Simulating groundnut (Arachis hypogaea L.) phenophase and yield in Kerala with DSSAT- CROPGRO model

K.S. Vinu, P. Shajeesh Jan, B. Ajithkumar, Arjun Vysakh


An experiment was conducted to simulate groundnut (Arachis hypogaea L.) phenophase and yield by using the DSSAT- CROPGRO model. The experiment was carried out at Instructional farm Vellanikkara, Kerala Agricultural University with four dates of planting, viz., November 1st, November 15th, December 1st, and December 15th and three irrigation levels (IW/CPE 0.6, 0.8 and 1.0) with the variety TNAU CO-6. The phenological data collected from the field experiment during 2019-2020 was used for calibrating the genetic coefficient for groundnut variety TNAU CO-6. The DSSAT CROPGRO peanut model was used in the simulation studies. The pod yield, shelling percentage and phenological stages as simulated by model were compared with the observed data. The result revealed that, simulated values of pod yield, physiological maturity, days to germination, anthesis and shelling percentage were in good agreement with observed yield.


Crop weather modeling

Full Text:



Boote, K. J., Jones, J. W., and Hoogenboom, G. 1998. Simulation of crop growth: CROPGRO model. In: Peart, R.M.,Curry, R.B. (Eds.), Agricultural Systems Modeling and Simulation (Chapter 18). Marcel Dekker, Inc, New York, pp. 651-692

Giridhar, B. S. 2019. Simulation of summer groundnut (Arachis hypogaea L.) yield using DSSAT model (version 4.6) under varied environmental condition in Parbhani district (Arachis hypogea L.). M. Sc.thesis. Vasantrao Naik Marathwada Krishi Vidyapeeth, Parbhani. pp.39-79.

Jones, J. W. 1993. Decision support systems for agricultural development. In: Penning de Vries, F., Teng, P., Metselaar, K. (Eds.), Systems Approaches for Agricultural Development. Kluwer Academic Press, Boston, pp. 459-471.

Jones, J. W., Tsuji, G. Y., Hoogenboom, G., Hunt, L. A., Thornton, P. K., Wilkens, P. W., Imamura, D. T., Bowen, W. T., and Singh, U. 1998. Decision support system for agro technology transfer; DSSAT v3. In: Tsuji, G.Y., Thornton, P.K. (Eds.), Understanding Options for Agricultural Production. Kluwer Academic Publishers, Dordrecht, the Netherlands, pp. 157-177.

Kambiranda, D. M., Vasanthaiah, H. K. N., Katam, R., Ananga, A., Basha, S. M., and Naik, K. 2011. Impact of drought stress on peanut (Arachis hypogaea L.) productivity and food safety. In: Vasanthaiah, H. (Ed.), Plants and Environment, InTech, pp. 249-272.

Singh, P., Boote, K. J., and Virmani, S. M. 1994. Evaluation of the groundnut model PNUTGRO for crop response to plant population and row spacing. Field Crops Res., 39: 163-170.

Vysakh, A., Ajithkumar, B., and Rao, A. S. 2016. Evaluation of CERES-Rice model for the selected rice varieties of Kerala. J. Agrometeorol., 18(1):120.

Willmot, C. J. 1982. Some comments on the evaluation of model performance. Am. Meteorol. Soc. Bull., 63: 1309-1313.

Woli, P., Joel, O., Paz, Hoogenboom, G., Garcia, A. G., and Fraisse. C. W. 2013. The ENSO effect on peanut yield as influenced by planting date and soil type. Agric. Sys., 121: 1- 8.


  • There are currently no refbacks.

A KAU publication [CODEN: JTAGEI; ISSN 0971-636X; eISSN 0973-5399]