Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
8891990 | LWT - Food Science and Technology | 2018 | 6 Pages |
Abstract
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 (tGâ²1) and cutting time (tGâ²30). Prediction models were fitted using data from a factorial design with three factors: inulin (2, 5, 8â¯g/100â¯g), protein (3, 4, 5â¯g/100â¯g) and calcium (100, 200â¯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 tGâ²1 and tGâ²30 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.
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Authors
O. Arango, A.J. Trujillo, M. Castillo,