultural Machinery in Crop Cultivation)
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Open AccessArticle
Sarcocornia fruticosa, a Potential Candidate for Saline Agriculture: Antioxidant Levels in Relation to Environmental Conditions in the Eastern Iberian Peninsula
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Neus Ortega Albero, Sara Vallejo Sardon, Ioan Lupuţ, Monica Boscaiu, Maria P. Donat-Torres, Ana Fita and Sara González-Orenga
Agriculture 2024, 14(9), 1657; https://doi.org/10.3390/agriculture14091657 (registering DOI) - 22 Sep 2024
Abstract
Sustainable crop production requires an innovative approach due to increasing soil salinisation and decreasing freshwater availability. One promising strategy is the domestication of naturally salt-tolerant plant species with commercial potential. Sarcocornia fruticosa is a highly salt-tolerant halophyte, common in Mediterranean marshes, which may
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Sustainable crop production requires an innovative approach due to increasing soil salinisation and decreasing freshwater availability. One promising strategy is the domestication of naturally salt-tolerant plant species with commercial potential. Sarcocornia fruticosa is a highly salt-tolerant halophyte, common in Mediterranean marshes, which may hold promise for biosaline agriculture. This study included 11 populations of this species spread over the territory of the Valencian Community in eastern Spain. Climatic data for each locality were obtained from the nearest meteorological stations. Soil analyses included texture, pH, electroconductivity, organic carbon and organic matter. Biochemical analyses on wild-sampled plant material focused on antioxidant compounds, such as carotenoids, phenolics, flavonoids and proline with malondialdehyde (MDA) used as a marker of oxidative stress. All variables (climatic, edaphic and biochemical) were evaluated together using Principal Component Analysis and Spearman correlation. The results obtained indicated some climatic differences in terms of mean annual precipitation, with a clear N-S gradient and considerable edaphic variability. However, none of the environmental conditions showed a clear correlation with plant biochemical characteristics. Significant differences in the levels of phenolic compounds, flavonoids and MDA between populations were probably due to genetic factors and cannot be explained as a response to environmental conditions.
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(This article belongs to the Section Ecosystem, Environment and Climate Change in Agriculture)
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Assessing Economic Viability of Resilient Sheep Foraging Alternatives in Lowland Regions of Romania
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Rodica Chetroiu, Steliana Rodino, Vili Dragomir, Diana Maria Ilie and Ancuța Marin
Agriculture 2024, 14(9), 1656; https://doi.org/10.3390/agriculture14091656 (registering DOI) - 22 Sep 2024
Abstract
Sheep farming is an important branch of the animal husbandry sector in Europe. In 2023, Romania’s sheep and goat herds ranked third in the European Union, with more than 10 million heads, contributing substantially to the production of meat, traditional cheeses, and wool.
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Sheep farming is an important branch of the animal husbandry sector in Europe. In 2023, Romania’s sheep and goat herds ranked third in the European Union, with more than 10 million heads, contributing substantially to the production of meat, traditional cheeses, and wool. However, in the current climate context, with extreme weather events and especially long periods of drought, providing optimal fodder ratio becomes a challenge for farmers. As animal nutritionists provide valid alternatives, consistent with the nutritional requirements of the species, the present work aims to present some economically efficient fodder alternatives to use for milk production in sheep farms of different sizes. The study brings added value to research in the field of using fodder alternatives in animal nutrition through the economic aspects researched because profitability is pursued in any activity, thus completing the technical arguments of previous studies in the literature in the field. Several economic indicators were calculated, such as the total value by categories of expenses, the value of production, the level of profit, and the rate of gross and net return. The analysis demonstrated that regardless of their size, the sheep farms located in lowland areas can reach positive values of profitability indicators when using alternative fodder in animal feeding.
