The relationship between climate and agriculture is very close and agriculture is probably the most influential activity in climate conditions. The climate factor is one of the most influential natural factors in determining crop species as it identifies areas that can be cultivated with specific crops, including the wheat crop under study. The goal of this research is a study (climate assessment of the geographical distribution of Iraq's wheat crop) that identifies the geography of the applied climate. The study showed the extent to which climate elements and manifestations of dust atmosphere (solar radiation, wind, moisture, dust storms, rising dust and stuck dust) affect Iraq's wheat cultivation and production. The study relied on eight climate stations for the study area (Iraq) and climate data for the period 1990-2020. The study examined Iraq's climatic characteristics for monthly and annual rates (solar radiation, temperature rates, wind, relative humidity, dust phenomena). The study also examined the geographical distribution of the cultivation and production of wheat in Iraq for the cultivated area and total production and for the average productivity (yield) for the study years (2012, 2013, 2014, 2019, 2020).

The relationship between climate and agriculture is very close; perhaps agriculture is the most significant activity regarding climate conditions. The climate factor is one of the most influential natural factors in determining the types of crops, as it determines the areas that can be cultivated with certain crops, including the wheat crop, which is the subject of the study. This study aims to study (the biothermal areas suitable for wheat cultivation and production in Iraq) that determine the geography of the applied climate. To clarify the biothermal areas suitable for wheat cultivation and production in Iraq, including the use of statistical equations in order to reach accurate and precise statistical results. The study also dealt with statistical analysis, the most crucial step that follows scientific research. Two methods were used to measure the statistical relationship: correlation and regression. Our study relied on the correlation coefficient, regression coefficient and coefficient of determination in measuring and estimating the relationship, its nature, and the level of influence between the selected study variables, which are the average productivity and salinity ratio according to units.