Abstract
Abstract Amylose content is commonly used to predict the texture of cooked rice. However, rice classification using only amylose content can misclassify actual sensory quality. Quality assessment of cooked rice can be determined by a combined evaluation of physical, chemical and sensory properties, but this process is costly and requires use of trained panelists. In this study, an alternate method for predicting rice amylose content was investigated. Paste viscosity and cooked rice texture of nine rice varieties were measured that had either low, medium, or high amylose content. Data were analyzed using analysis of variance, Pearson correlation, and discriminant analysis. Results showed that protein content, which played a major role in cooked rice texture, did not correlate with amylose content. Discriminant analysis results showed that only pasting attributes could discriminate the amylose groups but not texture. Pasting property, peak viscosity, and trough were the best discriminators with an eigenvalue of 32.9. These discriminators correctly predicted 100% of medium‐ and high‐amylose rice, but only correctly predicted 66.7% of low‐amylose rice with 88.9% of cross‐validated grouped cases correctly classified. The use of rice texture and pasting properties in combination with multivariate analysis techniques has potential as an easier and less costly method for the accurate classification of rice based on sensory quality.
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Claims 8
Claim · model-written summary
Rice protein content did not correlate with amylose content.
- Taxon
- Rice
Oryza sativat0 - Outcome
- amylose contente0
- Qualifier
- protein contente0
Not reportedCompoundDirection
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“protein content, which played a major role in cooked rice texture, did not correlate with amylose content”
t0“Rice”
Claim · model-written summary
Protein content played a major role in cooked rice texture.
- Taxon
- RiceOryza sativat0
- Organ / stage
- cooked ricee0
- Outcome
- cooked rice texturee0
- Qualifier
- protein contente0
Not reportedDirection
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“protein content, which played a major role in cooked rice texture”
t0“Rice”
Claim · model-written summary
Pasting attributes discriminated amylose groups.
- Taxon
- RiceOryza sativat0
- Outcome
- discriminate the amylose groupse0
- Comparator
- texturee0
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“only pasting attributes could discriminate the amylose groups but not texture”
t0“Rice”
Claim · model-written summary
Texture did not discriminate amylose groups.
- Taxon
- RiceOryza sativat0
- Outcome
- discriminate the amylose groupse0
- Comparator
- texturee0
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“only pasting attributes could discriminate the amylose groups but not texture”
t0“Rice”
Claim · model-written summary
Peak viscosity and trough were best discriminators with eigenvalue 32.9.
- Taxon
- RiceOryza sativat0
- Outcome
- best discriminatorse0
- Value
- 32.9e0
- Qualifier
- peak viscosity, and troughe0
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“peak viscosity, and trough were the best discriminators with an eigenvalue of 32.9”
t0“Rice”
Claim · model-written summary
The discriminators correctly predicted all medium amylose rice.
Verbatim
e0“correctly predicted 100% of medium‐ and high‐amylose rice”
Claim · model-written summary
The discriminators correctly predicted 66.7% of low amylose rice.
Verbatim
e0“only correctly predicted 66.7% of low‐amylose rice”
Claim · model-written summary
Cross validation correctly classified 88.9% of grouped cases.
- Taxon
- RiceOryza sativat0
- Outcome
- cross‐validated grouped cases correctly classifiede0
- Value
- 88.9%e0
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“88.9% of cross‐validated grouped cases correctly classified”
t0“Rice”