m. raeini sarjaz

IntroductionWheat (Triticum aestivum L.) has become very important as a valuable strategic product with high energy level. The importance of investigating environmental stresses and their role in predicting and evaluating the growth and crops yield is essential. A wide range of plant response to stress is extended to morphological, physiological and biochemical responses. Considering the rapid advancement in computer model development, plant growth models have emerged as a valuable tool to predict changes in production yield. These growth simulation models effectively incorporate the intricate influences of various factors, such as climate, soil characteristics, and management practices on crop yield. By doing so, they offer a cost-effective and time-efficient alternative to traditional field research methods. Material and MethodsThis research was conducted in the research farm of Varamin province, which has a silty loam soil texture. The latitude and longitude of the region are 35º 32ʹ N and 51º 64ʹ E, respectively. Its height above sea level is 21 meters. According to Demarten classification, Varamin has a temperate humid climate. The long-term mean temperature of Varamin is 11.18 ° C and the total long-term rainfall is 780 mm. In this study, in order to simulate irrigated wheat cv. Mehregan growth under drought stress, an experimental based on completely randomized blocks (CRBD) including: non-stress as control (NS), water stress at booting stage (WSB), water stress at flowering stage (WSF), water stress at milking stage (WSM) and water stress at doughing stage (WSD) with three replications during growth season 2019-2020 was carried out in Varamin, Iran. Crop growth simulation was done using SSM-wheat model. This model simulates growth and yield on a daily basis as a function of weather conditions, soil characteristics and crop management (cultivar, planting date, plant density, irrigation regime). Results and DiscussionBased on the results, the simulation of the phenological stages of irrigated wheat cv. Mehregan under water stress condition using SSM-wheat model showed that there was no difference between observed and simulated values. Summary, the values of day to termination of seed growth (TSG) were observed under non- stress, stress in the booting stage, flowering, milking and doughing of the grains, 222, 219, 219, 221, 221 days, respectively andsimulation values with 224, 221, 220, 221, respectively. However, with their simulation values, there were slight differences with 224, 221, 220, 221, respectively. Acceptable values of RMSE (11.7 g.m-2) and CV (3.5) indexes showed the high ability of the SSM model in simulating the grain yield of irrigated wheat cv. Mehregan under water stress conditions. Grain yield values were observed in non-stress conditions of 5783, water stress in booting, flowering, milking and doughing of the grain stages in 5423, 5160, 5006 and 5100 kg. h-1, respectively. While the simulated values were 5630, 5220, 4920, 4680 and 4880 kg. h-1, respectively. Based on the findings, observed and simulated values of leaf area index (LAI) were observed under water stress condition in the booting, flowering, milking and doughing of the grain stages (4.3 and 4.47), (4.33) and 4.46), (4.4 and 4.57) and (4.4 and 4.58) cm-2, respectively. Evaluation of the 1000-grain weight of irrigated wheat cv. Mehregan under the water stress showed that the SSM model was highly accurate. RMSE (4.6 g.m-2) and CV (1.8) values indicate the ability of the SSM model to simulate the 1000-grain weight of irrigated wheat cv. Mehregan. Also, the simulated values of the harvest index were 34.7 % in non-stress conditions, which decreased by 6 % compared to the observed value. Harvest index values were observed under water stress conditions in the in the booting, flowering, milking and doughing of the grain stages in 30.2, 29.3, 29.9 and 29.5 %, respectively. Compared to its observed values, it was reduced by 3, 3.5, 5, and 5.5 %, respectively. ConclusionBased on the findings, the slight difference between the observed and simulated values demonstrates the SSM model's capability to accurately capture water stress impacts on the phenological stages, grain yield, and yield components of irrigated wheat cv. Mehregan during critical growth stages, including booting, flowering, milking, and doughing. The results indicate that the SSM model is effective in simulating wheat growth under water stress conditions, showcasing its potential as a valuable tool for modeling irrigated wheat growth. The model's ability to account for water stress and its effects on various growth parameters makes it a reliable and efficient tool for predicting crop performance in water-limited environments.

The study of temperature fluctuations is essential for agricultural planning and environmental studies. With global warming affecting various regions, access to long-term temperature data is becoming increasingly important. Dendroclimatology is a useful tool for long-term climate study, and in this study, the average habitat temperature was reconstructed after developing the chronology of Juniperus polycarpus trees in Keygoran site (Aligodarz, Lorestan). The correlation of annual tree rings with climatic variables of meteorological stations was investigated to reconstruct the average temperature in January-March for the period 1910-2014 for this region. The findings show a positive and significant correlation between the average January-March temperature and the growth of annual tree rings. The results show the occurrence of cold years in the first years of the 1910s to the first half of the 1960s. Warm periods have occurred since the second half of the 1960s, and the temperature trend has generally been increasing in recent years. An examination of the positive and negative pointer years also shows that most of the positive pointer years occurred in the second half of the twentieth century.

