Study on nitrogen characteristics of coated controlled-release fertilizer with different particle sizes
Bibliographic record
Abstract
At present,although controlled-release fertilizer(CRFs) has stepped on the industrial scale in China,the technology of controlled release is behind that of developed countries such as USA and Canada.Qualities of CRF of different products are different.One of the reasons for the quality difference might come from the difference of substrate of CRF,being kernel compounds of the CRF. Currently,most of researches on CRF pay great attention to the coating materials and coating technique rather than the substrate.The previous study of the authors has found that particle sizes and its distribution of the substrate affected greatly on the longevity,being a quality parameter of controlled release fertilizers.The CRFs used in this study were a resin coated Kemira Grow-How NPK(15-15-15) granule which is manufactured by Planta Controlled Release Company.The substrate was mixed based on the real proportion of particle size distribution of the commercial products.Amount of coating material is 7.7% of the substrate. Then the CRFs were divided into three groups of 23mm,34 mm and 45 mm,and incubated in distilled water with a ratio of fertilizer to water of 1∶20 for 0,1,2,3,4,5,6,7,14,21,28 and 56 days under constant temperature at 25℃±1℃,respectively.The ammonium and nitrate were determined at the given time to evaluate the effect of granule size on the nitrogen release rate(NRR).Results showed that the NRR and initial solubility are decreased with the increase of the substrate particle sizes.However,the longevity of CRF is increased with the substrate particle size.The NRR after 24 h incubation was 26.9%,4.45% and 1.26% for CRF with a particle size of 2 to 3,3 to 4 and 4 to 5 mm,respectively.The longevity is 4 d,28 d and 56 d for CRF with a particle size of 2 to 3,3 to 4 and 4 to 5 mm separately.During the early stage of incubation,nitrogen released mainly from CRF which particle size is smaller than 3 mm,whereas the later stage is from CRF which particle size is bigger than 3 mm.The ratio of coating material to substrate is increased with increase of the particle size.The ratio of coating material to substrate of CRF with particle size of 2 to 3 mm is decreased by 15.58% and that of 3 to 4 mm decreased by 4.29%.Nevertheless,the ratio of coating material to substrate of CRF with particle size of 4 to 5 mm is increased by 5.65%. Therefore,the substrate evenly distributed in particle size is one of the most important factors affecting quality of CRFs.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), 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".