Purification and identification of rice bran (Oryza sativa L.) phenolic compounds with in-vitro antioxidant and antidiabetic activity using macroporous resins

This study was designed to establish an efficient purification method for phenolic compounds from rice bran and to acquire insightful knowledge of purification impact on its chemical constituents, antioxidant and antidiabetic activity. Among the eight macroporous resins investigated, HPD-300 resin was verified to bosses superior adsorption and desorption qualities for the extract. Purification parameters were optimised. Eighteen phenolic compounds were identified using HPLC-PDA, the contents of ferulic acid and syringaldehyde were significantly (P < 0.05) higher than the other constituents. However, phenolic compounds concentrations varied significantly (P < 0.05) after HPD-300 resin purification. In addition, the extract exhibited a significant (P < 0.05) increase in total flavonoid contents, in vitro antioxidant (DPPH and FRAP) and antidiabetic (α-glucosidase and BSA-glycation inhibition) activity after HPD-300 resin treatment. These findings indicate that selection of resin and applying optimal purification condition is an appropriate economical approach for obtaining bioactive phenolic compounds from rice bran.     

Hybridized approach of image segmentation in classification of fruit mango using BPNN and discriminant analyzer

In machine learning, image classification accuracy generally depends on image segmentation and feature extraction methods with the extracted features and its qualities. The main focus of this paper is to determine the defected area of mangoes using image segmentation algorithm for improving the classification accuracy. The Enhanced Fuzzy based K-means clustering algorithm is designed for increasing the efficiency of segmentation. Proposed segmentation method is compared with K-means and Fuzzy C-means clustering methods. The geometric, texture and colour based features are used in the feature extraction. Process of feature selection is done by Maximally Correlated Principal Component Analysis (MCPCA). Finally, in the classification step, severe portions of the affected area are analyzed by Backpropagation Based Discriminant Classifier (BBDC). Proposed classifier is compared with BPNN and Naive Bayes classifiers. The images are classified into three classes in final output like Class A –good quality mango, Class B-average quality mango, and Class C-poor quality mango. Finally, the evaluated results of the proposed model examine various defected and healthy mango images and prove that the proposed method has the highest accuracy when compared with existing methods.

     

Nanomaterial‐based biosensors for sensing key foodborne pathogens: Advances from recent decades

Foodborne pathogen contamination has become a severe threat to human health. Traditional methods for foodborne pathogen detection have several disadvantages, including long detection time, low sensitivity, and low selectivity. The emergence of multiple excellent nanomaterials enables the construction of novel biosensors for foodborne pathogen detection. Based on the outstanding properties of nanomaterials, the novel biosensors possess the advantages of sensitivity, specificity, rapidity, accuracy, and simplicity. The present review comprehensively summarizes the advanced biosensors, including electrochemical, colorimetric, fluorescent, and surface enhanced Raman scattering biosensors for sensing key foodborne pathogens in recent decades. Furthermore, several issues are identified for further exploration, and possible directions for the development of biosensors are discussed.     

Phytosterols and their derivatives: Potential health‐promoting uses against lipid metabolism and associated diseases,mechanism, and safety issues

Consumption of phytosterols (PSs), the plant‐based analogs of cholesterol, can reduce serum cholesterol levels. This review discusses the current state of the art into the research of the structural features and dietary sources of PSs and their derivatives. The effect of PSs on individual lipid metabolites is summarized in the present review. PS‐related nonalcoholic fatty liver disease (NAFLD), obesity, and the alleviation of inflammatory bowel diseases are discussed. PSs reduce the risk of having NAFLD by improving the blood biochemical parameters related to lipid transport and metabolism. However, current research on the circulating PSs indicates its safety concern regarding fatty liver disease induction. In addition, PS oxidation products exhibit pro‐atherogenic properties, cytotoxicity oxidative stress, apoptosis, and pro‐inflammatory properties. Further research is needed to investigate the bioavailability and safety issues of PSs and their derivatives in animal models and clinical trials.