The agricultural land worldwide become unproductive every

The chemical and
physical properties of soils determine their potential and limitations for
agricultural and non-agricultural uses. Therefore, our understanding of their
properties, functions and of their variability in space and time is essential
for sustainable land management (McBratney, 2000). Mismanagement of soils in
arid areas might be the main factor to degradation. Soil degradation is a
severe global problem of modern times. About 6million hectares of agricultural
land worldwide become unproductive every year due to the various soil
degradation processes (El Baroudy, 2011; Asio et al. 2009). Especially in arid
areas, soil more sensitive to salinization, compaction, aridization. The increasing world population is extending degraded
areas and decrease soil productivity. To understand negative process of soil needs enhanced laboratory analysis but
it could be time-consuming and expensive.Vis-N?R
spectroscopy is an alternative method for
investigating soil properties and has a number of advantages over the
traditional methods, as it is a method of non-destructive andanalysis, does not
pollute the environment because it does not use any chemical reagents, is cheap
and fast, measures many parameters in a single analysis and can perform
analyses in situ and online for a large number of samples per minute (Vasques
et al. 2008, Stenberg, et al. 2010).Studies have shown that the Vis-N?R
spectroscopy is a rapid, non-destructive and cost-effective analytical method
for measuring successfully several chemical, physical and mineralogical soil
properties simultaneously (Minasny, &McBratney,
2013; Chang et al. 2001, Yu et al. 2016). In
the last years, laboratory visible-near-infrared (Vis-N?R) spectroscopy has
been widely applied to soil characterization (Bilgili
et al. 2010; Conforti et al. 2017; Rossel et al. 2006; Leone et al. 2012).

There are
several works which get high results of soil properties prediction using vis-N?R
technology. Viscarra Rossel et al (2009) identified that  the wavelengths where there were significant
differences between the spectra collected in situ, at field conditions and the
spectra collected in the laboratory from dry, 2 mm soil. They have a good
comparison to predict soil colour, clay and mineral composition of soils in

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Summers and et
al (2011) have shown that it is possible to predict clay content, soil organic
carbon, iron oxide content and carbonate content with reflectance data produced
with a high-resolution laboratory spectrometer and stated the utility of
particular regions of the 400–2500 nm spectrum for prediction of clay content
(1900 and 2200 nm), SOC (600–900 nm), iron oxides (400–1100 nm) and carbonate (1900–2300

The main important
factor of  predicting of the soil
properties is finding certain data pre processing and calibration procedures,
where, correlation between soil spectral data and values of each soil
properties could be achieved (Mouazen, 2006; Yang, 2012; García-Sánchez et al.
2017, Islam, et al.2003).Several preprocessing techniques have been
used to improve the accuracy of SOC prediction with Vis-NIR data and these techniques have been used to
transform soil spectra, remove noise, emphasize features and extract useful
information on quantitative predictive models (Dotto, et al. 2017, Rinnan et
al. 2009 ).

and et al (2008) have shown that the best multivariate technique to predict
soil total carbon content from soil VNIR spectra was PLSR. Overall, parametric
multivariate techniques outperformed tree-based ones. Based on the mean R2
and mean RMSEv, the predictive ability of the multivariate techniques tested
decreased in the following order: PLSR>SMLR>CT>PCR>RT.

Soil survey, due to the complexity of collected information is a time
loosing activity with high costs. Besides the survey, soil sample analysis is
also costly. This high survey and analytical costs could be reduced by the
adoption of new instruments as spectroradiometers(Mohamed et al, 2017; Dotto,
et al., 2017). Due to advantage of modern technology Mughan plain very
attractive for soil investigation because of its agricultural and ecological

The study area has been intensively used and undergoes
high anthropogenic pressure because of high-density settlement and agricultural
demand of all country. Recent years there are not reliable soil research to
monitor soil changes. The lack of soil data does not let to prognosis the
future development of soil resources.

 The goal of this study was ( to evaluate the potential
for Vis-NIR spectroscopy to predict SOM using PLSR ii ) to draw attention to
proximal soil sensing such as rapid methods of soil and monitor soil quality
and iii ) to formalize soil spectral database of Azerbaijan for harmonizing
with global soil data.


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