Metabolomics aims at determining a sample's metabolites profile and hence provides a straight functional statement of an organism's physiological condition. Here, we investigated comprehensive profiling, natural variation and species-specific accumulation of both primary and secondary metabolites in foxtail millet using LC-MS, and inheritance patterns of metabolome in millet hybrids. The application of a broad target metabolomics method facilitated the simultaneous identification and quantification of more than 300 metabolites. The metabolic analysis of these compounds, such as flavonoids, phenolamides, hydrocinnamoyl derivatives, vitamins and LPCs, revealed their developmentally controlled accumulation, and natural variation in different tissues/varieties. Species-specific accumulation of secondary metabolites was observed based on a comparative metabolic analysis between millet and rice, such as flavonoid O-rutinosides/neohesperidosides and malonylated flavonoid O-glycosides. In analyzing the metabolic variations between hybrid progenies and their parental lines, including a photothermo-sensitive genic male sterility line and five Zhangzagu varieties, metabolic overdominant, and dominant patterns of inheritance could be observed. For example, hydrocinnamoyl derivatives and feruloylated flavonoids were identified as over-parent heterosis (overdominant) metabolites in milet hybrids. Our work paves the way for developing predictors of hybrid performance and the future analysis of the biosynthesis and regulation of relevant metabolic pathways in millet.
Background and objectives The aim of this study was to construct near‐infrared reflectance spectroscopy (NIRS) models to test the contents of apparent amylose, total starch, and crude protein for both foxtail millet grain and dehusked millet grain. The construction of models is based on chemical values and optimized spectral data of 111 core foxtail millet germplasm materials after analyzation of partial least square (PLS) method with cross‐validation. Findings Model calibration showed that there was better fitting degree of dehusked millet grain than that of foxtail millet. The coefficient determination for calibration (Rc2) of former is >0.843, while that of latter is >0.823. The coefficient determination of prediction (Rp2) of each component ranged from 0.794 to 0.888 for foxtail millet grain and 0.833 to 0.970 for dehusked millet grain. Conclusions The constructed NIRS models of both samples can be used to rapidly test foxtail millet quality, and the nondestructive nature of foxtail millet grain‐based test (which maintains seed vigor) better meets the requirements of the breeding, although the accuracy needs to be further improved. Significance and novelty This study developed a rapid method to detect the main nutritional quality for foxtail millet using two different samples, which can be used in germplasm resource innovation and contribute to the acceleration of cereal breeding.
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