Journal of Near Infrared Spectroscopy最新文献

{"title":"A chemometric method for the viability analysis of spinach seeds by near infrared spectroscopy with variable selection using successive projections algorithm","authors":"M. K. Lakshmanan, B. Boelt, R. Gislum","doi":"10.1177/09670335221138955","DOIUrl":"https://doi.org/10.1177/09670335221138955","url":null,"abstract":"This paper proposes a chemometric method for evaluating the viability of spinach seeds using near infrared (NIR) spectroscopy and successive projections algorithms (SPA). An essential step of the procedure is to apply the SPA to optimize the choice of variables for multivariate classification. Variable selection using SPA has been described as an optimization problem in which a cost function is minimized. Selecting the correct variables makes the chemometric models more complete, precise, accurate, and less complex. The NIR spectra were processed using the Savitzky-Golay and multiplicative scatter correction techniques. After that, the best wavelength subset was selected using SPA. Different classification techniques are then applied to the dimension-reduced data to determine the seeds’ viability. The results show that the proposed method is less complex compared to existing canonical variance methods (1.7% miscalculation error in the proposed way) and is also easier to implement.","PeriodicalId":16551,"journal":{"name":"Journal of Near Infrared Spectroscopy","volume":null,"pages":null},"PeriodicalIF":1.8,"publicationDate":"2022-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47554785","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":"Predicting sugarcane quality using a portable visible near infrared spectrometer and a benchtop near infrared spectrometer","authors":"Kittipon Aparatana, Yumika Naomasa, Morito Sano, Kenta Watanabe, Muneshi Mitsuoka, M. Ueno, Y. Kawamitsu, E. Taira","doi":"10.1177/09670335221136545","DOIUrl":"https://doi.org/10.1177/09670335221136545","url":null,"abstract":"Sugar quality (Brix and Pol) is the key index to evaluate the value of sugarcane. Hence, a rapid, accurate, and time-efficient method is needed to determine the sugar quality. This study develops a two-point sugarcane quality model that uses a benchtop near infrared (NIR) spectrometer and a portable visible–near infrared (Vis-NIR) spectrometer to measure the sugarcane juice and stalk spectra, respectively. GT two experiments for developing a two-point sugarcane quality model. In the first, a model to calibrate the sugar quality as measured by a polarimeter and refractometer, and also by the benchtop NIR spectrometer. In the second, we developed a model to calibrate the sugar quality predicted from the calibration model developed in the first experiment, by measuring the sugarcane stalk absorption spectra using a portable Vis-NIR spectrometer. The results of the first experiment showed that the standard normal variate (SNV) spectral pretreatment was the most effective method for Brix calibration, with a coefficient of determination of prediction ( r p 2 ) of 0.99 and root mean square error of prediction (RMSEP) of 0.2%. In the case of Pol, second derivatives were the best spectral pretreatment for effective calibration (r2 = 0.99, RMSEP = 0.3%). The results of the second experiment showed that the multiple linear regression model developed using the stalk spectra with the second derivative was the best model for Brix calibration (r2 = 0.70, RMSEP = 1.4%). The second derivative with the SNV pretreatment was best for Pol calibration (r2 = 0.70, RMSEP = 1.4%). Our study showed that a sugar quality regression model can be developed for a portable Vis-NIR spectrometer using the data from the sugar quality predicted by a benchtop NIR spectrometer.","PeriodicalId":16551,"journal":{"name":"Journal of Near Infrared Spectroscopy","volume":null,"pages":null},"PeriodicalIF":1.8,"publicationDate":"2022-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44162868","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 diffuse reflectance portable near infrared spectroscopy system for the determination of biuret content in urea fertilizer","authors":"Jing Liu, Sha Yu, Shupeng Hu, Ziyang Ling, Jiguang Gao, Binmei Liu, Lixiang Yu, Yang Yang, Ye Yang, Qi Wang, Xiaoyu Ni, Liping Zhao, Yuejin Wu","doi":"10.1177/09670335221136546","DOIUrl":"https://doi.org/10.1177/09670335221136546","url":null,"abstract":"Simple, rapid, and reliable determination of the biuret content in urea fertilizer is very important for the development of fertilizer industry. A near infrared diffuse reflectance measurement system with a portable spectrometer was developed, in which the reference and dark background spectrum could also be recorded automatically in addition to the absorbance data. The key performances of the proposed NIR system have been tested on urea fertilizer. Numerical experiments showed that the coefficient of determination (R2) of the external validation set was 0.97, with a root mean square error (RMSE) of 0.04%. The ratios of the performance deviation (RPD) value in the calibration and validation sets were 12 and 