コンピュータービジョンによるブロッコリー外観品質の客観的評価

Abstract

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.

Digitization of Broccoli Freshness Integrating External Color and Mass Loss

“…In the classification ( Table 2 A), with green color retention and mass retention rates as the input variables, there were eight misclassifications, and the correct answer rate was 67%. Usually, the freshness of broccoli is evaluated by measuring the greenness of the flower buds [ 25 , 30 , 31 ]. Therefore, Figure 5 shows the changes over time in the green color retention rates of the test data set.…”

“…As shown in Figure 3 , since the area retention rate is highly correlated with mass retention rate, it is possible to create a freshness evaluation index that integrates color and mass only by image capturing when these factors are combined with the green color retention rate. However, because the classification accuracy by storage period duration was similar to the evaluation conducted using only green color retention rate, the conventional method [ 25 , 30 , 31 ] was used. In contrast, when the mass retention rate determined by weighing was added, the storage period durations could be classified with higher accuracy even when yellowing had progressed, as compared with a freshness evaluation using only green color.…”

“…Freshness was measured every 2 days during the storage period. External color was measured with a CVS [ 31 ], and mass was measured with an electronic balance (MS4002S, Mettler Toledo International Inc., Tokyo, Japan). The data were obtained for nine biological samples at eight storage timepoints from 0 day to 14 days (every 2 days), and a total of 72 data points were obtained.…”

“…The green color retention of each sample was quantified by the method of Makino et al [ 31 ]. Specifically, the images (Windows bitmap format) acquired by the CVS were imported into MATLAB ver.…”

“…Wang et al [ 25 ] evaluated − a */ b * with a colorimeter and objectively evaluated controlled atmosphere storage and modified atmosphere packaging on the green color retention of broccoli. Makino et al [ 31 ] used a computer vision system (CVS) to visualize the temporal changes in the two-dimensional spatial distribution of green color retention associated with decreased freshness of broccoli flower buds. In addition to yellowing, a significant decrease in mass was also observed [ 32 ].…”