Non-invasive assessment of internal quality attributes of whole avocado fruit by NIRS

Abstract

The utility of Fourier Transform (FT) - near infra-red spectroscopy (NIRS) was investigated as a non-invasive technique for estimating percentage dry matter (%DM) of whole intact ‘Hass’ avocado fruit. Partial least square (PLS) regression models were developed from the diffuse reflectance spectra to predict %DM, taking into account effects of intra-seasonal variation and orchard conditions. The study found that combining three harvests (early, mid and late seasons) yielded a predictive model for %DM with Rv 2=0.86, root mean square error of prediction (RMSEP)=1.18% for the DM in the range 18.2 – 35.0%. These results indicate the potential of FT-NIRS, in diffuse reflectance mode to non-invasively predict the %DM (and thus internal fruit quality) of whole ‘Hass’ avocado fruit.