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The need for cheese grading

Assessment of cheese quality is essential in order to determine if the cheese conforms to legal standards, meets the requirements of the buyer and ultimately the customer and to grade the cheese for payment. A cheese may meet all legal and safety requirements but have appearance, taste, flavour and or texture defects that make it unpalatable or only suitable as an ingredient in e.g. sauces. Because cheeses like Cheddar require extended maturation in some cases for as long as 18 months or more to give extra mature high value cheese, assessment of quality through a grading scheme is used to exclude cheeses with defects. Storage is expensive and companies cannot afford to waste money storing inferior quality cheeses.

The traditional method of assessing cheese quality is organoleptic assessment by a cheese grader. Until relatively recently the suitability of cheese for end consumer use was judged almost entirely on flavour and texture assessments by commercial cheese graders. To assess the cheese, the cheese grader visually examines the outside, and an inner core of the cheese. Examination of the sample core, immediately on withdrawal from the cheese, provides the grader with indices of aroma, colour, texture and body. These typically form the basis of traditional approaches to cheese grading.

Giles and Lawrence (1973) discussed the failings of commercial graders in selecting Cheddar cheese for extended maturation for export by referring to work by Robertson (1968) who found that only 20 to 40% of conventionally made cheeses which graded “Finest” at 14 days in New Zealand retained their grade on re-examination five to six months later in London, England.

Interestingly Giles and Lawrence (1973) suggested that the loss in quality at maturity was generally due either to fracturing of the body or the development of sulphide-type flavours. While they explained that these defects are partly due to the variable composition of the cheeses they may also occur if the rate and extent of acid development is abnormally high during manufacture. This latter point is important and is still relevant today!

Increasingly, chemical and physiochemical indicators are being used in conjunction with more traditional cheese grading particularly when selecting cheese for extended maturation.

This article explores a model using simple chemical or physiochemical components that can be used to predict the quality of Cheddar cheese and whether a batch of cheese is suitable or extended maturation to yield a high value mature cheese. The model can be freely evaluated using On Line calculator.

Modelling cheese quality

During maturation, bacteria and enzymes act on the fat, protein and carbohydrate in the cheese to produce the body, texture and flavour characteristic of mature Cheddar and other cheeses. The changes in body and texture that transform the rubbery, elastic mass of curd to a cheese with a firm close texture are the results of protein and fat degradation. The release of volatile components from the curd gives the aroma to cheese and associated flavours.. 

In efforts to focus the New Zealand dairy industry on a more uniform end product that would facilitate the development of new markets a model for predicting Cheddar cheese quality was developed by Gilles and Lawrence (1973). This model was an attempt to grade Cheddar cheese into grade categories based on an analysis of chemical and physiochemical components, 24 hours after cheese manufacture.

The model was based on four main compositional factors.

 1. The percentage of salt in moisture (S/M): S/M is the major factor controlling water activity (aw) in young Cheddar cheese. Available water will influence the rate of bacterial and enzyme activity e.g. the activity of residual chymosin within the curd and can be used to influence the microflora of the mature cheese. Cheese makers should aim for a S/M percentage which when combined with temperature control will allow the metabolism of lactose by the starter bacteria at a controlled rate and reduce the potential for growth of non-starter lactic acid bacteria such as lactobacilli. At S/M percentages of <3.5% there is greater potential for starter growth to high cell densities with the risk of bitter flavour development and more rapid growth of non-starter lactic acid bacteria with further potential flavour and body defects. Proteolysis by residual coagulant will also be greater, increasing the potential of off flavour and body defects. At S/M levels of > 6%, lactose metabolism by starter cultures is effectively inhibited, resulting in at best, slow ripening cheese with flavour and texture defects. On the other hand at S/M concentrations > 4% and <6 % Lawrence and others have found that there is a high probability of cheese of at least satisfactory quality being produced.

