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

Agronomy decision making

7min

Agronomists handle high amount of heterogeneous data and must take accurate decisions fastly. They use specific tools to store, query, analyze and report their research data. Digital tools secure and valorize vegetal R&D information but require some standardization. How to stay creative and innovative with a research software?

New technologies bring interactive graphics and instant reporting. Free from individual data, agronomists’ minds can focus on key performance indicators and general trends. Liberated from repetitive tasks, researchers get more productive and responsive. They are able to appreciate the benefits of real time, genetical markers, high throughput phenotyping… What tools can help them visualize their data and take agronomy decisions wisely?

Agronomical research involves several steps of evaluation at various levels before taking a decision, and agronomists can highly benefit from some automation of key decisional flow steps. How can they save time and avoid errors all along the agronomy decision-making processes?

Let’s see 3 use cases of agronomy decision-making situations: the qualification of parental line, the management of resources and the data analysis management.

Free from individual data, agronomists’ minds can
focus on key performance indicators and general trends.

Management of agronomy research resources

agronomy decision making inventory stock seed

Inventory stock warning

An agronomist must be sure he has enough seeds before setting up a field trial. An inventory displaying research seed stocks in real time is highly useful when planning an experimentation. This agronomy decision making tool enables to check the availability of the needed quantity for every material and gives warnings in case of seed insufficiency.

agronomy decision making work advancement dashboard

Work advancement dashboard

Most important resource over all, the team of the research department deserves its agronomy decision making tool, to optimize task allocation and process workflow. Let’s see how a work advancement dashboard helps share research work on a trial experiment. For instance, on a tomato scoring campaign the manager visualizes the progress of every task by experiment and by technician, when a scoring needs to be done and can anticipate the digital notebook preparation. The full integration of such decision making tool to the agronomy testing software enables future tasks anticipation and helps provide the whole team with the best working conditions.

agronomy decision making scoring app synchronization

Scoring app synchronization

Accurate agronomy data is the key to making make informed decisions and keep the R&D department responsive and competitive. Hence is important to optimize the data workflow to get as much information as possible in real time. Let’s focus on field data collection and see the benefits of synchronization of notations: when technicians are in the field, they score the plots on their plant scoring app and then synchronize to the central IT system. The researcher can see the scoring and in case of some outlier he can ask to reevaluate some plots if necessary.

Real time agronomy data is the key to making informed decisions
and keep the R&D department responsive and competitive.

Parental line qualification during the breeding program

All along the breeding program, breeders evaluate materials to choose those matching the most with their breeding objectives. This cornerstone decision of their activity relies on two kinds of data: the targeted markers and DNA sequences from the lab and the traits evaluation from the field. How agronomy decision making tools facilitate this breeding process?

agronomy decision making combining ability matrix

Combining ability matrix

The combining abilities matrix is useful for the selection of suitable parents for crossings and hybridizations among the germplasm management system. It displays the General Combining Ability¹ of each male and female parent, and the Specific Combining Ability of every specific crossing. Thanks to the filter the breeder can select only the Females and Males with positive combining abilities, which crosses may be interesting.

agronomy decision making crossing matrix

Responsive crossing matrix

Breeders use a responsive crossing matrix to compare potential parental lines and choose the crossings of the next generation. In this example let’s compare 15 males and 15 females according to breeding’s requirements: all parents Resistant to Dwarf Mosaïc and Rust, and males with a late precocity. After applying the trait filter, the breeder chooses its future crosses by checking boxes in the white area. Integrated in the plant breeding software, it saves time and helps researchers avoid errors.

agronomy decision making genealogy graph

Dynamic genealogy tool

Breeders sometimes need to query their whole database, explore genetical material over multiple generations by traits, characteristics, field results, pictures. The breeder interactive graph is a multi-window tool enabling to visualize heterogeneous data, such as the pedigree of a selected hybrid on the one hand, and on the other hand the performances of this hybrid's "relatives" such as graphs, raw data and statistics.

Integrated in the breeding decision making process,
dynamic graphs and matrices save time and help researchers avoid errors.

Agronomy data visualization and analysis

Agronomists strive to make the most of all their vast amounts of heterogeneous data. To take good decisions, and get the most out of field trials, they have much to gain in representing their information graphically or geographically and analyzing it statistically. Agronomy decision-making tools can help, by automating some representation or reporting processes.

agronomy decision making dunamic graph

Dynamic graph

Interactive graphics allow agronomists to have a quick view of their data and enables data manipulation from one experiment to another. Linked to a data grid, a graphical representation configured within the research software enables to analyze data dynamically according to various criteria. By selecting a material on a graph, the researcher gets the corresponding information on the data grid. A few clicks on a material exports it to another experiment, for instance to order a lab analysis on outlier materials.

agronomy decision making statistical report

Standard statistical report

Standard statistical reports enable agronomists to check in a few seconds a complete overview of a dataset. Including a summary of the trials, mean comparison analysis, ranking of materials, ANOVA results, analysis of residuals, estimation of missing value, and most of the statistical analysis needed for agronomy decision making.

agronomy decision making web mapping application

Web mapping application

Web mapping applications allow agronomists to compare the varieties over years and over locations. By selecting materials and traits of interest, the research department presents its results in real time on an interactive web-based map, accessible for their management or other departments (such as seed production research) through a highly secured authentication.

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

Agronomy decision making tools enable to store data, compile heterogenous information, provide knowledge management and automate decisions, give analytics and reporting.

All the examples presented here have been set up with our standard software RnDExperience®. At Doriane we have been providing research departments in breeding, testing and biotechnology with IT systems for 30 years. We design, configure and maintain RnDExperience® with a special focus on agronomy decision making since it benefits to all the actors of the research department.

From our expertise in IT for agronomy research we have seen the benefits of automated agronomy decision making tools of key decisional flow steps: faster and better analysis of the results, real time view of agronomical data and workflow, which lead to save time and resources to the R&D department.

A prerequisite is to unify the IT system: It is critical to build bridges between research activities thanks to a collaborative system allowing to combine various information from different sources, to be reactive and make the most of research data. With a transversal research information system, breeders and agronomists stay connected with other services, other departments, even other organizations, with a high level of security.

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The expertise of Doriane brings the three players of R&D the resources to organize, share and valorize their research projects:
RESEARCH DEPARTMENTS: Fast implementation of business processes ; Liberation of researchers creativity
IT DEPARTMENTS: Real-time centralization of multilocation data ; Security and integrity of data
MANAGEMENT: Maximization of research investments ; Research departments monitoring ; Intellectual assets valorization and sustainability

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