Respiration rate of potatoes (solanum tuberosum l.) measured in a two-bin research scale storage facility, using heat and moisture balance and gas analysis techniques
Bibliographic record
Abstract
Fennir, M.A., Landry, J.A. and Raghavan, G.S.V. 2003. Respiration rate of potatoes (Solanum tuberosum L.) measured in a two-bin research scale storage facility, using heat and moisture balance and gas analysis techniques. Canadian Biosystems Engineering/Le genie des biosystemes au Canada 45: 4.1-4.9. Heat and moisture balance, in-store gas analysis, and mass loss methods were applied for quantifying respiration rates and moisture losses of potatoes stored in a two-bin research scale storage facility that was specially built and instrumented for long term storage of potatoes. The heat and moisture balances were applied on data collected for two months, and in-store gas analysis also was performed during a 40-day period. Net heating rate produced by potatoes was quantified and converted into respiration rates as CO2 (mL kg -1 h -1 ). The daily in-store gas analysis was also used for quantifying respiration rate as CO2 produced. Respiration rates obtained by the heat and moisture balance were found to be in agreement with ranges reported in the literature. However, they were higher than rates obtained by in-store gas analysis and by closed system gas analysis. Mass losses were quantified using the mass balance and mass loss analysis performed over the entire storage period. Results showed agreements among the two measurements and losses estimated were also in agreement with those reported in the literature. The study demonstrated the feasibility of using the heat and moisture balances and mass loss methods for instore determination of respiration rates, and their use as indicators for changes in physiological and health status of stored perishables.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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".