Monitoring vegetation growth of oil rose (Rosa damascena Mill.) by hyperspectral sensing

Abstract

In this study, traceability of the oil rose growth during vegetation period was investigated using hyperspectral detection method under the field conditions. The study was conducted in the Rose Garden at Suleyman Demirel University. Five pieces of 5 years old rose rootstocks (3 replications from each plant) were selected for the purpose of measuring and sampling. The study lasted for 33 weeks and the traditional growing activities were applied to the selected plants. Under the field conditions a spectral reflections were measured at wavelengths of between 325-1075 nm by using ASD FieldSpec HandHeld spectroradiometer and plant probe. Chlorophyll analysis was performed on selected samples. Spectral reflectance measurements and chlorophyll content were compared by Stepwise Multiple Linear Regression Analysis method, and predicting models were established. Results showed that (i) for hyperspectral sensing purpose the vegetation process of the oil rose should be divided into four major periods as growth, harvest, decline and the formation of new leaves, (ii) hyperspectral applications and reflectance values measured in the field might be used to predict chlorophyll a, chlorophyll b and chlorophyll a + b content in the oil rose, (iii) the physiological decline affecting harvest yield during vegetative growth might be identified in all periods by spectral reflectance values.