Journal of Near Infrared Spectroscopy最新文献

{"title":"Multivariate calibration strategy in simultaneous determination of temperature properties of petroleum diesel by near infrared spectrometry","authors":"A. R. Othman, S. Zain, K. Low","doi":"10.1177/09670335221130425","DOIUrl":"https://doi.org/10.1177/09670335221130425","url":null,"abstract":"It is essential to control the quality of diesel products so that they comply with relevant fuel specifications, however, the quality assessments rely upon conventional wet chemical analyses that are costly and time consuming. Rapid, simultaneous quality measurement enabling immediate online optimisation for process control and blending offers tremendous cost savings by minimising product quality give-away, shipment demurrage, tank inventory, and laboratory analysis. In this study, the use of near infrared spectroscopy and chemometrics demonstrates a straightforward workflow for simultaneous determination of the petroleum diesel’s boiling point at 95% recovery (T95), flash point (FP), cloud point (CP), and cetane index (CI) calibration development. It involved appropriate spectral region selection, calibration/validation set partition, data pre-processing, regression modelling and validation. Based on the calibration and validation results, the supervised learning models that are obtained from a combination region of 4000–4800 cm−1 on a randomly selected calibration set managed to deliver promising predictive performance in terms of coefficient of determination for prediction (r2P/T95 ≥ 0.94, r2P/FP ≥ 0.89, r2P/CP ≥ 0.89, r2P/CI ≥ 0.993), root mean square error of prediction (RMSEP (T95) ≤ 5.2°C, RMSEP (FP) ≤ 2.0°C, RMSEP (CP) ≤ 2.4°C, RMSEP (CI) ≤ 0.3), and ratio of performance deviation (RPD (T95) ≥ 3.7, RPD (FP) ≥ 3.0, RPD (CP) ≥ 2.9, RPD (CI) ≥ 11). Regardless of principal component regression or partial least square regression on either the multiplicative scattering corrected spectra or Savitzky-Golay second derivative spectra, the developed models met respective ASTM reproducibility requirements, and were considered adequate for immediate quality assessment of diesel.","PeriodicalId":16551,"journal":{"name":"Journal of Near Infrared Spectroscopy","volume":null,"pages":null},"PeriodicalIF":1.8,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42269278","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A useful quantitative model for determining the optical purity of praziquantel enantiomers based on near infrared spectroscopy with partial least squares","authors":"Fei Teng, Jianbo Ji, Yue Yang, Haina Wang","doi":"10.1177/09670335221130428","DOIUrl":"https://doi.org/10.1177/09670335221130428","url":null,"abstract":"In this study, a new method was developed for the determination of praziquantel (PZQ) enantiomers in solution. Praziquantel, as a highly effective and low-toxic broad-spectrum antiparasitic drug developed in the 1970s, is the first choice for the etiology of schistosomiasis treatment recommended by the World Health Organization. It is by far the most effective anti-schistosomiasis drug. PZQ is a chiral drug with a chiral carbon atom and two enantiomers, of which R-PZQ is the main contributor of the anti-schistosome effect. The quantitative model was established based on near infrared (NIR) spectroscopy combined with the partial least square (PLS) method. Using sucrose as a chiral selector, the collected spectral information was processed by the second derivative and Savitzky-Golay smoothing filter, and comprehensively analyzed in the two bands of 1816.9–1884.3 nm and 1405.3–1425.4 nm to establish a good PLS regression model. Internal cross-validation of the model was carried out. In principle, the enantiomeric excess could be determined as low as 1.33%. The mole fraction of S-PZQ determined by HPLC was used as a reference method, and three batches of samples from the same manufacturer were used for independent external validation with an error of ± 4%. The results showed that this quantitative model could be used to determine the enantiomer content of the chiral drug PZQ. It realized the rapid and sensitive analysis of PZQ tablets and provided a new strategy for the quality analysis of chiral drugs.","PeriodicalId":16551,"journal":{"name":"Journal of Near Infrared Spectroscopy","volume":null,"pages":null},"PeriodicalIF":1.8,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48405989","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Non-destructive evaluation of strength and stiffness of Eucalyptus pellita. A comparison of near infrared spectroscopy and acoustic wave velocity assessment","authors":"Y. Japarudin, R. Meder, M. Lapammu, A. Alwi, Mark Brown","doi":"10.1177/09670335221117301","DOIUrl":"https://doi.org/10.1177/09670335221117301","url":null,"abstract":"Tree improvement programmes benefit from measured data for multiple phenotypes in order to potentially gain maximum genetic leverage for selection. Diameter at breast height, tree height and tree