Predicting Soil Bulk Density Using Advanced Pedotransfer Functions in an Arid Environment

Direct measurement and prediction of bulk density on alluvial soils of central Chile

“…The anomalous behavior of the published PTFs used in this study suggests that the mineralogy of the validation soil samples may have been different from that of the soils from which the PTFs were developed. On the other hand, rb is largely controlled by SOM in a non-linear relationship, while soil particles have a linear effect on this property (Al-Qinna and Jaber, 2013). Further studies are needed to incorporate soil structure as an input parameter to derive PTFs.…”

“…Pedotransfer functions (PTFs) have been gaining widespread recognition for their ability to predict rb using extractable available soil databases (Tranter et al, 2007;Al-Qinna and Jaber, 2013). At least four factors affect the performance of a PTF in simulations: the accuracy of basic soil data used as inputs in PTFs, the accuracy of PTF itself, specific features of the simulation model, and the output used as a functional criteria (Donatelli et al, 2004).…”

“…At least four factors affect the performance of a PTF in simulations: the accuracy of basic soil data used as inputs in PTFs, the accuracy of PTF itself, specific features of the simulation model, and the output used as a functional criteria (Donatelli et al, 2004). Although preliminary studies showed that soil organic matter (SOM) has an important effect on rb, it has since been observed that soil texture plays a major role in controlling rb and SOM is a minor component (Rawls, 1983;Al-Qinna and Jaber, 2013). Moreover, more recent research (Hollis et al, 2012) reports that other physical and chemical soil properties are involved.…”

Snowball ICA: A Model Order Free Independent Component Analysis Strategy for Functional Magnetic Resonance Imaging Data

“…The stronger the non-Gaussianity of the signals, the more this assumption of ICA is satisfied. The standard measure of non-Gaussianity is kurtosis (Hyvärinen and Oja, 2000). The kurtosis of signal y with mean value µ and standard deviation σ is defined by:…”

“…For the simulated data, Matlab FastICA (Hyvärinen and Oja, 2000) was used as a representative traditional approach with model orders of 10, 29, 50, 100, 200, 400, 500, 800, and 1000, in order to compare the results under different model orders. The mutual information of sources with noise was also calculated.…”