Molecular and morphological characterization of Ektaphelenchoides maafiae n. sp. (Nematoda: Ektaphelenchinae) from northern forests of Iran

Ektaphelenchoides maafiae n. sp. was isolated during a survey of nematodes associated with bark samples of an oak tree (Quercus castaneifolia) in Gorgan, Golestan Province, northern Iran. The new species has a body length of 480–546 μm (in females) and 431–480 μm (in males). The cuticle is weakly annulated, with three lateral lines. Lip region offset. The stylet is 13–15 μm long without basal swellings. The excretory pore is located at the level of the metacorpus base to slightly posterior, and hemizonid is at 15–17 μm posterior to the excretory pore. The post‐uterine sac is short, 6–8 μm long. Spicules having rounded condylus, rostrum short, conical with bluntly pointed tip, a cucullus (apophysis) presented on the dorsal distal end. Male tail bearing four (2 + 2) caudal papillae, conical, with sharply pointed terminus. The new species is close to four known species of the genus, including E. hunti, E. ruehmi, E. caspiensis and E. poinari, but differs from them by body size, shape of tail terminus, stylet length, shape and size of spicules, length of post‐vulval uterine sac and number of caudal papillae. Phylogenetic analysis based on small subunit (SSU) and partial large subunit (LSU) sequences of rDNA confirmed its status as a new species.     

Sulphate Adsorption in Soils of North and Northeast Iran

Abstract

Gypsum (CaSO₄ · 2H₂O) is used in agriculture both as a source of calcium (Ca) and sulphate (SO₄ ^2?) and as an amendment to improve soil structure. The effect of gypsum on the adsorption of SO₄ ^2? in irrigated and nonirrigated soils was examined. Almost all of the indigenous sulphate (SO₄) in a range of Golesthan and North Khorasan soils with moderate pH values (>6) was found to be present in the soil solution and, as a consequence, was highly susceptible to leaching. The adsorption of sulphate to the soils receiving no gypsum was greater with correlation coefficient of r=0.91 at 0 kg S ha^?1 as compared to the soils received 40 kg ha^?1 of gypsum as fertilizer with the value of r=0.88 in Golesthan Province. The same trend was observed in Khorasan Province with r=0.79 and r=0.75 with soils receiving 0 and 40 kg S ha^?1, respectively. The results were more pronounced in irrigated fields for both provinces. The amount of sulphate adsorption in Golesthan Province soils was comparatively greater than soils of Khorasan Province. The results raise questions regarding the efficiency of SO⁴‐containing fertilizers in correcting and preventing S deficiency in situations where leaching is a concern.     

Molecular detection of Coxiella burnetii in horse sera in Iran

Coxiella burnetii is a zoonotic bacterium that can infect a wide range of animals including horses. However, its circulation dynamics in and through horses are still unclear. The aim of this study was to evaluate prevalence of C. burnetii and its genomic characteristics in horse sera samples in the North of Iran (Golestan Province). The samples were collected in 2018 and the age, sex, and breed of each animal were recorded. Nested-PCR was used to detect C. burnetii based on the presence of the transposable gene IS1111. The results showed that 7.50 % (P < 0.05; 95 % CI: 0.5 %–0.12 %) of the examined sera samples were positive for C. burnetii. Based on the resuls, prevalence of C. burnetii in the age groupof < Years 1–5 (p-value <0.05, 95 % CI: 1 %–8 %) was less than the age group of >6 years old (p-value <0.05, 95 %, CI: 7 %–19.8 %). In previous studies, it was concluded that the horses' population in Golestan Province should be considered as an important factor in the epidemiology of Q fever and consequently in public health. Further studies should be implemented to evaluate if horses may be relevant indicators of zoonotic risk in urban and suburban endemic areas.     

Assessment of deforestation impact on soil erosion in loess formation using 137Cs method (case study: Golestan Province,Iran)

Golestan, a province in the North-East of Iran, is characterized by high coverage of loess deposits. Since 1963, the area has experienced approximately 200,000 ha deforestation due to land-use changes in agriculture and increasing demand for wood. Approximately, 110,000 ha of the clear-cut lands are under dry-farming, mainly for wheat cropping, and about 86,000 ha have been reforested. This IAEA funded project is the first attempt to use nuclear techniques in the East of Hircanian Forest for determination of on-site impacts of deforestation due to two land-use changes (i.e. dry farming and reforestation). Practicing long-term dry-farming led to 60% soil losses with a mean rate of 2 mm per year. The net erosion rate of croplands on loess deposits in the study area was 32.27 t ha⁻¹ yr⁻¹. Reforestation, cultivation of even-aged Cypress trees since 1993, showed 13 to 60 percent effectiveness in soil conservation. Dry-farming land use resulted in the loss of 95 t ha⁻¹ soil organic carbon (SOC) stock at a mean rate of 1.7 t ha⁻¹ over 54 years. Cultivating Cypress trees successfully restored the SOC content by 100% compared with the SOC in original forests. The conversion of dry-farming lands to orchards of olive trees since 2004, brought more income for farmers but were less effective in soil conservation because of low canopy cover of olive trees. Our data provide key information and guidance for land users and decision-makers about implementing strategic and sustainable conservation practices to restore degraded land.     

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.