Accuracy and stability improvement for meat species identification using multiplicative scatter correction and laser-induced breakdown spectroscopy

Chu, Yan; Tang, Shisong; Xiang, Shi; Yu, Yang; Hao, Zhongqi; Guo, Yang Min; Guo, Lian Bo; Lu, Yong Feng; Zeng, Xianlin

doi:10.1364/oe.26.010119

Cited by 63 publications

(26 citation statements)

References 22 publications

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“…The MSC, SNV and PMSC transforms are capable of correcting multiplicative effects introduced by light scattering from different sized particles . Among them, the MSC transform assumes that the scatter for each spectrum is a linear deviation from a reference spectrum in a dataset . The SNV transform has equivalent results to the MSC transforms, and the main difference between them is that the application of the SNV transform does not need a reference spectrum .…”

Section: Methodsmentioning

confidence: 99%

Rapid quantitative analysis of adulterated rice with partial least squares regression using hyperspectral imaging system

Guo

et al. 2019

J Sci Food Agric

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BACKGROUND: Rice adulteration in the food industry that infringes on the interests of consumers is considered very serious. To realize the rapid and precise quantitation of adulterated rice, a visible near infrared (VNIR) hyperspectral imaging system (380-1000 nm) was developed in the present study. A Savitsky-Golay first derivative (SG1) transform was utilized to eliminate the constant spectral baseline offset. Then, the adulterated levels of rice samples were quantified by partial least squares regression (PLSR). RESULTS:A SG1-PLSR model based on full-wavelength was attained with a coefficient of determination of prediction set (R P ) of 0.9909, root-mean-square error of prediction set (RMSE P ) of 0.0447 g kg −1 and residual predictive deviation (RPD P ) of 11.28. Furthermore, fifteen important wavelengths were selected based on the weighted regression coefficients (B W ) and a simplified model (PLSR-15) was established with R P of 0.9769, RMSE P of 0.0708 g kg −1 and RPD P of 3.49. Finally, two visualization maps produced by applying the optimal models (SG1-PLSR and PLSR-15) were used to visualize the adulterated levels of rice.CONCLUSION: These results demonstrate that VNIR hyperspectral imaging system is an effective tool for rapidly quantifying and visualizing the adulterated levels of rice.

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Section: Methodsmentioning

confidence: 99%

Rapid quantitative analysis of adulterated rice with partial least squares regression using hyperspectral imaging system

Guo

et al. 2019

J Sci Food Agric

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“…K-nearest neighbor (KNN) calculates the distance between the sample and the remaining samples, selects k samples from the nearest distance, then classifies the samples into the category with the largest proportion, and finally achieves the classification of the samples [30].…”

Section: Methodsmentioning

confidence: 99%

“…Compared with traditional detection methods, LIBS technique has the advantages of fast analysis speed, little sample preparation, and simultaneous analysis of multiple elements [21,25]. By analyzing the spectral signal emitted from laser plasma, LIBS has been widely used in the quantitative and qualitative analysis of plant materials [21,25,27,28,29], animal tissue [24,30], mineral resources [31,32], industrial application [33] and so on. The previous studies provide a basis for LIBS to be applied in the authenticity identification of Chinese medicine.…”

Section: Introductionmentioning

confidence: 99%

Rapid Identification of Kudzu Powder of Different Origins Using Laser-Induced Breakdown Spectroscopy

Liu

Wang

Shen

et al. 2019

Sensors

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The rapid identification of kudzu powder of different origins is of great significance for studying the authenticity identification of Chinese medicine. The feasibility of rapidly identifying kudzu powder origin was investigated based on laser-induced breakdown spectroscopy (LIBS) technology combined with chemometrics methods. The discriminant models based on the full spectrum include extreme learning machine (ELM), soft independent modeling of class analogy (SIMCA), K-nearest neighbor (KNN) and random forest (RF), and the accuracy of models was more than 99.00%. The prediction results of KNN and RF models were best: the accuracy of calibration and prediction sets of kudzu powder from different producing areas both reached 100%. The characteristic wavelengths were selected using principal component analysis (PCA) loadings. The accuracy of calibration set and the prediction set of discrimination models, based on characteristic wavelengths, is all higher than 98.00%. Random forest and KNN have the same excellent identification results, and the accuracy of calibration and prediction sets of kudzu powder from different producing areas reached 100%. Compared with the full spectrum discriminant analysis model, the discriminant analysis model based on the characteristic wavelength had almost the same discriminant effects, and the input variables were reduced by 99.92%. The results of this research show that the characteristic wavelength can be used instead of the LIBS full spectrum to quickly identify kudzu powder from different producing areas, which had the advantages of reducing input, simplifying the model, increasing the speed and improving the model effect. Therefore, LIBS technology is an effective method for rapid identification of kudzu powder from different habitats. This study provides a basis for LIBS to be applied in the genuineness and authenticity identification of Chinese medicine.

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“…Sezer et al 188 used LIBS for the identication and quantication of LiNa, a toxic salt substitute in meatballs, demonstrating a limit of detection for Li of about 4.5 ppm. Bilge et al 189 and Chu et al 190 used LIBS for the identication of different meat species; Velioglu et al 191 exploited these results for the identication of possible offal adulteration in beef. A similar analysis was done by Casado-Gavalda et al 192 using copper content in beef as a possible indicator of offal adulteration.…”

Section: Food and Feed Industrymentioning

confidence: 99%

Industrial applications of laser-induced breakdown spectroscopy: a review

et al. 2020

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Accuracy and stability improvement for meat species identification using multiplicative scatter correction and laser-induced breakdown spectroscopy

Cited by 63 publications

References 22 publications

Rapid quantitative analysis of adulterated rice with partial least squares regression using hyperspectral imaging system

Rapid quantitative analysis of adulterated rice with partial least squares regression using hyperspectral imaging system

Rapid Identification of Kudzu Powder of Different Origins Using Laser-Induced Breakdown Spectroscopy

Industrial applications of laser-induced breakdown spectroscopy: a review

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