© 2018 Elsevier Ltd Optical sensors based on light backscatter are being used by important cheese industries worldwide for predicting cutting time, but predictions can be affected by factors influencing coagulation such as milk composition or ingredients addition. Enzymatic coagulation of reconstituted milk with inulin as a fat substitute was monitored in parallel using a rheometer and an optical sensor, in order to obtain and validate models for predicting rheological gelation time (tG′1) and cutting time (tG′30). Prediction models were fitted using data from a factorial design with three factors: inulin (2, 5, 8 g/100 g), protein (3, 4, 5 g/100 g) and calcium (100, 200 mg/L) concentrations, and afterwards were validated with data from a central composite design experiment, where the same factors, but with different levels were evaluated. The addition of inulin to milk decrease tG′1 and tG′30 due to the inulin water retention capability. The increase in protein and calcium concentrations also produced a decrease in the curd firming phase. Optical parameters were sensitive enough to account variations in milk composition or ingredients addition and allowed obtaining and validating good prediction models for gelation and cutting times.
|Journal||LWT - Food Science and Technology|
|Publication status||Published - 1 May 2018|
- Cutting time
- NIR light backscatter
- Optical sensor
- Prediction models
Arango, O., Trujillo, A. J., & Castillo, M. (2018). Modelling gelation and cutting times using light backscatter parameters at different levels of inulin, protein and calcium. LWT - Food Science and Technology, 91, 505-510. https://doi.org/10.1016/j.lwt.2018.01.081