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Potential benefits of drought and heat tolerance in groundnut for adaptation to climate change in India and West Africa

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Abstract

Climate change is projected to intensify drought and heat stress in groundnut (Arachis hypogaea L.) crop in rainfed regions. This will require developing high yielding groundnut cultivars that are both drought and heat tolerant. The crop growth simulation model for groundnut (CROPGRO-Groundnut model) was used to quantify the potential benefits of incorporating drought and heat tolerance and yield-enhancing traits into the commonly grown cultivar types at two sites each in India (Anantapur and Junagadh) and West Africa (Samanko, Mali and Sadore, Niger). Increasing crop maturity by 10 % increased yields up to 14 % at Anantapur, 19 % at Samanko and sustained the yields at Sadore. However at Junagadh, the current maturity of the cultivar holds well under future climate. Increasing yield potential of the crop by increasing leaf photosynthesis rate, partitioning to pods and seed-filling duration each by 10 % increased pod yield by 9 to 14 % over the baseline yields across the four sites. Under current climates of Anantapur, Junagadh and Sadore, the yield gains were larger by incorporating drought tolerance than heat tolerance. Under climate change the yield gains from incorporating both drought and heat tolerance increased to 13 % at Anantapur, 12 % at Junagadh and 31 % at Sadore. At the Samanko site, the yield gains from drought or heat tolerance were negligible. It is concluded that different combination of traits will be needed to increase and sustain the productivity of groundnut under climate change at the target sites and the CROPGRO-Groundnut model can be used for evaluating such traits.

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References

  • Aggarwal PK (2008) Global climate change and Indian agriculture: impacts, adaptation and mitigation. Indian J Agric Sci 78:911–919

    Google Scholar 

  • Alagarswamy G, Boote KJ, Allen LH Jr, Jones JW (2006) Evaluating the CROPGRO-Soybean model ability to simulate photosynthesis response to carbon dioxide levels. Agron J 98:34–42

    Article  Google Scholar 

  • Anothai J, Patanothai A, Pannangpetch K, Jogloy S, Boote KJ, Hoogenboom G (2009) Multi-environment evaluation of peanut lines by model simulation with the cultivar coefficients derived from a reduced set of observed field data. Field Crop Res 110:111–121

    Article  Google Scholar 

  • Batjes NH (2012) ISRIC-WISE derived soil properties on a 5 by 5 arc-minutes global grid (ver 1.2), report 2012/01 with data set. ISRIC—World Soil Information, Wageningen, p 57

    Google Scholar 

  • Birthal PS, Parthasarathy Rao P, Nigam SN, Bantilan MCS, Bhagavatula S (2010) Groundnut and soybean economies in Asia: facts, trends and outlook. International Crops Research Institute for the Semi-Arid Tropics, Patancheru 502 324, Andhra Pradesh, India. (ISBN: 978-92-9066-531-1), p 92

  • Boote KJ, Jones JW (1986) Applications of, and limitations to, crop growth simulation models to fit crops and cropping systems to semi-arid environments. In: Bidinger FR, Johansen C (eds) Drought research priorities for the dryland tropics. International Crops Research Institute for the Semi-Arid Tropics, Patancheru, pp 63–75

    Google Scholar 

  • Boote KJ, Tollenaar M (1994) Modeling genetic yield potential. In: Boote KJ, Bennett JM, Sinclair TR, Paulsen GM (eds) Physiology and determination of crop yield. ASA-CSSA-SSSA, Madison, pp 533–565

    Google Scholar 

  • Boote KJ, Jones JW, Hoogenboom G, Pickering NB (1998) Simulation of crop growth: CROPGRO model. In: Tsuji GY, Hoogenboom G, Thornton P (eds) Understanding the option for agricultural production. Kluwer Academic Publishers, London, pp 99–128

    Chapter  Google Scholar 

  • Boote KJ, Kropff MJ, Bindraban PS (2001) Physiology and modeling of traits in crop plants: implications for genetic improvement. Agric Syst 70:395–420

