Non-destructive method of biomass and nitrogen (N) level estimation in Stevia rebaudiana using various multispectral indices

Unmanned Aerial Vehicle (UAV) based remote sensing is one of the modern techniques for crop management, which has been used in this study for biomass and Nitrogen (N) level estimations for Stevia rebaudiana, a medicinal crop used as an alternative to sugar as a natural sweetener. Different levels of nitrogen treatments were given to S. rebaudiana and the crops were harvested for biomass estimation. Mica sense Altum multispectral sensor on board was used for acquiring the image data of the crop. The linear regression model was used to examine the best vegetation index using K-fold cross validation approach. Excess Green Index (ExG) was identified as best vegetation index for biomass estimation (R2 = 0.7; RMSE = 23.77 g/m2; nRMSE = 29.14%), whereas Enhanced Normalized Difference Vegetation Index (ENDVI) was found as best predictor for Nitrogen (N) level estimation (R2 = 0.9; RMSE = 1.75 g/m2; nRMSE = 14.59%).