Global Journal of Agricultural Innovation, Research & Development, 2014, 1, 17-26 17 E-ISSN: 2409-9813/14 © 2014 Avanti Publishers Vis-NIR Spectroscopy for Determining Physical and Chemical Soil Properties: An Application to an Area of Southern Italy Massimo Conforti and Gabriele Buttafuoco * Institute for Agricultural and Forest Systems in the Mediterranean (ISAFOM), National Research Council (CNR) of Italy, Rende (CS), Italy Abstract: The development of rapid, accurate, cost effective methods to determine soil physical and chemical properties is important for sustainable land management. In the last two to three decades, the interest in using visible and near infrared (Vis-NIR) spectroscopy as an alternative method for determining soil properties has increased. To obtain reliable predictions of soil properties, multivariate calibration techniques such as Partial Least Squares Regression (PLSR) are commonly used to correlate the spectra with the chemical, physical and mineralogical properties of soils. The objective of the paper was to assess the potential of Vis-NIR spectroscopy coupled with PLSR to determine soil chemical and physical properties such as organic carbon (SOC), sand, silt, clay, and calcium carbonate (CaCO3) contents in a sample site of southern Italy. Spectral curves showed that the soils could be spectrally separable on the basis of chemical and physical properties. PLSR calibration models were derived for each of the soil properties and were validated with an independent data set. The optimum number of factors to be retained in the calibration models was determined by leave-one-out cross- validation. The accuracy of the calibration and validation models for the different soil properties was evaluated with the coefficient of determination (R 2 ) and the root mean squared error (RMSE). The results showed that predictions were satisfactory for all soil properties analyzed with high values of R 2 > 80. A combination of Vis-NIR spectroscopy and multivariate statistical techniques, therefore, can be used as a rapid, low cost and quantitative means of characterizing the soils of southern Italy. Keywords: Soil properties, Vis-NIR reflectance spectroscopy, PLSR, Southern Italy. 1. INTRODUCTION Soil is one of the most important natural resources because it plays a key role in biochemical and geochemical cycling, water partitioning (storage and release), land protection and buffering, and energy partitioning, all of which are essential for supporting ecosystems [1]. Moreover, soil represents the largest pool of carbon (C), storing approximately 1500 PgC in the top 1 m [2, 3]; hence, even relatively small changes in soil C storage per unit area could have a significant impact on the global carbon balance. Therefore, accurately quantifying soil properties and their spatial and temporal variability is an important issue for sustainable land management, precision agriculture and soil mapping as well as for carbon sequestration. However, conventional methods of estimating soil properties, based on field or laboratory methods, are relatively complex, time consuming, and expensive when large numbers of soil samples need to be analyzed [4]. To overcome this, visible and near- infrared spectroscopy (Vis-NIR, 350 - 2500 nm) has become, in recent decades, an important tool for quantitative evaluation of soil properties, e.g., *Address correspondence to this author at the Institute for Agricultural and Forest Systems in the Mediterranean (ISAFOM), National Research Council (CNR) of Italy, Rende (CS), Italy; Tel: +390984841484; Fax: +390984841497; E-mail: gabriele.buttafuoco@cnr.it carbonate content, organic carbon (OC), total nitrogen (N), iron (Fe) oxide minerals, soil texture [5-10]. Compared to conventional laboratory methods, the Vis- NIR spectroscopy technique has been accepted as rapid and cost effective, requiring minimal sample preparation and no hazardous chemicals. It is non- destructive and several soil properties can be determined from a single measure [e.g. 4, 10-15]. The Vis-NIR spectroscopy method is based on the simple assumption that the soil reflectance in the 350-2500 nm spectral region is a linear combination of the spectral signatures of its various components weighted by their abundance [16, 17]. So, small changes in physical, chemical, mineralogical and biological soil properties produce different spectral characteristics that can be identified by reflectance spectroscopy [12, 18-23]. Although measuring soil Vis-NIR reflectance requires only a few seconds, the reflectance spectra are largely non-specific due to interference resulting from the overlapping spectra of soil constituents that are themselves varied and interrelated [24]. Therefore, the physical, chemical and mineralogical properties of soils can be correlated to reflectance spectra by suitable multivariate calibration procedures [15, 25, 26] such as multiple linear regression (MLR), principal components regression (PCR), partial least-squares regression (PLSR) and artificial neural networks (ANN) [e.g. 6, 7, 12, 14, 21, 27-29].