Balanced nutrition and crop production practices for the study of grain sorghum nutrient partitioning and closing yield gaps
Why this work is in the frame
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Bibliographic record
Abstract
Mid-west grain sorghum (Sorghum bicolor (L.) Moench) producers are currently obtaining much lower than attainable yields across varying environments, therefore, closing yield gaps will be important.Yield gaps are the difference between maximum economic attainable yield and current on-farm yields.Maximum economic yield can be achieved through the optimization of utilizing the best genotypes and management practices for the specific siteenvironment (soil-weather) combination.This research project examines several management factors in order to quantify complex farming interactions for maximizing sorghum yields and studying nutrient partitioning.The factors that were tested include narrow row-spacing (37.5 cm) vs. standard wide row-spacing (76 cm), high (197,600 seeds ha -1 ) and low (98,800 seeds ha -1 ) seeding rates, balanced nutrient management practices including applications of NPKS and micronutrients (Fe and Zn), crop protection with fungicide and insecticide, the use of a plant growth regulator, and the use of precision Ag technology (GreenSeeker for N application).This project was implemented at four sites in Kansas during 2014 (Rossville, Scandia, Ottawa, and Hutchinson) and 2015 (Topeka, Scandia, Ottawa, Ashland Bottoms) growing seasons.Results from both years indicate that irrigation helped to minimize yield variability and boost yield potential across all treatments, though other factors affected the final yield.In 2014, the greatest significant yield difference under irrigation in Rossville, KS (1.32 Mg ha -1 ) was documented between the 'low-input' versus the 'high-input' treatments.The treatment difference in grain sorghum yields in 2014 was not statistically significant.In 2014, the Ottawa site experienced drought-stress during reproductive stages of plant development, which resulted in low yields and was not influenced by the cropping system approach.In 2015 the treatments were significant, and in Ottawa, narrow row spacing at a lower seeding rate maximized yield for this generally low-yielding environment (<6 Mg ha -1 ) (treatment two at 6.26 vs. treatment ten at 4.89 Mg ha -1 ).Across several sites, including Rossville, Hutchinson, Scandia, Topeka, and Ashland, a similar trend of narrow row spacing promoting greater yields has been documented.Additionally, when water was not limiting sorghum yields (i.e., under irrigation), a balanced nutrient application and optimization of production practices did increase grain sorghum yields ('high-input' vs. 'lowinput'; the greatest difference was seen in 2014 in Rossville, 1.2 Mg ha -1 , and in 2015 in Ashland, 1.98 Mg ha -1 ).In the evaluation of nutrient uptake and partitioning in different plant fractions, there was variability across all site-years which did not always follow the same patterns as the yield, however, the low-input treatment was shown to have significantly lower nutrient uptakes across all the nutrients evaluated (N, P, K, S, Fe, Zn) and across most fractions and sampling times.The objectives of this project were to identify management factors that contributed to high sorghum yields in diverse environments, and to investigate nutrient uptake and partitioning under different environments and crop production practices.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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