In green leafy vegetables, the retention of green colour is one of the most generally index used to evaluate the overall quality and freshness and it is associated to total chlorophyll content. The aim of this research is to demonstrate the relationship between changes in colour and total chlorophyll content during storage of fresh-cut rocket leaves. Fresh-cut rocket leaves (Eruca sativa Mill.) were put in open polypropylene bags containing about 150 g of product each and stored at three temperatures (20, 10 and 5°C) for 6, 12 and 16 days, respectively. Sixty-four bags were prepared for each storage temperature. At each storage time (0, 2, 5 and 6 days at 20°C; 0, 5, 8 and 12 days at 10°C; 0, 6, 13 and 16 days at 5°C) fresh-cut rocket samples were subjected to colour analysis by a computer vision system (CVS) and a colourimeter. Then were analysed for total chlorophyll content using a spectrophotometer method and a SPAD-meter. A part of data (70%) were subjected to regression analysis to build predictive models of total chlorophyll content using as predictors the colour data (L*, a*, b*) obtained by colourimeter and CVS. Unseen data (remaining 30%) were used to validate the models obtained. Results demonstrated that is possible to predict the total chlorophyll content starting by colour parameters, using CVS or colourimeter with similar performance in validation (mean R2=0.74). Moreover, similar performances were obtained using the SPAD-meter to predict the total chlorophyll of fresh-cut rocket leaves (R2=0.79).

Colour analysis to predict the total chlorophyll content of rocket leaves

Pace Bernardo;Cefola Maria;Cavallo Dario Pietro;Attolico Giovanni
2021

Abstract

In green leafy vegetables, the retention of green colour is one of the most generally index used to evaluate the overall quality and freshness and it is associated to total chlorophyll content. The aim of this research is to demonstrate the relationship between changes in colour and total chlorophyll content during storage of fresh-cut rocket leaves. Fresh-cut rocket leaves (Eruca sativa Mill.) were put in open polypropylene bags containing about 150 g of product each and stored at three temperatures (20, 10 and 5°C) for 6, 12 and 16 days, respectively. Sixty-four bags were prepared for each storage temperature. At each storage time (0, 2, 5 and 6 days at 20°C; 0, 5, 8 and 12 days at 10°C; 0, 6, 13 and 16 days at 5°C) fresh-cut rocket samples were subjected to colour analysis by a computer vision system (CVS) and a colourimeter. Then were analysed for total chlorophyll content using a spectrophotometer method and a SPAD-meter. A part of data (70%) were subjected to regression analysis to build predictive models of total chlorophyll content using as predictors the colour data (L*, a*, b*) obtained by colourimeter and CVS. Unseen data (remaining 30%) were used to validate the models obtained. Results demonstrated that is possible to predict the total chlorophyll content starting by colour parameters, using CVS or colourimeter with similar performance in validation (mean R2=0.74). Moreover, similar performances were obtained using the SPAD-meter to predict the total chlorophyll of fresh-cut rocket leaves (R2=0.79).
2021
Istituto di Scienze delle Produzioni Alimentari - ISPA
Istituto di Sistemi e Tecnologie Industriali Intelligenti per il Manifatturiero Avanzato - STIIMA (ex ITIA)
978-94-62613-09-6
Chlorophyll content
image analysis
no-destructive evaluation
fresh-cut leaves
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/365150
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