Impact of Elevated CO2 and Temperature on Growth, Development and Nutrient Uptake of Tomato
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Elevated carbon dioxide (EC) can increase the growth and development of different C3 fruit crops, which may further increase the nutrient demand by the accumulated biomass. In this context, the current investigation was conceptualized to evaluate the growth performance and nutrient uptake by tomato plants under elevated CO2 (EC700 and EC550 ppm) and temperature (+2 °C) in comparison to ambient conditions. Significant improvement in the growth indicating parameters like leaf area, leaf area index, leaf area duration and crop growth rate were measured at EC700 and EC550 at different stages of crop growth. Further, broader and thicker leaves of plants under EC700 and EC550 have intercepted higher radiation by almost 11% more than open field plants. Conversely, elevated temperature (+2 °C) had negative influence on crop growth and intercepted almost 7% lower radiation over plants under ambient conditions. Interestingly, earliness of phenophases viz., branch initiation (3.0 days), flower initiation (4.14 days), fruit initiation (4.07 days) and fruit maturation (7.60 days) were observed at EC700 + 2 °C, but it was statistically on par with EC700 and EC550 + 2 °C. Irrespective of the plant parts and growth stages, plants under EC700 and EC550 have showed significantly higher nutrient uptake due to higher root biomass. At EC700, the tune of increase in total nitrogen, phosphorus and potassium uptake was almost 134%, 126% and 135%, respectively compared to open field crop. This indicates higher nutrient demand by the crop under elevated CO2 levels because of higher dry matter accumulation and radiation interception. Thus, nutrient application is needed to be monitored at different growth stages as per the crop needs.
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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 | 0.000 |
| 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) | 0.000 | 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 it