Seed production research
Agronomical practices and environmental conditions in the hybrid seed production fields have a great impact on profitability, and there is much to gain in finding the conditions that produce the more seeds of the best quality in the less acreage.
The aim of the seed production research team is to elaborate crop production protocols. They need to conduct experimentation to study how to use the genitors at their best for optimal hybrid production. Then they compare all the heterogeneous information of agronomical testing, analyze it and prepare the production protocol sheets.
Let’s see how a departmental plant breeding software enables researchers to conduct these studies with confidentiality, reliability and swiftness.
Testing for seed production research
Seed production researchers combine information from Breeding and Testing, they take decisions with the R&D management and production managers, and deliver protocols to Seed Production managers, Multiplication farms and follow-up technicians. (see image).
The testing campaign involves two kinds of experimentation:
- Study each parental line separately to describe its vegetal and agronomical characteristics
- Study parental lines planted together to determine the optimal conditions for seed production
Researchers run multi-location experiments and collect observations and measures during the plant growth: emergence date, leaves apparition, tasseling, lodging, disease symptoms, etc. They need strong tools such as a plant scoring app to collect accurate data from the field, over many locations and centralize it in the plant breeding software to compare it with metadata and historical data.
Metadata is very important. It consists in covariables of the experiment such as location, year, weather, sowing date, sowing density, phytosanitary, nutrient and water supply. Studying their effects on the plant growth gives information to adjust crop production protocols.
Data analysis for seed production research
Data analysis compares the performances of the parental lines depending on the covariables, in order to prepare recommendations for the seed production protocols.
On analytical reports such as the one here, researchers study two variables (yield and moisture) over two covariables (location and sowing density). It gives information on the parental line, for instance Justice yields more with a sowing density of 20.
Testing data enables researchers to study various subjects: disease resistances, Pollen release, seed quality, dates and modalities for all field operations (fertilization, castration...), sowing dates and pattern, etc. Every topic is analyzed and researchers evaluate the biggest strengths and weaknesses of the parental line.
Dynamic maps help researchers visualize results globally or more locally. Directly connected to the database, it displays trial metadata and phenotypic data.
Reporting for seed production research
Final purpose of the Research Production activity, reports summarize information in a concise way. There are two kinds of reports:
- Parental lines description depending on agricultural practices and environmental conditions. Quite similar to a variety sheet of the Product development department.
- Seed production recommendations, specific to some year and location. Depending on weather and location data, these reports issue some recommendation of sowing pattern, sowing delay between males and females, phytosanitary and nutrient treatments.
When the crop management plan is ready, it needs to be formatted and sent to seed producers in the multiplication farms. A plant breeding software such as RnDExperience® enables to prepare advanced reports including Excel and Word, that are automatically generated in PDF in several languages for fast broadcast over the world.
Seed production is the last (but not least!) step in the breeding process. The production protocol it delivers have an impact on the global profitability of the hybrid.
Researchers work closely with many different actors and deserve strong tools to communicate efficiently with Breeders on the one hand, and with Production managers on the other. They work also with field operators to collect data, and with several third parties to whom they deliver the protocols.