Food and fuel from Canadian oilseed grains: Biorefinery production may optimize both resources
Bibliographic record
Abstract
Food and fuel markets are seen as competing for common land and biomass resources. However, in a well‐designed biorefinery, the production of food and fuel might be synergistic. Canadian oilseed crops could be processed in Canada to increase opportunities for rural development and improved environmental stewardship. Biorefinery processing of grain crops will yield fractions with little or no utility as food. The objective of this study was to simultaneously optimize the yield of high quality food, animal feed, and energy co‐products. Oilseed crops grown in western Canada are typically processed into two fractions: oil and meal. The quality of oilseed meal, as a nutritional ingredient, is greatly affected by extraction processes. It is proposed that processes are developed to separate anti‐nutrients and compounds that have nutritional value to achieve a maximum yield of total nutrients. Practical applications : Organic materials that have little nutritional value might then be processed for utilization as biomass for energy or chemicals. We have devised processes for fractionation of various Cruciferous crops that simultaneously produce food, feed, industrial chemicals, and raw materials for energy production. In this report, we describe the performance of several crops that potentially produce high quality protein for food as well as oil, carbohydrate, and glucosinolates that could be used for industrial purposes. It is proposed that processes are developed to separate anti‐nutrients and compounds that have nutritional value to achieve an optimum utilization. The composition of the input material before processing is determined by both plant genotype and environment. Principal component analysis shows trends in composition that reflect the impact of genotype and environment. Protein was highest (greatest CP1) in seeds grown in Canora and lowest in Truro while protein was highest in Sinapis alba and lowest in Brassica rapa . Oil was highest in seed grown in Saskatoon and for Brassica juncea (greatest CP2).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".