Development of FTIR-ATR spectra and PLS regression combination model for discrimination of pure and adulterated acacia honey

IF 5.6 1区农林科学 Q1 FOOD SCIENCE & TECHNOLOGY

Food Control Pub Date : 2024-11-04 DOI:10.1016/j.foodcont.2024.110996

Rafieh Fakhlaei , Arman Amani Babadi , Naziruddin Mat Ariffin , Zou Xiaobo

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引用次数: 0

Abstract

A Fourier Transform Infrared Spectroscopy and attenuated total reflectance (FTIR-ATR)-based chemometric model was evaluated for the rapid identification and estimation of adulterants in honey. Two types of honey, bee honey and stingless bee honey, were adulterated with acid adulterants (acetic acid, citric acid, and tamarind extract) at different concentrations of 1%, 3%, 5%, and 7% and sugar adulterants (liquid corn syrup, cane sugar, palm sugar, and inverted sugar) at different concentrations of 1%, 2%, and 3%. The physicochemical properties (Brix, moisture content, pH, and free acidity) and sugar contents (glucose, fructose, and sucrose) of each type of honey and their adulterated samples were determined before FTIR analysis. For all the samples, FTIR spectra were acquired in the mid-infrared range (400-3600 cm⁻¹) and the spectra obtained were subjected to partial least squares (PLS) analysis to develop the model for the determination of adulterants in honey samples. The PLS model produced high coefficient of determination (R²) for bee honey adulterated with acetic acid (0.95), citric acid (0.98), tamarind extract (0.97), and stingless bee honey adulterated with liquid corn syrup (0.99), inverted sugar (0.91), cane sugar (0.86), and palm sugar (0.77). A recognition model was developed for mixture detection and verified through the physicochemical analysis. The combination of FTIR-ATR spectra and the PLS regression model can be a fast, reliable, nondestructive method to detect honey adulteration.

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建立傅立叶变换红外-ATR光谱和 PLS 回归组合模型，用于鉴别纯正洋槐蜜和掺假洋槐蜜

对基于傅立叶变换红外光谱和衰减全反射（FTIR-ATR）的化学计量模型进行了评估，以快速识别和估计蜂蜜中的掺假物质。在两种蜂蜜（蜜蜂蜂蜜和无刺蜜蜂蜂蜜）中掺入了不同浓度（1%、3%、5%和 7%）的酸掺合物（醋酸、柠檬酸和罗望子提取物）和不同浓度（1%、2%和 3%）的糖掺合物（液体玉米糖浆、蔗糖、棕榈糖和反式糖）。在进行傅立叶变换红外分析之前，先测定了每种蜂蜜及其掺假样品的理化性质（白利糖度、水分含量、pH 值和游离酸度）和糖含量（葡萄糖、果糖和蔗糖）。所有样品的傅立叶变换红外光谱均在中红外波段（400-3600 cm-1）采集，并对采集到的光谱进行偏最小二乘法（PLS）分析，以建立蜂蜜样品中掺假物质的测定模型。该偏最小二乘法模型对掺入醋酸（0.95）、柠檬酸（0.98）、罗望子提取物（0.97）的蜜蜂蜂蜜，以及掺入液态玉米糖浆（0.99）、倒置糖（0.91）、蔗糖（0.86）和棕榈糖（0.77）的无刺蜜蜂蜂蜜产生了较高的判定系数（R2）。建立了混合物检测识别模型，并通过理化分析进行了验证。傅立叶变换红外-ATR光谱与PLS回归模型的结合是一种快速、可靠、无损的蜂蜜掺假检测方法。

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来源期刊

Food Control 工程技术-食品科技

CiteScore

12.20

自引率

6.70%

发文量

758

审稿时长

33 days

期刊介绍： Food Control is an international journal that provides essential information for those involved in food safety and process control. Food Control covers the below areas that relate to food process control or to food safety of human foods: • Microbial food safety and antimicrobial systems • Mycotoxins • Hazard analysis, HACCP and food safety objectives • Risk assessment, including microbial and chemical hazards • Quality assurance • Good manufacturing practices • Food process systems design and control • Food Packaging technology and materials in contact with foods • Rapid methods of analysis and detection, including sensor technology • Codes of practice, legislation and international harmonization • Consumer issues • Education, training and research needs. The scope of Food Control is comprehensive and includes original research papers, authoritative reviews, short communications, comment articles that report on new developments in food control, and position papers.