Effect of Sugarbeet Density and Harvest Date on Most Profitable Nitrogen Rate
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Core Ideas First evaluation of profitable N rates in sugarbeet using variable revenue and costs. Most profitable N rate was 136 kg N ha −1 , regardless of plant density or harvest date. More fertilizer N needed to maximize root yield than profits or sucrose yield (recoverable white sucrose per tonne). Opportunity to modify payment structure to reward sucrose over root yield. Risk of potential N losses was lower with higher plant density and later harvest. The response of sugarbeet ( Beta vulgaris L.) root and sucrose yield to N fertility is well known, but the influence of recent changes of higher plant densities and/or earlier harvest dates may influence optimal fertilizer N rates. An experiment, in a split‐plot design, was established in 2013 to 2015 at two locations each year. There were 10 whole plot treatments consisting of combinations of five N rates and two plant densities and subplot of harvest date (mid‐September, late October). A lack of interactions among N rate, harvest date, and plant density for root or sucrose yield and profit margins, suggested no need to adjust fertilizer N based on these production practices. Nitrogen use efficiency (NUE) indices and N remaining in the field at harvest suggest a higher potential for N loss with an early than late harvest and at low vs. high plant densities; therefore, from an environmental perspective and based on equivalent profit margins, late harvest and high plant densities were recommended. Based on regression analysis, the N fertilizer rate to maximize root yield, recoverable white sucrose per tonne (RWST) and profit margins was 157, 12, and 136 kg N ha −1 , respectively. Less fertilizer N (113 vs. 152 kg N ha −1 ) was required with legume compared to grass species as the previous crop. This was the first study in a humid, temperate climate to establish recommended fertilizer N rates based on profit margins and identify an opportunity to restructure grower payments to encourage higher RWST.
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.
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 | 0.001 | 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 it