form have traditionally dominated the measured phenotype due to their ease of measurement, and the fact that logs are traded by volume. More complex traits, including those that potentially offer economic benefit in terms of quality and end-product performance such as strength and stiffness, are more difficult to measure in standing trees and are frequently overlooked. These traits are therefore in need of rapid methods of assessment. Tree improvement of Eucalyptus pellita in Malaysian Borneo for solid wood and veneer product utilisation is one such example of where selection for improved stiffness is desirable. Genetic trials of E. pellita were assessed using acoustic velocity measurements at several intervention points, including the standing tree, fallen stem, logs and boards, along with near infrared spectroscopic measurement of the final test samples. Calibrations were developed for modulus of elasticity (MOE), modulus of rupture (MOR) and compression parallel to the grain, using reference values obtained from 3-point bending of small clearwood test samples obtained from the trees following felling and sawing to ensure back-to-log recovery of the test sample location. Dynamic MOE calculated from the standing tree acoustic velocity showed good correlation with the mean MOE from static bending for the wood in the butt log, representing the location where standing tree acoustic velocity measurements were obtained. The Savitzky-Golay second derivative pre-treatment yields the best performing calibration for the microNIR and MPA on ground wood for MOE (R2Cal = 0.76, r2CV = 0.80, r2Pred = 0.46, RMSEC and RMSECV = 1.4 GPa, RMSEP = 2.3 GPa, LV = 3) for the microNIR and R2Cal = 0.98, r2CV and r2Pred = 0.70, RMSEC = 0.5 GPa, RMSECV and RMSEP =1.5 GPa, LV = 4 for the MPA.","PeriodicalId":16551,"journal":{"name":"Journal of Near Infrared Spectroscopy","volume":null,"pages":null},"PeriodicalIF":1.8,"publicationDate":"2022-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42254548","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Discrimination of Gonipterini weevil genera using near infrared spectroscopy","authors":"Joel B. Johnson","doi":"10.1177/09670335221117300","DOIUrl":"https://doi.org/10.1177/09670335221117300","url":null,"abstract":"This proof-of-concept study aimed to investigate the potential of using near infrared (NIR) spectroscopy to discriminate between genera of Gonipterini weevil. NIR spectra (10,000–4,000 cm−1) were collected from 15 Gonipterini specimens, comprising three genera and five species. Principal component analysis (PCA) highlighted the inter-specific variation in NIR spectra, with separation observed between most species across the first two principal components. Partial least squares discriminant analysis (PLS-DA) could be used to differentiate between the genera (78% accuracy), although support vector machine (SVM) modelling gave improved accuracy (91%). The results support the prospect of NIR spectroscopy for the rapid discrimination between Gonipterini genera.","PeriodicalId":16551,"journal":{"name":"Journal of Near Infrared Spectroscopy","volume":null,"pages":null},"PeriodicalIF":1.8,"publicationDate":"2022-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42774182","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Transfer of a calibration model for the prediction of lignin in pulpwood among four portable near infrared spectrometers","authors":"Xiaoxue Zhang, Xinyu Chen, Zhi-xin Xiong, H. Siesler, Long Liang","doi":"10.1177/09670335221110013","DOIUrl":"https://doi.org/10.1177/09670335221110013","url":null,"abstract":"In order to reduce the time and cost for near infrared (NIR) model development and maintenance, the transfer of NIR spectra measured on four different portable spectrometers (one master and three target instruments) for predicting the lignin content of pulp wood is investigated in this work. Eighty-two wood samples were prepared by chipping and grinding, and their NIR spectra were recorded with four spectrometers. Calibration models for the determination of lignin in pulp wood have been developed by partial least squares (PLS) regression, while average Mahalanobis distances (AMD) and average differences of spectra (ADS) were used to quantify the spectral differences. Then piecewise direct standardization (PDS) has been applied, and compared to direct standardization (DS), slope/bias correction (SBC) and canonical correlation analysis (CCA). The accuracy of the models has been evaluated by comparing their prediction performance. The results indicated that the prediction performances of the three target instruments are greatly improved by using the three algorithms. The advantage of the PDS algorithm is that fewer samples are required for the transfer sets, which means lower model maintenance cost for practical applications. When it comes to window size setting procedure, it was found that if there are large spectral differences between the master and the target