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Soil bulk density (ρb) is an important indicator of soil quality, productivity, compaction and porosity. Despite its importance, ρb is often omitted from global datasets due to the costs of making many direct ρb measurements and the difficulty of direct measurement on rocky, sandy, very dry, or very wet soils. Pedotransfer functions (PTFs) are deployed to address these limitations. Using readily available soil properties, PTFs employ estimator equations to fit existing datasets to estimate properties like ρb. However, PTF performance often declines when applied to soils outside those in the training dataset. Potentially, recalibrating existing PTFs using new observations would leverage the power of large datasets used in the original PTF derivation, while updating information based on new soil observations. Here, we evaluate such a recalibration approach for ρb estimation, benchmarking its performance against two alternatives: the original, uncalibrated PTFs, and novel, local PTFs derived solely from new soil observations. Using a ρb dataset of N = 360 total observations obtained in West Azerbaijan, Iran, we varied the local dataset size (with N = 15, 30, 60, and 360) and recalibrated four existing PTFs with these data. Local PTFs were generated based on stepwise multiple linear regression for the same datasets. The same PTFs (original, recalibrated, and local) were also applied to the study area, and the resulting ρb estimates were compared with the global SoilGrids dataset. Recalibration of PTFs reduced errors relative to the original uncalibrated PTFs; for instance, the NSE increased from −22.07 to 0.30 (uncalibrated) to 0.20–0.41 (recalibrated), and RMSE decreased from 0.12 to 0.60 Mg m−3 (uncalibrated) to 0.10–0.13 Mg m−3 (recalibrated). The recalibrated PTFs performance was comparable to or better than local PTFs applied to the same data. Recalibration of existing PTFs with local/regional uses provides a viable alternative to the use of global datasets or the development of local PTFs in data‐scarce regions. Highlights: Existing global PTFs were calibrated and tested using a small dataset for local utilisation.Several new local PTFs were also developed using the same datasets.Recalibration of existing global PTFs is comparable to or more accurate than developing new PTFs. [ABSTRACT FROM AUTHOR]

Soil nutrients are the key factors in soil fertility, which have important roles in plant growth. Determining soil nutrient contents, including macro and micronutrients, is of crucial importance in agricultural productions. Conventional laboratory techniques for determining soil nutrients are expensive and time-consuming. This research was aimed to develop linear regression (LR) models for remote sensing of total nitrogen (TN) (mg/kg), available phosphorous (AP) (mg/kg), available potassium (AK) (mg/kg), and micronutrients such as iron (Fe) (mg/kg), manganese (Mn) (mg/kg), zinc (Zn) (mg/kg), and copper (Cu) (mg/kg) extracted by DTPA in rain-fed agricultural lands in the northwest of Iran. First, 101 soil samples were collected from 0–30 cm of these lands and analyzed for selected nutrient contents. Then a linear regression along with principal component analysis was conducted to correlate soil nutrient contents with reflectance data of different Landsat OLI bands. Finally, the spatial distributions of soil nutrients were drawn. The results showed that there were linear relationships between soil nutrient contents and standardized PC1 (ZPC1). The highest significant determination coefficient with an R2 value of 0.46 and the least relative error (%) value of 11.97% were observed between TN and ZPC1. The accuracy of the other LR's developed among other soil nutrient contents and remotely sensed data was relatively lower than that obtained for TN. According to the results obtained from this study, although remote sensing techniques may quickly assess soil nutrients, new techniques, technologies, and models may be needed to have a more accurate prediction of soil nutrients. [ABSTRACT FROM AUTHOR]

Pseudomonas aeruginosa (P. aeruginosa) is a common bacteria associated with burn infections and resistance to a wide range of disinfectants and antimicrobial agents which is able to produce different virulence factors. In this study, the susceptibility of P. aeruginosa isolates from the burn (burn=57) and hospital environment (HE=19) to antimicrobial agents and chemical disinfectants was determined by disc and well diffusion agar method, respectively. The results showed 100% sensitivity to polymyxin B, while sensitivity to other agents was low and ranged from 40.8% for imipenem and amikacin to 6.6% for ceftizoxime. Among the disinfectant used, the mean diameter of inhibition zones (DIZ) was higher for Deconex, while nitrofurazone had the lowest DIZ. In most cases, the HE isolates were significantly more susceptible to disinfectants and antimicrobial agents compared to burn isolates (P=0.01). The genes for the exoenzyme T, Y, U, and S were detected in 100%, 89.8%, 43.4%, and 48.7% of the isolates, respectively. The prevalence of exo U and exoY was significantly higher in the burn isolates compared to HE isolates (P=0.001). The results of this study indicate a significantly higher level of resistance against the majority of the antimicrobial agents in the burn isolates compared to HE isolates, which was significantly higher than the environmental isolates. The prevalence of T3SS effectors proteins and their pattern were also different in the burn, and the HE isolates, indicating a divergence in pathogenicity of the burn isolates from those of the environmental isolates. [ABSTRACT FROM AUTHOR]