3.5, respectively. It can be concluded that this NIR system for the determination of biuret content in urea fertilizer may potentially be used as an alternative method to traditional wet chemical methods due to its simplicity, sensitivity, and portability.","PeriodicalId":16551,"journal":{"name":"Journal of Near Infrared Spectroscopy","volume":null,"pages":null},"PeriodicalIF":1.8,"publicationDate":"2022-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43956830","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":"Design of a miniaturized frequency domain near infrared spectrometer with validation in solid phantoms and human tissue","authors":"Alper Kılıç, Yun Miao, V. Koomson","doi":"10.1177/09670335221134206","DOIUrl":"https://doi.org/10.1177/09670335221134206","url":null,"abstract":"Hemoglobin is one of the most important chromophores in the human body, since oxygen is carried to the tissue by binding with the hemoglobin. Therefore measuring the concentrations of oxy-hemoglobin (HbO) and deoxy-hemoglobin (HbR) is very important in both clinical settings and academic fields. Frequency domain near infrared spectroscopy (fdNIR spectroscopy) is a technique that can be used to measure the absolute concentrations of HbO and HbR non-invasively and locally. The fdNIR spectrometer utilizes the attenuation and the phase shift (with respect to the source) that an intensity modulated NIR light experiences in order to calculate the absorption (μa) and reduced scattering (μ′s) coefficient of the tissue. In this work, a miniaturized dual-wavelength fdNIR spectrometry instrument is presented with both tissue-like phantom and in vivo occlusion measurements. Systematic tests were performed on tissue phantoms to quantify the accuracy and stability of the instrument. The absolute errors for μa and μ′s were below 15% respectively. The amplitude and phase uncertainty were below 0.25% and 0.35°. In vivo measurements were also conducted to further validate the system.","PeriodicalId":16551,"journal":{"name":"Journal of Near Infrared Spectroscopy","volume":null,"pages":null},"PeriodicalIF":1.8,"publicationDate":"2022-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45327653","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":"Rapid recognition of different sources of methamphetamine drugs based on hand-held near infrared spectroscopy and multi-layer-extreme learning machine algorithms","authors":"Jianqiang Zhang, Jun Yang, Jin Chen, Junxun Hu, Shuangyan Yang","doi":"10.1177/09670335221130433","DOIUrl":"https://doi.org/10.1177/09670335221130433","url":null,"abstract":"The rapid recognition of the sources of the drugs can provide valuable clues and provide the basis for determining the nature of a drug case. Here, a novel recognition method was put forward to identify the source of methamphetamine drugs rapidly and non-destructively by using a hand-held near infrared (NIR) spectrometer and a multi-layer-extreme learning machine (ML-ELM) algorithm. The accuracy, precision, sensitivity, and F-score were higher with the proposed ML-ELM algorithm than in traditional linear discriminant analysis (LDA), extreme learning machine (ELM) classification, and partial least squares (PLS) regression algorithms. The prediction accuracy of ML-ELM algorithm is 25.0%, 15.3% and 18.1% higher than that of LDA, ELM and PLS regression, respectively. The ML-ELM models for recognizing the different sources of methamphetamine drugs had the best generalization ability and prediction results. The experimental results indicated that the combination of hand-held NIR technology and ML-ELM algorithm can recognize the different sources of methamphetamine drugs rapidly, accurately, and non-destructively.","PeriodicalId":16551,"journal":{"name":"Journal of Near Infrared Spectroscopy","volume":null,"pages":null},"PeriodicalIF":1.8,"publicationDate":"2022-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42134503","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":"Before reliable near infrared spectroscopic analysis - the critical sampling proviso. Part 1: Generalised theory of sampling","authors":"K. Esbensen, N. Abu-Khalaf","doi":"10.1177/09670335221124612","DOIUrl":"https://doi.org/10.1177/09670335221124612","url":null,"abstract":"Non-representative sampling of materials, lots and processes intended for near infrared (NIR) analysis is often contributing hidden additions to the full Measurement Uncertainty (MUtotal = TSE + TAENIR). The Total Sampling Error (TSE) can dominate over the Total Analytical Error (TAENIR) by factors ranging from 5 to 10 to even 25 times, depending on material heterogeneity and the specific sampling procedures employed to produce the minuscule aliquot, which is the only material analysed. This review (Parts 1 and 2), extensively referenced with easily available complementing literature, presents a brief of all sampling uncertainty elements in the “lot-to-aliquot” pathway, which must be identified and correctly managed (eliminated or maximally reduced) in order to achieve, and to be able to document, fully minimised MUtotal. The more irregular and pervasive the