Using digital imaging to quantify lentil crop growth curves and yield

Germplasm
Germplasm Genus
Lens
Germplasm Scientific Name
Lens culinaris
Germplasm Collection
  • AGILE Lentil Diversity Panel (LDP)
  • Lentil Nested Association Mapping (NAM)
Executive Summary

to be expanded

Attribution
The following researchers and their organizations were involved in this work and should be credited for their role in any resulting or related publications.
Data Custodian
Kirstin E Bett
Collaborator
  • Derek M. Wright
  • Sandesh Neupane
  • Karsten Neilson
  • Tania Gioia
Data Curator
Lacey-Anne Sanderson
Research Organization
University of Saskatchewan
Experiments
UAV imaging Lentil to dissect crop growth curves: Lentil AGILE LDP over four site-years from 2017-2018
Data Collector
  • Sandesh Neupane
  • Derek M Wright
Experimental Site Locations
  • Rosthern, Saskatchewan, Canada
  • Sutherland, Saskatchewan, Canada
  • Metaponto, Matera, Italy
Timepoints
  • 2017
  • 2018
Key Measurements
  • Canopy Height (m)
  • Canopy Area (m2)
  • Canopy Volume (m3)
Objectives

  • Quantify the height, area and volume of crop vegetative growth across multiple timepoints using UAV mounted RGB and multispectral cameras across diverse germplasm and environments.

  • Develop genetic markers by modelling the vegetative growth curve from the above data and combining that with a dense exome capture dataset.

Associated Datasets

  • Groundtruth Phenotyping datasets (GitHub)

    These datasets consist of directly observed measurements taken by researchers using traditional methods. More specifically, the following measurements are included: plant length (cm), canopy height (cm), canopy width (cm), straw biomass (g), lodging (1-5 scale), growth habit (0-2 scale). Additionally, phenological measurements (e.g. days to flower) were taken. These data were collected on the same plots that were surveyed via UAV.

  • UAV Image-derived Phenotyping datasets (GitHub)

    These datasets consist of "crop_height" (i.e. canopy height), "crop_area" and "crop_volume" measurements derived from UAV-collected images using PlotVision (see Experimental Design for more details). These data were exported from PlotVision and are further defined in their docs. As mentioned above, these data were derived from images taken of the same plots the ground truth dataset describes.

  • GWAS datasets (GitHub)

    These datasets were used to perform the genome-wide association studies undertaken within this experiment.

UAV-based high-throughput phenotyping for crop growth analysis: Lentil AGILE NAM over four site-years from 2021-2022
Grant Activity
AGILE Activity 2: Phenotyping in three major lentil production macro-environments
AGILE: Application of Genomic Innovation in the Lentil Economy
  • Kirstin E Bett
  • Albert Vandenberg
University of Saskatchewan
2014-2019