    Article  Google Scholar 

  • Boote KJ, Jones JW, Batchelor WD, Nafziger ED, Myers O (2003) Genetic coefficients in the CROPGRO-soybean model: links to field performance and genomics. Agron J 95:32–51

    Article  Google Scholar 

  • Boote KJ, Allen LH Jr, Vara Prasad PV, Jones JW (2010) Testing effects of climate change in crop models. In: Hillel D, Rosenzweig C (eds) Handbook of climate change and agroecosystems. Imperial College Press, London, pp 109–129

    Chapter  Google Scholar 

  • Boote KJ, Ibrahim AMH, Lafitte R, McCulley R, Messina C, Murray SC, Specht JE, Taylor S, Westgate ME, Glasener K, Bijl CG, Giese JH (2011) Position statement on crop adaptation to climate change. Crop Sci 51:2337–2343

    Article  Google Scholar 

  • Cooper P, Rao KPC, Singh P, Dimes J, Traore PS, Rao KP, Dixit P, Twomlow S (2009) Farming with current and future climate risk: advancing a ‘hypothesis of hope’ for rain-fed agriculture in the semi-arid tropics. J SAT Agric Res 7:1–19

    Google Scholar 

  • Craufurd PQ, Prasad PVV, Kakani VG, Wheeler TR, Nigam SN (2003) Heat tolerance in groundnut. Field Crop Res 80:63–77

    Article  Google Scholar 

  • Easterling WE (1996) Adapting North American agriculture to climate change in review. Agric For Meteorol 80:1–53

    Article  Google Scholar 

  • FAO (2012) URL:http://faostat.fao.org/site/567/default.aspx#ancor. Accessed on: 15 April 2012

  • Farquhar GD, von Caemmerer S (1982) Modeling of photosynthetic response to environment. In: Lange OL, Nobel PS, Osmond CB, Zeigler H (eds) Encyclopedia of plant physiology, new series, vol 12B. Physiological plant ecology II, vol 12B. Springer, Berlin, pp 549–587

    Chapter  Google Scholar 

  • Fischer G, Shah M, Tubiello FN, van Velhuizen H (2005) Socio-economic and climate change impacts on agriculture: an integrated assessment, 1990–2080. Phil Trans Royal Soc B 360:2067–2073

    Article  Google Scholar 

  • Gilbert RA, Boote KJ, Bennett JM (2002) On-farm testing of the PNUTGRO crop growth model in Florida. Peanut Sci 29:58–65

    Article  Google Scholar 

  • Hammer GL, Butler DG, Muchow RC, Meinke H (1996) Integrating physiological understanding and plant breeding via crop modeling and optimization. In: Cooper M, Hammer GL (eds) Plant adaptation and crop improvement. CAB International, Wallingford, pp 419–441

    Google Scholar 

  • Hammer GL, Kropff MJ, Sinclair TR, Porter JR (2002) Future contributions of crop modeling: from heuristics and supporting decision making to understanding genetic regulation and aiding crop improvement. Eur J Agron 18:15–31

    Article  Google Scholar 

  • Hammer GL, Sinclair TR, Chapman S et al (2004) On systems thinking, systems biology and the in silico plant. Plant Physiol 134:909–911

    Article  Google Scholar 

  • Hammer GL, Chapman S, van Oosterom E, Podlich D (2005) Trait physiology and crop modeling as a framework to link phenotypic complexity to underlying genetic systems. Aust J Agric Res 56:947–960

    Article  Google Scholar 

  • Hoogenboom G, Jones JW, Wilkens PW, Porter CH, Boote KJ, Hunt LA, Singh U, Lizaso JL, White JW, Uryasev O, Royce FS, Ogoshi R, Gijsman AJ, Tsuji GY (2010) Decision support system for agrotechnology transfer (DSSAT) version 4.5 [CD–ROM]. University of Hawaii, Honolulu

