Prediction of pH and total soluble solids content of mango using biresponse multipredictor local polynomial nonparametric regression

Abstract

Mango's internal quality can be determined based on its acidity and sweetness in the form of pH and total soluble solids (TSS) content. Research on fruit internal quality prediction based on near-infrared spectroscopy generally uses parametric regression modeling such as linear and partial least square regression. The study proposed biresponse multipredictor local polynomial nonparametric regression to determine mango's internal quality. The study aims to apply the theory of biresponse multipredictor local polynomial nonparametric regression for predicting the mango's internal quality in the form of pH and TSS value. We created R code for estimating nonparametric regression model of the biresponse multipredictor local polynomial. The predicted performance is determined by Mean Absolute Percentage Error (MAPE) value. The MAPE value of mango’s pH and TSS prediction is 4.473%. This means that the proposed method was highly accurate for predicting the mango maturity because the MAPE value is less than 10%.