Prediction of hass avocado maturity via FT-NIRS

Wedding, B.B., Wright, C., Grauf, S., White, R.D., Tilse, B., and Gadek, P. (2010) Prediction of hass avocado maturity via FT-NIRS. In: Proceedings of 14th International conference on Near Infrared Spectroscopy. pp. 261-264. From: 14th International Conference on Near Infared Spectroscopy (NIRS), 7 - 16 November 2009, Bangkok, Thailand.

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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.

Item ID: 16501
Item Type: Conference Item (Research - E1)
ISBN: 978-1-906715-03-8
Keywords: fruit, avocado, dry matter, maturity, near infrared spectroscopy, eating quality
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Date Deposited: 16 May 2011 00:15
FoR Codes: 02 PHYSICAL SCIENCES > 0205 Optical Physics > 020599 Optical Physics not elsewhere classified @ 50%
07 AGRICULTURAL AND VETERINARY SCIENCES > 0706 Horticultural Production > 070605 Post Harvest Horticultural Technologies (incl Transportation and Storage) @ 50%
SEO Codes: 97 EXPANDING KNOWLEDGE > 970102 Expanding Knowledge in the Physical Sciences @ 100%
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