scholarly journals Determination of glomalin in agriculture and forest soils by near-infrared spectroscopy

2017 ◽  
Vol 63 (No. 5) ◽  
pp. 226-230 ◽  
Author(s):  
Zbíral Jiří ◽  
Čižmár David ◽  
Malý Stanislav ◽  
Obdržálková Elena
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Forest Soils ◽  
Near Infrared ◽  
Arable Land ◽  
Calibration Model ◽  
Sustainable Land Management ◽  
Chemical Methods ◽  
Calibration Models

Determining and characterizing soil organic matter (SOM) cheaply and reliably can help to support decisions concerning sustainable land management and climate policy. Glomalin was recommended as one of possible indicators of SOM quality. Extracting glomalin from and determining it in soils using classical chemical methods is too complicated and therefore near-infrared spectroscopy (NIRS) was studied as a method of choice for the determination of glomalin. Representative sets of 84 different soil samples from arable land and grasslands and 75 forest soils were used to develop NIRS calibration models. The parameters of the NIRS calibration model (R = 0.90 for soils from arable land and grasslands and R = 0.94 for forest soils) proved that glomalin can be determined in air-dried soils by NIRS with adequate trueness and precision simultaneously with determination of nitrogen and oxidizable carbon.

scholarly journals Characterization of soil organic matter by near infrared spectroscopy – determination of glomalin in different soils

2016 ◽  
Author(s):  
Jiří Zbíral ◽  
David Čižmár ◽  
Stanislav Malý ◽  
Elena Obdržálková
Keyword(s):  
Organic Matter ◽  
Infrared Spectroscopy ◽  
Soil Organic Matter ◽  
Near Infrared Spectroscopy ◽  
Forest Soils ◽  
Near Infrared ◽  
Arable Land ◽  
Soil Samples ◽  
Calibration Model ◽  
Calibration Models

Abstract. Determining and characterizing soil organic matter (SOM) cheaply and reliably can help to support decisions concerning sustainable land management and climate policy. Glomalin, a glycoprotein produced by arbuscular mycorrhizal fungi, was recommended as a promising indicator of SOM quality. But extracting glomalin from and determining glomalin in soils using classical chemical methods is too complicated and time consuming and therefore limits the use of this parameter in large scale surveys. Near infrared spectroscopy (NIRS) is a very rapid, non-destructive analytical technique that can be used to determine many constituents of soil organic matter. Representative sets of 84 different soil samples from arable land and grasslands and 75 forest soils were used to develop reliable NIRS calibration models for glomalin. One calibration model was developed for samples with a low content of glomalin (arable land and grasslands), the second for soils with a high content of glomalin (forest soils), and the third calibration model for all combined soil samples. Calibrations were validated and optimized by leave-one-sample-out-cross-validation (LOSOCV) and by the external validation using eight soil samples (arable land and grassland), and six soil samples (forest soils) not included in the calibration models. Two different calibration models were recommended. One model for arable and grassland soils and the second for forest soils. No statistically significant differences were found between the reference and the NIRS method for both calibration models. The parameters of the NIRS calibration model (RMSECV = 0,70 and R = 0,90 for soils from arable land and grasslands and RMSECV = 3,8 and R = 0,94 for forest soils) proved that glomalin can be determined directly in air-dried soils by NIRS with adequate trueness and precision.

Temperature compensation for determination of moisture and reducing sugar of longan honey by near infrared spectroscopy

2017 ◽  
Vol 25 (1) ◽  
pp. 36-44 ◽  
Author(s):  
Chalermpun Thamasopinkul ◽  
Pitiporn Ritthiruangdej ◽  
Sumaporn Kasemsumran ◽  
Thongchai Suwonsichon ◽  
Vichai Haruthaithanasan ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Temperature Compensation ◽  
Near Infrared ◽  
Sugar Content ◽  
Reducing Sugar ◽  
Sample Temperature ◽  
Calibration Model ◽  
Calibration Models

Near infrared spectra of honeys are affected by sample temperature variation, mainly due to a change in hydrogen bonding of water. The aim of this study was to develop robust and powerful calibration models which can compensate for a variation of sample temperature for the determination of moisture and reducing sugar content in honey using near infrared spectroscopy. Partial least squares regression with the aid of standard normal variate transformation was used to develop three calibration models at constant temperature (25, 35 and 45℃) and a robust calibration model with temperature compensation. All the developed models for moisture and reducing sugar content showed high performance of prediction with coefficient of determination ( r2) and residual prediction deviation values greater than 0.95 and 3.8, respectively. The results show that the temperature compensation model can be considered as a robust calibration model for near infrared determination of moisture and reducing sugar in the honey when sample temperature is varied.

scholarly journals Estimation of selected properties of forest soils using near-infrared spectroscopy (NIR)

2016 ◽  
Vol 67 (1) ◽  
pp. 32-36 ◽  
Author(s):  
Mateusz Kania ◽  
Piotr Gruba
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Forest Soils ◽  
Near Infrared ◽  
C:N Ratio ◽  
Soil Samples ◽  
Initial Assessment ◽  
Calibration Model ◽  
Organic Carbon Content ◽  
Spectra Analysis

Abstract The study was focused on the application of near-infrared spectroscopy (NIR) as a tool for evaluation of selected properties of forest soils. We analysed 144 soil samples from the topsoil of nine plots located in southern Poland. Six plots were established under pine stands, and three plots under oak stands. The NIR measurements were performed using Antharis II FT scanner. On the basis of the spectrum files obtained from scanning of 96 samples and the measurement results obtained for selected properties of the soil samples, we developed a calibration model. The model was validated using 48 independent samples. We attempted to estimate the following properties of forest soils: pH, C:N ratio, the organic carbon content (Ct), total nitrogen (Nt), clay content (Clay), base cation content (BC), cation exchange capacity (CEC) and total acidity (TA). We conclude that estimation of soil properties using NIR method can be applied as additional (to laboratory analysis) or initial assessment of soil quality. Our results also suggest that forest species composition may affect the mathematical model applied to NIR spectra analysis, however, this hypothesis needs some of further investigations.

