Determination of Holocellulose and Alpha-Cellulose Contents in Triploid Clones of Populus tomentosa Using NIRS

2011 ◽  
Vol 675-677 ◽  
pp. 329-332
Author(s):  
Sheng Yao ◽  
Mian Xing ◽  
Yi Fei Jiang ◽  
Guo Feng Wu ◽  
Jun Wen Pu
Keyword(s):  
Correlation Coefficients ◽  
Nir Spectroscopy ◽  
Populus Tomentosa ◽  
Planting Density ◽  
Calibration Models ◽  
Wet Chemical ◽  
Predicted Values ◽  
Mean Square Errors ◽  
Triploid Clones

The aim of this work was to study the ability of NIR spectroscopy to determine holocellulose and alpha-cellulose contents in triploid clones of Populus tomentosa. For this purpose 90 trees with five families in different planting density grown in Shandong were analyzed. Calibration models were developed from wet chemical and NIR data using partial least squares (PLS) regression. High coefficients of determination (R2) and low root mean square errors of cross-validation (RMSECV) were obtained for holocellulose (R2 = 0.7805, RMSECV =0.652) and alpha-cellulose (R2 = 0.8702, RMSECV = 0.548) from wood meal. Prediction produced high correlation coefficients between laboratory and predicted values for holocellulose and alpha-cellulose contents, which R2 values are 0.7467 and 0.8505, and RMSEP are 0.993 and 0.553, respectively. This study showed that NIR analysis can be reliably used to predict holocellulose and alpha-cellulose contents in triploid clones of Populus tomentosa.

scholarly journals Application of FT NIR spectroscopy in the determination of basic chemical composition of pork and beef

2011 ◽  
Vol 51 (No. 8) ◽  
pp. 361-368 ◽  
Author(s):  
J. Mlček ◽  
K. Šustová ◽  
J. Simeonovová
Keyword(s):  
Chemical Composition ◽  
Chemical Analysis ◽  
Cross Validation ◽  
Correlation Coefficients ◽  
Nir Spectroscopy ◽  
Calibration And Validation ◽  
Meat Composition ◽  
Calibration Models ◽  
Predicted Values

The objective of this paper was to determine basic components of pork and beef (fat, protein, water content) using FT NIR spectroscopy. The samples were analysed on an FT NIR Nicolet Antaris device in a reflec-tance regimen. Reference results from classical analyses were used for the calibration of the device. Calibration models were created using PLS algorithm (method of partial least squares) and verified by cross-validation. High correlation coefficients (R) of calibration were calculated (fat 0.998; protein 0.976; water 0.994), and subsequently of validation as well (fat 0.997; protein 0.970; water 0.993) and very low standard deviations of the calibration and validation (SEC, SEP). No statistically significant differences between the reference and predicted values of determination were detected in Z-test. According to the published results, the NIRS method has a high potential to replace an expensive and time demanding chemical analysis of meat composition.  

scholarly journals Pseudo-Univariate Calibration Based on NIR Spectroscopy in the Determination of Anthocyanins and Antioxidant Activity in Grape Juices

2021 ◽  
Author(s):  
Karla Beltrame ◽  
Thays Gonçalves ◽  
Paulo Março ◽  
Sandra Gomes ◽  
Makoto Matsushita ◽  
...  
Keyword(s):  
Antioxidant Activity ◽  
Near Infrared ◽  
Correlation Coefficients ◽  
Nir Spectroscopy ◽  
Grape Juice ◽  
Calibration Models ◽  
Total Anthocyanins ◽  
Alternative Methodology ◽  
Grape Juices

This work shows an alternative methodology based on a portable near-infrared (NIR) spectroscopy coupled to independent components analysis (ICA) in a pseudo-univariate calibration way to determine total anthocyanins (TA) concentration and antioxidant activity (AA) in whole grape juice. To this, the scores proportions more related to TA and AA were plotted against TA and AA obtained by its respective references methodology to build pseudo-univariate calibration models with correlation coefficients of 0.9699 and 0.9814, respectively. From the results, it is possible the suggestion that NIR spectra coupled to ICA enable to overcome interferences using first-order data and work properly when there is enough selectivity for the analyte profile in the sample data.

