Optimizing BP neural network algorithm for Pericarpium Citri Reticulatae (Chenpi) origin traceability based on computer vision and ultra-fast gas-phase electronic nose data fusion.

This study utilized computer vision to extract color and texture features of Pericarpium Citri Reticulatae (PCR). The ultra-fast gas-phase electronic nose (UF-GC-E-nose) technique successfully identified 98 volatile components, including olefins, alcohols, and esters, which significantly contribute to the flavor profile of PCR. Multivariate statistical Analysis was applied to the appearance traits of PCR, identifying 57 potential marker-trait factors (VIP > 1 and P < 0.05) from the 118 trait factors that can distinguish PCR from different origins. These factors include color, texture, and odor traits. By integrating multivariate statistical Analysis with the BP neural network algorithm, a novel artificial intelligence algorithm was developed and optimized for traceability of PCR origin. This algorithm achieved a 100% discrimination rate in differentiating PCR samples from various origins. This study offers a valuable reference and data support for developing intelligent algorithms that utilize data fusion from multiple intelligent sensory technologies to achieve rapid traceability of food origins.

Vitamin A Nutritional Status of Urban Lactating Chinese Women and Its Associated Factors.

We aimed to investigate dietary vitamin A (DVA) intake, serum vitamin A (SVA) concentrations, and breast milk vitamin A (BMVA) concentrations of urban lactating Chinese women and explore the associated factors. We recruited 326 lactating women from ten cities in China and collected their dietary information, blood samples, and breast milk samples. SVA and BMVA were assessed with high-performance liquid chromatography. Mann-Whitney U tests, Kruskal-Wallis H tests, Chi-square tests, Spearman correlation tests, and multiple regression analyses were conducted. The median (25th, 75th) of DVA, SVA and BMVA were 372.36 (209.12, 619.78) µg RAE/day, 1.99 (1.71, 2.35) µmol/L, and 1.67 (1.13, 2.15) µmol/L, respectively. Only 3.1% of lactating women met the recommended nutrient intake of Vitamin A (VA), and 20.6% had a BMVA level below 1.05 µmol/L. Compared to underweight or normal weight women, overweight or obese lactating women had lower DVA and BMVA but higher SVA (p = 0.022; p = 0.030; p = 0.003). Multiparous women had a higher risk of inadequate BMVA (p = 0.023) than primiparous women. SVA and BMVA were positively associated with DVA, especially for lactating women not using VA supplements (ß = 0.174, 95%CI = 0.025, 0.324, p = 0.022; ß = 0.501, 95%CI = 0.208, 0.795, p = 0.001). There was no association between SVA and BMVA (ß = 0.165, 95%CI = -0.037, 0.366, p = 0.109). In conclusion, VA nutritional status among Chinese urban lactating women needs more attention, especially for those who are obese, overweight, or higher parity. Increased DVA may contribute to increased BMVA.