Pearl millet populations characterized by Fusarium prevalence, morphological traits, phenolic content, and antioxidant potential

Ultrasound-mediated hydration of finger millet: Effects on antinutrients, techno-functional and bioactive properties, with evaluation of ANN-PSO and RSM optimization methods

Finger millet, rich in nutrients, faces bioavailability limitations due to antinutrients like phytates and tannins that can be reduced by ultrasound mediated hydration (USH). Here, USH process of finger millet was optimized by varying ultrasound amplitude, water to grain ratio (W:G), treatment time, and frequency for reducing antinutrients and improving techno-functional attributes. USH resulted in a maximum reduction of 73% and 71% in phytates and tannins, respectively. The process was modeled using artificial neural network (ANN) and response surface methodology (RSM). ANN outperformed RSM in process prediction, and particle swarm optimization (ANN-PSO) suggested optimal conditions: 76% amplitude, W:G of 3.5:1, 17.5 min treatment time at 40 kHz. USH samples showed higher β-sheet, β-turn, and random coil proportions, with lower α-helix levels. Multivariate analysis also identified higher amplitude and frequency, with shorter treatment time as desirable USH conditions. USH could aid in enhancing commercial viability and nutritional quality of finger millet.

Effect of Marjoram Leaf Powder Addition on Nutritional, Rheological, Textural, Structural, and Sensorial Properties of Extruded Rice Noodles

Food-to-food fortification is an emerging technique to enrich the micronutrients in foods. Pertaining to this technique, noodles could also be fortified with natural fortificants. In this study, marjoram leaf powder (MLP) at a level of 2-10% was used as a natural fortificant to produce fortified rice noodles (FRNs) through an extrusion process. The MLP addition caused a significant increase in the iron, calcium, protein, and fiber in the FRNs. The noodles had a lower whiteness index than unfortified noodles but had a similar water absorption index. The water solubility index increased significantly due to the higher water retention ability of MLP. A rheological study showed a minimal effect of fortification on the gelling strength of the FRNs at lower levels. The microstructural studies found incremental cracks, which facilitated a lower cooking time and hardness but had an insignificant effect on the cooked noodle texture. Fortification improved the total phenolic content, antioxidant capacity, and total flavonoid content. However, no significant changes in bonds were observed, but a reduction in the noodles' crystallinity could be seen. The sensory analysis of the noodles reflected a higher acceptability of the 2-4% MLP fortified samples compared to the others. Overall, the MLP addition improved the nutritional content, antioxidant activity, and the cooking time but slightly affected the rheological, textural, and color properties of the noodles.

Crop Model Parameterisation of Three Important Pearl Millet Varieties for Improved Water Use and Yield Estimation

Pearl millet is an important crop for food security in Asia and Africa’s arid and semi-arid regions. It is widely grown as a staple cereal grain for human consumption and livestock fodder. Mechanistic crop growth and water balance models are useful to forecast crop production and water use. However, very few studies have been devoted to the development of the model parameters needed for such simulations for pearl millet. The objectives of the study were to determine crop-specific model parameters for each of three pearl millet varieties (landrace, hybrid, and improved), as well as to calibrate and validate the Soil Water Balance (SWB) model for predicting pearl millet production and water use based on weather data. The SWB was chosen because it is widely used in southern Africa; however, the developed parameters should benefit other models as well. The presented crop-specific parameter values were derived from field observations and literature. Varieties with different phenology, maturity dates and tillering habits were grown under well-watered and well-fertilised conditions for calibration purposes. The calibrated model was used to predict biomass production, grain yield and crop water use. The hybrid’s water use efficiency was higher than that of the landrace and improved variety.