Unmanned aerial vehicle-based vegetation monitoring of aboveground and belowground traits of the turmeric plant (Curcuma longa L.)

Unmanned aerial vehicle (UAV) platform is a high throughput phenotyping technology that successfully estimates the growth performance, physiological changes, and yield. The objective of this study was to classify different clusters of turmeric genotypes based on UAV multispectral imageries of the aboveground traits and to predict the belowground rhizome attributes. In the case of the aboveground traits, estimated leaf area, pseudostem height, pseudostem fresh weight, and pseudostem dry weight in two clusters of turmeric plants were closely related to green leaf index (GLI(red); R-2 = 0.81), UAV-calculated equation (R-2 = 0.57), green normalized difference vegetation index (GNDVI; R-2 = 0.62), and GNDVI (R-2 = 0.46), respectively. UAV-derived GLI(red) accurately estimated the belowground rhizome traits, i.e., rhizome fresh weight (R-2 = 0.60) and rhizome dry weight (R-2 = 0.75) of turmeric genotypes. Root and rhizome traits in turmeric genotypes were subjected to multivariate cluster analysis and were categorized into two clusters [Cluster I: TRG1, UB, URT, ST, Lei, and PB (bulky rhizome); Cluster II: TK, PNG, PJT, and IND (miniature rhizome)] using normalized difference vegetation index (NDVI) and GNDVI. Finally, based on curcuminoids yield, the main deciding factor in turmeric production, two elite genotypes, namely TRG1 (4.3 g plant(-1)) and ST (3.8 g plant(-1)), were identified as superior turmeric accessions. In conclusion, the present study successfully developed an approach to estimate the aboveground and belowground traits of turmeric plants using the UAV platforms and also verified the superior accession by curcuminoids yield.

Automated summary

This study successfully estimated the aboveground and belowground traits of turmeric plants using a UAV platform, and verified the superior genotypes based on curcuminoids yield.