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(This article belongs to the Special Issue Sustainable Rural Development and Agri-Food Systems—2nd Edition)
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Open AccessArticle
Real-Time ConvNext-Based U-Net with Feature Infusion for Egg Microcrack Detection
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Chenbo Shi, Yuejia Li, Xin Jiang, Wenxin Sun, Changsheng Zhu, Yuanzheng Mo, Shaojia Yan and Chun Zhang
Agriculture 2024, 14(9), 1655; https://doi.org/10.3390/agriculture14091655 (registering DOI) - 22 Sep 2024
Abstract
Real-time automatic detection of microcracks in eggs is crucial for ensuring egg quality and safety, yet rapid detection of micron-scale cracks remains challenging. This study introduces a real-time ConvNext-Based U-Net model with Feature Infusion (CBU-FI Net) for egg microcrack detection. Leveraging edge features
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Real-time automatic detection of microcracks in eggs is crucial for ensuring egg quality and safety, yet rapid detection of micron-scale cracks remains challenging. This study introduces a real-time ConvNext-Based U-Net model with Feature Infusion (CBU-FI Net) for egg microcrack detection. Leveraging edge features and spatial continuity of cracks, we incorporate an edge feature infusion module in the encoder and design a multi-scale feature aggregation strategy in the decoder to enhance the extraction of both local details and global semantic information. By introducing large convolution kernels and depth-wise separable convolution from ConvNext, the model significantly reduces network parameters compared to the original U-Net. Additionally, a composite loss function is devised to address class imbalance issues. Experimental results on a dataset comprising over 3400 graded egg microcrack image patches demonstrate that CBU-FI Net achieves a reduction in parameters to one-third the amount in the original U-Net, with an inference speed of 21 ms per image (1 million pixels). The model achieves a Crack-IoU of 65.51% for microcracks smaller than 20 m and a Crack-IoU and MIoU of 60.76% and 80.22%, respectively, for even smaller cracks (less than 5 m), achieving high-precision, real-time detection of egg microcracks. Furthermore, on the publicly benchmarked CrackSeg9k dataset, CBU-FI Net achieves an inference speed of 4 ms for 400 × 400 resolution images, with an MIoU of 81.38%, proving the proposed method’s robustness and generalization capability across various cracks and complex backgrounds.
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(This article belongs to the Special Issue Intelligent Agricultural Machinery and Robots: Embracing Technological Advancements for a Sustainable and Highly Efficient Agricultural Future)
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Open AccessArticle
Addressing Rural Decline: China’s Practices in Rural Transformation and Farmers’ Income Growth
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Deshuo Zhang, Qingning Lin and Shiping Mao
Agriculture 2024, 14(9), 1654; https://doi.org/10.3390/agriculture14091654 (registering DOI) - 22 Sep 2024
Abstract
In the context of global rural decline, fostering endogenous momentum through rural transformation to increase farmers’ incomes is a challenge that nations worldwide must address. This study utilizes the 2022 “China Rural Micro-Economic Data” to construct a multidimensional rural transformation index system at
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In the context of global rural decline, fostering endogenous momentum through rural transformation to increase farmers’ incomes is a challenge that nations worldwide must address. This study utilizes the 2022 “China Rural Micro-Economic Data” to construct a multidimensional rural transformation index system at the village level, encompassing demographic, land, industrial, social, digital, and ecological transformations. This study evaluates the levels of rural transformation across 15 surveyed provinces in China. Furthermore, it empirically examines the impact of rural transformation on farmers’ incomes, the underlying mechanisms, and the heterogeneity of different transformation models. The findings are as follows: (1) Coastal economically developed regions exhibit higher levels of rural transformation, while inland agricultural provinces show significant lag; (2) Rural transformation effectively promotes the upgrading of agricultural value chains, increases farmers’ market participation, and enhances their access to financial services, thereby boosting farmers’ incomes; and (3) The impact of different transformation models on farmers’ incomes varies significantly; industrial, social, and demographic transformations contribute most prominently to income growth. While digital transformation shows some positive effects, it remains relatively limited. Land and ecological transformations have yet to demonstrate a significant positive impact on farmers’ incomes.