    Google Scholar 

  • Howden SM, Soussana JF, Tubiello FN, Chhetri N, Dunlop M, Meinke H (2007) Adapting agriculture to climate change. PNAS 104:19691–19696

    Article  Google Scholar 

  • IPCC (2001) Climate change 2001: the scientific basis. Contribution of working group I to the third assessment report of the intergovernmental panel on climate. Cambridge University Press, Cambridge, p 881

    Google Scholar 

  • IPCC (2007) Climate change 2007: the physical science basis. Contribution of working group I to the fourth assessment report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge, p 996

    Google Scholar 

  • Jones JW, Hoogenboom G, Porter CH, Boote KJ, Batchelor WD, Hunt LA, Wilkens PW, Singh U, Gijsman AJ, Ritchie JT (2003) DSSAT cropping system model. Eur J Agron 18:235–265

    Article  Google Scholar 

  • Jongrungklang N, Toomsan B, Vorasoot N, Jogloy S, Boote KJ, Hoogenboom G, Patanothai A (2011) Rooting traits of peanut genotypes with different yield responses to pre-flowering drought stress. Field Crop Res 120:262–270

    Article  Google Scholar 

  • Lal S, Deshpande SB, Sehgal J (1994) Soil series of India. Soils bulletin 40. National Bureau of Soil Survey and Land Use Planning, Nagpur, p 648

    Google Scholar 

  • Landivar JA, Baker DN, Jenkins JN (1983) Application of GOSSYM to genetic feasibility studies. II. Analyses of increasing photosynthesis, specific leaf weight and longevity of leaves in cotton. Crop Sci 23:504–510

    Article  Google Scholar 

  • Messina CD, Jones JW, Boote KJ, Vallejos CE (2006) A gene-based model to simulate soybean development and yield responses to environment. Crop Sci 46:456–466

    Article  Google Scholar 

  • Naab JB, Singh P, Boote KJ, Jones JW, Marfo KO (2004) Using the CROPGRO-peanut model to quantify yield gaps of peanut in the Guinean savanna zone of Ghana. Agron J 96:1231–1242

    Article  Google Scholar 

  • Nautiyal PC, Ravindra V, Rathnakumar AL, Ajay BC, Zala PV (2012) Genetic variations in photosynthetic rate, pod yield and yield components in Spanish groundnut cultivars during three cropping seasons. Field Crop Res 125:83–91

    Article  Google Scholar 

  • Ntare BR, Williams JH, Dougbedji F (2001) Evaluation of groundnut genotypes for heat tolerance under field conditions in a Sahelian environment using a simple physiological model for yield. J Agric Sci 136:81–88

    Article  Google Scholar 

  • Painawadee M, Jogloy S, Kesmala T, Akkasaeng C, Patanothai A (2009) Identification of traits related to drought tolerance in peanut (Arachis hypogaea L.). Asian J Plant Sci 8:120–128

    Article  Google Scholar 

  • Prasad PVV, Boote KJ, Allen LH Jr, Thomas JMG (2003) Supra-optimal temperatures are detrimental to peanut (Arachis hypogaea L.) reproductive processes and yield at ambient and elevated carbon dioxide. Glob Chang Biol 9:1775–1787

    Article  Google Scholar 

  • Prasad PVV, Kakani VG, Upadhyaya HD (2009) Growth and production of groundnut. In: Verheye WH (ed) Soils, plant growth and crop production, encyclopedia of life support systems. Eolss Publishers, Oxford

    Google Scholar 

  • Putto C, Pathanothai A, Jogloy S, Pannangpetch K, Boote KJ, Hoogenboom G (2009) Determination of efficient test sites for evaluation of peanut breeding lines using the CSM-CROPGRO-peanut model. Field Crop Res 110:272–281

    Article  Google Scholar 

  • Ritchie JT (1998) Soil water balance and plant stress. In: Tsuji GY, Hoogenboom G, Thornton PK (eds) Understanding options for agricultural production. Kluwer Academic Publishers, Dordrecht, pp 41–54

