4.4 Article

The Use of Image Analysis and Sensory Analysis for the Evaluation of Cultivar Differentiation of Freeze-Dried and Lacto-Fermented Beetroot (Beta vulgaris L.)

Journal

FOOD ANALYTICAL METHODS
Volume 15, Issue 4, Pages 1026-1041

Publisher

SPRINGER
DOI: 10.1007/s12161-021-02187-x

Keywords

Freeze-drying; Lacto-fermentation; Image analysis; Discriminative models; Sensory evaluation

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The research aimed to compare the differentiation of processed beetroot cultivars using image analysis and sensory evaluation techniques. Differences in textures within color spaces served as effective indicators for distinguishing beetroot varieties, with image analysis techniques shown to be more accurate than sensory attributes.
The aim of the research was to compare the possibility of distinguishing the cultivars of processed beetroots using image analysis technique and sensory evaluation. The differentiation of processed samples was tested for freeze-dried beetroot 'Czerwona Kula' and 'Cylindra', lacto-fermented beetroot 'Czerwona Kula' and 'Cylindra', freeze-dried lacto-fermented beetroot 'Czerwona Kula' and 'Cylindra'. The textures from the images of quarters of root slices, as well as sensory attributes evaluated by expert sensory assessors, were determined. The differences in the means of selected textures from color spaces Lab, RGB and XYZ for different cultivars of raw and processed beetroots were observed. The raw beetroots 'Czerwona Kula' and 'Cylindra' were discriminated with the accuracy of up to 94.5% for models built based on selected texture from color space RGB. In the case of processed beetroots 'Czerwona Kula' and 'Cylindra', the accuracy reached 96% (color space Lab) for freeze-dried beetroots, 99% (color space Lab) for lacto-fermented beetroots, 98.5% (color space Lab) for freeze-dried lacto-fermented beetroots. In the case of sensory attributes, no statistically significant differences were observed between the beetroot samples.

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