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(This article belongs to the Section Agricultural Economics, Policies and Rural Management)
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Open AccessArticle
Rapid Lactic Acid Content Detection in Secondary Fermentation of Maize Silage Using Colorimetric Sensor Array Combined with Hyperspectral Imaging
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Xiaoyu Xue, Haiqing Tian, Kai Zhao, Yang Yu, Ziqing Xiao, Chunxiang Zhuo and Jianying Sun
Agriculture 2024, 14(9), 1653; https://doi.org/10.3390/agriculture14091653 (registering DOI) - 22 Sep 2024
Abstract
Lactic acid content is a crucial indicator for evaluating maize silage quality, and its accurate detection is essential for ensuring product quality. In this study, a quantitative prediction model for the change of lactic acid content during the secondary fermentation of maize silage
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Lactic acid content is a crucial indicator for evaluating maize silage quality, and its accurate detection is essential for ensuring product quality. In this study, a quantitative prediction model for the change of lactic acid content during the secondary fermentation of maize silage was constructed based on a colorimetric sensor array (CSA) combined with hyperspectral imaging. Volatile odor information from maize silage samples with different days of aerobic exposure was obtained using CSA and recorded by a hyperspectral imaging (HSI) system. Subsequently, the acquired spectral data were subjected to preprocessing through five distinct methods before being modeled using partial least squares regression (PLSR). The coronavirus herd immunity optimizer (CHIO) algorithm was introduced to screen three color-sensitive dyes that are more sensitive to changes in lactic acid content of maize silage. To minimize model redundancy, three algorithms, such as competitive adaptive reweighted sampling (CARS), were used to extract the characteristic wavelengths of the three dyes, and the combination of the characteristic wavelengths obtained by each algorithm was used as an input variable to build an analytical model for quantitative prediction of the lactic acid content by support vector regression (SVR). Moreover, two optimization algorithms, namely grid search (GS) and crested porcupine optimizer (CPO), were compared to determine their effectiveness in optimizing the parameters of the SVR model. The results showed that the prediction accuracy of the model can be significantly improved by choosing appropriate pretreatment methods for different color-sensitive dyes. The CARS-CPO-SVR model had better prediction, with a prediction set determination coefficient ( ), root mean square error of prediction (RMSEP), and a ratio of performance to deviation (RPD) of 0.9617, 2.0057, and 5.1997, respectively. These comprehensive findings confirm the viability of integrating CSA with hyperspectral imaging to accurately quantify the lactic acid content in silage, providing a scientific and novel method for maize silage quality testing.
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(This article belongs to the Section Digital Agriculture)
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Open AccessArticle
Combined Genome-Wide Association Studies (GWAS) and Linkage Mapping Identifies Genomic Regions Associated with Seedling Root System Architecture (RSA) under Different Nitrogen Conditions in Wheat (Triticum aestivum L.)
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Yulin Jia, Ninglu Xu, Jun Zhang, Kaiming Ren, Jinzhi Wu, Chunping Wang, Ming Huang and Youjun Li
Agriculture 2024, 14(9), 1652; https://doi.org/10.3390/agriculture14091652 (registering DOI) - 21 Sep 2024
Abstract
The nitrogen (N) use efficiency (NUE) in the roots of seedlings is beneficial for increasing crop yield. Creating marker-assisted selection for wheat root traits can assist wheat breeders in choosing robust roots to maximize nutrient uptake. Exploring and identifying the effect of different
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The nitrogen (N) use efficiency (NUE) in the roots of seedlings is beneficial for increasing crop yield. Creating marker-assisted selection for wheat root traits can assist wheat breeders in choosing robust roots to maximize nutrient uptake. Exploring and identifying the effect of different N supply conditions on root system architecture (RSA) is of great significance for breeding N efficient wheat varieties. In this study, a total of 243 wheat varieties native to the Yellow and Huai Valley regions of China were utilized for genome-wide association studies (GWAS). Furthermore, a recombinant inbred line (RIL) population of 123 lines derived from the cross between Avocet and Chilero was utilized for linkage examination. A hydroponic seedling experiment using a 96-well tray was conducted in the lab with two treatments: normal N (NN) and low N (LN). Five RSA traits, including the relative number of root tips (RNRT), relative total root length (RTRL), relative total root surface area (RTRS), relative total root volume (RTRV), and relative average root diameter (RARD), were investigated. GWAS and linkage analysis were performed by integrating data from the wheat 660 k single nucleotide polymorphism (SNP) chip and diversity arrays technology (DArT) to identify genetic loci associated with RSA. The results showed that, based on the ratio of RSA-related traits under two N supply conditions, a total of 497 SNP markers, which are significantly associated with RSA-related traits, were detected at 148 genetic loci by GWAS. A total of 10 QTL loci related to RSA were discovered and identified by linkage mapping. Combining two gene localization methods, three colocalized intervals were found: AX-95160997/QRtrl.haust-3D, AX-109592379/QRnrt.haust-5A, and AX-110924288/QRtrl.haust-7D/QRtrs.haust-7D. According to the physical location of the colocalization of these two sites, between 39.61 and 43.74 Mb, 649.97 and 661.55 Mb, and 592.44 and 605.36 Mb are called qRtrl-3D, qRnrt-5A, and qRtrl-7D. This study has the potential to enhance the effectiveness of selecting root traits in wheat breeding programs, offering valuable insights into the genetic underpinnings of NUE in wheat. These results could help in breeding wheat varieties with higher NUE by implementing focused breeding strategies.
