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Rapid Nondestructive Detection of Water Content and Granulation in Postharvest "Shatian" Pomelo Using Visible/Near-Infrared Spectroscopy. BIOSENSORS-BASEL 2020; 10:bios10040041. [PMID: 32326115 PMCID: PMC7235785 DOI: 10.3390/bios10040041] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/12/2020] [Revised: 04/15/2020] [Accepted: 04/15/2020] [Indexed: 11/17/2022]
Abstract
Visible/near-infrared (VIS/NIR) spectroscopy is a powerful tool for rapid, nondestructive fruit quality detection. This technology has been widely applied for quality detection of small, thin-peeled fruit, though less so for large, thick-peeled fruit due to a weak spectral signal resulting in a reduction of accuracy. More modeling work should be focused on solving this problem. “Shatian” pomelo is a traditional Chinese large, thick-peeled fruit, and granulation and water loss are two major internal quality factors that influence its storage quality. However, there is no efficient, nondestructive detection method for measuring these factors. Thus, the VIS/NIR spectral signal detection of 120 pomelo samples during storage was performed. Information mining (singular sample elimination, data processing, feature extraction) and modeling were performed in different ways to construct the optimal method for achieving an accurate detection. Our results showed that the water content of postharvest pomelo was optimally detected using the Savitzky–Golay method (SG) plus the multiplicative scatter correction method (MSC) for data processing, genetic algorithm (GA) for feature extraction, and partial least squares regression (PLSR) for modeling (the coefficient of determination and root mean squared error of the validation set were 0.712 and 0.0488, respectively). Granulation degree was best detected using SG for data processing and PLSR for modeling (the detection accuracy of the validation set was 100%). Additionally, our research showed a weak relationship between the pomelo water content and granulation degree, which provided a reference for the existing debates. Therefore, our results demonstrated that VIS/NIR combined with optimal information mining and modeling methodswas feasible for determining the water content and granulation degree of postharvest pomelo, and for providing references for the nondestructive internal quality detection of other large, thick-peeled fruits.
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Yang X, Li Y, Wang L, Li L, Guo L, Huang F, Zhao H. Determination of 10-Hydroxy-2-Decenoic Acid of Royal Jelly Using Near-Infrared Spectroscopy Combined with Chemometrics. J Food Sci 2019; 84:2458-2466. [PMID: 31483872 DOI: 10.1111/1750-3841.14748] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2019] [Revised: 06/29/2019] [Accepted: 07/03/2019] [Indexed: 11/29/2022]
Abstract
A rapid quantitative analysis model for determining the hydroxy-2-decenoic acid (10-HDA) content of royal jelly based on near-infrared spectroscopy combining with PLS has been developed. Firstly, near-infrared spectra of 232 royal jelly samples with different 10-HDA concentrations (0.35% to 2.44%) were be collected. Second-order derivative processing of the spectra was carried out to construct a full-spectrum PLS model. Secondly, GA-PLS, CARS-PLS, and Si-PLS were used to select characteristic wavelengths from the second-order derivative spectrum to construct a PLS calibration model. Finally, 58 samples were used to select the best predictive model for 10-HDA content. The result show that the PLS model constructed after wavelength selection was significantly more accurate than the full spectrum model. The Si-PLS algorithm performed best and the corresponding characteristic wavelength range were: 980 to 1038, 1220 to 1278, 1340 to 1398, and 1688 to 1746 nm. The prediction results were RMSEP = 0.1496% and RP = 0.9380. Hence, it is feasible to employ near-infrared spectra to analyze 10-HDA in royal jelly.
