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Commercially, cold-filled acidic pickles, sauces (e.g. salad cream, mayonnaise), and food dressings are preserved, and their microbiological safety and stability are assured, by the use of acetic acid, salt (NaCl), and sugar. This article provides an overview of a preservation model and access to the model to enable the effect of sauce components and pH to be investigated.
Comite´ des Industries des Mayonnaises et Sauces Condimentaires de la Communaute´ Économique Européenne (1992) (CIMSCEE) has provided guidance on a safety value, Σs, for a microbiologically safe product preserved using acetic acid and a stability value, Σ, above which microbial spoilage should not occur.
A safe product has been defined as one which is so formulated that when an inoculum of viable cells of Escherichia coli is added to the product this is reduced by 3 log cycles in less than 72 h. Products exhibiting this level of antibacterial activity have a CIMSCEE safety value (Σs) of greater than 63. Σs is calculated using equation 1. A microbiologically stable product is one that will not support microbial growth at ambient temperature and has a Σ value of greater than 63. Σ is calculated using equation 2.
Equation 1. Σs =15.75 (1 - ɑ) (total acetic acid* %) + 3.08 (salt* %) + (hexose* %) + 0.5 (disaccharide* %) + 40 (4-pH). Note, values with an * must be calculated as water phase values.
Equation 2. Σ =15.75 (1 - ɑ) (total acetic acid* %) + 3.08 (salt* %) + (hexose* %) + 0.5 (disaccharide* %). Note, values with an * must be calculated as water phase values.
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The Dairy Science and Food Technology website contains several free, On Line calculators, for determining the cumulative lethality (F, B*, P or PU) of thermal processes, the concentration of Thermal Process Indicators (TTI) following UHT treatment of milk and several other process indicators.
These calculators are listed on the Calculators and Models page under Thermal Processing e.g.
- Calculator for determining the lethality (F, value) of a thermal process using the Trapezoid and Simpson's rules. This unique calculator works with thousands of pasted values e.g. from a data logger.
- Calculator for determining the lethality (F, B* values) and chemical changes (C* value, formation of HMF, Lactulose, Furosine, and destruction of thiamine) in heated milk integrated using the Trapezoid and Simpson's rules.
- Calculator for determining the lethality (F, B* values) and chemical changes (C* value) for generic high-temperature processes using the Trapezoid and Simpson's rules.
- Determine the accuracy of 3 algorithms for predicting the concentration of lactulose in milk after defined heat treatment.
The lethality calculators convert temperature readings to lethal rates, plot the lethal rates against time, and determine appropriate lethality values or chemical indicators for a heat process whether using hot water, saturated steam or dry heat. The area under the time-lethality curve is determined by numerical integration using the industry standard method, the trapezoid rule or the more accurate Simpson's rules or both for comparative purposes. In general, the more values, the more accurate the value for F or P will be. One of the calculators will also upload CSV files of a thermal process and provides a facility for free, independent validation of a thermal process.
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Microbial testing is still important but it is critical to understand its limitations in assuring food safety.
Despite the global use of HACCP systems and a legal requirement for the use of HACCP in many jurisdictions' food poisoning remains an endemic problem and large numbers of people continue to be hospitalised, die and as a result companies either face substantial legal costs and / or in many cases are forced to cease trading.
While the use of HACCP systems significantly reduces the need for microbiological end point testing of foods, sampling schemes and microbial analysis have important roles in system validation and quality assurance. This article also provides access to three free On-Line calculators that enable the probability of detecting a pathogen in a food, the number of samples required to test to meet a food standard and how to calculate the prevalence of a pathogen when all the samples taken for testing return negative results.
This raises an issue concerning the adequacy of sampling schemes and microbial analysis in commercial food manufacture.
In September 2015 the US Centers for Disease Control and Prevention reported on a multistate outbreak of listeriosis allegedly caused by Mediterranean-type soft cheeses. Some 30 people were affected, twenty-eight people were hospitalized and three deaths were reported. However, listeria were not isolated from the cheeses produced by the manufacturer concerned.
Further information on the mathematics of microbial sampling
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In this article we will explore how to use mix composition to control the hardness or "scoopability" of ice cream or gelato. The serving temperature which influences the concentration of ice present will also be considered. The volume of air added during freezing (overrun), the manufacturing process and the concentration and type of emulsifier can also affect hardness.
