Leaf area index based nitrogen diagnosis in irrigated lowland rice
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 P...
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Format: | Article |
Language: | English |
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Elsevier
2018-01-01
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Series: | Journal of Integrative Agriculture |
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Online Access: | http://www.sciencedirect.com/science/article/pii/S2095311917617143 |
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doaj-d82cb5fd4bc143138a095aa89072b46e |
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record_format |
Article |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Xiao-jun LIU Qiang CAO Zhao-feng YUAN Xia LIU Xiao-ling WANG Yong-chao TIAN Wei-xing CAO Yan ZHU |
spellingShingle |
Xiao-jun LIU Qiang CAO Zhao-feng YUAN Xia LIU Xiao-ling WANG Yong-chao TIAN Wei-xing CAO Yan ZHU Leaf area index based nitrogen diagnosis in irrigated lowland rice Journal of Integrative Agriculture leaf area index rice LAI-2000 nitrogen diagnosis plant characters |
author_facet |
Xiao-jun LIU Qiang CAO Zhao-feng YUAN Xia LIU Xiao-ling WANG Yong-chao TIAN Wei-xing CAO Yan ZHU |
author_sort |
Xiao-jun LIU |
title |
Leaf area index based nitrogen diagnosis in irrigated lowland rice |
title_short |
Leaf area index based nitrogen diagnosis in irrigated lowland rice |
title_full |
Leaf area index based nitrogen diagnosis in irrigated lowland rice |
title_fullStr |
Leaf area index based nitrogen diagnosis in irrigated lowland rice |
title_full_unstemmed |
Leaf area index based nitrogen diagnosis in irrigated lowland rice |
title_sort |
leaf area index based nitrogen diagnosis in irrigated lowland rice |
publisher |
Elsevier |
series |
Journal of Integrative Agriculture |
issn |
2095-3119 |
publishDate |
2018-01-01 |
description |
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. |
topic |
leaf area index rice LAI-2000 nitrogen diagnosis plant characters |
url |
http://www.sciencedirect.com/science/article/pii/S2095311917617143 |
work_keys_str_mv |
AT xiaojunliu leafareaindexbasednitrogendiagnosisinirrigatedlowlandrice AT qiangcao leafareaindexbasednitrogendiagnosisinirrigatedlowlandrice AT zhaofengyuan leafareaindexbasednitrogendiagnosisinirrigatedlowlandrice AT xialiu leafareaindexbasednitrogendiagnosisinirrigatedlowlandrice AT xiaolingwang leafareaindexbasednitrogendiagnosisinirrigatedlowlandrice AT yongchaotian leafareaindexbasednitrogendiagnosisinirrigatedlowlandrice AT weixingcao leafareaindexbasednitrogendiagnosisinirrigatedlowlandrice AT yanzhu leafareaindexbasednitrogendiagnosisinirrigatedlowlandrice |
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1721390603654135808 |
spelling |
doaj-d82cb5fd4bc143138a095aa89072b46e2021-06-08T04:38:59ZengElsevierJournal of Integrative Agriculture2095-31192018-01-01171111121Leaf area index based nitrogen diagnosis in irrigated lowland riceXiao-jun LIU0Qiang CAO1Zhao-feng YUAN2Xia LIU3Xiao-ling WANG4Yong-chao TIAN5Wei-xing CAO6Yan ZHU7National Engineering and Technology Center for Information Agriculture/Key Laboratory for Crop System Analysis and Decision Making, Ministry of Agriculture/Jiangsu Key Laboratory for Information Agriculture/Jiangsu Collaborative Innovation Center for Modern Crop Production/Nanjing Agricultural University, Nanjing 210095, P.R.ChinaNational Engineering and Technology Center for Information Agriculture/Key Laboratory for Crop System Analysis and Decision Making, Ministry of Agriculture/Jiangsu Key Laboratory for Information Agriculture/Jiangsu Collaborative Innovation Center for Modern Crop Production/Nanjing Agricultural University, Nanjing 210095, P.R.ChinaNational Engineering and Technology Center for Information Agriculture/Key Laboratory for Crop System Analysis and Decision Making, Ministry of Agriculture/Jiangsu Key Laboratory for Information Agriculture/Jiangsu Collaborative Innovation Center for Modern Crop Production/Nanjing Agricultural University, Nanjing 210095, P.R.ChinaNational Engineering and Technology Center for Information Agriculture/Key Laboratory for Crop System Analysis and Decision Making, Ministry of Agriculture/Jiangsu Key Laboratory for Information Agriculture/Jiangsu Collaborative Innovation Center for Modern Crop Production/Nanjing Agricultural University, Nanjing 210095, P.R.ChinaNational Engineering and Technology Center for Information Agriculture/Key Laboratory for Crop System Analysis and Decision Making, Ministry of Agriculture/Jiangsu Key Laboratory for Information Agriculture/Jiangsu Collaborative Innovation Center for Modern Crop Production/Nanjing Agricultural University, Nanjing 210095, P.R.ChinaNational Engineering and Technology Center for Information Agriculture/Key Laboratory for Crop System Analysis and Decision Making, Ministry of Agriculture/Jiangsu Key Laboratory for Information Agriculture/Jiangsu Collaborative Innovation Center for Modern Crop Production/Nanjing Agricultural University, Nanjing 210095, P.R.ChinaNational Engineering and Technology Center for Information Agriculture/Key Laboratory for Crop System Analysis and Decision Making, Ministry of Agriculture/Jiangsu Key Laboratory for Information Agriculture/Jiangsu Collaborative Innovation Center for Modern Crop Production/Nanjing Agricultural University, Nanjing 210095, P.R.ChinaCorrespondence ZHU Yan, Tel: +86-25-84396598, Fax: +86-25-84396672; National Engineering and Technology Center for Information Agriculture/Key Laboratory for Crop System Analysis and Decision Making, Ministry of Agriculture/Jiangsu Key Laboratory for Information Agriculture/Jiangsu Collaborative Innovation Center for Modern Crop Production/Nanjing Agricultural University, Nanjing 210095, P.R.ChinaLeaf 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.http://www.sciencedirect.com/science/article/pii/S2095311917617143leaf area indexriceLAI-2000nitrogen diagnosisplant characters |