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Affiliation(s)
- Xinhao Yang
- Guangdong Provincial Key Laboratory of Optical Fiber Sensing and Communications, Dept. of Optoelectronic Engineering, Jinan Univ., Guangzhou, 510632, China
| | - Yuanpeng Li
- Guangdong Provincial Key Laboratory of Optical Fiber Sensing and Communications, Dept. of Optoelectronic Engineering, Jinan Univ., Guangzhou, 510632, China
| | - Lei Wang
- Hangzhou Tienchu Miyuan Health Food Co., Ltd
| | - Liqun Li
- Guangdong Key Laboratory of Animal Conservation and Resource Utilization, Guangdong Public Laboratory of Wild Animal Conservation and Utilization, Guangdong Inst. of Applied Biological Resources, Guangzhou, 510260, China
| | - Liu Guo
- Guangdong Provincial Key Laboratory of Optical Fiber Sensing and Communications, Dept. of Optoelectronic Engineering, Jinan Univ., Guangzhou, 510632, China
| | - Furong Huang
- Guangdong Provincial Key Laboratory of Optical Fiber Sensing and Communications, Dept. of Optoelectronic Engineering, Jinan Univ., Guangzhou, 510632, China.,Research Inst. of Jinan Univ. in Dongguan, Dongguan, 523000, China
| | - Hongxia Zhao
- Guangdong Key Laboratory of Animal Conservation and Resource Utilization, Guangdong Public Laboratory of Wild Animal Conservation and Utilization, Guangdong Inst. of Applied Biological Resources, Guangzhou, 510260, China
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Nondestructive Determination and Visualization of Quality Attributes in Fresh and Dry Chrysanthemum morifolium Using Near-Infrared Hyperspectral Imaging. APPLIED SCIENCES-BASEL 2019. [DOI: 10.3390/app9091959] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Rapid and nondestructive determination of quality attributes in fresh and dry Chrysanthemum morifolium is of great importance for quality sorting and monitoring during harvest and trade. Near-infrared hyperspectral imaging covering the spectral range of 874–1734 nm was used to detect chlorogenic acid, luteolin-7-O-glucoside, and 3,5-O-dicaffeoylquinic acid content in Chrysanthemum morifolium. Fresh and dry Chrysanthemum morifolium flowers were studied for harvest and trade. Pixelwise spectra were preprocessed by wavelet transform (WT) and area normalization, and calculated as average spectrum. Successive projections algorithm (SPA) was used to select optimal wavelengths. Partial least squares (PLS), extreme learning machine (ELM), and least-squares support vector machine (LS-SVM) were used to build calibration models based on full spectra and optimal wavelengths. Calibration models of fresh and dry flowers obtained good results. Calibration models for chlorogenic acid in fresh flowers obtained best performances, with coefficient of determination (R2) over 0.85 and residual predictive deviation (RPD) over 2.50. Visualization maps of chlorogenic acid, luteolin-7-O-glucoside, and 3,5-O-dicaffeoylquinic acid in single fresh and dry flowers were obtained. The overall results showed that hyperspectral imaging was feasible to determine chlorogenic acid, luteolin-7-O-glucoside, and 3,5-O-dicaffeoylquinic acid. Much more work should be done in the future to improve the prediction performance.
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Determination of Total Polysaccharides and Total Flavonoids in Chrysanthemum morifolium Using Near-Infrared Hyperspectral Imaging and Multivariate Analysis. Molecules 2018; 23:molecules23092395. [PMID: 30235811 PMCID: PMC6225252 DOI: 10.3390/molecules23092395] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2018] [Revised: 09/16/2018] [Accepted: 09/18/2018] [Indexed: 11/17/2022] Open
Abstract
The rapid and nondestructive determination of active compositions in Chrysanthemum morifolium (Hangbaiju) is of great value for producers and consumers. Hyperspectral imaging as a rapid and nondestructive technique was used to determine total polysaccharides and total flavonoids content in Chrysanthemum morifolium. Hyperspectral images of different sizes of Chrysanthemum morifolium flowers were acquired. Pixel-wise spectra within all samples were preprocessed by wavelet transform (WT) followed by standard normal variate (SNV). Partial least squares (PLS) and least squares-support vector machine (LS-SVM) were used to build prediction models using sample average spectra calculated by preprocessed pixel-wise spectra. The LS-SVM model performed better than the PLS models, with the determination of the coefficient of calibration (R2c) and prediction (R2p) being over 0.90 and the residual predictive deviation (RPD) being over 3 for total polysaccharides and total flavonoids content prediction. Prediction maps of total polysaccharides and total flavonoids content in Chrysanthemum morifolium flowers were successfully obtained by LS-SVM models, which exhibited the best performances. The overall results showed that hyperspectral imaging was a promising technique for the rapid and accurate determination of active ingredients in Chrysanthemum morifolium, indicating the great potential to develop an online system for the quality determination of Chrysanthemum morifolium.
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Li X, Zhou R, Xu K, Xu J, Jin J, Fang H, He Y. Rapid Determination of Chlorophyll and Pheophytin in Green Tea Using Fourier Transform Infrared Spectroscopy. Molecules 2018; 23:molecules23051010. [PMID: 29701638 PMCID: PMC6100186 DOI: 10.3390/molecules23051010] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2018] [Revised: 04/16/2018] [Accepted: 04/20/2018] [Indexed: 11/29/2022] Open
Abstract
The chlorophyll, pheophytin, and their proportions are critical factors to evaluate the sensory quality of green tea. This research aims to establish an effective method to determine the quantification of chlorophyll and pheophytin in green tea, based on Fourier transform infrared (FT–IR) spectroscopy. First, five brands of tea were collected for spectral acquisition, and the chlorophyll and pheophytin were measured using the reference method. Then, a relation between these two pigments and FT–IR spectroscopy were developed based on chemometrics. Additionally, the characteristic IR wavenumbers of these pigments were extracted and proved to be effective for a quantitative determination. Successively, non-linear models were also built based on these characteristic wavenumbers, obtaining coefficients of determination of 0.87, 0.80, 0.85 and 0.89; and relative predictive deviations of 2.77, 2.62, 2.26 and 3.07 for the four pigments, respectively. These results demonstrate the feasibility of FT–IR spectroscopy for the determination of chlorophyll and pheophytin.
