Document Type : Research Paper

Authors

• N. Asgari ¹
• S. Ayoubi ²
• A. Dematte ³
• H. Khademi ²

¹ Ph.D student, College of Agriculture, Isfahan University of Technology, Iran.

² Professor, College of Agriculture, Isfahan University of Technology, Iran.

³ Professor, Department of Soil Science, College of Agriculture Luiz de Queiróz, Piracicaba, SP, Brazil.

Abstract

Introduction Carbonates are an essential and prominent constituent of soil chemical properties particularly in arid and semiarid regions, in regards with soil productivity and conservation. The conventional techniques for assessing soil properties rely on direct laboratory measurements which are expensive, time consuming and labor intensive. Hence, it is required to develop fast and cost-efficient techniques for evaluation of mentioned parameters. The Koppen climatic classification generally categorizes Iran among the arid and semi-arid climates. About 90 % of its lands are arid or semiarid. According to Soil Survey Staff (2014), calcareous soils contain 5% or more volumes of inorganic carbon (or carbonate calcium equivalent), which are the prevailing formation in arid and semi-arid areas. These soils are typical of areas where minerals cannot be leached away from the soil profile due to low precipitation. Based on the reports of FAO.UNDP (1972), approximately 12% of soils all over the world and 65% in Iran are calcareous. Therefore, carbonate is a key component that physically and chemically influences soil properties, as well as its fertility and productivity. One of the fast, easy-to-use, cost-effective and non-destructive methods of soil analysis is the visible to near-infrared (Vis-NIR) and mid-infrared (mid-IR) spectroscopy, that can partly be employed for the optimization of traditional techniques. Therefore, the reflectance spectroscopy is considered as one of relatively inexpensive and fast techniques to evaluate these features. The purpose of the present study was to evaluate the capability of the reflectance spectroscopy technique in Vis-NIR (250-2500 nm) and mid-IR (400-400 cm^1-) ranges to estimate soil carbonates content as one of the key components affecting the physical and chemical properties of soils (especially in arid and semi-arid regions).
Materials and Methods The study area is located in Juneqan District, Chaharmohal and Bakhtiari Province, southwest of Iran. 272 soil samples were collected from a depth of 0-10 cm, air dried and passed through a 2 mm sieve. The carbonates value of each sample was determined by standard laboratory method. The spectral reflectance of soil samples was extracted in the Vis-NIR (250-2500 nm) and mid-IR (400-400 cm^1-) ranges using a spectroradiometer FieldSpec 3 (ASD-Analytical Spectral Devices, Boulder Colorado, USA) and Nicolet 6700 Fourier Transform Infrared (FT-IR) (Thermo Fisher Scientific Inc., Waltham, MA), respectively. In the next step, seven preprocessing methods included absorbance transformation (log [1/reflectance]) (Abs), multiplicative scatter correction (MSC), standard normal variate transformation (SNV), Savitzsky-Golay derivation (SGD), Continuum removal transformation (CR), Normalization in range <-1,>1 (Nor) and Detrend (Det), were performed over original spectra for correcting light scattering in reflectance measurements and data improvement before using data in calibration models. Afterward, The dataset (272 samples) for each spectra range was randomly divided in calibration (70%) and validation (30%) datasets. Four different calibration models were fitted over Vis-NIR and mid-IR spectra to develop carbonates prediction models including: Partial Least Squares Regression (PLSR), Support Vector Machine (SVM), Random Forest (RF) and Gaussian Process Regression (GPR). The evaluation of soil predicting models was done according to the value of R², RMSE and RPD. According to some researches, RPD values more than 2 shows that the models provide precise predictions, values of RPD between 1.4 and 2 are considered to be reasonably representative, and values less than 1.4 indicate poor predictive value.
Results and Discussion The carbonates content in studied samples ranged from 1 to 76% with an average value of 24.7%. Overall, carbonates content promoted increase of spectral reflectance intensity on several region of spectrum in both spectral ranges. The specific absorption wavelength in Vis-NIR spectra used to indicate the presence of soil carbonates was 2338 nm and in the mid-IR range were 714, 850, 870, 1796, and 2510 cm¹. The results showed that the best performance of the used models in the Vis-NIR spectral range was related to the SVM model (R²=0.81, RMSE=5.36) and in the mid-IR range allocated to PLSR model (R²=0.86, RMSE=4.5). Both of these models showed great accuracy in carbonates estimating (RPD>2). Besides, the results showed that the mid-IR spectral range in the prediction of carbonates provided better performance than the Vis-NIR range. This can explained by the fact that the fundamental molecular vibrations of soil components occur in the mid-IR range, while only their overtones and combinations are detected in the Vis-NIR range.
Conclusion It seems that the reflectance spectroscopy technique can be considered as a precise substitute for the conventional methods of measuring carbonates, which are sometimes costly, time consuming and destructive. However, due to the spatial and temporal variability of soil properties as well as the huge variety of models and spectral preprocessing methods, it is necessary to examine the capability of this technique in other areas with other preprocessing methods and regression models.

Keywords

• Spectral preprocessing
• Diffuse reflectance
• spectroscopy
• Soil reflection spectrum
• PLSR
• Spectral continuum-removed curve