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1.
Applied Food Biotechnology. 2014; 1 (1): 37-44
in English | IMEMR | ID: emr-171606

ABSTRACT

Considering the ever increasing population and industrialization of the developmental trend of human life, we are no longer able to detect the toxins produced in food products using the traditional techniques. This is due to the fact that the isolation time for food products is not cost-effective, and even in most of the cases, the precision of practical techniques like bacterial cultivation and other techniques suffers from operator errors, or the errors of the mixtures used. Hence, with the advent of nanotechnology, the design of selective and smart sensors has turned into one of the greatest industrial revelations of the quality control of food products that, in few minutes time and with a very high precision, can identify the volume and toxicity of the bacteria. In this research, based on the bacterial antibody's connection to nanoparticles, a sensor was used. In this part of the research, as the basis for absorption for the recognition of bacterial toxin, medium sized silica nanoparticles of 10 nm in the form of solid powder were utilized with Notrino brand. Then the suspension produced from the agent-linked nanosilica, which was connected to the bacterial antibody, was positioned near the samples of distilled water, which were contaminated withStaphylococcus aureus bacterial toxin with the density of 10[-3] molar, so that in case any toxin exists in the sample, a connection between the toxin antigen and the antibody would be formed. Finally, the light absorption related to the connection of antigen to the particle-attached antibody was measured using spectrophotometry. The 23S rRNA gene that is conserved in allStaphylococcus spp. was used as the control. The accuracy of the test was monitored by using the serial dilution [l0[-6]] of overnight cell culture of Staphylococcus spp. bacteria [OD[600]: 0.02 = 107 cell]. It showed that the sensitivity of PCR is 10 bacteria per ml of cells within few hours. The results indicated that the sensor detects up to 10-[4] molar density. Additionally, the sensitivity of the sensor was examined after 60 days; by the 56 day, it had confirmatory results, which started to decrease after this time. Comparison of practical nanobiosensory method with the conventional methods including culture and bio-technology methods [such as polymerase chain reaction] confirmed its accuracy, sensitiveness and uniqueness. It also reduces the time from hours to 30 minutes


Subject(s)
Exotoxins , Silicon Dioxide , Nanoparticles , Genotyping Techniques , Multiplex Polymerase Chain Reaction
2.
Scientific and Research Journal of Army University of Medical Sciences-JAUMS. 2013; 11 (1): 32-38
in Persian | IMEMR | ID: emr-127136

ABSTRACT

We are no longer able to detect the toxins produced in food products using the traditional techniques. This is due to the fact that the isolation time for food products is not cost-effective and even in most of the cases. Hence with the advent of nanotechnology, the design of selective and smart sensors is one of the greatest industrial revelations of the quality control of food products. This was an laboratory experimental study. In this technique, based on the bacterial antibody connection to nanoparticle, a sensor was used. In this part of the research, as the basis for absorption for the recognition of bacterial toxin, medium sized silica nanoparticles of 10 nano meter in form of solid powder were utilized with Notrino brand. Then the suspension produced from agent-linked nanosilica which was connected to bacterial antibody was positioned near the samples of distrilled water, that were contaminated with Staphylococcus aureus bacterial toxin with the density of 10-3, so that in case any toxin exists in the sample, a connection between toxin antigen and antibody would be formed. Finally, the light absorption related to the connection of antigen to the particle attached antoibody was measured using spectrophotometry. The results indicate that the sensor, up to 10-4 of density is detectable. Additionally, the sensitivity of the sensors were examined after 60 days, the sensor by the 56 day had confirmatory results and started to decrease after those time periods. Nano-particles have unique property in bioanalysis. They have high speed and high sensitivity along with cost effectiveness


Subject(s)
Exotoxins , Biosensing Techniques , Nanotechnology , Silicon Dioxide
3.
Iranian Journal of Nutrition Sciences and Food Technology. 2012; 7 (1): 23-30
in Persian | IMEMR | ID: emr-116703

ABSTRACT

Developing minced-based products is a good opportunity for production of value-added products. Fish burgers are an example of an acceptable value-added fast food. In the present study, fish burgers were produced from deep flounder fish with no coating and their chemical, microbial, and sensory characteristics during storage at ?18°C for 5 months were determined periodically after thawing at 4°C. Fish burgers were produced and packaged in PVC/PE polymer bags. Microbial load [including total plate count, total coliform count, Escherichia coli, Staphylococcus aureus, and psychrotrophic bacteria], chemical characteristics [moisture, pH, total volatile base nitrogen [TVB-N], and TBA], and sensory characteristicswere were determined monthly. Data were analyzed using the SPSS for Windows program. The TVB-N and TBA values increased significantly by the end of the first and second month, respectively. After that no further statistically significalt changes occured in the former, while the latter decreased until the end of storage period, presumably due to reaction of the MDA produced with protein breakdown products and formation of new peoducts. The data also showed that pH increased significantly by the end of the first month; no changes were observed afterwards. All of the microbial counts and sensory parameters had decreased significantly [p<0.05] at the end of storage period. The best expiry time for lizardfish burgers [if stored at 18°C] is 3 months after production, and sensory evaluation is the most reliable way for predicting their shelf life

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