PJB-2023-148
ESTIMATION OF THE EFFECT OF CHITOSAN APPLICATION ON THE RELATIVE INJURY RATIO OF CHICKPEA SEEDLINGS IN SALT STRESS WITH ARTIFICIAL NEURAL NETWORK
Ruziye KARAMAN
Abstract
Salinity stress is the most common abiotic stress factor. Salt stress disrupts the normal physiology of plants and causes serious changes in the ionic balance. For these reasons, the aim of this study was to estimate the effect of chitosan application on the relative injury ratio of chickpea seedlings under salt stress using artificial neural network. The factors in the study were salt doses (0, 5, 10 and 15 dS m-1) and chitosan doses (0, 1, 2 and 4 g l-1). The seed material was a registered chickpea variety named Ubet. The study was established as a pot study in the greenhouse. Seedling characteristics such as seedling height, stem diameter, dry matter rate, ion leakage and relative injury rate were analyzed. The R2 values obtained from the model provide an indication of how well the model is performing in explaining the variance in the target variable, with the model able to explain a high proportion of the variance in all phases of the analysis. The model was able to explain 94.534% of the variance in all the data combined As a result, the findings of this research suggest that the machine learning model developed has the potential to be a valuable tool in future research and applications related to plant health and injury assessment. In addition, in the study, It has been found that it can be generally reduced negative effects of increasing salt doses by 4 g l-1 chitosan application.
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