β-glucan is a non-starch soluble polysaccharide widely present in yeast, mushrooms, bacteria, algae, barley, and oat. β-Glucan is regarded as a functional food ingredient due to its various health benefits. The high molecular weight (Mw) and high viscosity of β-glucan are responsible for its hypocholesterolemic and hypoglycemic properties. Thus, β-glucan is also used in the food industry for the production of functional food products. The inherent gel-forming property and high viscosity of β-glucan lead to the production of low-fat foods with improved textural properties. Various studies have reported the relationship between the molecular structure of β-glucan and its functionality. The structural characteristics of β-glucan, including specific glycosidic linkages, monosaccharide compositions, Mw, and chain conformation, were reported to affect its physiochemical and biological properties. Researchers have also reported some chemical, physical, and enzymatic treatments can successfully alter the molecular structure and functionalities of β-glucan. This review article attempts to review the available literature on the relationship of the molecular structure of β-glucan with its functionalities, and future perspectives in this area.

In China, peanut sprouts are popular among consumers as functional vegetables. This study reports the change in total phenolic content (TPC), total flavonoid content (TFC), monomeric anthocyanin content (MAC), vitamin C, trans-resveratrol content, antioxidant capacities, and phenolic profile of three different varieties of peanut during 8 days of germination. The TPC, TFC, and antioxidant capacity of peanut samples were reduced and then increased with an increase in germination time. TFC values were highly correlated with 2,2-diphenyl-1-picrylhydrazyl (DPPH) and ferric reducing antioxidant power (FRAP) values. MAC values of peanuts were first increased and then decreased during 8 days of germination. The TFC, DPPH, and FRAP values of germinated peanuts were lower compared to the non-germinated peanut. Germination of peanut samples enhanced the total phenolic acids and trans-resveratrol content, but the vitamin C content of peanut sprouts was lower than ungerminated peanuts.

China is a major producer of various kinds of food legumes. Some of the under-utilized food legumes are consumed by the local society from different areas in China. The antioxidant capacity and phytochemical profile of these under-utilized food legumes haven’t been investigated until now. In this study, colorimetric and high-performance liquid chromatography was employed to explore the antioxidant capacity and phytochemical profile of 21 under-utilized food legumes. Different legumes under investigation exhibit a wide range of variations in their total phenolic content (TPC), total flavonoids content (TFC) and condensed tannins content (CTC). Among all the legume samples, the velvet bean from Hechi, Guangxi exhibited the highest antioxidant capacity while the white flat bean from Shangrao, Shanxi presented the least antioxidant capacity. Gallic acid was observed to be a major phenolic acid and its content in the velvet bean was significantly higher compared to the other legume samples explored in this study. The composition of flavonoids was different among all the legumes. Kaempferol was observed to be the most predominant flavonoid. The findings of this study will be beneficial for plant breeders, food scientists and consumers for the better selection of germplasm with a high level of phytochemicals that in turn possess maximum health benefits.

This study aimed to systematically assess the phenolic profiles and antioxidant capacities of 21 chestnut samples collected from six geographical areas of China. All these samples exhibit significant differences (p < 0.05) in total phenolic contents (TPC), total flavonoids content (TFC), condensed tannin content (CTC) and antioxidant capacities assessed by DPPH free radical scavenging capacity (DPPH), ABTS free radical scavenging capacities (ABTS), ferric reducing antioxidant power (FRAP), and 14 free phenolic acids. Chestnuts collected from Fuzhou, Jiangxi (East China) exhibited the maximum values for TPC (2.35 mg GAE/g), CTC (13.52 mg CAE/g), DPPH (16.74 μmol TE/g), ABTS (24.83 μmol TE/g), FRAP assays (3.20 mmol FE/100 g), and total free phenolic acids (314.87 µg/g). Vanillin and gallic acids were found to be the most abundant free phenolic compounds among other 14 phenolic compounds detected by HPLC. Overall, the samples from South China revealed maximum mean values for TPC, CTC, DPPH, and ABTS assays. Among the three chestnut varieties, Banli presented prominent mean values for all the assays. These finding will be beneficial for production of novel functional food and developing high-quality chestnut varieties.

The paper demonstrates a low-cost rice quality assessment system based on image processing and machine learning (ML) algorithms. A Raspberry-Pi based image acquisition module was developed to extract the structural and geometric features from 3081 images of eight different varieties of rice grains. Based on features such as perimeter, area, solidity, roundness, compactness, and shape factor, an automatic identification system is developed to segment the grains based on their types and classify them by using seven machine learning algorithms. These ML models are trained using the images and are compared using different ML models. ROC curves are plotted for each model for quantitative analysis to assess the model’s performance. It is concluded that the random forest classifier presents an accuracy of 77 percent and is the best-performing model for the classification of rice varieties. Furthermore, the same algorithm is efficiently employed to determine the price of adulterated rice samples based upon the market price of individual rice.