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Agricultural industries are the foundation of the modernization of agricultural and rural areas in China. National Modern Agricultural Industrial Parks (NMAIPs) provides a considerable nationwide platform for agricultural industries. We take 200 NMAIPs in China as objects. Through spatial analysis, the Herfindahl–Hirschman index, and the SBM-DEA model, we analyzed the development characteristics and regional differences of NMAIPs from the muti-level perspective of national planning, provincial coordination, and county implementation to propose policy recommendations aimed at sustainable and high-quality development. The results are as follows: (1) Regarding geospatial characteristics, NMAIPs are unevenly distributed, with a decreasing gradient from east to west. The direction is east (northward) to west (southward), consistent with the direction of the Hu line. The distribution density shows that the east is dense and the west is sparse. (2) For industrial concentration, the leading industries in NMAIPs tend to be homogenous. The HHI indicates that the homogenization of leading industries is widely represented in each province. The low oligopolistic areas are in the central and eastern regions of China, while the highly oligopolistic locations are in the western and northeastern provinces. (3) In inputs–outputs efficiency, the comprehensive technical efficiency is high but not optimal, while the distribution of values is high in the south and low in the north. Ten provinces are non-effective. According to inputs and outputs, the ineffective contribution of population of townships covered, occupied area and the capital from the collective economy are development barriers, and the high output value of NMAIPs cannot fully drive the employment and income of farmers. Further improvements are needed in terms of both pure technical efficiency and scale efficiency, and adjustments to scale operations should be in response to different returns to scale. Our research results provide policy recommendations for NMAIPs, including the establishment of a multi-level management mechanism, balancing regional development, diversifying and coordinating regional leading industries, and improving the efficiency of utilization factors. [ABSTRACT FROM AUTHOR]

Determining the nutrient requirements of industrial hemp to increase the yield requires quantifying variations in soil nutrients and enzyme activities in different growth stages, along with relevant soil microbial response. This study investigated the effects of different growth stages of industrial hemp on rhizosphere soil nutrients, enzyme activities, and microbial communities. The results showed that with the increase in the growth stages, the pH and available phosphorus (AP) decreased, while the soil organic matter (SOM), available nitrogen (AN), and available potassium (AK) increased substantially, indicating that the demand for nutrients of industrial hemp was constantly changing. Proteobacteria, Acidobacteria, Ascomycota, and Basidiomycota were found to be the keystone taxa to adapt to the nutrient requirements of industrial hemp at different growth stages by regulating soil enzyme activity. Furthermore, using the redundancy analysis and Spearman's correlation analysis, we found that microbial taxonomic composition was related to the variations in AN, AP, and pH. In general, we emphasized that the interaction between industrial hemp and soil is closely related to the growth stage, which increases plant adaptability and growth because of the change of soil microorganisms. [ABSTRACT FROM AUTHOR]

Quality grading in antler mushroom industrial production is a labor-intensive operation. For a long time, manual grading has been used for grading, which produces various problems such as insufficient reliability, low production efficiency, and high mushroom body damage. Automatic grading is a problem to be solved urgently for antler mushroom industrial development with increasing labor costs. To solve the problem, this paper deeply integrates the single-stage object detection of YOLOv5 and the semantic segmentation of PSPNet, and proposes a Y-PNet model for real-time object detection and an image segmentation network. This article also proposes an evaluation model for antler mushroom's size, which eliminates subjective judgment and achieves quality grading. Moreover, to meet the needs of efficient and accurate hierarchical detection in the factory, this study uses the lightweight network model to construct a lightweight YOLOv5 single-stage object detection model. The MobileNetV3 network model embedded with a CBAM module is used as the backbone extractor in PSPNet to reduce the model's size and improve the model's efficiency and accuracy for segmentation. Experiments show that the proposed system can perform real-time grading successfully, which can provide instructive and practical references in industry. [ABSTRACT FROM AUTHOR]

Mungbean (Vigna radiata L.), one of the most widely grown edible legumes in Asia, plays important roles in the improvement of agricultural cultivation systems as well as human diets. As an understudied crop, however, most mungbean varieties are characterized by unstable yields, poor disease resistance, and unsuitability for mechanical harvesting, thereby leading to a low production income. We, therefore, developed Jilv 20, a new mungbean cultivar with a dull seed coat, by crossing Bao 942-34 with Weilv 9002-341. After 11 years of selection and evaluation, Jilv 20 has shown wide adaptability, early maturity, high yield, halo blight resistance, and suitability for mechanical harvesting. The growth period of Jilv 20 is 79.5 and 66.7 days in the spring and summer sowing seasons, respectively, and the average plant height is approximately 56.4 cm. In this study, average yields were 1737.9, 1532.3, and 2045.1 kg/hm2 in northern spring-sowing, northern summer-sowing, and southern sites, respectively; these values were respectively 27.83%, 28.48%, and 6.96% higher than those of control cultivar Zhonglv 5, which has been popular in past decades because of its wide adaptability. The average protein and starch contents of Jilv 20 seeds were 25.0% and 49.56%, respectively. Further application and extension of Jilv 20 in China should contribute to mungbean production, breeding, and industrial development. [ABSTRACT FROM AUTHOR]

The prime goals of this article are to classify farmers' production structures in different regions through comparative analysis and propose a structural framework that can quantify the transformation and upgrade of the vegetable industry in Shaanxi. The study utilized New Structural Economics (NSE) theory to construct the theoretical model, and the empirical data set has been crafted from 1992 vegetable growers in the Shaanxi, Hebei, and Shandong provinces. We qualitatively evaluated the potentiality of the Shaanxi vegetable industry, facilitating an industrial upgrade by drawing on the development experience of other regions. More specifically, we utilized the tomato growers to construct a five-step analysis method to transform and upgrade the vegetable industries. This article found that the chosen three provinces have structural differences and similarities in their production sides, and, compared with Hebei and Shandong, the vegetable industry in Shaanxi is still in the catching-up stage. Hebei has similar planting characteristics to Shaanxi, but the production characteristics of growers in Shaanxi are quite different from those in Shandong. Therefore, tomato growers in Hebei are the desired learning object for growers in Shaanxi. By learning planting experience from Hebei growers, tomato growers in the Shaanxi Province can improve their yield and product quality. We found that Shaanxi farmers have 15.57 percent improvement potential in improving crop management and rational allocation of production materials. Proper information-sharing platforms should be implemented to grasp consumption trends on the demand side and guide industrial upgrading. [ABSTRACT FROM AUTHOR]