Abstract
Leaf area index (LAI) is used for crop growth monitoring in agronomic research, and is promising to diagnose the nitrogen (N) status of crops. This study was conducted to develop appropriate LAI-based N diagnostic models in irrigated lowland rice. Four field experiments were carried out in Jiangsu Province of East China from 2009 to 2014. Different N application rates and plant densities were used to generate contrasting conditions of N availability or population densities in rice. LAI was determined by LI-3000, and estimated indirectly by LAI-2000 during vegetative growth period. Group and individual plant characters (e.g., tiller number (TN) and plant height (H)) were investigated simultaneously. Two N indicators of plant N accumulation (NA) and N nutrition index (NNI) were measured as well. A calibration equation (LAI=1.7787LAI2000–0.8816, R2=0.870**) was developed for LAI-2000. The linear regression analysis showed a significant relationship between NA and actual LAI (R2=0.863**). For the NNI, the relative LAI (R2=0.808**) was a relatively unbiased variable in the regression than the LAI (R2=0.33**). The results were used to formulate two LAI-based N diagnostic models for irrigated lowland rice (NA=29.778LAI–5.9397; NNI=0.7705RLAI+0.2764). Finally, a simple LAI deterministic model was developed to estimate the actual LAI using the characters of TN and H (LAI=–0.3375(TH×H×0.01)2+3.665(TH×H×0.01)–1.8249, R2=0.875**). With these models, the N status of rice can be diagnosed conveniently in the field.
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Claims 7
Claim · model-written summary
An LAI-2000 calibration equation had R2=0.870.
- Taxon
- rice
Oryza sativat0 - Outcome
- calibration equatione0
- Value
- R2=0.870**e0
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“A calibration equation (LAI=1.7787LAI2000–0.8816, R2=0.870**) was developed for LAI-2000.”
t0“rice”
Claim · model-written summary
Plant nitrogen accumulation was significantly related to actual LAI.
- Taxon
- riceOryza sativat0
- Outcome
- NAe0
- Value
- R2=0.863**e0
- Comparator
- actual LAIe0
Not reportedDirection
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“The linear regression analysis showed a significant relationship between NA and actual LAI (R2=0.863**).”
t0“rice”
Claim · model-written summary
Relative LAI was a less biased predictor of NNI than LAI, with R2 values of 0.808 and 0.33.
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“For the NNI, the relative LAI (R2=0.808**) was a relatively unbiased variable in the regression than the LAI (R2=0.33**).”
t0“rice”
Claim · model-written summary
The authors formulated an LAI-based nitrogen accumulation model.
- Taxon
- riceOryza sativae0
- Outcome
- NAe0
- Value
- NA=29.778LAI–5.9397e0
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“The results were used to formulate two LAI-based N diagnostic models for irrigated lowland rice (NA=29.778LAI–5.9397; NNI=0.7705RLAI+0.2764).”
t0“rice”
Claim · model-written summary
The authors formulated a relative LAI-based NNI model.
- Taxon
- riceOryza sativae0
- Outcome
- NNIe0
- Value
- NNI=0.7705RLAI+0.2764e0
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“The results were used to formulate two LAI-based N diagnostic models for irrigated lowland rice (NA=29.778LAI–5.9397; NNI=0.7705RLAI+0.2764).”
t0“rice”
Claim · model-written summary
A deterministic model estimated actual LAI from tiller number and height with R2=0.875.
- Taxon
- riceOryza sativat0
- Outcome
- actual LAIe0
- Value
- R2=0.875**e0
- Qualifier
- TN and He0
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“Finally, a simple LAI deterministic model was developed to estimate the actual LAI using the characters of TN and H (LAI=–0.3375(TH×H×0.01)2+3.665(TH×H×0.01)–1.8249, R2=0.875**).”
t0“rice”
Claim · model-written summary
These models could conveniently diagnose rice nitrogen status in the field.
- Taxon
- riceOryza sativae0
- Outcome
- N status of rice can be diagnosed conveniently in the fielde0
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“With these models, the N status of rice can be diagnosed conveniently in the field.”
t0“rice”