scholarly journals A Review of Recent Studies Employing Hyperspectral Imaging for the Determination of Food Adulteration

Photochem ◽  
2021 ◽  
Vol 1 (2) ◽  
pp. 125-146
Author(s):  
Havva Tümay Temiz ◽  
Berdan Ulaş
Keyword(s):  
Hyperspectral Imaging ◽  
Meat Products ◽  
Selection Methods ◽  
Future Perspectives ◽  
Wavelength Selection ◽  
Food Adulteration ◽  
Cereal Products ◽  
Alternative Approaches ◽  
Fish And Fishery Products

Applications of hyperspectral imaging (HSI) methods in food adulteration detection have been surveyed in this study. Subsequent to the research on existing literature, studies were evaluated based on different food categories. Tea, coffee, and cocoa; nuts and seeds; herbs and spices; honey and oil; milk and milk products; meat and meat products; cereal and cereal products; and fish and fishery products are the eight different categories investigated within the context of the present study. A summary of studies on these topics was made, and articles reported in 2019 and 2020 were explained in detail. Research objectives, data acquisition systems, and algorithms for data analysis have been introduced briefly with a particular focus on feature wavelength selection methods. In light of the information extracted from the related literature, methods and alternative approaches to increasing the success of HSI based methods are presented. Furthermore, challenges and future perspectives are discussed.

scholarly journals Sensitive Wavelengths Selection in Identification of Ophiopogon japonicus Based on Near-Infrared Hyperspectral Imaging Technology

2017 ◽  
Vol 2017 ◽  
pp. 1-11 ◽  
Author(s):  
Zhengyan Xia ◽  
Chu Zhang ◽  
Haiyong Weng ◽  
Pengcheng Nie ◽  
Yong He
Keyword(s):  
Least Squares ◽  
Partial Least Squares ◽  
Hyperspectral Imaging ◽  
Near Infrared ◽  
Support Vector ◽  
Calibration Model ◽  
Least Squares Regression ◽  
Selection Methods ◽  
Wavelength Selection ◽  
Ophiopogon Japonicus

Hyperspectral imaging (HSI) technology has increasingly been applied as an analytical tool in fields of agricultural, food, and Traditional Chinese Medicine over the past few years. The HSI spectrum of a sample is typically achieved by a spectroradiometer at hundreds of wavelengths. In recent years, considerable effort has been made towards identifying wavelengths (variables) that contribute useful information. Wavelengths selection is a critical step in data analysis for Raman, NIRS, or HSI spectroscopy. In this study, the performances of 10 different wavelength selection methods for the discrimination of Ophiopogon japonicus of different origin were compared. The wavelength selection algorithms tested include successive projections algorithm (SPA), loading weights (LW), regression coefficients (RC), uninformative variable elimination (UVE), UVE-SPA, competitive adaptive reweighted sampling (CARS), interval partial least squares regression (iPLS), backward iPLS (BiPLS), forward iPLS (FiPLS), and genetic algorithms (GA-PLS). One linear technique (partial least squares-discriminant analysis) was established for the evaluation of identification. And a nonlinear calibration model, support vector machine (SVM), was also provided for comparison. The results indicate that wavelengths selection methods are tools to identify more concise and effective spectral data and play important roles in the multivariate analysis, which can be used for subsequent modeling analysis.

Determination of Cholesterol Using a Novel Magnetohydrodynamic Acoustic-Resonance Near-IR (MARNIR) Spectrometer

1993 ◽  
Vol 47 (7) ◽  
pp. 887-890 ◽  
Author(s):  
Robert G. Buice ◽  
Robert A. Lodder
Keyword(s):  
Prediction Error ◽  
Principal Component Regression ◽  
Principal Component ◽  
Acoustic Resonance ◽  
Selection Methods ◽  
Wavelength Selection ◽  
Spectral Techniques ◽  
Near Ir ◽  
Physical Environments

Near-IR spectrometric determination of minor constituents of biological systems is complicated by the fact that near-IR spectra of these materials vary in different chemical and physical environments. In such cases, wavelength selection methods and full-spectral techniques such as partial least-squares and principal component regression (which weight each wavelength in calibration) produce excess error because they must attempt to model both variations in major constituents and variations in the analyte. A magnetohydrodynamic acoustic-resonance near-IR (MARNIR) spectrometer can determine major constituents of biological materials noninvasively and nondestructively, leaving the near-IR spectrum of the analyte to be used quantitatively with less prediction error.

