Calibration and validation of four common ET0 estimation equations by lysimeter data in a semi-arid environment

In this study, four different methods for reference crop evapotranspiration (ET₀) were calibrated and validated for estimation of daily to mean monthly ET₀ by weighing lysimeter data during 2005–2006 and 2004–2005, respectively, in a semi-arid region. The value of the constant in the Hargreaves–Samani method changed from 0.0023 to 0.0026 for daily to mean monthly ET₀, and can be used in stations with only air temperature data. The constant of the aerodynamic resistance equation in the FAO-56 Penman–Monteith method (208.0) changed to 85.0. The value of coefficient a in the FAO-24-Radiation method was between ?0.5 and ?0.67. Further, the empirical equations were modified to estimate the value of b in the FAO-24-Radiation method and C in the FAO-24 corrected Penman method. The results showed that the modified FAO-56, corrected Penman–Monteith and FAO-24-Radiation methods are the most appropriate for estimating daily to mean monthly ET₀. Furthermore, the modified FAO-24 corrected Penman method was ranked in fourth place and its accuracy was lower than that of the other methods. However, it is appropriate for estimating mean monthly ET₀. Smoothing the daily data decreased the fluctuation in measured daily weather data and ET₀ measured by lysimeter, and consequently resulted in a higher accuracy in the estimation of daily ET₀.     

Physiological characteristics and irrigation water productivity of quinoa (Chenopodium quinoa Willd.) in response to deficit irrigation imposed at different growing stages—A field study from Southern Iran

Iran has been faced to drought during last decades, and one way to overcome this phenomenon is to improve the water productivity by introducing new crops tolerant to water stresses such as quinoa. Two-year field experiment was performed to find out the response of quinoa (cv. Titicaca) to deficit irrigation imposed at different growing stages. Hence, the effect of full irrigation (100% irrigation water requirement) and deficit irrigation (50% full irrigation) on physiological parameters, yield, irrigation water productivity and root density of quinoa was investigated during 2016 and 2017 growing seasons. The result showed that there was a significant difference between all variables in two years. Higher average air temperature in 2017 (2.0°C) resulted in a reduction of seed yield and water productivity (55% and 40% of that obtained in 2016, respectively). Application of deficit irrigation during different growing stages reduced crop height, stomatal conductance and seed yield, while it increased the root length density in both years. In conclusion, flowering stage of quinoa was very sensitive to deficit irrigation, and irrigation at grain filling stage would not help to recover the seed yield. Furthermore, the seed yield was lower than that obtained in other studies performed in other countries using same quinoa cultivar, which could be due to higher amount of applied irrigation water and different phenology under different climatic conditions. A decision on cultivating this crop under semi-arid conditions has to be made considering limited water resources.     

Soil seed banks in the Arasbaran Protected Area of Iran and their significance for conservation management

The Arasbaran Protected Area is an important but little studied nature reserve in NW Iran. In the past habitat heterogeneity and biodiversity have been threatened by over-exploitation; in the future depopulation may lead to partial abandonment. The soil seed bank was examined to see whether there are sufficient species represented as persistent seeds to reconstitute the vegetation in the event of habitat deterioration. There were differences between seed banks from different soils and vegetation types but essentially all soil seed banks contained few species and low densities of seed. Moreover, the species in the seed bank were unrepresentative of the vegetation. During future periods of changing land use it will be important to maintain the existing vegetation. There are however indications of successful recent conservation management. Annuals are abundant in the woodland seed bank but absent from the vegetation. The forest is recovering from the disturbance of collecting fire-wood.     

Comparison of Different Methods of Estimating Saffron Yield Based on Soil Properties in Golestan Province

ABSTRACT

Evaluation of the relationship between soil properties and saffron yield estimation may contribute to agricultural planning in finding suitable lands for the growth of this valuable product. This study aimed to investigate the performance of artificial neural network (ANN), multiple linear regression (MLR), and adaptive neuro-fuzzy inference system (ANFIS) in terms of saffron yield estimation in some lands of Golestan province, Iran. To this end, 100 areas under saffron cultivation were selected. For rapid and low-cost saffron yield estimation, six different models were designed based on soil properties as inputs using MLR, ANN, and ANFIS methods. According to the results, ANN showed the highest accuracy (R² = 0.58–0.89) in estimating saffron yield as compared to MLR (R² = 0.41–0.47) and ANFIS (R² = 0.41–0.69) models. A comparison of the results obtained from the six models defined in these three methods indicated that Model 4 (R² _Reg = 0.45, R² _ANFIS = 0.57, R² _ANN = 0.87), with the inputs, organic phosphorus, potassium, and calcium carbonate, was the best model in terms of accuracy and speed in estimating saffron yield phosphorus. The RI indexes for ANN in the model were 50% and 34% relative to MLR and ANFIS, respectively, demonstrating the higher accuracy of ANN in saffron yield estimation. The study results can be used to identify lands suitable for saffron cultivation in the study area using organic phosphorus and organic matter levels in the soil.     

