One of the important problems in economic is estimating a Production Function.but one of the problems associated with the estimation of Production Function is that Crop-specific input levels are generally not available. The purpose of this study is to estimate the input allocation in Crops during 1375-84 in Iran. Using the general maximum Entropy approach.When there aren’t any information about parameters and can’t be estimated by standard techniques this method can solve this problem. In this study this method has been used to estimate of each Crop Production Function at Province level, while the shre of land is available for each Crop at Province, but the share of other inputs are only available at province level. The results present the input elasticities have changed over time and in the grain Crops machinery input elasticity in 1379 and 1380 is fix. The average share of inputs per Crops level in during 1375-1384 shows that the share of labor input in grain Crops level and machinery input in cereals level are maximum.

Identifying the constraining factors of Production and yield gap is very important. Therefore; this research was performed to identify the Production constraining factors of local rice cultivars. All management practices from nursery preparation to harvesting stages for 100 paddy fields of local rice cultivars were recorded through field studies, in Sari, from 2015-2016. In the CPA, the actual and calculated potential yield were 4495 and 5703 kg/ha, respectively and the gap was 1221 kg/ha. The yield gap caused by number of top-dressing variables was 324 kg/ha, equal to 27% of the total yield gap. The yield gap related to previous year of legumes cultivation was 218 kg ha-1, equal to 18% of the total yield variation. Among the 10 variables entered in the CPA model, the effects of top-dress fertilizer application and its application frequency and foliar application were remarkable, which could compensate a significant part of the yield gap (444 kg/ha, 37% of total) in the farmers’ fields by managing these variables. According to boundary line analysis (BLA) finding, actual yield mean on the basis of optimal limit related to 12 variables under study was 5369 kg/ha, with 881 kg/ha yield gap . Mean relative yield and relative yield gap for 12 variables (transplanting date, seedling age, number of seedlings per hill, planting density, nitrogen and phosphorous per hectare, nitrogen before transplanting, harvesting date, lodging problem, pest problem, diseases problem and weeds problem) were 83.64 and 16.35 kg/ha, respectively. Based on the finding, it can be stated that the model precision is appropriate and can be applied for both estimation of the quantity of yield gap and determining the portion of each restricting yield variables.

The aim of this study was to determine the probability of working days (PWD) for tillage operation using weather data with Multiple Linear Regression (MLR) and Radial Basis Function (RBF) artificial networks. In both models, seven variables were considered as input parameters, namely minimum, average and maximum temperature, relative humidity, rainfall, wind speed, and evaporation on a daily basis. The PWD was considered to be the output of the developed models. Performance criteria were RMSE, MAPE, and R2. Results showed that the R2-value was 0. 78 and 0. 99 for MLR and RBF models, respectively. Both models had acceptable performance, but the RBF model was more accurate than the MLR model. The RMSE and MAPE values for the RBF model were lower than those for the MLR model. Thus, the RBF model was selected as the suitable model for predicting PWD. Moreover, the results of these models were compared to the prior soil moisture model. It was indicated that the results of the studied models had a good agreement with the results of the soil moisture model. However, the RBF model had the highest R2 (99%). In conclusion, the developed RBF model could be used to predict the probability of working days in terms of agricultural management policies.

Decreasing water resources has made optimum water allocation in agriculture essential. Planning optimum irrigation and Crop Production Function considering accessible water and growing stage is an efficient approach to increase water productivity. Studies have applied this approach to maximize Crop Production using the FAO Crop Production method introduced in 1979. However, the FAO introduced a new method in 2003 that has been rarely studied. The objective of this study is to compare the performance of the two FAO methods in the Zayandh Rud irrigation system using climate information from the 1998 drought in the region. Wheat, barley, sugar beets and potatoes, the region’s main Crops, are selected and their Production Function and temporal pattern of optimum irrigation water by growing stage (10 days of irrigation) are compared. The results show that the new FAO method estimates lower Crop yield under water stress; however, the temporal pattern of irrigation depth is smoother and more uniform during the Crop growing stages.

Drought and its stress are the most important factors for Crop Production. This research was carried out for determination of Crop water Production Function and investigation different levels of irrigation water on yield component total dry matter, grain and harvest index in different irrigation levels for corn in Khoozestan in a research farm in Islamic Azad University, Dezfool Branch in 1014-2015. It was conducted in randomized complete block design with four treatments including 60%, 80%, 100% and 120% of full irrigation (W60, W80, W100 and W120, respectively) and four replications. According to the total dry matter, grain and shot, the best Crop water Production Function was obtained as linear Function with R2 equal 0. 897, 0. 682 and 0. 927, respectively which was significant in level of 1%. In comparison to W60 treatment, full irrigation treatment (W100) increased total dry matter yield (70%) but in comparison to W100, W80 treatment decreased total dry matter yield (5%). On the basis of total dry matter yield and grain (4. 8 and 2. 06 kg/ m3), maximum harvest index (0. 43) and maximum water use efficiency were obtained for W80 treatment. The results show that the best grain yield and water use efficiency were related to W80.

Crop Production challenges in Iran are: preserving natural resources, climate change and environmental sustainability. A nation who could not be able to save his environment including soil erosion, forests, climate change and increasing consumption of natural resources, would not be survived. Such nations, like Polynesians and Mayan people are cited in this article. Ignoring soil erosion through agricultural activities has been the cause of plaguing ancient civilizations, too.Increasing cultivated area without specific plans, deforestation, overgrazing, overusing of fertilizers, insecticides, and fossil fuels cause environmental contaminations, increase greenhouse gases, increasing air temperature which altogether result in change in precipitation pattern, incidence of droughts, floods, dust storms, and water shortage in the area. Confrontation of these challenges are: population control, sustainable consumption pattern, reducing the use of insecticides and fertilizers, range and forests conservation as carbon sequestering sources, suitable cultivation methods like notillage, replacing fossil energy by renewable energy, making logical balance between development and ecological strength of environment, breeding agronomic and horticultural cultivars resistant to heat, drought, pests and diseases, and using new agricultural management policies. Environmental factors affecting Crop yields are: water, land, soil, soil nutrition, energy, food, biodiversity, solid waste recycling, management and climate change. In addition, drought, temperature, atmosphere CO2 and ozon, biotic and abiotic stresses affect Crop Production, too. The food needs of Iran for strategic Crops such as wheat, rice, sugar, fat, barley, corn, and pulses for now and for 2025 and 2050, with respect to population growth, have been estimated. To meet the food needs of growing population in Iran, increasing cultivated areas should not be considered. Instead, genetics and breeding approaches to develop new cultivars and also Production and management techniques should be taken into account. Management approaches such as efficient water use, new cultivation techniques, efficient use of fertilizers, precision seed planters, integrated pest management (IPM) and new Cropping information technology have been discussed in this article. Our planet earth is sustainable in terms of water and sunshine. Natural resources and environment are the main background for agricultural activities and their safeguarding is the main factor for agricultural Production in any habitat.

The main purpose of this study is to analyze comparative advantage and protection indices of industrial Crop Productions during 1383. For this purpose Domestic Resource Cost Index and Policy Analysis Matrix have been used. The results indicated that Iran has had comparative advantage in Irrigated Cotton and Soybean Production. On the contrary, Iran showed that it hasn’t had comparative advantage in Sugar beet and Flower seed Production.Results also revealed that the private values of Cotton and Soybean are less than their social values. Respondent told that governmental policies have imposed some taxes on producers. But for all of farming Crops in this paper, farmers have been protected in tradable inputs.At last, the effective protection coefficients generally indicated an affective protection on sugar beet and flower seed.