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采用响应面法优化蜂蜜酒的生产。

Optimization of mead production using response surface methodology.

机构信息

ESA-Polytechnic Institute of Bragança, Apartado 1172, Bragança, Portugal.

出版信息

Food Chem Toxicol. 2013 Sep;59:680-6. doi: 10.1016/j.fct.2013.06.034. Epub 2013 Jul 13.

Abstract

The main aim of the present work was to optimize mead production using Response Surface Methodology. The effects of temperature (x₁: 20-30°C) and nutrients concentration (x₂: 60-120g /hL) on mead quality, concerning the final concentrations of glucose (Y₁), fructose (Y₂), ethanol (Y₃), glycerol (Y₄) and acetic acid (Y₅), were studied. Twelve operational conditions were tested. No delays and moods were observed during fermentations. The second order polynomial models determined produced satisfactory fittings of the experimental data with regard to glucose (R²=0.646, p=0.001), ethanol (R²=0.741, p=0.049), glycerol (R²=0.899, p=0.002), fructose (R²=0.902, p=0.033) and acetic acid (R²=0.913, p=0.001). The optimum extraction conditions determined in order to maximize the combined responses were 24°C and a nutrients concentration of 0.88g/L. The mead produced under these conditions had the following characteristics: ethanol concentration of 10.2%, acetic acid 0.54 g/L, glycerol 7.8 g/L, glucose 1.8 g/L and fructose 2.5 g/L. These values were in agreement with the predicted and were within the safe limit established for acetic acid and the recommended range for glycerol. Furthermore, the residual sugars concentration was also low, decreasing the possibility of occurring undesirable refermentations.

摘要

本工作的主要目的是使用响应面法优化蜂蜜酒的生产。研究了温度(x₁:20-30°C)和营养物浓度(x₂:60-120g / hL)对蜂蜜酒质量的影响,涉及葡萄糖(Y₁)、果糖(Y₂)、乙醇(Y₃)、甘油(Y₄)和乙酸(Y₅)的最终浓度。测试了 12 种操作条件。发酵过程中未观察到延迟和情绪。确定的二阶多项式模型对葡萄糖(R²=0.646,p=0.001)、乙醇(R²=0.741,p=0.049)、甘油(R²=0.899,p=0.002)、果糖(R²=0.902,p=0.033)和乙酸(R²=0.913,p=0.001)的实验数据具有令人满意的拟合效果。为了最大化综合响应,确定的最佳提取条件为 24°C 和 0.88g/L 的营养物浓度。在这些条件下生产的蜂蜜酒具有以下特点:乙醇浓度为 10.2%,乙酸 0.54g/L,甘油 7.8g/L,葡萄糖 1.8g/L,果糖 2.5g/L。这些值与预测值一致,并且在乙酸的安全限量和甘油的推荐范围内。此外,残余糖浓度也较低,降低了发生不良再发酵的可能性。

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