Rapid detection of the component contents in caryophylli flos by a handheld near infrared spectrometer based on digital light processing technology

2018 ◽  
Vol 26 (6) ◽  
pp. 389-397
Author(s):  
Hui Yan ◽  
Yue Ma ◽  
Bangxing Han
Keyword(s):  
Standard Error ◽  
Near Infrared ◽  
Processing Technology ◽  
Quantitative Detection ◽  
Least Squares Regression ◽  
Digital Light Processing ◽  
Standard Normal Variate ◽  
Eugenyl Acetate ◽  
Infrared Spectrometer ◽  
Near Infrared Spectrometer

A handheld and inexpensive near infrared spectrometer based on digital light processing technology was used to investigate the potential of fast quantitative detection of eugenol, beta-caryophyllene and eugenyl acetate in caryophylli flos. Gas chromatography was used to determine the reference values. The diffuse reflectance spectra of caryophylli flos powder were recorded and were pretreated by different methods, and then the partial least squares regression was applied to develop calibration models; furthermore, the competitive adaptive reweighted sampling was used for the wavelength selection to improve the performance of models. The results show that the best performance of the pretreatment methods is seen with the combination of the first derivative and standard normal variate, and the performance of calibration is improved by the competitive adaptive reweighted sampling. For the eugenol, the standard error of calibration and standard error of prediction are 0.46% and 0.60%, respectively, and the corresponding R-squares are 0.955 and 0.89; for beta-caryophyllene, the standard error of calibration and standard error of prediction are 0.11% and 0.14%, respectively, and the corresponding R-squares are 0.89 and 0.86; for eugenyl acetate, the standard error of calibration and standard error of prediction are 0.30% and 0.38%, respectively, and the corresponding R-squares are 0.89 and 0.80. The overall results of this work revealed the feasibility of the use of handheld near infrared spectrometers as a method for the quantitative on-site determination of eugenol, beta-caryophyllene and eugenyl acetate in caryophylli flos.

Investigating the total antioxidant capacity of gluten-free grains with miniaturized near-infrared spectrometer

NIR news ◽  
2019 ◽  
Vol 30 (5-6) ◽  
pp. 35-38
Author(s):  
Verena Wiedemair ◽  
Christian Wolfgang Huck
Keyword(s):  
Antioxidant Capacity ◽  
Total Antioxidant Capacity ◽  
High Performance ◽  
Near Infrared ◽  
Least Squares Regression ◽  
Test Set ◽  
Total Antioxidant ◽  
Infrared Spectrometer ◽  
Near Infrared Spectrometer ◽  
Infrared Instruments

The use of ever smaller near-infrared instruments is becoming more and more prevalent, since they are cheaper, more versatile and often advertised as high-performance spectrometer. The last claim is rarely verified by independent researchers, which is why the presented work evaluates the performance of three hand-held spectrometers in comparison to a benchtop instrument. Seventy-seven samples comprising buckwheat, millet and oat were investigated for their total antioxidant capacity using Folin–Ciocalteu and near-infrared spectroscopy. Partial least squares regression models were established using cross- and test set validation. Results showed that all instruments were able to predict total antioxidant capacity to some extent. The coefficients of determinations ranged from 0.823 to 0.951 for cross-validated and from 0.849 to 0.952 for test set validated models. Errors for cross-validated models ranged from 1.11 to 2.08 mgGAE/g and for test set validated models from 1.02 to 1.86 mgGAE/g.

scholarly journals Investigations into the Performance of a Novel Pocket-Sized Near-Infrared Spectrometer for Cheese Analysis

Molecules ◽  
2019 ◽  
Vol 24 (3) ◽  
pp. 428 ◽  
Author(s):  
Verena Wiedemair ◽  
Dominik Langore ◽  
Roman Garsleitner ◽  
Klaus Dillinger ◽  
Christian Huck
Keyword(s):  
Data Analysis ◽  
Partial Least Squares Regression ◽  
Near Infrared ◽  
Coefficient Of Determination ◽  
Least Squares Regression ◽  
Analysis Software ◽  
Infrared Spectrometer ◽  
Automated Tools ◽  
Near Infrared Spectrometer ◽  
Data Analysis Software

The performance of a newly developed pocket-sized near-infrared (NIR) spectrometer was investigated by analysing 46 cheese samples for their water and fat content, and comparing results with a benchtop NIR device. Additionally, the automated data analysis of the pocket-sized spectrometer and its cloud-based data analysis software, designed for laypeople, was put to the test by comparing performances to a highly sophisticated multivariate data analysis software. All developed partial least squares regression (PLS-R) models yield a coefficient of determination (R2) of over 0.9, indicating high correlation between spectra and reference data for both spectrometers and all data analysis routes taken. In general, the analysis of grated cheese yields better results than whole pieces of cheese. Additionally, the ratios of performance to deviation (RPDs) and standard errors of prediction (SEPs) suggest that the performance of the pocket-sized spectrometer is comparable to the benchtop device. Small improvements are observable, when using sophisticated data analysis software, instead of automated tools.

