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Shi S, Tang Z, Ma Y, Cao C, Jiang Y. Application of spectroscopic techniques combined with chemometrics to the authenticity and quality attributes of rice. Crit Rev Food Sci Nutr 2023:1-23. [PMID: 38010116 DOI: 10.1080/10408398.2023.2284246] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2023]
Abstract
Rice is a staple food for two-thirds of the world's population and is grown in over a hundred countries around the world. Due to its large scale, it is vulnerable to adulteration. In addition, the quality attribute of rice is an important factor affecting the circulation and price, which is also paid more and more attention. The combination of spectroscopy and chemometrics enables rapid detection of authenticity and quality attributes in rice. This article described the application of seven spectroscopic techniques combined with chemometrics to the rice industry. For a long time, near-infrared spectroscopy and linear chemometric methods (e.g., PLSR and PLS-DA) have been widely used in the rice industry. Although some studies have achieved good accuracy, with models in many studies having greater than 90% accuracy. However, higher accuracy and stability were more likely to be obtained using multiple spectroscopic techniques, nonlinear chemometric methods, and key wavelength selection algorithms. Future research should develop larger rice databases to include more rice varieties and larger amounts of rice depending on the type of rice, and then combine various spectroscopic techniques, nonlinear chemometric methods, and key wavelength selection algorithms. This article provided a reference for a more efficient and accurate determination of rice quality and authenticity.
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Affiliation(s)
- Shijie Shi
- College of Plant Science and Technology, Huazhong Agricultural University, Wuhan, Hubei, China
| | - Zihan Tang
- College of Plant Science and Technology, Huazhong Agricultural University, Wuhan, Hubei, China
| | - Yingying Ma
- College of Plant Science and Technology, Huazhong Agricultural University, Wuhan, Hubei, China
| | - Cougui Cao
- College of Plant Science and Technology, Huazhong Agricultural University, Wuhan, Hubei, China
- Shuangshui Shuanglü Institute, Huazhong Agricultural University, Wuhan, Hubei, China
| | - Yang Jiang
- College of Plant Science and Technology, Huazhong Agricultural University, Wuhan, Hubei, China
- Shuangshui Shuanglü Institute, Huazhong Agricultural University, Wuhan, Hubei, China
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Fu G, Hu W, Xie W, Yao X, Xu J, Yang P, Yao M. Quantitative analysis of Cd based on the stress effect of minerals in rice by laser-induced breakdown spectroscopy. ANALYTICAL METHODS : ADVANCING METHODS AND APPLICATIONS 2023; 15:5867-5874. [PMID: 37902026 DOI: 10.1039/d3ay01340e] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/31/2023]
Abstract
Cadmium (Cd) is a highly toxic heavy metal that can accumulate in the food chain, posing a significant threat to human health. One of the key food sources through which Cd is often observed is rice. Therefore, determining heavy metals in rice is essential to assess the risk status of rice. Laser-induced breakdown spectroscopy (LIBS) has the advantages of simple sample preparation and fast analysis, which is expected to achieve real-time and rapid detection of rice. In this work, 40 naturally matured rice samples growing from the area that is possibly contaminated with Cd were collected to determine the Cd reference content in rice by graphite furnace atomic absorption spectroscopy as recommended by the Chinese National Standard. LIBS spectral acquisition and analysis are adopted as well. The Cd characteristic spectral lines were selected to predict the Cd content directly using PCA, PLSR, and ELM models, and the coefficient of determination (R2) of the models' training and prediction sets was 0.9278, 0.8920; 0.9036, 0.9771; 0.7940, and 0.8409, respectively. Further, based on the Cd stress effect in rice, the spectra of elements Mn, Mg, K, and Na with highly significant and significant correlation with Cd were selected and coupled with the Cd characteristic spectra to form a new matrix of the same size for quantitative analysis. Based on the stress effect, R2 of models' training and prediction sets was improved to 0.9786, 0.9753; 0.9395, 0.9900; 0.9798, and 0.9927, respectively. It is demonstrated that combining the stress effect when using LIBS for quantitative analysis of Cd in rice reduces the overfitting and further improves the model's prediction accuracy. This work indicates that using LIBS combined with suitable mathematical models to predict the Cd content of naturally matured rice based on stress effects in rice is feasible. It is promising to evaluate the safety of rice by analyzing LIBS spectra.
