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Nonhypothesis Analysis of a Mutagenic Soybean ( Glycine max [L.]) Population for Protein and Fatty‐Acid Composition
Author(s) -
Anderson James,
Lakhssassi Naoufal,
Kantartzi Stella K.,
Meksem Khalid
Publication year - 2018
Publication title -
journal of the american oil chemists' society
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.512
H-Index - 117
eISSN - 1558-9331
pISSN - 0003-021X
DOI - 10.1002/aocs.12063
Subject(s) - stearic acid , oleic acid , population , fatty acid , food science , biology , microbiology and biotechnology , multivariate analysis of variance , biochemistry , selection (genetic algorithm) , mutant , gene , chemistry , mathematics , computer science , statistics , demography , organic chemistry , sociology , artificial intelligence
Soybean is a major source of oil for food, feed, and biofuel production. Mutagenesis is a tool for creating unique traits useful in breeding programs. The aim of this study is to use nonhypothesis statistical testing methods to make decisions about a mutagenic population. To this end, a total of 1037 mutation lines and 28 wild‐type lines were analyzed for fatty‐acid composition and protein content. Principal component analysis (PCA) was used to analyze the fatty acid profile, multivariate analysis of variance (MANOVA) to build a selection model for seed weight per plant and weight per 10 seeds, and clustering in conjunction with power analysis to determine the minimum number of individuals needed to create a MANOVA selection model for the oil to protein content. Five of the 35 possible entries were identified by PCA analysis for stearic acid and four of 16 possible entries for oleic acid. Interestingly, most of the selected mutants were validated genetically. In fact, selected mutants with high seed stearic acid or high seed oleic acid contents were verified to carry mutations on GmFAD2‐1A , GmFAD2‐1B , and GmSACPD‐C genes. This shows a promising method of identifying smaller portion of the population to screen for desired mutations.