Innovation uptake by plant breeders
Explore what is known in literature surrounding how plant breeders make decisions when faced with complex information, the particularities of technology adoption and knowledge dissemination in public institutions, and the role of market opportunities in framing technology choice.
Answer a range of questions: What would make them use, or increase the use of, databases? What would help breeders extract maximum value from complex information? How do breeders prefer to have complex and varied information organized?
Recent advances in the ‘omics research has led to a dramatic growth in technologies available to the breeders. The availability of various ‘omics data sets should theoretically provide them with a more comprehensive information relating to their crop species. However, big data generated by various novel technologies brings the challenge of actually using it and transforming it into decision-relevant knowledge. The USask lentil breeding program regularly receives offers from other renowned, well- intentioned R&D partners who wish to develop “game-changing” technologies to “revolutionize” the breeding program. The end results of these collaborations, however, often fall short due to a deep philosophical divide between the ‘omics and plant breeding worlds.
Although implausible and counter-intuitive, even highly educated experts from various science fields avoid or postpone technology uptake. As a case in point, we witnessed an extremely low adoption of a digital data collection method developed by the KnowPulse team at the outset of the AGILE project. Adoption of this method was also uneven in other pulse crop research and breeding programs (e.g. pea, chickpea) at the USask. In collaboration with P2IRC, online questionnaires and semi-structured interviews were conducted to assess uptake and use. Our study results demonstrated that how and when the technology was introduced to the breeders, along with the institutional regulations, organizational structure, attitudes towards risk, and leadership styles all affected the decision to adopt.
Breeders in public research institutions have significant autonomy in managing their breeding program. Their decision-making process may also include bias, errors, framing issues and attitudes towards risk. Deconstructing this decision-making process into building blocks will help understand its complexity and subsequently allow R&D stakeholders (e.g. managers of research institutions, funder organizations) to create a conducive environment to facilitate the uptake of novel technologies in the breeding program.
Attribution
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Lacey-Anne Sanderson
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Research Outputs
Put down the pen; pick up the tablet: A Case Study on the Adoption of a Digital Data Collection System for Plant Breeding
Simona Lubieniechi, Crystal Chan, Kirstin Bett, Peter WB Phillips
With the rise in interest in curating, linking and using big data for plant breeding, the big question is whether users will come if systems are built. This paper explores the uptake and use of a digital data collection template and of KnowPulse, a platform website hosted at University of Saskatchewan. KnowPulse was designed to provide a one-stop site for genomics and phenomics data and a range of relevant tools for breeders of pulse crops, especially lentil. The paper highlights a host of variables that have limited full uptake and use of this innovative tool.
Canadian Plant Breeders and Bioinformaticians: Factors Influencing Decision Making and Knowledge Transfer
Simona Lubieniechi and Peter WB Phillips
This report presents the results of two questionnaires: one directed at the plant breeding community and the other was directed to the bioinformatics community. We explored whether there was a disconnect between these two communities. Answers converged in many instances and various topics, such as when ranking plant breeders’ essential skills and competencies or when learning what type of information breeders regularly look up when they make selection decisions during the plant breeding process. Some notable communication gaps surround 1) who is involved in making breeding decisions, 2) how often breeders are using digital devices such as automated sensors or imaging tools, 3) what type of databases (internal or external) breeders’ access in their breeding program, both indoors and in the field.