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.

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.

Comparison of Two Different Approaches toward Model Transferability in NIR Spectroscopy

1998 ◽  
Vol 52 (1) ◽  
pp. 7-16 ◽  
Author(s):  
H. Swierenga ◽  
W. G. Haanstra ◽  
A. P. De Weijer ◽  
L. M. C. Buydens
Keyword(s):  
Ternary Mixture ◽  
Multivariate Calibration ◽  
Nir Spectroscopy ◽  
Data Preprocessing ◽  
Calibration Model ◽  
Model Transferability ◽  
Calibration Models ◽  
Calibration Samples ◽  
Direct Standardization

Recently, efficient methods have become available to transfer a multivariate calibration model from one instrument to another. Two categories can be distinguished: improvement of the robustness of the calibration model by, for example, a proper data preprocessing; and adaptation of the calibration model by, for example, (piecewise) direct standardization. In direct standardization, a subset from the calibration set should be measured on both instruments. Usually, however, the calibration samples cannot be measured on both instruments. When data preprocessing is applied to the transfer of multivariate calibration models, there is no need for remeasurement of a subset on both instruments. In this paper, both categories are compared for the determination of the component concentrations in a ternary mixture of methanol, ethanol, and 1-propanol using NIR spectroscopy. The calibration models obtained on one instrument are transferred to other NIR instruments. It has been found that the results of proper data preprocessing are comparable with the results obtained by direct standardization when the models are transferred over three NIR instruments.

scholarly journals Rapid determination of hyaluronic acid concentration in fermentation broth with near-infrared spectroscopy

2014 ◽  
Vol 07 (06) ◽  
pp. 1450012 ◽  
Author(s):  
Qin Dong ◽  
Hengchang Zang ◽  
Lixuan Zang ◽  
Aihua Liu ◽  
Yanli Shi ◽  
...  
Keyword(s):  
Hyaluronic Acid ◽  
Fermentation Process ◽  
Near Infrared ◽  
Fermentation Broth ◽  
Rapid Determination ◽  
Nir Spectroscopy ◽  
Promising Tool ◽  
Calibration Models ◽  
Order Polynomial

Hyaluronic acid (HA) concentration is an important parameter in fermentation process. Currently, carbazole assay is widely used for HA content determination in routine analysis. However, this method is time-consuming, environment polluting and has the risk of microbial contamination, as well as the results lag behind fermentation process. This paper attempted the feasibility to predict the concentration of HA in fermentation broth by using near infrared (NIR) spectroscopy in transmission mode. In this work, a total of 56 samples of fermentation broth from 7 batches were analyzed, which contained HA in the range of 2.35–9.69 g/L. Different data preprocessing methods were applied to construct calibration models. The final optimal model was obtained with first derivative using Savitzky–Golay smoothing (9 points window, second-order polynomial) and partial least squares (PLS) regression with leave-one-block-out cross validation. The correlation coefficient and Root Mean Square Error of prediction set is 0.98 and 0.43 g/L, respectively, which show the possibility of NIR as a rapid method for microanalysis and to be a promising tool for a rapid assay in HA fermentation.

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.

scholarly journals Nondestructive Prediction of Optimal Harvest Time of Cherry Tomatoes Using VIS-NIR Spectroscopy and PLSR Calibration

2011 ◽  
Vol 1 ◽  
pp. 92-96 ◽  
Author(s):  
Hai Qing Yang
Keyword(s):  
Near Infrared ◽  
Nir Spectroscopy ◽  
Coefficient Of Determination ◽  
Harvest Time ◽  
Least Squares Regression ◽  
Calibration Models ◽  
Optimal Harvest ◽  
Leave One Out

