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Τετάρτη 7 Ιουνίου 2017

Effect of uncertainty in composition and weight measures in control of cheese yield and fat loss in large cheese factories

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Publication date: Available online 7 June 2017
Source:Journal of Dairy Science
Author(s): Brenda Margolies, Michael C. Adams, Joice Pranata, Kathleen Gondoutomo, David M. Barbano
Our objective was to develop a computer-based cheese yield, fat recovery, and composition control performance measurement system to provide quantitative performance records for a Cheddar and mozzarella cheese factory. The system can be used to track trends in performance of starter cultures and vats, as well as systematically calculate theoretical yield. Yield equations were built into the spreadsheet to evaluate cheese yield performance and fat losses in a cheese factory. Based on observations in commercial cheese factories, sensitivity analysis was done to demonstrate the sensitivity of cheese factory performance to analytical uncertainty of data used in the evaluation. Analytical uncertainty in the accuracy of milk weight and milk and cheese composition were identified as important factors that influence the ability to manage consistency of cheese quality and profitability. It was demonstrated that an uncertainty of ±0.1% milk fat or milk protein in the vat causes a range of theoretical Cheddar cheese yield from 10.05 to 10.37% and an uncertainty of yield efficiency of ±1.5%. This equates to ±1,451 kg (3,199 lb) of cheese per day in a factory processing 907,185 kg (2 million pounds) of milk per day. The same is true for uncertainty in cheese composition, where the effect of being 0.5% low on moisture or fat is about 484 kg (1,067 lb) of missed revenue opportunity from cheese for the day. Missing the moisture target causes other targets such as fat on a dry basis and salt in moisture to be missed. Similar impacts were demonstrated for mozzarella cheese. In analytical performance evaluations of commercial cheese quality assurance laboratories, we found that analytical uncertainty was typically a bias that was as large as 0.5% on fat and moisture. The effect of having a high bias of 0.5% moisture or fat will produce a missed opportunity of 484 kg of cheese per day for each component. More accurate rapid methods for determination of moisture, fat, and salt contents of cheese in large cheese factories will improve the accuracy of yield performance evaluation and control of consistency of cheese composition and quality.



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