Response of greenhouse-grown bell pepper (<i>Capsicum annuum</i> L.) to variable irrigation
Why this work is in the frame
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Bibliographic record
Abstract
Aladenola, O. and Madramootoo, C. 2014. Response of greenhouse-grown bell pepper (Capsicum annuum L.) to variable irrigation. Can. J. Plant Sci. 94: 303–310. In order to optimize water use in bell pepper production information about the appropriate irrigation water applications and agronomic and physiological response to mild and severe water stress is necessary. Different water applications were tested on yield, quality and water stress threshold of greenhouse-grown bell pepper (Capsicum annuum L.) cultivar Red Knight in 2011 and 2012 on the Macdonald Campus of McGill University, Ste Anne De Bellevue, QC. The study was carried out on a soil substrate in the greenhouse. Irrigation was scheduled with four treatments:120% (T 1 ), 100% (T 2 ), 80% (T 3 ), and 40% (T 4 ) replenishment of crop evapotranspiration in a completely randomized design. The highest marketable yield, water use efficiency and irrigation water use efficiency were obtained with T 1 in both years . T 1 received 20% more water than T 2 to produce 23% more marketable yield than T 2. Fruit total soluble solids content was highest in T 4 , and smallest in T 1 . The mean crop water stress index (CWSI) of the irrigation treatments ranged between 0.08 and 1.18. Leaf stomatal conductance of bell pepper was 75 to 80% lower in T 4 than in T 1. Regression obtained between stomatal conductance and CWSI resulted in a polynomial curve with coefficients of determination of 0.88 and 0.97 in 2011 and 2012, respectively. The result from this study indicate that the yield derived justifies the use of an extra quantity of water. Information from this study will help water regulators to make appropriate decision about water to be allocated for greenhouse production of bell pepper.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 it