Response surface optimization of thermo-sonication conditions and taro mucilage concentrations for the preparation of soy yogurt

分离 粘液 响应面法 可滴定酸 超声 食品科学 化学 大豆蛋白 色谱法 植物 生物
作者
Alkatuzzakia Akhi,Tanvir Ahmed,Rowshon Ara,Md Rahmatuzzaman Rana
出处
期刊:Journal of agriculture and food research [Elsevier]
卷期号:: 100918-100918
标识
DOI:10.1016/j.jafr.2023.100918
摘要

The present study embarked on developing soy yogurt utilizing soybean and taro mucilage. Box-Behnken Design (BBD) of Response Surface Methodology (RSM) was executed to optimize the ingredient and thermo-sonication conditions such as temperature (A: 40–60 °C), time (B: 5–15 min), and mucilage concentrations (0.1–0.3 g/100 mL) on the responses such as pH, acidity, syneresis, water holding capacity, viscosity, texture profile (firmness, adhesiveness, gumminess), and overall acceptability. The analyses showed that the soy yogurts have a titratable acidity (0.73 ± 0.43 % - 0.85 ± 0.58 %), pH (4.7 ± 0.40–4.93 ± 0.68), total soluble solid (26 ± 3.2 °Brix - 42.2 ± 4 °Brix), syneresis (26 ± 3.2 % - 39.98 ± 3.7 %), water holding capacity (36.33 ± 4.91 % - 55.7 ± 2.27 %), viscosity (1367.3 ± 2.98 mPa s - 2306.13 ± 3.21 mPa s), whitening index (76.1 ± 3.22–82.33 ± 2.18), firmness (14 ± 5 g - 26 ± 2 g), cohesiveness (13 ± 3.74 g s - 23.2 ± 2.88 g s), gumminess (0.7 ± 0.01 g - 1.8 ± 0.03 g), and overall acceptability (3.96 ± 0.16–4.54 ± 0.32). From the variance analysis, the R2 of eleven response variables is more than 0.85, which indicates the model explained a high proportion of variability. At 60 °C thermo-sonication temperature, 13 min thermo-sonication time, and 0.3 g/100 mL mucilage concentration, the optimal conditions recorded for 0.780 ± 0.21 % (titratable acidity), 4.701 ± 0.51 (pH), 10.986 ± 0.76 °Brix (total soluble solid), 27.886 ± 0.49 % (syneresis), 54.687 ± 0.38 % (water holding capacity), 1810.541 ± 5.75 mPa s (viscosity), 23.126 ± 0.45 (firmness), 16.945 ± 0.21 (cohesiveness), 1.485 ± 0.48 (gumminess), 81.764 ± 0.32 (whitening index), and 4.365 ± 0.42 (overall acceptability). Furthermore, the developed models' actual response and predicted values correlated with each other as the Residual Standard Error (RSE) values were ≤5 %. This suggests that our model can reliably guide the selection of optimal parameters for any combination of factors. Ultimately, the insights garnered from this study hold promise for the large-scale production of taro mucilage-based soy yogurt, offering a versatile and nutritious addition to the repertoire of dairy alternatives.
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