Environmental and Cultivation Factors Affect the Morphology, Architecture and Performance of Root Systems in Soilless Grown Plants
Bibliographic record
Abstract
Soilless culture systems are currently one of the fastest-growing sectors in horticulture. The plant roots are confined into a specific rootzone and are exposed to environmental changes and cultivation factors. The recent scientific evidence regarding the effects of several environmental and cultivation factors on the morphology, architecture, and performance of the root system of plants grown in SCS are the objectives of this study. The effect of root restriction, nutrient solution, irrigation frequency, rootzone temperature, oxygenation, vapour pressure deficit, lighting, rootzone pH, root exudates, CO2, and beneficiary microorganisms on the functionality and performance of the root system are discussed. Overall, the main results of this review demonstrate that researchers have carried out great efforts in innovation to optimize SCS water and nutrients supply, proper temperature, and oxygen levels at the rootzone and effective plant–beneficiary microorganisms, while contributing to plant yields. Finally, this review analyses the new trends based on emerging technologies and various tools that might be exploited in a smart agriculture approach to improve root management in soilless cropping while procuring a deeper understanding of plant root–shoot communication.
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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 | 0.000 |
| 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".