حمید کوهکن

 Due to Iran's location in the arid and semi-arid region of the world, the possibility of drought is high. Therefore, implementing low irrigation to increase the efficiency of limited water resources is a scientific solution to reduce water consumption. On the other hand, irrigation deficit in cotton  is the most important factor limiting production worldwide, which indicates the need for optimal use of water resources to determine the real water needs of cotton plants. Therefore, development and introduction of drought tolerant cultivars and useful method to improve water productivity and efficiency in the face of drought and water scarcity. The aim of this experiment was to evaluate cotton cultivars by measuring traits related to photosynthetic pigments and yield in order to select drought tolerant cultivars. The present study, evaluated physiological traits of 10 cotton cultivars that were known as tolerant cultivar under irrigation deficit based on the measurement of traits and mechanisms of drought tolerance split-plot arrangement using randomized complete blocks design with three replications in 2021 and 2022 years, in the educational and research farm of Gonbadkavos University (Golestan province), Iran. Experimental research includes two different irrigation regime The main factor of irrigation stress in two levels including low irrigation stress (two times of irrigation in the stages of bud formation and beginning of flowering) and no stress (four times of irrigation in the stages of bud formation, beginning of flowering, beginning of bud formation and beginning of bud opening) and the factor Sub-types of cotton were included in 10 levels (Shayan, Sahel, Sepid, Sajidi, Golestan, Latif, Armaghan, Parto, Mai and Lodos). The studied traits include physiological characteristics such as chlorophyll a, b and carotenoids, proline and boll yield. Photosynthetic pigments were measured by spectrophotometer and its concentration was performed by Arnon (1967) method. Based on the results of this experiment, cultivars with low irrigation stress treatments showed a significant difference in terms of traits related to photosynthetic pigments and non-enzymatic antioxidants and their yield. The study of compound analysis of interaction effect of cultivars in the stress of low irrigation during two crop years showed a significant difference in the yield of Vash and malendialdehyde. Most of the studied traits were affected by the intensity of low irrigation stress and growth stage. The amount of proline increased with the increase of stress so that at the medium stress level of two stages of irrigation (bud formation and beginning of flowering) it increased significantly compared to the condition of no stress. The amount of chlorophyll a was affected by the intensity of stress, but there was no significant change in the amount of chlorophyll b. In the first and second year, the highest yield of rice in non-stress conditions belonged to Sajidi variety with 4596 and 4593 kg/ha-1, respectively, and the lowest yield in water stress conditions in the first and second year belonged to Sepid variety, with 1649 and 1756 kg/ha-1, respectively. The decrease in the yield of cotton was due to the decrease in the number of bolls in the plant under the condition of low irrigation stress. The results of this study indicated the traits of  tolerance cultivars under irrigation deficit. Also, cultivars showed different reactions to the studied traits.  According to the results of the research and the correlation coefficients between the traits, among the water stress tolerant cultivars studied, Golestan and Sajidi cultivars are among the stress tolerant cultivars, Sahil and Sepid cultivars are the sensitive cultivars to water stress, and the other cultivars are the semi-sensitive cultivars. Water stress was introduced.

 Sorghum (Sorghum bicolor L.) belongs to the cereal family and was domesticated at the same time as other cereals around three thousand years ago. Sorghum is the fifth most important cereal in the world after wheat, rice, corn and barley. Crop modeling is one of the branches of agriculture and crop physiology that has been around for 40 years and the development of powerful and efficient computers has played a major role in the development of this field. SSM model is a simple simulator to estimate the yield of different crops and the effects of climate change. This model requires limited input and easily accessible information. The above model has been evaluated for more than 30 Iranian crop species using various evaluation parameters. Evaluation of SSM_iSorghum model to predict different stages of phenology and yield of grain sorghum under temperate humid climate conditions in Gorgan.

SSM-Sorghum is a model to simulate sorghum crop phenology, growth and yield formation. The model was derived from SSM-Wheat model described by Soltani and Sinclair (2013). The sorghum model structure is the same as that wheat model except for phenology submodel. Phenology submodel is based on Alagarswamy and Ritchie (1990) with some modifications. The growth and development of sorghum were simulated using the SSM_iSorghum model based on meteorological data of Gorgan city during the years 2010 to 2011, including minimum and maximum temperature, amount of sunlight and rainfall on Kimia cultivar using different scenarios. For model input parameters including meteorological data, soil properties, crop management (using the values obtained from field experiments of 2010-2011 in the research farm of Gorgan Agricultural Research Station) was used. These experiments were performed under favorable agronomic conditions. Experiments at four different densities (17, 21, 28 and 35 plants/m2) and five different planting dates (May 10th and May 15th of 2010, May 10th and May 15th and June 15th 2011) during two growing years in total with 20 different scenarios were performed.

Results and Discussion :

The results showed that model predicted day from planting to emergence, day from planting to ripening, harvest index, biological yield and grain yield with high accuracy (R2=0.91-0.94%). In using the models to predict the performance, it has been reported that the value of the explanation coefficient should be more than 60%, which is a condition in this model. Regarding the 1:1 line between the observed yield and the simulated yield, it was found that values are in the range of 15% up and down the 1: 1 line. So the model has a suitable simulation of Gorgan conditions for grain yield.