• Study addresses adoption of conservation agricultural initiatives (CAIs). • Compatibility and observability affect adoption. • Farm revenue affects CAIs adoption. • Electrical conductivity and organic carbon content are significantly different between the two groups of farms. • Topographical information indicates that CAIs farms are with a gradient of less than 5%. Over the past decades, agro-ecological measures, such as conservation agricultural initiatives (CAIs) have been widely implemented in developing countries, in like manner with Tabriz city as would be a leading case situated in northwest Iran. In light of linear discriminant analysis (LDA), this cross-sectional research calls on a knowledge gap respecting the differentiation of farmers who become involved in CAIs (adopters) from those not involved (non-adopters), as three data modules, including attitudinal, soil testing, and topographical data, were used. The study takes advantage of a sample of 382 respondents, stratified as regards the geographical location of their farms. Using theory-triangulation, the theoretical foundation enfolds demographic theory, the theory of planned behavior, innovation diffusion model, and resource-based model. The results of hierarchical LDA provide evidence that the hypothesized model is entitled to be fitted with data and accordingly three variables including (1) observability, (2) farm revenue, and (3) compatibility ascertain adopter farmers from non-adopter ones. Furthermore, it was revealed that the soil dynamic quality features, such as electrical conductivity, EC, (dS m−1) (Mann-Whitney U = 353, P < 0.05) and organic carbon content, OC (%), (Mann-Whitney U = 935.5, P < 0.05) were significantly different between the two groups of farms, while carbonate calcium equivalent, CCE (%) (Mann-Whitney U = 935.5, P > 0.05) showed no significant differences. Likewise, the topographical data analyzed in ArcGIS software make manifest that CAIs farms have more steady topographic features rather non-CAI farms and are also situated in the regions with a gradient of less than 5%. In conclusion, the paper delivers management implications for the agricultural extension and authorities of the agricultural research centers who tend to promote CAIs in on-site and off-site farmlands. [ABSTRACT FROM AUTHOR]

This study reviews the history of seismometry in Iran and specifically the evolution of Iranian Seismological Center's (IRSC) seismic network and investigates the artifacts and systematic errors of this center's earthquake catalog. Our analysis indicates instability of magnitude estimation in the IRSC catalog to the extent that in the western and eastern parts of Iran, events with the same USGS reported mb magnitude could result in MN values 0.3 units apart. This catalog is contaminated with quarry and mine blasts, in which about 19% of the reported events are most likely not tectonic earthquakes. In addition, heterogeneity of magnitude of completeness as a function of space and time is observed. While Mc has gradually improved since 2006, its reduction in different parts of the country varies between 0 to 0.5 units of magnitude. In addition to artifacts, more than 54% of the reported events were located using a simplified velocity model and need to be relocated using more accurate velocity models. Moreover, in the hypocenter determination of about 7% of earthquakes, at least data from one station with wrong coordinates was employed. For these two groups of events, a clear dependence exists between the azimuthal gap and the value of the observed shift in the location parameters; with increasing the azimuthal gap, the shift increases. Investigations on the manually picked phases in the IRSC catalog show a large number of phase misidentification cases which are the other source of systematic errors. Examining the depth reported for events associated with mine blasts in a region in southern Iran implies systematic errors and high overestimation of depth for these events. The reported depth for most of these blasts is more than 10 km. [ABSTRACT FROM AUTHOR]

Under the fifth strategic development plan of Iran, the government is necessitated to trigger the agro-ecological initiatives like conservation agriculture (CA) by stimulating farmers to become involved in the schemes as efficiently as possible, along the lines of global policies to enhance environmentally-friendly development. This study, as being the case, calls for the knowledge gap of motivation-intention-behavior, investigating the association of diverse motivations of 382 farmers in Tabriz, East Azerbaijan, with the soil conservation behavior (SCB), also inclusive of the contribution of CA features, including relative advantage, compatibility, complexity, observability, and testability, as the farmers were stratified to low and high SCB. The theoretical framework consists of the theory of planned behavior (TPB) and motivational model (MM), the former is commonly used and the latter has the potential to be given much attention, conceptualized by well-being, identity, hedonistic, and idealistic concepts. The study provides evidence that 70.42% of farmers adhere to and carry out SCB at a low rate; whereas, 29.58% of the rest has a high adoption rate. The results also illustrate that attitude towards CA contributes to influencing SCB, as well as the significant and positive impact of PBC on behavioral intention and SCB. While well-being motivation has a negative impact on attitude towards CA, behavioral intention, and SCB, identity and hedonistic motivations have a significant and positive impact on attitude and SCB that are mediated by behavioral intention. The paper concludes that (1) the agricultural extension needs to change farmers' attitudes by making farmers aware of the relative advantage, compatibility, and testability of CA, (2) farmers should receive technical, financial, and educational support to increase their volitional control on CA, (3) it is strongly suggested addressing the primary obstacles to SCB, which are facilitated by delivering the subsidized agricultural inputs (e.g., fertilizer, fuel, and livelihoods) to farmers with well-being motivations, (4) the agricultural extension is also recommended recognizing farmers with identity and hedonistic incentives, they are as a reference group and are imitated by non-adopter or slowly adopter farmers. • Study addresses the intake of conservation agriculture. • Attitude towards conservation agriculture affects soil conservation behavior. • Behavioral control affects behavioral intention and soil conservation behavior. • Well-being motivations affect attitude towards conservation agriculture negatively. • Identity and hedonistic motivations affect intention and soil conservation behavior. [ABSTRACT FROM AUTHOR]