Evaluating the consistency of rice and paddy quality using four-dimensional fingerprint analysis

Abstract

The aim of this paper is to evaluate the quality of 13 batches of rice and 17 batches of paddy. Differential scanning calorimetry curves, Fourier transform infrared spectroscopy, ultraviolet spectroscopy and electrochemical curves of 30 batches of rice and paddy were collected, and this paper utilized the quantitative fingerprints evaluated by using the systematic quantitative fingerprinting method, macro qualitative similarity (S_m) and macro quantitative similarity (P_m) to reflect the internal differences of the samples. A new quality assessment method was explored to quantify the obtained fingerprint profiles and to compare the correlation between the original fingerprints and the quantum fingerprints using a t-test. Using the parameters S_m and P_m as analysis criteria, hierarchical clustering analysis (HCA), orthogonal partial least squares discriminant analysis (OPLS-DA) and the equal-weight integrated evaluation method were used to evaluate the quality of the four analysis methods.