Nitrogen rate and source effects on foliar sugar, glycoalkaloid, and amino acid composition of potato Russet Burbank
Bibliographic record
Abstract
The foliar chemicals in potatoes (Solanum tuberosum L.) could affect the growth and development of agricultural pests, such as Colorado potato beetle Leptinotarsa decemlineata (Say) and aphid Macrosiphum euphorbiae (Thomas). Thus, altering the chemical composition of potato leaves could potentially supplement integrated pest management (IPM). In this study, field experiments were conducted in Quebec, Canada, to investigate the effects of nitrogen (N) rate and source on foliar sugar, glycoalkaloid, and amino acid concentrations and tuber yield of potato cultivar Russet Burbank. Three N fertilizer sources of ammonium nitrate, ammonium sulfate, and polymer-coated urea were used at four rates of 60, 120, 200, and 280 kg N ha −1 plus an unfertilized control in a randomized complete block design. The fourth leaves from the top of 20 randomly selected plants in each plot were collected at 54, 68, and 82 d after planting for sugar, glycoalkaloid, and amino acid analysis. Tubers were collected at harvest, and the total and marketable yields were determined. Results showed that N fertilization linearly decreased sugar concentrations and these reduced sugars were conveyed and stored in tubers as starch. Glycoalkaloid concentrations in leaves were influenced by N source and rate. Both total and marketable yields quadratically varied with increasing N rates regardless of N sources, with average values of 36.4 and 28.3 Mg ha −1 , respectively. As N rate affected potato foliar chemical composition and tuber yield, N fertilization could be considered as a supplemental tool to the IPM strategy for potato pest control.
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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 | 0.001 | 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".