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Affiliation(s)
- Gangrong Fu
- College of Engineering, Jiangxi Agricultural University, Nanchang 330045, China.
| | - Wei Hu
- College of Engineering, Jiangxi Agricultural University, Nanchang 330045, China.
| | - Weiping Xie
- College of Engineering, Jiangxi Agricultural University, Nanchang 330045, China.
| | - Xiaoying Yao
- College of Vocational and Technical Education, Jiangxi Agricultural University, Nanchang 330045, China
| | - Jiang Xu
- College of Engineering, Jiangxi Agricultural University, Nanchang 330045, China.
| | - Ping Yang
- Institute of Electronic, Changzhou College of Information Technology, Changzhou 213164, China
| | - Mingyin Yao
- College of Engineering, Jiangxi Agricultural University, Nanchang 330045, China.
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Zaldarriaga Heredia J, Wagner M, Jofré FC, Savio M, Azcarate SM, Camiña JM. An overview on multi-elemental profile integrated with chemometrics for food quality assessment: toward new challenges. Crit Rev Food Sci Nutr 2022; 63:8173-8193. [PMID: 35319312 DOI: 10.1080/10408398.2022.2055527] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Food products, especially those with high value-added, are commonly subjected to strict quality controls, which are of paramount importance, especially for attesting to some peculiar features related, for instance, to their geographical origin and/or the know-how of their producers. However, the sophistication of fraudulent practices requires a continuous update of analytical platforms. Different analytical techniques have become extremely appealing since the instrumental analysis tools evolution has substantially improved the capability to reveal and understand the complexity of food. In light of this, multi-elemental composition has been successful implemented solving a plethora of food authentication and traceability issues. In the last decades, it has existed an ever-increasing trend in analysis based on spectrometry analytical platforms in order to obtain a multi-elemental profile that combined with chemometrics have been noteworthy analytical methodologies able to solve these problems. This review provides an overview of published reports in the last decade (from 2011 to 2021) on food authentication and quality control from their multi-element composition in order to evaluate the state-of-the-art of this field and to identify the main characteristics of applied analytical techniques and chemometric data treatments that have permit achieve accurate discrimination/classification models, highlighting the strengths and the weaknesses of these methodologies.
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Affiliation(s)
- Jorgelina Zaldarriaga Heredia
- Instituto de Ciencias de la Tierra y Ambientales de La Pampa (INCITAP-CONICET), Santa Rosa, La Pampa, Argentina
- Facultad de Ciencias Exactas y Naturales, Universidad Nacional de La Pampa (UNLPam), Santa Rosa, La Pampa, Argentina
| | - Marcelo Wagner
- Instituto de Ciencias de la Tierra y Ambientales de La Pampa (INCITAP-CONICET), Santa Rosa, La Pampa, Argentina
| | - Florencia Cora Jofré
- Instituto de Ciencias de la Tierra y Ambientales de La Pampa (INCITAP-CONICET), Santa Rosa, La Pampa, Argentina
- Facultad de Ciencias Exactas y Naturales, Universidad Nacional de La Pampa (UNLPam), Santa Rosa, La Pampa, Argentina
| | - Marianela Savio
- Instituto de Ciencias de la Tierra y Ambientales de La Pampa (INCITAP-CONICET), Santa Rosa, La Pampa, Argentina
- Facultad de Ciencias Exactas y Naturales, Universidad Nacional de La Pampa (UNLPam), Santa Rosa, La Pampa, Argentina
| | - Silvana Mariela Azcarate
- Instituto de Ciencias de la Tierra y Ambientales de La Pampa (INCITAP-CONICET), Santa Rosa, La Pampa, Argentina
- Facultad de Ciencias Exactas y Naturales, Universidad Nacional de La Pampa (UNLPam), Santa Rosa, La Pampa, Argentina
| | - José Manuel Camiña
- Instituto de Ciencias de la Tierra y Ambientales de La Pampa (INCITAP-CONICET), Santa Rosa, La Pampa, Argentina
- Facultad de Ciencias Exactas y Naturales, Universidad Nacional de La Pampa (UNLPam), Santa Rosa, La Pampa, Argentina
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Müller-Maatsch J, van Ruth SM. Handheld Devices for Food Authentication and Their Applications: A Review. Foods 2021; 10:2901. [PMID: 34945454 PMCID: PMC8700508 DOI: 10.3390/foods10122901] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2021] [Revised: 11/18/2021] [Accepted: 11/21/2021] [Indexed: 12/18/2022] Open
