Research On Year Identification Of Corn Reserve Grain Based On Spectral Technology

One of the crucial building blocks of China’s industries,including those of industry,food,and animal husbandry,is maize,and its annual testing is one of the most essential indicators for national planning.Hence,the most pressing requirement at this moment is for a testing method that is quick,non-destructive,real-time,and simple to use.The demand has been difficult for conventional biochemical detection methods to meet up to this point,and spectral detection technology has emerged as a potent supplement to conventional detection methods and is anticipated to emerge as a new alternative technology.This work combines the benefits of hyperspectral imaging and Raman spectroscopy to conduct research on the detection and characterisation of maize reserve grain years.For three storage years,conduct Raman spectroscopy detection tests on corn.Create a molecular model of the interior components of corn using computer simulation and density functional theory.Then,examine and debate the theoretical calculations and experimental findings.Create two mathematical models for year identification,namely,support vector machine and limit learning machine,based on the results of the software’s processing of the hyperspectral data,and collect hyperspectral images of the surface of corn for five storage years.Improve and choose a model with a high rate of recognition.Results indicated that utilising Raman spectroscopy to identify and examine maize in various years revealed a positive correlation between changes in the internal components of corn through time and changes in Raman peak area,full width at half peak,and Raman peak intensity of the spectrum.The analysis of maize in different years using Raman spectroscopy showed that there was a positive link between changes in the internal components of corn through time and changes in the Raman peak area,full breadth at half peak,and Raman peak intensity of the spectrum.Identify the storage year of corn reserve grain by using hyperspectral imaging technology to detect and evaluate different corn years,create a classification model for spectral image data and year evolution,and then achieve the best model based on both the whole band spectrum and band screening.This article lays the groundwork for food production safety by introducing a new detection method for identifying the year of various agricultural seeds and fruits.