Leaf area index based nitrogen diagnosis in irrigated lowland rice

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.