Application of response surface methodology for optimization of wheat flour milling process

Abstract

AbstractBackground and objectivesFlour millers are faced with constraints of having to meet proximate specifications, usually defined by supply contracts, while trying to maximize yield. The study investigated the application of response surface methodology (RSM), in a commercial scale flour mill, as a means of maximizing yield while meeting quality constraints.FindingsThis study utilized a Box–Behnken design to develop mathematical models using RSM to describe the effect of three independent variables, wheat conditioning level (12%–18%), first break roll gap (350–600 µm), and second break roll gap (200–600 µm) on the responses. The model R2 for the responses was .98, .96, .98, and .98 for ash, protein and moisture contents, and flour yield, respectively. All models were statistically significant (p < .05) and validated with four independent experiments. RSM models were used to optimize the process to produce flour with a protein content greater than 12.0%, ash content less than 0.54%, moisture content less than 14.5%, and yield greater than 84.2% on a clean wheat, unconditioned basis. This was achieved with conditioning wheat to 18.4%, first break roll gap of 450 µm, and second break roll gap of 250 µm.ConclusionThe optimum mill settings resulted in a flour yield increase of 1.45% and reduction in ash content from 0.58% to 0.53%.Significance and noveltyUsing RSM, significant financial gains could be achieved by producing more flour from a given quantity of wheat with lower levels of bran contamination.