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乳酸菌发酵蓝莓汁产胞外多糖的研究:优化、发酵特性及可见-近红外光谱模型

Investigation on the exopolysaccharide production from blueberry juice fermented with lactic acid bacteria: Optimization, fermentation characteristics and Vis-NIR spectral model.

作者信息

Yang Suqun, Tao Yang, Maimaiti Xiayidan, Su Wei, Liu Xiaoli, Zhou Jianzhong, Fan Linlin

机构信息

Institute of Agro-product Processing, Jiangsu Academy of Agricultural Sciences, Nanjing 210014, China; School of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, China.

College of Food Science and Technology, Nanjing Agricultural University, Nanjing 210095, China.

出版信息

Food Chem. 2024 Sep 15;452:139589. doi: 10.1016/j.foodchem.2024.139589. Epub 2024 May 10.

Abstract

The exopolysaccharide production from blueberry juice fermented were investigated. The highest exopolysaccharide yield of 2.2 ± 0.1 g/L (increase by 32.5 %) was reached under the conditions of temperature 26.5 °C, pH 5.5, inoculated quantity 5.4 %, and glucose addition 9.1 % using the artificial neural network and genetic algorithm. Under the optimal conditions, the viable cell counts and total acids were increased by 2.0 log CFU/mL and 1.6 times, respectively, while the content of phenolics and anthocyanin was decreased by 9.26 % and 7.86 %, respectively. The changes of these components affected the exopolysaccharide biosynthesis. The absorption bands of -OH and -CH associated with the main functional groups of exopolysaccharide were detected by Visible near-infrared spectroscopy. The prediction model based on spectrum results was constructed. Competitive adaptive reweighted sampling and the random forest were used to enhance the model's prediction performance with the value of R = 0.936 and R = 0.835, indicating a good predictability of exopolysaccharides content during fermentation.

摘要

对蓝莓汁发酵产生胞外多糖的情况进行了研究。使用人工神经网络和遗传算法,在温度26.5℃、pH值5.5、接种量5.4%和葡萄糖添加量9.1%的条件下,胞外多糖产量达到最高,为2.2±0.1 g/L(提高了32.5%)。在最佳条件下,活菌数和总酸分别增加了2.0 log CFU/mL和1.6倍,而酚类和花青素含量分别降低了9.26%和7.86%。这些成分的变化影响了胞外多糖的生物合成。通过可见近红外光谱检测了与胞外多糖主要官能团相关的-OH和-CH吸收带。构建了基于光谱结果的预测模型。采用竞争自适应重加权采样和随机森林来提高模型的预测性能,R值分别为0.936和0.835,表明发酵过程中胞外多糖含量具有良好的可预测性。

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