Phytic acid and Fe and Zn concentration in lentil (Lens culinaris L.) seeds is influenced by temperature during seed filling period

Phytic acid (PA), found in cereal and legume staple foods, is considered an antinutrient for iron (Fe) and zinc (Zn). Amongst numerous factors, temperature has a substantial effect on PA synthesis in seeds of legumes. PA, Fe, and Zn concentrations were determined for mature seeds of eleven lentil genotypes grown under simulated long term temperature regimes representative of Saskatoon, Canada (decreasing temperatures) and Lucknow, India (increasing temperatures). PA and Zn concentrations in lentil seeds were significantly higher in the rising temperature regime (8.8 mg/g and 69 mg/kg, respectively) than in the decreasing temperature regime (6.7 mg/g and 61 mg/kg, respectively). Fe concentrations followed the same trend (116 vs. 113 mg/kg). The cooler temperatures of temperate summers might be an important factor in the production of seeds with lower PA concentrations. These results are relevant to the development of biofortification strategies aimed at lowering the PA content in staple crops.     

Evaluation of Simple and Inexpensive High-Throughput Methods for Phytic Acid Determination

High‐throughput/low‐cost/low‐tech methods for phytic acid determination that are sufficiently accurate and reproducible would be of value in plant genetics, crop breeding and in the food and feed industries. Variants of two candidate methods, those described by Vaintraub and Lapteva (Anal Biochem 175:227–24, 1988 ; “VL” methods) and Huang and Lantzsch (J Sci Food Agric 34:1423–1426, 1983 ; “HL” methods), were evaluated. The primary concern with these methods is that, due to interference of matrix constituents including inorganic P, they can overestimate phytic acid and are ineffective at low levels of phytic acid. Twelve seed flours, representing lines of soybean, maize, barley and dry bean, containing a wide range of phytic acid levels, were analyzed by a minimum of eight cooperating laboratories using three variants of the VL method and two variants of the HL method. No method had consistently acceptable (?2.0”) “Horwitz ratios”, a measure of reproducibility, although some treatments approached that. For example, one variant of the VL method when used to assay a soybean flour with a “standard” level of phytic acid had a Horwitz ratio of 2.15. Some variants of the VL method were adequate for analyses of cereal grains regardless of phytic acid level but none accurately measured phytic acid when at low levels in soybean flours. One variant of the HL method in which the 0.2 N HCl extraction media is modified to contain 10% Na₂SO₄, did accurately measure phytic acid levels in both cereal and legume flours regardless of endogenous phytic acid levels or matrix constituents.     

Frequency domain set membership fast normalised LMS adaptive algorithm

The concept of set membership (SM) adaptive filtering is extended to the frequency domain and a novel frequency domain SM algorithm is derived. Simulations show that the new SM algorithm has a much improved convergence rate over the conventional fast normalised least mean square (FNLMS) algorithm with identical misadjustment performance. Moreover, the SM algorithm has the same order of computational complexity as the FNLMS algorithm.     

A global survey of effects of genotype and environment on selenium concentration in lentils (Lens culinaris L.): Implications for nutritional fortification strategies

Lentils (Lens culinaris L.) are an important protein and carbohydrate food, rich in essential dietary components and trace elements. Selenium (Se) is an essential micronutrient for human health. For adults, 55 μg of daily Se intake is recommended for better health and cancer prevention. Millions of people around the world have Se-deficient diets and biofortification may be an effective solution. The total Se concentration of lentils grown in six major lentil-producing countries were analysed to determine the potential for Se biofortification in these regions. The highest Se concentrations based on location means were found in lentils from Nepal (180 μg/kg) and southern Australia (148 μg/kg) while the lowest were those from Syria (22 μg/kg), Morocco (28 μg/kg), northwestern USA (26 μg/kg), and Turkey (47 μg/kg). Significant location effects within a country were observed for Nepal and Australia. All values were lower than previous published data for Saskatchewan grown lentils (425–672 μg/kg). Lentils originating from Australia, Nepal, or Canada could be considered good sources of Se, as consumption of 50 g would provide 13–61% of the recommended dietary allowance (RDA). Our findings indicate lentil may be appropriate as a target crop for Se biofortification and investigated as a food-based solution for populations with Se deficiencies.     

Prebiotic carbohydrate concentrations of common bean and chickpea change during cooking,cooling, and reheating

Thermal processing of pulse crops influences the type and levels of prebiotic carbohydrates present. Pulses such as common bean and chickpea are rich sources of prebiotic carbohydrates, including sugar alcohols (SAs), raffinose family oligosaccharides (RFOs), fructooligosaccharides (FOSs), resistant starch (RS), and amylose. This study determined the changes in prebiotic carbohydrate concentrations of seven common bean and two chickpea market classes after thermal processing (cooking, cooling, and reheating). A 100-g serving of common bean provides 0.7 to 10.6 mg of SAs, 3.9 to 5.2 g of RFOs, 57 to 143 mg of FOSs, 2.6 to 3.9 g of RS, and 25 to 33 g of amylose; cooling and reheating reduced RFOs but increased SAs, FOSs, and RS in many cases. A 100-g serving of chickpea (cooked at 90 °C for 4 hr) provides 1.2 to 1.7 g of SAs, 2.5 to 3.2 g of RFOs, 26 to 43 mg of FOSs, 3.6 to 5.3 g of RS, and 24 to 30 g of amylose; cooling and reheating reduced SAs and RFOs but increased FOSs, RS, and amylose concentrations. Processing methods change the nutritional quality of pulse crops by changing the type and quantity of prebiotic carbohydrates.     

