Galactooligosaccharides (GOS) production from whey, a relevant by-product of dairy industry, answers to the Circular Economy principle of extending the life cycle of products. Indeed, it allows the reuse of dairy waste to produce prebiotics to be used in functional food preparations. For this purpose, the effective monitoring of GOS production should be performed in real time and by environmentally friendly techniques. Thus, FTIR spectroscopy, combined with different chemometric approaches, has been tested to assess a Process Analytical Technology to follow GOS production from cheese whey. Partial Least Square regression models were reliable for lactose, glucose and galactose determination (Root Mean Square Error of Prediction of 21.9, 11.1 and 12.4 mg mL⁻¹, respectively). Furthermore, Multivariate Curve Resolution – Alternating Least Square models were proposed to describe trends of the reaction components along the process being an interesting alternative to chromatographic determinations. The real time implementation of the proposed approach will provide the dairy industry with a reliable and green Process Analytical Technology for dairy waste reallocation, avoiding sample pre-processing, large use of organic solvents and long times of analysis.

乳制品相关副产品乳清生产的低聚半乳糖（GOS）符合延长产品生命周期的循环经济原则。实际上，它可以使乳制品废料再利用以生产用于功能性食品制剂的益生元。为此，应实时并通过环保技术对GOS生产进行有效监控。因此，已经测试了结合不同化学计量学方法的FTIR光谱法，以评估工艺分析技术，以追踪奶酪乳清中GOS的生产。偏最小二乘回归模型可用于确定乳糖，葡萄糖和半乳糖（预测的均方根误差为21.9、11.1和12.4 mg mL ^-1）， 分别）。此外，提出了多元曲线分辨率–交替最小二乘模型来描述反应过程中反应组分的趋势，这是色谱测定的一种有趣的替代方法。拟议方法的实时实施将为乳制品行业提供可靠，绿色的过程分析技术，用于乳制品废物的重新分配，避免样品前处理，有机溶剂的大量使用和长时间的分析。