Optimization of corn soaking conditions in wet milling through the application of protease enzymes

Conventional wet milling of corn relies on extended steeping with sulfur dioxide, which is energy intensive and generates solute losses as well as environmental concerns. This study explored the potential of enzyme-assisted soaking as an alternative approach to improve efficiency and product quality. Yellow corn was subjected to traditional steeping (48 h with 2000 ppm sulfur dioxide) and to treatments with the protease ProEx FG at varying concentrations (1–4 mL/100 g) for shorter durations (2–8 h). Key parameters evaluated included starch yield and purity, fiber content, germ and oil recovery, protein composition, and soluble solids. Traditional soaking produced 68% starch with 98.1% purity and 6.4% soluble losses. In contrast, enzyme-assisted soaking shortened processing time, increased starch purity to 99.4%, and reduced soluble losses to 0.72%. Higher enzyme concentrations enhanced protein solubilization but could lower starch and oil recovery due to excessive degradation or limited hydration. The most effective treatment was 2 mL enzyme/100 g corn for 8 h, which balanced starch purity and oil recovery. Overall, enzyme-assisted soaking provides a promising alternative to conventional corn steeping by reducing time and solute losses while improving product quality, with process optimization being crucial for industrial application.

Authors

Institutions

Publication Details

Journal
Journal of Scientific Research in Science /Journal of Scientific Research in Science
Published
2025-12-01
DOI
https://doi.org/10.21608/jsrs.2025.437218.1255
Primary Topic
Food composition and properties
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Optimization of corn soaking conditions in wet milling through the application of protease enzymes

Ali Osman, Hossam Saad EL-BELTAGI, Aqeel Ahmed, Hefnawy taha et al.
Journal of Scientific Research in Science /Journal of Scientific Research in Science
Food composition and properties
article

Optimization of corn soaking conditions in wet milling through the application of protease enzymes

Ali Osman, Hossam Saad EL-BELTAGI, Aqeel Ahmed, Hefnawy taha, Haiam O. Elkatary, Ibrahim M. Elkhodairy, Ahmed E. Awad, Yousef Abdulrahman Almuharif
article en

Abstract

Conventional wet milling of corn relies on extended steeping with sulfur dioxide, which is energy intensive and generates solute losses as well as environmental concerns. This study explored the potential of enzyme-assisted soaking as an alternative approach to improve efficiency and product quality. Yellow corn was subjected to traditional steeping (48 h with 2000 ppm sulfur dioxide) and to treatments with the protease ProEx FG at varying concentrations (1–4 mL/100 g) for shorter durations (2–8 h). Key parameters evaluated included starch yield and purity, fiber content, germ and oil recovery, protein composition, and soluble solids. Traditional soaking produced 68% starch with 98.1% purity and 6.4% soluble losses. In contrast, enzyme-assisted soaking shortened processing time, increased starch purity to 99.4%, and reduced soluble losses to 0.72%. Higher enzyme concentrations enhanced protein solubilization but could lower starch and oil recovery due to excessive degradation or limited hydration. The most effective treatment was 2 mL enzyme/100 g corn for 8 h, which balanced starch purity and oil recovery. Overall, enzyme-assisted soaking provides a promising alternative to conventional corn steeping by reducing time and solute losses while improving product quality, with process optimization being crucial for industrial application.

Journal of Scientific Research in Science /Journal of Scientific Research in ScienceVol. 42(2)
Zagazig University (EG), King Faisal University (SA)
Openalex Percentile: Top 33%
Food composition and properties
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.