Precipitation forecasting by large-scale climate indices and machine learning techniques

Global warming is one of the most complicated challenges of our time causing considerable tension on our societies and on the environment. The impacts of global warming are felt unprecedentedly in a wide variety of ways from shifting weather patterns that threatens food production, to rising sea levels that deteriorates the risk of catastrophic flooding. Among all aspects related to global warming, there is a growing concern on water resource management. This field is targeted at preventing future water crisis threatening human beings. The very first stage in such management is to recognize the prospective climate parameters influencing the future water resource conditions. Numerous prediction models, methods and tools, in this case, have been developed and applied so far. In line with trend, the current study intends to compare three optimization algorithms on the platform of a multilayer perceptron (MLP) network to explore any meaningful connection between large-scale climate indices (LSCIs) and precipitation in the capital of Iran, a country which is located in an arid and semi-arid region and suffers from severe water scarcity caused by mismanagement over years and intensified by global warming. This situation has propelled a great deal of population to immigrate towards more developed cities within the country especially towards Tehran. Therefore, the current and future environmental conditions of this city especially its water supply conditions are of great importance. To tackle this complication an outlook for the future precipitation should be provided and appropriate forecasting trajectories compatible with this region's characteristics should be developed. To this end, the present study investigates three training methods namely backpropagation (BP), genetic algorithms (GAs), and particle swarm optimization (PSO) algorithms on a MLP platform. Two frameworks distinguished by their input compositions are denoted in this study: Concurrent Model Framework (CMF) and Integrated Model Framework (IMF). Through these two frameworks, 13 cases are generated: 12 cases within CMF, each of which contains all selected LSCIs in the same lead-times, and one case within IMF that is constituted from the combination of the most correlated LSCIs with Tehran precipitation in each lead-time. Following the evaluation of all model performances through related statistical tests, Taylor diagram is implemented to make comparison among the final selected models in all three optimization algorithms, the best of which is found to be MLP-PSO in IMF.     

Effect of soil pore size distribution on plant-available water and least limiting water range as soil physical quality indicators

Soil pore size distribution(SPSD) is one of the most important soil physical properties. This research investigated the relationships of location and shape parameters of the SPSD curves with plant-available water(PAW) and least limiting water range(LLWR) of the light-textured soils at the Torogh Agricultural Research Station in north-eastern Iran. Soil moisture release curve(SMRC), PAW and LLWR in matric heads of 100 and 330 h Pa for the field capacity and location and shape parameters of the SPSD curves of 30 soils with different texture and organic carbon contents were determined, and the variable relationships were statistically analyzed. The results showed that the median equivalent pore diameter(de), mean de, standard deviation(SD*), and skewness of the SPSD curves were significantly correlated with PAW(PAW330) and LLWR(LLWR330) measured in a matric head of 330 h Pa. Decrease in deand increase in the diversity of soil pore size(SD*) increased PAW330 and LLWR330. The SD* values of all the soil samples were lower than the optimal ranges suggested in literature. Neither PAW nor LLWR values were significantly different in the soils with the optimal modal deand those with non-optimal modal de. Optimal values of median and mean equivalent pore diameters and kurtosis of SPSD curves led to a significant improvement of PAW330 and LLWR330 as soil physical quality indicators. It was recommended to revise the optimal ranges for SD* and modal defor future studies.     

Analysis of the variations in dry matter yield and resource use efficiency of maize under different rates of nitrogen,phosphorous and water supply

Abstract

Increasing resources use efficiency in intensive cultivation systems of maize (Zea mays L.) can play an important role in increasing the production and sustainability of agricultural systems. The objectives of the present study were to evaluate DM yield and the efficiency of inputs uses under different levels of water, nitrogen (N) and phosphorus (P) in maize. Therefore, three levels of irrigation including 80 (ETc₈₀), 100 (ETc₁₀₀) and 120% (ETc₁₂₀) of crop evapotranspiration were considered as the main plots, and the factorial combination of three levels of zero (N₀), 200 (N₂₀₀) and 400 (N₄₀₀) kg N ha^?1 with three levels of zero (P₀), 100(P₁₀₀) and 200 (P₂₀₀) kg P ha^?1 was considered as the sub plots. The results showed that increasing the consumption of water and P was led to the reduction of N and P utilization efficiency, while RUE increased. WUE was also increased in response to application of N and P, but decreased when ET_C increased. DM yield under ETc₈₀ treatment reduced by 11 and 12%, respectively, compared to ETc₁₀₀ and ETc₁₂₀ which was due to reduction of cumulative absorbed radiation (R_abs(cum)) and RUE. Under these conditions, changes of stomatal conductance (gs) had little effect on DM yield. It was also found that N limitation caused 11 and 20% reduction in DM yield compared to N₂₀₀ and N₄₀₀, respectively. This yield reduction was mainly the result of decrease in RUE. By decreasing R_abs(cum), P deficiency also reduced DM yield by 5 and 9%, respectively, relative to P₁₀₀ and P₂₀₀ treatments.     

