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Higher Sensitivity of NIR v,Rad in Detecting Net Primary Productivity of C4 Than that of C3: Evidence from Ground Measurements of Wheat and Maize.

Authors :
Chen, Siru
Zhao, Wenhui
Zhang, Renxiang
Sun, Xun
Zhou, Yangzhen
Liu, Leizhen
Source :
Remote Sensing. Feb2023, Vol. 15 Issue 4, p1133. 20p.
Publication Year :
2023

Abstract

Accurate quantification of net primary productivity (NPP) is key to estimating vegetation productivity and studying the global carbon cycle. However, C3 and C4 plants vary in their living environments and potential productivity due to their different photosynthetic pathways. This study thus explored the potential of the near-infrared radiance of vegetation (NIRv,Rad) to track hourly and daily changes in C3 and C4 plants and investigate whether their photosynthetic pathways affect the relationship between NPP and NIRv,Rad. Statistics including long-term spectral data, the growth environment, and physiological indicators were collected using an automatic spectral monitoring system. The vegetation index NIRv,Rad was extracted from the collected spectral data and NPP was calculated using the collected net photosynthetic rate and leaf area index. The results showed that NIRv,Rad can effectively respond to NPP changes in C3 and C4 plants on hourly and daily scales. The NPP–NIRv,Rad relationship on the hourly scale was superior, with R2 values for winter wheat and summer maize of 0.81 and 0.70, respectively. Furthermore, when the accumulation of NPP was equal, the NIRv,Rad of summer maize showed larger changes, indicating that it was more sensitive to NPP change for this species than for winter wheat. Overall, the study demonstrated that NIRv,Rad can serve as an effective proxy indicator of NPP. In addition, this study provides a theoretical basis and scientific guidance for the construction of new simple models and realizing efficient agriculture, as well as a new method for rapid and accurate quantification of the NPP of C3 and C4 plants at geospatial scales in future research. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20724292
Volume :
15
Issue :
4
Database :
Academic Search Index
Journal :
Remote Sensing
Publication Type :
Academic Journal
Accession number :
162160955
Full Text :
https://doi.org/10.3390/rs15041133