Comparing Visible Light Based Vegetation Index and Chlorophyll Meter to Estimate Chlorophyll and Nitrogen Content of Tea (Camellia Sinensis L. Kuntze) Leaves

Abstract

Leaf chlorophyll content is widely used as an indicator of tea leaves quality as well as plant nitrogen status. The development of a rapid and low-cost estimation method will considerably useful to the management of sustainable crop production. This research was aimed to develop a new method usinguncalibrated visible light images captured by a commercial camera mounted on an Unmanned Aerial Vehicle (UAV) and compared them to chlorophyll meter SPAD-502. The study used B*A* simple difference vegetation index (BAVI) which derived from L*a*b data transformation of uncalibrated RGB images captured from a UAV. Data was collected from an experiment of nitrogen dosage levels on 3 years after prunning tea crops. The result showed that the regression of BAVI values with shoots’ chlorophyll content were shown by linear equations y = 0.0025x + 0.9816with determinant coefficients (R²) = 0.8012 (P<0.01), while its regression with nitrogen content of shoots was y = 0.0045x + 2.982 with R² = 0.6341( P<0.01). The maximum bias of the measurement with 95% confidence was 4.14% (foliar chlorophyll content measurement) and 2.73% (foliar nitrogen content measurement) of the SPAD-502 method.