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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.