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, Cerdanyola del Vallès, Barcelona, Spain.
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, Cerdanyola del Vallès, Barcelona, Spain.
Food Res Int. 2022 Nov;161:111745. doi: 10.1016/j.foodres.2022.111745. Epub 2022 Jul 29.
A plethora of different factors, such as heat treatment, pH, soluble calcium and phosphate concentrations, colloidal calcium phosphate, ionic strength, redox potential, etc., affect functionally of critical milk components such as casein micelles, fat globules and whey proteins. These physicochemical changes induce fat- or protein-protein interactions that would be associated to changes in particle size that might be revealed using light backscatter measurements. We hypothesized that inline, simple, low-cost light backscatter measurements might have the potential to provide functionally related information, representing an interesting opportunity for process control. Casein micelle particle size and near infrared light backscatter spectra were measured in milks heat treated at 80 and 90 °C and pH 6.3, 6.7 and 7.1 in order to obtain prediction models for estimating changes in casein micelle particle size during milk heat treatment. Light intensity was measured over a spectral range of 200-1100 nm using a simple optical backscatter sensor and was implemented into models for particle size predictions as a function of heat treatment temperature and pH. Models which included an exponential factor containing a ratio of two specific wavebands were found to improve R when compared to single wavelength models. The best model exhibited an R of 0.993 and SEP of 2.36 nm. The developed prediction models show promise for in-line monitoring of whey protein denaturation and casein micelle particle size.
大量不同的因素,如热处理、pH 值、可溶钙和磷酸盐浓度、胶体磷酸钙、离子强度、氧化还原电位等,都会影响到关键牛奶成分的功能,如酪蛋白胶束、脂肪球和乳清蛋白。这些物理化学变化会导致脂肪或蛋白质-蛋白质相互作用,从而与粒径变化相关联,这些变化可以通过光背散射测量来揭示。我们假设在线、简单、低成本的光背散射测量可能具有提供功能相关信息的潜力,这代表了一种有趣的过程控制机会。在 80 和 90°C 以及 pH 值为 6.3、6.7 和 7.1 的条件下对牛奶进行热处理,测量了酪蛋白胶束粒径和近红外光背散射光谱,以获得用于估计牛奶热处理过程中酪蛋白胶束粒径变化的预测模型。使用简单的光学背散射传感器在 200-1100nm 的光谱范围内测量光强度,并将其作为热处理温度和 pH 值的函数纳入粒径预测模型中。与单波长模型相比,发现包含两个特定波段比值的指数因子的模型能够提高 R。最佳模型的 R 为 0.993,SEP 为 2.36nm。所开发的预测模型有望用于在线监测乳清蛋白变性和酪蛋白胶束粒径。