loading page

Low cost, automated high throughput plant phenotyping system to evaluate the response of Menthol mint (Mentha arvensis) crop to water stress
  • +1
  • Manoj Semwal,
  • Nupoor Prasad,
  • Rajesh Verma,
  • Alok Kalra
Manoj Semwal
CSIR-Central Institute of Medicinal and Aromatic Plants

Corresponding Author:[email protected]

Author Profile
Nupoor Prasad
CSIR-Central Institute of Medicinal and Aromatic Plants
Rajesh Verma
CSIR-Central Institute of Medicinal and Aromatic Plants
Alok Kalra
CSIR-Central Institute of Medicinal and Aromatic Plants


Image based high throughput plant phenotyping is a powerful tool to capture and quantify diverse plant traits. The available commercial platforms are often cost-prohibitive. This study describes the development of a low cost, automated plant phenotyping platform, which can acquire images, transfer data, segment the images, extract the traits and perform data analysis using low-cost microcomputers, cameras and IoT irrigation system. Quantifiable plant traits (e.g., shape, area, height, color) were extracted from the plant images using an in-house pipeline developed in R language. An experiment of water stress (waterlogging and drought) on Mentha arvensis (Menthol mint) crop (cv. CIM-Kosi) was conducted to demonstrate image traits being used as a proxy for plant response to water stress. It was found that the effect of drought stress on plant height and number of secondary branches could be correlated to color traits of plant canopy images. Also, the effect of waterlogging stress on chlorophyll and flavonoid content could be related to the shape traits of plant canopy images and effect on waterlogging on plant height and canopy width could be associated with color and texture traits. The imaging platforms could successfully demonstrate a viable low-cost solution for incorporating high-throughput plant phenotyping in various plant stress related research applications.
24 Oct 2022Submitted to NAPPN 2023 Conference Papers
28 Oct 2022Published in NAPPN 2023 Conference Papers