Özet:

The structural characteristics and the factors affecting the soil analysis decisions of the farmers in Edirne and Tekirdağ provinces were determined in this study. The factors affective on the soil analysis decisions of the farmers were analyzed by using logistic regression analysis and artificial neural networks and the comparison of the methods was done. In each province, 3 laboratories which had the most sample acceptance number for soil analysis were selected. The surveys were conducted with total of 60 farmers who referred to the laboratories and utilized from soil analysis subsidies and 40 farmers who did not utilize from soil analysis subsidies and had the similar characteristics with the farmers who utilized from soil analysis subsidies in each province and total of 200 farmers participated in the survey in 2019. The most significant factors on soil analysis decisions of the farmers were determined as total land size, age, agricultural experience, experience on taking soil sample, family size, education period and the activity type in each two methods. Total accurate classification ratio was found as 77% in logistic regression analysis and 80.67% in artificial neural network analysis. It was determined that the classification percentages obtained by two methods were pretty close to each other. The farmers who had low yield and low qualified crop due to not having soil analysis should be informed and necessary publication studies should be done.

Anahtar Kelimeler: