1158Microwaveassisted extraction of chickpea protein isolate:Impact on structural and physicochemical properties

Yangyi Zheng1, Paraskevi Paximada1

1School of Food Science & Nutrition, University of Leeds, LS2 9JT, Leeds, UK

This aim of this study was to systematically explore microwave-assisted extraction (MAE) of chickpea protein isolate (CPI) as an innovative alternative to conventional extraction methods. Impacts of varying microwave power (200–800 W) and duration (60–300 s) on yield, purity, protein composition secondary structure of CPI was studied and functional properties in terms of solubility and surface hydrophobicity were examined as a function of pH and compared against commercial and conventional alkaline extraction process. The optimal extraction conditions were identified at moderate microwave treatment (400 W for 120 s), achieving higher extraction yields (~15%) and similar protein purity (~77%) to those of conventional alkaline extracted protein isolates (AE-CPI). Higher power particularly at 800 W resulted in high degree of protein denaturation and reduction in yield and purity. Sodium dodecyl sulphate polyacrylamide gel electrophoresis (SDS-PAGE) analysis indicated that MAE preserved protein structure comparable to AE-CPI, avoiding significant structural damage observed via circular dichroism (CD) in Com-CPI, attributed to rapid dielectric heating lowering the cumulative thermal processing, consequently limiting thermal denaturation and/ or crosslinking particularly at lower powers (200-400 W). Moderate microwave treatments effectively maintained desirable secondary structures, notably α-helices and unordered conformations with improved solubility (10% at even near isoelectric point, pH 5.0) and increased surface hydrophobicity (~50% at all pH) for MAE samples ], unlike the high degree of β-sheets and reduced surface hydrophobicities observed for Com-CPI. Overall, these findings highlight the potential of MAE to improve functionality whilst conserving protein structure and yield versus traditional extraction approaches