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Current IssueEditorial BoardOnline First Articles
Indian Journal of
Agricultural Research
Print ISSN: 0367-8245
Online ISSN: 0976-058X
NASS Rating
5.60
SJR
0.217
CiteScore
0.595

Chief Editor:
V. Geethalakshmi
Tamil Nadu Agricultural University Coimbatore, INDIA
Frequency:Monthly
Indexing:
BIOSIS Preview, ISI Citation Index, Biological Abstracts, Elsevier (Scopus and Embase), AGRICOLA, Go...

Research Article

Indian Journal of Agricultural Research, volume 52 issue 2 (april 2018) : 140-145

Application of CSM–CERES–Rice in scheduling irrigation and simulating effect of drought stress on upland rice yield 

T. Hussain, J. Anothai, C. Nualsri, W. Soonsuwon
1Department of Plant Science, Faculty of Natural Resources, Prince of Songkla University, Hat Yai, 90112, Thailand
Cite article:- Hussain T., Anothai J., Nualsri C., Soonsuwon W. (2018). Application of CSM–CERES–Rice in scheduling irrigation and simulating effect of drought stress on upland rice yield. Indian Journal of Agricultural Research. 52(2): 140-145. doi: 10.18805/IJARe.A-321.

ABSTRACT

Crop models can provide rapid and cost effective means to deal with rice crop management. The objectives of this study included, exploring the ability of CSM–CERES–Rice in scheduling irrigation and to simulate the effect of drought stress on upland rice yield. Irrigation treatments 100, 70 and 50 % of field capacity (FC) were applied from 80 days after planting (DAP) at flowering stage until maturity and CSM–CERES–Rice was used to predict irrigation amount for each water regime for treatment duration. Results showed that, at 70 and 50 % FC, performance of an upland rice genotype, Dawk Pa-yawm was decreased significantly as compared to 100 % FC. Normalized root mean square error (RMSEn) values less than 10 % for each treatment indicated a strong agreement between simulated and observed grain yield (GY) and biomass. d-index approaching to unity and RMSEn less than 10 % indicated a good agreement between simulated and observed soil moisture contents (SMC) for all irrigation treatments. Overall, it was concluded that drought stress had negative correlation with GY and CSM–CERES–Rice was able to predict irrigation amount for all treatments assuring that, model has potential for its use as a tool to schedule irrigation for experiments under water limited conditions.

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