(1) Background: In order to study the effects of different electric cookers on the nutritional components of millet porridge, five different electric cookers (No. 1–5) were selected to cook millet porridge, then sensory and nutritional components in millet porridge, millet soup, and millet grains were analyzed; (2) Methods: Using principal component and cluster analysis, a variety of nutritional components were comprehensively compared; (3) Results: The results showed that among the different cooked samples, the content of amylose and reducing sugars was the highest in the samples cooked by electric cooker No. 3. The electric cooker No. 4 samples had the highest sensory evaluation score, crude fat, and protein content. The contents of ash, fatty acids, bound amino acids, and minerals were the highest in the electric cooker No. 5 samples. The sensory evaluation score and content of crude fat, ash, reducing sugars, direct starch, and Cu were higher in millet grains than in millet soup or porridge. The content of fatty acids, protein, amino acid, Zn, Fe, Mg, Mn, and Ca was highest in millet soup. Different electric cookers produced millet porridge with varying nutritional levels; (4) Conclusions: This study provides a reference for the further development of new electric cookers.

In order to improve the nutritional value and quality of steamed bread, and promote the industrial development of the whole-grain food industry, a texture analyzer was used to study the effects of cultivars of whole foxtail millet flour (WFMF) on the texture of Chinese steamed bread (CSB). Orthogonal partial least squares discriminant analysis (OPLS-DA) was also conducted. The addition of different cultivars of WFMF significantly altered the height–diameter ratio, specific volume, hardness, cohesiveness, gumminess, and chewiness of CSB (p < 0.05). Large amounts of foxtail millet flour significantly increased the hardness, gumminess and chewiness of the bread (p < 0.05), and the bread height–diameter ratio, specific volume, cohesiveness and springiness significantly decreased (p < 0.05). We screened sensory evaluation, chewiness, specific volume, and hardness as the signature differences in the quality components according to the variable influence on the projection (VIP) values. OPLS-DA could distinguish the addition levels of different samples.