Skip to main content
Log in

Validation of a Crop Yield and CO2 Fixation Model over Southeast Asia by Carbon Partitioning in Grain Plants

  • Research Article
  • Published:
Journal of the Indian Society of Remote Sensing Aims and scope Submit manuscript

Abstract

A photosynthetic-sterility model for grain production monitoring has been developed and validated under the background of climate change and Asian economic growth in developing countries. This paper presents an application of the model to evaluate carbon-fixation rates in yields of paddy rice, winter wheat, and maize in Asia. The validation of the model is based on carbon partitioning in grain plants. The carbon hydrate in grains has the same chemical formula as that of cellulose in grain vegetation. The partitioning of carbon in plants can validate fixation amounts of computed carbon using a satellite-based photosynthesis model. The model estimates the photosynthesis fixation of rice reasonably in Japan and China. Results were validated through examination of carbon in grains, but the model tends to underestimate results for winter wheat and maize. This study also provides daily distributions of the PSN, which is the CO2 fixation in Asian areas combined with a land-cover distribution classified from MODIS data, NDVI from SPOT VEGETATION, and meteorological re-analysis data by European Centre for Medium-Range Forecasts (ECMWF). The mean CO2 and carbon fixation rates in paddy areas were 25.92 (t CO2/ha) and 5.28 (t C/ha) in Japan, respectively. Comparisons between the model’s values and MODIS seasonal PSNs show similar trends. The writers are preparing to compare computed photosynthesis rates with observed AsiaFlux data for the validation of this model at field sites of paddy, grassland and forests in Japan and Asian countries.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

References

  • Gale, F. (2002). China’s statistics: Are they reliable? China’s food and agriculture: Issues for the 21st Century, Economic Research Service/USDA, AIB-775, 4p. http://www.ers.usda.gov/Data/China/ Accessed on 14 October 2010.

  • Kaneko, D., Ohnishi, M., & Ishiyama, T. (2003). Proposal of early monitoring method for crop production in China and India In the recent era of water resources restriction. Environmental Systems Research, Japan Society of Civil Engineers, 31, 235–244 (In Japanese with English abstract).

    Google Scholar 

  • Kaneko, D., Ohnishi, M., Ishiyama, T. and Tateishi, R. (2004a). Proposal of a photosynthesis type of crop yield index for monitoring crop production in China and India in the era of water resource restriction, Proc. 4th International Crop Science Congress, held at Brisbane, Australia, from Sept. 26-Oct. 1, 2004. 4p. http://www.cropscience.org.au/icsc2004/poster/2/8/252_daijir.htm#TopOfPage.

  • Kaneko, D., Ohnishi, M., Ishiyama, T., and Tateishi, R. (2004b). Modeling of a photosynthetic crop production index for early warning using NDVI and Meteorological data, Proc. of SPIE, Remote Sensing for Agriculture, Ecosystems, and Hydrology, 11th SPIE International Symposium on Remote Sensing, The international society for Optical Engineering, held at Gran Canaria, Spain, from Sept. 14–16, SPIE Vol. 5568, 2004, pp. 1–10.

  • Kaneko, D., Ohnishi, M., and Ishiyama, T. (2005). Photosynthetic rice production index for early warning using Remote Sensing and meteorological data, Proc. of SPIE Remote Sensing for Agriculture, Ecosystems, and Hydrology, 12th SPIE EUROPE International Symposium on Remote Sensing, The international society for Optical Engineering, held at Bruges, Belgium, from Sep. 20–22, SPIE Vol. 5976, 2005, pp.59761A-1-9.

  • Kaneko, D. (2006a). In J. A. Sobrino (Ed.), Developing a photosynthetic prediction model for rice yield using remotely sensed and meteorological data, Second recent advances in quantitative remote sensing (pp. 549–554). Valencia: University of Valencia.

