Near infrared spectroscopy coupled chemometric algorithms for prediction of the antioxidant activity of peanut seed (Arachis hypogaea)

2021 ◽  
pp. 096703352097942
Author(s):  
Muhammad Bilal ◽  
Zou Xiaobo ◽  
Muhmmad Arslan ◽  
Haroon Elrasheid Tahir ◽  
Yue Sun ◽  
...  
Keyword(s):  
Near Infrared ◽  
Cross Validation ◽  
Rapid Assessment ◽  
Research Work ◽  
Antioxidant Properties ◽  
Correlation Coefficients ◽  
Nir Spectroscopy ◽  
Peanut Seed ◽  
Chemometric Algorithms ◽  
Selection Algorithms

In the present research work, near infrared (NIR) spectroscopy coupled with chemometric algorithms such as partial least-squares (PLS) regression and some effective variable selection algorithms (synergy interval-PLS (Si-PLS), Backward interval-PLS (Bi-PLS), and genetic algorithm-PLS (GA-PLS)) were used for the quantification of antioxidant properties of peanut seed samples. The compositional parameters, such as DPPH, ABTS, FRAP, TPC, FCA, TFC, and TAC, were quantified using NIR spectroscopy. The developed models were assessed using correlation coefficients of the calibration (R2) and prediction (r2); root mean standard error of cross-validation, RMSECV; root mean square error of prediction, RMSEP and residual predictive deviation, RPD. The efficiency of the developed model was significantly enhanced with the use of Si-PLS, Bi-PLS, and GA-PLS as compared to the classical PLS model. The results of the R2 and r2 set varied from 0.76 to 0.95 and 0.72 to 0.94, respectively. The obtained results revealed that NIR spectroscopy, coupled with different chemometric algorithms, has the potential to be used for rapid assessment of the antioxidant properties of peanut seed.

scholarly journals Use of FT-NIR Spectroscopy for Bovine Colostrum Analysis

2006 ◽  
Vol 75 (1) ◽  
pp. 57-63 ◽  
Author(s):  
P. Navrátilová ◽  
L. Hadra ◽  
M. Dračková ◽  
B. Janštová ◽  
L. Vorlová ◽  
...  
Keyword(s):  
Fourier Transformation ◽  
Near Infrared ◽  
Cross Validation ◽  
Correlation Coefficients ◽  
Nir Spectroscopy ◽  
Bovine Colostrum ◽  
Total Solids ◽  
Calibration Models ◽  
Spectral Ranges ◽  
Pls Method

Fourier transformation near infrared spectroscopy (FT-NIR) in combination with partial least squares (PLS) method were used to determine the content of total solids, fat, non-fatty solids, lactose and proteins in bovine colostrum. Spectra of 90 samples were measured in the reflectance mode with a transflectance cuvette in the 10000-4000 cm-1 spectral ranges with 100 scans. Calibration was performed and statistical values of correlation coefficients (R) and standard error of calibration values (SEC) were computed for total solids (0.986 and 0.919, respectively), fat (0.997 and 0.285, respectively), non-fatty solids (0.995 and 0.451, respectively), lactose (0.934 and 0.285, respectively) and protein (0.999 and 0.149, respectively). The calibration models developed were verified by cross validation. It follows from the study that FT-NIR spectroscopy can be used to determine the components of bovine colostrum.

scholarly journals Feasibility of Using VIS/NIR Spectroscopy and Multivariate Analysis for Pesticide Residue Detection in Tomatoes

Processes ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 196
Author(s):  
Araz Soltani Nazarloo ◽  
Vali Rasooli Sharabiani ◽  
Yousef Abbaspour Gilandeh ◽  
Ebrahim Taghinezhad ◽  
Mariusz Szymanek ◽  
...  
Keyword(s):  
Near Infrared ◽  
Cross Validation ◽  
Low Cost ◽  
Moving Average ◽  
Nir Spectroscopy ◽  
Control Treatment ◽  
Residue Detection ◽  
Non Destructive ◽  
Reflective Spectroscopy