Polyvinylidene fluoride nanofiber coated polypropylene nonwoven fabric as a membrane for lithium-ion batteries

Polyvinylidene fluoride (PVdF) membranes in spite of having many critical properties necessary for lithium-ion batteries, do not have satisfying thermal and mechanical resistance. The goal of this study was to combine the good mechanical and thermal properties of PP nonwoven fabric with the excellent electrochemical properties of PVdF nanofibers to exploit a high-performance membrane for lithium-ion batteries. This work reports the preparation of PVdF nanofiber membranes using electrospinning on a polypropylene (PP) spunbonded nonwoven fabric and an aluminum foil followed by a hot-pressing treatment. The morphology and size of the membranes were studied by the scanning electron microscopy. The tensile strength of the membrane with the PP support was superior to the PVdF membrane. Thermal stability of the prepared membranes was determined using the TGA method and the dimensional stability was investigated by measuring the shrinkage ratio at 105 °C. The results have shown that the PVdF/PP membrane was thermally more stable than the PVdF and the commercial Celgard 2325 membranes. The batteries using PVdF/PP membrane exhibited higher electrochemical oxidation limit, better cycling performance and less discharge capacity fading during 100 cycles compared to PVdF and Celgard membranes. The results of this study showed that PVdF/PP membrane is a promising advanced membrane in lithium-ion batteries.     

Surface wildfire in conifer broad-leaved forests of the Hyrcanian region of Iran: short-term effect on regeneration and damage to trees

Wildfires in recent years have resulted in degradation and damage to the Hyrcanian forest ecosystems in Northern Iran.This study was carried out to investigate fire damage to trees and changes in regeneration in early-season growth after wildfires in the Golestan Province.For this purpose,a random sampling plan was used,with 60 circular plots(each plot is 1000 m2) for each stand and 240 circular(25 m2) plots for regeneration within the burned and unburned areas,respectively.In each plot,habitat factors were recorded,including crown canopy percentage,forest stratum,herb-layer cover percentage,species,diameter at breast height,tree and regeneration quality,and quantity of seedlings and saplings.Our results showed that bark is an important factor for fire resistance in Hyrcanian forests.The Persian ironwood and European yew has the highest and lowest fire resistance;as broad leave species are more resistant than needle leaf species.Density of regeneration in unburned area was higher than burned area,and statistical analysis showed significant differences for all species between two areas.Fire effects on sapling were different among species which indicates sapling has different resistance to fire.Forest floor fuel,season,stand composition and microclimate have more effects on fire severity while environmental factors,regeneration and management practices shaping future composition stands.     

Effect of apple peel extract as natural antioxidant on lipid and protein oxidation of rainbow trout (Oncorhynchus mykiss) mince

International Aquatic Research - The aim of this study was to use apple peel extract (APE) as antioxidant for inhibition of lipid and protein oxidation in rainbow trout (Oncorhynchus mykiss) mince...     

Nonparametric phenotypic stability analysis in advanced barley (<Emphasis Type="Italic">Hordeum vulgare</Emphasis> L.) genotypes

The development of genotypes with adaptation to a wide range of environments is one of the most important goals of plant breeding programs. In order to compare nonparametric stability measures and to identify promising high-yield and stable barley (Hordeum vulgare L.), 20 barley genotypes selected from the Iran/ICARDA joint project and grown in nine environments during 2009-11 in Iran. Four nonparametric statistical tests of significance for genotype × environment (GE) interaction and 10 nonparametric measures of stability were used to identify stable genotypes in nine environments. Results of nonparametric tests of G×E interaction (Kubinger, Hildebrand, and Kroon/ Laan) and a combined ANOVA across environments, indicated the presence of both crossover and non-crossover interactions. Also, only TOP and rank-sum values were positively associated with high yield. Thus, in the simultaneous selection for high yield and stability, only the rank-sum and TOP methods were useful in terms of the principal component analysis results, and correlation analysis of nonparametric stability statistics and yield. According to these stability parameters (TOP and rank-sum), three genotypes (G13, G12, and G17) were the most stable for grain yield. The results also revealed that based on nonparametric test results, stability could be classified into three groups, according to agronomic and biological concepts of stability.     

Dietary zinc requirement of Siberian sturgeon (Acipenser baerii,Brandt 1869) juveniles,based on the growth performance and blood parameters

International Aquatic Research - This study investigated the effect of dietary Zn levels on growth performance, feed utilization, and hematological parameters of juvenile Siberian sturgeon...     

Salinity tolerance of wild barley Hordeum vulgare ssp. spontaneum

Salinity tolerance of 47 wild barley genotypes and six barley cultivars was evaluated under control and salinity stress (300 mM NaCl) conditions. Shoot and root dry weight (DW), plant height, membrane stability index (MSI), relative water content, survival rate, leaf malondialdehyde (MDA) and proline contents, root and leaf Na, K, Ca and K/Na ratio, and chlorophyll a fluorescence were measured. Salinity stress caused significant increase in the MDA, proline content, Na and Ca concentrations of the roots and leaves, but resulted in a decrease in the other traits. H. spontaneum genotypes were considerably less affected by the salinity than the genotypes of H. vulgare. Plant survivability was negatively correlated with the Na concentration (r =−.66) but positively correlated with the leaf K/Na ratio (r = .67) and MSI (r = .68). Tolerance mechanisms such as ion exclusion (Na) were likely to be present in the wild barley causing K/Na homeostasis as well as the much lower root and shoot Na, resulting in the higher survival rate.