تخمین و مقایسه انحراف معیار تجدیدپذیری استاندارد SIR(عدم قطعیت) در آزمون های کمی میکروبی آیتم های مواد غذایی مختلف بر اساس استاندارد ایزو 19036 سال 2019

نویسندگان
1 گروه بهداشت مواد غذایی و آبزیان ،دانشکده دامپزشکی، دانشگاه فردوسی مشهد، مشهد، ایران
2 گروه بهداشت مواد غذایی و آبزیان ، دانشکدهدامپزشکی، دانشگاه فردوسی مشهد، مشهد، ایران
3 گروه تغذیه، دانشکده پزشکی، دانشگاه علوم پزشکی مشهد، مشهد، ایران
چکیده
این مطالعه با هدف تخمین و مقایسه، انحراف معیار تجدید پذیری درون آزمایشگاهی(SIR) یا عدم قطعیت اندازه گیری (MU) بعنوان شاخص عملکردی در تصدیق انجام روش های آزمون کمی میکروب شناسی مواد غذایی، انجام شده است. آزمون های شمارش کلی میکروارگانیسم های هوازی مزوفیلACC و شمارش آنتر وباکتریاسهECC، بعنوان دو آزمون مهم در ارزیابی میکروبی مواد غذایی، انتخاب و محاسبات انحراف معیار تجدیدپذیری استاندارد درون آزمایشگاهی (عدم قطعیت) در آیتم های غذایی منتخب: گوشت چرخ کرده، همبرگر، پودر سویا، تخم مرغ مایع پاستوریزه، شیر پاستوریزه و فرادما، بستنی، آبمیوه، آرد، کیک و ادویه بر اساس استاندارد ایزو -19036 سال 2019 انجام گردید. سایر مولفه های عدم قطعیت ماتریکس، توزیعی، مرکب وگسترده محاسبه و گزارش شدند. محاسبه عدم قطعیت فنی آزمون ECC در (شیرپاستوریزه و فرادما، بستنی، آب میوه و تخم مرغ مایع پاستوریزه) با ایجاد آلودگی مصنوعی در سه سطح توسط ارگانیسم هدف (Shigella felxseneri ) و در سایر آیتم های غذایی آلودگی طبیعی بود، در آزمونACC صرفا آلودگی طبیعی محاسبه و نتایج، مورد مقایسه قرار گرفت. نتایج عدم قطعیت فنی آزمون ECC، از 0.487 تا 0.07 و در آزمون ACC، از 390/0 تا 105/0 log10 cfu/g متغیر بود. بیشترین مقادیر عدم قطعیت فنی و ماتریکس در نمونه های گوشت، کیک، همبرگر و پنیر یعنی در مواد غذایی ناهمگن (جامد و نیمه جامد) و کمترین مقادیر در نمونه های مایع (همگن) مشاهده شد. ارزیابی تغییرپذیری و در نتیجه عدم قطعیت راهی برای استاندارد کردن بیان تنوع مرتبط با داده‌های به‌دست‌آمده در روش‌های میکروبیولوژیکی برای برجسته کردن علل و میزان چندین عامل متنوع موثر پیشنهاد می گردد.
کلیدواژه‌ها

موضوعات


عنوان مقاله English

Estimation and comparison of interalaboratoary standarad deviation (SIR) measurement uncertainty in Quantitative microbiological tests in different food items based on EN ISO:19036-2019

نویسندگان English

Mohammad Khezri 1
saeid khanzadi 2
Mohammad Hashemi 3
1 1Department of Food Hygiene and Aquaculture, Faculty of Veterinary Medicine, Ferdowsi University of Mashhad, Mashhad, Iran
2 Department of Food Hygiene and Aquaculture, Faculty of Veterinary Medicine, Ferdowsi University of Mashhad, Mashhad, Iran.
3 2Department of Medical Biotechnology and Nanotechnology, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
چکیده English

