Barroca, Maria JoãoGuiné, RaquelCalado, Ana Rita P.Correia, PaulaMendes, Mateus2017-11-082017-11-082017Barroca, M.J., Guiné, R.P.F., Calado, A.R.P., Correia, P.M.R., & Mendes, M. (2017). Artificial neural network modelling of the chemical composition of carrots submitted to different pre-drying treatments. Journal of Food Measurement and Characterization, 11(4), 1815-1826. doi: 10.1007/s11694-017-9563-9http://hdl.handle.net/10400.19/4701The effect of various pre-drying treatments on the quality of dried carrots was evaluated by assessing the values of moisture, ash, protein, fibre, sugars and col- our. The pre-drying treatments under investigation were dipping, either in ascorbic acid or sodium metabisulphite at different concentrations and pre-treatment times, as well as blanching. The experimental data was analysed using neural networks, so that relevant patterns in the data were found and conclusions drawn about each variable. The results showed that the type of pre-drying treatment (chemical or physical) had variable impact on the nutri- tional composition of the dried carrots but not on the colour parameters, which were found to be mostly unaffected by the pre-treatment procedure. Pre-treatment with chemical agents such as ascorbic acid or metabisulphite seem to have the least impact on the parameters studied. The results of the analysis by artificial neural networks confirmed these findings.engPre-drying treatment DryingNeural network CarrotsColourChemical compositionjournal article10.1007/s11694-017-9563-9