Fluorescence-Based Accurate Estimation of Chlorophyll in Tea Leaves Using Smartphone

Abstract

Estimation of plant leaf chlorophyll is critical for assessment of overall health condition of plants. The existing detection methods demand relatively expensive and bulky instruments, thus restricting its use for onsite investigations. Present work demonstrates a low-cost, compact fluorescence-based sensor using a smartphone to estimate the chlorophyll content in plant leaves. The extracted plant chlorophyll samples have been optically excited by using an external LED with peak emission wavelength of 475 nm, and the corresponding emitted fluorescence signals at 679 nm have been recorded by the ambient light sensor of the phone. A 3D printed compact set-up has been designed to couple it with the phone to record the emitted fluorescence signal intensity from the sample. Chlorophyll concentrations in the range of 1-12 mg/g prepared from fresh tea leaves have been accurately estimated with a sensitivity of 0.068 AU g/mg and Limit of Detection (LoD) of 0.618 μg/L. The performance of the proposed smartphone sensor has been assessed by comparing the data with the commercial chlorophyll meter.