Chamsai Tossaporn, Wanyo Pitchaporn
Department of Mechanical Engineering, Faculty of Agriculture and Technology, Rajamangala University of Technology Isan, Surin Campus, Surin 32000, Thailand.
Department of Food Technology, Faculty of Agricultural Technology, Kalasin University, Kalasin 46000, Thailand.
ACS Omega. 2025 Jul 15;10(29):32080-32096. doi: 10.1021/acsomega.5c03787. eCollection 2025 Jul 29.
Germinated brown rice (GBR) is a functional food rich in γ-aminobutyric acid (GABA) and antioxidants. However, its bioaccessibility is limited by the dense bran structure. Ultrasonic-assisted enzymatic pretreatment has emerged as a green technology to enhance the nutritional profile of germinated grains. In this study, we optimized ultrasonic-assisted cellulase pretreatment for GBR to enhance the GABA content and antioxidant activity. Process variablesultrasonic time and cellulase concentrationwere modeled using response surface methodology (RSM) and artificial neural network-genetic algorithm (ANN-GA). The ANN-GA model demonstrated higher predictive accuracy compared to RSM. Under optimized conditions, the GBR exhibited increased levels of GABA, total phenolics, and antioxidant activity, alongside a reduction in the optimal cooking time. In vitro digestion further revealed improved bioaccessibility of GABA and total phenolic content (115.74% and 128.53%, respectively). This approach presents a sustainable, scalable strategy for producing GBR-based functional foods with enhanced health benefits and processing efficiency.
发芽糙米（GBR）是一种富含γ-氨基丁酸（GABA）和抗氧化剂的功能性食品。然而，其生物可及性受到致密麸皮结构的限制。超声辅助酶预处理已成为一种提高发芽谷物营养成分的绿色技术。在本研究中，我们优化了GBR的超声辅助纤维素酶预处理，以提高GABA含量和抗氧化活性。使用响应面法（RSM）和人工神经网络-遗传算法（ANN-GA）对工艺变量（超声时间和纤维素酶浓度）进行建模。与RSM相比，ANN-GA模型显示出更高的预测准确性。在优化条件下，GBR的GABA、总酚含量和抗氧化活性增加，同时最佳烹饪时间缩短。体外消化进一步表明，GABA和总酚含量的生物可及性得到改善（分别为115.74%和128.53%）。该方法为生产具有更高健康益处和加工效率的基于GBR的功能性食品提供了一种可持续、可扩展的策略。
