Showing 3 results for Hayati
Ezatollah Karami, Daryoosh Hayati,
Volume 2, Issue 1 (spring 1998)
Abstract
Sustainability has become a part of the language of almost all development projects. Although, in many instances it has been overused and misused, attaining sustainability in agricultural development is always one of our concerns. This paper aims (1) to clarify and describe the core beliefs and values underlying the two opposing world views of agriculture, i.e., “conventional agricultural paradigm” and “sustainable agricultural paradigm” (2) to describe an instrument developed to measure the basic beliefs and values assumed to constitute the two competing paradigms (3) to measure the adherence of extensionists and researchers of the Ministry of Agriculture towards sustainable agriculture and (4) to compare the adherence to alternative paradigms against conventional agricultural paradigms of Iranian groups with permaculture groups and agricultural chemical dealers of USA. The instrument was used in a nation wide survey. A two-stage random sample was used. In the first stage, 11 provinces were randomly selected and then in each of the selected provinces a simple random sample of extension agents, extension experts and agricultural researchers were selected for the study. The findings indicated that there is no significant difference among agricultural researchers, extension agents and extension experts in their mean endorsement score of sustainable agriculture. Data from a similar study in the USA were used to provide a means of comparison. Two extreme groups were selected, permaculture group with strong sustainable agricultural score and agricultural chemical dealers with lowest mean scores of sustainable agriculture. The mean scores of sustainable agriculture adherence of three Iranian groups were considerably lower than that of the USA permaculture group. However, there was no significant difference between three Iranian groups and USA agricultural chemical dealers which indicates low adherence of Iranian sample to sustainable agriculture. Considering the challenges Iranian farmers face for food production in the next decade and the role of the Ministry of Agriculture personnel, recommendations are put forth for changing knowledge, attitudes and skills of agricultural researchers and extensionists.
Daryoosh Hayati, Ezzatollah Karami,
Volume 3, Issue 2 (summer 1999)
Abstract
Studies on sustainable agricultural have not paid adequate attention to farmers' behaviour regarding sustainability. The objectives of this research were: 1) to determine the relationship between socio-economic and farming factors with “sustainable agricultural knowledge”, 2) to predict “sustainable agricultural knowledge” based on socio-economic and farming factors, and 3) to determine the relationship between sustainable agricultural knowledge and sustainability of farming systems. A survey research was used with a multi-stage cluster sampling technique to collect data for the study. In the first stage, 39 villages were selected in Fars Province. Then 200 wheat producers were randomly selected in these villages for interview. The findings indicated that there was a significant and positive correlation between “sustainable agricultural knowledge” with level of literacy, achievement motivation, amount of total wheat production, technical knowledge about wheat production, economic condition, wheat farming model, amount of supervision by Agricultural Service Centers, and educational services provided by extension agents. Stepwise multiple regression indicated that technical knowledge about wheat production, achievement motivation, type of land revenue system, level of literacy and wheat farming model (independent variables) explained more than 50 percent of variability in “sustainable agricultural knowledge”. There was no significant correlation between “sustainable agricultural knowledge” and “sustainability of farming systems”. Possible reasons for this lack of relationship have been discussed. Based on the findings of this study, recommendations are provided towards achieving a more sustainable agricultural system.
F. Hayati, A. Rajabi, M. Izadbakhsh, . S. Shabanlou,
Volume 25, Issue 1 (Spring 2021)
Abstract
Due to drought and climate change, estimation and prediction of rainfall is quite important in various areas all over the world. In this study, a novel artificial intelligence (AI) technique (WGEP) was developed to model long-term rainfall (67 years period) in Anzali city for the first time. This model was combined using Wavelet Transform (WT) and Gene Expression Programming (GEP) model. Firstly, the most optimized member of wavelet families was chosen. Then, by analyzing the numerical models, the most accurate linking function and fitness function were selected for the GEP model. Next, using the autocorrelation function (ACF), the partial autocorrelation function (PACF) and different lags, 15 WGEP models were introduced. The GEP models were trained, tested and validated in 37, 20- and 10-years periods, respectively. Also, using sensitivity analysis, the superior model and the most effective lags for estimating long-term rainfall were identified. The superior model estimated the target function with high accuracy. For instance, correlation coefficient and scatter index for this model were 0.946 and 0.310, respectively. Additionally, lags 1, 2, 4 and 12 were proposed as the most effective lags for simulating rainfall using hybrid model. Furthermore, results of the superior hybrid model were compared with GEP model that the hybrid model had more accuracy.
