ORIGINAL RESEARCH
An Identification Method of Maize Crop’s Nutritional Status Based on Index Weight
,
 
,
 
,
 
 
 
More details
Hide details
1
College of Information and Electrical Engineering, Heilongjiang Bayi Agricultural University, Daqing 163319, China
 
2
South Subtropical Crops Research Institute, Chinese Academy of Tropical Agriculture Science, Zhanjiang 524000, China
 
 
Submission date: 2023-08-11
 
 
Final revision date: 2023-11-06
 
 
Acceptance date: 2023-11-28
 
 
Online publication date: 2024-04-25
 
 
Publication date: 2024-05-23
 
 
Corresponding author
Li Tian   

College of Information and Electrical Engineering, Heilongjiang Bayi Agricultural University, China
 
 
Pol. J. Environ. Stud. 2024;33(4):4365-4374
 
KEYWORDS
TOPICS
ABSTRACT
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.
eISSN:2083-5906
ISSN:1230-1485
Journals System - logo
Scroll to top