An Identification Method of Maize Crop's Nutritional Status Based on Index Weight

文献类型： 外文期刊

第一作者： Tian, Li

作者： Tian, Li;Wang, Chun;Li, Hailiang;Sun, Haitian

作者机构：

关键词： index weight; maize crops; nutritional status; distinguish; index system; probabilistic neural network

期刊名称：POLISH JOURNAL OF ENVIRONMENTAL STUDIES （ 影响因子：1.8； 五年影响因子：1.7 ）

ISSN： 1230-1485

年卷期： 2024 年 33 卷 4 期

页码：

收录情况： SCI

摘要： In view of the lack of considering index weight and less nutritional status classification in maize crop's nutritional status identification, an identification method of maize crop's nutritional status based on index weight is studied. Based on the five aspects of Agronomic and soil properties, 15 identification indexes such as plant height and soil available phosphorus content are selected to construct the identification index system of maize crop's nutritional status. Through the evidence fusion process, the subjective weight calculation method is combined with the objective weight calculation method to calculate each identification index system. The nutritional status of maize crops is divided into nine grades: extreme poor nutrition to extreme severe eutrophication. Samples are generated by random interpolation between the values of grade standard domain. The probabilistic neural network recognition model is constructed, and the randomly generated samples are used to train and test the model to obtain the recognition model architecture that meets the accuracy requirements. The weight of each index and the normalized sample index matrix are calculated and input into the trained recognition model to obtain the recognition results of nutritional status of corn crop samples. The test results show that the index weight obtained by this method has higher reliability and can meet the application needs of maize crop's nutritional status identification.

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