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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.

The LP system can be used to prevent bacterial deterioration of milk when refrigeration is not available.  It can also be used to prolong the safe storage life of refrigerated milk.  Arguably the LP-system, immunoglobulins and lactoferrin have potential to be of value in neonate nutrition.  The remaining section largely concerns the exploitation of the LP-system in the protection of neonates.

Manufacture of milk powders containing a functional LP system

That milk provides neonates with nutrients and  various protective antimicrobial factors has been discussed previously.  Because many of these factors are denatured by the heat treatments used in milk replacer manufacture commercial products, unless specially produced, generally do not contain antimicrobial proteins in active form.

This article discusses the background of the change in classification of the lactic streptococci to the genus Lactococcus.

The lactic group of the genus Streptococcus originally included the species Str. lactis and Str. cremoris and a subspecies of Str. lactis, Str. lactis subsp. diacetylactis (Deibel and Seeley, 1974). However, even in the 1970s workers were suggesting that Str. lactis strains might be variants of Str. diacetylactis that were unable to ferment citric acid, since citrate permease – negative strains of Str. diacetylactis had been described (Lawrence, Thomas and Terzaghi, 1976).

Bacteria in this group were designated as the lactic streptococci. The designation 'lactic' was used by Sherman (1937) for mainly historical reasons, including the use of the term by Lister (1878) to describe a bacterium that we now know as Lc. lactis subsp. lactis.

lee-williamsLee Williams owns and operates Valenti’s Gelato-Artisan, a Company dedicated to promoting Artisan Ice Cream and Gelato making throughout the UK. He has over 35 years’ experience in the Ice Cream Industry. Lee began his career in a family business, a second generation of Ice Cream makers in SW England. During this time he worked in various locations including Southern Africa, creating a global perspective to his service. More recently he has developed strong working partnerships with European equipment manufacturers and Italian flavour houses. Valenti’s product portfolio includes all types of Artisan Ice Cream making equipment, gelato shop with parlour design and ingredients, together with training, mix formulation and technical support, available throughout the UK and Ireland.

 Valenti’s can provide specialist training at their Academy based in Cornwall the home of Ice Cream making and also on-site training programmes at the clients own premises.

Contact

Range of flavoured ice creams

Ice cream and gelato manufacturers produce products with a range of favours. There are often significant variations in sweetness and hardness between flavours. This article provides an explanation of sweetness, how it is measured and how it can be controlled.

Relative sweetness and the Potere Dolcificante method are discussed and calculations are used to explain the differences. The limitations and disadvantages of using numerical values of sweetness are explained. Since sweetness and hardness are closely related the reader is also referred to the article on controlling hardness or resistance to scooping.

Living microorganisms are widely used for several therapeutic purposes and their beneficial effects as biotherapeutic agents are well known. While certain strains of lactic acid bacteria and bifidobacteria are used as probiotics in pharmaceutical preparations, feed additives and so-called functional foods yeasts also possess some medicinal efficiency.

Modelling the spoilage of pasteurized milk

Spoilage of pasteurized milk is almost always due to the growth of microorganisms. These are generally introduced after heat treatment and are referred to as post process contaminants (PPCs).

The shelf life of pasteurized milk is largely dependent on the number of PPCs and storage temperature (e.g. Muir, 1996). Muir (1996) has described a simple equation (equation 1) relating the number of number of PPCs and storage temperature to shelf life of pasteurised milk.

Equation 1. Shelf life (h)={0.00621*(T+273-(269.55-0.74))*(CFC15)-0.11 x ( CFC15) x 2} -2.

Where T = storage temperature in °K; CFC15, =log10 count after pre-incubation of pasteurized milk at 15°C for 24 hours enumeration on milk agar containing a selective supplement for pseudomonads called cetrimide-fucidincephaloridine (CFC).

Muir (1996) has explained that the equation can predict shelf life at storage temperatures between 6°C and 14°C to within 1 day for between 60 and 90% of samples. The accuracy of the equation has been reported to increase as the storage temperature of the pasteurized milk increases.

Go to Shelf Life of Pasteurized Milk Calculator .



Literature cited
Muir, D.D. (1996) The shelf-life of dairy products: 2. Raw milk and fresh products. Journal of the Society of Dairy Technology. 49, 44-48.


How to cite this article

Mullan, W.M.A. (2015). [On-line]. Available from: https://www.dairyscience.info/index.php/cheese-starters/209-articles.html?start=40 . Accessed: 11 December, 2019.  

DRAFT ARTICLE

This article is available On Line to enable editing. Its draft status is scheduled to be removed by September, 2015. In the meantime comments are invited from scientists and technologists familiar with the subject area to help improve this article. I wish to acknowledge the generous comments and advice received from workers in this area. As a result of the feedback I will include more information about the principles behind modelling bacterial growth and the limitations of models.

Considerable effort has been devoted to modelling the growth of pathogenic and spoilage bacteria in food. This is referred to as predictive microbiology. Mathematical equations are used to describe the effect of environment, for example temperature, or in more complex models temperature, pH, available water (Aw) and other factors that affect microbial behaviour.

The advantages of modelling have been described in the article on "Modelling in Food Technology" including reducing the costs and time required in determining the safe shelf life of new products or in undertaking pathogen challenge testing. However, caution and scientific expertise are required e.g. the Food Safety Authority of Ireland (2012) has cautioned the food industry on the use of predictive models.

The purpose of this article and supporting material is to illustrate how published research in predictive microbiology can be used in practice. This is an area in which Food Science and Food Technology undergraduates sometimes find difficulty. Part of the difficulty may exist because the steps in the calculations involved are not usually presented.

This article describes a model for the growth of salmonella on cut tomatoes and a calculator where you can enter the initial numbers of salmonella, the incubation temperature and the incubation time to obtain a prediction of final numbers.

Modelling microbial growth

Because of the critical importance of temperature early work attempted to modify the Arrhenius Law to describe microbial growth but this was either unsuccessful or the relationships derived were generally too complex for routine use. In a classic paper, Australian workers (Ratkowsky et al., 1982) proposed a relatively simple, two–factor empirical equation (equation 1) to describe the influence of temperature on microbial growth up to the maximum growth temperature of an organism, Tmax.  This is often called the square root model.

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Many students have problems in understanding the mathematics describing the destruction of microorganisms by heat. Log reductions of pathogens and equivalent time-temperature treatments along with the associated lethalities account for a large part of the harder to understand topics. The quiz below is a simple test of of some of the basic concepts. Note Z value is not dealt with in this quiz. If there is sufficient interest I will provide the answers.

Heat Processing Quiz

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