B.B. Wedding

Non-destructive prediction of 'Hass' avocado dry matter via FT-NIR spectroscopy

BACKGROUNDnThe inability to consistently guarantee internal quality of horticulture produce is of major importance to the primary producer, marketers and ultimately the consumer. Currently, commercial avocado maturity estimation is based on the destructive assessment of percentage dry matter (%DM), and sometimes percentage oil, both of which are highly correlated with maturity. In this study the utility of Fourier transform (FT) near-infrared spectroscopy (NIRS) was investigated for the first time as a non-invasive technique for estimating %DM of whole intact Hass avocado fruit. Partial least squares regression models were developed from the diffuse reflectance spectra to predict %DM, taking into account effects of intra-seasonal variation and orchard conditions.nnnRESULTSnIt was found that combining three harvests (early, mid and late) from a single farm in the major production district of central Queensland yielded a predictive model for %DM with a coefficient of determination for the validation set of 0.76 and a root mean square error of prediction of 1.53% for DM in the range 19.4-34.2%.nnnCONCLUSIONnThe results of the study indicate the potential of FT-NIRS in diffuse reflectance mode to non-invasively predict %DM of whole Hass avocado fruit. When the FT-NIRS system was assessed on whole avocados, the results compared favourably against data from other NIRS systems identified in the literature that have been used in research applications on avocados.

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.

Novel method for shark age estimation using near infrared spectroscopy

Accurate age determination is an important component of assessing and managing fish populations, yet traditional ageing using growth bands is time-consuming and has limitations. In the present study, an alternative approach to shark age estimation using near infrared spectroscopy (NIRS) was investigated using two species. The ages of Sphyrna mokarran and Carcharhinus sorrah vertebrae that had been traditionally aged and validated were successfully predicted up to 10 years of age using NIRS. The correlations between the known ages of the vertebrae and their near infrared spectra were strong, with R2 values of 0.89 and 0.84 for S. mokarran and C. sorrah respectively. The major advantage of the NIRS ageing approach was the rapid speed of age estimation, which could enable large numbers of sharks to be aged quickly. This would offer the fisheries management benefit of improving the reliability of age information for stock and risk assessments.

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

BACKGROUNDnA 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.nnnRESULTSnThe 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%.nnnCONCLUSIONSnThe 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.