Evaluation of Eating Quality in Japonica Rice: A Multi-Trait Analysis of Starch Properties, Protein Content and Taste Value.

Yuqianqian Li, Meng Li, Jiayuan Chang, Kaiwen Gu, Jing Yu, Xiaoming Zhang, Jinsong Bao

Abstract read

In one paragraph

Article in Foods (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed

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3 · Its place in the literature

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1 citing paper in PubMed.

Physicochemical characteristics and metabolomic profiling of representative rice cultivars distinct in eating quality.Frontiers in nutrition · 2026
Article

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5 · Who and what money

Authors and funding

7 authors.

Yuqianqian LiInstitute of Nuclear Agricultural Sciences, Key Laboratory of Nuclear Agricultural Science of Ministry of Agriculture and Rural Affairs, College of Agriculture and Biotechnology, Zhejiang University, Zijingang Campus, Hangzhou 310058, China.

Meng LiInstitute of Nuclear Agricultural Sciences, Key Laboratory of Nuclear Agricultural Science of Ministry of Agriculture and Rural Affairs, College of Agriculture and Biotechnology, Zhejiang University, Zijingang Campus, Hangzhou 310058, China.

Jiayuan ChangInstitute of Nuclear Agricultural Sciences, Key Laboratory of Nuclear Agricultural Science of Ministry of Agriculture and Rural Affairs, College of Agriculture and Biotechnology, Zhejiang University, Zijingang Campus, Hangzhou 310058, China.

Kaiwen GuInstitute of Nuclear Agricultural Sciences, Key Laboratory of Nuclear Agricultural Science of Ministry of Agriculture and Rural Affairs, College of Agriculture and Biotechnology, Zhejiang University, Zijingang Campus, Hangzhou 310058, China.

Jing YuInstitute of Nuclear Agricultural Sciences, Key Laboratory of Nuclear Agricultural Science of Ministry of Agriculture and Rural Affairs, College of Agriculture and Biotechnology, Zhejiang University, Zijingang Campus, Hangzhou 310058, China.

Xiaoming ZhangInstitute of Crop and Nuclear Technology Utilization, Zhejiang Academy of Agricultural Sciences, Hangzhou 310021, China.

Jinsong BaoInstitute of Nuclear Agricultural Sciences, Key Laboratory of Nuclear Agricultural Science of Ministry of Agriculture and Rural Affairs, College of Agriculture and Biotechnology, Zhejiang University, Zijingang Campus, Hangzhou 310058, China.ORCID 0000-0002-9606-6615

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Rice eating quality is a core determinant of consumer preference and commercial value. Although it is chemically determined by the accumulation and distribution of the substances in rice seeds, the comprehensive physicochemical basis underlying this trait in japonica rice remains insufficiently clarified. To identify the key physicochemical indicators that predict and regulate japonica rice eating quality, the taste value of 59 japonica rice varieties was evaluated, and the protein content (PC), apparent amylose content (AAC), starch pasting properties, gelatinization characteristics, and textural attributes were systematically measured. The results indicated that japonica rice has an average taste value of 72.0 with a range between 54.0 and 87.8. The taste value was significantly negatively correlated with PC, onset (To), peak (Tp) and conclusion (Tc) gelatinization temperatures, but was significantly positively correlated with appearance score, mouthfeel score, hot paste viscosity (HPV), and cool paste viscosity (CPV). PCA further indicated that AAC, HPV, CPV, peak viscosity (PV), and setback value (SB) were the major contributors to the first principal component, explaining 38.5% of the total variation. Stepwise regression analysis showed that the best regression equation for predicting taste value was: Taste value = 142.526 - 5.226 PC - 0.425 To (R

Indexed as

eating qualitygelatinization temperaturephysicochemical propertyprotein contenttaste value

Identifiers

PMID42195894

DOI10.3390/foods15101689

PMCPMC13205976

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.