Defining Irrigation Set Points Based on Substrate Properties for Variable Irrigation and Constant Matric Potential Devices in Greenhouse Tomato
Bibliographic record
Abstract
Ongoing research on organic growing media for greenhouse tomato production is driven by the constant changes in the quality, stability, and form of the organic byproducts used in the manufacturing of these media. This study was undertaken to determine appropriate irrigation set points for a sawdust–peat mix (SP) under development given that the performance of this substrate appeared to be strongly dependent on appropriate irrigation management. A greenhouse tomato experiment was conducted to compare different irrigation management approaches for a SP substrate in the spring and summer. Using preliminary measurements from an initial experiment (Expt. 1), different irrigation strategies for the SP substrate were compared in a second experiment (Expt. 2): 1) a variable irrigation regime using a timer control (with frequency adjusted as a function of irradiance); 2) tensiometer control at –1.5 kPa; and 3) two constant substrate water potential devices: –1.1 kPa and –0.9 kPa. An irrigation timer/controller using solar radiation input was used with a rockwool control (RC) substrate. Measurements of plant activity [photosynthesis rate and stomatal conductance ( g S )], substrate physical and chemical properties, biomass, and yield were obtained. For all irrigation strategies, results indicated that 10% to 20% higher photosynthesis rates and g S values were obtained with the SP substrate compared with RC. Data indicated that moderate drying conditions (matric potential ranging from –2.2 kPa to –1.5 kPa in Expt. 1 and Expt. 2, respectively) relative to container capacity (–0.6 kPa) were beneficial for improving plant photosynthetic activity and allowed the highest yields for the SP substrate. Variable irrigation management showed higher levels of plant activity than constant watering and increased the oxygen concentration in the substrate by ≈2% in absolute value relative to the constant water potential device. Lower CO 2 and N 2 O levels were also observed with the variable irrigation strategy. On the other hand, maximum nutrient solution savings were achieved with the constant matric potential devices (8% to 31% relative to the RC). This study showed high productivity potential for the SP substrate with suitable irrigation management. Replacing conventional growing media with organic waste-based products using an appropriate irrigation strategy may help to increase the sustainability of the greenhouse industry.
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 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 | 0.001 |
| 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 | 0.001 | 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 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".