Carole Wright

The Application of Near Infrared Spectroscopy for the Assessment of Avocado Quality Attributes

[Extract] Quality and safety evaluation of agricultural products has become an increasingly important consideration in market/commercial viability and systems for such evaluations are now demanded by customers, including distributors and retailers. Unfortunately, most horticultural products struggle with delivering adequate and consistent quality to the consumer. Removing inconsistencies and providing what the consumer expects is a key factor for retaining and expanding both domestic and international markets. 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. However, the external appearance of most fruit is generally not an accurate guide to the internal or eating quality of the fruit. Internal quality of fruit is currently subjectively judged on attributes such as volatiles, firmness, and appearance. Destructive subjective measures such as internal flesh colour, or objective measures such as extraction of juice to measure sweetness (°Brix) or assessment of dry matter (DM) content are also used, although obviously not for every fruit – just a sample to represent the whole consignment.

The application of FT-NIRS for the detection of bruises and the prediction of rot susceptibility of ‘Hass’ avocado fruit: The application of FT-NIRS for the detection of bruises and the prediction of rot susceptibility of ‘Hass’ avocado fruit

BACKGROUND A rapid non-destructive in-line grading system that can rapidly and accurately assess individual avocado fruit for internal quality attributes, including bruises and rots, would allow the avocado industry to provide a more consistent fruit quality to the consumer, optimise market distribution and ensure maximum yield for the producer and retailer. Fourier transform-near-infrared (FT-NIR) spectroscopy was investigated to detect bruises and rot susceptibility as an indication of shelf-life in avocado fruit at both the sprung stage of ripeness and eating ripe fruit. RESULTS The classification models (principal component linear discriminant analysis, partial least squares discriminant analysis and support vector machine) for each of three growing seasons found hard green fruit that were deliberately bruised could be correctly detected with 70-78% accuracy after 2-5 h following impact damage and with 83-89% accuracy after 24 h. For eating ripe fruit, the accuracy was 60-100% after 2-5 h following impact damage and 66-100% after 24 h. The ability of the classification models to accurately predict rot development into two classes, ≤10% and >10% of flesh affected, ranged from 65% to 84% over the three growing seasons. When the rot classes were defined as ≤30% and >30% the accuracy was 69-77%. CONCLUSIONS The results of the study highlight the potential of FT-NIR reflectance spectroscopy for application in a commercial, in-line setting for the non-destructive evaluation of impact damage and rot susceptibility of whole avocado fruit. The study indicates that fruit should be held for approximately 24 h prior to scanning to allow bruise development to occur, particularly in hard fruit (i.e., stage 2) prior to bruise assessment.