The aim of study was estimated and compared intra-laboratory quantification deviation (SIR) or measurement uncertainty (MU) as a performance Charateristics in verification of the implementation step of quantitative test methods in food microbiology laboratories. The aerobic mesophilic colony counts of microorganisms (ACC) and Enterobacteriaceae colony count (ECC), as two important and common tests in the microbial evaluation of all type of food was selected and interlaboratoary standard deviation estimation of selected food items: minced meat, hamburger, soy powder, pasteurized liquid eggs, pasteurized and UHT milk, ice cream, Fruit juice, flour, cake and spice (PEPER) were calculated based on ISO-19036 standard method (2019). In this comparison, technical, matrix, distribution, confirmation and combined Uncertinity were calculated and reported. Calculation of the technical uncertainty of the ECC test in (pasteurized and ultra-heated milk, ice cream, fruit juice and pasteurized liquid eggs) by created the artificial contamination on three levels with the target organism (Shigella felxseneri) and in other food items it was natural contamination, in the ACC test was only natural contamination was calculated. The technical uncertainty results of the ECC test ranged from 0.487 to 0.07 and in the ACC test, from 0.390 to 0.105 log10 cfu/g. The highest values of technical and matrix uncertainty were observed in meat, cake, hamburger and cheese samples, which showed the heterogeneous foods (solid and semi-solid) and the lowest values were observed in liquid (homogeneous) samples. Evaluation of variability and followed the uncertainty is proposed as a way to standardize the expression of variability associated with data obtained in microbiological methods to highlight the causes and extent of several influencing factors.

