Moderate Deficit Irrigation and Reduced Nitrogen Application Maintain Tuber Quality and Improve Nitrogen Use Efficiency of Potato (Solanum tuberosum L.)
Why this work is in the frame
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Bibliographic record
Abstract
Efficient water and nitrogen (N) management are essential for sustaining potato (Solanum tuberosum L.) production under limited resource conditions. This study investigated the effects of deficit irrigation and reduced N application on tuber quality parameters including specific gravity (SG), starch content (SC), and tuber dry matter (TDM) as well as agronomic water use efficiency (WUE) and nitrogen use efficiency (NUE) in four commercial potato cultivars (Canela Russet, Mesa Russet, Russet Norkotah 3, and Yukon Gold) over two seasons (2016 and 2017) at Colorado State University’s San Luis Valley Research Center. Three irrigation levels (100%, ~80%, and ~70% evapotranspiration replacement) and two N application rates (165 and 131 kg N ha−1) were evaluated using four replications. Moderate deficit irrigation (up to ~18% ET reduction) improved or maintained SG, SC, and TDM in all four cultivars, while severe deficit irrigation (~30–40% reduction) reduced tuber quality. Reduced N application improved NUE in all cultivars without compromising tuber quality or yield. While WUE responded variably to deficit irrigation, NUE was highest under moderate to full irrigation and low N rate. Although effects on WUE were variable, integrating moderate deficit irrigation (18%) with reduced N application (20%) enhanced NUE while maintaining tuber quality.
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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 | 0.000 | 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 | 0.000 | 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 it