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Analysing nine rice bran extracts with different γ-oryzanol concentrations revealed cytotoxic effects on four human tumour cell lines.

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Seed and flour characteristics of 79 chickpea (Cicer arietinum L.) accessions from a representative collection of the germplasm used by European breeders were evaluated. The accessions were grouped according to desi or kabuli types and by different seed traits (size, shape, colour, surface). The variation in nutritional composition was assessed by principal component analysis (PCA) of data from 13 quality parameters. The first PCA component discriminated the accessions by basic composition (protein, fibre, fat) plus δ-tocopherol, and the second by carotenoid composition (zeaxanthin). Whereas desi types showed higher protein and fibre, kabuli accessions exhibited higher fat contents. The majority of accessions analysed showed very low (<1%) resistant starch content. Higher carotenoid concentration was obtained in desi-type accessions and it was related to specific seed traits: small seed size, angular shape and black colour. Besides discrimination between desi and kabuli groups, the detected associations of classes of shape, size and colour seed traits can be explored in chickpea-quality breeding programs. Several accessions showed higher concentrations of α-tocopherol (>200 μg g–1). LEGCA728, with green colouring in the seed coat and cotyledons, showed exceptional lutein concentration (28.32 μg g–1). We conclude that the chickpea germplasm in use by European breeders presents high potential for improvement of nutritional and health-benefit components not yet routinely implemented in the breeding of this important pulse crop.

Pea is one of the most produced and consumed pulse crops around the world. The study of genetic variability within pea germplasm is an important tool to identify outstanding accessions with optimal functional and nutritional qualities. In the present study, a collection of 105 pea accessions was analysed for physicochemical properties, pasting viscosity, and basic composition parameters. While pasting viscosities were negatively correlated to hydration capacity, cooking time, and basic composition, a positive correlation was found between the hydration capacity and the basic composition parameters. Basic composition (protein, fibre, fat, and resistant starch) parameters were further evaluated regarding seed trait morphology, namely, seed shape, colour, and surface. Allelic characterisation at the r and rb genetic loci was performed in a subgroup of 32 accessions (3 phenotyped as smooth and 29 as rough seeded), revealing that none of the initially classified rough-seeded accessions were rb mutants, 19 were r mutants, and 13 were neither r nor rb. Despite their initial phenotypic classification, the 13 accessions genetically classified as smooth behaved differently (p < 0.05) to the 19 r mutants in terms of physicochemical properties, pasting viscosity, and basic composition parameters. Using multivariate analysis of the most discriminatory parameters for the food-related traits studied, the best-performing accessions at functional and nutritional levels were identified for future plant breeding to improve field pea production and consumption.

Development of food products from legume flours is increasing. Seed and flour characteristics must be analysed for selection of the best screening quality traits. With this purpose, germplasm collections of faba bean (Vicia faba), chickpea (Cicer arietinum), lentil (Lens culinaris) and grass pea (Lathyrus sativus) were evaluated for their physico-chemical, pasting and cooking characteristics. The accessions were grouped accordingly to several seed traits (size, shape, colour, variety and surface) that affected final viscosity, cooking time, hydration capacity and seed weight. In general, seed weight was correlated with hydration capacity. Among species, faba bean revealed higher values of pasting parameters. Cooking time was significantly negatively correlated with final viscosity (–0.298) and positively correlated with seed weight (0.601). The general variance was analysed by using principal component analysis, which allowed identification of specific accessions with important traits such as higher protein or fibre content, hydration capacity or seed weight.

The present study was aimed at studying the physico-chemical and functional properties of 31 Portuguese common bean varieties. In addition, the whole bean flours (WBF) and starch isolates (SI) of three representative bean varieties and their rice: bean blends (70:30; 50:50) were assessed for amylose content, thermal and pasting properties in view of supplementation in rice based processed foods. Bean varieties showed significant differences in protein content (20.78-27.10%), fat content (1.16-2.18%), hydration capacity (95.90-149.30%), unhydrated seeds (4.00-40.00%), γ tocopherol (3.20-98.05 mg/100 g fat), δ tocopherol (0.06-4.72 mg/100 g fat) and pasting behavior. Amylose content of WBF (11.4-20.2%) was significantly lower than rice flour (23.51%) whereas SI of beans (40.00-47.26%) had significantly higher amylose content than SI of rice (28.13%). DSC results showed that WBF (11.4-20.2 °C) had significantly broader and lower gelatinization temperature range (∆Tr) than corresponding SI (20.9-23.1 °C). WBF had significantly lower pasting viscosity due to low starch content and compositional matrix effect as compared to SI. Setback viscosities of WBF and rice: bean blends was lower than rice flour. Low setback viscosities of rice:bean blends may be used to prevent syneresis and stabilizing the quality of frozen foods in rice based processed foods.

In the dataset presented in this article, 168 rice samples comprising sixteen rice varieties (including Indica and Japonica sub species) from a Portuguese Rice Breeding Program obtained from three different sites along four seasons, and 11 standard rice varieties from International Rice Research Institute were characterised. The amylose concentration was evaluated based on iodine method, and the near infrared (NIR) spectra were determined. To assess the advantage of Near infrared spectroscopy, different rice varieties and specific algorithms based on Matlab software such as Standard Normal Variate (SNV), Multiple Scatter Calibration (MSC) and Savitzky-Golay filter were used for NIR spectra pre-processing.