Agriculture

19 pages, 28399 KiB

Open AccessArticle

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 - 23 Sep 2024

Viewed by 1116

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 [...] Read more.

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. Full article

(This article belongs to the Section Crop Production)

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5 pages, 147 KiB

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 - 23 Sep 2024

Viewed by 778

Abstract

The mechanization of agricultural work has contributed significantly to the improvement of agricultural productivity and reduced production costs [...] Full article

(This article belongs to the Special Issue Soil Mechanical Systems and Related Farming Machinery)

23 pages, 7137 KiB

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 - 23 Sep 2024

Cited by 1 | Viewed by 2051

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 [...] Read more.

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. Full article

(This article belongs to the Special Issue Feature Review in Agricultural Soils—Intensification of Soil Health)

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16 pages, 5488 KiB

Open AccessArticle

Long-Term Minimum Tillage and Straw Retention Promote Macroaggregate Formation, Carbon and Nitrogen Sequestration under Wheat-Maize Rotation in Northern China

by 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 - 22 Sep 2024

Viewed by 1151

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), [...] Read more.

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. Full article

(This article belongs to the Section Agricultural Soils)

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20 pages, 5659 KiB

Open AccessArticle

Research on the Energy Management Strategy of a Hybrid Tractor OS-ECVT Based on a Dynamic Programming Algorithm

by Kai Zhang, Xiaoting Deng, Zhixiong Lu and Tao Wang

Agriculture 2024, 14(9), 1658; https://doi.org/10.3390/agriculture14091658 - 22 Sep 2024

Viewed by 749

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 [...] Read more.

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. Full article

(This article belongs to the Special Issue From Planting to Harvesting: The Role of Agricultural Machinery in Crop Cultivation)

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16 pages, 1959 KiB

Open AccessArticle

Sarcocornia fruticosa, a Potential Candidate for Saline Agriculture: Antioxidant Levels in Relation to Environmental Conditions in the Eastern Iberian Peninsula

by 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 - 22 Sep 2024

Viewed by 883

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 [...] Read more.

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. Full article

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

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17 pages, 945 KiB

Open AccessArticle

Assessing Economic Viability of Resilient Sheep Foraging Alternatives in Lowland Regions of Romania

by Rodica Chetroiu, Steliana Rodino, Vili Dragomir, Diana Maria Ilie and Ancuța Marin

Agriculture 2024, 14(9), 1656; https://doi.org/10.3390/agriculture14091656 - 22 Sep 2024

Viewed by 867

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. [...] Read more.

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. Full article

(This article belongs to the Special Issue Sustainable Rural Development and Agri-Food Systems—2nd Edition)

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19 pages, 5919 KiB

Open AccessArticle

Real-Time ConvNext-Based U-Net with Feature Infusion for Egg Microcrack Detection

by 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 - 22 Sep 2024

Viewed by 863

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 [...] Read more.

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

μ

m and a Crack-IoU and MIoU of 60.76% and 80.22%, respectively, for even smaller cracks (less than 5

μ

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. Full article

(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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18 pages, 1378 KiB

Open AccessArticle

Addressing Rural Decline: China’s Practices in Rural Transformation and Farmers’ Income Growth

by Deshuo Zhang, Qingning Lin and Shiping Mao

Agriculture 2024, 14(9), 1654; https://doi.org/10.3390/agriculture14091654 - 22 Sep 2024

Viewed by 1292

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 [...] Read more.

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. Full article

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

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19 pages, 6483 KiB

Open AccessArticle

Rapid Lactic Acid Content Detection in Secondary Fermentation of Maize Silage Using Colorimetric Sensor Array Combined with Hyperspectral Imaging

by 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 - 22 Sep 2024

Viewed by 736

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 [...] Read more.

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 (

R_{P}^{2}

), 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. Full article

(This article belongs to the Section Digital Agriculture)

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16 pages, 4313 KiB

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.)

by 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 - 21 Sep 2024

Viewed by 734

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 [...] Read more.

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. Full article

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

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17 pages, 7845 KiB

Open AccessArticle

Bud-YOLO: A Real-Time Accurate Detection Method of Cotton Top Buds in Cotton Fields

by Xuening Zhang and Liping Chen

Agriculture 2024, 14(9), 1651; https://doi.org/10.3390/agriculture14091651 - 21 Sep 2024

Viewed by 834

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 [...] Read more.

