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Liang J, Wang B, Xu X, Xu J. Integrating portable NIR spectrometry with deep learning for accurate Estimation of crude protein in corn feed. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2024; 314:124203. [PMID: 38565047 DOI: 10.1016/j.saa.2024.124203] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/05/2023] [Revised: 03/12/2024] [Accepted: 03/26/2024] [Indexed: 04/04/2024]
Abstract
This study investigates the challenges encountered in utilizing portable near-infrared (NIR) spectrometers in agriculture, specifically in developing predictive models with high accuracy and robust generalization abilities despite limited spectral resolution and small sample sizes. The research concentrates on the near-infrared spectra of corn feed, utilizing spectral processing techniques and CNNs to precisely estimate crude protein content. Five preprocessing methods were implemented alongside two-dimensional (2D) correlation spectroscopy, resulting in the development of both one-dimensional (1D) and 2D regression models. A comparative analysis of these models in predicting crude protein content demonstrated that 1D-CNNs exhibited superior predictive performance within the 1D category. For the 2D models, CropNet and CropResNet were utilized, with CropResNet demonstrating more accurate and superior predictive capabilities. Overall, the integration of 2D correlation spectroscopy with suitable preprocessing techniques in deep learning models, particularly the 2D CropResNet, proved to be more precise in predicting the crude protein content in corn feed. This finding emphasis the potential of this approach in the portable spectrometer market.
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Affiliation(s)
- Jing Liang
- College of Artificial Intelligence, Nankai University, Tianjin 300350, China
| | - Bin Wang
- College of Artificial Intelligence, Nankai University, Tianjin 300350, China
| | - Xiaoxuan Xu
- College of Artificial Intelligence, Nankai University, Tianjin 300350, China; Yunnan Research Institute, Nankai University, Kunming 650091, China.
| | - Jing Xu
- College of Artificial Intelligence, Nankai University, Tianjin 300350, China
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Wang T, Xu L, Lan T, Deng Z, Yun YH, Zhai C, Qian C. Nondestructive identification and classification of starch types based on multispectral techniques coupled with chemometrics. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2024; 311:123976. [PMID: 38330764 DOI: 10.1016/j.saa.2024.123976] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/21/2023] [Revised: 01/16/2024] [Accepted: 01/27/2024] [Indexed: 02/10/2024]
Abstract
Starch is the main source of energy and nutrition. Therefore, some merchants often illegally add cheaper starches to other types of starches or package cheaper starches as higher priced starches to raise the price. In this study, 159 samples of commercially available wheat starch, potato starch, corn starch and sweet potato starch were selected for the identification and classification based on multispectral techniques, including near-infrared (NIR), mid-infrared (MIR) and Raman spectroscopy combined with chemometrics, including pretreatment methods, characteristic wavelength selection methods and classification algorithms. The results indicate that all three spectral techniques can be used to discriminate starch types. The Raman spectroscopy demonstrated superior performance compared to that of NIR and MIR spectroscopy. The accuracy of the models after characteristic wavelength selection is generally superior to that of the full spectrum, and two-dimensional correlation spectroscopy (2D-COS) achieves better model performance than other wavelength selection methods. Among the four classification methods, convolutional neural network (CNN) exhibited the best prediction performance, achieving accuracies of 99.74 %, 97.57 % and 98.65 % in NIR, MIR and Raman spectra, respectively, without pretreatment or characteristic wavelength selection.
