Determination of cellulose, hemicellulose and lignin content using near-infrared spectroscopy in flax fiber

2019 ◽  
Vol 89 (23-24) ◽  
pp. 4875-4883 ◽  
Author(s):  
Jing Huang ◽  
Chongwen Yu
Keyword(s):  
Spectral Range ◽  
Near Infrared ◽  
Lignin Content ◽  
Full Range ◽  
Accurate Determination ◽  
Principal Component ◽  
Flax Fiber ◽  
Fiber Composition ◽  
Wet Chemical

The rapid and accurate determination of flax fiber composition is necessary for its application, but until now it has mainly been tested by the wet chemical method, which is time-consuming and not environmentally friendly. In this paper, near-infrared (NIR) spectroscopy was studied to determinate the main composition of flax, in which 43 flax samples were tested according to the traditional Chinese wet chemical component test standard. Five sets of spectra were generated to show the characteristic of each sample; in total 215 spectra sets were collected using a Fourier transform near-infrared spectrometer. The methods of partial least squares (PLS) and principal component regression (PCR) were used to establish the relationships between the data from the chemical and NIR methods. PLS proved to be a better quantitative method than PCR, based on the value of the coefficient of multiple determination for calibration ( Rc2) and prediction ( Rp2), the ratio of performance to standard deviate (RPD) and the root mean square error of prediction (RMSEP). With the best pretreatment method, the spectral range of 10,000–4000 cm–1yielded a better predictive result than the full range, with Rc2of 0.968, Rp2of 0.955, RMSEP of 1.060%, RPD of 4.641 for cellulose and Rc2of 0.958, Rp2of 0.906, RMSEP of 0.678%, RPD of 3.305 for hemicellulose, while the spectral range 6900–5600 cm–1yielded a better predictive result with Rc2of 0.936, Rp2of 0.769, RMSEP of 0.455%, and RPD of 2.366 for lignin. The study shows that NIR models can provide a simple and fast way to analyze flax fiber composition, which is also beneficial to evaluate its quality.

Nondestructive NIR and NIT Determination of Protein, Fat, and Water in Plastic-Wrapped, Homogenized Meat

1992 ◽  
Vol 46 (11) ◽  
pp. 1685-1694 ◽  
Author(s):  
Tomas Isaksson ◽  
Charles E. Miller ◽  
Tormod Næs
Keyword(s):  
Diffuse Reflectance ◽  
Near Infrared ◽  
Multivariate Calibration ◽  
Principal Component Regression ◽  
Principal Component ◽  
Prediction Errors ◽  
Optimal Test ◽  
Meat Samples ◽  
Water Contents

In this work, the abilities of near-infrared diffuse reflectance (NIR) and transmittance (NIT) spectroscopy to noninvasively determine the protein, fat, and water contents of plastic-wrapped homogenized meat are evaluated. One hundred homogenized beef samples, ranging from 1 to 23% fat, wrapped in polyamide/polyethylene laminates, were used. Results of multivariate calibration and prediction for protein, fat, and water contents are presented. The optimal test set prediction errors (root mean square error of prediction, RMSEP), obtained with the use of the principal component regression method with NIR data, were 0.45, 0.29 and 0.50 weight % for protein, fat, and water, respectively, for plastic-wrapped meat (compared to 0.40, 0.28 and 0.45 wt % for unwrapped meat). The optimal prediction errors for the NIT method were 0.31, 0.52 and 0.42 wt % for protein, fat, and water, respectively, for plastic-wrapped meat samples (compared to 0.27, 0.38, and 0.37 wt % for unwrapped meat). We can conclude that the addition of the laminate only slightly reduced the abilities of the NIR and NIT method to predict protein, fat, and water contents in homogenized meat.

Analysis of artificial mixtures of pure chemicals by near-infrared reflectance

1990 ◽  
Vol 114 (3) ◽  
pp. 253-257 ◽  
Author(s):  
G. Z. Wetherill ◽  
I. Murray ◽  
C. A. Glasbey
Keyword(s):  
Near Infrared ◽  
Compositional Analysis ◽  
Principal Component ◽  
Infrared Reflectance ◽  
Near Infrared Reflectance ◽  
Chemical Methods ◽  
Wet Chemical ◽  
Linear Regressions ◽  
Unexplained Variation ◽  
Artificial Mixtures

SUMMARYCompositional analysis of feeds and other materials by near-infrared reflectance (NIR) has been proposed as a cheap and rapid alternative to traditional wet chemical methods. A theoretical basis for NIR measurements is needed and may be obtained from the study of artificial mixtures of pure chemicals.Mixtures of lactose, casein and sodium oleate, in widely differing concentrations, were analysed by NIR. Principal component analysis was used to study the variations between spectra, and multiple linear regressions gave predictors of sample compositions from the spectra. Optical densities at most combinations of wavelengths gave good predictions of sample compositions because there was much less unexplained variation between NIR spectra than would occur between natural samples.