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(This article belongs to the Section Crop Genetics, Genomics and Breeding)
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Open AccessArticle
Bud-YOLO: A Real-Time Accurate Detection Method of Cotton Top Buds in Cotton Fields
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Xuening Zhang and Liping Chen
Agriculture 2024, 14(9), 1651; https://doi.org/10.3390/agriculture14091651 (registering DOI) - 21 Sep 2024
Abstract
Cotton topping plays a crucial and indispensable role in controlling excessive growth and enhancing cotton production. This study aims to improve the operational efficiency and accuracy of cotton topping robots through a real-time and accurate cotton top bud detection algorithm tailored for field
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Cotton topping plays a crucial and indispensable role in controlling excessive growth and enhancing cotton production. This study aims to improve the operational efficiency and accuracy of cotton topping robots through a real-time and accurate cotton top bud detection algorithm tailored for field operation scenarios. We propose a lightweight structure based on YOLOv8n, replacing the C2f module with the Cross-Stage Partial Networks and Partial Convolution (CSPPC) module to minimize redundant computations and memory access. The network’s neck employs an Efficient Reparameterized Generalized-FPN (Efficient RepGFPN) to achieve high-precision detection without substantially increasing computational cost. Additionally, the loss calculation of the optimized prediction frame was addressed with the Inner CIoU loss function, thereby enhancing the precision of the model’s prediction box. Comparison experiments indicate that the Bud-YOLO model is highly effective for detecting cotton top buds, with an AP50 of 99.2%. This performance surpasses that of other YOLO variants, such as YOLOv5s and YOLOv10n, as well as the conventional Faster R-CNN model. Moreover, the Bud-YOLO model exhibits robust performance across various angles, occlusion conditions, and bud morphologies. This study offers technical insights to support the migration and deployment of the model on cotton topping machinery.
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(This article belongs to the Section Digital Agriculture)
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Open AccessArticle
Farmers’ Adoption of Agricultural Nature-Based Solutions in Northeast China: An Extended Theory of Planned Behavior Approach
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Minglong Zhang, Yanfang Huang, Yunzheng Zhang, Fengying Nie and Xiangping Jia
Agriculture 2024, 14(9), 1650; https://doi.org/10.3390/agriculture14091650 (registering DOI) - 20 Sep 2024
Abstract
The academic field has limited studies on implementing nature-based solutions (NbSs) in Chinese agriculture, especially regarding households’ and farmers’ attitudes toward the acceptance of agricultural NbS technologies. Based on this, this study aims to fill this knowledge gap by examining the factors behind
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The academic field has limited studies on implementing nature-based solutions (NbSs) in Chinese agriculture, especially regarding households’ and farmers’ attitudes toward the acceptance of agricultural NbS technologies. Based on this, this study aims to fill this knowledge gap by examining the factors behind farmers’ agricultural practices of NbS adoption in Northeast China. Accordingly, this paper constructs an extended theoretical framework of planned behavior (TPB) and empirically tests it using partial least squares structural equation modeling (PLS-SEM) on data from 298 farmers in Inner Mongolia. It was found that incorporating institutional trust (IT) into TPB improves the prediction of Chinese farmers’ intention to de-farm behavior. Unlike previous studies, this study identified two indirect pathways influencing farmers’ intention to adopt agricultural NbS technologies: from institutional trust through attitude to intention, and from institutional trust through perceived behavioral control to intention. The findings broaden the research perspective in this area, provide empirical evidence for the application of NbSs in agricultural practices in China and other developing countries, and demonstrate in practice that NbS has been promoted as an essential tool to maximize nature’s ability to provide ecosystem services and create direct economic benefits for farmers through increased yields and reduced costs.
