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|Scopus||Web of Science®||Altmetric|
|Title:||Objective assessment of dried sultana grape quality using digital image analysis|
|Citation:||Australian Journal of Grape and Wine Research, 2018; 24(2):234-240|
|Publisher:||Australian Society of Viticulture and Oenology|
|F.C. Doerflinger, V. Pagay|
|Abstract:||Background and Aims: Evaluation of dried grape berry quality in Australia is currently based on visual assessment by trained humans, a process that is subjective and prone to error. The goal of this work was to develop an objective methodology to evaluate the quality of dried grapes from Vitis vinifera L. cv. Thompson Seedless, referred to as ‘sultanas’. Methods and Results: A non‐destructive method for berry quality assessment based on digital image analysis using the MATLAB programing language enabled the development of a novel quality index and computer application for classification of berry quality based on surface colour. The method separated individual berries into several colour classes and assigned the batch an overall crown grade that was consistent with industry assessment. Conclusion: Digital image analysis of berry surface colour using the new method was an accurate and reliable method for objectively evaluating dried sultana quality. Significance of the Study: This method will facilitate the rapid and objective evaluation of sultana quality at packinghouses to ensure that a fair price is paid to growers and to reduce potential conflicts arising from subjective fruit grading by humans.|
|Keywords:||Dried fruit; grape colour; MATLAB; postharvest; quality classification|
|Rights:||© 2017 Australian Society of Viticulture and Oenology Inc.|
|Appears in Collections:||Agriculture, Food and Wine publications|
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