MODELING STEVIA YIELDS DEPENDING ON DENSITY AND MINERAL FERTILIZERS RATES
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Date
2021
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Abstract
Stevia is one of the most prospective sweeteners and medicinal plants in dietic treatment. The crop is cultivated almost worldwide,
however the cultivation technology is still studied insufficiently. The generalization of current achievements of Ukrainian and foreign
scientists in the field of stevia cultivation was used as the basis for the creation of mathematical models of crop productivity depending
on plant density and NPK fertilizers rates. The mathematical models, developed using the means of polynomial and multiple linear
regression analysis, provided reasonable accuracy of the crop yield prediction (MAPE-28.77%-52.86%). The lowest errors (MAPE-
3.09%) were observed for the model of stevia productivity depending on plant density, which was created using an artificial neural
network approach. It was determined that the best yields of stevia are obtained under the plant density of 80-120 thousand plant/ha
and mineral nutrition with phosphorus and potassium fertilizers, while nitrogen ones are less important.
Description
Vozhehova R., Lykhovyd, P., Bilaieva I., Shebanova V., Rudik O., Sinhaievsky Andrii. Modeling stevia yields depending on density and mineral fertilizers rates. Modern Phytomorphology 15:82-85, 2021. https://cutt.ly/xTvJeXG
Keywords
Stevia rebaudiana Bertoni, medicinal plant, neural network, regression analysis, fertilization, plant density, productivity