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. Full article

(This article belongs to the Section Digital Agriculture)

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20 pages, 4776 KiB

Open AccessArticle

Farmers’ Adoption of Agricultural Nature-Based Solutions in Northeast China: An Extended Theory of Planned Behavior Approach

by Minglong Zhang, Yanfang Huang, Yunzheng Zhang, Fengying Nie and Xiangping Jia

Agriculture 2024, 14(9), 1650; https://doi.org/10.3390/agriculture14091650 - 20 Sep 2024

Viewed by 779

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 [...] Read more.

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. Full article

(This article belongs to the Special Issue Feature Papers in the Fields of Agricultural Economics, Policies and/or Rural Management)

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19 pages, 6791 KiB

Open AccessArticle

Vegetation Phenology Changes and Recovery after an Extreme Rainfall Event: A Case Study in Henan Province, China

by 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 - 20 Sep 2024

Viewed by 486

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 [...] Read more.

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. Full article

(This article belongs to the Special Issue Novel Applications of Optical Sensors and Machine Learning in Agricultural Monitoring—2nd Edition)

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14 pages, 2043 KiB

Open AccessArticle

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 - 20 Sep 2024

Viewed by 500

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 [...] Read more.

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. Full article

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

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24 pages, 12131 KiB

Open AccessArticle

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 - 20 Sep 2024

Viewed by 710

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 [...] Read more.

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. Full article

(This article belongs to the Special Issue Comprehensive Application and Prospects of New Technologies for Plant Protection)

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25 pages, 9183 KiB

Open AccessArticle

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 - 20 Sep 2024

Viewed by 696

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 [...] Read more.

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. Full article

(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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22 pages, 6605 KiB

Open AccessArticle

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

Viewed by 531

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. [...] Read more.

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. Full article

(This article belongs to the Section Agricultural Technology)

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15 pages, 5302 KiB

Open AccessArticle

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

Viewed by 754

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 [...] Read more.

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. Full article

(This article belongs to the Section Agricultural Technology)

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14 pages, 7196 KiB

Open AccessArticle

Identification of Ascorbate Oxidase Genes and Their Response to Cold Stress in Citrus sinensis

by Xiaoyong Xu, Xingchen Miao, Naiyi Deng, Mengge Liang, Lun Wang, Lijuan Jiang and Shaohua Zeng

Agriculture 2024, 14(9), 1643; https://doi.org/10.3390/agriculture14091643 - 19 Sep 2024

Viewed by 603

Abstract

Ascorbate oxidase (AAO) plays an important role in maintaining cellular redox homeostasis, thereby influencing plant growth, development, and responses to both biotic and abiotic stresses. However, there has been no systematic characterization of AAO genes in Citrus, especially their roles in response [...] Read more.

Ascorbate oxidase (AAO) plays an important role in maintaining cellular redox homeostasis, thereby influencing plant growth, development, and responses to both biotic and abiotic stresses. However, there has been no systematic characterization of AAO genes in Citrus, especially their roles in response to cold stress. In the present study, nine AAO genes were identified in C. sinensis through bioinformatics analyses, exhibiting uneven distribution across four chromosomes. All CsAAOs possessed three conserved domains and were predicted to localize in the apoplast. The CsAAO gene family displayed varied intron–exon patterns. Phylogenetic analysis categorized the CsAAO family into three main clades (Clade A–C), suggesting distinct biological functions. Collinearity and Ka/Ks analysis revealed three duplicate gene pairs within the CsAAO gene family, with all duplicated CsAAOs primarily evolving under purifying selection. Analysis of cis-acting elements showed the presence of multiple hormone response elements and stress response elements within the CsAAO promoters. The computational analysis of microRNA target transcripts suggested that CsAAO9 may be a target of csi-miR156. RNA-Seq data demonstrated high expression levels of CsAAOs in roots and young fruits, while qRT-PCR analysis showed significant upregulation of six CsAAOs in response to cold treatment. Furthermore, the activities of CsAAOs exhibited a pattern of initial decrease followed by an increase after exposure to low temperatures. These findings offer important insights into the role of CsAAOs in response to cold stress. Furthermore, AAOs could be target genes for breeding crops with better cold resistance. Full article

