Analysis of yield status and it its relation with leaf area in wheat fields based on interpolation methods (A case study in army fields, Golestan province)

Background and objectives: In sciences like ecology, that measured value of a quantity to be processed within a definite border, the estimation of variable values in a particular time and place, using existing data from the use of information variable or variables another is common. In geoeographic studies, data collection is often the point. Usually, it is essential that this data be generalized to the total points that to be made by interpolation methods.
Materials and methods: In this study, spatial variations of leaf area index in tillering and booting stages and related values of wheat yield in army fields of Golestan province was evaluated using Geostatistic methods and some of deterministic interpolation methods. For this purpose, 101 plant samples were taken from the fields in 2012 and aforementioned variables were recorded. Statistical indices including Mean Absolute Error, Mean Bias Error and Root Mean Square Error that are base on cross validation method were used as assessment indices.
Results: Analysis on semivariograms showed that the spherical, circular and exponential models were fitted better than other models on plant variables. Base on selected interpolation models, results showed that yield varied from 2.876 to 6.453 t.ha-1, while LAI changed from 0.304 to 2.317 and 2.66 to 6.049 in tillering and booting stages, respectively. Looking at yield data and correlations between yield and leaf area index indicates that considerable difference in the amount of producted leaf area in farms, is an important reason for the chronic variance in different parts of the farm, so that differences in leaf area estimated for A part in tillering and booting stage respectively is 1.729 and 2.363 t.ha-1 and in the B part of the field is 2.013 and 3.43 t.ha-1.
Conclusion: Results of study of correlation between yield and LAI data showed issues such as non- coincidence machinery capacity with the farm area, resulting in significant differences in planting date of different parts, non-uniformity in soil EC and the varieties with the different potential can be most important reasons for these fluctuations. Therefore, using of those management options which will decrease LAI variation throughout the field such as decreasing planting date variation, could also be so effective in optimization of wheat production systems.. Produced yield and leaf area maps very well showed that wheat planting in the studied fields haven’t similar and systematic management and it is necessary for a general review of the planting patterns of the farms.