Fungal decay of spruce and beech wood assessed by near-infrared spectroscopy in combination with uni- and multivariate data analysis

Holzforschung ◽  
2007 ◽  
Vol 61 (6) ◽  
pp. 680-687 ◽  
Author(s):  
Karin Fackler ◽  
Manfred Schwanninger ◽  
Cornelia Gradinger ◽  
Ewald Srebotnik ◽  
Barbara Hinterstoisser ◽  
...  
Keyword(s):  
Data Analysis ◽  
Multivariate Data Analysis ◽  
Near Infrared ◽  
Lignin Content ◽  
Beech Wood ◽  
Multivariate Data ◽  
Principal Component ◽  
Brown Rot ◽  
White Rot ◽  
Least Squares Regression

Abstract Wood is colonised and degraded by a variety of micro-organisms, the most efficient ones are wood-rotting basidiomycetes. Microbial decay processes cause damage to wooden constructions, but also have great potential as biotechnological tools to change the properties of wood surfaces and of sound wood. Standard methods to evaluate changes in infected wood, e.g., EN350-1 1994, are time-consuming. Rapid FT-NIR spectroscopic methods are also suitable for this purpose. In this paper, degradation experiments on surfaces of spruce (Picea abies L. Karst) and beech (Fagus silvatica L.) were carried out with white rot basidiomycetes or the ascomycete Hypoxylon fragiforme. Experiments with brown rot or soft rot caused by Chaetomium globosum were also performed. FT-NIR spectra collected from the degraded wood were subjected to principal component analysis. The lignin content and mass loss of the specimens were estimated based on univariate or multivariate data analysis (partial least squares regression).

Determination of the moisture content of paprika (Capsicum annuum) powders: a comparative study/ Determinación de la humedad del pimentón (Capsicum annuum): estudio comparativo

1996 ◽  
Vol 2 (1) ◽  
pp. 23-27 ◽  
Author(s):  
E. Forgács ◽  
V. Kiss ◽  
T. Cserháti ◽  
J. Holló
Keyword(s):  
Principal Component Analysis ◽  
Moisture Content ◽  
Capsicum Annuum ◽  
Near Infrared ◽  
Principal Component ◽  
Peak Height ◽  
Data Matrix ◽  
Drying Method ◽  
Electric Oven

The moisture content of 25 different paprika powders was determined by an electronic moisture analyzer at 40, 50, 60, 70, 80, 90, 100 and 105°C by near infrared spectroscopy, using both peak area and peak height for the water; and by the traditional drying method, using an electric oven at 100°C for 1, 2 and 3 h. The data matrix was evaluated by principal component analysis. It was established that the moisture content of paprika powders can be equally determined by each method. The use of the NIR method has been proposed because it is both rapid and accurate, and the presence of other volatile compounds does not influence the reliability of the determination of the moisture content.

scholarly journals Rapid and accurate determination of the lignin content of lignocellulosic biomass by solid-state NMR

Fuel ◽  
2015 ◽  
Vol 141 ◽  
pp. 39-45 ◽  
Author(s):  
Li Fu ◽  
Scott A. McCallum ◽  
Jianjun Miao ◽  
Courtney Hart ◽  
Gregory J. Tudryn ◽  
...  
Keyword(s):  
Solid State ◽  
Lignocellulosic Biomass ◽  
Solid State Nmr ◽  
Lignin Content ◽  
Accurate Determination

A Method for Calculating the Index of Refraction of Thin Films

1975 ◽  
Vol 53 (18) ◽  
pp. 1737-1742 ◽  
Author(s):  
J. H. Wohlgemuth ◽  
D. E. Brodie
Keyword(s):  
Thin Films ◽  
Spectral Range ◽  
Variational Approach ◽  
Accurate Determination ◽  
Normal Incidence ◽  
Index Of Refraction ◽  
New Method ◽  
Reflection And Transmission ◽  
Transmission Measurements

A new method for determining the index of refraction from normal incidence reflection and transmission measurements has been developed. Several other methods are reviewed to explain why a new method is needed. The author's method used a thickness variational approach. For an accurate determination of n and k, the method requires normal incidence reflection and transmission measurements over a fairly broad spectral range for at least two different film thicknesses. These requirements are unavoidable for normal incidence methods.

Analysis of undried grass silage by near-infrared spectroscopy

1994 ◽  
Vol 1994 ◽  
pp. 119-119
Author(s):  
H W Morris ◽  
S Fisher ◽  
J R Newbold ◽  
S Wilson ◽  
C W Ashby ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Volatile Components ◽  
Chemical Methods ◽  
Grass Silage ◽  
Nutrient Value ◽  
Wet Chemical ◽  
Calibration Equations

The analysis of grass silage by near-infrared spectroscopy (NIR) of dried samples is established as a valid alternative to wet chemical methods. Analysis of undried samples offers potential advantages in terms of :d of analysis and accuracy of determination of volatile components, provided calibration equations can be validated against independent populations of silage. Accumulation of analyses for a large number of pies allows relationships between silage nutrient value and management factors such as additive use, which are poorly understood, to be examined.

Sign in / Sign up

Export Citation Format

Share Document