The purpose of this work was to investigate the detection of the pesticide residual (profenofos) in tomatoes by using visible/near-infrared spectroscopy. Therefore, the experiments were performed on 180 tomato samples with different percentages of profenofos pesticide (higher and lower values than the maximum residual limit (MRL)) as compared to the control (no pesticide). VIS/near infrared (NIR) spectral data from pesticide solution and non-pesticide tomato samples (used as control treatment) impregnated with different concentrations of pesticide in the range of 400 to 1050 nm were recorded by a spectrometer. For classification of tomatoes with pesticide content at lower and higher levels of MRL as healthy and unhealthy samples, we used different spectral pre-processing methods with partial least squares discriminant analysis (PLS-DA) models. The Smoothing Moving Average pre-processing method with the standard error of cross validation (SECV) = 4.2767 was selected as the best model for this study. In addition, in the calibration and prediction sets, the percentages of total correctly classified samples were 90 and 91.66%, respectively. Therefore, it can be concluded that reflective spectroscopy (VIS/NIR) can be used as a non-destructive, low-cost, and rapid technique to control the health of tomatoes impregnated with profenofos pesticide.

Rapid Determination of Heartwood Extractives in Larix sp. by Means of Fourier Transform near Infrared Spectroscopy

2002 ◽  
Vol 10 (3) ◽  
pp. 203-214 ◽  
Author(s):  
N. Gierlinger ◽  
M. Schwanninger ◽  
B. Hinterstoisser ◽  
R. Wimmer
Keyword(s):  
Fourier Transform ◽  
Near Infrared ◽  
Cross Validation ◽  
Nir Spectroscopy ◽  
Solid Wood ◽  
Hot Water ◽  
Extractive Content ◽  
Fast Method ◽  
Wood Powder ◽  
Test Set

The feasibility of Fourier transform near infrared (FT-NIR) spectroscopy to rapidly determine extractive and phenolic content in heartwood of larch trees ( Larix decidua MILL., L. leptolepis (LAMB.) CARR. and the hybrid L. x eurolepis) was investigated. FT-NIR spectra were collected from wood powder and solid wood using a fibre-optic probe. Partial Least Squares (PLS) regression analyses were carried out describing relationships between the data sets of wet laboratory chemical data and the FT-NIR spectra. Besides cross and test set validation the established models were subjected to a further evaluation step by means of additional wood samples with unknown extractive content. Extractive and phenol contents of these additional samples were predicted and outliers detected through Mahalanobis distance calculations. Models based on the whole spectral range and without data pre-processing performed well in cross-validation and test set validation, but failed in the evaluation test, which is based on spectral outlier detection. But selection of data pre-processing methods and manual as well as automatic restriction of wavenumber ranges considerably improved the model predictability. High coefficients of determination ( R2) and low root mean square errors of cross-validation ( RMSECV) were obtained for hot water extractives ( R2 = 0.96, RMSECV = 0.86%, range = 4.9–20.4%), acetone extractives ( R2 = 0.86, RMSECV = 0.32%, range = 0.8–3.6%) and phenolic substances ( R2 = 0.98, RMSECV = 0.21%, range = 0.7–4.9%) from wood powder. The models derived from wood powder spectra were more precise than those obtained from solid wood strips. Overall, NIR spectroscopy has proven to be an easy to facilitate, reliable, accurate and fast method for non-destructive wood extractive determination.

scholarly journals Application of FT near spectroscopy for determination of true protein and casein in milk

2008 ◽  
Vol 52 (No. 9) ◽  
pp. 284-291 ◽  
Author(s):  
K. Šustová ◽  
J. Růžičková ◽  
J. Kuchtík
Keyword(s):  
Cross Validation ◽  
Reference Data ◽  
Correlation Coefficients ◽  
Nir Spectroscopy ◽  
Rapid Analysis ◽  
Validation Method ◽  
Goat’S Milk ◽  
Goat's Milk ◽  
True Protein

Our study deals with a possibility of determining true protein and casein in cow’s, ewe’s and goat’s milk and in ewe’s colostrums by FT NIR spectroscopy. Samples of milk were analysed by FT NIR in the reflectance mode with the transflectance cuvette. The values of correlation coefficients of calibration were as follows: cow’s protein 0.943; cow’s casein 0.964; ewe’s protein 0.997; ewe’s casein 0.977; goat’s protein 0.989; goat’s casein 0.890; ewe’s colostrum protein 0.983. Calibration was tested using the same set of samples by the cross validation method. The values of correlation coefficients of validation were as follows: cow’s protein 0.923; cow’s casein 0.910; ewe’s protein 0.994; ewe’s casein 0.963; goat’s protein 0.972; goat’s casein 0.814; ewe’s colostrum protein 0.871. The NIRS results were compared with reference data and no significant differences between them were found (<i>P</i> = 0.05). Results of this study indicate that FT NIR spectroscopy can be used for a rapid analysis of protein and casein in cow’s, ewe’s and goat’s milk and ewe’s colostrum.

