Evaluation of climate changes and its effects on the performance and well-being of producers and consumers of oilseeds (sesame and rapeseed).

Abstract

Introduction

After cereals, oilseeds form the second largest food reserve in the world. Sesame has been one of the oldest oil plants in the world, which is known as the queen of oil plants due to its pleasant taste, high stability and stability, high resistance to dryness and the fact that the oil does not oxidize. Sesame is considered as an oil-protein source and sesame seeds contain 34-60% oil and 19-30% protein. Rapeseed is another oilseed that has more than 40% of oil in the seed and about 40% of protein in its meal, which plays an important role in human nutrition and animal and poultry feed.

Climate change is a significant and persistent change in the statistical distribution of weather patterns that occurs over a long period of time in a specific region or for the entire global climate. In fact, this phenomenon occurs as a result of internal factors such as dynamic processes of the earth or external factors such as changes in the intensity of sunlight or human activities.

As a result of climate change, the average weather variables such as temperature and precipitation do not remain constant and change in different regions.

Materials and methods

The purpose of this study is to evaluate climate change and predict its effects on the performance and well-being of the producer and the well-being of the consumer of the two products of sesame and canola. The required meteorological and agricultural data were collected in the form of combined data for two crops during 1370-1398. Using weather forecasting scenarios, the performance of two products was predicted. Finally, with the help of non-linear programming model, consumer welfare, producer welfare and total welfare were calculated and predicted using the partial balance method. Eviews, Excel and GAMS software were used to conduct this study. Khuzestan province was zoned into three climatic zones for more accurate estimation of yield response function.

Results and discussion

In this research, the climatic conditions of Iran in the decades of 2000, 2025, 2050 and 2100 were modeled using the output of two atmospheric general circulation models ECHAM4 and HadCM 2. The results show an increase in the temperature of all the provinces of the country in the coming decades. These two models predicted an average temperature increase of 3 to 3.6 degrees Celsius until the 2100s for the country. The panel data method is used to estimate the climate model.

Conclusion

According to the results obtained from the calculation of welfare, it was found that the welfare surplus of the producer is higher than the welfare surplus of the consumer, and the results obtained from the welfare forecast according to the climate scenarios show that the amount of welfare generally follows a decreasing trend with fluctuation and The amount of losses caused by climate change has been higher for consumers than for producers.

Keywords

Performance response function, panel data, well-being, weather forecast scenario, climatic components



Abstract

Introduction

After cereals, oilseeds form the second largest food reserve in the world. Sesame has been one of the oldest oil plants in the world, which is known as the queen of oil plants due to its pleasant taste, high stability and stability, high resistance to dryness and the fact that the oil does not oxidize. Sesame is considered as an oil-protein source and sesame seeds contain 34-60% oil and 19-30% protein. Rapeseed is another oilseed that has more than 40% of oil in the seed and about 40% of protein in its meal, which plays an important role in human nutrition and animal and poultry feed.

Climate change is a significant and persistent change in the statistical distribution of weather patterns that occurs over a long period of time in a specific region or for the entire global climate. In fact, this phenomenon occurs as a result of internal factors such as dynamic processes of the earth or external factors such as changes in the intensity of sunlight or human activities.

As a result of climate change, the average weather variables such as temperature and precipitation do not remain constant and change in different regions.

Materials and methods

The purpose of this study is to evaluate climate change and predict its effects on the performance and well-being of the producer and the well-being of the consumer of the two products of sesame and canola. The required meteorological and agricultural data were collected in the form of combined data for two crops during 1370-1398. Using weather forecasting scenarios, the performance of two products was predicted. Finally, with the help of non-linear programming model, consumer welfare, producer welfare and total welfare were calculated and predicted using the partial balance method. Eviews, Excel and GAMS software were used to conduct this study. Khuzestan province was zoned into three climatic zones for more accurate estimation of yield response function.

Results and discussion

In this research, the climatic conditions of Iran in the decades of 2000, 2025, 2050 and 2100 were modeled using the output of two atmospheric general circulation models ECHAM4 and HadCM 2. The results show an increase in the temperature of all the provinces of the country in the coming decades. These two models predicted an average temperature increase of 3 to 3.6 degrees Celsius until the 2100s for the country. The panel data method is used to estimate the climate model.

Conclusion

According to the results obtained from the calculation of welfare, it was found that the welfare surplus of the producer is higher than the welfare surplus of the consumer, and the results obtained from the welfare forecast according to the climate scenarios show that the amount of welfare generally follows a decreasing trend with fluctuation and The amount of losses caused by climate change has been higher for consumers than for producers.

Keywords

Performance response function, panel data, well-being, weather forecast scenario, climatic components