A method to objectively evaluate the external quality of broccoli heads using a computer vision system (CVS), a type of digital camera, was proposed. The CVS was effective in calculating the spatial distribution of color space values of broccoli heads. Value of-a*/b* (chromaticity of Commission Internationale de l'Éclairage) was effective in evaluating the concentration of chlorophyll a. Ana*/b* value greater than 0.94 indicated fresh buds that remained green. Conversely, the value of a* was effective in evaluating the existence of anthocyanins that damage the external quality of the broccoli head. Buds with low concentrations of anthocyanin had an a* value less than-12. These two thresholds were used for visualizing high-quality buds with high concentrations of chlorophyll a and low concentrations of anthocyanin. The proportion of high-quality buds of typical heads that included low or high concentrations of anthocyanin reduced from 39% or 22% to 15% or 5.4% during 5 d storage. The proportion of high-quality buds of typical heads with low anthocyanin concentrations was usually higher than those with high anthocyanin concentrations. These results suggest that the proposed method using the CVS is suitable for objectively evaluating the external quality of broccoli heads and selecting high-quality heads.
Yellowing of green vegetables due to chlorophyll decomposition is a phenomenon indicating serious deterioration of freshness, and it is evaluated by measuring color space values. In contrast, mass reduction due to water loss is a deterioration of freshness observed in all horticultural crops. Therefore, in this study, we propose a novel freshness evaluation index for green vegetables that combines the degree of greenness and mass loss. The green color retention rate was measured using a computer vision system, and the mass retention rate was measured by weighing. Linear discriminant analysis (LDA) was performed using both variables (greenness and mass) as covariates to obtain a single freshness evaluation value (first canonical variable). The correct classification of storage period length by LDA was 96%. Green color retention alone allowed for classification of storage durations between 0 day and 10 days, whereas LDA could classify storage durations between 0 day and 12 days. The novel freshness evaluation index proposed by this research, which integrates greenness and mass, has been shown to be more accurate than the conventional evaluation index that uses only greenness.
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