Abstract
This review summarises miniaturised technologies, commercially available devices, and device applications for food authentication or measurement of features that could potentially be used for authentication. We first focus on the handheld technologies and their generic characteristics: (1) technology types available, (2) their design and mode of operation, and (3) data handling and output systems. Subsequently, applications are reviewed according to commodity type for products of animal and plant origin. The 150 applications of commercial, handheld devices involve a large variety of technologies, such as various types of spectroscopy, imaging, and sensor arrays. The majority of applications, ~60%, aim at food products of plant origin. The technologies are not specifically aimed at certain commodities or product features, and no single technology can be applied for authentication of all commodities. Nevertheless, many useful applications have been developed for many food commodities. However, the use of these applications in practice is still in its infancy. This is largely because for each single application, new spectral databases need to be built and maintained. Therefore, apart from developing applications, a focus on sharing and re-use of data and calibration transfers is pivotal to remove this bottleneck and to increase the implementation of these technologies in practice.
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Affiliation(s)
- Judith Müller-Maatsch
- Wageningen Food Safety Research, Wageningen University and Research, P.O. Box 230, 6700 EV Wageningen, The Netherlands;
| | - Saskia M. van Ruth
- Wageningen Food Safety Research, Wageningen University and Research, P.O. Box 230, 6700 EV Wageningen, The Netherlands;
- Food Quality and Design, Wageningen University and Research, P.O. Box 17, 6700 AA Wageningen, The Netherlands
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Chen JY, Chen XW, Lin YY, Yen GC, Lin JA. Authentication of dark brown sugars from different processing using three-dimensional fluorescence spectroscopy. Lebensm Wiss Technol 2021. [DOI: 10.1016/j.lwt.2021.111959] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
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Stefas D, Gyftokostas N, Nanou E, Kourelias P, Couris S. Laser-Induced Breakdown Spectroscopy: An Efficient Tool for Food Science and Technology (from the Analysis of Martian Rocks to the Analysis of Olive Oil, Honey, Milk, and Other Natural Earth Products). Molecules 2021; 26:4981. [PMID: 34443568 PMCID: PMC8401734 DOI: 10.3390/molecules26164981] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2021] [Revised: 08/11/2021] [Accepted: 08/14/2021] [Indexed: 11/16/2022] Open
Abstract
Laser-Induced Breakdown Spectroscopy (LIBS), having reached a level of maturity during the last few years, is generally considered as a very powerful and efficient analytical tool, and it has been proposed for a broad range of applications, extending from space exploration down to terrestrial applications, from cultural heritage to food science and security. Over the last decade, there has been a rapidly growing sub-field concerning the application of LIBS for food analysis, safety, and security, which along with the implementation of machine learning and chemometric algorithms opens new perspectives and possibilities. The present review intends to provide a short overview of the current state-of-the-art research activities concerning the application of LIBS for the analysis of foodstuffs, with the emphasis given to olive oil, honey, and milk.
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Affiliation(s)
- Dimitrios Stefas
- Department of Physics, University of Patras, 26504 Patras, Greece; (D.S.); (N.G.); (E.N.); (P.K.)
- Institute of Chemical Engineering Sciences (ICE-HT), Foundation for Research and Technology-Hellas (FORTH), 26504 Patras, Greece
| | - Nikolaos Gyftokostas
- Department of Physics, University of Patras, 26504 Patras, Greece; (D.S.); (N.G.); (E.N.); (P.K.)
- Institute of Chemical Engineering Sciences (ICE-HT), Foundation for Research and Technology-Hellas (FORTH), 26504 Patras, Greece
| | - Eleni Nanou
- Department of Physics, University of Patras, 26504 Patras, Greece; (D.S.); (N.G.); (E.N.); (P.K.)
