Water activity measurement: demonstration of a single and nonspecific optimal storage value for orthodox forest seeds
Bibliographic record
Abstract
Water activity (aw) is a non destructive, portable and rapid technique to assess moisture of hygroscopic materials like orthodox seeds. aw, as equilibrium Relative Humidity (eRH), is a reliable moisture indicator because it is a function of the water potential (Ψ) which portrays the energy status of water in hygroscopic matrixes.\nCemagref (France) demonstrated the efficiency of aw applied to moisture management of major temperate forest orthodox seeds. Since 2007, in cooperation with Cemagref, the Ministère des Ressources naturelles et de la Faune du Québec decided to verify that aw is also efficient with orthodox boreal species. The three major species of the Québec's reforestation program, representing 95% of the 470 millions seeds used in 2009, were characterized through the production of sorption isotherms. These isotherms allowed to describe the moisture behaviour of the seeds and to determine the optimal aw value for storage. All the results follow the same pattern obtained formerly in France. aw is now successfully used in France and Québec tree seed centres. Thanks to the numerous sorption isotherms data on the different species, it appears that every optimal storage value obtained for each orthodox species, always ranges in the region of aw 0.35 (140 MPa water potential). We assume that this value could be profitably used as a universal target for moisture management of diverse orthodox reproductive material in gene banks where it is not operationally possible to determine optimal gravimetric moisture content for mid to long-term storage due to the samples size.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".