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Successive use of sand on the soil surface during garlic planting process facilitates clove sprouting and prevents soil crust formation. However, this process has led to the destruction and damage of the soil structure and texture in the East Azerbaijan province, northwest of Iran. In this study, the effects of different organic mulches and irrigation methods on soil properties and garlic yield were investigated. Experiments were conducted based on the split-plot design with three replications. The treatments consisted of two surface and drip irrigation methods, while seven types of mulches (straw 1.5 kg m−2, cow manure in two quantities of 2 kg m−2 and 4 kg m−2, sand in two quantities of 4 kg m−2 and 8 kg m−2, poultry manure 1.5 kg m−2, polyethylene mulch) and no mulch as a control treatment were used. The use of poultry and cow manures increased the average yield of garlic to 18.51 and 20.92 ton ha−1, respectively, as compared to the sand mulch case (11.5 ton ha−1). The results of this study showed that the use of cow manure and poultry manure can increase soil fertility and better garlic yield. Moreover, the use of drip irrigation method instead of surface irrigation method, besides maintaining soil characteristics and consuming fewer water levels, was increased the average yield of garlic from 14.19 to 16.67 ton ha−1. [ABSTRACT FROM AUTHOR]

Solar radiation, moisture and temperature are the most vital meteorological variables which affect plant growth. Due to the fact that the global solar radiation (GSR) is scarcely gauged at meteorological stations in developing countries, it is commonly estimated by data-driven techniques or by empirical equations. In this study, support vector regression (SVR), model trees (MT), gene expression programming (GEP) and adaptive neuro-fuzzy inference system (ANFIS) and several empirical equations were applied to assess the relations between GSR and several meteorological variables including minimum temperature (Tmin), maximum temperature (Tmax), relative humidity (RH), sunshine hours (n), maximum sunshine hours (N), corrected clear-sky solar irradiation (ICSKY), day of year (DOY) and extra-terrestrial radiation (Ra). For this purpose, the daily GSR measured from the beginning of 2011 to the end of 2013 at Tabriz synoptic station, which is located in semi-arid regions of Iran, were used. A direct strong relationship was observed to exist between the GSR and n. For evaluating the performances of studied techniques, three different statistical indicators were used namely root mean square error (RMSE), mean absolute error (MAE), and correlation coefficient (CC). Additionally, a Taylor diagram was utilized to test the similarity between the observed and predicted GSR values. Results indicated that the SVR-6 with input parameters of Ra, RH, Tmin, Tmax, n/N had better accuracy in predicting GSR with RMSE of 1.656, MAE of 0.990, CC of 0.980 and WI of 0.990 than the other models. Moreover, MT-6 ranked as the second best model in the prediction of GSR values. As an interesting point, studied empirical equations had lower accuracies comparing with the SVR, GEP, MT and ANFIS methods. For instance, GSR values were computed by Angstrom and Prescott equation, as the best empirical equation, with RMSE of 1.786, MAE of 1.156, CC of 0.977 and WI of 0.988. Conclusively, results from the current study proved that the SVR provided reasonable trends for GSR modeling at Tabriz synoptic station. Furthermore, MT models with linear equations can be implemented with a high degree of simplicity and acceptable precision in GSR estimation. [ABSTRACT FROM AUTHOR]

The model MSM (Maize Simulation Model) was modified and validated, using data on furrow irrigation in Fars province in Iran during 2003 and 2004. The planted cultivar was SC704 (single cross) a late maturity hybrid. Three nitrogen levels (300, 150, and 0 kg N ha-1 as urea) and four irrigation treatments (applied water at 1.2, 1.0, 0.8, and 0.6 ratios of potential maize water requirements as I4, I3, I2, and I1 treatments, respectively) were considered. The potential water requirements were estimated based on the differences between soil field capacity and measured soil water contents at root depth in the I3 treatments before irrigation. The MSM model was modified based on field data in 2003 as: (i) Modification of root N uptake based on soil water pressure head and van Genuchten soil parameters for soil moisture retention curve α, and (ii) modification of grain yield prediction based on seasonal plant stover nitrogen uptake and grain N content. Model subroutines, i.e. leaf area index, dry matter production, prediction of soil water contents at different depths and at different days after planting did not require any modifications. Comparisons between measured data and predicted values by the modified model indicated favorable validation. [ABSTRACT FROM AUTHOR]