(This article belongs to the Special Issue Abiotic Stress Responses in Horticultural Crops)

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17 pages, 5564 KiB

Open AccessArticle

Modeling for Apple-Slice Drying in Carbon Dioxide Gas

by Tien Cong Do, Quoc Tuan Le and Thi Thu Hang Tran

Agriculture 2024, 14(9), 1642; https://doi.org/10.3390/agriculture14091642 - 19 Sep 2024

Viewed by 674

Abstract

In this study, a numerical model of a modified air-drying process of apple slices that considers the conjugate heat and mass transfer in the drying chamber is developed. Inside the apple slice sample, the continuum model is incorporated to describe the non-isothermal two-phase [...] Read more.

In this study, a numerical model of a modified air-drying process of apple slices that considers the conjugate heat and mass transfer in the drying chamber is developed. Inside the apple slice sample, the continuum model is incorporated to describe the non-isothermal two-phase transport. The intra- and extra-sample heat, mass, and momentum transfer are coupled to simulate the transportation phenomena inside the drying chamber using the finite volume method implemented in computational fluid dynamic software (COMSOL Multiphysics 6.0). In this manner, temperature, velocity, moisture content of the drying agent inside the chamber, sample temperature, and moisture content distributions can be predicted. The validity of the proposed model is confirmed by a good agreement between the numerical and experimental data in terms of the overall evaporation rate and temperature. The simulation results indicate that the maldistribution of the convective heat and mass transfer resistance on the sample surface is significant. This can be explained by the nonuniform velocity distribution inside the drying chamber. Additionally, both experimental and numerical observations show that the drying process can be divided into two periods: the quasi-constant drying rate and falling drying rate periods. The impact of dryer operational conditions on the drying process is numerically investigated. Full article

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

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16 pages, 6522 KiB

Open AccessArticle

Experiment and Analysis of Physical Properties of Sweet Potato Varieties at Different Harvesting Periods

by Jiwen Peng, Haiyang Shen, Gongpu Wang, Zhilong Zhang, Baoliang Peng, Guangyu Xue, Sen Huang, Wenhao Zheng and Lianglong Hu

Agriculture 2024, 14(9), 1641; https://doi.org/10.3390/agriculture14091641 - 19 Sep 2024

Viewed by 693

Abstract

To fill the research gap in the mechanical and physical properties of different varieties of sweet potatoes at different points in the harvest period and to provide a theoretical basis for the design of key components of the sweet potato harvester, the physical [...] Read more.

To fill the research gap in the mechanical and physical properties of different varieties of sweet potatoes at different points in the harvest period and to provide a theoretical basis for the design of key components of the sweet potato harvester, the physical properties of Su-Shu 16, Su-Shu 36, and Ning-Zi 4 during the harvest period were studied at three time points: 15 October, 25 October, and 4 November 2023. The moisture content of sweet potatoes was determined using the DGF30/7-IA electric hot air-drying oven. The results showed that the moisture content of sweet potatoes decreased with increasing growth time at three different time points during the harvest period. The moisture content of Su-Shu 16 was, on average, 12.74% higher than that of Su-Shu 36, while the moisture content of Ning-Zi 4 was, on average, 8.07% higher than that of Su-Shu 36. The density of Su-Shu 36 measured by the drainage method is greater than that of Su-Shu 16 and Ning-Zi 4, but the difference is relatively small, and the density tends to decrease slowly with the increase of growth time. Using an electronic universal testing machine, compression tests were conducted on Su-Shu 16, Su-Shu 36, and Ning-Zi 4 at loading speeds of 5 mm/min and 10 mm/min, respectively. The results showed that the compressive strength limit range of Su-Shu 36 was slightly higher than that of Su-Shu 16 and significantly higher than that of Ning-Zi 4. The Poisson’s ratio, elastic modulus, and shear modulus values of Su-Shu 16 and Su-Shu 36 were similar and much higher than those of Ning-Zi 4. Studying sweet potatoes’ growth and physical characteristics for different purposes can provide data references for the design of digging depth, working width, and conveyor chain gap of sweet potato harvesters, as well as data references for sweet potato simulation experiments. Full article

