13May
On: 13 May 2019 In: Agriculture

How drone data significantly improves seed breeding and seed production

Seed companies around the world deploy drone solutions to collect high throughput plant data and unlock the phenotyping bottleneck with aerial drone data.

Collecting large-scale field-based plant phenotypic data with sufficient resolution and accuracy, and in a reproducible manner, represents a challenge in plant science research and has been a real bottleneck for the effective use of genomic data for crop improvement. It can also be very labor intensive and costly. Recent drone hardware and image processing innovations now enable frequent, fast, non-invasive and accurate measures of traits, and help streamline processes. Drone solutions also help accurate seed production monitoring and forecasting, thus lowering both logistics and markets risks. These solutions ar e currently successfully deployed globally by Delair – a leading supplier of professional UAV solutions – and its breeder and seed producer customers, in order to provide farmers with the most optimal crop varieties in terms of flowering time, grain yields or disease resistance.

Digital twins of experimental fields and phenotyping with drones

By combining new-generation drone systems and sophisticated aerial imagery analytics, seed breeders and producers can get a complete, integrated and easy-to-use workflow to extract data. This complete workflow includes:

  1. Build the digital twins of an experimental field with drones
  2. Assess and validate the trial
  3. Extract key traits phenotyping thank to aerial imagery analytics
  4. Link the extracted traits at microplot level with market software used by seed companies, so that they can value external data and algorithms

Delair performed such an operation for Mas Seeds, a leading European seed producer active in 40 countries across continental Europe and around the Mediterranean basin, for all hybrid field crops. Sunflower being a major crop supplying 50% of Europe’s food oil market, Mas Seeds’ main objective is to continuously improve sunflower seeds in order to decrease the breeding burden while enhancing the phenotyping capacities.

Digital twin of sunflower trial plots built from data collected by the Delair UX11 Ag multispectral drone and analyzed on Delair Aerial intelligence platform (delair.ai)
Learn more

The seed producer has collaborated with Delair on two key aspects of seed breeding: plant counting and yield forecasting. Based on the digital twins of more than 4,000 micro-plots in fields of around 10 hectares (25 acres), Delair has been able to provide unprecedented insights on the biomass, the Leaf Area Index (LAI) and the chlorophyll concentration for each plant in the field. A benchmark of every microplot of the field has also allowed to quickly quantify traits and varieties performances.

There are many other traits that can be extracted from aerial imagery, including physical characteristics (plant height and color, emergence quality, flowering, stay-green or weed presence).

  • Emergence quality: a key trait to select plants that grow very rapidly at the start of the growth cycle.
  • FCover: this is a process to map the fraction of ground covered by green vegetation. Practically, it quantifies the spatial extent of the vegetation and distinguishes where the biomass is, and then calculates the ratio.
  • Stay Green: a key trait for corn crops is the capacity of the plants to stay green as late as possible in the season. Aerial imagery collected by drones enables frequent, accurate and cost-effective monitoring of this trait.
  • Flowering: flowering stage measurement is another key trait that can be extracted from drone data. Quantification is possible to benchmark the crop behaviour in between the microplots, by providing a flowering rate at microplot level.
  • Stay Green: a key trait for corn crops is the capacity of the plants to stay green as late as possible in the season. Aerial imagery collected by drones enables frequent, accurate and cost-effective monitoring of this trait.

 

 

Stay green capacity: in dark green, the microplots of high stay-green capacity. In white, the microplots that are already yellowing.
  • Flowering: flowering stage measurement is another key trait that can be extracted from drone data. Quantification is possible to benchmark the crop behaviour in between the microplots, by providing a flowering rate at microplot level.

 

 

Flowering answer of a Canola field: in dark red, high rates of flowering, in pink, low rates.

Crop inventory and yield forecasting drastically simplified with drone data

Accurate and reliable yield forecasting is a long-standing challenge for seed producers as uncertainty can have high impact across the value chain. To achieve better forecast accuracy, drone-based data is a real game changer to better estimate key parameters that will have an impact on yields and drive precision practices.

Early in the season, analytics such as exact planted area measure, male and female qualification, plant population estimates and health monitoring are timely tools that greatly decrease the uncertainty areas and allow smart sampling in the field. They also enable precision herbicide spraying, with both an environmental (50% less volume applied, and no product waste) and an economical impacts benefits (savings of 20€/ha).

Watch our free webinars

null

Watch now!

Seed breeding and production reinvented with aerial data acquisition and analytics – in partnership with SeedWorld