Analysis of Black Wattle (Acacia mearnsii De Wild) Bark by Near Infrared Spectroscopy

Holzforschung ◽  
2003 ◽  
Vol 57 (5) ◽  
pp. 527-532 ◽  
Author(s):  
L. R. Schimleck ◽  
Y. Yazaki
Keyword(s):  
Near Infrared ◽  
Rapid Assessment ◽  
Nir Spectroscopy ◽  
Hot Water ◽  
Soluble Solids ◽  
Tannin Content ◽  
Acacia Mearnsii ◽  
Considerable Potential ◽  
Black Wattle

Summary The analysis of two sets of Acacia mearnsii De Wild (Black Wattle) samples by near infrared (NIR) spectroscopy is reported. Set 1 samples were characterised in terms of hot water extractives, Stiasny value and polyflavanoid content. Set 2 samples were characterised by nine different parameters, including tannin content. NIR spectra were obtained from the milled bark of all samples and calibrations developed for each parameter. Calibrations developed for hot water extractives and polyflavanoid content (set 1) gave very good coefficients of determination (R2) and performed well in prediction. Set 2 calibrations were generally good with total and soluble solids, tannin content, Stiasny value-2 and UV-2, all having R2 greater than 0.8. Owing to the small number of set 2 samples, no predictions were made using the calibrations. The strong relationships obtained for many parameters in this study indicates that NIR spectroscopy has considerable potential for the rapid assessment of the quality of extractives in A. mearnsii bark.

Waveband Selection for NIR Spectroscopic Analysis of Zn2+ in Soil

2013 ◽  
Vol 365-366 ◽  
pp. 737-740
Author(s):  
Li Jun Yao ◽  
Jie Mei Chen ◽  
Tao Pan
Keyword(s):  
Root Mean Square Error ◽  
Near Infrared ◽  
Spectroscopic Analysis ◽  
Correlation Coefficients ◽  
Nir Spectroscopy ◽  
Optimal Number ◽  
Moving Window ◽  
Mean Square ◽  
Selection For

Near-infrared (NIR) spectroscopy combined with moving window partial least squares (MWPLS) method was successfully applied to the waveband selection for the rapid chemical-free determination of Zn2+ in soil. Based on randomness and similarity, an effective approach was performed to obtain objective and practical models. The optimal MWPLS waveband was 1136-1252 nm, and the corresponding optimal number of PLS factors was 6. The validation root mean square error (V-SEP) and validation correlation coefficients (V-RP) of prediction were 15.658 mg kg-1 and 0.925, respectively. The Zn2+ prediction values of the validation samples are close to the measured values. The results provided a reliable NIR model and can serve as valuable references for designing the dedicated spectroscopic instruments.

scholarly journals Analysis of ewe’s milk by FT Near Infrared spectroscopy: measurement of samples on Petri dishes in reflectance mode

2006 ◽  
Vol 54 (2) ◽  
pp. 131-138 ◽  
Author(s):  
Květoslava Šustová ◽  
Jan Kuchtík ◽  
Stanislav Kráčmar
Keyword(s):  
Dry Matter ◽  
Near Infrared ◽  
Correlation Coefficients ◽  
Nir Spectroscopy ◽  
Urea Nitrogen ◽  
Ewe's Milk ◽  
Petri Dishes ◽  
True Protein ◽  
Metallic Mirror

Our work deals with a possibility of determination of basic composition (dry matter, fat, protein, casein, lactose and urea nitrogen) of ewe’s milk and colostrum by FT NIR spectroscopy. Samples of milk were warmed to 40 °C, agitated, cooled to 20 °C, transferred into Petri dishes and analysed by reference methods and by FT NIR in reflectance mode. The measured area was spaced by a metallic mirror. Statistically significant differences between the reference values and the calculated values of NIR were not found (p=0.05). Results of calibration for ewe’s milk determined the highest correlation coefficients: dry matter 0.983, fat 0.989, true protein 0.997, casein 0.977, lactose 0.980 and urea nitrogen 0.973. The study showed that NIRS method, when samples of milk are measured on Petri dishes, is a useful technique for the prediction of dry matter, fat, protein and casein in ewe’s milk.

