Computer aided decision making to use optimum water in safflower growing


  • Kerim Karadağ* Department of Electrical and Electronics Engineering, Faculty of Engineering, Harran University, Sanliurfa, 63290, Turkey



n plants, it is one of the important factors to provide ecological factors for productivity. Plants perceive the effects of environmental factors
outside as stress and create appropriate physiological responses in their metabolism. Water stress is a type of abiotic stress and is one
of the important factors affecting the growth and development of plants. Irrigation water management is very important for sustainable
use of water resources. Therefore, support tools are becoming increasingly important in deciding irrigation. With the developments the
technology, computerized support applications are usually used in agricultural areas. In the study, it is aimed to determine the effects of
irrigation applications performed in different periods on yield quality and spectral reflections of safflower plant and to create applicable
irrigation programs in safflower cultivation. From the reflections detained from safflower leaves by using spectroradiometer device, the
determination of safflower plant according to water ratio different situations is done. Reflections are taken as three groups where the
plants are grown at wavelengths of 325 nm to 1075 nm. Water due diligence related with safflower is consist of two stages. The first
stage is the provision of the feature vector, the second stage is the classification of the feature vector related to data. As classification
methods, support vector machine, k-nearest neighbor and decision tree are used. In comparison of three groups, the average value of
the performance is high. As a result, considering the fallowed method and the procedure used, it is evaluated that such studies can be
used in agriculture and cultivation.


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How to Cite

Karadağ*, K. “Computer Aided Decision Making to Use Optimum Water in Safflower Growing”. Emirates Journal of Food and Agriculture, vol. 34, no. 9, Nov. 2022, doi:10.9755/ejfa.2022.v34.i9.2948.