Characterizing Spatial Variability of Soil Textural Fractions and Fractal Parameters Derived from Particle Size Distributions

Soil particle size distribution (PSD) is a fundamental physical property affecting other soil properties. Characterizing spatial variability of soil texture is very important in environmental research. The objectives of this work were: 1) to partition PSD of 75 soil samples, collected from a flat field in the University of Guilan, Iran, into two scaling domains using a piecewise fractal model to evaluate the relationships between fractal dimensions of scaling domains and soil clay, silt, and sand fractions and 2) to assess the potential of fractal parameters as an index used in a geostatistical approach reflecting the spatial variability of soil texture. Features of PSD of soil samples were studied using fractal geometry, and geostatistical techniques were used to characterize the spatial variability of fractal and soil textural parameters. There were two scaling domains for the PSD of soil samples. The fractal dimensions of these two scaling domains (D₁ and D₂) were then used to characterize different ranges of soil particle sizes and their relationships to the soil textural parameters. There was a positive correlation between D₁ and clay content (R² = 0.924), a negative correlation between D₁ and silt content (R² = 0.801), and a negative correlation between D₂ and sand content (R² = 0.913). The geometric mean diameter of soil particles had a negative correlation with D₁ (R² = 0.569) and D₂ (R² = 0.682). Semivariograms of fractal dimensions and soil textural parameters were calculated and the maps of spatial variation of D₁ and D₂ and soil PSD parameters were provided using ordinary kriging. The results showed that there were also spatial correlations between D₁ and D₂ and particle size fractions. According to the semivariogram models and validation parameters, the fractal parameters had powerful spatial structure and could better describe the spatial variability of soil texture.     

利用人工神经网络以及相关地形属性绘制数字土壤地图

Detailed soil surveys involve costly and time-consuming work and require expert knowledge. Since soil surveys provide information to meet a wide range of needs, new methods are necessary to map soils quickly and accurately. In this study, multilayer perceptron artificial neural networks (ANNs) were developed to map soil units using digital elevation model (DEM) attributes. Several optimal ANNs were produced based on a number of input data and hidden units. The approach used test and validation areas to calculate the accuracy of interpolated and extrapolated data. The results showed that the system and level of soil classification employed had a direct effect on the accuracy of the results. At the lowest level, smaller errors were observed with the World Reference Base (WRB) classification criteria than the Soil Taxonomy (ST) system, but more soil classes could be predicted when using ST (7 soils in the case of ST vs. 5 with WRB). Training errors were below 11% for all the ANN models applied, while the test error (interpolation error) and validation error (extrapolation error) were as high as 50% and 70%, respectively. As expected, soil prediction using a higher level of classification presented a better overall level of accuracy. To obtain better predictions, in addition to DEM attributes, data related to landforms and/or lithology as soil-forming factors, should be used as ANN input data.     

Control of weed barley species in winter wheat with sulfosulfuron at different rates and times of application

Field experiments were conducted at five locations in the major wheat production regions of Iran to evaluate the efficacy of sulfosulfuron in controlling weed barley species (including Hordeum spontaneum , Hordeum murinum , Hordeum distichon , and Hordeum vulgare ) in the 2004–2005 and 2005–2006 growing seasons. Sulfosulfuron was applied either postemergence (POST) or preplant-incorporated (PPI) at 0, 20.25, 30.75, 40.5, 51.0, 60.75 or 71.25 g ai ha⁻¹ to plots arranged in a randomized complete block design with four replications. Sulfosulfuron at the recommended rate (20.25 g ai ha⁻¹) failed to provide acceptable control of the weed barley species. However, the level of control increased with the application rate, particularly at rates >51.0 g ai ha⁻¹. Generally, PPI-applied sulfosulfuron resulted in markedly greater control levels than those of a POST application and complete control of H. murinum and H. vulgare was achieved with PPI-applied sulfosulfuron at all rates >20.25 and 30.75 g ai ha⁻¹, respectively. In most cases, the wheat yield increased with the application rate without any crop injury. The highest yield increase (186%) was obtained with a PPI application of 71.25 g ai ha⁻¹.     

