Development of a Danish national Vis-NIR soil spectral library for soil organic carbon determination

2012 ◽  
pp. 403-408 ◽  
Author(s):  
M Knadel ◽  
F Deng ◽  
A Thomsen ◽  
M Greve
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Spectral Library ◽  
Carbon Determination

Building a near infrared spectral library for soil organic carbon estimation in the Limpopo National Park, Mozambique

Geoderma ◽  
2012 ◽  
Vol 183-184 ◽  
pp. 41-48 ◽  
Author(s):  
A.H. Cambule ◽  
D.G. Rossiter ◽  
J.J. Stoorvogel ◽  
E.M.A. Smaling
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
National Park ◽  
Near Infrared ◽  
Spectral Library ◽  
Infrared Spectral

scholarly journals Methods of soil organic carbon determination in Brazilian savannah soils

2014 ◽  
Vol 71 (4) ◽  
pp. 302-308 ◽  
Author(s):  
Juliana Hiromi Sato ◽  
Cícero Célio de Figueiredo ◽  
Robélio Leandro Marchão ◽  
Beáta Emöke Madari ◽  
Luiz Eduardo Celino Benedito ◽  
...  
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Brazilian Savannah ◽  
Carbon Determination

scholarly journals COMPARISON OF TWO METHODS OF SOIL ORGANIC CARBON DETERMINATION

2016 ◽  
Vol 48 (1) ◽  
pp. 47 ◽  
Author(s):  
Gabriela Barančíková ◽  
Jarmila Makovníková
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Statistical Processing ◽  
Soil Samples ◽  
Soil Parameters ◽  
Wide Range ◽  
Soil Complex ◽  
Complex Monitoring ◽  
Carbon Determination

<p>Soil organic carbon (SOC) is one of the basic soil parameters which takes part in many biological, chemical and physical soil processes and the SOC is currently considered as a key indicator of soil quality. For this reason determination of the SOC is a part of soil complex monitoring which has been performed in Slovakia since 1993. From 1993 until 2007 the “wet” method of determination of the SOC was used. Since 2008 the “dry” method for determination of the SOC has been applied. The goal of this work has been to evaluate and compare two methods of the SOC determination; the “wet”(Ťiurin method in modification of Nikitin (TN)) and the “dry” determination of the SOC by means of the CN analyser (EA), which was performed on 95 soil samples of topsoil coming from 17 sampling sites with a wide range of the SOC (1–15%). Sampling sites include arable lands and grasslands and represent main soil types and subtypes of Slovakia. On the basis of statistical processing it has been found that in soils with the SOC content up to 3%, differences between two methods are minimal. However, in the case of a higher content of the SOC, the EA method reaches a higher value than the TN method. Obtained data shows that in the case of soil samples with a higher content of the SOC, when changing an analytical method, the PTF function that reduces differences and allows to use all time series monitoring data should be used for the purpose of the tracking trends of the SOC monitoring.</p><p> </p><p>Celem pracy było porównanie wyników oznaczania węgla organicznego (SOC) w próbkach gleb dwoma metodami: spalania „na mokro“ (Tiurina) oraz spalania „na sucho“ w autoanalizatorzee CN. Analizowano 95 próbek gleb z 17 miejsc kompleksowego monitoringu gleb Słowacji, o zwawartości węgla organicznego od 1 do 15%. Analiza statystyczna wykazała, że różnice wyników oznaczania SOC dwoma metodami w próbkach o zawarości węgla do 3% nie były istotne statystycznie. Dla próbek o wyższej zawartości SOC, wyniki uzyskane metodą spalania „na sucho“ były istotnie wyższe niż uzyskane metodą Tiurina, dlatego do celów porównawczych zawartości SOC w tych glebach oznaczonych różnymi metodami należy stosować odpowiednie przeliczniki.</p>

Stratification of a local VIS-NIR-SWIR spectral library by homogeneity criteria yields more accurate soil organic carbon predictions

Geoderma ◽  
2019 ◽  
Vol 337 ◽  
pp. 565-581 ◽  
Author(s):  
Jean Michel Moura-Bueno ◽  
Ricardo Simão Diniz Dalmolin ◽  
Alexandre ten Caten ◽  
André Carnieletto Dotto ◽  
José A.M. Demattê
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Spectral Library

Assessing the Effectiveness of the Walkley-Black Method for Soil Organic Carbon Determination in Tephra Soils of Cameroon

2018 ◽  
Vol 49 (19) ◽  
pp. 2379-2386 ◽  
Author(s):  
Roger Kogge Enang ◽  
Bernard Palmer Kfuban Yerima ◽  
Georges Kogge Kome ◽  
Eric Van Ranst
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Carbon Determination

scholarly journals Application of Spectrally Derived Soil Type as Ancillary Data to Improve the Estimation of Soil Organic Carbon by Using the Chinese Soil Vis-NIR Spectral Library

2018 ◽  
Vol 10 (11) ◽  
pp. 1747 ◽  
Author(s):  
Yi Liu ◽  
Zhou Shi ◽  
Ganlin Zhang ◽  
Yiyun Chen ◽  
Shuo Li ◽  
...  
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Soil Type ◽  
Near Infrared ◽  
Expert Knowledge ◽  
Nir Spectroscopy ◽  
Soil Classification ◽  
Soil Types ◽  
Spectral Library ◽  
Ancillary Data

Ancillary data, such as soil type, may improve the visible and near-infrared (vis-NIR) estimation of soil organic carbon (SOC); however, they require data collection or expert knowledge. The application of a national soil spectral library to local SOC estimations usually requires soil type information, because the relationships between vis-NIR spectra and SOC from different populations may vary. Using 515 samples of five soil types (genetic soil classification of China, GSCC) from the Chinese soil spectral library (CSSL), we compared three strategies in the vis-NIR estimation of SOC. Different regression models were calibrated using the entire dataset (Strategy I, without using soil type as ancillary data) and the subsets stratified by soil type from CSSL as ancillary data (strategies II and III). In Strategy II, the subsets were stratified by soil type from the CSSL for validation. In Strategy III, the subsets were stratified by spectrally derived soil type for validation. The results showed that 86.72% of the samples were successfully discriminated for the soil types by using the vis-NIR spectra. The coefficients of determination in the prediction ( R p 2 ) of SOC estimation by strategies I, II, and III were 0.74, 0.83, and 0.82, respectively. The stratified calibration strategies (strategies II and III) improved the vis-NIR estimation of SOC. The misclassification of the soil type in the application of Strategy III slightly affected the SOC estimations. Nevertheless, this strategy is inexpensive and beneficial when expert knowledge on soil classification is lacking. We concluded that vis-NIR spectroscopy could be applied to distinguish some soil types in terms of GSCC, which further provided essential and easily accessible ancillary data for the application of stratified calibration strategies in the vis-NIR estimation of SOC.

When does stratification of a subtropical soil spectral library improve predictions of soil organic carbon content?

2020 ◽  
Vol 737 ◽  
pp. 139895
Author(s):  
Jean Michel Moura-Bueno ◽  
Ricardo Simão Diniz Dalmolin ◽  
Taciara Zborowski Horst-Heinen ◽  
Alexandre ten Caten ◽  
Gustavo M. Vasques ◽  
...  
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Carbon Content ◽  
Organic Carbon Content ◽  
Spectral Library ◽  
Soil Organic Carbon Content ◽  
Subtropical Soil
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