Identification of geographical origin of TPFD based on handheld NIR spectroscopy and PLSDA

NIR news ◽  
2020 ◽  
Vol 31 (5-6) ◽  
pp. 25-29
Author(s):  
Rita-Cindy Aye-Ayire Sedjoah ◽  
Bangxing Han ◽  
Hui Yan
Keyword(s):  
Quality Control ◽  
Near Infrared ◽  
Geographical Origin ◽  
Nir Spectroscopy ◽  
Analysis Model ◽  
First Order ◽  
Standard Normal Variate ◽  
Standard Normal ◽  
Infrared Spectrometer ◽  
Near Infrared Spectrometer

The present study is focused on the identification of geographical origin (Zhejiang, Yunnan and Anhui, China) of Dendrobium officinale’s dried stem called Tiepi fengdou by mean of the handheld near-infrared spectrometer. Raw data were preprocessed to reduce unwanted spectral variations by the first-order derivative followed by standard normal variate transformation, and partial least squares discriminant analysis model was developed for calibration. The results showed that more than 90% of the origins were identified. Therefore, it is possible to classify the geographical origin of Tiepi fengdou by the use of the handheld near-infrared spectrometer for effective quality control.

Calibration transfer across near infrared spectrometers for measuring hematocrit in the blood of grazing cattle

2017 ◽  
Vol 25 (1) ◽  
pp. 15-25 ◽  
Author(s):  
Xuan Luo ◽  
Akifumi Ikehata ◽  
Kunio Sashida ◽  
Shanji Piao ◽  
Tsutomu Okura ◽  
...  
Keyword(s):  
Latent Variables ◽  
Near Infrared ◽  
Least Squares Regression ◽  
Calibration Transfer ◽  
Grazing Cattle ◽  
Robust Model ◽  
Infrared Spectrometer ◽  
Near Infrared Spectrometer ◽  
Direct Standardization

For fast diagnosis of anemia for cattle farmed on pastures, portable short wavelength near infrared spectrometer instrument was built, and the feasibility of estimating hematocrit by partial least squares regression modeling was validated in our previous work. As a follow-up, the present study reports calibration transfer from one master instrument to two slave instruments. Different approaches, i.e. making robust models, skew and bias correction, and piecewise direct standardization, were compared. Our results show that making more use of simple models based on appropriate preprocessing, number of latent variables, and wavelength selection, can sometimes be as effective as applying standardization algorithm (e.g. piecewise direct standardization) when tackling the spectral differences between instruments. The importance of a robust model during the process of calibration transfer is shown. Application of standardization such as piecewise direct standardization could be risky when the model to be transferred is not robust enough.

scholarly journals Prediksi Indeks Panen Jambu “Kristal” secara Non Destruktif Menggunakan Portable Near Infrared Spectrometer

2021 ◽  
Vol 9 (3) ◽  
pp. 103-110
Author(s):  
Ayu Putri Ana ◽  
Y. Aris Purwanto ◽  
Slamet Widodo
Keyword(s):  
Standard Error ◽  
Near Infrared ◽  
Quality Parameters ◽  
Solid Content ◽  
Partial Least Square ◽  
Least Square ◽  
Soluble Solid Content ◽  
Soluble Solid ◽  
Infrared Spectrometer ◽  
Near Infrared Spectrometer

“Crystal” guava (Psidium guajava L.) is a climacteric fruit that is generally harvested by farmers based on cultivation experience. In this study, portable 740-1070 nm of near-infrared spectrometer was employed to rapidly predict harvest indices of “crystal” guava, by means of non-contact and non-destructive approach. Samples of guava fruit were collected at days after anthesis (DAS) of 91, 94, 97, and 100. The total number of each sample were 30 fruits. The firmness, soluble solid content, acidity and sugar acid ration were evaluated as quality parameters. Partial least square (PLS) method was utilized for data processing. It was found that Standard Normal Variate (SNV) resulted the best pre-processing for all quality parameters. Performances of best models were demonstrated by coefficient of corraltion (R), standard error of calibration (SEC) and standard error of prediction (SEP), which were respectively 0.88, 6.21, 5.92 for firmness prediction, 0.74, 0.84, 0.79 for soluble solid content prediction, 0.59, 0.19, 0.26 for acidity prediction, and 0.71, 1.21, 1.58 for sugar acid ratio prediction model.

