Storage behaviour of ohmic heated and ultrasonicated amla juice: AI mediated correlation between ascorbic acid content and color attributes

Artificial neural networking (ANN) based models are being increasingly and effectively used in the prediction and estimation of response variables during various food processing applications. We demonstrated the feasibility of a feed forward back propagation ANN model to estimate ascorbic acid content in fresh amla juice that was ohmic heating assisted vacuum evaporated (OHVC) with/without ultrasonication (US) from color attributes (L*, a*, b* and ΔE) during 4 weeks of ambient storage. There was a positive effect of synergistic processing of OHVC and US on the quality of stored amla juice with the fresh untreated sample witnessing ascorbic acid and total phenolic degradation of up to 60