Indian Journal of Agricultural Research

  • Chief EditorV. Geethalakshmi

  • Print ISSN 0367-8245

  • Online ISSN 0976-058X

  • NAAS Rating 5.60

  • SJR 0.293

Frequency :
Bi-monthly (February, April, June, August, October and December)
Indexing Services :
BIOSIS Preview, ISI Citation Index, Biological Abstracts, Elsevier (Scopus and Embase), AGRICOLA, Google Scholar, CrossRef, CAB Abstracting Journals, Chemical Abstracts, Indian Science Abstracts, EBSCO Indexing Services, Index Copernicus
Indian Journal of Agricultural Research, volume 47 issue 1 (february 2013) : 78-82

TEMPERATURE EFFECT ON GROWTH PARAMETERS OF WHEAT (CV. PBW-343) USING CERES-WHEAT MODEL FOR DIFFERENT SOWING DATES IN FOOT HILLS OF WESTERN HIMALAYAS

R.K. Pal*, S.N. Murty
1Department of Agrometeorology, College of Agriculture G.B. Pant University of Agriculture and Technology-263 145, India
  • Submitted|

  • First Online |

  • doi

Cite article:- Pal* R.K., Murty S.N. (2024). TEMPERATURE EFFECT ON GROWTH PARAMETERS OF WHEAT (CV. PBW-343) USING CERES-WHEAT MODEL FOR DIFFERENT SOWING DATES IN FOOT HILLS OF WESTERN HIMALAYAS. Indian Journal of Agricultural Research. 47(1): 78-82. doi: .
To quantify the effect of temperature on productivity of wheat (cv. PBW-343) using CERES-wheat model in foot hills of Western Himalayas, experiments were conducted at the Norman E. Borlaug Crop Research Centre of GBPUAT, Pantnagar during 2007-08 and 2008-09. The experiments were laid out in split plot design (SPD) with three dates of sowing i.e. November 20, December 15 and January 09. The CERES-wheat model was calibrated based on actual data of field experiments in foot hills of Western Himalayas. All crop characters, as simulated by the CERES-wheat model, in terms of anthesis, physiological maturity and grain yield were found to have increased due to decreased units of minimum and maximum temperatures (Tmin and Tmax) and vice-versa for all sowing dates. More decreased in simulated grain yields were accounted due to increased units of Tmin (13.3, 23.7 and 34.5% by 1, 2 and 3°C, respectively) and Tmax (10.4, 20.9 and 31.5% by 1, 2 and 3°C, respectively) on 20th November sowing. While, the simulated grain yield increased significantly more on 20th November sowing due to decreased Tmin (6.0, 11.6 and 19.2% by 1, 2 and 3°C, respectively) and Tmax (9.2, 14.6 and 21.9% by 1, 2 and 3°C, respectively).
  1. Aggarwal, P.K. and Kalra, N. (1994). Analyzing the limitations set by climatic factors, genotype and water and nitrogen availability on productivity of wheat II. Climatically potential yields and management strategies. Field Crop Res., 38: 93-103. 
  2. Aggarwal, P.K. and Sinha, S.K. (1993). Effect of probable increase in carbon dioxide and temperature on wheat yields in India. J. Agril. Meteo., 48: 811-814.
  3. Asseng, S.; Foster, I. and Turner, N.C. (2011). The impact of temperature variability on wheat yields. Global Change Biol., 17: 997–1012. 
  4. David, B.L.; Sibley, A. and Ortiz-Monasterio, J.I. (2012). Extreme heat effects on wheat senescence in India. Nature Climate Change. 
  5. Directorate of Economics and Statistics (DES), Department of Agriculture and Cooperation (2010). eands.dacnet.nic.in/ At_A_Glance-2011/4.7(b).xls.
  6. Hoogenboom, G.; Tsuji, G.Y.; Jones, J.W.; Singh, U.; Godwin, D.C.; Pickering, N.B. and Curry, R.B. (1995). Decision support system to study climate change impacts on crop production. In C. Rosenzweig et al. (ed.) Climate change and agriculture: Analysis of potential international impacts. ASA Spec. Publ. No. 59. Am. Soc. of Agron., Madison, WI. p.51-75.
  7. Jones, J. W.; Hoogenboom, G.; Wilkens, P.W.; Porter, C.H. and Tsuji, G.Y. (2003). Decision Support System for Agrotechnology Transfer Version 4.0. Volume 4. DSSAT v4: Crop Model Documentation. University of Hawaii, Honolulu, HI
  8. Matthews, R.; Stephens, W.; Hess, T.; Mason, T. and Graves, A.R. (2002). Application of crop-soil simulation models in tropical agricultural systems. Adv. Agron., 17:31-123. 
  9. Modarresi, M.; Mohammadi, V.; Zali, A. and Mardi, M. (2010). Response of Wheat Yield and Yield Related Traits to High Temperature. Cereal Res. Communications 38(1): 23–31. 
  10. Muchow, R.C.; Evensen, C.I.; Osgood, R.V. and Robertson, M.J. (1997). Yield accumulation in irrigated sugarcane. II. Utilization of intercepted radiation. Agron. J., 89: 652-656.
  11. Nain, A.S.; Dadhwal V.K. and Singh T.P. (2002). Real time wheat yield assessment using technology trend and crop simulation model with minimal data set. Current Sci., 82(10): 1255-1258. 
  12. Nain, A.S.; V.K. Dadhwal, and T.P. Singh. (2004). Use of CERES-wheat model for wheat yield forecast in central Indo- Gangetic plains of India. J. Agric. Sci., 142: 59-70.
  13. Patel, H.R. and Shekh, A.M. (2005). Sensitivity analysis of CERES-wheat model to various weather and non-weather parameters for wheat (cv.GW-496). J. Agric. Sci., 1(2):21-30.
  14. Pathak H.; Ladha, J.K.; Aggarwal, P.K.; Peng, S.; Das, S.; Singh, Y.; Singh, B.; Kamara, S.K; Mishra, B.; Sastri, A.S.R.A.S.; Aggarwal, H.P.; Das, D.K. and Gupta, R.K. (2003). Trends of climatic potential and on-farm yields of rice and wheat in the Indo-Gangetic Plains. Field Crops Res., 80: 223-234. 
  15. Sharma, K.; Bishnoi, O.P.; Niwas, R. and Khichar, M.L. (2010). Impact assessment of climatic variability on wheat and pearl millet productivity using CERES models in arid zone of Haryana. J. Agrometeorol., 12(1): 123-127.
  16. Tripathi, P.; Singh, A.K. and Chaturvedi, A. (2006). Impact, adaptation and vulnerability of Indian agriculture to climate change. N.D.U.A.&T., Kumarganj, Faizabad (Annual project report). 
  17. United State Department of Agriculture (USDA). (2011). Production, Supply, & Distribution, electronic database, at www.fas.usda.gov/psdonline, updated 9 December 2011.

Editorial Board

View all (0)