In situ determination of optimal harvest time of tomatoes is of value for growers to optimize fruit picking schedule. This study evaluates the feasibility of using visible and near infrared (VIS-NIR) spectroscopy to make an intact estimation of harvest time of tomatoes. A mobile, fibre-type, AgroSpec VIS-NIR spectrophotometer (Tec5, Germany), with a spectral range of 350-2200 nm, was used for spectral acquisition of tomatoes in reflection mode. The harvest time of tomatoes was measured by the days before harvest. After dividing spectra into a calibration set (70%) and an independent prediction set (30%), spectra in the calibration set were subjected to a partial least-squares regression (PLSR) with leave-one-out cross validation to establish calibration models. Validation of calibration models on the independent prediction set indicates that the best model can produce excellent prediction accuracy with coefficient of determination (R2) of 0.90, root-mean-square error of prediction (RMSEP) of 2.5 days and residual prediction deviation (RPD) of 3.01. It is concluded that VIS-NIR spectroscopy coupled with PLSR models can be adopted successfully for in situ determination of optimal harvest time of tomatoes, which allows for automatic fruit harvest by a horticultural robot.

Analysis of Contaminants in Lubricant Oil by near Infrared Spectroscopy and Interval Partial Least-Squares

2003 ◽  
Vol 11 (3) ◽  
pp. 211-218 ◽  
Author(s):  
Juliana Paschoal ◽  
Fernando D. Barboza ◽  
Ronei J. Poppi
Keyword(s):  
Ethylene Glycol ◽  
Least Squares ◽  
Partial Least Squares ◽  
Near Infrared ◽  
Multivariate Calibration ◽  
Correlation Coefficients ◽  
Full Spectrum ◽  
Lubricant Oil ◽  
Mean Square Errors

The feasibility of using near infrared (NIR) transmission spectroscopy for rapid and conclusive determination of contaminants in lubricant oil was investigated. The NIR spectrum in the region from 1300 to 1700 nm was used to predict gasoline and ethylene glycol concentrations present in lubricant oil. A graphically-oriented local multivariate calibration modelling procedure called interval partial least-squares (iPLS) was applied to find variable intervals that featured the lowest prediction error. When compared with the full spectrum PLS model, better results were obtained through the iPLS program. High correlation coefficients and low root mean square errors of cross-validation ( RMSECV) were obtained for gasoline ( R = 0.98, RMSECV = 0.38%, range = 0.2–8.0% w/w) and ethylene glycol determinations ( R = 0.97, RMSECV = 0.04%, range = 0.06 to 0.7% w/w), indicating that the proposed methodology can be used for contaminant determinations in lubricant oil.

scholarly journals Determination of selected parameters of quality of the dairy products by NIR spectroscopy

2011 ◽  
Vol 24 (No. 6) ◽  
pp. 255-260 ◽  
Author(s):  
J. Růžičková ◽  
K. Šustová
Keyword(s):  
Dairy Products ◽  
Near Infrared ◽  
Correlation Coefficients ◽  
Nir Spectroscopy ◽  
Integrating Sphere ◽  
Calibration Model ◽  
Titrable Acidity ◽  
Non Destructive

The possibility of the application of near-infrared spectroscopy to the analysis of the selected parameters of quality of the dairy products was followed. The contents of solids and fat, as well as pH in yoghurts (also the titrable acidity), milk semolina, and milk rice were determined. The samples were analysed by reference methods and by FT NIR spectroscope at integrating sphere within reflectance mode in the wavelength range of 10 000&ndash;4&nbsp;000 cm<sup>&ndash;1 </sup>with 100&nbsp;scans. To develop the calibration model for the components examined, the partial least squares (PLS) was used and this model was validated by full cross validation. The highest correlation coefficients were found with yoghurt: 0.998 (solids), 0.989 (fat), 0.875 (pH) and 0.989 (titrable acidity), with milk semolina: 0.967 (solids), 0.983 (fat) and 0.992 (pH), and with milk rice: 0.987 (solids), 0.990 (fat) and 0.852 (pH). The results of this study showed the availability of NIR spectroscopy for a quick and non-destructive analysis of the dairy products. &nbsp;

Sign in / Sign up

Export Citation Format

Share Document