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

Wedding, B.B. and White, R.D. and Grauf, S. and Wright, C. and Tilse, B. and Hofman, P. and Gadek, P.A. (2011) Non-destructive prediction of 'Hass' avocado dry matter via FT-NIR spectroscopy. Journal of the Science of Food and Agriculture, 91 (2). pp. 233-238.

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Article Link(s): http://dx.doi.org/10.1002/jsfa.4175

Publisher URL: http://www.interscience.wiley.com

Abstract

BACKGROUND: The 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.

RESULTS: It 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%.

CONCLUSION: The 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.

Item Type:Article
Additional Information:© Society of Chemical Industry.
Keywords:Avocados; non-invasive assessment; near-infrared spectroscopy; avocado; dry matter; fruits; harvesting date; mathematical models; maturity; non destructive testing; reflectance; regression analysis; seasonal variation; Queensland; Australia.
Subjects:Technology > Technology (General) > Spectroscopy > NIR (Near Infrared)
Plant culture > Fruit and fruit culture > Culture of individual fruits or types of fruit > Stonefruit
Deposited On:01 Mar 2011 02:34
Last Modified:17 Jun 2011 01:21

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