基于人工神经网络的数据处理和多目标群方法用土壤传递函数(PTFs)估算保水性

Pedotransfer functions(PTFs) have been developed to estimate soil water retention curves(SWRC) by various techniques.In this study PTFs were developed to estimate the parameters(θ s,θ r,α and λ) of the Brooks and Corey model from a data set of 148 samples.Particle and aggregate size distribution fractal parameters(PSDFPs and ASDFPs,respectively) were computed from three fractal models for either particle or aggregate size distribution.The most effective model in each group was determined by sensitivity analysis.Along with the other variables,the selected fractal parameters were employed to estimate SWRC using multi-objective group method of data handling(mGMDH) and different topologies of artificial neural networks(ANNs).The architecture of ANNs for parametric PTFs was different regarding the type of ANN,output layer transfer functions and the number of hidden neurons.Each parameter was estimated using four PTFs by the hierarchical entering of input variables in the PTFs.The inclusion of PSDFPs in the list of inputs improved the accuracy and reliability of parametric PTFs with the exception of θ s.The textural fraction variables in PTF1 for the estimation of α were replaced with PSDFPs in PTF3.The use of ASDFPs as inputs significantly improved α estimates in the model.This result highlights the importance of ASDFPs in developing parametric PTFs.The mGMDH technique performed significantly better than ANNs in most PTFs.     

Specificity of polyclonal antibodies to different antigenic preparations of Pseudomonas syringae pv. pisi strain UQM551 and Pseudomonas syringae pv. syringae strain L

Polyclonal antibodies were produced against sonicated and heat-killed cells of Pseudomonas syringae pv. pisi strain UQM551 and Pseudomonas syringae pv. syringae strain L, and their specificities were compared. Evidence is presented that the serological specificity between these two pathovars lies in surface antigens. Of the surface antigens purified and tested, only flagella and lipopolysaccharide from the cell wall showed no cross-reactivity with heterologous antisera. Antisera to glutaraldehyde-fixed flagella of the two strains showed a high level of specificity. At a species or genus level, antisera prepared from heat-killed cells of P. syringae distinguished this species from all other bacterial species and genera tested, including strains of Pseudomonas fluorescens, Escherichia coli, Agrobacterium and Rhizobium.     

Weed control in irrigated corn by hairy vetch interseeded at different rates and times

In order to study the potential of interseeded hairy vetch as a living mulch to control weeds in corn, a field study was conducted at the Agricultural Research Farm, Razi University, Kermanshah, Iran. The experiment was carried out in a split-split plot arrangement with four replications. The main plots were two weed treatments (weedy and weed-free for all of the growing season), the subplots were two hairy vetch planting dates (simultaneous with corn planting and 10 days after corn emergence), and the sub-subplots were three hairy vetch planting rates (0, 25, and 50 kg ha⁻¹). The results indicated that the weedy condition for all of the growing season reduced corn plant traits, including the seed yield, number of ears per plant, number of seeds per ear, 100-seed weight, height, Leaf Area Index, and leaf chlorophyll content, as compared to the weed-free condition for the entire growing season. The hairy vetch dry weight also was reduced by the full-season weedy condition. The traits under study were not significantly influenced by the hairy vetch planting times, but increasing the hairy vetch planting rate from 0 to 50 kg ha⁻¹ improved the corn yield, number of seeds per ear, 100-seed weight, height, Leaf Area Index, and leaf chlorophyll content. However, the number of ears per plant was not significantly influenced and the weed dry weight was reduced by half. Overall, from the standpoint of corn seed production, an interseeding amount of 25 kg ha⁻¹ of hairy vetch is recommended; taking into consideration the legume forage yield, an interseeding amount of 50 kg ha⁻¹ of hairy vetch is more beneficial.     

Effects of Haloxylon spp. of Different Age Classes on Vegetation Cover and Soil Properties on an Arid Desert Steppe in Iran

In arid regions, afforestation has been considered as a method for ecological revival in terms of vegetation enrichment and soil amelioration. In this study, the effects of afforestation with Haloxylon spp. on vegetation cover and soil properties were measured < 3, 3, 6, and 25 years after planting in an arid desert in Iran. Soil samples were collected at two depths (0-30 and 30-60 cm) under and between shrub canopies. Afforestation succession significantly affected plant community characteristics. In total, 16 species from 8 families and 15 genera were observed along the afforestation successional gradient. Plant species richness and diversity and vegetation cover increased slowly during the succession, and reached the maximum values in the area where Haloxylon had been planted for 25 years. Soil nutrient values gradually increased during the succession, and the levels of organic matter, total nitrogen, available potassium, and available phosphorus were significantly higher under Haloxylon canopies than between them. Afforestation reduced soil pH under and between Haloxylon canopies during the succession, while soil electrical conductivity followed an opposite pattern. Haloxylon planting increased the silt content in the 0-30 cm soil layer. Our results suggest that Haloxylon establishment plays an important role in the reestablishment of desertified ecosystems in arid regions.     