- Institute of Chemical Engineering Sciences (ICE-HT), Foundation for Research and Technology-Hellas (FORTH), 26504 Patras, Greece
| | - Panagiotis Kourelias
- Department of Physics, University of Patras, 26504 Patras, Greece; (D.S.); (N.G.); (E.N.); (P.K.)
- Institute of Chemical Engineering Sciences (ICE-HT), Foundation for Research and Technology-Hellas (FORTH), 26504 Patras, Greece
| | - Stelios Couris
- Department of Physics, University of Patras, 26504 Patras, Greece; (D.S.); (N.G.); (E.N.); (P.K.)
- Institute of Chemical Engineering Sciences (ICE-HT), Foundation for Research and Technology-Hellas (FORTH), 26504 Patras, Greece
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Detection of Meat Adulteration Using Spectroscopy-Based Sensors. Foods 2021; 10:foods10040861. [PMID: 33920872 PMCID: PMC8071343 DOI: 10.3390/foods10040861] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2021] [Revised: 03/31/2021] [Accepted: 04/13/2021] [Indexed: 11/16/2022] Open
Abstract
Minced meat is a vulnerable to adulteration food commodity because species- and/or tissue-specific morphological characteristics cannot be easily identified. Hence, the economically motivated adulteration of minced meat is rather likely to be practiced. The objective of this work was to assess the potential of spectroscopy-based sensors in detecting fraudulent minced meat substitution, specifically of (i) beef with bovine offal and (ii) pork with chicken (and vice versa) both in fresh and frozen-thawed samples. For each case, meat pieces were minced and mixed so that different levels of adulteration with a 25% increment were achieved while two categories of pure meat also were considered. From each level of adulteration, six different samples were prepared. In total, 120 samples were subjected to visible (Vis) and fluorescence (Fluo) spectra and multispectral image (MSI) acquisition. Support Vector Machine classification models were developed and evaluated. The MSI-based models outperformed the ones based on the other sensors with accuracy scores varying from 87% to 100%. The Vis-based models followed in terms of accuracy with attained scores varying from 57% to 97% while the lowest performance was demonstrated by the Fluo-based models. Overall, spectroscopic data hold a considerable potential for the detection and quantification of minced meat adulteration, which, however, appears to be sensor-specific.
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Laser-induced breakdown spectroscopy coupled with machine learning as a tool for olive oil authenticity and geographic discrimination. Sci Rep 2021; 11:5360. [PMID: 33686131 PMCID: PMC7970888 DOI: 10.1038/s41598-021-84941-z] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2020] [Accepted: 02/18/2021] [Indexed: 02/06/2023] Open
Abstract
Olive oil is a basic element of the Mediterranean diet and a key product for the economies of the Mediterranean countries. Thus, there is an added incentive in the olive oil business for fraud through practices like adulteration and mislabeling. In the present work, Laser Induced Breakdown Spectroscopy (LIBS) assisted by machine learning is used for the classification of 139 virgin olive oils in terms of their geographical origin. The LIBS spectra of these olive oil samples were used to train different machine learning algorithms, namely LDA, ERTC, RFC, XGBoost, and to assess their classification performance. In addition, the variable importance of the spectral features was calculated, for the identification of the most important ones for the classification performance and to reduce their number for the algorithmic training. The algorithmic training was evaluated and tested by means of classification reports, confusion matrices and by external validation procedure as well. The present results demonstrate that machine learning aided LIBS can be a powerful and efficient tool for the rapid authentication of the geographic origin of virgin olive oil.
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Olive Oils Classification via Laser-Induced Breakdown Spectroscopy. APPLIED SCIENCES-BASEL 2020. [DOI: 10.3390/app10103462] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
The classification of olive oils and the authentication of their geographic origin are important issues for public health and for the olive oil market and related industry. The development of fast, easy to use, suitable for on-line, in-situ and remote operation techniques for olive oils classification is of high interest. In the present work, 36 olive oils from different places in Crete, Greece, are studied using a laser-based technique, Laser-Induced Breakdown Spectroscopy (LIBS), assisted by machine learning algorithms, aiming to classify them in terms of their geographical origin. The excellent classification results obtained demonstrate the great potential of LIBS, which is further extended by the use of machine learning.
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