Predicting farinograph parameters by rapid visco analyser pasting profile using partial least square regression
Main Article Content
Keywords
rheology, wheat
Abstract
Farinograph parameters are widely used to predict flour and dough functionality. Accurate prediction of farinograph parameters using other instruments would provide key information in determining cereal products quality and functional properties. This study was undertaken to provide calibration models using rapid visco analyser (RVA) to predict farinograph flour parameters and dough end-use functionality. A total of 267 samples consisted of wheat flour substituted with various ratios of disrupted chickpea (Cicer arietinum) and lentil (Lens culinaris) flours were used in this study. Samples (n=237) were randomly selected and used to develop calibration models of farinograph parameters using RVA profile. Another sample set consisting of 30 flour samples were used to validate the developed models. The partial least squares regression method using the RVA profile was used to develop prediction models for farinograph parameters treatments. Farinograph parameters (water absorption, peak time, mixing tolerance index, stability, arrival and departure times) were moderately fitted with a coefficient of determination (R2) of predicted and measured values of 0.881, 0.911, 0.903 and 0.913, 0.751 and 0.824, respectively. Root mean square of calibrated and predicted models for farinograph parameters ranged from 0.083 and 5.687 and from 0.090 to 6.215, respectively, indicating the fitness of the developed model in predicting farinograph parameters. Results further indicated satisfactory developed models in predicting farinograph parameters except arrival time.
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