However, these effects are generally less significant than the concentration of sweeteners used and serving temperature. This article should be read in conjunction with the article on the sweetness of ice cream.
This article originally had the title "Goldilock's ice cream. Controlling hardness or scoopability." Goldilocks was a character from "Goldilocks and the Three Bears" a British 19th-century fairy tale and I originally thought that everyone would understand if an ice cream was acceptable to Goldilocks it had to be good! I have changed the title to reflect that many readers have not read this fairy tale and I may have been inadvertenly confusing people.
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This article discusses the origins and role of starters in dairy fermentations, the ecology of starter bacteria, the classification of starter bacteria, the types of starter culture used and concludes with some observations on artisanal cultures. The author has provided a broader perspective on the use of starter cultures in food fermentations in the Encyclopedia of Food Microbiology. The chapter can be downloaded from Elsevier Ltd. This article should be read in conjunction with the article discussing the major functions of starters in dairy fermentations and the relative importance and effectiveness of the antimicrobial agents produced by starters. Note the classification of many bacteria previously known as lactobacilli has changed see https://www.dairyscience.info/index.php/site-news/430-nomenclature-lab.html.
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This article discusses the major functions of starters in dairy fermentations. Recent research on the relative importance of the antimicrobial agents produced by starters is included. The importance of undissociated lactic acid (HLac) is discussed with regard to the inhibition of the growth of Listeria monocytogenes, Escherichia coli and Staphylococcus aureus.
The author recommends that regulators should require manufacturers of raw milk cheeses to meet a minimum value for HLac that must be achieved prior to product release for retail sale.
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Introduction
This article provides access to a calculator and an introduction to the mathematics derived by Dr Tomas Skoglund that enables the z-value, a term used in microbial thermal death time calculations, to be corrected to comply with Arrhenius calculations. This value can be defined in several ways, including that z is the number of degrees that the temperature must be increased to achieve a tenfold (i.e.,1 log10) reduction in the decimal reduction value (D-value). The D-value is the time required to reduce the number of organisms by 1 log cycle and is an indication of the heat resistance of an organism.
Bigelow and the Arrhenius models
There are two main approaches to calculating the bactericidal effectiveness of a heat process namely the Bigelow and Arrhenius methods. Both methods require the use of constants to allow for the temperature dependence of the kinetics of thermal destruction. The Bigelow method uses z-value (SI unit K or °C) and the Arrhenius model uses activation energy (Ea, SI unit J/ mol).
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Dr Saumya Bhaduri received his Master of Science in Biochemistry and PhD in Biochemistry from the University of Calcutta, India. He immigrated to the United States as an NIH Fellow at the University of Nebraska in Lincoln, NE. Dr. Bhaduri worked as a faculty member for 6 years at the Institute of Molecular Virology in St. Louis, MO. He later served as a faculty member at Washington University Medical School in St. Louis, MO. After 5 years in the Pathology Department, Dr. Bhaduri joined the USDA/ARS as a Senior Scientist in the Eastern Regional Research Centre (ERRC) in Philadelphia, PA.
During his time at the USDA/ARS, Dr. Bhaduri created and established the first molecular biology laboratory at ERRC. He received a year-long sabbatical fellowship in order to further his exploration of DNA sequencing of food borne pathogens at the University of Reading, England. Over the course of his extensive experience at various institutions, Dr. Bhaduri’s major research areas focused on initiation of protein synthesis and genetic code, molecular virology, mapping of the histidine operon, and detection and isolation of foodborne pathogens.
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The editorial group of Wiley is offering Assistant Editor positions based in their Beijing or Shanghai offices in China for their internationally-renowned food science and nutrition journals, including Molecular Nutrition and Food Research. As part of an international team of editors, the focus of this role is on evaluating manuscripts, handling peer review and making decisions on which manuscripts to accept for publication. Link removed.
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It is important that students understand accuracy, precision and error before embarking on research projects and reflect this understanding in reports and dissertations.
There is a free tutorial by Cecil McIntosh on Sophia that explains these concepts and also provide self assessed questions to test understanding.