heterogeneity, the higher the number of increments needed to reach ‘fit-for-purpose representativity’. A particular focus is necessary regarding the sampling bias, which is fundamentally different from the well-known analytical bias. Whereas the latter can easily be subjected to bias correction, the sampling bias is non-correctable by any posteori means, notably not by chemometrics, nor statistics. Instead, all sampling operations must be designed to exclude the so-called Incorrect Sampling Errors (ISE), which are the hidden bias-generating agents. The key element in this endeavour is representative sampling and sub-sampling before analysis, as laid out by the Theory of Sampling (TOS), which is presented here in a novel compact fashion along with a complement of selected examples and demonstrations. TOS includes a safeguard facility, termed the Replication Experiment (RE), which enables estimation of the total sampling-plus-analysis uncertainty level (MUtotal) associated with NIR analysis (the RE is, for practical and logistical reasons, found in Part 2). Neglecting the TSE effects from the before-analysis domain is lack of due diligence. TOS to the fore!","PeriodicalId":16551,"journal":{"name":"Journal of Near Infrared Spectroscopy","volume":null,"pages":null},"PeriodicalIF":1.8,"publicationDate":"2022-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46015330","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":"Monitoring the physical state of wood during multiple tensile load-unload cycles by the eigenvalue distribution of near infrared spectra","authors":"T. Fujimoto","doi":"10.1177/09670335221130469","DOIUrl":"https://doi.org/10.1177/09670335221130469","url":null,"abstract":"Wood is a typical viscoelastic material that shows a clear mechanical hysteresis loop during cyclic loading, which implies the irreversibility of the process and is important for the processing and long-term utility of wood. Changes in the physical state of wood were examined during multiple tensile load-unload cycles based on the eigenvalue distribution of the near-infrared spectra. The set of eigenvalues H = {λ1, λ2, …, λ n }, calculated from the spectral matrix successively acquired during the cycling test, was treated as the Hamiltonian, which represents the energy eigenstate of the wood. Using statistical physics and random matrix theory, the variation in the physical state of wood was discussed from both macroscopic and microscopic perspectives. Unlike traditional methods, the energy state of wood can be followed in real time during cyclic loading; in other words, the Helmholtz free energy and Shannon entropy varied with load changes. The commutator, defined by the density and diagonal matrix of H, could be used to quantitatively evaluate the irreversible changes in wood during the cyclic processes. The proposed method is independent of a specific coordinate system, and can therefore be applied using a wide variety of chemical information other than that obtained from the near-infrared spectra.","PeriodicalId":16551,"journal":{"name":"Journal of Near Infrared Spectroscopy","volume":null,"pages":null},"PeriodicalIF":1.8,"publicationDate":"2022-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47858930","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":"Near infrared spectroscopy for blend uniformity monitoring: An innovative qualitative application based on the coefficient of determination","authors":"Y. Roggo, Lizbeth Martínez, A. Peinado, S. Matero","doi":"10.1177/09670335221130430","DOIUrl":"https://doi.org/10.1177/09670335221130430","url":null,"abstract":"Blending process is a critical unit operation in the pharmaceutical industry during the solid dosage form production. Near infrared (NIR) spectroscopy is a powerful analytical tool to assess the blend homogeneity in real-time. In this paper, a new methodology for blending process monitoring and for end point confirmation is proposed. Quantitative procedure validation and maintenance of NIR procedures are time-consuming activities that can prevent the adoption of PAT tools in the pharmaceutical industry. Clearly, there is a need in the industry for simpler and more intuitive qualitative blend monitoring analytical procedure that are easy to build, validate and maintain. The method introduced herein consists of tracking the trend of the Coefficient of Determination (CD) between a mean reference spectrum from a homogeneous batch and the NIR spectra that are recorded during the blending operation. Four formulations of commercial products were selected from different scales–including low dosage solid form-to show the usefulness of the method. In addition, this analytical procedure is tested with data from two different types of spectrometers (diode array instruments). Method calibration was performed with five batches (representing expected process variability) for each product: one for the computation of the homogeneous batch target spectrum and four to compute the limit of the CD values related to anticipated and acceptable homogeneity. Method validation was performed with homogeneous batches and with challenge