با همکاری انجمن مهندسان مکانیک ایران

نوع مقاله : مقاله پژوهشی لاتین

نویسندگان

1 گروه مهندسی بیوسیستم، دانشکده کشاورزی، دانشگاه فردوسی مشهد، مشهد، ایران

2 مرکز هوش مصنوعی و یادگیری ماشین، دانشگاه ادیت کوان، استرالیا

3 گروه شیمی، دانشکده علوم، دانشگاه فردوسی مشهد، مشهد، ایران

10.22067/jam.2023.83040.1173

چکیده

در تحقیق حاضر با استفاده از دو روش الکتروشیمیایی ولتامتریک چرخه‌ای و زبان الکترونیک، میزان تقلب در آبلیمو مورد بررسی قرار گرفت. میزان اسید سیتریک در آبلیمو به‌عنوان یک معیار مورد پذیرش در آزمایشگاه‌ها به‌منظور بررسی تقلب در آبلیمو مورد استفاده قرار می‌گیرد، ابتدا با استفاده از دستگاه پتانسیو استات و روش چرخه‌ای ولتامتری، میزان غلظت آن بررسی شد. از الکترودهای گلسی‌کربن، گرافیت، طلا، گلسی‌کربن اصلاح‌شده توسط ذرات نانو لوله‌ی کربن و نانو ذرات طلا، استفاده شد. نوع بافر و میزان pH تغییر داده شد. نتایج نشان داد که رفتار الکتروشیمیایی اسید سیتریک بسیار پایین می‌باشد و با این روش، نمی‌توان رفتار آن را بررسی کرد. در بخش دوم، سیستم زبان الکترونیکی قابل‌حمل (e-tongue) ارزیابی شد. هشت نمونه سطوح تقلب در آبلیمو (0، 5، 10، 20، 40، 70، 95 و 100 درصد ناخالصی) ایجاد گردید. مدل‌های بدون نظارت شامل تحلیل مؤلفه اصلی (PCA) و خوشه‌بندی سلسله‌مراتبی (HCA) و مدل‌های نظارت‌شده شامل شبکه‌های عصبی پرسپترون چندلایه (MLP) و ماشین بردار پشتیبانی (SVM) استفاده شد. بر اساس نتایج، اثر انگشت PCA تمایز خوبی بین سطوح تقلب نشان داد. این موضوع توسط HCA نیز تایید گردید. نتایج روش‌های نظارت شده نشان داد که عملکرد مدل MLP برای پیش‌بینی سطوح تقلب بهتر از مدل SVM با میزان موفقیت 99.33 درصد و ضرایب همبستگی بالا R2=0.9973 و RMSE=0.09 بود. نتایج نشان می‌دهد که این سیستم می‌تواند به‌عنوان یک سیستم کنترل کیفیت طعم مورد استفاده قرار گیرد.

کلیدواژه‌ها

موضوعات

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