基于地形属性使用回归, 克里格和人工神经网络方法估算饱和导水率空间分布

Several methods,including stepwise regression,ordinary kriging,cokriging,kriging with external drift,kriging with varying local means,regression-kriging,ordinary artificial neural networks,and kriging combined with artificial neural networks,were compared to predict spatial variation of saturated hydraulic conductivity from environmental covariates.All methods except ordinary kriging allow for inclusion of secondary variables.The secondary spatial information used was terrain attributes including elevation,slope gradient,slope aspect,profile curvature and contour curvature.A multiple jackknifing procedure was used as a validation method.Root mean square error (RMSE) and mean absolute error (MAE) were used as the validation indices,with the mean RMSE and mean MAE used to judge the prediction quality.Prediction performance by ordinary kriging was poor,indicating that prediction of saturated hydraulic conductivity can be improved by incorporating ancillary data such as terrain variables.Kriging combined with artificial neural networks performed best.These prediction models made better use of ancillary information in predicting saturated hydraulic conductivity compared with the competing models.The combination of geostatistical predictors with neural computing techniques offers more capability for incorporating ancillary information in predictive soil mapping.There is great potential for further research and development of hybrid methods for digital soil mapping.     

地质统计学评估伊朗伊斯法罕城市采矿过渡区近地表土壤上铅锌镉的污染

Due to the lack of regulation and environmental education and awareness, Sepahanshahr located in vicinity of Isfahan City, central Iran, is now a rapid growing residential area suffering from the considerable consequences of poorly regulated mining activities operating in its vicinity. A survey was carried out on soil Pb, Zn and Cd concentrations around Sepahanshahr Town to explore the spatial structure of Pb, Zn and Cd distribution and to map their concentrations using geostatistical techniques. 100 near-surface soil samples were collected and analyzed for Pb, Zn and Cd and some related soil physical and chemical variables such as pH, organic matter content, electrical conductivity, and clay, silt and sand contents. The variography results showed a strong spatial dependency in heavy metals concentration due to the dilution effects of natural factors including atmospheric dispersion and precipitation. The almost same range values calculated for both ln-transformed Pb and sand data suggested presence of spatial co-regionalization. However, ln-transformed Zn data showed a shorter spatial dependency among the three tested heavy metals. Kriged maps of all three heavy metals showed a strong gradient of contamination around the three mining sites activating in the area. The results of this study provide insight into identification of the extent and spatial variability of Pb, Zn and Cd pollution in the mining sites and surrounding urban areas.     

Genotype×tillage interaction and the performance of winter bread wheat genotypes in temperate and cold dryland conditions

Growing concerns for food security and the alleviation of hunger necessitate knowledge-based crop management technologies for sustainable crop production. In this study, 13 winter bread wheat genotypes (old, relatively old, modern, and breeding lines) were evaluated under three different tillage systems, i.e., conventional tillage (CT, full tillage with residue removed), reduced tillage (RT, chisel tillage with residue retained) and no-tillage (NT, no-tillage with residue retained on the soil surface) in farmer's fields under rainfed conditions using strip-plot arrangements in a randomized complete block design with three replications in the west of Iran (Kamyaran and Hosseinabad locations) over two cropping seasons (2018–2019 and 2019–2020).The main objectives were to investigate the effects of tillage systems and growing conditions on the agronomic characteristics, grain yield and stability performance of rainfed winter bread wheat genotypes.Significant (P<0.01) genotype×tillage system interaction effects on grain yield and agronomic traits suggested that the genotypes responded differently to the different tillage systems. The number of grains per spike and plant height were positively (P<0.0) associated with grain yield under the NT system, so they may be considered as targeted traits for future wheat breeding. Using statistical models, the modern cultivars (“Sadra” and “Baran”) were identified as high yielding and showed yield stability across the different tillage systems. As per each tillage system, genotype “Sadra” followed by “Zargana-6//Dari 1-7 Sabalan” exhibited higher adaption to CT; while cultivars “Jam” and “Azar2” showed better performance under the RT system; and cultivars “Varan” and “Baran” tended to have better performance expression in the NT condition.The increased grain yields achieved in combination with lower costs and greater profits from conservation agriculture suggest that adapted cultivar and NT systems should be evaluated and promoted more widely to farmers in the west of Iran as an attractive package of crop management technologies.In conclusion, variations in the performance of genotypes and the significant genotype×tillage system interaction effects on grain yield and some agronomic traits assessed in this study suggest that the development and selection of cultivars adapted to the NT system should be considered and included in the strategies and objectives of winter wheat breeding programs for the temperate and cold dryland conditions of Iran.