True Accuracy of near Infrared Spectroscopy and its Dependence on Precision of Reference Data

2002 ◽  
Vol 10 (1) ◽  
pp. 15-25 ◽  
Author(s):  
L.K. Sørensen
Keyword(s):  
Near Infrared ◽  
Cross Validation ◽  
Reference Data ◽  
Nir Spectroscopy ◽  
Limited Resources ◽  
Standard Errors ◽  
Calibration Data ◽  
Pls Regression ◽  
Calibration Equations ◽  
Very High

A more precise estimate of the accuracy of near infrared (NIR) spectroscopy is obtained when the measured standard errors of cross validation ( SECV) and prediction ( SEP) are corrected for imprecision of the reference data. The significance of correction increases with increasing imprecision of reference data. Very high precision of reference data obtained through replicate analyses under reproducibility conditions may not be the optimal goal for the development of calibration equations. In a situation of limited resources, the precision of the reference data should be related to the obtainable accuracy of the spectroscopic system. Investigation of several routine applications based on the partial least-squares (PLS) regression technique showed that increased precision of calibration data only resulted in marginal improvements in true accuracy if the total standard error of reference results from the beginning was less than the estimated true accuracy of the corresponding NIR calibration.

Estimation of Crystallinity of Poplar Cellulose Using Near Infrared Spectroscopy

2012 ◽  
Vol 622-623 ◽  
pp. 1532-1535
Author(s):  
Zhen Bo Liu ◽  
Wen Yang Kong ◽  
Yi Xing Liu ◽  
Zhan Chuan Xue ◽  
Xiao Yan Shen ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Partial Least Squares Regression ◽  
Near Infrared ◽  
Correlation Coefficients ◽  
Nir Spectroscopy ◽  
Wood Properties ◽  
Least Squares Regression ◽  
Cellulose Crystallinity ◽  
Test Models

Many studies have successfully applied near infrared (NIR) spectroscopy to estimate important wood properties. In this paper, the use of NIR (350–2500 nm) spectroscopy to predict the cellulose crystallinity of Poplar (Populus nigra var.) was investigated. The calibration and test models were constructed using partial least squares regression (PLS). The correlations were significant both the calibration and the test samples using six factors, and the correlation coefficients (R2) were 0.9367, 0.9472 respectively. The results suggest that NIR spectroscope may provide a useful tool for rapid and accurate prediction of the cellulose crystallinity of Poplar.

Estimating the Composition of Tomato Juice Products by near Infrared Spectroscopy

2003 ◽  
Vol 11 (2) ◽  
pp. 123-136 ◽  
Author(s):  
Athanasia M. Goula ◽  
Konstantinos G. Adamopoulos
Keyword(s):  
Near Infrared ◽  
Correlation Coefficients ◽  
Nir Spectroscopy ◽  
Tomato Juice ◽  
Calibration Data ◽  
Multilinear Regression ◽  
Statistical Parameters ◽  
Data Set ◽  
Prediction Ability ◽  
Specific Product

The use of near infrared (NIR) reflectance spectroscopy for the rapid and accurate measurement of moisture, sugar, acid, protein and salt was explored in a diverse group of tomato juice products. Partial and overall calibrations were performed on four different tomato juice products. Partial calibrations for each product included samples of the specific product, whereas overall calibration used samples of all the products. Samples were analysed employing traditional chemical methods and scanned using an Instalab 600-Dickey-John NIR apparatus to obtain NIR spectra. Calibrations were achieved with the use of multilinear regression between chemical and spectral data from each calibration data set. A separate set of samples was used to validate the calibrations. Linear regression was applied to compare the results obtained by NIR spectroscopy for all constituents of the validation set with those obtained by the reference methods. In addition, the root mean square error of prediction ( RMSEP), the bias and the correlation coefficients ( r and r′) were calculated. All of the statistical parameters were better with overall than with partial calibrations. Prediction ability of overall calibration was very good for all the constituents. r and r′ values were higher than 0.9488 and 0.9453, respectively, RMSEP values were smaller than 0.1067, whereas bias varied from −0.020 to 0.016. The partial calibrations are considerable less variable with the correlation coefficients r and r′ ranged from 0.8890 to 0.9477 and from 0.7202 to 0.8518, respectively, RMSEP varied from 0.0647 to 0.4942 and bias from −0.365 to 0.071. NIR measurement as performed by the Dickey-John Analyser was proved a rapid and accurate method for analysis of tomato juice samples and may be used as a replacement for conventional expensive and time-consuming wet chemistry methods.

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