spectrometer, a large window size should be used and if the spectral difference is a significant lateral shift, an asymmetric window with appropriate window size is necessary to ensure a good transfer performance for the PDS algorithm.","PeriodicalId":16551,"journal":{"name":"Journal of Near Infrared Spectroscopy","volume":null,"pages":null},"PeriodicalIF":1.8,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46226095","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Determination of ash content in silicon dioxide filled epoxy-phenolic prepreg using near infrared spectroscopy","authors":"Yi-Hui Wu, Dan Li","doi":"10.1177/09670335221110011","DOIUrl":"https://doi.org/10.1177/09670335221110011","url":null,"abstract":"This paper presents an application of near infrared spectroscopy associated with partial least squares regression calibration, for ash content analysis of prepreg in the manufacturing progress of copper clad laminate for printed circuited boards. The performance of the model was assessed by cross validation and external validation. The correlation coefficient and the root mean squared error of calibration and validation were 0.99, 0.25% and 0.98, 0.34%, and the measurement process was accomplished in less than 2 min compared to over 60 min for traditional thermo gravimetric analyzsis. The paired t-test results revealed that there was no significant difference between the two methods.","PeriodicalId":16551,"journal":{"name":"Journal of Near Infrared Spectroscopy","volume":null,"pages":null},"PeriodicalIF":1.8,"publicationDate":"2022-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48840265","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Use of wavelength interaction terms to improve near infrared spectroscopy models of donkey milk properties","authors":"G. Altieri, Mahdi Rashvand, O. Mammadov, Attilio Matera, Francesco Genovese, G. C. Di Renzo","doi":"10.1177/09670335221097004","DOIUrl":"https://doi.org/10.1177/09670335221097004","url":null,"abstract":"Ranchers are continuously searching for suitable tools to rapidly and inexpensively assess the characteristics of donkey milk and because spectroscopic models are useful to assess the composition of many foods, an attempt to further improve the prediction performance of donkey milk protein, lactose and dry-matter content has been made using three widely used spectroscopic models by adding some interaction terms, namely product, ratio, sum and difference of absorbances for each couple of wavelengths. Principal component regression using product terms showed an improvement in prediction error achieving 1.8%, 1.7% and 0.9% for protein, lactose and dry-matter content respectively. Furthermore, the added ratio terms showed a very great improvement in the predictive overall performance achieving 0.3%, 0.4% and 0.2%. A coefficient has been found relating the widely used RPD, a standard index of prediction performance, to the new proposed “range of confident prediction error percent” being a more understandable parameter to assess the goodness of the prediction model.","PeriodicalId":16551,"journal":{"name":"Journal of Near Infrared Spectroscopy","volume":null,"pages":null},"PeriodicalIF":1.8,"publicationDate":"2022-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45647602","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Metaheuristic algorithms in visible and near infrared spectra to detect excess nitrogen content in tomato plants","authors":"Raziyeh Pourdarbani, S. Sabzi, M. Rohban, G. García-Mateos, J. Molina-Martínez, J. Paliwal, J. I. Arribas","doi":"10.1177/09670335221098527","DOIUrl":"https://doi.org/10.1177/09670335221098527","url":null,"abstract":"Chemical fertilizers are widely applied in agriculture to achieve high yield, enhance produce quality and build resistance to diseases; in our case the plant being tomato (Solanum lycopersicum L. var. Royal). However, the acidity, size and taste of tomato fruits could change with excess nitrogen (N) application. The present study aims at the early detection of nitrogen-rich tomato leaves using hyperspectral imaging techniques in the visible and near infrared (Vis-NIR) spectrum, in order to improve plant nutrition composition at an early growth stage. A 30% over-dose of nitrogen was applied to half of the tomato pots. Five leaves were randomly collected from each pot for 3 days (classes D0, D1, D2 and D3), and images were captured with a hyperspectral camera. A metaheuristic approach of artificial neural networks and the firefly algorithm (ANN-FA) was used to determine the most discriminative wavelengths. Afterwards, a combination of ANN and particle swarm optimization (ANN-PSO) was used to classify tomato leaves into the four classes. The training/classification process was repeated 200 times, and results indicated that the proposed approach was able to detect the excess of nitrogen even at the first day (D1), with a precision of 92.9%. Considering all the classes, the average correct classification