Use of a handheld near infrared spectrometer and partial least squares regression to quantify metanil yellow adulteration in turmeric powder

2020 ◽  
Vol 28 (2) ◽  
pp. 81-92 ◽  
Author(s):  
Isaac R Rukundo ◽  
Mary-Grace C Danao ◽  
Curtis L Weller ◽  
Randy L Wehling ◽  
Kent M Eskridge
Keyword(s):  
Least Squares ◽  
Partial Least Squares ◽  
Partial Least Squares Regression ◽  
Near Infrared ◽  
Prediction Performance ◽  
Least Squares Regression ◽  
Calibration Models ◽  
Infrared Spectrometer ◽  
Metanil Yellow ◽  
Near Infrared Spectrometer

The efficacy of using a handheld near infrared spectrometer to predict metanil yellow (MY) adulteration levels (0-30% w/w) in dried turmeric powder was tested against a benchtop near infrared spectrometer using partial least squares regression models. The differences between near infrared instruments were resolution (i.e., 1 nm (handheld) vs. 0.5 nm (benchtop)) and sample container during scanning (plastic pouch (handheld) vs. quartz glass cup (benchtop)). Prediction performance of the calibration models developed was evaluated using number of model factors ([Formula: see text]), coefficients of determination of calibration and validation ([Formula: see text] and[Formula: see text], respectively), root-mean-square errors of calibration, cross-validation, and validation (RMSEC, RMSECV, and RMSEP), ratio of prediction error to standard deviation (RPD), and limits of detection (LOD) and quantification (LOQ). The best benchtop calibration models were based on spectral data preprocessed with Savitzky–Golay first derivative algorithm for the benchtop near infrared and standard normal variate for the handheld near infrared, yielding low[Formula: see text], high [Formula: see text] and[Formula: see text], low RMSEC, RMSECV, RMSEP, and high RPD. The LOD and LOQ for both spectrometers were 0.33 and 1.10%, respectively, and no significant difference was found between the predicted [Formula: see text] values by the benchtop and handheld near infrared spectrometers. The models were, in general, not sensitive to sample source and size of the validation set. When spectra from the benchtop near infrared were standardized using a reverse standardization strategy, calibrated against[Formula: see text], and transferred to the handheld near infrared, prediction performance dropped, from [Formula: see text] of 0.99 to 0.98, RMSEP increased from 0.96% to 1.53%, and [Formula: see text] decreased from 10.1 to 6.3. Despite the reduced prediction performance, the handheld near infrared with a transferred calibration model from the benchtop near infrared was still useful for screening, quality control, and process control applications.

scholarly journals The Improvement on the Performance of DMD Hadamard Transform Near-Infrared Spectrometer by Double Filter Strategy and a New Hadamard Mask

Micromachines ◽  
2019 ◽  
Vol 10 (2) ◽  
pp. 149 ◽  
Author(s):  
Zifeng Lu ◽  
Jinghang Zhang ◽  
Hua Liu ◽  
Jialin Xu ◽  
Jinhuan Li
Keyword(s):  
Near Infrared ◽  
Signal To Noise Ratio ◽  
Nonuniform Distribution ◽  
Stray Light ◽  
Spectral Energy ◽  
Hadamard Transform ◽  
Digital Micromirror Device ◽  
Infrared Spectrometer ◽  
Near Infrared Spectrometer ◽  
The Impact

In the Hadamard transform (HT) near-infrared (NIR) spectrometer, there are defects that can create a nonuniform distribution of spectral energy, significantly influencing the absorbance of the whole spectrum, generating stray light, and making the signal-to-noise ratio (SNR) of the spectrum inconsistent. To address this issue and improve the performance of the digital micromirror device (DMD) Hadamard transform near-infrared spectrometer, a split waveband scan mode is proposed to mitigate the impact of the stray light, and a new Hadamard mask of variable-width stripes is put forward to improve the SNR of the spectrometer. The results of the simulations and experiments indicate that by the new scan mode and Hadamard mask, the influence of stray light is restrained and reduced. In addition, the SNR of the spectrometer also is increased.

A Compact Near-Infrared Spectrometer based on an FR4 Electromagnetic Scanning Grating

2021 ◽  
Author(s):  
Russell Farrugia ◽  
Barnaby Portelli ◽  
Ivan Grech ◽  
Joseph Micallef ◽  
Owen Casha ◽  
...  
Keyword(s):  
Near Infrared ◽  
Electromagnetic Scanning ◽  
Infrared Spectrometer ◽  
Near Infrared Spectrometer
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