Predicting the moisture content of organic wheat in the first stage of tempering

Abstract

The tempering process is a key process in wheat flour milling that requires proper adjustments to achieve a desired level of flour quality and yield. The present study aims to develop a tool to predict the moisture content of organic wheat at the end of the first stage of tempering. A study case was conducted at a mill located in the Quebec region to build and compare flour models: ordinary least squares (OLS), LASSO, RIDGE and ElasticNet. The models are based on wheat properties (initial wheat moisture content, wheat protein content and wheat temperature), process parameters (targeted wheat moisture content, wheat flow rate, water flow rate, wheat quantity and resting time) and tempering conditions (water quantity and day weather). The increase of wheat moisture achieved during the first tempering stage varies between 0% and 5%. The results indicated that ElasticNet model outperformed others in determining the final increase of wheat moisture with an average prediction errors of 0.21%.