کلیدواژه‌ها English

Aerobic mesophilic microorganisms
Enterobacteriaceae
Impementation verification
Measurement uncertainty
Performance characterisrics
reproducibility standard deviation and verification
[1] Jarvis, B. (2016). The distribution of microorganisms in foods in relation to sampling. Statistical Aspects of the Microbiological Examination of Foods, 45-69.‌
[2] Do Prado-Silva, L.; Brancini, G.T.P.; Braga, G.Ú.L.; Liao, X.; Ding, T.; Sant’Ana, A.S. (2022). Antimicrobial photodynamic treatment (aPDT) as an innovative technology to control spoilage and pathogenic microorganisms in agri-food products: An updated review. Food Control, 132: 108527.
[3] Saviano, A. M., da Silva, R. J. B., & Lourenço, F. R. (2019). Measurement uncertainty for the potency estimation by rapid microbiological methods (RMMs) with correlated data. Regulatory Toxicology and Pharmacology, 102: 117-124.‌
[4] Corry, J. E., Jarvis, B., Passmore, S., & Hedges, A. (2007). A critical review of measurement uncertainty in the enumeration of food micro-organisms. Food microbiology, 24(3), 230-253
[5] Anonymous, EN ISO /IEC 17025, 2017. General requirements for the competence of testing and
calibration laboratories, is the international reference for testing and calibration laboratories wanting
to demonstrate their capacity to deliver reliable results.
[6] ISO 19036:2019: Microbiology of the food chain – Estimation of measurement uncertainty for quantitative determinations.
[7] Kornacki, J. L. and Johnson, J. L. “2001. Enterobacteriaceae, Coliforms, and Escherichia coli as Quality and Safety Indicators,” Compendium of Methods for the Microbiological Examination of Foods,4: 69-82.
[8] ICMSF (International Commission on Microbiological Specifications for Foods) (1978). Microorganisms in Foods. 1. Their significance and methods of enumeration. Toronto: University of Toronto Press.
[9] EC Regulation 2073/2005 (2005). Commission regulation (EC) no. 2073/2005 of 15 November 2005 on microbiological criteria for foodstuffs. Off J Eur :union: L338:1–25
[10] ]. REGULATION ON TURKISH FOOD CODEX , REGULATION ON TURKISH FOOD CODEX (5) MICROBIOLOGICAL CRITERIA , Law of Authorization: 5996 , Official Gazette of Publication: 29. 12. 2011 -28157 , MICROBIOLOGICAL CRITERIA, www.tarimorman.gov.tr.
[11] El-Ziney, M. G. (2018). Evaluation of microbiological quality and safety of milk and dairy products with reference to European and Gulf Standards. Food and Public Health, 8(2):47-56.
[12] M5 1400 , ZABTEH MICROBILOGICAL SPESIFICATION , M5-1400 ,2021, IRAN FDO:
https://fdlabnet2.fda.gov.ir//Help/PDF/20762_PZ.pdf
[13] ISIRI : 2395,2406,2304, 11063, 2304,2303, Iranian National Standardization Organization (INSO) No. 2592 . Website: http://www.isiri.gov.ir
[14]Anonymous, EN ISO 16140-3: (2020). Microbiology of the food chain — Method validation — Part 3, Protocol for the verification of reference methods and validated alternative methods in a single laboratory.
[15] Keykhosravy, K., Khanzadi, S., Hashemi, M., Azizzadeh, M. ( 2020). Chitosan-loaded nanoemulsion containing Zataria Multiflora Boiss and Bunium persicum Boiss essential oils as edible coatings: Its impact on microbial quality of turkey meat and fate of inoculated pathogens. International journal of biological macromolecules. 150:904-13.
[16] Anonymous (2004). ISO 21528-2. Microbiology of food and animal feeding stuffs – Horizontal methods for the detection and enumeration of Enterobacteriaceae – Part 2: Colony-count method. International Organization for Standardisation, Geneva, Switzerland.
[17] Nyamakwere, F., Muchenje, V., Mushonga, B., Makepe, M., Mutero, G. (2016). Assessment of Salmonella, Escherichia Coli, Enterobacteriaceae and Aerobic Colony Counts Contamination Levels During the Beef Slaughter Process. Journal of Food Safety. 36(4):548-56.
[18] ISO 14461-1: (2005). Milk and milk products – Quality control in microbiological laboratories – Part 1: Analyst performance assessment for colony counts
[19] https://committee.iso.org/sites/tc34sc9/home/general-standards/content-left-area/culture-media/iso-19036-estimation-of-measurem.html
[20] Anonymous, (2005). Statistical methods for use in proficiency testing by 116 interlaboratory comparison. International Sandardization Organization, vol.13528.
[21] Rohde, A., Hammerl, J. A., Appel, B., Dieckmann, R., & Al Dahouk, S. (2015). Sampling and homogenization strategies significantly influence the detection of foodborne pathogens in meat. BioMed Research International, (5):1-8
[22] Augustin, J.-C., Carlier, V. (2006). Lessons from the organisation of a proficiency testing program in food microbiology by interlaboratory comparison: analytical methods in use, impact of methods on bacterial counts and measurement uncertainty of bacterial counts, Food Microbiology, 26: 1–38.
[23] Pendrill, L. (2014) Using measurement uncertainty in decision-making and conformity assessment. Metrologia, 206–18.
[24] Arienzo, A., Losito, F., Stalio, O., & Antonini, G. (2016). Comparison of uncertainty between traditional and alternative methods for food microbiological analysis. Am J Food Technol, 11(1-2), 29-36.‌
[25] Saviano, A. M., da Silva, R. J. B., & Lourenço, F. R. (2019). Measurement uncertainty for the potency estimation by rapid microbiological methods (RMMs) with correlated data. Regulatory Toxicology and Pharmacology, 102: 117-124.‌
[26] Jarvis, B., Hedges, A. J., & Corry, J. E. (2007). Assessment of measurement uncertainty for quantitative methods of analysis: comparative assessment of the precision (uncertainty) of bacterial colony counts. International journal of food microbiology, 116(1): 44-51.‌
[27] Rezic Dereani, V., & Matek Sarić, M. (2010). Validation and measurement uncertainty estimation in food microbiology: differences between quantitative and qualitative methods, Mljekarstvo, 60 (3): 207-213
[28] Uhlig, S., & Gowik, P. (2018). Efficient estimation of interlaboratory and in-house reproducibility standard deviation in factorial validation studies. Journal of Consumer Protection and Food Safety, 13(3): 315-322