Published 2015

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Publication details

Journal : Talanta: The International Journal of Pure and Applied Analytical Chemistry , vol. 143 , p. 138–144 , 2015

Publisher : Pergamon Press

International Standard Numbers :
Printed : 0039-9140
Electronic : 1873-3573

Publication type : Academic article

Contributors : Helgerud, Trygve; Wold, Jens Petter; Pedersen, Morten Bøhler; Liland, Kristian Hovde; Ballance, Simon; Knutsen, Svein Halvor; Rukke, Elling-Olav; Afseth, Nils Kristian

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Prediction of dry matter content in whole potatoes is a desired capability in the processing industry. Accurate prediction of dry matter content may greatly reduce waste quantities and improve utilization of the raw material through sorting, hence also reducing the processing cost. The following study demonstrates the use of a low resolution, high speed NIR interactance instrument combined with partial least square regression for prediction of dry matter content in whole unpeeled potatoes. Three different measuring configurations were investigated: (1) off-line measurements with contact between the potato and the light collection tube; (2) off-line measurements without contact between the potato and the light collection tube; and (3) on-line measurements of the potatoes. The offline contact measurements gave a prediction performance of R2=0.89 and RMSECV=1.19. Similar prediction performance were obtained from the off-line non-contact measurements (R2=0.89, RMSECV=1.23). Significantly better (p=0.038) prediction performance (R2=0.92, RMSECV=1.06) was obtained with the on-line measuring configuration, thus showing the possibilities of using the instrument for on-line measurements. In addition it was shown that the dry matter distribution across the individual tuber could be predicted by the model obtained.