2. Moisture in, the fat-free-substance (MFFS): This is an indication of the relative amounts of moisture and casein in the cheese. The effect of moisture is more closely related to the amount of moisture per unit of casein since it is in the matrix of moisture and casein that the enzymatic reactions responsible for ripening largely take place. Several workers have found that MFFS was a major compositional parameter affecting grade of cheese and cheese quality in general. There is now convincing evidence that it is the relative hydration of the casein in the curd, rather than the overall moisture content that influences the ripening process

3. Fat in the dry matter or fat in the water-free substance (FDM or FWFS): While FDM has the potential to have a significant effect on the body of Cheddar cheese this parameter is relatively easily controlled by standardisation of the casein to fat ratio in the raw milk. As it is the casein matrix that binds the fat, the more fat present the weaker the body and vice versa. It should be noted however that relatively large ranges of FDM, within the legal range for Cheddar, can be tolerated.

4. pH: The pH of cheese curd is one of the distinguishing characteristics that can differentiate cheese types. The pH and the ratio calcium/ Kg of solids-not-fat (SNF) can be used to classify traditionally manufactured cheese varieties. pH like S/M also influences rates of enzymatic and bacterial activity. Manipulation of pH can be used to influence the microflora of the mature cheese. The pH of the curd at one day post manufacture gives an indication as to the extent of acid development during manufacture and the level of preservation and the potential 'safety' of the cheese. The potential for further acid development is dependent on the residual lactose in the curd and the buffering capacity of the curd. The model (fig.1) developed by Giles and Lawrence  (1973) uses the four compositional factors outlined previously (fig.1) and through analysis of an extensive volume of results obtained from commercial cheese plants sets limits on each. The limits are divided into two categories, that of Premium (S/M 4-6%, MNFS, 52-56%; FDM 52-55; pH 4.95-5.1 and First grade cheese (S/M 2.5-6%, MNFS, 50-57%; FDM 50-56; pH 4.85-5.2). These workers have suggested that if a curd falls within the specifications for Premium and has no flavour defects at 14 days it is suitable for export and hence long maturation.

Lawrence model for predicting grade value of Cheddar cheese


The model works fairly well in practice. Browsers can obtain predicted grading values for individual lots of Cheddar cheese using the calculator below. Please note that the calculator is provided for educational use only and the grade values are not warranted in any way! It is very easy to modify this calculator using results from individual plants so as to have a more accurate grade prediction model.

Importance of rate of acid development in cheese making

During the development of the model Giles and Lawrence (1973) reminded readers of work by Harkness et al. (1958) that a “sweeter” (lower titratable acidity at milling) make of cheese has a more pleasant flavour at maturity than an “acid” cheese.

However, a “sweet” make cheese does not grade well at 14 days since the cheese is still rather “curdy” (not “broken down”). Hence, these workers explained that New Zealand cheesemakers were reluctant to make such cheese for export.

Giles and Lawrence (1973) explained that their proposed grading system would enable such cheese to be graded “Premium” since the composition and pH of the cheese would indicate that the curdiness was not due to partial starter failure and that the cheese would subsequently develop in a normal and satisfactory manner.
It has not been sufficiently recognized in the past that the rate and extent of acid production not only determines indirectly the composition of the cheese but also governs the degree of acceptability of the cheese to the customer. Grading cheese by composition and pH does to a large extent overcome this problem.

Limitations of the Giles and Lawrence model

Many models have limitations and this is also true for the Lawrence model. While it is outside the scope of this article to discuss these in detail, some of the limitations are apparent from the requirement to use a flavour assessment after 14 days of ripening to exclude cheeses with flavour problems. This flavour check is required for several reasons including the absence of factors influencing grading quality at 14 days in the model e.g. no allowance has been made for using milk stored for significant periods prior to use in cheese manufacture or containing a) high concentrations of microbial-lipases, b) significant concentrations of colostrum or late lactation milk, or c) high somatic cell counts.

Evaluate the Giles and Lawrence model


Giles, J. and Lawrence, R. C. (1973). N. Z. J. Dairy Sci. Technol. 8, 148–151.
Harkness, W. L., Gilles, J. and Whitehead H. R. (1958). 31st Annual Report, New Zealand Dairy Research Institute.
Robertson, P. S. (1968). The Primary Producer, June 14 (Aust).

How to cite this article

Mullan, W.M.A. (2005). [On-line]. Available from: https://www.dairyscience.info/cheese-manufacture/66-modeling-the-grade-value-of-cheddar-cheese.html . Accessed: 21 January, 2017. Updated 2015. Updated January 2017.

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