UAV imaging Lentil to dissect crop growth curves: Lentil AGILE LDP over four site-years from 2017-2018
Overview
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.
Parent Research Study
Experiment Summary
This experiment uses images captured by RGB and multispectral cameras mounted on unoccupied aerial vehicles (UAV) flown over multiple site-years in Saskatchewan, Canada and Metaponto, Italy. These images survey a lentil diversity panel (324 genotypes) to derive canopy height, area and volume measurements across a number of time points throughout the growing season. These data enable modeling of growth curves for volume, height, and area of a large population grown in multiple environments.
A principal component analysis and hierarchical clustering revealed differential growth patterns across contrasting environments, with large variations in temperature and photoperiod, within our lentil diversity panel. Combining this analysis with the SNPs collected in Exome capture sequencing and variant calling of the AGILE Lentil diversity panel: 324 lentil lines analyzed in 2017-2020, we identified genetic markers associated with crop growth.
Germplasm
| Germplasm Genus |
Lens
|
|---|---|
| Germplasm Scientific Name |
Lens culinaris
|
| Germplasm Collection |
AGILE Lentil Diversity Panel
|
Experimental Design
| Experimental Site Locations |
|
|---|---|
| Timepoints |
|
Experimental Design
Field trials were arranged in a randomized lattice square (18 x 18) experimental design with three replications in each site year. A lentil diversity panel (LDP) consisting of 324 lentil genotypes were evaluated over 4 site-years in Sutherland, Canada 2017 (Su17), Sutherland, Canada 2018 (Su18), Rosthern, Canada 2017 (Ro17) and Metaponto, Italy 2017 (It17).
Manually collected measurements of plant length (length of longest stem in the plot), canopy height (from ground to top of vegetative growth at highest point in the plot) and canopy width (longest straight line across the plot with vegetative cover) were recorded using a meter scale and taken at swollen pod stage (when 10% of plants per plot had one swollen pod). Plot (straw + seed), Straw (above-ground) and Seed biomass were measured using a scale after each plot had been harvested and dried. Days from sowing to: emergence (DTE), flowering (DTF), swollen pods (DTS) and maturity (DTM), were recorded on a plot basis when 10% of the plants had emerged, one open flower, one swollen pod, and 50% dry pods, respectively.
Image acquisition was carried out using the following:
- Canada Siteyears: Two Draganfly quadcopter UAV (X4-P and Commander) with 24.3 MP Sony a5100 or 20.1 MP Sony QX1 (2017 sites) and a MicaSense RedEdge 3 multispectral camera (2018 sites). The UAV had been programmed to fly the trial autonomously at 15 or 20 m above ground level at a ground speed of 1.7 meters per second.
- Italy Siteyear: A DJI Inspire 1 Pro UAV with 16 MP DJI Zenmuse X5 camera. The UAV was programmed to fly in autonomous mode at an altitude of 15 or 20 meters above ground level, with an optimized ground speed to ensure accurate coverage.
After imaging the field trials, individual images were stitched together, and orthormosaics of each flight date were generated using Pix4Dmapper. Further image analyses were carried out using PlotVision following the default methods to obtain vegetative indices (Blue Normalized Difference Vegetative Index or Excess Green) from which plot height, plot area and plot volume were derived.
Phenomics
Key Measurements
- Canopy Height (m)
- Canopy Area (m2)
- Canopy Volume (m3)
Attribution
Researchers
| Data Collector |
|
|---|---|
| Data Custodian |
Kirstin E Bett
|
| Data Curator |
Lacey-Anne Sanderson
|
Associated Datasets
Dataset
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.
Funding
Research Organization
Funding Statement
This research was conducted as part of the “Application in Genomics to Innovation in the Lentil Economy (AGILE)”, a project funded by Genome Canada and managed by Genome Prairie. We acknowledge the matching financial support from the Saskatchewan Pulse Growers, Western Grains Research Foundation, the Government of Saskatchewan, and the University of Saskatchewan. This was also funded in part by the Canada First Research Excellence Fund (CFREF), Plant Phenotyping and Imaging Research Centre (P2IRC), managed by the Global Institute for Food Security (GIFS). We are grateful to the Agronomic Crop Imaging (ACI) lab and pulse breeding field crews at the University of Saskatchewan (U of S) and ALSIA (Agenzia Lucana di Sviluppo e di Innovazione in Agricoltura) in Metaponto, Italy.
Funding Grant
Grant Logo
Title
AGILE: Application of Genomic Innovation in the Lentil Economy
Data Custodian
- Kirstin E Bett
- Albert Vandenberg
Research Organization
Funding Range
2014-2019