Near infrared spectroscopic data for rapid and simultaneous prediction of quality attributes in intact mango fruits

Abstract

Presented dataset contains spectral data on near infrared region for a total of 186 intact mango fruit samples from 4 different cultivars (cv. Kweni, Cengkir, Palmer and Kent). Near infrared spectral data were collected and recorded as absorbance (Log(1/R)) data in wavelength range of 1000–2500 nm. Those spectral data are potential to be re-used and analysed for the prediction of mango quality attributes in form of vitamin C, soluble solids content (SSC) and total acidity (TA). Spectra data can be corrected and enhanced using several algorithms such as multiplicative scatter correction (MSC) and de-trending (DT). Prediction models can be established using common regression approach like partial least square regression (PLSR). Keywords: NIRS, Spectroscopy, Spectral data, Mango, Prediction