Characteristics - Cevrin di Coazze is a ripened cheese produced from a mixture of goats' and cows' milk.  The concentration of cows' milk must be 60-70%.  Cevrin di Coazze cheese is cylindrical with flat surfaces.  The cylindrical shape has a diameter of 15-18 cm, an edge of 7-10 cm and a weight of 800-1500 g. Ripening lasts at least 20 days but is frequently longer than 120 days.  The crust is smooth and regular but not elastic.  The colour is wrinkled, hard, and reddish-grey with yellow and white highlights depending on its age.  The dough is yellowish with small and sparse holes.  The texture is soft and elastic.  The odour is strong and persistent.  The taste is very savoury and mainly hot, salty and acid in ripened products.

Can you destroy Mycobacterium avium subsp. paratuberculosis (MAP) by pasteurization? How important is holding time compared with holding temperature?  Use the powerful free tools in this section to answer these questions.

 DSFT provides a range of consultancy services to ice cream, gelato, sherbet and sorbet manufacturers. These range from help in formulating recipes, reducing costs by replacing expensive imported additives, problem solving, courses in advanced product manufacture, advice on all aspects of HACCP including process validation, providing assistance in discussions with regulatory authorities to independent audits of plant, process and external advice received. Independent nutritional advice on the manufacture and safety of low or sugar-free gelato and ice cream products is also provided.

We can help with the development and commercial production of soya and dairy-free, high protein ice cream-like products with or without sucrose. There are better options than sorbitol and fructose. Science based advice on describing products intended for consumers with health issues can also be provided.

Despite work undertaken over 20-years ago by researchers in Canada many large scale ice cream producers have limited knowledge of the minimum holding time of ice cream mix processed using HTST or HHST heat-processes. Furthermore many lack the evidence that they meet regulatory requirements for holding time. DFST can use your plant data to calculate average holding time, flow type, minimum residence or holding time, the log reductions of major pathogens and advise on any remedial action required.

 

Contact DSFT

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.

The purpose of this article is to show how the calculator for predicting salmonella growth on tomatoes was written in ASP. I would like to encourage lecturers and students to learn how to programme. While ASP is being replaced by ASP.NET the basic premises using in ASP coding can be applied to other languages and even if you decide to learn PHP which is a particularly versatile web language or other language (probably good idea) you will be able to apply the concepts learned.

There are several programming languages used to construct models that will run on web servers. These include Perl, PHP, Python, Classic ASP, JavaScript and ASP.Net. These languages can be used with appropriate databases to develop powerful web-based applications.

PHP has become particularly popular and is fairly easy to learn. Classic ASP is even easier to learn but is increasingly being replaced by ASP.NET. Virtually anyone who can put a spreadsheet together is capable of learning a basic web programming language such as ASP or PHP.

Constructing the data entry form

The HTML and ASP code used to construct the data entry form is shown below. For simplicity web page header information, value information in ASP and some form security information has not been shown. Nevertheless the form and script below will work on a PC or webserver that supports ASP without amendment.

The input form was constructed by writing the code for a table in HTML and adding in HTML text boxes to allow initial number (no), temperature (t) and incubation time (hr) to be entered.

 <%@LANGUAGE="VBSCRIPT" CODEPAGE="1252"%> ' A standard HTML header could be used instead

<form id="form1" name="form1" method="post" action="sam1.asp">

<table width="75%" border="1" cellspacing="0" cellpadding="1">
<tr>
<th colspan="2" scope="col">Predict the growth of salmonella in cut tomatoes at 10&deg;C to 35&deg;C</th>
</tr>
<tr>
<td width="41%">Initial number of salmonella / gram</td>
<td width="59%"><input name="no" type="text" id="no" value="<%=no%>" /></td>
</tr>
<tr>
<td>Temperature, &deg;C</td>
<td><input name="t" type="text" id="t" value="<%=t%>" /></td>
</tr>
<tr>
<td height="20">Incubation time, hours</td>
<td><input name="hr" type="text" id="hr" value="<%=hr%>" /></td>
</tr>
<tr>
<td height="20" colspan="2"><div align="center">
<input type="submit" name="Predict number of samonella" id="Predict number of samonella" value="Predict number of salmonella" />
</div></td>
</tr>
</table>
<p>&nbsp;</p>
</form>

Writing the data processing script

A simplified, but fully working, version of the processing script is given below. The notes which are preceded by a ' explain how the script works.