Enzyme Immunoassay for Determination of Gluten in Foods: Collaborative Study

1991 ◽  
Vol 74 (2) ◽  
pp. 257-264 ◽  
Author(s):  
John H Skerritt ◽  
Amanda S Hill
Keyword(s):  
Enzyme Immunoassay ◽  
Collaborative Study ◽  
Wheat Gluten ◽  
Meat Products ◽  
Processed Meat ◽  
Cereal Products ◽  
Relative Standard ◽  
Cooked Meats ◽  
Wheat Flours

Abstract A collaborative study was performed In 15 laboratories to validate a monoclonal antibody-based enzyme Immunoassay (EIA) for determination of gluten in foods. The study Included 13 samples: maize starch, "gluten-free" baking mixes, wheat flours, cookies, cooked meats, and a soup. Gluten was present In these samples at either zero or 0.02 to 10% by weight, I.e., over almost 3 orders of magnitude. The mean assay values for the foods varied from 88 to 105% of the actual amounts. The assay was quantitative for cereal products and the soup with repeatability (RSDr, relative standard deviation) and reproducibility (RSDR) of 16-22% and 24-33%, respectively. The assay was semiquantitative for the processed meat products (RSDr 14 and 26% and RSDr 46 and 56%), probably because gluten was unevenly distributed In the small (1 g) samples that were analyzed. The ELISA method produced no false positive results, and false negatives obtained with tannin-containing foods could be avoided by use of a modified sample extractant. None of the collaborators reported problems In following the protocol. The method has been adopted official first action by AOAC for determination of wheat gluten in foods.

scholarly journals Enzymatic Determination of Lactose and Galactose in Foods: NMKL Collaborative Methods Performance Study

1997 ◽  
Vol 80 (3) ◽  
pp. 584-590 ◽  
Author(s):  
Antti Mustranta ◽  
Carola Östman ◽  
I Aminoff ◽  
P Baardseth ◽  
E Eklund ◽  
...  
Keyword(s):  
Milk Powder ◽  
Meat Products ◽  
Enzymatic Oxidation ◽  
Performance Study ◽  
Cereal Products ◽  
Enzymatic Determination ◽  
Relative Standard ◽  
Analytical Tools ◽  
Hydrolysis Of

Abstract Enzymes are widely used in food chemistry as analytical tools. An enzymatic method for determining lactose and galactose in foods was evaluated in an interlaboratory methods performance study by 12 laboratories in 4 countries. The method is based on enzymatic hydrolysis of lactose and enzymatic oxidation of the hydrolysis products. The exchange of the coenzyme in the second reaction is the basis of quantitation. The method may be used for various types of foods, such as liquid and solid milk products, meat products, cereal products, fats, dressings, sweets, chocolate, and foods for special dietary uses. It is also applicable to lactose-free foods but not to products in which lactose has been partially hydrolyzed enzymatically to glucose and galactose. Six commonly used foodstuffs with lactose concentrations ranging from 0.4 g/100 g to 40 g/100 g and galactose concentrations up to 0.7 g/100 g were analyzed: crisp rye bread, milk chocolate, sausage, cheese, margarine, and baby food containing milk powder. They were distributed to the 12 participants as 12 randomly numbered test samples, representing blind duplicates of the 6 materials. The relative standard deviations for reproducibility (RSDR) were between 2.3-11% for lactose and 6.8-50% for galactose.

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