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Summary: Starch is a versatile biomaterial with a wide range of applications across various industrial sectors. Therefore, starch isolation methods play a crucial role in fulfilling the demand for high‐quality starch required for different applications. Waxy maize starch is the most used starch for different food applications. It is isolated using an alkaline extraction method and available in the market at a high price. The traditional process of starch isolation involves labour‐intensive and costly downstream processing that leads to exploring cost‐effective isolation methods for various food applications. Finger millet (Eleusine coracana) is an underutilised cereal crop composed of 65–70% of starch. In the present study, the starch from finger millet is isolated using conventional and ultrasound‐assisted isolation methods to fulfil the current requirement. The isolated finger millet starch was characterised by morphological structure obtained by scanning electron microscopy (SEM), X‐ray diffractogram (XRD), infrared spectrum obtained by Fourier transform infrared spectrometer (FT‐IR), differential scanning calorimetry (DSC) analysis, and rheological analysis. The SEM images confirmed the reduced particle size and uniform grain size distribution in the starch isolated using ultrasound‐assisted isolation. The relative crystallinity of starch isolated using ultrasound‐assisted isolation method (69.05 ± 0.57%) was higher compared to other conventional isolation methods (57.18 ± 0.70%, 67.66 ± 1.00%, and 68.34 ± 0.33% for distilled water soaking, alkali soaking, and sodium bisulphite soaking, respectively). The FTIR analysis confirmed no significant changes in the functional group of starch with respect to different isolation methods. Thermal and rheological analysis of isolated starch using ultrasound‐assisted isolation indicated the lowest gelatinisation enthalpy (45.38 ± 1.67 J/g) and showed the lowest loss factor indicating the most elastic behaviour, respectively. [ABSTRACT FROM AUTHOR]

Consumers have been more inclined towards functional food due to various health issues. Non‐dairy‐based probiotic milk could be the potential alternative to fulfill consumer demand. Spray drying of functional health drinks could enhance the shelf life and reduce the transportation cost of developed food powder. The current study was focused on the modeling and optimization of spray‐drying process parameters using an artificial neural network (ANN) coupled with a genetic algorithm (GA). The data so obtained using ANN‐GA was also compared with the data obtained using response surface methodology (RSM) coupled with desirability function (DF). The results indicated that the ANN model was better at predicting the response parameters compared to the RSM model with a higher correlation coefficient (R) of.9997,.9994,.9964, and.9992 for training, testing, validation, and all datasets, respectively. The optimum conditions obtained using RSM‐DF were 160.41°C of inlet air temperature, 33.77% of maltodextrin content, and 138.79 mL/h of feed rate while that for ANN‐GA were 160.87°C, 20%, and 200 mL/h. The RSM‐DF method proved to be better for the optimization of response parameters. Therefore method selection for modeling and optimization of process and response parameters must be based on fulfilling the specific criteria. Practical Applications: Non‐dairy milk production has gained popularity in the area of research and product development. Various process protocols have been reported to produce high‐quality non‐dairy milk to fulfill the demand for a vegan diet. However, nutrient bioavailability, longer shelf life, product stability, and consumer acceptability are hard to obtain from cereal‐based non‐dairy milk. The current study contributes to produce spray‐dried milk powder followed by fermentation at optimum drying conditions with good quality and stability. The process has been modeled and optimized in the study using advanced statistical tools such as ANN‐GA and RSM‐DF. They can effectively predict the quality parameters and determine the optimal conditions for new experimental data. [ABSTRACT FROM AUTHOR]

Ripe Palm (Borassus flabellifer) juice contains high sugars that make it difficult to store for a longer period, which limits its use for spray drying. The present work explores the feasibility and optimization of spray drying to make powder from enzymatically extracted ripe palm juice using maltodextrin and gum Arabic as wall materials. Various parameters such as moisture, water activity, solubility, ascorbic acid, colour change, and yield were optimized using response surface method with the central composite design. A mixture of maltodextrin and gum Arabic at a ratio of 3:1(w/w) combined with lactose, and spray drying with an inlet temperature of 140°C resulted in the optimum powder quantity and quality. The palm powder yield was maximum (63.5±0.29 %) with acceptable solubility (31.6±0.33 secs), colour change (ΔE= 18.37±0.03), ascorbic acid content (54±0.0003 µg/ml), moisture content (3.3±0.61), and water activity (0.29±0.05). The optimized conditions can be replicated on an industrial scale for the production of palm powder. [ABSTRACT FROM AUTHOR]