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Proposed Methodology for Quality Preselection of Rice Populations
Author(s) -
Moreira Adriane M.,
Bassinello Priscila Z.,
Caliari Márcio,
Borba Tereza C. O.
Publication year - 2014
Publication title -
cereal chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.558
H-Index - 100
eISSN - 1943-3638
pISSN - 0009-0352
DOI - 10.1094/cchem-08-13-0152-r
Subject(s) - selection (genetic algorithm) , amylose , cultivar , population , microbiology and biotechnology , trait , statistics , brown rice , mathematics , breeding program , quality (philosophy) , agricultural engineering , food science , agronomy , biology , machine learning , engineering , computer science , starch , philosophy , demography , epistemology , sociology , programming language
The evaluation of culinary and sensory characteristics of a particular cultivar is an important trait for rice grain quality because it guides decisions for breeding programs and allows the prediction of rice market acceptance. The aim of this study was to apply direct and indirect tests for the characterization of the grain quality in a segregating rice population under different treatments (2 × 2). A methodology was proposed from the data based on mathematical equations to aid rice breeding programs in the preselection of promising genotypes. Grain samples were evaluated for apparent amylose content, gelatinization temperature, and viscoamylographic profile. In addition, the samples were subjected to a cooking test. The evaluated parameters were weighted and grouped into two linear equations, yielding scores that were subjected to the selection criteria. Using this methodology, families of the studied population were preselected, which reduced the number of samples for final selection by at least 76%. The physical‐chemical analysis did not indicate a direct positive correlation to accurately infer the culinary and sensorial quality of the rice for human consumption, but this analysis was shown to be useful in the preselection of lineages through the proposed strategy.