Nowadays, the fundamental role of having a purpose for life in physical and mental health has been confirmed. According to victor frankl, presence of a purpose in life gives life a meaning and increases resilience against pains and traumas. The importance of the purpose in life construct reveals the need for a reliable and valid tool to measure it. Crumbaugh and Maholick's purpose in life questionnaire is the first and one of the most applied tools for the assessment of life's purposefulness. The aim of this research is to determine the FACTOR structure of purpose in life questionnaire. The questionnaire was administered on 206 students who were selected through random stratified sampling at Ferdowsi University of Mashhad. Exploratory FACTOR analysis showed that there are two FACTORs "comprehension" and "purpose" and this finding were confirmed by confirmatory FACTOR analysis. Altogether results of this research showed FACTOR validity of the purpose in life questionnaire with a two FACTOR pattern

Today all countries are seeking to achieve high productivity. This means that they can achieve more production with fewer resources. Productivity has an important and effective role in increasing production and growth in sectors of economy. Through calculating and analyzing the indicators of productivity the efficiency of various economic sectors can be reviewed. In this study with a Solow residual and lag model, total FACTOR productivity growth in agricultural production during the period 1387-1358 were calculated. For this purpose, the Agriculture CROP sector production function with capital, labor and energy was estimated using the ARDL approach. Then, using the index of Solow, TFP growth in agriculture CROP sector was calculated. The results showed that total FACTOR productivity growth in agriculture CROP sector had experienced periods of high volatility. So that the average period of 0.8 percent. The mean total FACTOR productivity growths in CROP sector of agriculture, with the figure predicted in the fourth program (2.2) are of significant difference. It is suggested that the cycle of productivity policy should be done, to increase TFP in this sub-sector of agriculture.

CROP Simulation models are used for water management in farms and are widely used for optimization of water use efficiency. AquaCROP model, developed by FAO, is based on yield response to water. Compared to other similar models, AquaCROP requires fewer input parameters. The objective of this study was evaluation of this model for barley under deficit irrigation in Pakdasht region. The experiment was done in 2014-15 growing season and included three irrigation treatments and three sowing dates. The irrigation treatments included full irrigation and two treatments of 80% and 60 percent of full irrigation. Sowing dates included early, normal, and late planting. Comparing the estimated values of AquaCROP model and measured values showed that the model is well capable of simulating the barley biomass production. Average R2, RMSE and MBE for the comparison between measured and estimated values were calculated to be 0.96, 8.4 %, and 2.6 %, respectively.

CROP models are suitable for simulation of CROP yield by different scenarios of deficit irrigation and salinity. In this research, the AquaCROP model was evaluated to simulate the soybean grain yield and biomass under different levels of salinity and deficit irrigation in Gorgan County during 2011 and 2012 growing seasons. The model was calibrated by experimental data of 2011 and validated with data of 2012. The experiment included three irrigation levels of 100%, 75% and 55% water requirement and three salinity levels of 0.7, 5 and 10 dS/m. Statistical indices of the results of validated model including RMSE, E, and d for grain yield were 0.225 ton/ha, 0.88 and 0.97, respectively, and for biomass, they were 0.718 ton/ha, 0.77 and 0.95, respectively. Results showed that grain yield decreased with decrease in the amount of irrigation water and increase in salinity level. Further analysis showed that the sensitivity of AquaCROP model to the canopy decline coefficient (CDC) was more than the other parameters at senescence and maximum canopy cover stages.

Iran is a country with an average rainfall of about one third of the world's average rainfall, and is severely under water due to water resources. Therefore, improvement of water use efficiency based on production in agricultural sector is very important. In this regard, the simulation of plant growth stages and, as a result of the need for forecasting, will result in better planning and more efficient management in the production process.Nowadays, tools are needed to help irrigation system designers to optimize irrigation water management in agriculture; Therefore, the FAO, with the development of the Aqua CROP model, provides these essential management tools for the various agricultural sectors necessary; In this research, Aqua CROP plant model was used for water requirement of barberry cultivars. For this purpose, inputs to the model include meteorological, vegetation data, irrigation management, farm management, soil characteristics, simulation time period, and initial conditions in the field. The survey of water requirement zonation map indicates that, considering the climatic conditions, the climate of the northern regions of the country, despite the fact that it is not recommended for the cultivation of barberry, is the least water requirement in comparison with other regions of the country. The provinces of Khorasan Razavi, North and South, which are the best places to grow barberry at the moment, and the major production of barberry in these areas, are higher than other areas in need of water. The northern parts of the country also have a moderate water requirement.

Deficit Irrigarion in water scarcity is the most important strategy to maintain CROP water productivity. Therefore, cultivating drought-resistant CROPs such as quinoa can increase physical productivity on farm. To evaluate the yield and growth of quinoa in water shortage conditions, information about yield response FACTOR is required. In this study, Quinoa cultivar Titicaca was cultivated in two CROPping years of 2020 and 2021. To evaluate different levels of irrigation, four irrigation treatments were applied based on measuring soil moisture in different periods of plant growth, including: full irrigation, 30% Allowable Depletion, 50% Allowable Depletion and 70% Allowable Depletion. Based on the results in the two years, the initial growth period was 20 days, the development period was 30 days, the middle period was 28 days and the final period was 12 days. The most sensitive growth period in quinoa plant was determined as the middle period with a yield response FACTOR of 0. 88. On average, with a consumption of 2563 cubic meters of water, the maximum productivity will be about 1. 85 kg per cubic meter. In general, the results show that this plant has a high resistance to deficit irrigation and therefore this plant can be grown in areas with water shortage and good performance can be expected in water stress conditions.