| Title |
Advantages and limitations of potential methods for the analysis of bacteria in milk: a review
|
|---|---|
| Published in |
Journal of Food Science and Technology, August 2015
|
| DOI | 10.1007/s13197-015-1993-y |
| Pubmed ID | |
| Authors |
Frederick Tawi Tabit |
| Abstract |
Contamination concerns in the dairy industry are motivated by outbreaks of disease in humans and the inability of thermal processes to eliminate bacteria completely in processed products. HACCP principles are an important tool used in the food industry to identify and control potential food safety hazards in order to meet customer demands and regulatory requirements. Milk testing is of importance to the milk industry regarding quality assurance and monitoring of processed products by researchers, manufacturers and regulatory agencies. Due to the availability of numerous methods used for analysing the microbial quality of milk in literature and differences in priorities of stakeholders, it is sometimes confusing to choose an appropriate method for a particular analysis. The objective of this paper is to review the advantages and disadvantages of selected techniques that can be used in the analysis of bacteria in milk. SSC, HRMA, REP, and RAPD are the top four techniques which are quick and cost-effective and possess adequate discriminatory power for the detection and profiling of bacteria. The following conclusions were arrived at during this review: HRMA, REP and RFLP are the techniques with the most reproducible results, and the techniques with the most discriminatory power are AFLP, PFGE and Raman Spectroscopy. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Saudi Arabia | 1 | 50% |
| Poland | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 50% |
| Scientists | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 184 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 184 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 33 | 18% |
| Student > Master | 27 | 15% |
| Researcher | 19 | 10% |
| Student > Ph. D. Student | 18 | 10% |
| Student > Doctoral Student | 7 | 4% |
| Other | 21 | 11% |
| Unknown | 59 | 32% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 34 | 18% |
| Biochemistry, Genetics and Molecular Biology | 30 | 16% |
| Immunology and Microbiology | 18 | 10% |
| Medicine and Dentistry | 7 | 4% |
| Chemistry | 7 | 4% |
| Other | 22 | 12% |
| Unknown | 66 | 36% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 16 January 2022.
All research outputs
#13,989,437
of 22,888,307 outputs
Outputs from Journal of Food Science and Technology
#543
of 1,446 outputs
Outputs of similar age
#132,867
of 266,258 outputs
Outputs of similar age from Journal of Food Science and Technology
#29
of 52 outputs
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