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• W1492731093 abstract "This study presents an attempt to predict the sensory quality of carrots using NearInfrared (NIR) technology and multivariate data analysis (e.g. PCA, PLS-DA) toanalyse some of factors modulating carrot sensory quality using classification system.The aim is to introduce a technology to develop a sensor that can non-destructivelypredict the sensory quality of different commodities. Such sensors could be used onlinein warehouses and public fruit markets. A NIR spectrometer with Photo Diode Array(PDA) detector, was able to classify different carrot samples according to their cultivarand production system (organic, conventional) with a high accuracy. Non-destructiveclassification and modelling was based on optical reflectance in NIR range (700-1100nm). Different cultivars and different production system samples were correctlyclassified in rates of > 64% and > 82% respectively. The ability of NIR to classifysamples with different cultivars and production systems indicates that NIR is able topredict the sensory quality of carrots, which are mainly dependant on cultivar,production system and year." @default.
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• W1492731093 date "2004-03-01" @default.
• W1492731093 modified "2023-09-27" @default.
• W1492731093 title "Distinguishing Carrot’s Characteristics by Near Infrared (NIR)Reflectance and Multivariate Data Analysis" @default.
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• W1492731093 hasPublicationYear "2004" @default.
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