Rapid determination of oil content in dried-ground oil palm mesocarp and kernel using near infrared spectroscopy

2017 ◽  
Vol 25 (5) ◽  
pp. 338-347 ◽  
Author(s):  
Sudarno ◽  
Divo D Silalahi ◽  
Tauvik Risman ◽  
Baiq L Widyastuti ◽  
F Davrieux ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Oil Palm ◽  
Standard Error ◽  
Oil Content ◽  
Near Infrared ◽  
Cross Validation ◽  
Calibration Model ◽  
Reliable Technique

Near infrared spectroscopy calibrations for rapid oil content determination of dried-ground oil palm mesocarp and kernel were developed. Samples were analyzed, one set using the Soxhlet extraction method for reference analysis and the other set scanned by near infrared spectroscopy instrument for calibration. Successful calibrations were obtained with good accuracy and precision for mesocarp and kernel, based on statistical models. Math treatment and scatter correction had significant effects on the fitting of the calibration model. The best obtained calibration models were demonstrated by multiple correlation coefficient (R2), standard error of calibration, standard error of cross validation, coefficient of determination in cross validation (1-VR) and relative predictive deviation of calibration, which respectively were 0.997, 1.21%, 1.23%, 0.997 and 17.89 for mesocarp and 0.952, 0.47%, 0.53%, 0.94 and 4.00 for kernel. The correlations between reference and predicted values for samples in the validation sets were in agreement with high linearity, high ratio performance to deviation of prediction (≥4.00) and low standard error of prediction samples for both samples. The results demonstrated that near infrared spectroscopy can be used as an alternative and reliable technique to estimate the mesocarp and kernel oil contents in dry matter basis accurately and rapidly.

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.

scholarly journals Near-Infrared Spectroscopy for Measuring Urea in Hemodialysis Fluids

2001 ◽  
Vol 47 (7) ◽  
pp. 1279-1286 ◽  
Author(s):  
Christopher V Eddy ◽  
Mark A Arnold
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Spectral Range ◽  
Near Infrared ◽  
Factor Model ◽  
Partial Least Square ◽  
Least Square ◽  
Calibration Model ◽  
Calibration Models ◽  
Sensitivity And Selectivity

Abstract Background: Near-infrared spectroscopy is proposed as a method for providing real-time urea concentrations during hemodialysis treatments. The feasibility of such noninvasive urea measurements is evaluated in undiluted dialysate fluid. Methods: Near-infrared spectra were collected from calibration solutions of urea prepared in dialysate fluid. Spectra were collected over three distinct spectral regions, and partial least-squares calibration models were optimized and compared for each. Selectivity for urea was demonstrated with two-component samples composed of urea and glucose in the dialysate matrix. The clinical significance of this approach was assessed by measuring urea in real hemodialysate samples. Results: Urea absorptions within the combination and short-wavelength, near-infrared spectral regions provided sufficient spectral information for sound calibration models in the dialysate matrix. The combination spectral region had SEs of calibration (SEC) and prediction (SEP) of 0.38 mmol/L and 0.26 mmol/L, respectively, over the 4720–4600 cm−1 spectral range with 5 partial least-square factors. A second calibration model was established over the combination region from a series of solutions prepared with independently variable concentrations of urea and glucose. The best calibration model for urea in the presence of variable glucose concentrations had a SEC of 0.6 mmol/L and a SEP of 0.4 mmol/L for a 5-factor model over the 4600–4350 cm−1 spectral range. There was no significant decrease in SEP when the 4720–4600 cm−1 calibration model was used to measure urea in real samples collected during actual hemodialysis. Conclusions: Urea can be determined with sufficient sensitivity and selectivity for clinical measurements within the matrix of the hemodialysis fluid.

scholarly journals Determination of fatty acid content in sheep milk by means of near infrared spectroscopy

2014 ◽  
Vol 83 (10) ◽  
pp. S27-S34 ◽  
Author(s):  
Táňa Lužová ◽  
Květoslava Šustová ◽  
Jan Kuchtík ◽  
Jiří Mlček ◽  
Lenka Vorlová ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Fatty Acid Content ◽  
Correlation Coefficients ◽  
Standard Errors ◽  
Sheep Milk ◽  
Calibration Models ◽  
The Fourier Transform

The study focused on the use of the Fourier transform near infrared spectroscopy in determining the content of selected fatty acids in raw non-homogenized sheep milk. The raw sheep milk sample spectra were scanned in reflectance mode using the FT NIR Antaris spectrophotometer. The reliable functional calibration models were created for estimation of the contents of myristic, oleic, lauric, palmitic, and stearic acids (with calibration correlation coefficients of R = 0.999; 0.999; 0.993; 0.992; 0.858) and with standard errors SEC = 0.056; 0.152; 0.066; 0.367; 1.36%.

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