Physiological and growth responses of potato cultivars to heat stress
Bibliographic record
Abstract
Climate warming is subjecting plants to heat stress, which can affect their physiological processes thereby impacting their growth, development, and productivity. Potato (Solanum tuberosum L.) is a staple food worldwide, but potato crops are very sensitive to heat stress. We have studied the effects of heat stress on the leaf chlorophyll content, plant growth, and tuber yield of 55 commercial potato cultivars in clonal tests under heat-stress conditions [HS; 35 °C (day), 28 °C (night)] and control (non-stress) conditions [CK; 22 °C (day), 18 °C (night)]. The potato cultivars varied in their response to heat stress. Overall, heat stress reduced leaf size, increased the SPAD index values for leaf chlorophyll by up to 65%, and increased plant height by 64%, but severely reduced (by 93%) the mass of the largest tuber. The HS:CK SPAD ratios positively correlated with the HS:CK plant height ratio, mass of the largest tuber under heat stress, and the HS:CK ratio for mass of the largest tuber. Potato cultivars displayed a correlated response to heat stress for their leaf chlorophyll content, plant height, and tuber mass. We have identified the most heat-tolerant and heat-susceptible cultivars for these traits. Under heat-stress conditions, potato cultivars tend not to show as much reduction in tuber mass if the plants have greater increases in leaf chlorophyll content and plant height.
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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 | 0.000 | 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 | 0.001 |
| 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".