(This article belongs to the Special Issue From Planting to Harvesting: The Role of Agricultural Machinery in Crop Cultivation)

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19 pages, 13127 KiB

Open AccessArticle

Optimization of the Camellia oleifera Fruit Harvester Engine Compartment Heat Dissipation Based on Temperature Experiments and Airflow Field Simulation

by Wenfu Tong, Kai Liao, Lijun Li, Zicheng Gao, Fei Chen and Hong Luo

Agriculture 2024, 14(9), 1640; https://doi.org/10.3390/agriculture14091640 - 19 Sep 2024

Viewed by 696

Abstract

The Camellia oleifera fruit harvester, a specialized agricultural device, is engineered for efficient operation within the densely planted C. oleifera groves of China’s undulating terrains. Its design features a notably small footprint to navigate the constrained spaces between trees. With the enhancement of [...] Read more.

The Camellia oleifera fruit harvester, a specialized agricultural device, is engineered for efficient operation within the densely planted C. oleifera groves of China’s undulating terrains. Its design features a notably small footprint to navigate the constrained spaces between trees. With the enhancement of the functionality and power of the harvester, the engine compartment becomes even more congested. This, while beneficial for performance, complicates heat dissipation and reduces harvesting efficiency. In this study, experiments were initially conducted to collect temperature data from the main heat-generating components and parts susceptible to high temperatures within the harvester’s engine compartment. Subsequently, a 3D model was developed for numerical simulations, leading to the proposal of optimization schemes for the engine compartment’s structure and the validation of these schemes’ feasibility. A comparison of the experimental data, both before and after optimization, revealed a significant reduction in the surface temperatures of components within the engine compartment following optimization. As a result, the heat dissipation of the engine compartment has been greatly optimized. The harvester has demonstrated prolonged normal operation, enhancing the reliability and economy of the harvester. Full article

(This article belongs to the Special Issue Agricultural Machinery and Technology for Fruit Tree Management)

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18 pages, 20690 KiB

Open AccessArticle

Halving Environmental Impacts of Diverse Crop Production in Fujian, China through Optimized Nitrogen Management

by Jun Li, Minglei Wang, Wenjiao Shi and Xiaoli Shi

Agriculture 2024, 14(9), 1639; https://doi.org/10.3390/agriculture14091639 - 19 Sep 2024

Viewed by 832

Abstract

Nitrogen (N) fertilizer is essential for agricultural production as it is the main nutrient driving crop growth. However, in China, only one-third of applied N fertilizer is effectively absorbed by crops, while the rest leads to significant environmental impacts. In this study, we [...] Read more.

Nitrogen (N) fertilizer is essential for agricultural production as it is the main nutrient driving crop growth. However, in China, only one-third of applied N fertilizer is effectively absorbed by crops, while the rest leads to significant environmental impacts. In this study, we introduced a nitrogen threshold boundary (NTB) approach to establish different thresholds for N use efficiency (NUE) and N surplus without affecting crop yield. We also developed an integrated assessment framework to systematically evaluate the potential for improving N utilization and reducing environmental impacts in the production of grain crops (rice, wheat, maize, and soybeans) and cash crops (tea, fruits, and vegetables) at the county level in Fujian Province. Three N management strategies were evaluated: a scenario with reduced N surplus (S1), a scenario with increased NUE (S2), and a combined scenario that simultaneously reduces N surplus and increases NUE (S3). The predictions indicate that, under the aforementioned scenarios, there will be a decrease of 66%, 58%, and 71% in N application without affecting crop yields, respectively. Correspondingly, N surplus will decrease by 65%, 56%, and 67%, while greenhouse gas (GHG) emissions will decrease by 54%, 48%, and 57%. In addition, NUE will increase by 23%, 17% and 25%, respectively. It is notable that scenario S3 demonstrated the greatest potential for improvement. For cash crops, N application will decrease by 65–78%, NUE will increase by 13–21%, N surplus will decrease by 63–74%, and GHG emissions will reduce by 66–78%. In contrast, for grain crops, N application will decrease by 27–38%, NUE will increase by 9–13%, N surplus will decrease by 26–37%, and GHG emissions will reduce by 24–28%. Overall, the potential for improvement is greater for cash crops compared to grain crops. The application of the assessment framework in this study demonstrates its effectiveness as a valuable tool for promoting green and sustainable development in conventional agricultural regions. Full article

