Rapid and non-destructive detection of cassava flour adulterants in wheat flour using a handheld MicroNIR spectrometer

被引:20
|
作者
Tao, Feifei [1 ]
Liu, Li [1 ]
Kucha, Christopher [1 ]
Ngadi, Michael [1 ]
机构
[1] McGill Univ, Dept Bioresource Engn, 21,111 Lakeshore Rd, Ste Anne De Bellevue, PQ H9X 3V9, Canada
关键词
Food adulteration; Handheld spectrometer; Near-infrared spectroscopy; Partial least squares discriminant analysis; Principal component analysis-linear discriminant analysis; FOOD; INSPECTION; POWDER; NIR;
D O I
10.1016/j.biosystemseng.2020.12.010
中图分类号
S2 [农业工程];
学科分类号
0828 ;
摘要
The low-cost, ultra-compact and handheld microNIR spectrometer over the spectral range of 1150-2150 nm was explored to detect the adulteration of wheat flour in this study. Eight varieties of cassava flour were used as adulterants and were adulterated in wheat flour at five adulteration levels of 5, 10, 20, 30 and 40%. Both principal component analysis-linear discriminant analysis (PCA-LDA) and partial least squares discriminant analysis (PLS-DA) methods were employed to establish 2-class, 3-class and 6-class discriminant models, using different types of preprocessed absorbance spectra. The overall prediction accuracies of the 2-class discriminant models all achieved over 95.00% in separating the pure and adulterated wheat flour, with the best overall accuracy of 97.53%, regardless of the adulterated cassava flour variety. The best overall prediction accuracy of 93.83% was obtained in discriminating the flour samples into the three classes of 0% (pure wheat), 5% thorn 10% and 20% thorn 30% thorn 40%, regardless of the adulterated cassava flour variety. However, the highest overall accuracy of the 6-class model attained only 75.31% in classifying the wheat samples into the six groups of 0% (pure wheat), 5, 10, 20, 30 and 40%, regardless of the adulterated cassava flour variety. Overall, the obtained results demonstrated the usefulness of the employed low-cost spectrometer in detecting the wheat flour adulteration in a rapid and non-destructive manner. (c) 2020 IAgrE. Published by Elsevier Ltd. All rights reserved.
引用
收藏
页码:34 / 43
页数:10
相关论文
共 50 条
  • [41] Rapid and non-destructive detection of organic carrot powder adulteration using spectroscopic techniques
    Arslan, Aysel
    Keskin, Muharrem
    Soysal, Yurtsever
    JOURNAL OF FOOD COMPOSITION AND ANALYSIS, 2023, 123
  • [42] Proximate Composition and Rheological Properties of a Cake Mix Elaborated Using Composite Flour Wheat: Cassava
    Cueto Bautista, Davdmary E.
    Perez, Elevina E.
    INTERNATIONAL JOURNAL OF FOOD ENGINEERING, 2010, 6 (03)
  • [43] Non-destructive prediction of protein content in wheat using NIRS
    Ye, Dandan
    Sun, Laijun
    Zou, Borui
    Zhang, Qian
    Tan, Wenyi
    Che, Wenkai
    SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY, 2018, 189 : 463 - 472
  • [44] Non-destructive, solvent-free quantification of wood preservatives in wood flour and wooden objects using GC-DTIMS
    Ude, Fabian
    Schumann, Achim
    Telgheder, Ursula
    TALANTA, 2024, 268
  • [45] Hyperspectral imaging combined with chemometrics for rapid detection of talcum powder adulterated in wheat flour
    He, Hong-Ju
    Chen, Yan
    Li, Guanglei
    Wang, Yuling
    Ou, Xingqi
    Guo, Jingli
    FOOD CONTROL, 2023, 144
  • [46] Predicting wheat flour quality for making Japanese sponge cake using flour pasting properties as measured by the Rapid Visco Analyzer
    Mense, Andrew L.
    Ross, Andrew S.
    Bock, Jayne E.
    CEREAL CHEMISTRY, 2024, 101 (05) : 954 - 967
  • [47] Rapid visible-near infrared (Vis-NIR) spectroscopic detection and quantification of unripe banana flour adulteration with wheat flour
    Ndlovu, Phindile Faith
    Magwaza, Lembe Samukelo
    Tesfay, Samson Zeray
    Mphahlele, Rebogile Ramaesele
    JOURNAL OF FOOD SCIENCE AND TECHNOLOGY-MYSORE, 2019, 56 (12): : 5484 - 5491
  • [48] DETECTION OF STEROIDS ON CHROMATOPLATES USING A NON-DESTRUCTIVE METHOD
    BOYD, GS
    HUTTON, HRB
    BIOCHIMICA ET BIOPHYSICA ACTA, 1963, 69 (02) : 419 - &
  • [49] Non-destructive Crack detection using GMI sensor
    Goktepe, M
    Ege, Y
    Bayri, N
    Atalay, S
    SECOND SEEHEIM CONFERENCE ON MAGNETISM, PROCEEDINGS, 2004, : 3436 - 3439
  • [50] Study on Rapid Non-Destructive Detection of the Freshness of Paddy Based on NIRS
    Li Juan
    Li Zhong-hai
    Fu Xiang-jin
    SPECTROSCOPY AND SPECTRAL ANALYSIS, 2012, 32 (08) : 2126 - 2130