ArticleCarbohydrate polymers2021
Deploying viscosity and starch polymer properties to predict cooking and eating quality models: A novel breeding tool to predict texture.
Article in Carbohydrate polymers, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed.
- Genome editing ofCurrent research in food science · 2026Article
- Protein Contents Determine the Thermal Stability and Gel Consistency of High-Amylose Milled Rice.Foods (Basel, Switzerland) · 2025Article
- Delayed sowing under climate warming conditions improves rice quality by altering structural characteristics of starch.BMC plant biology · 2025Article
- TheInternational journal of molecular sciences · 2025Article
- Comprehensive GWAS and Transcriptome Analysis Discovered Candidate Gene Associated with Starch Pasting Properties of Temperate japonica rice (Oryza sativa L.).Rice (New York, N.Y.) · 2025Article
- Genetic improvement of eating and cooking quality of rice cultivars in southern China.Plant biotechnology journal · 2025Article
- Creation of high-resistant starch rice through systematic editing of amylopectin biosynthetic genes in rs4.Plant biotechnology journal · 2025Article
- Development of Whole-Grain Rice Lines Exhibiting Low and Intermediate Glycemic Index with Decreased Amylose Content.Foods (Basel, Switzerland) · 2024Article
- Multiomics of a rice population identifies genes and genomic regions that bestow low glycemic index and high protein content.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- OsCRLK2, a Receptor-Like Kinase Identified by QTL Analysis, is Involved in the Regulation of Rice Quality.Rice (New York, N.Y.) · 2024Article
- Exploring the impact of key physicochemical properties of rice on taste quality and instant rice processing.Frontiers in plant science · 2024Article
- Starch Properties and Morphology of Eight Floury Endosperm Mutants in Rice.Plants (Basel, Switzerland) · 2023Article
- Impacts of Inherent Components and Nitrogen Fertilizer on Eating and Cooking Quality of Rice: A Review.Foods (Basel, Switzerland) · 2023Review
- Mathematical modeling to predict rice's phenolic and mineral content through multispectral imaging.Food chemistry advances · 2022Article
- Effects of Variations in the Chemical Composition of Individual Rice Grains on the Eating Quality of Hybrid Indica Rice Based on Near-Infrared Spectroscopy.Foods (Basel, Switzerland) · 2022Article
- Post-genomics revolution in the design of premium quality rice in a high-yielding background to meet consumer demands in the 21st century.Plant communications · 2022Review
- QTL mapping for starch paste viscosity of rice (Oryza sativa L.) using chromosome segment substitution lines derived from two sequenced cultivars with the same Wx allele.BMC genomics · 2021Article
- Dataset on viscosity and starch polymer properties to predict texture through modeling.Data in brief · 2021Article
- Deploying viscosity and starch polymer properties to predict cooking and eating quality models: A novel breeding tool to predict texture.Carbohydrate polymers · 2021Article
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Acceptance of new rice genotypes demanded by rice value chain depends on premium value of varieties that match consumer demands of regional preferences. High throughput prediction tools are not available to breeders to classify cooking and eating quality (CEQ) ideotypes and to capture texture of varieties. The pasting properties in combination with starch properties were used to develop two layered models in order to classify the rice varieties into twelve distinct CEQ ideotypes with unique sensory profiles. Classification models developed using random forest method depicted the overall accuracy of 96 %. These CEQ models were found to be robust to predict ideotypes in both Indica and Japonica diversity panels grown under dry and wet seasons and across the years. We conducted random forest modeling using 1.8 million high density SNPs and identified top 1000 SNP features which explained CEQ model classification with the accuracy of 0.81. Furthermore these CEQ models were found to be valuable to predict textural preferences of IRRI breeding lines released during 1960-2013 and mega varieties preferred in South and South East Asia.
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