Intellectual Property Rights and Plant Variety Protection of Horticultural Crops: Evidence from Canada
Bibliographic record
Abstract
Horticultural farm cash receipts totaled CAN$8.6 billion in Canada in 2014. Horticultural crops have dominated the Plant Breeders’ Rights Office application submissions. In this paper, we first examine the application pattern of plant breeders’ rights (PBR) for horticultural crops following the enactment of the Canadian Plant Breeders’ Rights Act in 1990. Second, we assess whether stronger intellectual property rights (IPR) are needed to boost plant variety development. Plant breeders’ rights applications and grants data from the Canadian Food Inspection Agency from 1992–2014 are used to examine how PBR applications by public and private institutions have evolved in response to reductions in research and development funding for horticultural crop research by Canadian public institutions and changes to plant variety protection policies. We show that the bulk of PBR applications are for ornamental crops (followed by vegetables and fruits) involving mostly Rosa and Pelargonium and originate from European and U.S. corporations. Agriculture and Agri-Food Canada accounted for 35% and 53% of the total apple and cherry applications, respectively. Since 2005, applications for ornamental varieties have declined, suggesting the perception of a weak intellectual property protection environment. The PBR system allows farm-saved seed or propagating material use, while plant breeders can use germplasm material in new line breeding activities. Stronger IPR and royalty collection systems may promote greater private plant breeding and commercialization of new varieties for the heterogeneous Canadian horticultural crop industry.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".