CSM-CROPGRO-Chickpea

Chickpea (Cicer arietinum L.) is an N-fixing annual seed legume that grows during cool winter-spring dry seasons in the Asian continent.  It does not tolerate heat or high humidity as they cause disease.  India produces two-thirds of chickpea production, but chickpea is also widely grown and consumed in Mediterranean and Middle Eastern countries.  It is also known as gram or Begal gram, garbanzo or garbanzo bean, Egyptian pea, chana and chole. Chickpea seeds are high in protein and are used for human consumption as a vegetable, soups/dal, hummus, and paste for sandwiches.  

The original CHIKPGRO model was developed by Singh and Virmani (1996) patterned after the PNUTGRO model the precursor of the CROPGRO-legume model (Boote et. al., 1998).  Singh and Virmani (1996) adapted the model’s crop parameter files based on extensive growth analysis data collected on Annigeri and JG 74 cultivars grown under rainfed and irrigated conditions in 1984, 1985, 1986, 1987, 1992 and 1993 near Hyderabad, India.  Their adaptation required literature information on temperature sensitivity of processes and tissue compositions, and optimization of species and cultivar parameters affecting phenology, onset of reproductive growth, leaf area expansion, dry matter partitioning, tissue N concentrations, and photosynthetic productivity based on time-series observations of crop growth.  The CSM-CROPGRO-Chickpea model has since been updated, re-calibrated, and re-parameterized for elevated temperature stress by Singh et al. (2014) and Boote et al. (2018).   

The model requires inputs of management practices, environmental conditions and cultivar-specific traits (genetic coefficients) to predict daily growth and development (Boote et al., 1998). The species file describes characteristics assumed constant across cultivars such as tissue composition, partitioning, and sensitivity of processes to temperature, light, plant water deficit, and plant N deficiency. The required ecotype and cultivar data include lengths of developmental phases, vegetative traits, leaf traits, reference seed size, and seed composition (Jones et al., 2003). As with the other CSM-CROPGRO models (Boote et. al., 1998; Jones et al., 2003), the CROPGRO-Chickpea model shares the same source code including a hedge-row light interception model (Boote and Pickering, 1994) combined with a leaf-scale photosynthesis model based on the Farquhar approach for simulating response to CO2.  

Differences from peanut and soybean include:  1) chickpea is a cool-season crop with lower cardinal temperatures that allow it to grow over mild winters and being tolerant of moderate frost/freezing conditions, 2) it is a long-day species, and 3) its seed have low oil content.   However, it is not tolerant of high temperature or high humidity conditions.   

The CSM-CROPGRO-Chickpea model was used by Singh et al. (2014) to evaluate the potential benefits of heat and drought tolerance of genotypes for production under climate change conditions.  The model version used for that purpose was re-calibrated against extensive data (Singh et al., 2014) and re-parameterized for elevated temperature stress on reproductive processes (Singh et al., 2014; Boote et al., 2018).  Recently, the model had been used to study the impact of climate change on chickpea production in Ethiopia (Mohammed et al., 2017a, 2017b), planting date evaluation in Iran (Ilkaee et al., 2014), and for yield prediction in Gujarat, India (Patil and Patel, 2017; Patil et al., 2018) and Uttar Pradesh, India (Kumar et al., 2018; Pandey et al., 2019).

References

  • Boote, K. J., J. W. Jones, G. Hoogenboom, and N. B. Pickering.  1998.  The CROPGRO Model for Grain Legumes.  pp. 99-128.  In G. Y. Tsuji, G. Hoogenboom, and P. K. Thornton (eds.) Understanding Options for Agricultural Production.  Kluwer Academic Publishers, Dordrecht. 
  • Boote, K.J., and N.B. Pickering. 1994. Modeling photosynthesis of row crop canopies. HortScience 29: 1423–34. 
  • Boote, K. J., Vara Prasad, L. H. Allen, Jr., P. Singh, and J. W. Jones.  2018.  Modeling sensitivity of grain yield to elevated temperature in the DSSAT crop models for peanut, soybean, dry bean, chickpea, sorghum, and millet.  European Journal of Agronomy 100: 99-109. 
  • Ilkaee, M.N., F. Paknejad, F. Golzardi,  M.R. Tookalloo,  D. Habibi,  G. Tohidloo,  A. Pazoki,  F. Agayari, M. Rezaee, and Z.F. Rika. 2014. Simulation of some of important traits in chickpea cultivars under different sowing date using CROPGRO-Pea model. International Journal of Biosciences 4(12):84-92.
  • Jones, J.W., G. Hoogenboom, C.H. Porter, K.J. Boote, W.D. Batchelor, L.A. Hunt, P.W. Wilkens, U. Singh, A.J. Gijsman, and J.T. Ritchie. 2003. The DSSAT Cropping System Model. European Journal of Agronomy 18:235–65.
  • Kumar, N., A.K.  Singh, S.R. Mishra, A.N. Mishra, R. Chaudhari, and P.K. Singh. 2018. Performance & growth of chickpea (Cicer arietinum L.) cultivars on Dssat simulation model. Journal of Pharmacognosy and Phytochemistry 7(2):3397-3400.
  • Mohammed, A., T. Tana, P. Singh, D. Korecha, and A. Molla. 2017a. Management options for rainfed chickpea (Cicer arietinum L.) in northeast Ethiopia under climate change condition. Climate Risk Management 16:222-233. https://doi.org/10.1016/j.crm.2016.12.003.
  • Mohammed, A., T. Tana, P. Singh, A. Molla, and A. Seid. 2017b. Identifying best crop management practices for chickpea (Cicer arietinum L.) in Northeastern Ethiopia under climate change condition. Agricultural Water Management 194:68-77. htps://doi.org/10.1016/j.agwat.2017.08.022.
  • Pandey, V., A.K. Singh, S.R. Mishra, G. Singh, K. Deo, and A. Mishra. 2019. Evaluation of crop simulation modeling in chickpea crop using DSSAT model under agroclimatic conditions of eastern U.P. The Pharma Innovation Journal 8(4):1139-1142.
  • Patil, D.D., and H.R. Patel. 2017.  Calibration and validation of CROPGRO (DSSAT  4.6) model for chickpea  under Middle Gujarat agroclimatic region. International Journal of Agriculture Sciences Volume 9(27):4342-4344.
  • Patil, D.D., B.I. Karande., S.B. Satpute, and H.R. Patel. 2018. Sensitivity analysis to study the impact of climate change on chickpea using DSSAT (4.6) CROPGRO model over middle Gujarat agroclimaticregion. Contemporary Research in India IV:223-227.
  • Singh, P., S. Nedumaran, K. J. Boote, P. M. Gaur, K. Srinivas, and M. C. S. Bantilan.  2014.  Climate change impacts and potential benefits of drought and heat tolerance in chickpea in South Asia and East Africa.  European Journal of Agronomy 52:123-137.
  • Singh, P., and S.M. Virmani. 1996. Modeling growth and yield of chickpea (Cicer arietinum L.). Field Crops Research 46:41–59.