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

Abstract

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. © 2018 Society of Chemical Industry

Quantification of Dry Matter Content in Hass Avocado by Near-Infrared Spectroscopy (NIRS) Scanning Different Fruit Zones

“…These investigations span from 2002 to 2020. Other studies have demonstrated NIRS applications for the detection of bruises and the prediction of rot susceptibility in 'Hass' avocado fruit [34]. The progression of ripening has been monitored using NIRS to assess issues related to fruit transpiration [35], as well as postharvest classification strategies during avocado ripening, categorizing it by maturity stages based on firmness [36].…”

Development of Multimodal Fusion Technology for Tomato Maturity Assessment

“…Traditional methods for assessing fruit and vegetable maturity, such as compression and puncture tests, have been widely used but are destructive and compromise the profitability of produce [ 5 , 6 ]. With technological advancements, a range of non-destructive techniques, including haptics [ 7 , 8 ], machine vision [ 9 , 10 ], visible and near-infrared spectroscopy (Vis/NIR) [ 11 , 12 ], hyperspectral imaging [ 13 , 14 ], electronic noses (e-noses) [ 15 , 16 ], and magnetic resonance imaging (MRI), now facilitate comprehensive maturity detection without damage [ 17 , 18 ]. These methods enable the evaluation of both internal and external fruit characteristics, offering insights into multiple quality parameters simultaneously.…”