Digitization of Broccoli Freshness Integrating External Color and Mass Loss
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. Theref...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2020-09-01
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| Series: | Foods |
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| Online Access: | https://www.mdpi.com/2304-8158/9/9/1305 |
| _version_ | 1797553600187072512 |
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| author | Yoshio Makino Genki Amino |
| author_facet | Yoshio Makino Genki Amino |
| author_sort | Yoshio Makino |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-10T16:17:46Z |
| format | Article |
| id | doaj.art-9d937323ddc5439385e680bbe4f1deb3 |
| institution | Directory Open Access Journal |
| issn | 2304-8158 |
| language | English |
| last_indexed | 2024-03-10T16:17:46Z |
| publishDate | 2020-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Foods |
| spelling | doaj.art-9d937323ddc5439385e680bbe4f1deb32023-11-20T13:54:20ZengMDPI AGFoods2304-81582020-09-0199130510.3390/foods9091305Digitization of Broccoli Freshness Integrating External Color and Mass LossYoshio Makino0Genki Amino1Graduate School of Agricultural and Life Sciences, The University of Tokyo, 1-1-1, Yayoi, Bunkyo-ku, Tokyo 113-8657, JapanGraduate School of Agricultural and Life Sciences, The University of Tokyo, 1-1-1, Yayoi, Bunkyo-ku, Tokyo 113-8657, JapanYellowing 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.https://www.mdpi.com/2304-8158/9/9/1305<i>Brassica oleracea</i> var. <i>italica</i>computer visionmachine learningevaluationshelf lifestatistical analysis |
| spellingShingle | Yoshio Makino Genki Amino Digitization of Broccoli Freshness Integrating External Color and Mass Loss Foods <i>Brassica oleracea</i> var. <i>italica</i> computer vision machine learning evaluation shelf life statistical analysis |
| title | Digitization of Broccoli Freshness Integrating External Color and Mass Loss |
| title_full | Digitization of Broccoli Freshness Integrating External Color and Mass Loss |
| title_fullStr | Digitization of Broccoli Freshness Integrating External Color and Mass Loss |
| title_full_unstemmed | Digitization of Broccoli Freshness Integrating External Color and Mass Loss |
| title_short | Digitization of Broccoli Freshness Integrating External Color and Mass Loss |
| title_sort | digitization of broccoli freshness integrating external color and mass loss |
| topic | <i>Brassica oleracea</i> var. <i>italica</i> computer vision machine learning evaluation shelf life statistical analysis |
| url | https://www.mdpi.com/2304-8158/9/9/1305 |
| work_keys_str_mv | AT yoshiomakino digitizationofbroccolifreshnessintegratingexternalcolorandmassloss AT genkiamino digitizationofbroccolifreshnessintegratingexternalcolorandmassloss |