Global warming is leading to gradual and tremendous climate change following the increase in greenhouse gases. Methane gas can be produced in anaerobic processes in soil, such as paddy fields. Therefore, in the agricultural sector, waterlogged rice cultivation is one of the main sources of this methane gas emissions. On the other hand, straw burning brings a huge amount of pollutants to the atmospher. In this regard, a study with four experimental treatments was conducted: (a) without straw (control), (b) rice straws incorporated into the soil,  (c) burned rice straws left in the field, and finally (d) burned air-dried rice straws left from first cropping harvest. The experiment was carried out on the experimental field of Sari Agricultural Sciences and Natural Resources University. Methane gas sampling was performed at 10- day intervals and carbon dioxide gas sampling was performed one day after straw burning and then in three stages in the second cropping season. Finally, in order to compare the treatments in terms of methane and carbon dioxide emissions, the carbon dioxide equivalent of methane gas was calculated.The findings showed that the highest methane emission was from rice straws incorporated into the soil (6.75 mg/m2.day) and the lowest emissions were from the control treatment (2.97 mg/m2.day) ) and burned rice straws air-dried after harvest (2.62 mg/m2.day). Also, the results of carbon dioxide emissions during the second cropping season showed that the highest amount was from burned rice straws left in the field treatments (133.93 mg/m2.day) and the lowest amount was observed from burned rice straws air-dried after harvest (67.08 mg/m2.day). Finally the results of the total greenhouse gas emissions measured in the whole period showed that wet and dry straws burned treatments could have the potential to increase global warming almost 8 times more than the control treatment.

Global warming could affect snow-covered watersheds and the temporal and spatial distribution of snow, and thus the water needs below the basin. Therefore, the aim of this study is to investigate the spatio-temporal changes of snow cover and snow retention in the northern aspects of Central Alborz. The Normalized Difference Snow Index (NDSI) extracted from MODIS satellite images was employed to estimate snow cover during 2000 - 2018 intervals. The findings of this study showed that there is a significant and increasing trend in the temperatures of May and June. On the other hand, although there was no trend in the snow cover, the Sen's slope estimator showed that the snow cover in January decreased by about 220 km per year, which had a high negative correlation with the increase in the average temperature of this month. (r = - 0.77), while in March, the snow cover increased by nearly 60 kilometers a year. There was a significant positive correlation (r = 0.81) between snow cover and snow depth, and significant negative correlations (r = -0.80 to r = -0.60) were found between the annual snow cover and the average annual air temperature. These findings indicate that the effect of temporal and spatial changes in temperature on the extent and persistence of snow cover is meaningful. By reduction of the basin’s height from the west in Haraz, with an average height of 2059 m, to the east in the Tajan basin, with an average height of 980.7 m, the snow cover area and its durability reduced. From the findings it is concluded that temperature changes in this region follow the global warming trend, while this warming has affected on the variance of the snow cover extend.

Optimal use of agricultural inputs, especially water, will result in sustainable agriculture and food security. Therefore, proper management of soil moisture and the use of new methods to maintain and increase soil moisture storage capacity are important. Thus, the aim of this research was investigation the effect of irrigation management with injection superabsorbent gel and organic matter on water use efficiency and quantitative and qualitative yield of orange. The experiment was carried out as split plot in randomized complete blocks design with three replications in Miyandoroud region, Mazandaran province in 2015 and 2016. Three irrigation management including 100, 75 and 50% of plant water requirement were chosen as main plots and two superabsorbent gel injection depth including 30 and 60 cm were chosen as sub plots and four organic matter level (superabsorbent gel, vermi-compost, combined of organic matter and superabsorbent gel and control treatment were chosen as sub sub plots. The results revealed that the most fruit weight and fruit volume were obtained for 100% of water requirement irrigation management with gel injection in 30 cm of soil depth. Moreover, the maximum fruit diameter, fruit volume and fruit weight was achieved for 100% of water requirement irrigation management with combined applied of organic matter and superabsorbent gel. According to findings of treatments interaction, there were observed the negative correlation between TSS percentage and fruit diameter, fruit volume and fruit weight. Based on triple interaction of treatments, with decrease of water usage based on water requirement the young branch length, leaf area, pH, growth density, WUE, tree yield and yield per hectare were statistically significantly decreased that the negative impact of that at gel injection in 60 cm of soil depth and control treatment was more than other treatments. The highest WUE (16.14 kg.m-3) was obtained for 100% of water requirement irrigation management with gel injection in 30 cm of soil depth and combined applied of organic matter and superabsorbent gel. Moreover, the most tree yield was produced with 100% of water requirement irrigation management with gel injection in 30 cm of soil depth and consumption of superabsorbent gel, vermi-compost and combined applied of organic matter and superabsorbent gel. The maximum yield per hectare was achieved by 100% of water requirement irrigation management with gel injection in 30 cm of soil depth and consumption of vermi-compost and combined applied of organic matter and superabsorbent gel (44.03 and 46 ton per hectare, respectively). Therefore, combined applied of organic matter and superabsorbent gel can increase the moisture storage capacity by increasing the WUE and thus improving the quantitative and qualitative yield of orange.

In order to evaluate the performance of the CERES-Rice model in rice biomass and grain yield estimation in large scale، this study was carried out in paddy fields of Guilan، Iran. First the model was calibrated and evaluated using data from a research at Rice Research Institute of Iran، then the model accuracy was assessed in 26000 ha of Some Sara region. 110 common farmers fields were chosen، the soil، water، crop samples and other needed information were taken. The model was ran for each field. The results showed that the Error of yield and biomass estimation in research station were below 10 percent. The results in large scale showed that the model estimation of yield and biomass could be categorized in three different parts. While in fields with average biomass and yield observation the setimation error was negligible. Underestimation was observed in the fields with the yield above the average of the region while in high yielding fields overestimation was observed. The Normalized Root Mean Square Error was about 22. 7 and 21% for biomass and yield prediction. Although in some cases the error was about 50%، in 75% of the region it was in range of 0-10%، and in 95 % of the region it was in range of 0-20%. Water productivity based on water used in most of the fields was in the range of 0. 5- 0. 6 kg/m3 and the water productivity based on transpiration was 0. 85-0. 9 kg/ m3. The model showed a satisfactory accuracy to estimate both yield and biomass in large scale paddy fields.