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(This article belongs to the Special Issue Feature Papers in the Fields of Agricultural Economics, Policies and/or Rural Management)
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Open AccessArticle
Vegetation Phenology Changes and Recovery after an Extreme Rainfall Event: A Case Study in Henan Province, China
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Yinghao Lin, Xiaoyu Guo, Yang Liu, Liming Zhou, Yadi Wang, Qiang Ge and Yuye Wang
Agriculture 2024, 14(9), 1649; https://doi.org/10.3390/agriculture14091649 (registering DOI) - 20 Sep 2024
Abstract
Extreme rainfall can severely affect all vegetation types, significantly impacting crop yield and quality. This study aimed to assess the response and recovery of vegetation phenology to an extreme rainfall event (with total weekly rainfall exceeding 500 mm in several cities) in Henan
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Extreme rainfall can severely affect all vegetation types, significantly impacting crop yield and quality. This study aimed to assess the response and recovery of vegetation phenology to an extreme rainfall event (with total weekly rainfall exceeding 500 mm in several cities) in Henan Province, China, in 2021. The analysis utilized multi-sourced data, including remote sensing reflectance, meteorological, and crop yield data. First, the Normalized Difference Vegetation Index (NDVI) time series was calculated from reflectance data on the Google Earth Engine (GEE) platform. Next, the ‘phenofit’ R language package was used to extract the phenology parameters—the start of the growing season (SOS) and the end of the growing season (EOS). Finally, the Statistical Package for the Social Sciences (SPSS, v.26.0.0.0) software was used for Duncan’s analysis, and Matrix Laboratory (MATLAB, v.R2022b) software was used to analyze the effects of rainfall on land surface phenology (LSP) and crop yield. The results showed the following. (1) The extreme rainfall event’s impact on phenology manifested directly as a delay in EOS in the year of the event. In 2021, the EOS of the second growing season was delayed by 4.97 days for cropland, 15.54 days for forest, 13.06 days for grassland, and 12.49 days for shrubland. (2) Resistance was weak in 2021, but recovery reached in most areas by 2022 and slowed in 2023. (3) In each year, SOS was predominantly negatively correlated with total rainfall in July (64% of cropland area in the first growing season, 53% of grassland area, and 71% of shrubland area). In contrast, the EOS was predominantly positively correlated with rainfall (51% and 54% area of cropland in the first and second growing season, respectively, and 76% of shrubland area); however, crop yields were mainly negatively correlated with rainfall (71% for corn, 60% for beans) and decreased during the year of the event, with negative correlation coefficients between rainfall and yield (−0.02 for corn, −0.25 for beans). This work highlights the sensitivity of crops to extreme rainfall and underscores the need for further research on their long-term recovery.
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(This article belongs to the Special Issue Novel Applications of Optical Sensors and Machine Learning in Agricultural Monitoring—2nd Edition)
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Reducing Grain Damage in Moist Corn Threshing via Corncob Division
by
Gang Wang, Chengqian Jin, Min Zhang, Chongyou Wu, Qing Tang and Yao Yang
Agriculture 2024, 14(9), 1648; https://doi.org/10.3390/agriculture14091648 (registering DOI) - 20 Sep 2024
Abstract
For the prompt planting of subsequent crops, most of China’s corn harvest must occur before full maturity, with a grain moisture content above 25%. Harvesting moist corn presents challenges due to significant grain damage during threshing. We conducted a high-speed photography observation test
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For the prompt planting of subsequent crops, most of China’s corn harvest must occur before full maturity, with a grain moisture content above 25%. Harvesting moist corn presents challenges due to significant grain damage during threshing. We conducted a high-speed photography observation test of moist corn threshing. It demonstrated that corn ears, when passing through the threshing cylinder, often break into pieces. Grains on divided corncobs can be threshed more easily and earlier than those on undivided ones, suggesting that pre-dividing corn ears reduces grain damage. An experiment using the Lianchuang 825 variety examined the effect of moisture content and the divided rate of corncobs (DRC) on grain damage. The results showed that as moisture content increased from 25% to 37%, grain damage to undivided ears increased from 3.75% to 37.71%. Dividing corn ears before threshing significantly reduced damage, with an eight-piece division reducing damage by approximately 70% across all moisture levels. Verification with the Jinyu 1233 variety confirmed that a higher DRC consistently reduced damage. This study provides a new approach to reducing damage in moist corn threshing and aids in the development of low-damage threshing devices.