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Affiliation(s)
- Tao Wang
- School of Food Science and Engineering, Hainan University, Haikou 570228, PR China
| | - Lilan Xu
- School of Food Science and Engineering, Hainan University, Haikou 570228, PR China
| | - Tao Lan
- School of Food Science and Engineering, Hainan University, Haikou 570228, PR China
| | - Zhuowen Deng
- School of Food Science and Engineering, Hainan University, Haikou 570228, PR China
| | - Yong-Huan Yun
- School of Food Science and Engineering, Hainan University, Haikou 570228, PR China; Hainan Institute for Food Control, Key Laboratory of Tropical Fruits and Vegetables Quality and Safety for State Market Regulation, Haikou 570314, PR China.
| | - Chen Zhai
- COFCO Nutrition and Health Research Institute, Beijing Key Laboratory of Nutrition and Health and Food Safety, Beijing 102209, PR China.
| | - Chengjing Qian
- COFCO Nutrition and Health Research Institute, Beijing Key Laboratory of Nutrition and Health and Food Safety, Beijing 102209, PR China
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Tan Y, Xu S, Zhang H, Tang H, Wang Z, Li J, Tan N. A comprehensive quality evaluation strategy of Mailuoning oral liquid based on fingerprint, qualitative and quantitative analyses. J Pharm Biomed Anal 2023; 234:115497. [PMID: 37573813 DOI: 10.1016/j.jpba.2023.115497] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2023] [Revised: 05/12/2023] [Accepted: 05/28/2023] [Indexed: 08/15/2023]
Abstract
In order to obtain comprehensive quality evaluation of one traditional Chinese patent medicine of Mailuoning oral liquid (MLN), one smart strategy combined by fingerprint, qualitative and quantitative analyses were carried out in this study. Firstly, the fingerprints of MLN were established by HPLC-UV and HPLC-ELSD, and explained the similarity of twenty-seven batches of MLN by similarity analysis (SA). Secondly, qualitative analysis was performed by high performance liquid chromatography coupled with quadrupole-time-of-flight mass spectrometry (HPLC-QTOF-MS/MS). A total of 60 compounds were identified or tentatively identified based on chemical standards and fragmentation information. Finally, the quantitative method based on UPLC combined with triple quadrupole mass spectrometry (UPLC-QqQ-MS/MS) was developed for the simultaneous determination of 40 target compounds. The results showed that MLN samples of different productive year were clearly discriminated and eight compounds (5-hydroxymethyl-2-furaldehyde, neochlorogenic acid, loganic acid, chlorogenic acid, cryptochlorogenic acid, caffeic acid, isoacteoside, angoroside C) were selected as differential markers for MLN. In a word, this strategy including fingerprint, identification of chemical composition and multiple-component quantification could be well applied to modern quality evaluation of MLN, which could be valuable for the further quality control of more other traditional Chinese patent medicines.
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Affiliation(s)
- Yajie Tan
- Department of TCMs Pharmaceuticals, School of Traditional Chinese Pharmacy, China Pharmaceutical University, Nanjing 211198, PR China
| | - Siyi Xu
- Department of TCMs Pharmaceuticals, School of Traditional Chinese Pharmacy, China Pharmaceutical University, Nanjing 211198, PR China
| | - Hui Zhang
- Jinling Pharmaceutical Co., Ltd., Nanjing 210009, PR China
| | - Haojun Tang
- Department of TCMs Pharmaceuticals, School of Traditional Chinese Pharmacy, China Pharmaceutical University, Nanjing 211198, PR China
| | - Zhen Wang
- Department of TCMs Pharmaceuticals, School of Traditional Chinese Pharmacy, China Pharmaceutical University, Nanjing 211198, PR China
| | - Jian Li
- Department of TCMs Pharmaceuticals, School of Traditional Chinese Pharmacy, China Pharmaceutical University, Nanjing 211198, PR China; Jinling Pharmaceutical Co., Ltd., Nanjing 210009, PR China.
| | - Ninghua Tan
- Department of TCMs Pharmaceuticals, School of Traditional Chinese Pharmacy, China Pharmaceutical University, Nanjing 211198, PR China.
