Prediction of the viscosity of clarified fruit juice using artificial neural network: a combined effect of concentration and temperature

@inproceedings{Rai2005PredictionOT,
  title={Prediction of the viscosity of clarified fruit juice using artificial neural network: a combined effect of concentration and temperature},
  author={Pramod Rai and G. C. Majumdar and Sunando Dasgupta and Sirshendu De},
  year={2005}
}
Abstract An artificial neural network (ANN) model is presented for the prediction of viscosity of fruit juice as a function of concentration and temperature. The fruit juices considered in the present study were orange, peach, pear, malus floribunda and black current. The viscosity data of juices (1.53–3300 mPa s) were obtained from the literature for a wide range of concentration (5–70 °Brix) and temperature (30.7–71.7 °C). Several configurations were evaluated while developing the optimal ANN… CONTINUE READING

Citations

Publications citing this paper.
SHOWING 1-10 OF 14 CITATIONS

Chemical composition and temperature influence on honey texture properties

VIEW 2 EXCERPTS
CITES BACKGROUND

Non-linear assessment of anticancer activity of 17-picolyl and 17-picolinylidene androstane derivatives--chemometric guidelines for further syntheses.

VIEW 1 EXCERPT
CITES BACKGROUND

Artificial neural network model of pork meat cubes osmotic dehydration

VIEW 3 EXCERPTS
CITES BACKGROUND & METHODS