Prediction of hass avocado maturity via FT-NIRS

Abstract

Most commercial quality classification systems for fruit and vegetables are based on external features of the product, for example: shape, colour, size, weight and blemishes. For avocado fruit, external colour is not a maturity characteristic. Also its smell is too weak, and appears later in its maturity stage.1 Because maturity is a major component of avocado quality and palatability, it is important to harvest mature fruit, so as to ensure that fruit will ripen properly and have acceptable eating quality. Currently, commercial avocado maturity estimation is based on destructive assessment of the percentage of Dry Matter (%DM), and sometimes percent oil, both of which are highly correlated with maturity.2, 3 A rapid and non-destructive system that can accurately and rapidly monitor internal quality attributes would allow the avocado industry to provide better, more consistent eating quality fruit to the consumer, and thus improve industry competitiveness and profitability. The aim of this study was to assess the potential of FT-NIR diffuse reflectance spectroscopy as an objective non-invasive method to determine Hass avocado maturity and thereby eating quality, based on %DM, and its ability to predict over several growing seasons.