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This page provides access to an interactive spreadsheet in which data for the chemical composition of milk and cheese and actual yields can be recorded. The software will then calculate theoretical yield, process efficiency, key compositional criteria and provide a basic statistical analysis of the results. Real data have been provided and these can be replaced with test data to use the spreadsheet.

This software could be used with the cheese yield problem provided along with the overview of how the problem might be investigated to teach the principles of process control in cheese manufacture.

Go to interactive spreadsheet.

Whole milk powders with a range of fat concentrations are available commercially. The dairy technologist may be required to standardise raw milk to a particular fat concentration to enable the production of powder to a specified fat concentration to be produced.

A calculator for determining the fat concentration required in the raw milk to produce a powder of a specified fat concentration
can be accessed here.

This is the access page to the free molarity calculators designed by Dr Michael Mullan. It is not unusual for students and others to miscalculate the volumes of solutions or the weight of compounds required to produce solutions. The molarity calculators accessed here should enable students and others to check their calculations.

The calculator below is based on a model developed by Giles and Lawrence (1973) to predict the grade value of Cheddar cheese. Instructions on how to use the calculator are given below. Note that the pH and other values should be obtained from 24-hour old cheese.

Click here to use the calculator

Click here to use the calculator

# Ice Cream Mix Calculator

The objective in calculating ice cream mixes is to turn a formula into a recipe based on the intended ingredients and the mass or volume of mix required.  The recipe is then processed to obtain ice cream for distribution and sale.  In the UK and in North America the formula is given as percentages of fat, milk solids-not-fat (MSNF), sugar, stabilisers-(stabilizers in the US) and emulsifiers. Since several ingredients may be available to supply these components e.g. MSNF available ingredients are selected on the basis of quality and cost.

Because the concentration of fat, milk solids not fat (MSNF) and protein in milk vary with season, and other well documented factors, it is necessary to adjust the composition of milk for use in the manufacture of cheese and other dairy products. This process, called milk standardisation (standardization in the US) is designed to ensure that product composition and quality is maintained at a consistent level throughout the year e.g. fat in dry matter in cheeses. This area will be dealt with in more detail elsewhere in this website.

Increasingly standardisation is being done automatically using on line instrumentation. In small dairies this is still done 'manually' including calculating the volumes (or weights) of skim milk, milk powder, casein powder and whole milk required to produce a particular quantity of milk of a defined fat, protein, casein or MSNF concentration.

One of the simplest methods of routinely adjusting the fat concentration of milk for cheese, ice cream or whole milk powder manufacture is to use the Pearson Square or Rectangle. This method may also be called Pearson's Square or Pearson's Rectangle. This is a simplified method for solving a two variable simultaneous equation. While it is being used here with milk it is is a tool that can be used to help processors calculate the amounts of two components that need to be mixed together to give a final known concentration.

Note the process of standardization is widely used in the food industry. It can be used to calculate the amounts of fruit juice and sugar syrup to be mixed to make a fruit squash or fruit pulp and sugar to make a jam. It is also used in mixing rations for animal feeding and in the meat industry to produce meat products e.g. sausages to a particular fat content. Wines and other alcoholic beverages are also blended to give products of a specified alcohol concentration. Microsoft Excel spreadsheets for undertaking these calculations can be downloaded.

This tool can only be used for blending two components. When more than two components are involved, more complex mass balance equations have to be used. The first step in using this method is to draw a rectangle. At the centre of the rectangle write the concentration of fat required in the cheese milk. At the upper left hand side write the % fat concentration of the milk; the most concentrated fat source used. At the bottom left hand corner place the fat concentration of the skim-milk used. On the top right hand side write 'parts milk' and on the bottom left hand side write 'parts skim'.

The 'parts milk or skim' are obtained by subtracting the lowest value number, working diagonally, from either the desired final fat concentration in the case of milk or by subtracting the value for final fat concentration from the concentration of fat in the milk.

This process gives the proportions of milk and skim that must be mixed together to give the desired fat concentration. Knowing the weight or volume of the final mix, the actual quantities of milk and skim required can be obtained by a simple proportional calculation. Note this method can also be used to standardise protein, SNF and/or casein in milk.

Browsers can test their understanding of this basic calculation by using the calculator below. More information on Milk Standardisation is available in the Answers to cheese science and technology self assessment section.

Click here to use the calculator

How to cite this article

Mullan, W.M.A. (2006). [On-line]. Available from: https://www.dairyscience.info/index.php/packaging/78-articles/site-calculators-and-models.html . Accessed: 26 June, 2022.

Click here to use the calculator. Unlike most calculators on non-academic sites, the Dairy science calculator enables energy contribution from the the alcohol, organic acid and artificial sweetener components to be estimated.

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