Synergetic light and cytokinin treatments mitigate the recombinant protein yield depression induced by high‐density cultivation of hydroponically‐grown <i>Nicotiana benthamiana</i>
Bibliographic record
Abstract
Abstract Plant molecular farming is currently operating a transition from soil‐based cultures toward hydroponic systems. In this study, we designed a whole‐plant NFT (nutrient film technique) platform for the transient expression of influenza virus‐like particles harboring hemagglutinin H1 proteins in Nicotiana benthamiana . In particular, we examined the effects of plant density during the post‐infiltration expression phase on plant growth and H1 yield in relation to the daily light integral (DLI) received by the crop and the exogenous application of 6‐BAP cytokinin (CK). We expected from previous work that high DLI and CK treatments would stimulate the development of highly productive leaves on axillary (secondary) stems and thereby improve the H1 yield at the whole‐plant scale. Increasing plant density from 35.7 to 61 plants m –2 during the post‐infiltration phase significantly decreased the proportion of axillary leaf biomass by 30% and H1 yield per plant by 39%, resulting in no additional yield gain on a whole‐crop area basis. Adding CK to the recirculated nutrient solution decreased the harvested leaf biomass by 31% and did not enhance the relative proportion of S leaves of the plants as previously reported with foliar CK application. There was a 36% increase in H1 yield when doubling the DLI from 14 to 28 mol m –2 s –1 , and up to 71% yield gain when combining such an increase in DLI with the hydroponic CK treatment. Contrary to our expectations, leaves located on the main stem, particularly those from the upper half of the plant (i.e., eighth leaf and above), contributed about 80% of total H1 yield. Our study highlights the significantly different phenotype (~30% less secondary leaf biomass) and divergent responses to light and CK treatments of NFT‐grown N. benthamiana plants compared to previous studies conducted on potted plants.
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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 | 0.000 | 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 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".