ArticleFood science & nutrition2025
Optimization of Millet Malting Parameters Using Artificial Neural Network and Response Surface Methodology.
Article in Food science & nutrition, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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Who cites it
1 citing paper in PubMed.
- The Role of Malting and Brewer's Spent Grain in Sustainable Cereal Utilization.Foods (Basel, Switzerland) · 2026Review
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4 authors.
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Abstract
The quality of malt produced from cereals is significantly influenced by various factors, including steeping and germination periods. Monitoring these factors and their effects on malt grain characteristics is often time-consuming and costly. In this context, this study aimed to predict trends in changes to certain characteristics of millet-derived malt, influenced by varying steeping durations (24-48 h) and germination times (5-9 days). Changes in these characteristics were predicted using response surface methodology (RSM), which incorporated a central composite design and an artificial neural network (ANN). The findings indicated that increasing the steeping and germination durations led to a decrease in malting efficiency, thousand grain weight, and true density of the samples. Conversely, the cold-water extract efficiency, the Kolbach index, and the extract color increased. The optimization process revealed that to achieve the highest-quality malt, the steeping duration should be 42.54 h, followed by a germination period of 5 days. Under these conditions, the malting efficiency reached 75.44%, with a thousand grain weight of 4.85 g, a true density of 977.43 kg/m
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