Soil Water Tension Irrigation Criteria Affects Stevia rebaudiana Leaf Yield and Leaf Steviol Glycoside Composition
Bibliographic record
Abstract
Stevia ( Stevia rebaudiana Bertoni) is of interest for the production of steviol glycosides due to their noncaloric sweetening properties. Commercial stevia leaf production to date has focused on rebaudioside A and stevioside. Relatively little is known about the cultural practices necessary for the efficient production of stevia leaf and steviol glycosides. Irrigation management is an important agronomic technique that growers can use to obtain high yield while also pursuing water use efficiency (WUE). This trial investigated the effect that irrigation onset criteria measured as soil water tension (SWT) had on dry stevia leaf yields, steviol glycoside content and yield, and steviol glycoside ratios. Two stevia cultivars, SW 107 and SW 129 (S&W Seed Company Inc., Fresno, CA), were subjected to SWT irrigation criteria of 10, 20, 40, 60, and 80 kPa over a 57-day trial period at the Oregon State University (OSU) Malheur Experiment Station, Ontario, OR. Harvested plant material was evaluated for dry leaf yield and content of several steviol glycosides. Analysis of variance (ANOVA) showed significant cultivar differences in leaf yield, leaf stevioside and rebaudioside A content and yield, and steviol glycoside ratios ( P = 0.05). Examining the data by ANOVA, dry leaf yield, stevioside percent, rebaudioside C percent, total steviol glycoside (TSG) percent, rebaudioside C yield, and TSG yield were significantly greater among the wetter (closer to 10 kPa) compared with the drier (closer to 80 kPa) SWT criteria treatments, yet a preferred treatment regime was not clearly evident. When comparing cultivars by regression analysis, there was a highly significant decrease in the stevioside content, and an increase in the ratio of rebaudioside A to stevioside from wetter to drier irrigation onset criteria (due to lower stevioside), whereas the rebaudioside A content did not respond significantly to differing irrigation criteria. Increasing dry leaf productivity with wetter irrigation criteria (closer to 10 kPa), directly increased the total rebaudioside A yield also, which in turn could provide increased crop value to the grower. Irrigating near 10 kPa produced higher dry leaf yield and total rebaudioside A yield, than irrigating at drier criteria.
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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 | 0.001 | 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".