    Google Scholar 

  • Kaneko, D. (2006b). Estimation of rice situation index in Japan using remotely sensed and meteorological data. Journal of the Remote Sensing Society of Japan, 26(3), 202–212. In Japanese with English abstract.

    Google Scholar 

  • Kaneko, D. (2006c). Evaluation of CO2 fixation in Japanese paddy fields by a photosynthesis model using satellite data. Annual Journal Hydraulic Engineering, Japan Society of Civil Engineers, 50, 475–480 (In Japanese with English abstract).

    Google Scholar 

  • Kaneko, D. (2007). Crop yield monitoring based on a photosynthetic sterility model using NDVI and daily meteorological data, Proc. 14th SPIE EUROPE International Symposium on Remote Sensing, held at Florence, Italy, from Sept. 18–20, SPIE Vol. 6742, 2007, pp.674201 F-1-12.

  • Kaneko, D., Kumakura, T., & Yang, P. (2009). Data assimilation for crop yield and CO2 fixation monitoring in Asia by a photosynthetic-sterility model using satellites and meteorological data. International Journal Global Warming, 1(3), 179–200.

    Article  Google Scholar 

  • Kaneko, D., Yang, P., Yeh, P. J.-F., & Kumakura, T. (2010). Developing a photosynthetic sterility model to estimate CO2 fixation through the crop yield in Asia with the aid of MODIS data. Ecological Informatics, 5, 390–399.

    Article  Google Scholar 

  • NASA Goddard Space Flight Center (GSFC), MODIS land-cover (2010). http://www.ers.usda.gov/publications/aib775/aib775r.pdf. Accessed on 14 October 2010.

  • Prioul, J. L, and Chartier, P. (1977). Partitioning of transfer and carboxylation components of intracellular resistance to photosynthetic CO2 fixation: a critical analysis of the Methods used, Annals of Botany, 789–800.

  • Sasaki, H., Hara, T., Ito, S., Miura, S., Hoque, M. M., Lieffering, M., et al. (2005). Seasonal changes in canopy photosynthesis and respiration, and partitioning of photosynthate, in rice (Oryza sativa L.I) grown under free-air CO2 enrichment. Plant & Cell Physiology, 46(10), 1704–1712.

    Article  Google Scholar 

  • Sinclair, T. R. (1998). Historical changes in harvest index and crop nitrogen accumulation. Crop Science, 38, 638–643.

    Article  Google Scholar 

  • Vong, N. Q., & Murata, Y. (1997). Studies on the physiological characteristics of C3 and C4 crop species. I. The effects of air temperature on the apparent photosynthesis, dark respiration and nutrient absorption of some crops. Japanese Journal Crop Science, 46, 45–52.

    Article  Google Scholar 

  • Xiao, X., Boles, S., Liu, J., Zhuang, D., Frolking, S., Li, C., et al. (2005). Mapping paddy rice agriculture in southern China using multi-temporal MODIS images. Remote Sensing of Environment, 95, 480–492.

    Article  Google Scholar 

  • Xiao, X., Boles, S., Frolking, S., Li, C., Babu, Y., Salas, W., et al. (2006). Mapping paddy rice agriculture in Southeast Asia using multi-temporal MODIS images. Remote Sensing of Environment, 100, 95–113.

    Article  Google Scholar 

Download references

Acknowledgement

This study is funded by Grants-in-Aid (No. 21580319) for Scientific Research. We wish to express thanks to the Japan Society for the Promotion of Science, which belongs to Ministry of Education, Culture, Sports, Science and Technology.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Daijiro Kaneko.

About this article

Cite this article

Kaneko, D., Yang, P. & Kumakura, T. Validation of a Crop Yield and CO2 Fixation Model over Southeast Asia by Carbon Partitioning in Grain Plants. J Indian Soc Remote Sens 39, 297–306 (2011). https://doi.org/10.1007/s12524-011-0096-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12524-011-0096-0

Keywords

Navigation