Liu Siqi, Contreras Fanny, Alemán Ricardo S, Fuentes Jhunior Marcía, Arango Oscar, Castillo Manuel
Centre d'Innovació, Recerca i Transferència en Tecnologia dels Aliments (CIRTTA), Departament de Ciència Animal i dels Aliments, Facultat de Veterinària, Universitat Autònoma de Barcelona, 08193 Bellaterra, Spain.
Department of Poultry Science, Auburn University, Auburn, AL 36849, USA.
Foods. 2024 Aug 30;13(17):2766. doi: 10.3390/foods13172766.
Current systems that allow inline pH control in the fermented dairy industry have drawbacks, such as protein adhesion on the non-glass pH probes, measurement distortion, frequent recalibration needs, and sensitivity to extreme pH conditions encountered during clean-in-place operations. Therefore, the objective of this study was to validate the feasibility of estimating the pH of milk during the yogurt making process by using a NIR light backscatter sensor measuring under different fermentation temperatures and milk protein concentrations using a mathematical model that correlates the light scatter signal with pH. Three replications of the experiment with two protein concentrations (3.5 and 4.0%) and two fermentation temperatures (43 and 46 °C) were used to validate this inline pH prediction model. Continuous and discontinuous measurements of pH were collected as a reference during fermentation, simultaneously with the light backscatter data acquisition. Also, the effect of adjusting the initial voltage gain of the light scatter device on the accuracy of the pH prediction model was evaluated. Temperature and initial voltage were the main factors affecting the fitting accuracy of the model. The adjustment of the initial voltage gain improved the pH prediction model fit. The model has been successfully validated for both continuous and discontinuous measurements of pH, with SEP values < 0.09 pH units and CV < 1.78%. The proposed optical inline and non-destructive method was feasible for inline pH monitoring of milk fermentation, avoiding traditional manual pH measurement.
当前发酵乳制品行业中允许在线pH控制的系统存在缺点,例如蛋白质粘附在非玻璃pH探针上、测量失真、频繁重新校准的需求以及对原位清洗操作期间遇到的极端pH条件敏感。因此,本研究的目的是通过使用近红外光背散射传感器,在不同发酵温度和牛奶蛋白浓度下进行测量,并使用将光散射信号与pH相关联的数学模型,来验证在酸奶制作过程中估算牛奶pH值的可行性。使用两种蛋白质浓度(3.5%和4.0%)和两种发酵温度(43和46°C)进行了三次重复实验,以验证这种在线pH预测模型。在发酵过程中,作为参考,连续和不连续地收集pH测量值,同时采集光背散射数据。此外,评估了调整光散射装置的初始电压增益对pH预测模型准确性的影响。温度和初始电压是影响模型拟合精度的主要因素。初始电压增益的调整改善了pH预测模型的拟合。该模型已成功验证了pH的连续和不连续测量,SEP值<0.09 pH单位,CV<1.78%。所提出的光学在线和非破坏性方法对于牛奶发酵的在线pH监测是可行的,避免了传统的手动pH测量。