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Evaluation of Cooked Rice for Eating Quality and Its Components in Geng Rice

At present, ‘‘eating well” is increasingly desired by people instead of merely ‘‘being full”. Rice provides the majority of daily caloric needs for half of the global human population. However, eating quality is difficult to objectively evaluate in rice breeding programs. This study was carried out...

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Detalles Bibliográficos
Autores principales: Li, Cui, Yao, Shujun, Song, Bo, Zhao, Lei, Hou, Bingzhu, Zhang, Yong, Zhang, Fan, Qi, Xiaoquan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10486766/
https://www.ncbi.nlm.nih.gov/pubmed/37685200
http://dx.doi.org/10.3390/foods12173267
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author Li, Cui
Yao, Shujun
Song, Bo
Zhao, Lei
Hou, Bingzhu
Zhang, Yong
Zhang, Fan
Qi, Xiaoquan
author_facet Li, Cui
Yao, Shujun
Song, Bo
Zhao, Lei
Hou, Bingzhu
Zhang, Yong
Zhang, Fan
Qi, Xiaoquan
author_sort Li, Cui
collection PubMed
description At present, ‘‘eating well” is increasingly desired by people instead of merely ‘‘being full”. Rice provides the majority of daily caloric needs for half of the global human population. However, eating quality is difficult to objectively evaluate in rice breeding programs. This study was carried out to objectively quantify and predict eating quality in Geng rice. First, eating quality and its components were identified by trained panels. Analysis of variance and broad-sense heritability showed that variation among varieties was significant for all traits except hardness. Among them, viscosity, taste, and appearance were significantly correlated with eating quality. We established an image acquisition and processing system to quantify cooked rice appearance and optimized the process of measuring cooked rice viscosity with a texture analyzer. The results show that yellow areas of the images were significantly correlated with appearance, and adhesiveness was significantly correlated with viscosity. Based on these results, multiple regression analysis was used to predict eating quality: eating quality = 0.37 × adhesiveness − 0.71 × yellow area + 0.89 × taste − 0.34, R(2) = 0.85. The correlation coefficient between the predicted and actual values was 0.86. We anticipate that this predictive model will be useful in future breeding programs for high-eating-quality rice.
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spelling pubmed-104867662023-09-09 Evaluation of Cooked Rice for Eating Quality and Its Components in Geng Rice Li, Cui Yao, Shujun Song, Bo Zhao, Lei Hou, Bingzhu Zhang, Yong Zhang, Fan Qi, Xiaoquan Foods Article At present, ‘‘eating well” is increasingly desired by people instead of merely ‘‘being full”. Rice provides the majority of daily caloric needs for half of the global human population. However, eating quality is difficult to objectively evaluate in rice breeding programs. This study was carried out to objectively quantify and predict eating quality in Geng rice. First, eating quality and its components were identified by trained panels. Analysis of variance and broad-sense heritability showed that variation among varieties was significant for all traits except hardness. Among them, viscosity, taste, and appearance were significantly correlated with eating quality. We established an image acquisition and processing system to quantify cooked rice appearance and optimized the process of measuring cooked rice viscosity with a texture analyzer. The results show that yellow areas of the images were significantly correlated with appearance, and adhesiveness was significantly correlated with viscosity. Based on these results, multiple regression analysis was used to predict eating quality: eating quality = 0.37 × adhesiveness − 0.71 × yellow area + 0.89 × taste − 0.34, R(2) = 0.85. The correlation coefficient between the predicted and actual values was 0.86. We anticipate that this predictive model will be useful in future breeding programs for high-eating-quality rice. MDPI 2023-08-30 /pmc/articles/PMC10486766/ /pubmed/37685200 http://dx.doi.org/10.3390/foods12173267 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Li, Cui
Yao, Shujun
Song, Bo
Zhao, Lei
Hou, Bingzhu
Zhang, Yong
Zhang, Fan
Qi, Xiaoquan
Evaluation of Cooked Rice for Eating Quality and Its Components in Geng Rice
title Evaluation of Cooked Rice for Eating Quality and Its Components in Geng Rice
title_full Evaluation of Cooked Rice for Eating Quality and Its Components in Geng Rice
title_fullStr Evaluation of Cooked Rice for Eating Quality and Its Components in Geng Rice
title_full_unstemmed Evaluation of Cooked Rice for Eating Quality and Its Components in Geng Rice
title_short Evaluation of Cooked Rice for Eating Quality and Its Components in Geng Rice
title_sort evaluation of cooked rice for eating quality and its components in geng rice
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10486766/
https://www.ncbi.nlm.nih.gov/pubmed/37685200
http://dx.doi.org/10.3390/foods12173267
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