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Application of Vis–NIR Hyperspectral Imaging for prediction of flavonoids, anthocyanins and soluble solids content in table grapes

M. Gabrielli, C. Maury and P. Picouet, Ecole Supérieure d’Agriculture, INRA, France

Application of Vis–NIR Hyperspectral Imaging for prediction of flavonoids, anthocyanins and soluble solids content in table grapes

Grapes are one of the most spread fruits in the world as fresh fruit, wine, grape juice and raisins. According to the International Organization of Vine and Wine statistics, approximately 42% of world grape production is used as fresh fruit (OIV, 2018).

A great number of studies have shown that the ripening indices such as the changes in skin color, softening, titratable acidity, soluble solids content and flavonoids compounds are traditionally used to select the right commercial ripeness time. Furthermore, color is considered as one of the most important physical properties of agro-food products and it plays a fundamental role in the assessment of external quality in food industries.

However, these quality attributes change during postharvest storage and thus influence the hedonistic and nutritional value of table grapes. In this context, it may be important to evaluate the content of these secondary metabolites in grapes.

Nevertheless, conventional techniques and methods are normally sample-destructive, induce laborious sample preparation steps, are time-consuming, and generate chemical waste, thereby limiting their utility in online/in-line quality monitoring. Recently, the research has focused on the development of non-destructive techniques suitable to increase the samples analyzed and the number of determinations for each single sample, thus providing real-time information of fruits physiological evolution and a most robust statistical data analysis. Hyperspectral imaging (HSI) has been widely used in food analysis, and it has showed great potential in the grape industry.

This technique provides a new detection method that integrates imaging and spectral techniques into a single system, simultaneously providing information on spectral response values and spatial location for each pixel in the hyperspectral image.

This paper reports on the application of hyperspectral imaging technique for predicting the soluble solid content (SSC), total anthocyanins (TA) and total flavonoids (TF) of different table grape cultivars.

Article based on the paper presented at the SIVE OENOPPIA Awards (12th edition of Enoforum; Vicenza, Italy, May 21-23, 2019).

Published on 20/10/2020
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