Abbas Ahmadi

TL;DR: In this paper, the predictive capabilities of multiple linear regressions (MLR) and artificial neural networks (ANNs) are evaluated to estimate fruit firmness in six months, including each of nutrients concentrations (nitrogen (N), potassium (K), calcium (Ca) and magnesium (Mg)) alone (P 1 ), combination of nutrients concentration (P 2 ), nutrient concentration ratios alone (p 3 ), and combination of nutrient concentrations and nutrient concentration ratio (P 4 ).

TL;DR: In this article, the authors investigated how closely the soil interrill erodibility factor in WEPP model can be correlated to and predicted from soil aggregate size distribution or from their fractal dimensions.

TL;DR: In this article, the authors used an Artificial Neural Network (ANN) and Linear Regression Methodology (LRM) to predict soil respiration in arid areas of Iran using 150 data points obtained from soil samples collected from the surface to 20 cm of depth under different land use categories.

TL;DR: In this paper, the spectral indices derived from Landsat OLI, Sentinel-2 MSI and visible near-infrared (Vis-NIR) spectroscopy data, along with partial least squares regression (PLSR) method were used for predicting contents soil salt.

TL;DR: In this article, the applicability of fractal dimension of particle size distribution (PSD) for estimation of interrill erodibility and the relationship between interrill and soil texture components were studied.