(This article belongs to the Section Crop Production)

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30 pages, 1464 KiB

Open AccessReview

Abiotic Stress in Cotton: Insights into Plant Responses and Biotechnological Solutions

by Akshay Milind Patil, Bhausaheb D. Pawar, Sopan Ganpatrao Wagh, Harshraj Shinde, Rahul Mahadev Shelake, Nanasaheb R. Markad, Nandu K. Bhute, Jan Červený and Rajendra. S. Wagh

Agriculture 2024, 14(9), 1638; https://doi.org/10.3390/agriculture14091638 - 19 Sep 2024

Viewed by 2173

Abstract

Climate change has rapidly increased incidences of frequent extreme abiotic stresses, such as heat, drought, salinity, and waterlogging. Each of these stressors negatively affects the cotton crop (Gossypium spp.) and results in significant yield decreases. Every stressful event causes specific changes in [...] Read more.

Climate change has rapidly increased incidences of frequent extreme abiotic stresses, such as heat, drought, salinity, and waterlogging. Each of these stressors negatively affects the cotton crop (Gossypium spp.) and results in significant yield decreases. Every stressful event causes specific changes in the metabolism and physiology of plants, which are linked to complex molecular alterations. Understanding the molecular mechanisms that regulate a plant’s response to stress is essential to developing stress-resistant cotton varieties that can withstand various stress factors. Gene expressions in response to multiple stresses have been studied and mapped. These genes include ion transporters and heat shock proteins, which are vital to allowing adaptive responses. These approaches showed the ability to employ advanced genome sequencing and multi-omics techniques to identify dynamic gene expression patterns and elucidate intricate regulatory networks. Using genetic variation in combination with molecular techniques, it would be possible to generate stress-resilient cotton varieties that would enable sustainable cotton output in the face of abiotic stresses. Here, we reviewed the effects of major abiotic stressors on cotton plants, such as heat, salinity, drought, heavy metals, and waterlogging. We also examine the vast network of proteins, genes, and stress-sensitive signaling pathways that help cotton tolerate abiotic stress. Full article

(This article belongs to the Section Crop Production)

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19 pages, 4009 KiB

Open AccessArticle

Response of Bacterial Community Structure and Function in Rhizosphere Soil on the Photosynthesis of Selected Plant Types C₃ and C₄ under Bis(2,4,6-tribromophenoxy) Ethane Exposure

by Yixuan Chen, Sen Wang, Yuru Li, Wanyu Liu and Zhenchuan Niu

Agriculture 2024, 14(9), 1637; https://doi.org/10.3390/agriculture14091637 - 18 Sep 2024

Viewed by 801

Abstract

This study investigated the response of a bacterial community’s structure and function in the rhizosphere soil of C₃ and C₄ plants under bis(2,4,6-tribromophenoxy) ethane (BTBPE) exposure. The bacterial community composition was determined using 16S rRNA sequencing, while FAPROTAX and PICRUSt 2 [...] Read more.

This study investigated the response of a bacterial community’s structure and function in the rhizosphere soil of C₃ and C₄ plants under bis(2,4,6-tribromophenoxy) ethane (BTBPE) exposure. The bacterial community composition was determined using 16S rRNA sequencing, while FAPROTAX and PICRUSt 2 were employed for functional predictions. Results showed significant differences between C₃ and C₄ plants in terms of bacterial community structure. C₃ plants exhibited higher abundances of Proteobacteria, Bacteroidetes at the phylum level and Sphingomicrobium at the genus level, compared to C₄ plants. Conversely, C₄ plants had higher abundances of Actinobacteria and Patescibacteria at the phylum level and Nocardioides at the genus level. LEfSe and function prediction analyses revealed that the rhizosphere soil bacteria in C₃ plants exhibited significantly higher enrichment in nitrogen fixation functions (p < 0.05), whereas C₄ plants showed a significantly higher relative abundance of bacteria and functions related to organic pollutant degradation (p < 0.05). These findings suggest that the rhizosphere soil bacteria of C₃ plants exhibit a stronger response to BTBPE exposure in nitrogen metabolism-related processes, while C₄ plants possess superior biodegradation ability compared to C₃ plants. Full article

