مدل‌سازی تشخیص فراصوتی آلودگی پاکت‌های شیر UHT به باکتری Escherichia coli با شبکۀ عصبی مصنوعی

محمدی, وحید; ابراهیمی, رحیم; قاسمی‌ورنامخواستی, مهدی; عباس‌والی, مریم

doi:10.22059/ijbse.2015.56862

مدل‌سازی تشخیص فراصوتی آلودگی پاکت‌های شیر UHT به باکتری Escherichia coli با شبکۀ عصبی مصنوعی

نوع مقاله : مقاله پژوهشی

نویسندگان

¹ کارشناس ارشد، دانشکدۀ کشاورزی، دانشگاه شهرکرد

² دانشیار، دانشکدۀ کشاورزی، دانشگاه شهرکرد

³ استادیار، دانشکدۀ کشاورزی، دانشگاه شهرکرد

⁴ استادیار، دانشکدۀ دامپزشکی، دانشگاه شهرکرد، شهرکرد

10.22059/ijbse.2015.56862

چکیده

تشخیص آلودگی میکروبی شیر، به‌عنوان مهم‏ترین شاخص کیفیت شیر در صنایع لبنی، به‌کمک‏ روش‏های نوین مهندسی اهمیت زیادی دارد. در تحقیق حاضر، آلودگی میکروبی پاکت‏های شیر UHT با استفاده از حسگرهای فراصوتی تشخیص داده شد. پاکت‏ها به‌صورت مصنوعی در چهار رقت متفاوت و با سه تکرار به باکتری E. coliآلوده شدند. فرکانس مرکزی سنسورهای پیزوالکتریک MHz 02/1 بود و با ولتاژ پیک V 5/18 استفاده شدند. برای پایش مشخصه‏های فراصوتی، فاکتورهای دامنۀ ولتاژ، و تأخیر زمانی اندازه‏گیری شدند. شبکۀ عصبی مصنوعی برای پیش‏بینی تعداد باکتری و pH پاکت‏های شیر براساس فاکتورهای فراصوتی طراحی شد. نتایج نشان داد که آلودگی پاکت‏های شیر در رقت اولیۀ CFU/ml 1000 پس از 5/7 ساعت تشخیص‌پذیر است به‌صورتی ‌که با کاهش رقت اولیۀ باکتری، مدت زمان تشخیص افزایش خواهد داشت. شبکۀ عصبی مصنوعی آموزش داده‌شده مقادیر تعداد باکتری و pH را نسبت به داده‏های تجربی با ضرایب تبیین 872/0 و 851/0 پیش‏بینی کرد. براساس پژوهش انجام‌شده، مشاهده می‌شود که آلودگی میکروبی شیر با استفاده از فراصوت امکان‏پذیر بوده و برای حصول دقت بالاتر، نیازمند تحقیقات بیشتری است.

کلیدواژه‌ها

20.1001.1.20084803.1394.46.3.2.0

موضوعات

صنایع غذایی

عنوان مقاله [English]

Ultrasonic Detection Modeling of the Escherichia coli microbial contamination of UHT Milk packages using Artificial Neural Network

نویسندگان [English]

Vahid Mohammadi ¹
Rahim Ebrahimi ²
Mahdi Ghasemi-Varnamkhasti ³
Maryam Abbasvali ⁴

¹ Former Graduate Student, Faculty of Agriculture, Shahrekord University, Shahrekord , Iran

² Associate Professor, Faculty of Agriculture, Shahrekord University, Shahrekord , Iran

³ Assistant Professor, Faculty of Agriculture, Shahrekord University, Shahrekord , Iran

⁴ Assistant Professor, Faculty of Veterinary Medicine, Shahrekord University, Shahrekord, Iran

چکیده [English]

Detecting microbial contamination of milk using novel engineering techniques is very worthy. In current study, microbial contamination of UHT milk packages was detected using ultrasonic sensors. Milk packages artificially were inoculated to E. coli in four dilutions and three replications. Monitoring of ultrasonic properties was performed by measuring amplitude and time delay factors. Artificial neural network designed for predicting total count and pH of milk packages based on ultrasonic properties. Results showed that contamination of milk packages for initial dilution 1000 CFU/ml after 7.5 h is capable to detect, and detection period would be increased in conjunction with initial bacterial dilution decreasing. Trained neural network predicted total count and pH values with the coefficient of determination 0.979 and 0.795 against the experimental values. According to the current project, is resulted that microbial contamination is detectable using ultrasonic technique, and to achieve high accuracies, more researches are needed.

کلیدواژه‌ها [English]

Ultrasound
Microbial contamination
milk
detection
ANN

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