Influence of blue maize flour on gluten-free pasta quality and antioxidant retention characteristics.

Due to its bioactive compounds, blue maize flour is a valuable ingredient for developing gluten-free products. The incorporation of alternative flours into gluten-free pasta is a challenge as it usually results in products that, despite their enhanced nutraceutical features, show reduced quality characteristics. Composite pasta was prepared with variable (25, 50 and 75%) contents of flours from white and blue maize, chickpea and unripe plantain, following a laboratory-scale process.

Starch and antioxidant compound release during in vitro gastrointestinal digestion of gluten-free pasta.

The microstructure of cooked gluten-free pasta depends on the ingredients used, and this microstructure affects the starch hydrolysis (SH), the release of phenolic compounds (PC) and their antioxidant capacity (AC). The aim of this study was to evaluate the SD and bioaccessibility of PC during in vitro gastrointestinal digestion of gluten-free pasta and its relationship with the microstructure. The highest SH was during the intestinal phase (≈60%), but pasta with the highest content of unripe plantain and chickpea presented the lowest release of PC (≈60%).

Multivariable Analysis of Gluten-Free Pasta Elaborated with Non-Conventional Flours Based on the Phenolic Profile, Antioxidant Capacity and Color.

The phenolic compounds, color and antioxidant capacity of gluten-free pasta prepared with non-conventional flours such as chickpea (CHF), unripe plantain (UPF), white maize (WMF) and blue maize (BMF) were analyzed. Fifteen phenolic compounds (five anthocyanins, five hydroxybenzoic acids, three hydroxycinnamic acids, one hydroxyphenylacetic acid and one flavonol) were identified in pasta prepared with blue maize, and 10 compounds were identified for samples prepared with white maize. The principal component analysis (PCA) led to results describing 98% of the total variance establishing a clear separation for each pasta.

Effect on in vitro starch digestibility of Mexican blue maize anthocyanins.

The purpose of this study was to evaluate the effect of blue maize extracts obtained by acid-methanol treatment on the nutritional in vitro starch fractions such as: rapidly digestive starch (RDS), slowly digestive starch (SDS) and resistant starch (RS) of native and gelatinized commercial maize starch. Chromatographic analysis (HPLC-DAD/ESI-MS) of blue maize extracts showed the presence of seven anthocyanins, where cyanidin-3-(6″-malonylglucoside) was the main. Blue maize extracts modified nutritional in vitro starch fractions (decrease of RDS) while RS content increased (1.

Comparative Study of Phenolic Profile, Antioxidant Capacity, and Color-composition Relation of Roselle Cultivars with Contrasting Pigmentation.

Roselle is a plant that accumulates anthocyanins significantly, hence its importance as food coloring and as a source of antioxidant compounds for human health. This study was aimed to determine phenolic composition and antioxidant capacity of methanolic extracts, and beverages obtained from native roselle cultivars in Mexico (Negra, Sudan, Rosa and Blanca) with different degrees of pigmentation, and to establish the color-composition relationship. Chromatographic methods were used to determine phenolic compounds: flavanols, flavonols, benzoic, hibiscus and phenolic acids as well as two main anthocyanins (cyanidin 3-sambubioside and delphinidin 3-sambubioside).

Digital image analysis of diverse Mexican rice cultivars.

Background: Digital image analysis has an important role in geographical provenance of grains, as it can provide parameters of size, shape and color, which are important quality parameters for the design of engineering processes such as drying and milling of grains. In this study, digital image analysis was used to classify nine rice cultivars based on different morphometric parameters using the three sides of the grain (lateral, ventral and axial), Feret diameter, and 10 different form factors and color parameters (CIE L*, a* and b*).

Results: Result of principal component analyisis was an equation with seven variables (area, perimeter, length, width, thickness, sphericity and color), which was useful for distinguishing between nine different cultivars.