Abstract
The quadratic polynomial fertilizer response model (QPFM) is the primary method for implementing quantitative fertilization in crop production, but the success rate of this model's recommended fertilization rates in China is low because the model contains a high setting bias. This paper discusses a new modelling method for expanding the applicability of QPFM. The results of field experiments with 8 levels of N, P, or K fertilization showed that the dynamic trend between rice yield increases and fertilizer application rate exhibited a typical exponential relationship. Therefore, we propose a unary non-structural fertilizer response model (NSFM). The responses of 18 rice field experiments to N, P, or K fertilization indicated that the new models could significantly predict rice yields, while two experimental fitting results using the unary QPFM did not pass statistical significance tests. The residual standard deviations of 13 new models were significantly lower than that of the unary QPFM. The linear correlation coefficient of the recommended application rates between the new model and the unary QPFM reached a significant level. Theoretical analysis showed that the unary QPFM was a simplified version of the new model, and it had a higher fitting precision and better applicability.
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Claims 8
Claim · model-written summary
Rice yield increases exhibited an exponential relationship with fertilizer rate.
- Taxon
- rice
Oryza sativae0 - Treatment
- fertilizer application ratee0
- Outcome
- yield increasese0
- Qualifier
- typical exponential relationshipe0
- Setting
- fielde0
Not reportedDirection
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“The results of field experiments with 8 levels of N, P, or K fertilization showed that the dynamic trend between rice yield increases and fertilizer application rate exhibited a typical exponential relationship.”
Claim · model-written summary
A unary non-structural fertilizer response model was proposed.
- Outcome
- unary non-structural fertilizer response model (NSFM)e0
Not reportedTaxonComparator
Verbatim
e0“Therefore, we propose a unary non-structural fertilizer response model (NSFM).”
Claim · model-written summary
New models significantly predicted rice yields in 18 field experiments.
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“The responses of 18 rice field experiments to N, P, or K fertilization indicated that the new models could significantly predict rice yields, while two experimental fitting results using the unary QPFM did not pass statistical significance tests.”
Claim · model-written summary
Two unary QPFM fits did not pass statistical significance tests.
- Taxon
- riceOryza sativae0
- Treatment
- unary QPFMe0
- Outcome
- did not pass statistical significance testse0
- Value
- twoe0
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“The responses of 18 rice field experiments to N, P, or K fertilization indicated that the new models could significantly predict rice yields, while two experimental fitting results using the unary QPFM did not pass statistical significance tests.”
Claim · model-written summary
Residual standard deviations of 13 new models were significantly lower than unary QPFM.
Not reportedTaxon
Verbatim
e0“The residual standard deviations of 13 new models were significantly lower than that of the unary QPFM.”
Claim · model-written summary
Recommended application rates from the new model and QPFM had a significant linear correlation.
Not reportedTaxonDirection
Verbatim
e0“The linear correlation coefficient of the recommended application rates between the new model and the unary QPFM reached a significant level.”
Claim · model-written summary
Theoretical analysis identified unary QPFM as a simplified version of the new model.
Not reportedTaxon
Verbatim
e0“Theoretical analysis showed that the unary QPFM was a simplified version of the new model, and it had a higher fitting precision and better applicability.”
Claim · model-written summary
Theoretical analysis reported higher fitting precision and better applicability, with the model referent ambiguous.
Not reportedTaxonComparator
Verbatim
e0“Theoretical analysis showed that the unary QPFM was a simplified version of the new model, and it had a higher fitting precision and better applicability.”