Study on the influence of region of interest on the detection of total sugar content in apple using hyperspectral imaging technology

Abstract

This paper explores the influence of the selection method of the region of interest (ROI) on the results in the total sugar of apple detection based on hyperspectral imaging technology. Taking Fuji apple as the detection object, the hyperspectral images of the samples were collected based on the 900~1750 nm hyperspectral imaging system, and the total sugar content of the samples was obtained based on the anthrone colorimetric method. The square ROI and circular ROI of different sizes were extracted. The average spectrum of the region was used to establish a quantitative analysis model of apple's total sugar content by partial least squares (PLS). The results show that apple's total sugar detection model established by extracting a circular ROI with a diameter of 25 pixels has the highest accuracy and strongest prediction ability(R_c = 0.8977, RMSEC = 0.6459, R_P = 0.8836, RMSEP = 0.6627). The research shows that selecting ROI with a suitable shape and size for the research object is of great significance for improving the accuracy of the prediction model of apple's total sugar content and giving play to the advantages of hyperspectral images.

Keywords:
hyperspectral imaging technology; ROI; PLS; Fuji apple; total sugar content