Long‐term fertilization impacts on corn yields and soil organic matter on a clay‐loam soil in Northeast China
Bibliographic record
Abstract
Abstract A long‐term fertilization experiment with monoculture corn ( Zea mays L.) was established in 1980 on a clay‐loam soil (Black Soil in Chinese Soil Classification and Typic Halpudoll in USDA Soil Taxonomy) at Gongzhuling, Jilin Province, China. The experiment aimed to study the sustainability of grain‐corn production on this soil type with eight different nitrogen (N)‐, phosphorus (P)‐, and potassium (K)–mineral fertilizer combinations and three levels (0, 30, and 60 Mg ha –1 y –1 ) of farmyard manure (FYM). On average, FYM additions produced higher grain yields (7.78 and 8.03 Mg ha –1 ) compared to the FYM0 (no farmyard application) treatments (5.67 Mg ha –1 ). The application of N fertilizer (solely or in various combinations with P and K) in the FYM0 treatment resulted in substantial grain‐yield increases compared to the FYM0 control treatment (3.56 Mg ha –1 ). However, the use of NP or NK did not yield in any significant additional effect on the corn yield compared to the use of N alone. The treatments involving P, K, and PK fertilizers resulted in an average 24% increase in yield over the FYM0 control. Over all FYM treatments, the effect of fertilization on corn yield was NPK > NP = NK = N > PK = P > K = control. Farmyard‐manure additions for 25 y increased soil organic‐matter (SOM) content by 3.8 g kg –1 (13.6%) in the FYM1 treatments and by 7.8 g kg –1 (27.8%) in the FYM2 treatments, compared to a 3.2 g kg –1 decrease (11.4%) in the FYM0 treatments. Overall, the results suggest that mineral fertilizers can maintain high yields, but a combination of mineral fertilizers plus farmyard manure are needed to enhance soil organic‐matter levels in this soil type.
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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".