Evaluation of SSM-Sorghum model showed that this model simulates phenological stages, including harvest index, leaf area index, and biological yield with different planting dates and different densities with appropriate accuracy in Gorgan climatic conditions. Most of the points were in the reliable range (± 15%) of the 1:1 line, which indicates an accurate estimate of the model parameters or confirms the simulation efficiency of the model process steps. Therefore, this model can be used in farm management planning including selection of appropriate planting date and appropriate density. Although the model well simulates the phenology , it seems necessary to retest the accuracy of the model with data from various experiments and to use it in the equations if the results of this study are confirmed. Obviously, models are effective when used by analyzing physiological and ecological conditions and based on experiments and experimental measurements of the system.

Drought stress poses a significant challenge to crop production globally, including in Iran. Selecting drought-tolerant cultivars is crucial to mitigate adverse environmental conditions. This study aimed to evaluate the drought tolerance of various cotton cultivars using drought tolerance indices to identify the best cultivar adapted to low irrigation stress conditions. In order to investigate and determine the response of 10 cotton varieties to drought stress, an experiment in the form of a statistical design of randomised complete blocks under medium stress conditions and without stress with three replicates was conducted in 2021 and 2022 at the Teaching and Research Farm of Gonbad Kavos University. To evaluate the tolerance and sensitivity of the studied cotton cultivars to drought stress, TOL (tolerance index), MP (mean productivity index), SSI (stress sensitivity index), STI (stress tolerance index), GMP (geometric mean productivity index), YI (yield index), YSI (yield stability index), SDI (drought sensitivity index), K1STI (adjusted stress tolerance index under non-stressed conditions), K2STI (adjusted stress tolerance index under stressed conditions), SSPI (percentage sensitivity index to stress), SNPI (performance index of stress and non-stress conditions) were used. After the analysis of variance and comparison of means, correlation coefficients, principal component analysis and cluster analysis were performed to identify and introduce indicators of drought tolerance. The results of the composite Based on the analysis of variance and the significance of the simple effect and the interaction effects of year, variety and low irrigation, the comparison of the average data in two years was carried out separately, with the highest yield of Vash in the two years 2021 and 2022 under non-stressed (YP) and stressed conditions. Under low irrigation (YS), the Sajdi and Golestan varieties were the highest yielding. The varieties Mai, Shayan, Lodos, Armaghan and Latif achieved above-average yields under both non-stressed and low irrigation conditions. The analysis of the two-year correlation coefficients between the drought stress indices and rice yield under non-stress (YP) and low irrigation (YS) conditions showed the superiority of the STI, MP, GMP and K1STI indices. The results of the analysis by principal components showed that the first two components explained 99.51 and 96.50 per cent of the changes in the first and second year, respectively. The MP, GMP, STI and K2STI indices were the most suitable indices for selecting varieties tolerant under low irrigation stress, as they showed a high correlation with wash yield and more principal components under both conditions. The superior values and cluster analysis of Golestan and Sajdi cultivars were identified as the most tolerant and Sahel and Sepid cultivars as the most sensitive cultivars to low irrigation stress. It seems that production and presentation of varieties with high yield and tolerance to water stress is one of the effective solutions to reduce the harmful effects of water stress.

In order to study on relationships among yield and some agronomic traits, 141 pure lines soybean as well as three commercial varieties (controls) (Williams, Sahar, DPX) were arranged at simple lattice model (12×12) with two replications in Gorgan agricultural research station in 2009. Analysis of variance demonstrated a significant difference among pure lines at 1% and 5% probability levels for all traits. The results showed positive significant correlation among yield with percentage of protein, day to flowering, number of branches, pods per plant, plant height, and weight of seed per plant (g). Also the results indicated negative significant correlation among yield and oil percentage. Stepwise regression showed day to flowering, plant height, seeds per pod/plant, number of nod/plant and protein percentage could explain variations in yield. Path analysis showed that number of pod/ plant and plant height had highest direct effect on grain yield of soybean, and because their direct effects had agreement with ctotal effects thus for yield increase effective select lines taller plant with number pod. Using cluster analysis with UPGMA method and the squared Euclidean distance as a measure of the similarity, the cultivars were groped in to five groups. According to results, the number of pods/plant and plant height were criterion. index to improvement of soybean yield in breeding programs.

In order to study the grain yield and related traits of soybean pure lines in year 2008, 141 pure lines of soybean with three checks (Williams, Sahar and DPX) were evaluated in a simple 12×12 lattice, with two replication at the Agriculture and Natural Resource Research center of Golestan. The analysis of variance results showed that there were significant difference among genotypes for most of the traits which indicates the existence of genetic variations between genotypes. Results showed that grain yield was positively and significantly correlated with traits; days to flowering, plant height, number of branches, number of pods per plant, weight of seed per plant (gram) and percentage of protein. There were also significant and negative correlation between grain yield with oil percent, Step wise regression showed that traits; days to flowering, plant height, number of seeds per pod, number of nod per plant and percentage of protein could justify the highest variations for grain yield. Path analysis showed that the highest and least direct effect on grain yield were number of pods per plant (P=0.29) and percentageof protein (P=-0.26). According to the result number of pods per plant was identified as a selection criteria for improvement grain yield.