(This article belongs to the Topic Plant-Soil Interactions, 2nd Volume)

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16 pages, 4675 KiB

Open AccessArticle

Coupling Coordination and Spatial–Temporal Evolution of the Water–Land–Ecology System in the North China Plain

by Liang Chen, Xiaogang Wang, Mouchao Lv, Jing Su and Bo Yang

Agriculture 2024, 14(9), 1636; https://doi.org/10.3390/agriculture14091636 - 18 Sep 2024

Viewed by 527

Abstract

Exploring the coordination of agricultural water resources (W), cultivated land (L), and the ecoenvironment (E) system is crucial for sustainable agriculture in the North China Plain (NCP). However, the synergistic effects of this composite system remain unclear. Coupling coordination degrees (CCDs) of 53 [...] Read more.

Exploring the coordination of agricultural water resources (W), cultivated land (L), and the ecoenvironment (E) system is crucial for sustainable agriculture in the North China Plain (NCP). However, the synergistic effects of this composite system remain unclear. Coupling coordination degrees (CCDs) of 53 cities in the NCP for the years 2011, 2015, and 2020 were evaluated using the TOPSIS model, and the coupling coordination model, combined with the analytic hierarchy process and entropy weight method. The evaluation results were further analyzed to identify obstacle factors. The findings reveal the following: (1) The comprehensive development level showed a fluctuating upward trend, with closeness values ranging from 0.418 to 0.574 in 2020, indicating an improvement of 14.6–52.3% compared to 2011. The coefficient of variation (CV) for each province rose from 12.65% in 2011 to 13.64% and subsequently declined to 9.12% by 2020. (2) Between 2011 and 2020, CCDs of the W–L–E composite system exhibited a consistent upward trend. In 2020, regions with intermediate or better coordination accounted for 34.0%, and were primarily located in Jiangsu Province, the southern part of Anhui Province, the northwestern part of Shandong Province, and the municipalities of Beijing and Tianjin. (3) In 2011 and 2015, significant obstacle factors included the water quality compliance rate and the per capita disposable income of rural residents, although these were not primary obstacles in 2020. The water supply modulus and multiple cropping index were major obstacle factors in 2011, 2015, and 2020. Developing water-appropriate cropping patterns based on regional water resource endowment is the essential path for the sustainable and coordinated development of water, land, and ecology in the NCP. Full article

(This article belongs to the Section Agricultural Water Management)

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24 pages, 9931 KiB

Open AccessArticle

Peanut Pickup Combine Harvester Seedling Vines Crushing Mechanism Performance Enhancement and Pilot Studies

by Jinbiao Zhang, Zhuang Zhao, Zenghui Gao, Yu Tian, Dongwei Wang and Nan Xu

Agriculture 2024, 14(9), 1635; https://doi.org/10.3390/agriculture14091635 - 18 Sep 2024

Cited by 1 | Viewed by 476

Abstract

Aiming at the current peanut pickup combine harvester seedling vines crushing mechanism operation qualified seedling length rate is low, the impurity rate is high, and the seedling vines crushing mechanism is optimized design. On the basis of the material characteristics of peanut seedling [...] Read more.

Aiming at the current peanut pickup combine harvester seedling vines crushing mechanism operation qualified seedling length rate is low, the impurity rate is high, and the seedling vines crushing mechanism is optimized design. On the basis of the material characteristics of peanut seedling vines, taking the crushing mechanism as the research carrier, the interaction mechanism of the seedling vine mechanism was analyzed. Establish the mechanical model and motion trajectory model in the crushing process, simulate the peanut seedling vines crushing process based on the discrete element method, analyze the influence of the cutter shaft rotational speed, movement speed, and bending angle on the crushing of peanut seedling vines, and establish the regression model, and the results of the research show that the influence factors in the main order of priority are: knife shaft speed > movement speed > bending angle The optimal parameter combination is knife shaft speed 2171.94 r/min, movement speed 0.79 m/s, and bending angle 45°. According to the field test conditions, it is determined that the knife shaft rotational speed of 2170 r/min, movement speed of 0.8 m/s, and bending angle of 45° can make the peanut seedling vines crushing mechanism of the work performance to achieve a qualified seedling length rate of 97.292%, the rate of impurity content of 2.746%, and the error with the predicted value is less than 2%, which indicates that this study can provide a reference for the optimal design of the seedling vines crushing mechanism of the peanut pickup combine harvester. Full article

