Malting process optimization of an Italian common wheat landrace (Triticum aestivum L.) through response surface methodology and desirability approach. (1st January 2023)

• Record Type: Journal Article
• Authors: Calvi, Antonio; Preiti, Giovanni; Gastl, Martina; Poiana, Marco; Zarnkow, Martin
• Is Part Of: Lebensmittel-Wissenschaft + Technologie =. Volume 173(2023)
• Publication Date: 2023-01-01
• Subjects: Common wheat -- Landrace -- Micro-malting -- Response surface methodology -- Desirability function; RSM response surface methodology -- KI Kolbach index -- FAN free amino nitrogen -- AAL apparent attenuation limit -- d.m. dry matter -- MEBAK Mitteleuropaische Brau-und Analysenkommision -- FO first order -- TWI two-way interaction -- PQ pure quadratic -- L lowest acceptable value -- T desired target -- U highest acceptable value; Food industry and trade -- Periodicals; Food -- Composition -- Periodicals; Microbiology -- Periodicals; Nutrition -- Periodicals; 664.005
• DOI: 10.1016/j.lwt.2022.114242
• Languages: English
• ISSNs: 0023-6438

Abstract

Abstract: 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. Highlights: Micro-malting of a common wheat landrace ( Triticum aestivum L.). Combined utilization of RSM and desirability function in R software environment. Germination time and temperature influenced all the responses analysed. A combination of malting parameters was identified to achieve the desired targets.