Improved climate risk simulations for rice in arid environments

PloS One
Pepijn A J van OortKazuki Saito

Abstract

We integrated recent research on cardinal temperatures for phenology and early leaf growth, spikelet formation, early morning flowering, transpirational cooling, and heat- and cold-induced sterility into an existing to crop growth model ORYZA2000. We compared for an arid environment observed potential yields with yields simulated with default ORYZA2000, with modified subversions of ORYZA2000 and with ORYZA_S, a model developed for the region of interest in the 1990s. Rice variety 'IR64' was sown monthly 15-times in a row in two locations in Senegal. The Senegal River Valley is located in the Sahel, near the Sahara desert with extreme temperatures during day and night. The existing subroutines underestimated cold stress and overestimated heat stress. Forcing the model to use observed spikelet number and phenology and replacing the existing heat and cold subroutines improved accuracy of yield simulation from EF = -0.32 to EF =0.70 (EF is modelling efficiency). The main causes of improved accuracy were that the new model subversions take into account transpirational cooling (which is high in arid environments) and early morning flowering for heat sterility, and minimum rather than average temperature for cold sterility. Simulation...Continue Reading

References

Jan 10, 2002·Journal of Industrial Microbiology & Biotechnology·K FujitaK Isono
Apr 14, 2007·Journal of Experimental Botany·S V K JagadishT R Wheeler
Sep 17, 2013·Global Change Biology·Berta SánchezJohn R Porter
Apr 1, 2011·Functional Plant Biology : FPB·Krishna S V JagadishPeter Q Craufurd

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Citations

Dec 14, 2016·Proceedings of the National Academy of Sciences of the United States of America·Martin K van IttersumKenneth G Cassman
Jan 26, 2018·Global Change Biology·Julian Ramirez-VillegasAndrew J Challinor
Dec 13, 2017·Global Change Biology·Pepijn A J van Oort, Sander J Zwart
Jul 29, 2020·FEMS Microbiology Ecology·Matteo ChialvaErica Lumini
Aug 16, 2019·International Journal of Biometeorology·Lei ZhangZhiguo Huo

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Software Mentioned

SPFERT
WOFOST
ORYZA1
ORYZA
SIMDUR
RIDEV
ORYZA2000
SFHEAT
SUCROS
SUBLAI3

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