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Chen T, Qi X, Si Z, Cheng Q, Chen H. An energy dispersive X-ray fluorescence spectrometry approach for the identification of geographical origin of wheat flour. INTERNATIONAL JOURNAL OF FOOD ENGINEERING 2021. [DOI: 10.1515/ijfe-2020-0265] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Abstract
In this work, a method was established for discriminating geographical origins of wheat flour based on energy dispersive X-ray fluorescence spectrometry (ED-XRF) and chemometrics. 68 wheat flour samples from three different origins were collected and analyzed using ED-XRF technology. Firstly, the principal component analysis method was applied to analyze the feasibility of discrimination and reduce data dimensionality. Then, Competitive Adaptive Reweighted Sampling (CARS) was used to further extract feature variables, and 12 energy variables (corresponding to mineral elements) were identified and selected to characterize the geographical attributes of wheat flour samples. Finally, a non-linear model was constructed using principal component analysis and quadratic discriminant analysis (QDA). The CARS-PCA-QDA model showed that the accuracy of five-fold cross-validation was 84.25%. The results showed that the established method was able to select important energy channel variables effectively and wheat flour could be classified based on geographical origins with chemometrics, which could provide a theoretical basis for unveiling the relationship between mineral element composition and wheat origin.
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Affiliation(s)
- Tong Chen
- School of Biological and Chemical Engineering, Guangxi University of Science and Technology , Liuzhou 545006 , PR China
| | - Xingpu Qi
- School of Food Science and Technology, Jiangsu Agri-animal Husbandry Vocational College , Taizhou 225300 , PR China
| | - Zaiyong Si
- School of Biological and Chemical Engineering, Guangxi University of Science and Technology , Liuzhou 545006 , PR China
| | - Qianwei Cheng
- School of Biological and Chemical Engineering, Guangxi University of Science and Technology , Liuzhou 545006 , PR China
| | - Hui Chen
- School of Animal Science and Technology, Jinling Institute of Technology , Nanjing 210038 , PR China
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Peltier C, Winckler P, Dujourdy L, Bechoua S, Perrier-Cornet JM. Analysis of multivariate images in fluorescence microscopy. Methods Appl Fluoresc 2019; 7:035004. [PMID: 30974420 DOI: 10.1088/2050-6120/ab1886] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
A multivariate image is an image stack in which each pixel contains several variables. Such images are common in many fields (medicine, imaging microscopy, satellite imaging...) and their analysis requires adapted multivariate statistical methods. In fluorescence imaging microscopy, different probes or different measurements such as intensity, fluorescence lifetime or spectral information can be observed from one view. However, this is not yet analysed as multivariate images. Here, we are presenting a full approach of multivariate analysis of fluorescence microscopy images and we are proposing a free R package (multifluo) to conduct it.
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Affiliation(s)
- Caroline Peltier
- Univ. Bourgogne Franche-Comte, Agrosup Dijon, PAM UMR A 02.102, F21000 Dijon, France
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ElMasry G, Mandour N, Al-Rejaie S, Belin E, Rousseau D. Recent Applications of Multispectral Imaging in Seed Phenotyping and Quality Monitoring-An Overview. SENSORS 2019; 19:s19051090. [PMID: 30836613 PMCID: PMC6427362 DOI: 10.3390/s19051090] [Citation(s) in RCA: 55] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/21/2019] [Revised: 02/17/2019] [Accepted: 02/22/2019] [Indexed: 12/02/2022]
Abstract
As a synergistic integration between spectroscopy and imaging technologies, spectral imaging modalities have been emerged to tackle quality evaluation dilemmas by proposing different designs with effective and practical applications in food and agriculture. With the advantage of acquiring spatio-spectral data across a wide range of the electromagnetic spectrum, the state-of-the-art multispectral imaging in tandem with different multivariate chemometric analysis scenarios has been successfully implemented not only for food quality and safety control purposes, but also in dealing with critical research challenges in seed science and technology. This paper will shed some light on the fundamental configuration of the systems and give a birds-eye view of all recent approaches in the acquisition, processing and reproduction of multispectral images for various applications in seed quality assessment and seed phenotyping issues. This review article continues from where earlier review papers stopped but it only focused on fully-operated multispectral imaging systems for quality assessment of different sorts of seeds. Thence, the review comprehensively highlights research attempts devoted to real implementations of only fully-operated multispectral imaging systems and does not consider those ones that just utilized some key wavelengths extracted from hyperspectral data analyses without building independent multispectral imaging systems. This makes this article the first attempt in briefing all published papers in multispectral imaging applications in seed phenotyping and quality monitoring by providing some examples and research results in characterizing physicochemical quality traits, predicting physiological parameters, detection of defect, pest infestation and seed health.
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Affiliation(s)
- Gamal ElMasry
- Department of Pharmacology & Toxicology, College of Pharmacy, King Saud University, Riyadh 11564, Saudi Arabia.
- Faculty of Agriculture, Suez Canal University, Ring Road Km 4.5, Ismailia P.O. Box 41522, Egypt.
- INRA, UMR1345 Institut de Recherche en Horticulture et Semences, 42 rue Georges Morel CS 60057, F-49071 Beaucouzé CEDEX, Angers, France.
| | - Nasser Mandour
- Faculty of Agriculture, Suez Canal University, Ring Road Km 4.5, Ismailia P.O. Box 41522, Egypt.
| | - Salim Al-Rejaie
- Department of Pharmacology & Toxicology, College of Pharmacy, King Saud University, Riyadh 11564, Saudi Arabia.
| | - Etienne Belin
- INRA, UMR1345 Institut de Recherche en Horticulture et Semences, 42 rue Georges Morel CS 60057, F-49071 Beaucouzé CEDEX, Angers, France.
- Laboratoire Angevin de Recherche en Ingénierie des Systèmes (LARIS), Université d'Angers, 62 avenue Notre Dame du Lac, 49000 Angers, France.
| | - David Rousseau
- INRA, UMR1345 Institut de Recherche en Horticulture et Semences, 42 rue Georges Morel CS 60057, F-49071 Beaucouzé CEDEX, Angers, France.
- Laboratoire Angevin de Recherche en Ingénierie des Systèmes (LARIS), Université d'Angers, 62 avenue Notre Dame du Lac, 49000 Angers, France.
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