<%@LANGUAGE="VBSCRIPT" CODEPAGE="1252"%>


<% Option Explicit
'Use of option explicit will ensure that error messages are displayed if there are coding problems. These are helpful in finding solutions. %>

<%


'List variables

Dim no
Dim t
Dim hr

'no, t and hr are values that have been entered on the form
Dim r
Dim g
Dim gen
Dim pop

'r,g,gen, pop are the products of calculations that will be undertaken

'We will now obtain the information from the entry form to perform the calculation

no=CSng(Request.form("no"))
t=CSng(Request.form("t"))
hr=CSng(Request.form("hr"))


'Taking information from the form we will calculate r,g, gen and pop. This could easily be done in one calculation. The calculation has been broken down into its component parts so that it can be followed more easily.

'For an explanation of the calculation please see http://www.dairyscience.info/index.php/food-model/258-predict.html
 
r=0.026*(t)-0.1065
g=1/(r*r)  'note r is the square root of the growth rate, we need to obtain the growth rate by multiplying r by r
gen=hr/g
pop = no*2^gen

'We next need to provide the results of the calculation for pop which is the total number of salmonella after growth at the temperature chosen for the time inputted.

If t >9.99 AND t <35.01 THEN ' basic validation to ensure that the results are within the temperature parameters modelled

'The  'If Statement' is used to make a decision to execute code if some condition is True.
 
response.write ("The predicted number of samonella after" & "&nbsp;" & (hr)& "&nbsp;" & "hours has been calculated as" & "&nbsp;" & round(pop,0) & "&nbsp;" & "CFU/g.")
 END IF

'END IF is used to indicate the end of code execution


IF t < 10 THEN
Response.Write ("&nbsp; Caution. This model as not been validated at temperatures <10&deg;C.")
END IF

IF t > 35 THEN
Response.Write ("&nbsp; Caution. This model as not been validated at temperatures >35&deg;C")
END IF
%>

Using the scripts

The simplest way of using the scripts is to copy each using a simple text editor e.g. Notepad on a PC or its equivalent on a Mac or Linux machine. Save the form script using whatever "name" you want as name.htm or name.asp. The data processing script must be saved as sam.asp since sam.asp is the name of the script in the input form that has been designated to process the data.

These scripts will work on a Windows web server or a Windows PC running Microsoft's free IIS or PWS components. 

Qualifications/Disclaimer

The scripts  have been provided free and are not warranted in any way. They are intended for educational use only. They can easily be adapted to work using PHP or JavaScript. Users use the code provided at their own risk. 

Acknowledgements

I learned ASP, how to use Access Databases and HTML from a former colleague Dr Raymond Martin. Raymond generously helped me correct concatenation and many other errors and though his help I gradually learned how to write quite sophisticated data-base driven ASP applications. I gratefully acknowledge Raymond's help over many years.


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=80 . Accessed: 8 July, 2020. Updated December 2019. 

The basic principles of phage control in commercial plants have been known since the early 1940s and the pioneering work of Dr Hugh Whitehead and his colleagues in New Zealand. The review by Whitehead and Hunter (1945)* on the measures that were being used in New Zealand to control slow acid production due to phage infection is still of relevance to factory managers today.

Characteristics - Bruss is not a cheese but a typical Piedmont cheese by-product obtained by fermentation of a mix of fresh cheeses, ripened cheeses and ricotta.  These products are ground to help the fermentation and put in glass or terracotta containers.  After some day's alcohol is added to the mixture, called 'cream,' to accentuate the aroma and to stop the fermentation.

Subcategories

We use cookies to improve our website and your experience when using it. To find out more about the cookies we use, see our Privacy and Cookie Policy.

info_icon articles