Phytic acid and mineral micronutrients in field-grown chickpea (<Emphasis Type="Italic">Cicer arietinum</Emphasis> L.) cultivars from western Canada

Zinc (Zn), iron (Fe), magnesium (Mg), and calcium (Ca) in chickpea seed are important constituents in vegetarian diets. The aim was to investigate associations of these nutrients in different chickpea (Cicer arietinum L.) cultivars with phytic acid (PA), another naturally occurring constituent of grain that may influence the bioavailability of mineral micronutrients. Chickpea was grown at Saskatoon and Swift Current, SK, in 2002 and 2003, representing dryland production from high-yielding locations in western Canada. Minerals were measured by atomic absorption spectroscopy; PA was measured using high-performance anion-exchange conductivity detection methodology. Seed from 10 genotypes contained from 29 to 52 mg/kg Zn, 77–112 mg/kg Fe, 1,448–2,457 mg/kg Mg, 1,211–2,457 mg/kg Ca, to 3.8–9.0 mg/g PA. Phytic acid, Fe, Mg, and Ca decreased in 2003 from 2002 concentrations. Kabulis had greater Zn, the same Fe, but lower Mg and Ca concentrations than desi genotypes. Large-seeded genotypes had greater or the same Zn, the same Fe and Mg, but lower Ca than small-seeded genotypes. Iron and Ca concentrations positively correlated with PA concentration. Nutrients were affected by environment and genotype, which means that chickpea can be exploited by breeding, in addition to sourcing favorable nutritional profiles by environment, seed size, and market class.     

Biofortification of mungbean (Vigna radiata) as a whole food to enhance human health

Mungbean (Vigna radiata (L.) R. Wilczek var. radiata) is one of the most important pulse crops grown in South, East and Southeast Asia. It provides significant amounts of protein (240 g kg^?1) and carbohydrate (630 g kg^?1) and a range of micronutrients in diets. Mungbean protein and carbohydrate are easily digestible and create less flatulence than proteins derived from other legumes. In addition, mungbean is lower in phytic acid (72% of total phosphorus content) than pigeonpea (Cajanus cajan L. Millsp.), soybean (Glycine max L.) and cereals; phytic acid is commonly found in cereal and legume crops and has a negative impact on iron and zinc bioavailability in plant‐based diets. Owing to its palatable taste and nutritional quality, mungbean has been used as an iron‐rich whole food source for baby food. The wide genetic variability of mineral concentrations (e.g. 0.03–0.06 g Fe kg^?1, 0.02–0.04 g Zn kg^?1) in mungbean indicates possibilities to improve its micronutrient content through biofortification. Therefore biofortification of existing mungbean varieties has great potential for enhancing the nutritional quality of diets in South and Southeast Asia, where protein and micronutrient malnutrition are among the highest in the world. This review paper discusses the importance of mungbean in agricultural production and traditional diets and the potential of enhancing the nutritional quality of mungbean through breeding and other means, including agronomic practices. © 2013 Society of Chemical Industry     

Application of nonlinear fatigue damage models in power electronic module wirebond structure under various amplitude loadings

This paper presents mean fatigue lifetime prediction of a wire-bond structure model in power electronic module using a failure physics approach that integrates high fidelity modelling and reduced order modelling.Loading current with variable amplitudes is applied to a finite element model of simplified wirebond structures.The resulting accumulated fatigue damage due to random loads is predicted by using reduced order modelling based on failure physics,a cycle counting algorithm,and various nonlinear fatigue damage models widely used in the literature.The reduced order modelling approach based on failure physics uses prediction data for the electro-thermo-mechanical behaviour of the wire-bond design of a power module obtained through non-linear transient finite element simulations,in particular for the fatigue life-time of the aluminium wire attached to the silicon chip of the wire in the module.The reduced order models that capture the black box function of the accumulated plastic strain are used in predicting the mean fatigue life time of the wire bond structure under random loads.One of the widely used cycle counting algorithms,rainflow counting algorithm,is used to count cycles of the temperature profile at the specific point of the wire bond structure in a power electronic module.The cycle data from the rainflow algorithm mean life time of the wire bond structure are predicted with various cumulative fatigue models.Non-linear cumulative fatigue models such as damage curve approach(DCA),double linear damage rule(DLDR),and double damage curve approach(DDCA),and linear cumulative fatigue damage model such as Palmgren-Miner rule are used to predict the mean fatigue life of the wire bond structure,and the results are compared.