(This article belongs to the Section Agricultural Technology)

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16 pages, 8519 KiB

Open AccessArticle

Identification of Hotspot Regions for Candidate Genes Associated with Peanut (Arachis hypogaea L.) Pod and Seed Size on Chromosome A05

by Xiaoji Zhang, Luhuan Wang, Qimei Liu, Xiaoyu Zhang, Yuexia Tian, Yunyun Xue, Huiqi Zhang, Na Li, Xin Zhang and Dongmei Bai

Agriculture 2024, 14(9), 1634; https://doi.org/10.3390/agriculture14091634 - 18 Sep 2024

Viewed by 643

Abstract

The size of peanut pods and seeds, which directly affects yield and quality, also has significant implications for mechanized production and market efficiency. Identifying relevant loci and mining candidate genes is crucial for cultivating high-yield peanut varieties. In this study, we employed advanced [...] Read more.

The size of peanut pods and seeds, which directly affects yield and quality, also has significant implications for mechanized production and market efficiency. Identifying relevant loci and mining candidate genes is crucial for cultivating high-yield peanut varieties. In this study, we employed advanced generation recombinant inbred lines developed by crossbreeding Huayu 44 and DF12 as the experimental material. Quantitative trait locus (QTL) mapping for traits related to pod and seed size was conducted across six environments. A total of 44 QTLs were detected, distributed on chromosomes A02, A05, B04, B08, and B10. An enrichment region for multiple QTLs was also identified on chromosome A05 (19.28~52.32 cm). In this region, 10 KASP markers were developed, narrowing the enrichment area to two candidate gene hotspot regions of 600.9 kb and 721.2 kb. By combining gene prediction and functional annotation within the intervals, 10 candidate genes, including those encoding cytochrome P450 protein, polyamine synthase, mannose-1-phosphate guanylyltransferase, pentatricopeptide repeat protein, and E2F transcription factor, were identified as regulators of pod and seed size. This study provides technical support for the genetic improvement and key gene identification of peanut pod and seed size. Full article

(This article belongs to the Special Issue Molecular Breeding and Genetic Improvement of Oilseed Crops)

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17 pages, 2960 KiB

Open AccessArticle

Impact of Ecological Cognitive Bias on Pesticide Reduction by Natural Rubber Farmers in China: Insight from Price Insurance Satisfaction

by Donghui Chen, Jiyao Liu, Desheng Zhang, Zhixu Dong and Tao Xu

Agriculture 2024, 14(9), 1633; https://doi.org/10.3390/agriculture14091633 - 18 Sep 2024

Cited by 1 | Viewed by 909

Abstract

Some natural rubber farmers mistakenly equate the ecological functions of rubber plantations with those of primary forests. This cognitive bias can hinder pesticide reduction efforts. Meanwhile, natural rubber farmers gain security through price insurance, which helps them adopt a long-term perspective on environmental [...] Read more.

Some natural rubber farmers mistakenly equate the ecological functions of rubber plantations with those of primary forests. This cognitive bias can hinder pesticide reduction efforts. Meanwhile, natural rubber farmers gain security through price insurance, which helps them adopt a long-term perspective on environmental protection, mitigating the negative impact of cognitive biases on pesticide use decisions. However, existing research often overlooks the influence of ecological cognitive bias on pesticide reduction and the moderating role of price insurance satisfaction. This study utilizes field survey data from Hainan and employs logit models and double machine learning models to empirically analyze the impact of ecological cognitive bias on pesticide reduction among natural rubber farmers. It further tests the underlying mechanisms using moderation models. The results indicate that (1) ecological cognitive bias negatively affects pesticide reduction among natural rubber farmers, and (2) price insurance satisfaction mitigates the impact of ecological cognitive bias on pesticide reduction. Based on these findings, the government should enhance education and training to raise ecological awareness among natural rubber farmers and reduce ecological cognitive biases. Disseminating knowledge about price insurance and establishing a comprehensive insurance system can secure farmers’ income and promote the rational use of pesticides. Full article

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

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