rate was 92.6%, while the best execution achieved 95.5% accuracy. Thus, the method showed a high performance for practical uses.","PeriodicalId":16551,"journal":{"name":"Journal of Near Infrared Spectroscopy","volume":null,"pages":null},"PeriodicalIF":1.8,"publicationDate":"2022-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42961842","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Fourier transform near infrared spectroscopy as a tool to predict spawning status in Alaskan fishes with variable reproductive strategies","authors":"T. TenBrink, Sandra K. Neidetcher, Morgan B. Arrington, I. Benson, C. Conrath, T. Helser","doi":"10.1177/09670335221097005","DOIUrl":"https://doi.org/10.1177/09670335221097005","url":null,"abstract":"Fourier-transform near infrared (FT-NIR) spectroscopy of ovarian tissue was used to predict maturity status of fish species with variable reproductive strategies collected at limited time periods of their spawning cycle. Reference data were derived from histologically prepared tissue samples from four species: Pacific cod (Gadus macrocephalus), walleye pollock (Gadus chalcogrammus), Greenland turbot (Reinhardtius hippoglossoides), and northern rockfish (Sebastes polyspinis). Each data set was classified into reproductively immature (non-spawning) and reproductively mature (spawning-capable) categories. Principal component analysis of spectral data showed separation between ovarian tissues of spawning-capable and non-spawning females. Multivariate classification using partial least squares discriminant analysis indicated good discrimination based on spawning status with high predictive accuracy. Greenland turbot and northern rockfish showed clear distinction between ovaries of spawning-capable and non-spawning females and a model validation with 100% and 96.6% classification accuracy, respectively. Pacific cod and walleye pollock had more complicated reproductive patterns at time of collection and classification rates were still 96.6% and 92.1%. This study demonstrated the potential application of FT-NIR spectroscopy to predict spawning status from ovarian tissue even for species with complicated spawning patterns and for collections outside of the preferred spawning period. Future work may include the use of this technology to classify distinct oocyte development stages.","PeriodicalId":16551,"journal":{"name":"Journal of Near Infrared Spectroscopy","volume":null,"pages":null},"PeriodicalIF":1.8,"publicationDate":"2022-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48508591","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Performance evaluation of variable selection methods coupled with partial least squares regression to determine the target component in solid samples","authors":"Na Zhao, Zhisheng Wu, Chunying Wu, Shuyu Wang, Xueyan Zhan","doi":"10.1177/09670335221097236","DOIUrl":"https://doi.org/10.1177/09670335221097236","url":null,"abstract":"Variable selection can improve the robustness and prediction accuracy of partial least squares (PLS) regression models and decrease the calculation time by selecting the optimal subset of variables in multivariate calibration. In this study, the performance of two variable selection methods for wavelength interval and individual wavelength coupled with partial least squares regression are investigated by employing the experimental data of asiaticoside (AS) and madecassoside (MS) contents in centella total glucosides (CTG) and a public dataset of corn. The studied variable selection methods include interval partial least squares regression (iPLS), backward interval partial least squares (biPLS), synergy interval partial least squares regression (siPLS), competitive adaptive reweighted sampling (CARS), uninformative variable elimination (UVE) and variable importance in projection (VIP). The results show that the implementation of variable selection methods improved the performance of the model compared with full-spectrum modeling. All variable selection methods improved the prediction of AS or MS contents in CTG. When latent variables for PLS models are less than 10 in the practical application, the RPD value of AS models by iPLS method is 7.5, and the RPD value of MS models by biPLS method is 2.9. The results of wavelength interval selection are better than individual wavelength selection, especially for iPLS and biPLS. The same results were obtained with the public data for moisture in corn, and the RPD value of biPLS model of moisture is 1.6. Therefore, the wavelength interval selection methods, such as iPLS or biPLS, are appropriate for improving the PLS model’s accuracy and robustness to determine the target components’ contents in solid samples. Graphical Abstract","PeriodicalId":16551,"journal":{"name":"Journal of Near Infrared Spectroscopy","volume":null,"pages":null},"PeriodicalIF":1.8,"publicationDate":"2022-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42611250","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}