Journal of Food and Nutrition Research
ISSN (Print): 2333-1119 ISSN (Online): 2333-1240 Website: Editor-in-chief: Prabhat Kumar Mandal
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Journal of Food and Nutrition Research. 2016, 4(9), 592-595
DOI: 10.12691/jfnr-4-9-5
Open AccessArticle

Shelf Life Prediction for Non-accelerated Studies (SheNon) Applied to Minimally Processed Eggplant

Natália da Silva Martins1, , Eric Batista Ferreira1, Sonia Maria Stefano de Piedade2 and Flávia Della Lucia3

1Institute of Exact Sciences, Federal University of Alfenas, Alfenas, Brazil

2Department of Exact Sciences, University of Sao Paulo, Piracicaba, Brazil

3Faculty of Nutrition, Federal University of Alfenas, Alfenas, Brazil

Pub. Date: September 05, 2016

Cite this paper:
Natália da Silva Martins, Eric Batista Ferreira, Sonia Maria Stefano de Piedade and Flávia Della Lucia. Shelf Life Prediction for Non-accelerated Studies (SheNon) Applied to Minimally Processed Eggplant. Journal of Food and Nutrition Research. 2016; 4(9):592-595. doi: 10.12691/jfnr-4-9-5


This study aimed to propose a multivariate method for determining the shelf life of food in non-accelerated studies. The method allows incorporating different kinds of variables such as sensorial, physical, chemical and microbiological. The idea is to maintain two components most (co)related to(with) time (not necessarily the first two) and regress the score of a sample adjacent against these components, predicting the shelf live. It was applied in minimally processed eggplant data, resulting in a prediction of 9.6 days of life. Results suggest that the proposed method is promising and can be used in non-accelerated studies considering attributes of different types.

shelflife estimation food safety multivariate analysis regression analysis

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