The RQR’s 2024-2030 program is in phase with the evolution of societal issues and knowledge in the vast field of reproductive biology and its application. It integrates the issues and challenges we are currently facing, here and elsewhere in the world, such as climate change and the impact of the environment on reproductive efficiency. And to achieve this, it proposes the use of innovative tools such as modeling, bioengineering and artificial intelligence.
The program is made up of three main research axes determining the main program and two cross-functional axes, common to the three main axes, which will enhance the RQR’s scientific activities and accelerate the transfer of research results to end-users and society at large.
Leader : Vilceu Bordigon, McGill University
In the dairy and other animal production sectors alike, the economic profitability of businesses depends on the reproductive efficiency of their animals. And this efficiency is also responsible for the survival of wild species. This line of research also proposes concrete avenues to help the community target actions to improve farm animal reproduction.
Analysis of existing data will enable us to describe and quantify the extent of the impact of reproductive disorders on farms economics and animal welfare, and to target the parameters to be prioritized in conjunction with the stakeholders concerned. In parallel, to federate these data and obtain the desired results, it is crucial to examine uterine function and the factors influencing fertility and ovarian stimulation.
Other external factors also need to be better understood, such as embryo quality, semen storage techniques and assisted reproduction techniques, in order to ensure that all our efforts have the desired impact.
Sometimes, reproductive problems may require the use of antimicrobials to cure certain infections. Strategies and tools must therefore be successfully put in place to minimize their impact and presence in dairy farms.
It’s a well-known fact that living environments, diet and climate change influence health, various biological processes and the reproduction and survival of species. A better understanding of the interactions between environmental components and reproductive biology, and of the mechanisms involved, will help us to propose strategies for preventing, detecting and mitigating harmful interactions.
Moreover, facing the challenges of climate change, all avenues for action must be explored, including that of better reproductive management in companies. Thus, the results of Axis 1 research aimed at optimizing reproductive management take on their full importance here. By quantifying the impact of reproductive management on the environment, and adopting best practices in this area, Axis 2 research aims to propose concrete solutions to help achieve carbon neutrality in the dairy sector by 2050.
Revisiting and re-examining basic knowledge using new technologies and approaches can shed new light on the ever-changing challenges of reproductive biology. Axis 3’s research proposal aims to democratize the use of cutting-edge technologies to better understand male and female infertility, reproductive pathologies and why they occur, with the aim of preventing, detecting and better managing infertility in mammals.
This axis advocates innovation through the creation of biological study models, modeling and the integration of bioengineering techniques, among others, to further the study of reproductive functions. It also places great emphasis on the sharing of expertise between research laboratories.
Leader : Abdoulaye Baniré Diallo, UQAM
At the heart of any research program are data banks, which contain information on individuals, animals, cohorts, treatments, diseases and so on. Traditionally, these data are exploited in the form of various statistics, with the precautions and laws that apply. This line of research aims to better frame and organize these data, and offer a variety of ways of exploiting them.
Artificial intelligence is becoming increasingly accessible, enabling the innovative exploitation of immense data banks. Its integration into the three research axes of the RQR program is a unique opportunity for RQR members to learn about these new technologies and see how they can help achieve results. It will also encourage inter-axis and inter-institutional collaboration.
Freely defined, knowledge mobilization is a set of actions aimed at raising the profile of an organization through the simplified dissemination of its research findings to a defined target audience. These actions stem from a few key questions:
- What knowledge do we want to mobilize?
- Why is this knowledge important?
- For whom is this knowledge important?
- By what channels and means should this knowledge reach the targeted end-users?
And ultimately, a good knowledge mobilization plan should be able to measure whether it has had a concrete impact on the target clientele.
This axis aims to integrate good work habits related to knowledge transfer in RQR member laboratories. Training courses and tools will be made available to help members familiarize themselves with the various stages and means of disseminating the fruits of their research.