Bioactive components are partially responsible for the nutritional and health benefits of soybeans. Four major bioactive components: isoflavones, oligosaccharides, phospholipids, and saponins, were quantified in 763 soybean samples collected from widely distributed regions across China from 2010 to 2013. A majority of the tested bioactive components showed generally declining trends from the north (high latitude) to the south (low latitude). A positive relationship between total oligosaccharides (TO) and altitude was observed. Total isoflavones (TI), phospholipids (TP) and TO were negatively correlated with cumulative temperature above or equal to 15 ℃ (AT₁₅) and mean daily temperature (MDT), but positively correlated with diurnal temperature range (DTR) and hours of sunshine (HS). Total saponins (TS) were negatively correlated with MDT but positively correlated with rainfall (RF), whereas TO were negatively correlated with RF. Path-coefficient analysis showed that, besides genotype differences, temperature and HS during the reproductive period influenced TI and TP contents, while temperature and RF influenced TS and TO. The effects of weather factors on soybean bioactive components in diverse regions of China were characterized. These findings will be helpful in promoting soybean production for functional food purposes.

Interest in mung bean (Vigna radiata L.) as a functional food is growing; however, studies on the nutritional composition of major mung bean cultivars planted in China are limited. Twenty Chinese mung bean cultivars were collected and their nutritional compositions including starch, fat, protein, and phytochemicals were analyzed. The cultivars were found to have a high amount of resistant starch, accounting for 16.1%–22.3% of total starch, and balanced amino acid constitutions. Palmitic acid and linoleic acid were the two dominant fatty acids, accounting for respectively 32.4% and 36.1% of all of the assayed fatty acids. Four bound phenolic acids (syringic, caffeic, p-coumaric, and ferulic acids) and two free phenolic acids (caffeic and ferulic acids) were identified by HPLC. The antioxidant activity of 70% ethanol extracts from the 20 mung bean cultivars was evaluated. Their DPPH and ABTS⁺ free-radical-scavenging capacity ranged from 28.13 ± 2.24 to 35.68 ± 0.71 μmol g⁻¹ and from 3.82 ± 0.25 to 13.44 ± 1.76 μmol g⁻¹, respectively. Significant positive correlations of ABTS⁺ free-radical-scavenging capacity with total phenolic acids and total flavonoid contents were observed. These results suggest that Chinese mung bean cultivars are rich in balanced nutrients and that their phytochemicals should be considered as potential sources of natural antioxidants.

The objective of this study was to characterize the phaseolin type and α-amylase (αAI) level in common bean (Phaseolus vulgaris L.) accessions deposited in the Chinese National Genebank. The 40 accessions sampled were common varieties originating in Asia, North America, South America, Europe, and Africa. No Inca (I-) phaseolin was observed in the accessions. Only four accessions contained Tendergreen (T-) phaseolin and the remaining 36 contained Sanilac (S-) phaseolin. αAI proteins extracted from nine accessions showed higher α-amylase inhibitory activity than the control (Phase 2, IC₅₀ = 0.65 μg). These common bean accessions have potential use as nutraceutical ingredients.

To analyze the nutritional composition of faba bean (Vicia faba L.) seed, estimation models were developed for protein, starch, oil, and total polyphenol using near infrared spectroscopy (NIRS). Two hundred and forty-four samples from twelve producing regions were measured in both milled powder and intact seed forms. Partial least squares (PLS) regression was applied for model development. The model based on ground seed powder was generally superior to that based on the intact seed. The optimal seed powder-based models for protein, starch, and total polyphenol had coefficients of correlation (r²) of 0.97, 0.93 and 0.89, respectively. The relationship between nutrient contents and twelve producing areas was determined by two-step cluster analysis. Three distinct groupings were obtained with region-constituent features, i.e., Group 1 of high oil, Group 2 of high protein, and Group 3 of high starch as well as total polyphenol. The clustering accuracy was 79.5%. Moreover, the nutrition contents were affected by seeding date, longitude, latitude, and altitude of plant location. Cluster analysis revealed that the differences in the seed were strongly influenced by geographical factors.