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(This article belongs to the Special Issue Innovative Design and Application of Modern Agricultural Machinery Systems in Cropping Systems)
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Reproductive Structures of Female Phytoseiulus persimilis (Acari: Phytoseiidae) and the Development of Egg and Embryo in the Body
by
Binting Huang, Mingxia Li, Xiaohuan Jiang, Bo Zhang, Yong Huang and Xuenong Xu
Agriculture 2024, 14(9), 1647; https://doi.org/10.3390/agriculture14091647 (registering DOI) - 20 Sep 2024
Abstract
The Phytoseiulus persimilis specialized in preying on Tetranychus species, with particularly strong predation capability against Tetranychus urticae. To investigate the morphology of female reproductive structures and effects of different gravid times on structures of oocytes and embryos in Phytoseiulus persimilis, we
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The Phytoseiulus persimilis specialized in preying on Tetranychus species, with particularly strong predation capability against Tetranychus urticae. To investigate the morphology of female reproductive structures and effects of different gravid times on structures of oocytes and embryos in Phytoseiulus persimilis, we employed paraffin sectioning, transmission electron microscopy (TEM), and scanning electron microscopy (SEM) on the model species of predatory mite Phytoseiulus persimilis. The female adult possessed several reproductive organs, including paired solenostomes, major ducts, embolus, calyces, and vesicles within the sperm-access system, as well as lyrate organ and the ovary. Furthermore, the reproductive system also encompassed the uterus, vagina, and genital pore, which were involved in egg development and expulsion. The solenostomes were situated between the third and fourth legs, and they were scarcely discernible in virgin, but they became apparent during mating. The occurrence of mating significantly influenced the nucleus of lyrate organ. In virgin, the nucleus exhibited underdeveloped morphology, whereas in mated individuals, it was well-formed. However, the duration of mating did not impact its development. The cellular structure of the ovary was solely associated with the stage of the surrounding oocyte and was not directly linked to mating occurrences. The uterus was barely visible outside of mating periods but became observable 12 h after mating when eggs were present within the body. At this point, it opened in preparation for egg laying when both the vagina and reproductive opening were open. Positioned in front of the vesicle but behind the ovary was the lyrate organ, with its lower part housing the uterus. The vagina was connected to the genital pore. No significant difference was observed in oocyte morphology between the virgin ovaries and the mated. Oocyte development occurred through four stages: during stage I (4–9 h after mating), yolk accumulation took place; stage II (10 h after mating) involved egg relocation; stage III (12–13 h after mating) was marked by eggshell formation; finally, at stage IV (14–16 h after mating), embryonic development commenced, leading to egg deposition. The fusion of sperm and egg occurred approximately 9–10 h after mating. These findings established a solid foundation for investigating the Phytoseiid reproductive mechanisms.
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(This article belongs to the Special Issue Comprehensive Application and Prospects of New Technologies for Plant Protection)
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A High-Accuracy Contour Segmentation and Reconstruction of a Dense Cluster of Mushrooms Based on Improved SOLOv2
by
Shuzhen Yang, Jingmin Zhang and Jin Yuan
Agriculture 2024, 14(9), 1646; https://doi.org/10.3390/agriculture14091646 (registering DOI) - 20 Sep 2024
Abstract
This study addresses challenges related to imprecise edge segmentation and low center point accuracy, particularly when mushrooms are heavily occluded or deformed within dense clusters. A high-precision mushroom contour segmentation algorithm is proposed that builds upon the improved SOLOv2, along with a contour
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This study addresses challenges related to imprecise edge segmentation and low center point accuracy, particularly when mushrooms are heavily occluded or deformed within dense clusters. A high-precision mushroom contour segmentation algorithm is proposed that builds upon the improved SOLOv2, along with a contour reconstruction method using instance segmentation masks. The enhanced segmentation algorithm, PR-SOLOv2, incorporates the PointRend module during the up-sampling stage, introducing fine features and enhancing segmentation details. This addresses the difficulty of accurately segmenting densely overlapping mushrooms. Furthermore, a contour reconstruction method based on the PR-SOLOv2 instance segmentation mask is presented. This approach accurately segments mushrooms, extracts individual mushroom masks and their contour data, and classifies reconstruction contours based on average curvature and length. Regular contours are fitted using least-squares ellipses, while irregular ones are reconstructed by extracting the longest sub-contour from the original irregular contour based on its corners. Experimental results demonstrate strong generalization and superior performance in contour segmentation and reconstruction, particularly for densely clustered mushrooms in complex environments. The proposed approach achieves a 93.04% segmentation accuracy and a 98.13% successful segmentation rate, surpassing Mask RCNN and YOLACT by approximately 10%. The center point positioning accuracy of mushrooms is 0.3%. This method better meets the high positioning requirements for efficient and non-destructive picking of densely clustered mushrooms.
