“Elaborate statistics are not substitute
for meticulous experimentation.”
G.W. Snedecor

Farming robots collecting plant breeding data


Being used more and more on production farms, farming robots collecting plant breeding data start paving their way to the research department.

When monitoring the plants growth, researchers are gathering information to characterize every experimental condition. Yield and harvest quality are useful results but most of the time the study is more complex, it focuses on subtler trait expression. The information required can be collected manually by observing the plants and taking notations, or by farming robots collecting plant breeding data !

Farming robots can “learn” complex processes and achieve precision tasks in production fields. They replace manual labor and lessen agrochemical use, therefore reducing costs and environmental impact. Such robots also scan the production fields, gathering images to map field heterogeneities, and can as well be used to detect anomalies and apply treatment directly.

In the plant breeding department and in research stations, can be found other kinds of farming robots collecting plant breeding data in the fields. Integrating this new data set to the existing research information system can be complex and challenging. How can the IT system be adapted to integrate, store and analyze all this data?

1. Farming robots in the production fields




In production farms, farming robots can replace hard work such as fruit picking, pruning or chemical sprayings: by weeds destruction or drone auxiliaries dropping.

  • Automatic mechanical weeding, such as Oz by Naïo and Anatis by Carré
  • Grass management robots for vineyards and forestry such as Vitirover
  • Precision spraying of herbicide (Ecorobotix) or auxiliaries (Parabug) for field crops
  • Soil preparation with the high precision geopositioning CEOL by Agreenculture

Will these herds of mowers replace herbicides in the fields? It may soon become a reality, and we’ll see more and more help from robots, starting with fruit crops since they require manual work to maintain the trees and pick fruits, such as pruning bots.

Research departments worldwide are currently studying such farming robots, either to create new ones or to study the benefits of existing models on specific crops. 

2. Farming robots collecting plant breeding data

Monitoring a field for breeding or testing involves land planning and plant monitoring, usually done manually, with the help of data collection software. There comes the sensor-embedded farming robot collecting plant breeding data, which are “especially useful for plant breeders, who have to painstakingly analyze thousands of plants for plant size and color, fruit size and form, and insect damage” as explains Bosch experts about their Deepfield Robotics project.

Farming robots collecting plant breeding data




  • The BoniRob is an agricultural robot developed by Bosch that can conduct autonomously repeating phenotyping tasks for crop stands and even for individual plants. Furthermore, it can be used as a carrier, supplier and base for multiple BoniRob-Apps. Current apps are (i) phenotyping, (ii) penetrometer and (iii) precision spraying.
  • The vineyard mapping Physiocap by Fruition Sciences that measures shoot diameter, number of shoots per vine and average biomass, in each row it scans and generates maps.
  •  The Anatis robot by Carré is an example of auto-driving soil preparation robot able to collect several measures on the soil, air and plants.

Prototypes of farming robots collecting plant breeding data



  • The Thorvald, by the Norwegian University of Life Sciences, that is meant to support research on autonomous outdoor navigation and mapping, soil quality assessment, crop yield prediction, in-field logistics and transportation.
  • The Phoenix, also called Armadillo, developed by Hohenheim University in Germany is an autonomous sensor platform to develop new sensing systems.

High throughput phenotyping



This area of research consists in gathering as many pictures and measures of the studied plants as possible, generating a big data set that can increase the efficiency of crop improvement. Phenotyping platforms (HTPPs) such as Phenopsis enable such study indoor, but farming robots collecting breeding data are providing similar services to field breeding and testing:

  • The autonomous Phénomobile platform that collects plant information for evaluating growth, nutrition and stress data.
  • Heliaphen by Sunrise is a high throughput phenotyping robot to study plant responses to draught stress from germination to maturity.
  • The autonomous Robotanist by Carnegie Mellon University’s Robotics Institute provides high resolution spatial, spectral, and physical information about Sorghum field data.

Comparing various monitoring tools with farming robots collecting plant breeding data


Comparison of various toold to collect plant breeding data.

Various methods enable plant researchers to studying trait expression during the plant growth. Let’s compare them according to two criteria, for comparable resources :

  •  DEBIT: How much information they provide over time.
  •  EXHAUSTIVITY: How many plots can be covered over a period of time.

The graph on the left provided by Agri Sud-Ouest Innovation shows that farming robots collecting plant breeding data can be more efficient than manual data collection, and drones even more.

Nevertheless, every method has specific advantages, like the accuracy of still weather stations, the analytical ability of technicians taking notations, the homogeneity of robot measures, and the capacity of drones to capture data instantly over a large area. It’s a combination of such factors that influence the choice of researchers for the data collection method that fits optimally its objectives.

3. Integrating farming robots collecting plant breeding data in the information system


Integration of the farming robot collecting plant breeding data to the research IT system

Arvalis researchers in phenotyping reckon the biggest challenge is computational: “The change in obtained data type raises the question of their management and their integration in breeding tools and decision-making tools”.

When it comes to implementing new data and processes at the heart of the researcher’s work tool, precautions must be taken and every project adapted to its existing system. Besides, it is crucial to be able to adapt the R&D IT system to integrate the wealth of field information provided by automatic phenotype observation.

An interface needs to be built between the farming robot collecting plant breeding data and the existing experimentation management database. On the left is a typical example of data processing cycle Doriane has studied for one of its customers using aerial drones (drone data in green).

Implementation methods and tools may vary a lot, depending on the research objectives and the type of robot data or work needed, and may vary as well in time, since these technologies are evolving fast. Therefore, only research departments with an evolutive IT system will be able to integrate plant breeding robots.

With RnDExp Ready or RnDExp Custom from Doriane, all processes and data settings are configurable and can evolve along the needs of the researchers. It enables the possibility to integrate farming robots and drones in the research department.

RnDExp systems can be configured to integrate the processes required to handle farming robots collecting plant breeding data:

  • Planning of data capture projects with such tools
  • Centralization of results captured
  • Integration into the general process of breeding decision making thanks to data analysis tools.


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