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کاربرد طیف‌سنجی FT-IR با مدل‌های طبقه‌بندی و رگرسیون مختلف برای تشخیص و کمی‌سازی هیدروسولفیت سدیم در آرد گندم ایران

نوع مقاله : مقاله پژوهشی لاتین

نویسندگان

1 گروه مهندسی بیوسیستم، دانشکده کشاورزی، دانشگاه تبریز، تبریز، ایران

2 گروه مهندسی مکانیک، دانشکده فنی و مهندسی، دانشگاه بناب، بناب، ایران

3 گروه مهندسی بیوسیستم، دانشکده کشاورزی، دانشگاه مراغه، مراغه، ایران

چکیده

آرد گندم یکی از مهم‌ترین و استراتژیک‌ترین منابع غذایی به‌ویژه در کشورهای در حال توسعه است. افزودن هیدروسولفیت سدیم به آرد برای بهبود برخی ویژگی‌های ظاهری می‌تواند اثرات خطرناکی بر سلامت مصرف‌کننده داشته باشد. بنابراین تشخیص این ماده مضر از اهمیت عملی بالایی برخوردار است. در مطالعه حاضر، پتانسیل طیف‌سنجی مادون قرمز تبدیل فوریه (FT-MIR) در 400-4000  cm-1 برای تشخیص سریع پودر هیدروسولفیت سدیم در آرد گندم مورد بررسی قرار گرفت. پس از گرفتن داده‌های طیفی از نمونه‌ها، ابتدا از برخی روش‌های پیش‌پردازش برای تصحیح اثرات مضر و ناخواسته بر داده‌های طیفی استفاده شد و سپس از آنالیز مؤلفه‌های اصلی (PCA) به‌عنوان مدل بدون نظارت و از مدل‌های ماشین‌بردار بدون نظارت و پشتیبانی (SVM) و شبکه عصبی مصنوعی (ANN) به‌عنوان مدل‌های بانظارت استفاده شد. همچنین از مدل رگرسیون حداقل مربعات جزئی (PLSR) به‌عنوان مدل رگرسیونی برای تشخیص و تعیین کمیت تقلب در نمونه‌های آرد خالص استفاده شد. بهترین نتایج به‌ترتیب بادقت 86.66 و 86.70 برای مدل‌های SVM و ANN با پیش‌پردازش S-G + D2 + SNV و R2p = 0.99 برای مدل PLSR بود.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Application of FT-IR Spectroscopy with Various Classification and Regression Models for Detection and Quantification of Sodium Hydrosulfite in Iranian Wheat Flour

نویسندگان [English]

  • Amir Kazemi 1
  • Asghar Mahmoudi 1
  • Mostafa Khojastehnazhand 2
  • Seyyed Hassan Fattahi 3

1 Department of Biosystems Engineering, University of Tabriz, Tabriz, Iran

2 Department of Mechanical Engineering, University of Bonab, Bonab, Iran

3 Department of Biosystems Engineering, University of Maragheh, Maragheh, Iran

چکیده [English]

Wheat flour is one of the most important and strategic food resources especially in developing countries. The addition of Sodium hydrosulfite to flour for improving some appearance features can have dangerous impacts on the consumer health. Therefore, detection of this harmful substance is great practical significance. In the present study, the potential of Fourier transform-mid infrared (FT-MIR) spectroscopy in 400-4000 cm-1 for the fast detection of Sodium hydrosulfite powder in wheat flour was investigated. After getting the spectral data from samples, firstly some preprocessing methods were used to correct harmful and unwanted effects on spectral data, and then Principal Component Analysis (PCA) as unsupervised and Support Vector Machine (SVM) and Artificial Neural Network (ANN) models as supervised classification models and Partial Least Square Regression (PLSR) as regression model were applied to detect and quantify the adulteration in pure flour samples. The best outcomes were the accuracy of 86.66 and 86.70 for SVM and ANN models with S-G + D2 + SNV preprocessing, respectively and R2p = 0.99 For PLSR model.

کلیدواژه‌ها [English]

  • Adulteration
  • Chemometrics
  • Sodium hydrosulfite
  • Spectroscopy
  • Wheat flour

©2024 The author(s). This is an open access article distributed under Creative Commons Attribution 4.0 International License (CC BY 4.0).
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مجله پژوهشهای علوم و صنایع غذایی ایران
دوره 20، شماره 3 - شماره پیاپی 87
مرداد و شهریور 1403
صفحه 17-31
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  • تاریخ دریافت: 10 بهمن 1402
  • تاریخ بازنگری: 18 فروردین 1403
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