Abstract

This study aims to establish the discrimination of F1 hybrid seeds from their parental lines and rapid selection of proteinrich lines from inbreeding lines of corn using FT-IR spectroscopy combined by multivariate analysis. Eight individual seeds from the maternal and paternal lines of Gwangpyeongok and their F1 progeny seeds were subjected to FT-IR spectroscopy. A total of 176 corn inbreeding lines including commercial corn cultivars were subjected to FT-IR spectroscopy. To establish the prediction model for total protein content from corn seed, 33 corn inbreeding lines out of 176 were randomly selected and total seed protein contents using Bradford assay were examined. PLS-DA (partial least square regression discriminant analysis) could clearly discriminate F1 hybrid seeds from their parental lines. PC (principal component) loading values show that 1,700 – 1,500 cm−1 and 1,200 – 900 cm−1 regions of FT-IR spectra are significantly important for discrimination of corn lines. The prediction model for total protein contents was established by PLS (partial least square regression) algorithm, and its accuracy was confirmed by cross-validation test (R2 = 0.94). After external validation fromexternal 25 corn inbreeding lines, regression coefficient (R2) was 0.78 which indicated that the prediction model had relatively good accuracy. Thus, considering these results we suggest that FT-IR combined with multivariate analysis could be applied as a novel tool for high-throughput screening of F1 hybrid seeds from their parental lines and protein-rich lines for breeding of silage corn cultivar.

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