spectra for assessing the specificity of the method. Real-world examples (e.g. technical, validation batches and clinical batches) were presented in order to demonstrate that this method is able to detect inhomogeneous batches. The new qualitative method presented in this paper is useful for determination of the blending endpoint, in assessing the blend uniformity in real-time and in increasing process understanding during early development and troubleshooting. Graphical Abstract","PeriodicalId":16551,"journal":{"name":"Journal of Near Infrared Spectroscopy","volume":null,"pages":null},"PeriodicalIF":1.8,"publicationDate":"2022-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43235771","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":"Before reliable near infrared spectroscopic analysis - the critical sampling proviso. Part 2: Particular requirements for near infrared spectroscopy","authors":"K. Esbensen, N. Abu-Khalaf","doi":"10.1177/09670335221124611","DOIUrl":"https://doi.org/10.1177/09670335221124611","url":null,"abstract":"Non-representative sampling of materials, lots and processes intended for NIR analysis is often fraught with hidden contributions to the full Measurement Uncertainty MUtotal = TSE + TAENIR. The Total Sampling Error (TSE) can dominate over the Total Analytical Error TAENIR by factors of 5 to 10 to even 25 times, depending on the degree of material heterogeneity and the specific sampling procedures employed to produce the minuscule aliquot, which is the only material actually analysed. Part 1 presented a brief of all sampling uncertainty elements in the “lot-to-aliquot” pathway, which must be identified and correctly managed (eliminated or reduced maximally), especially the sampling bias, as a prerequisite to achieve fully representative sampling. The key for this is the Theory of Sampling (TOS), which is presented in two parts in a novel compact fashion. Part 2 introduces (i) application of TOS to process sampling, specifically addressing and illustrating how this manifests itself in the realm of PAT, Process Analytical Technology, and (ii) an empirical safeguard facility, termed the Replication Experiment (RE), with which to estimate the effective sampling-plus-analysis uncertainty level (MUtotal) associated with NIR analysis. The RE is a defence against compromising the analytical responsibilities. Ignorance, either caused by lack of awareness or training, or by wilful neglect, of the demand for TSE minimisation, is a breach of due diligence concerning analysis QC/QA. Part 2 ends with a special focus on: “What does all this TOS mean specifically for NIR analysis?”. The answer to this question will perhaps surprise many. There is nothing special that need worrying NIR analysts relative to professionals from all other analytical modalities; all that is needed is embedded in the general TOS framework. Still, this review concludes by answering a set of typical concerns from NIR practitioners.","PeriodicalId":16551,"journal":{"name":"Journal of Near Infrared Spectroscopy","volume":null,"pages":null},"PeriodicalIF":1.8,"publicationDate":"2022-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45834818","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":"Test of a light emitting diode fully integrated pre-prototype spectrometer for rapid evaluation of table tomato (Solanum lycopersicum L., Marinda F1) quality","authors":"A. Tugnolo, A. Pampuri, V. Giovenzana, A. Casson, R. Guidetti, R. Beghi","doi":"10.1177/09670335221119721","DOIUrl":"https://doi.org/10.1177/09670335221119721","url":null,"abstract":"The present research aims to evaluate the performance of an optical pre-prototype based on light emitting diode, (450–860 nm) to quantify table tomatoes’ quality features in a rapid and non-destructive way (Solanum lycopersicum L., Marinda F1). A total of 200 samples were analysed. Calibration of the pure near infrared (NIR, 960–1650 nm) and visible/near infrared (VIS/NIR, 400–1000 nm) commercial spectrometers to estimate the main tomato quality parameters, i.e. moisture content (MC) and total soluble solids (TSS), was performed by using PLS regression. Since no substantial differences were highlighted between the two commercial devices, to reduce the complexity while keeping the performance of the model using the whole spectra (1647 variables for VIS/NIR), a cost-effective pre-prototype was designed and built by using 12 bands in the VIS/NIR optical range. The pre-prototype shows slightly lower performance, resulting in RMSEP values of 2% and 1.45 °Brix for MC and TSS respectively, compared to RMSEP values of 1% and 1.19 °Brix for the VIS/NIR device (using the entire spectrum). Moreover, no significant differences at 95% were highlighted by using Passing-Bablok regression. In conclusion, the pre-prototype performance can be considered sufficiently accurate to allow an initial field screening of the trend of the analysed parameters (MC and TSS) using a new generation of simplified optical sensors.","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":"44983282","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}