Technological properties,in vitro starch digestibility and in vivo glycaemic index of bread containing crude malva nut gum

The effects of crude malva nut gum (CMG) on the texture, digestion and the glycaemic index (GI) of white bread were investigated. Different CMG levels (0%, 2.5%, 5%, 7.5% and 10% w/w based on weight of flour) were added into a bread formula. The lightness (L*) and loaf‐specific volumes of the bread decreased with increased CMG levels. Firmness of the bread increased with increased CMG content. The in vitro starch digestion kinetics showed that bread containing CMG had generally lower predicted GI (74–81 vs. the control). In vivo human testing showed that increasing the CMG reduced the GI of the bread. The GI values of bread containing CMG ranged from 73 to 98 of the control. Overall liking scores of consumers ranged between ‘like slightly’ and ‘like moderately’ (6.1–7.1) compared to 7.1 for the control. Thus, the addition of CMG in carbohydrate‐based foods may lower the GI.     

Production,iron analysis and consumer perception of functional Thai Sinlek iron rice (Oryza sativa) drink

We produced the iron rice (IR) drink, determined the relevant chemical composition and antioxidant activity and tested the consumers’ degree of satisfaction. IR grains were digested with α-amylase and analysed chemical composition and antioxidant activity, while the hydrolysate (pH 4.0) and flavouring agents were added for final preparation of the IR drink. The IR hydrolysate contained a total iron content of 13.9 mg g⁻¹, a total phenolic content of 1.33 ± 0.07 mg gallic acid equivalent g⁻¹ and γ-oryzanol of 70.12 ± 2.7 mg kg⁻¹ rice grain, all of which inhibited the generation of free radicals in a concentration-dependent manner. The IR drink was composed of flavonoids and phenolic acids for which kaempferol was predominant. The members of all three groups of elderly subjects who consumed the low-dose IR (1.47 mg iron/100 mL), high-dose IR (2.74 mg iron/100 mL) and white rice (WR; 0.5 mg iron/100 mL) drinks expressed satisfaction and interest with the beverages at 91.2%, 100% and 88.9%, respectively. In terms of sensory evaluation, the low-dose IR drink revealed a higher acceptance rating than high-dose IR and WR (P < 0.05). Notably, the Sinlek rice drink was abundant with iron, anti-oxidative phenolics and γ-oryzanol, for which consumers expressed an overall degree of acceptance (8.1 ± 1.1).     

Thalassaemia classification by neural networks and genetic programming

This paper presents the use of a neural network and a decision tree, which is evolved by genetic programming (GP), in thalassaemia classification. The aim is to differentiate between thalassaemic patients, persons with thalassaemia trait and normal subjects by inspecting characteristics of red blood cells, reticulocytes and platelets. A structured representation on genetic algorithms for non-linear function fitting or STROGANOFF is the chosen architecture for genetic programming implementation. For comparison, multilayer perceptrons are explored in classification via a neural network. The classification results indicate that the performance of the GP-based decision tree is approximately equal to that of the multilayer perceptron with one hidden layer. But the multilayer perceptron with two hidden layers, which is proven to have the most suitable architecture among networks with different number of hidden layers, outperforms the GP-based decision tree. Nonetheless, the structure of the decision tree reveals that some input features have no effects on the classification performance. The results confirm that the classification accuracy of the multilayer perceptron with two hidden layers can still be maintained after the removal of the redundant input features. Detailed analysis of the classification errors of the multilayer perceptron with two hidden layers, in which a reduced feature set is used as the network input, is also included. The analysis reveals that the classification ambiguity and misclassification among persons with minor thalassaemia trait and normal subjects is the main cause of classification errors. These results suggest that a combination of a multilayer perceptron with a blood cell analysis may give rise to a guideline/hint for further investigation of thalassaemia classification.