Baby lettuce leaves are generally produced for the unwashed ready-to-eat market. The aim of this research was to predict sensory and microbiological aspects of this product based on physicochemical properties during storage at 4 and 10°C. Products were analysed at sampling times chosen on the basis of five sensory visual quality (VQ) levels. Samples scoring VQ5 and VQ4 were considered acceptable (Ac), whereas the remaining scores were defined as unacceptable (UAc). Each VQ level was then characterized for physico-chemical (colour, ammonium, antioxidant activity, electrolytic leakage, phenols, chlorophyll, respiratory activity) and microbiological (total viable count, Pseudomonas spp., Enterobacteriaceae, lactic acid bacteria, yeast and moulds) parameters. UAc samples also proved unsatisfactory from a microbiological point of view (total viable count ≥107 CFU g-1). Partial least squares (PLS) regression analysis allowed us to identify colour change (ΔE∗) and total chlorophyll (TC) as suitable variables to predict the microbial load (TVC) associated with each sensory VQ level. The model obtained showed R2CV=0.94, RMSECV=0.41 and a relative error of 5.61%. In conclusion, the use of these parameters as quality indicators could be a new strategy for discriminating green leafy vegetables into acceptable or unacceptable products.

Physico-chemical parameters to predict microbiological and sensory quality aspects of baby lettuce leaves

AMODIO, MARIA LUISA
;
COLELLI, GIANCARLO;
2017-01-01

Abstract

Baby lettuce leaves are generally produced for the unwashed ready-to-eat market. The aim of this research was to predict sensory and microbiological aspects of this product based on physicochemical properties during storage at 4 and 10°C. Products were analysed at sampling times chosen on the basis of five sensory visual quality (VQ) levels. Samples scoring VQ5 and VQ4 were considered acceptable (Ac), whereas the remaining scores were defined as unacceptable (UAc). Each VQ level was then characterized for physico-chemical (colour, ammonium, antioxidant activity, electrolytic leakage, phenols, chlorophyll, respiratory activity) and microbiological (total viable count, Pseudomonas spp., Enterobacteriaceae, lactic acid bacteria, yeast and moulds) parameters. UAc samples also proved unsatisfactory from a microbiological point of view (total viable count ≥107 CFU g-1). Partial least squares (PLS) regression analysis allowed us to identify colour change (ΔE∗) and total chlorophyll (TC) as suitable variables to predict the microbial load (TVC) associated with each sensory VQ level. The model obtained showed R2CV=0.94, RMSECV=0.41 and a relative error of 5.61%. In conclusion, the use of these parameters as quality indicators could be a new strategy for discriminating green leafy vegetables into acceptable or unacceptable products.
2017
9789462611504
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11369/355709
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