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A rapid and effective method for species identification of edible boletes: FT-NIR spectroscopy combined with ResNet. J Food Compost Anal 2022. [DOI: 10.1016/j.jfca.2022.104698] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
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Schütz D, Riedl J, Achten E, Fischer M. Fourier-transform near-infrared spectroscopy as a fast screening tool for the verification of the geographical origin of grain maize (Zea mays L.). Food Control 2022. [DOI: 10.1016/j.foodcont.2022.108892] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
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De Géa Neves M, Poppi RJ, Breitkreitz MC. Authentication of plant-based protein powders and classification of adulterants as whey, soy protein, and wheat using FT-NIR in tandem with OC-PLS and PLS-DA models. Food Control 2022. [DOI: 10.1016/j.foodcont.2021.108489] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
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Rhouma M, Lachapelle V, Comeau G, Quessy S, Zanabria R, Provost F, Italiano C, Holley R, Smillie J, Brockhoff E, Bosch ML, Collins S, Dumas A, Chorfi Y, Costa M, Gaucher ML, Racicot M. Identification and selection of animal health and food safety-related risk factors to be included in the Canadian Food Inspection Agency's risk assessment model for livestock feed mills. Food Control 2021. [DOI: 10.1016/j.foodcont.2020.107642] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
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Chemometric non-targeted analysis for detection of soybean meal adulteration by near infrared spectroscopy. Food Control 2021. [DOI: 10.1016/j.foodcont.2020.107459] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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Marcheafave GG, Pauli ED, Tormena CD, Mattos LE, de Almeida AG, Rakocevic M, Bruns RE, Scarminio IS. Irrigated and CO2 level effects on metabolism in Coffea arabica beans from mixture design – near infrared fingerprints. Microchem J 2020. [DOI: 10.1016/j.microc.2019.104276] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
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Zhao Q, Lv X, Jia Y, Chen Y, Xu G, Qu L. Rapid determination of the fat, moisture, and protein contents in homogenized chicken eggs based on near-infrared reflectance spectroscopy. Poult Sci 2018; 97:2239-2245. [PMID: 29562300 DOI: 10.3382/ps/pey070] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2017] [Accepted: 02/06/2018] [Indexed: 11/20/2022] Open
Abstract
Current analytical methods used for composition analysis of egg products are time consuming and laborious. We developed a near-infrared reflectance spectroscopy (NIRS)-based method to determine the fat, moisture, and protein contents in homogenized egg yolk and the moisture and protein contents in homogenized egg albumen to substitute for conventional methods. The coefficients of determination in the external validation set (R2P) were over 0.8 for all chemical compositions. The ratios of performance to standard deviation (RPD) were 4.38, 2.25, 2.28, 2.31, and 3.03 for fat, moisture, protein and moisture in the egg yolk, and protein in the egg albumen, respectively. Thus, NIR spectroscopy could be an efficient tool for quantitative analysis of the nutrients in chicken eggs.
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Affiliation(s)
- Qingna Zhao
- Department of Animal Genetics and Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Xueze Lv
- Beijing General Station of Animal Husbandry, Beijing, 100107, China
| | - Yaxiong Jia
- Beijing General Station of Animal Husbandry, Beijing, 100107, China
| | - Yu Chen
- Beijing General Station of Animal Husbandry, Beijing, 100107, China
| | - Guiyun Xu
- Department of Animal Genetics and Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Lujiang Qu
- Department of Animal Genetics and Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
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Pereira JM, Leme LM, Perdoncini MRFG, Valderrama P, Março PH. Fast Discrimination of Milk Contaminated with Salmonella sp. Via Near-Infrared Spectroscopy. FOOD ANAL METHOD 2017. [DOI: 10.1007/s12161-017-1090-0] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