    Chapter  Google Scholar 

  • Singh P, Boote KJ, Virmani SM (1994a) Evaluation of the groundnut model PNUTGRO for crop response to plant population and row spacing. Field Crops Res 39:163–170

    Article  Google Scholar 

  • Singh P, Boote KJ, Yogeswara Rao A, Iruthayaraj MR, Sheikh AM, Hundal SS, Narang RS, Singh P (1994b) Evaluation of the groundnut model PNUTGRO for crop response to water availability, sowing dates, and seasons. Field Crops Res 39:147–162

    Article  Google Scholar 

  • Singh P, Boote KJ, Kumar U, Srinivas K, Nigam SN, Jones JW (2012) Evaluation of genetic traits for improving productivity and adaptation of groundnut to climate change in India. J Agron Crop Sci 198:399–413

    Article  Google Scholar 

  • Soil Conservations Service (1972) National engineering handbook, hydrology section 4, chapters 4–10

  • Songsri P, Jogloy S, Vorasoot N, Akkasaeng C, Patanothai A, Holbrook CC (2008) Root distribution of drought-resistant peanut genotypes in response to drought. J Agron Crop Sci 194:92–103

    Article  Google Scholar 

  • Suleiman AA, Ritchie JT (2003) Modeling soil water redistribution during second-stage evaporation. Soil Sci Soc Am J 67:377–386

    Article  Google Scholar 

  • Suriharn B, Patanothai A, Boote KJ, Hoogenboom G (2011) Designing a peanut ideotype for a target environment using the CSM-CROPGRO-Peanut model. Crop Sci 51:1887–1902

    Article  Google Scholar 

  • Tardieu F (2003) Virtual plants: modelling as a tool for genomics of tolerance to water deficit. Trends Plant Sci 8:9–14

    Article  Google Scholar 

  • Tubiello FN, Soussana J, Howden SM (2007) Crop and pasture response to climate change. PNAS 105:19686–19690

    Article  Google Scholar 

  • Whisler FD, Acock B, Baker DN, Fye RE, Hodges HF, Lambert JR, Lemmon HE, McKinion JM, Reddy VR (1986) Crop simulation models in agronomic systems. Adv Agron 40:141–208

    Article  Google Scholar 

  • White JW, Hoogenboom G (2003) Gene-based approaches to crop simulation: past experiences and future opportunities. Agron J 95:52–64

    Article  Google Scholar 

  • Willmott CJ (1982) Some comments on the evaluation of model performance. Bull Am Meteor Soc 63:1309–1313

    Article  Google Scholar 

  • Yin X, Kropff MJ, Stam P (1999) The role of ecophysiological models in QTL analysis: the example of specific leaf area in barley. Heredity 82:415–421

    Article  Google Scholar 

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Acknowledgments

We are grateful to the India Meteorological Department, Pune, for providing part of the weather data used in this study and to ICRISAT for providing financial support through the Global Futures project fund on climate change.

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Authors and Affiliations

  1. International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru, 502 324, Andhra Pradesh, India

    Piara Singh, S. Nedumaran, N. P. Singh, K. Srinivas & M. C. S. Bantilan

  2. International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Bamako, Mali, BP 320

    B. R. Ntare

  3. Agronomy Department, University of Florida, IFAS, Gainesville, FL, 32611-0290, USA

    K. J. Boote

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  1. Piara Singh
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  2. S. Nedumaran
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  3. B. R. Ntare
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  4. K. J. Boote
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  5. N. P. Singh
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  7. M. C. S. Bantilan
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Correspondence to Piara Singh.

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Singh, P., Nedumaran, S., Ntare, B.R. et al. Potential benefits of drought and heat tolerance in groundnut for adaptation to climate change in India and West Africa. Mitig Adapt Strateg Glob Change 19, 509–529 (2014). https://doi.org/10.1007/s11027-012-9446-7

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  • DOI: https://doi.org/10.1007/s11027-012-9446-7

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