Malting process optimization of an Italian common wheat landrace (Triticum aestivum L.) through response surface methodology and desirability approach

Local and alternative raw materials are of growing interest to the malting and brewing industry. These include wheat landraces, old varieties characterized by high protein content and resistance to biotic and abiotic stress. One of the basic ingredients of beer is malt, i.e., a grain that have been subjected to germination under controlled conditions. Malting awakens the seed’s physiological activity, thereby triggering its chemical and structural modification. The response surface methodology (RSM) was used to assess the impact of three independent variables (germination time, germination temperature, degree of steeping) on certain traits defining malt quality. Germination time and temperature exerted a major role during the malting experiments. A desirability function was applied to predict the best combination of parameters that would optimize the desired outcomes. After 6 days, at 18 ◦C and 42 g/100 g, the following results were achieved: extract 81.6% d.m., Kolbach index (KI) 38.3%, free amino nitrogen (FAN) 116 mg/100 g, apparent attenuation limit (AAL) 82.9%. The response surface methodology (RSM) proved to be largely suitable for the optimization of the malting process under study. Its implementation through the R statistics programming language and environment provided an alternative and valuable resource for conducting the statistical analysis and optimization.