Local Strategy Combined with a Wavelength Selection Method for Multivariate Calibration

Chang, Haitao; Zhu, Lianqing; Lou, Xiaoping; Meng, Xiaochen; Guo, Yangkuan; Wang, Zhongyu

doi:10.3390/s16060827

Cited by 4 publications

(3 citation statements)

References 24 publications

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“…Although PLS and PCR address some of the issues that rise from the large p , small n nature of spectroscopic data, it has been shown that the inclusion of uninformative wavelengths in the training process negatively affects the accuracy of predictions as well as model interpretability [19][20][21][22]43 . Moreover, from a more practical point of view, the identification of the specific wavelengths, or regions of the optical spectrum, that contain information about chemical species, significantly reduces the time and cost associated with monitoring them and facilitates the development of portable, high-speed sensors.…”

Section: Wavelength Selectionmentioning

confidence: 99%

Comparison of wavelength selection methods for in-vitro estimation of lactate: a new unconstrained, genetic algorithm-based wavelength selection

Mamouei

Budidha

Baishya

et al. 2020

Sci Rep

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Biochemical and medical literature establish lactate as a fundamental biomarker that can shed light on the energy consumption dynamics of the body at cellular and physiological levels. It is therefore, not surprising that it has been linked to many critical conditions ranging from the morbidity and mortality of critically ill patients to the diagnosis and prognosis of acute ischemic stroke, septic shock, lung injuries, insulin resistance in diabetic patients, and cancer. Currently, the gold standard for the measurement of lactate requires blood sampling. The invasive and costly nature of this procedure severely limits its application outside intensive care units. Optical sensors can provide a non-invasive, inexpensive, easy-to-use, continuous alternative to blood sampling. Previous efforts to achieve this have shown significant potential, but have been inconclusive. A measure that has been previously overlooked in this context, is the use of variable selection methods to identify regions of the optical spectrum that are most sensitive to and representative of the concentration of lactate. In this study, several wavelength selection methods are investigated and a new genetic algorithm-based wavelength selection method is proposed. This study shows that the development of more accurate and parsimonious models for optical estimation of lactate is possible. Unlike many existing methods, the proposed method does not impose additional locality constraints on the spectral features and therefore helps provide a much more granular interpretation of wavelength importance.

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Section: Wavelength Selectionmentioning

confidence: 99%

Comparison of wavelength selection methods for in-vitro estimation of lactate: a new unconstrained, genetic algorithm-based wavelength selection

Mamouei

Budidha

Baishya

et al. 2020

Sci Rep

View full text Add to dashboard Cite

show abstract

“…The optimal wavelength selection offers two clear benefits. Firstly, it has been shown that the inclusion of uninformative wavelengths in the training process negatively affects the accuracy of predictions and model interpretability [ 48 , 49 ]. Secondly, from a more practical point of view, the identification of a few wavelengths, or regions of the optical spectrum, that contain information about chemical species, significantly reduces the time and cost associated with their measurement and enables the development of portable and high-speed optical sensors.…”

Section: Resultsmentioning

confidence: 99%

Ultraviolet Spectroscopic Detection of Nitrate and Nitrite in Seawater Simultaneously Based on Partial Least Squares

Wang

2021

Molecules

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A direct, reagent-free, ultraviolet spectroscopic method for the simultaneous determination of nitrate (NO3−), nitrite (NO2−), and salinity in seawater is presented. The method is based on measuring the absorption spectra of the raw seawater range of 200–300 nm, combined with partial least squares (PLS) regression for resolving the spectral overlapping of NO3−, NO2−, and sea salt (or salinity). The interference from chromophoric dissolved organic matter (CDOM) UV absorbance was reduced according to its exponential relationship between 275 and 295 nm. The results of the cross-validation of calibration and the prediction sets were used to select the number of factors (4 for NO3−, NO2−, and salinity) and to optimize the wavelength range (215–240 nm) with a 1 nm wavelength interval. The linear relationship between the predicted and the actual values of NO3−, NO2−, salinity, and the recovery of spiked water samples suggest that the proposed PLS model can be a valuable alternative method to the wet chemical methods. Due to its simplicity and fast response, the proposed PLS model can be used as an algorithm for building nitrate and nitrite sensors. The comparison study of PLS and a classic least squares (CLS) model shows both PLS and CLS can give satisfactory results for predicting NO3− and salinity. However, for NO2− in some samples, PLS is superior to CLS, which may be due to the interference from unknown substances not included in the CLS algorithm. The proposed method was applied to the analysis of NO3−, NO2−, and salinity in the Changjiang (Yangtze River) estuary water samples and the results are comparable with that determined by the colorimetric Griess assay.

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“…Reducing dimensions and seeking the most informative wavelengths are effective methods for processing data while selecting the most informative wavelengths of target information is an effective measure to simplify computation and improve the model performance (Li et al, 2019 ; Zhou et al, 2020 ). First, it has been shown that the inclusion of uninformative wavelengths while modeling affects the performance of predicting or classifying and model interpretability (Chang et al, 2016 ). Second, the identification of wavelengths that contain information about the attribute the research focuses on, will reduce the computation time and cost, from a more practical point of view (Zhang et al, 2019 ; Mamouei et al, 2020 ).…”

Section: Introductionmentioning

confidence: 99%

Soluble Solids Content Binary Classification of Miyagawa Satsuma in Chongming Island Based on Near Infrared Spectroscopy

et al. 2022

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Citrus is one of the most important fruits in China. Miyagawa Satsuma, one kind of citrus, is a nutritious agricultural product with regional characteristics of Chongming Island. Near-infrared Spectroscopy (NIR) is a proper method for studying the quality of fruits, because it is low-cost, efficient, non-destructive, and repeatable. Therefore, the NIR technique is used to detect citrus's soluble solid content (SSC) in this study. After obtaining the original spectral data, the first 70% of them are divided into the training set and 30% into the test set. Then, the Random Frog algorithm is chosen to select characteristic wavelengths, which reduces the dimension of the data and the complexity of the model, and accordingly makes the generalization of the classification model better. After comparing the performance of various classifiers (AdaBoost, KNN, LS-SVM, and Bayes) under different characteristic wavelength numbers, the AdaBoost classifier outperforms using 275 characteristic wavelengths for modeling eventually. The accuracy, precision, recall, and F1-score are 78.3%, 80.5%, 78.3%, and 0.780, respectively and the ROC (Receiver Operating Characteristic Curve, ROC curve) is close to the upper left corner, suggesting that the classification model is acceptable. The results demonstrate that it is feasible to use the NIR technique to estimate whether the citrus is sweet or not. Furthermore, it is beneficial for us to apply the obtained models for identifying the quality of citrus correctly. For fruit traders, the model helps them to determine the growth cycle of citrus more scientifically, improve the level of citrus cultivation and management and the final fruit quality, and thus increase the economic income of fruit traders.

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Local Strategy Combined with a Wavelength Selection Method for Multivariate Calibration

Cited by 4 publications

References 24 publications

Comparison of wavelength selection methods for in-vitro estimation of lactate: a new unconstrained, genetic algorithm-based wavelength selection

Comparison of wavelength selection methods for in-vitro estimation of lactate: a new unconstrained, genetic algorithm-based wavelength selection

Ultraviolet Spectroscopic Detection of Nitrate and Nitrite in Seawater Simultaneously Based on Partial Least Squares

Soluble Solids Content Binary Classification of Miyagawa Satsuma in Chongming Island Based on Near Infrared Spectroscopy

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