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(This article belongs to the Special Issue Intelligent Agricultural Machinery and Robots: Embracing Technological Advancements for a Sustainable and Highly Efficient Agricultural Future)
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Design and Experimentation of Targeted Deep Fertilization Device for Corn Cultivation
by
Zhongying Qi, Cunliang Liu, Yao Wang, Zhiwei Zhang and Xiaobo Sun
Agriculture 2024, 14(9), 1645; https://doi.org/10.3390/agriculture14091645 - 20 Sep 2024
Abstract
In response to the challenges of low fertilizer utilization rates, excessive application amounts, and difficulties in precise targeted fertilization during the middle tillage and top-dressing period for corn, a targeted deep fertilization device is designed, integrating mechanical structure design and automatic control technology.
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In response to the challenges of low fertilizer utilization rates, excessive application amounts, and difficulties in precise targeted fertilization during the middle tillage and top-dressing period for corn, a targeted deep fertilization device is designed, integrating mechanical structure design and automatic control technology. The device mainly includes a strong discharge fertilization device and a targeted fertilization control system. The fertilization device has been designed, and the main factors affecting the performance of the fertilization wheel have been identified. Based on the structure, a strong discharge fertilization plate mechanism has been added, and a mechanical model for the fertilization wheel during the refilling and discharging processes has been constructed. A targeted fertilization control system for corn has been developed that utilizes a photoelectric sensor to detect the position of the corn plants. A microcontroller combines the plant position information and the device moving speed to adjust the intermittent rotation of the stepper motor in real time, achieving targeted deep fertilization for corn. Coupled simulation analysis was conducted using discrete element software EDEM and dynamic software Adams. Through single-factor and multi-factor experiments, the main factors affecting fertilization performance were analyzed, and the optimal structural parameters for the fertilization wheel were determined. Bench validation tests were conducted, and the results demonstrated that under forward speeds of 0.4 to 1.2 m/s, the coefficient of variation of the fertilizer application rate per hole of the discharge device ranged from 2.02% to 4.46%, the error in fertilizer application rate per hole ranged from 7.12% to 12.18%, the average length of fertilizer application holes ranged from 72.5 mm to 130.2 mm, and the coefficient of variation of hole length stability ranged from 1.94% to 3.54%. These parameters were consistent with the results from the simulation tests, and the operational performance met the requirements. Finally, field tests validated the overall operational performance of the device. When the device’s speed ranged from 0.4 m/s to 1.2 m/s, the coefficient of variation of the fertilizer application rate per hole, the error in fertilizer application rate per hole, the average length of fertilizer application holes, the coefficient of variation of hole length stability, and the qualification rate of fertilization position were 3.63%, 10.46%, 108.8 mm, 2.96%, and 87.16%, respectively. The overall performance of the device is stable and meets the requirements for targeted deep fertilization in corn cultivation.
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(This article belongs to the Section Agricultural Technology)
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Study on the Contact Parameter Calibration of the Maize Kernel Polyhedral Discrete Element Model
by
Huhu Chen, Haipeng Lin, Xuefeng Song, Fengwei Zhang, Fei Dai, Ting Yang and Baicheng Li
Agriculture 2024, 14(9), 1644; https://doi.org/10.3390/agriculture14091644 - 19 Sep 2024
Abstract
During maize production and transportation, maize kernels frequently interact with mechanical components. To accurately simulate the interaction process between maize and mechanical components, it is essential to establish a reliable maize kernel model and input precise contact parameters. This study established polyhedral discrete
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During maize production and transportation, maize kernels frequently interact with mechanical components. To accurately simulate the interaction process between maize and mechanical components, it is essential to establish a reliable maize kernel model and input precise contact parameters. This study established polyhedral discrete element models of different maize kernels and calibrated the contact parameters between maize kernels and steel plates using the inclined plane method. The coefficients of restitution, static friction, and dynamic friction between maize and steel sheets were measured to be 0.5, 0.545, and 0.213, respectively. Subsequently, the contact parameters between maize kernels were determined through steepest climb tests and central composite design response surface tests. Then, the above parameters were optimized using Design-Expert software. The coefficients of restitution, static friction, and dynamic friction between maize kernels were measured to be 0.318, 0.182, and 0.232, respectively. Finally, the optimized parameters were validated using the angle of repose experiment, which found that the relative error between the experiment and the simulation was only 1.24%. The results indicated that the obtained contact parameters were accurate and reliable.
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(This article belongs to the Section Agricultural Technology)
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