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Grelet C, Bastin C, Gelé M, Davière JB, Johan M, Werner A, Reding R, Fernandez Pierna J, Colinet F, Dardenne P, Gengler N, Soyeurt H, Dehareng F. Development of Fourier transform mid-infrared calibrations to predict acetone, β-hydroxybutyrate, and citrate contents in bovine milk through a European dairy network. J Dairy Sci 2016; 99:4816-4825. [DOI: 10.3168/jds.2015-10477] [Citation(s) in RCA: 81] [Impact Index Per Article: 10.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2015] [Accepted: 02/12/2016] [Indexed: 11/19/2022]
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de Jong J, López P, Mol H, Baeten V, Fernández Pierna JA, Vermeulen P, Vincent U, Boix A, von Holst C, Tomaniova M, Hajslova J, Yang Z, Han L, MacDonald S, Haughey SA, Elliott CT. Analytical strategies for the early quality and safety assurance in the global feed chain. Trends Analyt Chem 2016. [DOI: 10.1016/j.trac.2015.11.003] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
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Baeten V, Pierna JAF, Lecler B, Abbas O, Vincke D, Minet O, Vermeulen P, Dardenne P. Near Infrared Spectroscopy for Food and Feed: A Mature Technique. ACTA ACUST UNITED AC 2016. [DOI: 10.1255/nirn.1573] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/01/2022]
Affiliation(s)
- Vincent Baeten
- Food and Feed Unit, Valorisation of Agricultural Products Department, Walloon Agricultural Research Centre, CRA-W
| | | | - Bernard Lecler
- Food and Feed Unit, Valorisation of Agricultural Products Department, Walloon Agricultural Research Centre, CRA-W
| | - Ouissam Abbas
- Food and Feed Unit, Valorisation of Agricultural Products Department, Walloon Agricultural Research Centre, CRA-W
| | - Damien Vincke
- Food and Feed Unit, Valorisation of Agricultural Products Department, Walloon Agricultural Research Centre, CRA-W
| | - Olivier Minet
- Food and Feed Unit, Valorisation of Agricultural Products Department, Walloon Agricultural Research Centre, CRA-W
| | - Philippe Vermeulen
- Food and Feed Unit, Valorisation of Agricultural Products Department, Walloon Agricultural Research Centre, CRA-W
| | - Pierre Dardenne
- Food and Feed Unit, Valorisation of Agricultural Products Department, Walloon Agricultural Research Centre, CRA-W
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Origin authentication of distillers' dried grains and solubles (DDGS)--application and comparison of different analytical strategies. Anal Bioanal Chem 2015; 407:6447-61. [PMID: 26123435 DOI: 10.1007/s00216-015-8807-y] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2015] [Revised: 05/22/2015] [Accepted: 05/26/2015] [Indexed: 10/23/2022]
Abstract
In the context of products from certain regions or countries being banned because of an identified or non-identified hazard, proof of geographical origin is essential with regard to feed and food safety issues. Usually, the product labeling of an affected feed lot shows origin, and the paper documentation shows traceability. Incorrect product labeling is common in embargo situations, however, and alternative analytical strategies for controlling feed authenticity are therefore needed. In this study, distillers' dried grains and solubles (DDGS) were chosen as the product on which to base a comparison of analytical strategies aimed at identifying the most appropriate one. Various analytical techniques were investigated for their ability to authenticate DDGS, including spectroscopic and spectrometric techniques combined with multivariate data analysis, as well as proven techniques for authenticating food, such as DNA analysis and stable isotope ratio analysis. An external validation procedure (called the system challenge) was used to analyze sample sets blind and to compare analytical techniques. All the techniques were adapted so as to be applicable to the DDGS matrix. They produced positive results in determining the botanical origin of DDGS (corn vs. wheat), and several of them were able to determine the geographical origin of the DDGS in the sample set. The maintenance and extension of the databanks generated in this study through the analysis of new authentic samples from a single location are essential in order to monitor developments and processing that could affect authentication.
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Olivieri AC. Practical guidelines for reporting results in single- and multi-component analytical calibration: A tutorial. Anal Chim Acta 2015; 868:10-22. [DOI: 10.1016/j.aca.2015.01.017] [Citation(s) in RCA: 145] [Impact Index Per Article: 16.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2014] [Revised: 01/08/2015] [Accepted: 01/12/2015] [Indexed: 10/24/2022]
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