Rice and common bean blends: Effect of cooking on in vitro starch digestibility and phenolics profile

Application of spectroscopic technology with machine learning in Chinese herbs from seeds to medicinal materials: The case of genus Paris

To ensure the safety and efficacy of Chinese herbs, it is of great significance to conduct rapid quality detection of Chinese herbs at every link of their supply chain. Spectroscopic technology can reflect the overall chemical composition and structural characteristics of Chinese herbs, with the multi-component and multitarget characteristics of Chinese herbs. This review took the genus Paris as an example, and applications of spectroscopic technology with machine learning (ML) in supply chain of the genus Paris from seeds to medicinal materials were introduced. The specific contents included the confirmation of germplasm resources, identification of growth years, cultivar, geographical origin, and original processing and processing methods. The potential application of spectroscopic technology in genus Paris was pointed out, and the prospects of combining spectroscopic technology with blockchain were proposed. The summary and prospects presented in this paper will be beneficial to the quality control of the genus Paris in all links of its supply chain, so as to rationally use the genus Paris resources and ensure the safety and efficacy of medication.

Ferulic Acid—A Brief Review of Its Extraction, Bioavailability and Biological Activity

Ferulic acid is a widespread phenolic compound that occurs in seeds and leaves, both in its free form and conjugated to polysaccharides, carbohydrates, glycoproteins and lignins in the plant cell walls. It exhibits various biological activities, like antioxidant, anticarcinogenic, anti-inflammatory, hepatoprotective, antimicrobial, and antiviral activity, and it modulates enzyme activity. Given these wide potential health benefits, ferulic acid has attracted considerable research interest and may be considered a biomolecule with strong prospects as a functional food ingredient. Great attempts have been made to enhance its extraction process and recovery from natural matrices and agro-industrial wastes for its various applications relating to human health and nutrition. This review presents the recently available information on the extraction methods for quantifying ferulic acid in different samples, along with its bioavailability and stability in processing foods and biological activities.

Rapid and Nondestructive Identification of Origin and Index Component Contents of Tiegun Yam Based on Hyperspectral Imaging and Chemometric Method

Tiegun yam is a typical food and medicine agricultural product, which has the effects of nourishing the kidney and benefitting the lungs. The quality and price of Tiegun yam are affected by its origin, and counterfeiting and adulteration are common. Therefore, it is necessary to establish a method to identify the origin and index component contents of Tiegun yam. Hyperspectral imaging combined with chemometrics was used, for the first time, to explore and implement the identification of origin and index component contents of Tiegun yam. The origin identification models were established by partial least squares-discriminant analysis (PLS-DA), support vector machine (SVM), and random forest (RF) using full wavelength and feature wavelength. Compared with other models, MSC-PLS-DA is the best model, and the accuracy of the training set and prediction set is 100% and 98.40%. Partial least squares regression (PLSR), random forest (RF), and support vector regression (SVR) models were used to predict the contents of starch, polysaccharide, and protein in Tiegun yam powder. The optimal residual predictive deviation (RPD) values of starch, polysaccharide, and protein prediction models selected in this study were 5.21, 3.21, and 2.94, respectively. The characteristic wavelength extracted by the successive projections algorithm (SPA) method can achieve similar results as the full-wavelength model. These results confirmed the application of hyperspectral imaging (HSI) in the identification of the origin and the rapid nondestructive prediction of starch, polysaccharide, and protein contents of Tiegun yam powder. Therefore, the HSI combined with the chemometric method was available for conveniently and accurately determining the origin and index component contents of Tiegun yam, which can expect to be an attractive alternative method for identifying the origin of other food.

Simulated Digestion of the Pigmented Legumes' (Black Chickpea (Cicer arietinum L.) and Brown Lentil (Lens culinaris Medikus) Phenolics to Estimate Their Bioavailability

This study simulated the gastrointestinal digestion (GID) of black chickpeas (BC) and brown lentils (BL). BC phenolics increased from 105.01 to 141.86 mg GAE/100 g DW) while the BL phenolics decreased from 143.26 to 132.70 mg GAE/100 g DW after cooking. In contrast, the remaining flavonoids after cooking were higher in BL (325.55 mg RE/100 g DW). After in vitro GID, moderate levels of flavonoids were detected in the colon (OUT) fractions (144.36 and 104.22 mg RE/100 g DW for cooked BC and BL, respectively). The highest TAA levels were detected as by CUPRAC assay, in cooked and in vitro GID BC (517.03 mg TEAC/100 g DW) and BL (604.98 mg TEAC/100 g DW) samples. Catechin was the most abundant compound detected in BC samples, while gallic acid was the most abundant in BL. BC and BL have unique and superior benefits for health when compared with conventional legumes. The possible interactions between their remaining phenolics and other bioactive components in the colon are promising for their widespread consumption.

The final fate of food: On the establishment of in vitro colon models

The search for life/health quality has driven the search for a better understanding of food components on the overall individual health, which turns to be intrinsically related to the digestive system. In vitro digestion models are considered an alternative for the in vivo studies for a variety of practical reasons, but further research is still needed concerning the colon model establishment. An effective in vitro colon model should consider all unit operations and transport phenomena, together with chemical and biochemical reactions, material handling and reactor design. Due to the different techniques and dependence on the donor microbiota, it is difficult to obtain a standard protocol with results reproductible in time and space. Furthermore, the colon model should be fed with a representative substrate, thus what happens in upper digestion tract and absorption prior to colon is also of crucial importance. Essentially, there are two ways to think about how to achieve a good and useful in vitro colon model: a complex biomimetic system that provides results comparable with the in vivo studies or a simple system, that despite the fact it could not give physiologically relevant data, it is sufficient to understand the fate of some specific components.