Foxtail millet, a traditional cereal crop, has gained increasing attention for its high nutritional value and potential health benefits. This study aimed to investigate the simultaneous and rapid detection of amylose and amylopectin content of foxtail millet flour under different sheep manure application rates by hyperspectral imaging combined with chemometrics. The spectral data preprocessing used multiplicative scatter correction (MSC), and the combined algorithm of competitive adaptive reweighted sampling (CARS), random frog (RF), iterated retaining informative variables (IRIV) were employed for key band extraction. The partial least squares regression (PLSR) was then used to establish the prediction model and the regression equation, that was used to visualize the two components. Results demonstrated the key band extraction combined algorithm effectively reduced data dimension without compromising the accuracy of the prediction model. The prediction model for amylose using MSC-RF-IRIV-PLSR exhibited good performance, with the correlation coefficient (R) and root mean square error (RMSE) predicted to be 0.73 and 1.23, respectively. Similarly, the prediction model for amylopectin using MSC-CARS-IRIV-PLSR also demonstrated good performance, with the R and RMSE predicted to be 0.59 and 7.34, respectively. Then, the visualization graph generated clearly shows under the condition of applying 6 m3 of sheep manure, the amount of amylopectin accumulation was highest, and the amount of amylose was lowest. The experimental results offer valuable insights for the rapid detection of nutritional components in foxtail millet, serving as a basis for further research.

The grain filling rate (GFR) plays a crucial role in determining grain yield. However, the regulatory and molecular mechanism of grain filling rate (GFR) in foxtail millet remains unclear. In this study, we found the GFR of 'Changnong No.47' (CN47) was significantly higher at 14 days after flowering (DAF) and 21 DAF in comparison to 'Changsheng 13' (CS13). Furthermore, CN47 also exhibited higher thousand grain weight and yield than CS13. Therefore, we conducted transcriptomics and metabolomics to analyze the biological processes and functional genes associated with GFR during two stages of grain filling in both cultivars. A total of 765 differentially expressed genes (DEGs) and 246 differentially accumulated metabolites (DAMs) were identified at the 14 DAF stage, while at the 21 DAF stage, a total of 908 DEGs and 268 DAMs were identified. The integrated analysis of co-mapped DAMs and DEGs revealed enriched pathways, including flavonoid biosynthesis, plant hormone signal transduction, tyrosine metabolism, ATP-binding cassette (ABC) transporters, beta-alanine metabolism, as well as stilbenoid, diarylheptanoid and gingerol biosynthesis. In order to elucidate their potential functions in the context of GFR, we developed a gene-metabolite regulatory network for these metabolic pathways. Notably we found some genes associated with ABC transporters and plant hormone signal transduction pathway were implicated in auxin transport and signal transduction, highlighting the crucial role of auxin during grain filling. The results provide initial insights into the regulatory and molecular mechanisms underlying GFR in foxtail millet, as well as offer valuable genetic resources for further elucidation of GFR in future studies. The findings have established a theoretical basis for improving the efficiency of yield breeding in foxtail millet.

Foxtail millet (Setaria italica (L.) P. Beauv) is an important food and forage crop that is well adapted to nutrient-poor soils. However, little is known about how foxtail millet adapts to low nitrogen (LN) at the physiological and molecular levels. In the present study, two foxtail millet varieties with contrasting low nitrogen (LN) tolerance properties were investigated through integrative analyses of physiological featureparameters and transcriptomics. The physiological results showed that JG20 (high tolerance to LN) had higher biomass accumulation, nitrogen content and nitrogen use efficiency compared with JG22 (low tolerancesensitive to LN) under LN. JG20 had higher soluble sugar and soluble protein concentration in shoots compared with JG22 under LN, while contcentrations of soluble sugar and soluble protein contents were higher in the roots of JG22. Higher levels of CTK contentzeatin concentration were found in the shoots of JG20 com-pared with JG22, and a higher ABA contcentration was found in both the shoots and roots of JG22 compared with JG20 under LN. In the transcriptomics results, JG20 had more differentially ex-pressed genes (DEGs) than JG22 both in shoots and roots in response to LN. These LN-responsive genes were enriched in glycolysis, starch and sucrose metabolism, photosynthesis, biosynthesis of amino acids, hormone metabolism and nitrogen metabolism. Furthermore, the high-affinity nitrate transporter gene, SiNRT2.1, and glutamine synthetase gene, SiGS5, chlorophyll apoprotein of photosystem II gene, SiPsbQ, ATP synthase subunit gene, b, auxin-responsive protein gene, SiIAA25, and aldose 1-epimerase gene, SiAEP, in shoots, and high-affinity nitrate transporter gene, SiNRT2.3, SiNRT2.4, and glutamate synthase gene, SiGOGAT2, auxin-responsive protein gene, SiIAA4, fructose-bisphosphate aldolase gene, SiAEP5, in root, were important genes in-volved in the LN tolerance of foxtail millet. These results provide a detailed description of the physiological and transcriptome response of foxtail millet under LN condition.