Peng Xingguang, Liu Hongsheng, Li Xuying, Wang Huaibin, Zhang Kejia, Li Shuangqi, Bao Xianyang, Zou Wei, Yu Wenwen
School of Food Science and Engineering, South China University of Technology, Guangzhou 510000, China.
College of Agriculture and Biology, Shanghai Jiaotong University, Shanghai 200240, China.
Foods. 2023 Jan 14;12(2):404. doi: 10.3390/foods12020404.
In vitro digestion methods that can accurately predict the estimated GI (eGI) values of complex carbohydrate foods, including biscuits, are worth exploring. In the current study, standard commercial biscuits with varied clinical GI values between 9~30 were digested using both the INFOGEST and single-enzyme digestion protocols. The digestion kinetic parameters were acquired through mathematical fitting by mathematical kinetics models. The results showed that compared with the INFOGEST protocol, the AUR180 deduced from digesting using either porcine pancreatin or α-amylase showed the best potential in predicting the eGI values. Accordingly, mathematical equations were established based on the relations between the AUR180 and the GI values. When digesting using porcine pancreatin, GI= 1.834 + 0.009 ×AUCR180 (R2= 0.952), and when digesting using only α-amylase, GI= 6.101 + 0.009 ×AUCR180 (R2=0.902). The AUR180 represents the area under the curve of the reducing-sugar content normalized to the total carbohydrates versus the digestion time in 180 min. The in vitro method presented enabled the rapid and accurate prediction of the eGI values of biscuits, and the validity of the formula was verified by another batch of biscuits with a known GI, and the error rate of most samples was less than 30%.
能够准确预测包括饼干在内的复合碳水化合物食品估计血糖生成指数(eGI)值的体外消化方法值得探索。在本研究中,使用INFOGEST和单酶消化方案对临床血糖生成指数在9至30之间变化的标准商业饼干进行消化。通过数学动力学模型进行数学拟合获得消化动力学参数。结果表明,与INFOGEST方案相比,使用猪胰蛋白酶或α-淀粉酶消化得出的AUR180在预测eGI值方面显示出最佳潜力。因此,基于AUR180与血糖生成指数值之间的关系建立了数学方程。使用猪胰蛋白酶消化时,GI = 1.834 + 0.009×AUCR180(R2 = 0.952),仅使用α-淀粉酶消化时,GI = 6.101 + 0.009×AUCR180(R2 = 0.902)。AUR180表示还原糖含量相对于总碳水化合物的曲线下面积与180分钟内消化时间的关系。所提出的体外方法能够快速准确地预测饼干的eGI值,并且该公式的有效性通过另一批已知血糖生成指数的饼干得到验证,大多数样品的错误率小于30%。