Development of a monoclonal immunoassay selective for chlorinated cyclodiene insecticides

Organochlorine pesticides still generate public health concerns because of their unresolved health impact and their persistence in living beings, which is demanding appropriate analytical techniques for their monitoring. In this study, an enzyme-linked immunosorbent assay based on monoclonal antibodies (MAbs) for the detection of an important group of organochlorine pesticides, the cyclodiene group, has been developed. With this aim, several hapten-protein conjugates, characterized by exposure of the common hexachlorinated bicyclic (norbornene) moiety and differing in the linking structure to the carrier protein, were prepared. From mice immunized with these conjugates, several MAbs with the ability to sensitively bind the majority of cyclodienes were obtained. Among them CCD2.2 MAb displaying the broadest recognition to cyclodiene compounds (endosulfan, dieldrin, endrin, chlordane, heptachlor, aldrin, toxaphene: I(50) values in the 6-25 nM range) was selected for the assay. Interestingly, this MAb showed certain stereospecificity toward other polychlorinated cycloalkanes because the gamma-isomer of hexachlorocyclohexane (lindane) was also very well recognized (I(50) value of 22 nM). This immunoassay is potentially a very valuable analytical tool for the rapid and sensitive determination of cyclodiene insecticides and related compounds, which in turn may contribute to the understanding of the biological activities and of the overall environmental impact of these persistent organic pollutants.     

Full-genome characterization and genetic analysis of a H9N2 virus in commercial broilers in Iran, 2017

Tropical Animal Health and Production - Since 1998, Iran’s poultry industry has faced several outbreaks of low pathogenic avian influenza H9N2. Tissue samples were collected from a broiler...     

Potassium release from sand,silt and clay fractions in calcareous soils of southern Iran

The release of non-exchangeable potassium from 24 calcareous soils of divergent mineralogy, from southern Iran, was examined. Sand, silt and clay particles were fractionated after dispersion with an ultrasonic probe. Samples were extracted with 0.01 M CaCl₂ for 30 successive 2-h periods. The clay fraction released the largest amount of K in each soil. Cumulative K released ranged from 175 to 723, 35 to 128, and 71 to 146 mg kg^?1 contributing 20–90, 4–39 and 2–54% for clay, silt and sand fractions, respectively. The lower proportion of K released from sand and silt fractions can be explained by the presence of a high content of CaCO₃ and quartz in these fractions. The release kinetics for the non-exchangeable K data showed that parabolic diffusion and power function were the best fitting kinetic models. This indicated that slow diffusion of K from the mica interlayer positions is the main rate-controlling process. Cumulative K released and constant b values of parabolic diffusion model correlated significantly with the mica content of the clay fraction.     

EFFECTS OF PHYTOHORMONES ON PROLINE CONTENT AND ANTIOXIDANT ENZYMES OF VARIOUS WHEAT CULTIVARS UNDER SALINITY STRESS

Salinity stress is one of the important agricultural problems in the world. A factorial experiment based on completely randomized design with four replications was conducted to evaluate the effects of phytohormones (gibberellic acid and abscisic acid) on the activity of antioxidant enzymes (peroxidase, superoxide dismutase and catalase), rubisco activity and content, and proline in three wheat cultivars (Gascogen, Zagros, and Kuhdasht) under control and salinity stress (3.5 and 7 dS m^?1). The results showed that salinity stress (3.5 and 7 dS m^?1) decreased the activity of catalase, rubisco, carboxylase, but increased peroxidase, superoxide dismutase activity and proline content. Gibberellic acid caused 58.03% increased in rubisco carboxylase activity in Zagros at 7 dS m^?1 in comparison with abscisic acid under salinity stress compared with the control plants in Kuhdasht. Activity of superoxide dismutase in Kuhdasht cultivar at 7 dS m^?1 salinity level showed 76.43% increased in Gascogen under salinity stress compared with the control plants with gibberellic acid application. The highest proline content as an osmolyte was found in Zagros at 7 dS m^?1 salinity level with abscisic acid (194 μmol g^?1 DM) application. Peroxidase activity increased 83.31% and catalase activity decreased 61.27% compared with the control plants in Zagros. Gibberellic acid application significantly prevented reduction in rubisco content under salinity stress. In conclusion, increased in peroxidase and superoxide dismutase activity and proline content decreased the adverse effects of salinity stress on studied cultivars. Also, the foliage spray of gibberellic acid enhanced and improved the growth condition. In this experiment, Zagros cultivar showed more tolerance to salinity stress than the other two cultivars.     

Surface drainage nitrate loading estimate from agriculture fields and its relationship with landscape metrics in Tajan watershed

Pasture, forest, and farmland are the dominant land covers in the Tajan River watershed and this landscape status has a direct connection with nitrate pollution. Understanding the correlations between landscape variables and nitrate pollutant is a priority in order to assess pollutants loading and predicting the impact on surface water quality. The soil and water assessment tool was used to simulate nitrate loads in different land cover types in different years. The landscape pattern was calculated by FRAGSTATS. The contributing share of each land use/land cover shows nitrate pollutant produced by grassland (5.7%) and forest (29%) are less than those produced by agricultural land (64.2%). Agricultural land was identified as the main source of nitrate pollution. Paddy fields and orchards had the most intensive soluble nitrate loss especially in spring and summer. Statistical analysis indicated that nitrate was positively associated with patch density, edge density, patch number, total edge, effective mesh size, largest patch index, and landscape shape index (p ≤ 0.01). We then analyzed how nitrate was related to landscape attributes in six different sites. Also the regression analysis results suggested that landscape metrics could account for more than 94% of the variance of nitrate in the whole catchment. The regression models confirmed the great importance of the agriculture metrics and forest metric in predicting nitrate in watershed. Defining the generation and extent of pollution in this particular watershed which discharges into the Caspian Sea can constitute an important step toward protecting this ecosystem.     

Elucidate Genetic Diversity and Population Structure of Bread Wheat (Triticum Aestivum L.) Cultivars Using IRAP and REMAP Markers

Journal of Crop Science and Biotechnology - Analysis of genetic diversity and population structure in bread wheat is an essential step in their conservation, utilization, and breeding....