No abstract

In recent years, people have begun to collect environmental data in vegetable greenhouses. Therefore, this article studies the current internal control technology of vegetable greenhouses, and improves the sensor application in vegetable greenhouses, in a targeted manner by combining with the improved neural network algorithm. The model has more accurate prediction accuracy than traditional BP. By using the Android client and ZigBee artificial intelligence control technology it creates the most suitable living conditions for the vegetables, fruits, and other crops in the vegetable greenhouse by controlling the various valves, sun visors, and light supplementary switches inside the vegetable greenhouse. The simulation results show that the model proposed in this article has higher convergence accuracy. In addition, this article applies the improved neural network to the management of the agricultural product supply chain, starting from the agricultural product supply chain and agricultural product supply chain management. Based on this, the analytic hierarchy process is used to explore the influencing factors of agricultural product supply chain management, and the analysis shows that consumers are targeting different consumer demand raised by the agricultural product supply chain. The improved neural network provides new ideas for the research of sensor vegetable greenhouses and agricultural product supply chain management.

Faced with the pressure of slowing industrial growth and industrial transformation requirements, it is crucial to analyze the changes and the corresponding driving factors of the food processing industry in China. An analysis using traditional and spatial shift‐share models was conducted to decompose the changes in the food processing industry in each region of China from 2009 to 2019 into five effects: national growth effect (NG), industrial mix effect (IM), competitive effect (CE), neighbor‐nation competitive effect (NNC), and region‐neighbor competitive effect (RNC). Among the five effects from 2009 to 2019, the NG contributed the most to the growth in most regions, indicating that the development of the food processing industry in China was greatly influenced by the industrial base and that China's food processing industry has entered a “growth bottleneck period.” During the period 2009–2014 to period 2014–2019, compared to the IM and CE, the influence of spatial spillover effects was stronger and significantly enhanced. Moreover, the IM, CE, NNC, and RNC in most southern regions were stronger than those in most northern regions. Therefore, China's food processing industry needs and is transforming into high‐quality development. It is necessary to innovate the mode of development of food processing industry and strengthen interregional exchanges and cooperation.