Year of Publication

2011

Degree Name

Master of Science (MS)

Document Type

Thesis

College

Agriculture; Engineering

Department

Biosystems and Agricultural Engineering

First Advisor

Dr. Manuel Castillo

Second Advisor

Dr. Fred Payne

Abstract

Curd syneresis, a critical step in cheesemaking, directly influences the quality of cheese. The syneresis process is empirically controlled in cheese manufacturing plants. A sensor technology for this step would improve process control and enhance cheese quality. A light backscatter sensor with a Large Field of View (LFV) was tested using a central composite design over a broad range of cheese process conditions including milk pH, calcium chloride addition level, milk fat to protein ratio, temperature, and a cutting time factor (β). The research objectives were to determine if the LFV sensor could monitor coagulation and syneresis steps and provide information for predicting pressed curd moisture. Another objective was to optimize cheese yield and quality. The LFV sensor was found to monitor coagulation and syneresis and provide light backscatter information for predicting curd moisture content. A model for relating final curd moisture content with light backscatter response was developed and tested. Models for predicting whey fat losses, pressed curd moisture, and cheese yield were successfully developed (R2>0.75) using the test factors as independent variables. This was the first attempt to develop a technology for controlling pressed curd moisture using a sensor to monitor the syneresis step.

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