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

Abstract

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.

Determination of fat, protein, moisture, and salt content of Cheddar cheese using mid-infrared transmittance spectroscopy

“…It appears that the NIR fat calibration is not satisfactory in this factory. This is consistent with observations reported by Margolies et al (2017). For fat, the SDD between NIR and reference chemistry was larger (0.42) than the SDD between MIR and reference chemistry (0.11, Table 2).…”

“…The regression analyses of reference salt values as a function of predicted salt by the coulometric method ( Figure 3A) and MIR ( Figure 3B) had very different R 2 values of about 0.16 and 0.94, respectively. The large difference in prediction performance between the commonly used coulometric method in commercial cheese factories and the MIR was surprising, but the poor performance was consistent with observations of weakness in the quality of cheese analysis data observed in our previous study (Margolies et al, 2017). Protein content of cheese is not routinely measured in most cheese factories; however, protein makes a very important contribution to cheese yield.…”

“…The poor agreement between fat reference chemistry and NIR predictions could be due to inaccuracy in fat reference chemistry done in the cheese factory and that was used to calibrate their NIR or lack of robustness of the NIR PLS prediction model. In practice, this is what was seen in our survey of cheese factory analytical performance in the previous cheese yield and composition control study (Margolies et al, 2017).…”

“…Measurement of cheese yield, recovery of fat and protein, and evaluation of cheese composition control in large-scale cheese factories is an important aspect of cheese factory management. A system for evaluation and control of these parameters was reported by Margolies et al (2017).…”

“…During the testing of a cheese yield evaluation system in large commercial cheese factories, it was observed that the daily mean bias error in measurement was as high as ±0.5% for fat and moisture in commercial cheese factories. It was concluded that the accuracy of rapid secondary testing methods needed improvement (Margolies et al, 2017).…”