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Affiliation(s)
- Xiaoli Li
- College of Biosystems Engineering and Food Science, Zhejiang University, 866 Yuhangtang Road, Hangzhou 310058, China.
| | - Ruiqing Zhou
- College of Biosystems Engineering and Food Science, Zhejiang University, 866 Yuhangtang Road, Hangzhou 310058, China.
| | - Kaiwen Xu
- College of Biosystems Engineering and Food Science, Zhejiang University, 866 Yuhangtang Road, Hangzhou 310058, China.
| | - Jie Xu
- College of Biological Chemical Science and Engineering, Jiaxing University, Jiaxing 314001, China.
| | - Juanjuan Jin
- College of Biosystems Engineering and Food Science, Zhejiang University, 866 Yuhangtang Road, Hangzhou 310058, China.
| | - Hui Fang
- College of Biosystems Engineering and Food Science, Zhejiang University, 866 Yuhangtang Road, Hangzhou 310058, China.
| | - Yong He
- College of Biosystems Engineering and Food Science, Zhejiang University, 866 Yuhangtang Road, Hangzhou 310058, China.
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Comparison of grating-based near-infrared (NIR) and Fourier transform mid-infrared (ATR-FT/MIR) spectroscopy based on spectral preprocessing and wavelength selection for the determination of crude protein and moisture content in wheat. Food Control 2017. [DOI: 10.1016/j.foodcont.2017.06.015] [Citation(s) in RCA: 66] [Impact Index Per Article: 9.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
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Sensitive Wavelengths Selection in Identification of Ophiopogon japonicus Based on Near-Infrared Hyperspectral Imaging Technology. Int J Anal Chem 2017; 2017:6018769. [PMID: 28932243 PMCID: PMC5592010 DOI: 10.1155/2017/6018769] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2017] [Accepted: 05/29/2017] [Indexed: 11/23/2022] Open
Abstract
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.
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Determination and Visualization of Peimine and Peiminine Content in Fritillaria thunbergii Bulbi Treated by Sulfur Fumigation Using Hyperspectral Imaging with Chemometrics. Molecules 2017; 22:molecules22091402. [PMID: 28832506 PMCID: PMC6151643 DOI: 10.3390/molecules22091402] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2017] [Revised: 08/21/2017] [Accepted: 08/21/2017] [Indexed: 12/11/2022] Open
Abstract
Rapid, non-destructive, and accurate quantitative determination of the effective components in traditional Chinese medicine (TCM) is required by industries, planters, and regulators. In this study, near-infrared hyperspectral imaging was applied for determining the peimine and peiminine content in Fritillaria thunbergii bulbi under sulfur fumigation. Spectral data were extracted from the hyperspectral images. High-performance liquid chromatography (HPLC) was conducted to determine the reference peimine and peiminine content. The successive projection algorithm (SPA), weighted regression coefficient (Bw), competitive adaptive reweighted sampling (CARS), and random frog (RF) were used to select optimal wavelengths, while the partial least squares (PLS), least-square support vector machine (LS–SVM) and extreme learning machine (ELM) were used to build regression models. Regression models using the full spectra and optimal wavelengths obtained satisfactory results with the correlation coefficient of calibration (rc), cross-validation (rcv) and prediction (rp) of most models being over 0.8. Prediction maps of peimine and peiminine content in Fritillaria thunbergii bulbi were formed by applying regression models to the hyperspectral images. The overall results indicated that hyperspectral imaging combined with regression models and optimal wavelength selection methods were effective in determining peimine and peiminine content in Fritillaria thunbergii bulbi, which will help in the development of an online detection system for real-world quality control of Fritillaria thunbergii bulbi under sulfur fumigation.
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Xu JL, Riccioli C, Sun DW. Development of an alternative technique for rapid and accurate determination of fish caloric density based on hyperspectral imaging. J FOOD ENG 2016. [DOI: 10.1016/j.jfoodeng.2016.06.007] [Citation(s) in RCA: 62] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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Qu JH, Cheng JH, Sun DW, Pu H, Wang QJ, Ma J. Discrimination of shelled shrimp (Metapenaeus ensis) among fresh, frozen-thawed and cold-stored by hyperspectral imaging technique. Lebensm Wiss Technol 2015. [DOI: 10.1016/j.lwt.2015.01.018] [Citation(s) in RCA: 37] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
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Rapid Measurement of Antioxidant Activity and γ-Aminobutyric Acid Content of Chinese Rice Wine by Fourier-Transform Near Infrared Spectroscopy. FOOD ANAL METHOD 2015. [DOI: 10.1007/s12161-015-0144-4] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
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12
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Towards improvement in classification of Escherichia coli, Listeria innocua and their strains in isolated systems based on chemometric analysis of visible and near-infrared spectroscopic data. J FOOD ENG 2015. [DOI: 10.1016/j.jfoodeng.2014.09.016] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
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Wu Z, Xu E, Wang F, Long J, Jiao XXA, Jin Z. Rapid Determination of Process Variables of Chinese Rice Wine Using FT-NIR Spectroscopy and Efficient Wavelengths Selection Methods. FOOD ANAL METHOD 2014. [DOI: 10.1007/s12161-014-0021-6] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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