Maize root architecture and water stress tolerance: An approximation from crop models

Agronomy Journal

Volumn 106, Issue 6, 2014, Pages 2287-2295

  Carretero, Ramiro ^a   Bert, Federico Esteban ^a   Podestá, Guillermo ^b  

^a UNIVERSIDAD DE BUENOS AIRES   (Argentina)

^b UNIVERSITY OF MIAMI   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 84908250420     PISSN: 00021962     EISSN: 14350645     Source Type: Journal    
DOI: 10.2134/agronj14.0214     Document Type: Article

References (62)

1. Berbery, E.H., M.E. Doyle, and V. Barros. 2006. Tendencias regionales en la precipitacion. In: V. Barros, R. Clarke, and P. Silva Dias, editors, El cambio climatico en la Cuenca del Plata. CONICET, Buenos Aires, Argentina. p. 67–92.
2. Bert, F.B., E.H. Satorre, F. Ruiz Toranzo, and G.P. Podesta. 2006. Climatic information and decision-making in maize crop production systems of Argentinean Pampas. Agric. Syst. 88:180–204. doi:10.1016/j. agsy.2005.03.007.
3. Blum, A. 2005. Drought resistance, water-use efficiency, and yield potential— Are they compatible, dissonant, or mutually exclusive? Aust. J. Agric. Res. 56:1159–1168. doi:http://dx.doi.org/10.1071/AR05069.
4. Blum, A. 2009. Effective use of water (EUW) and not water-use efficiency (WUE) is the target of crop yield improvement under drought stress. Field Crops Res. 112:119–123. doi:http://dx.doi.org/10.1016/j.fcr.2009.03.009.
5. Boulanger, J.-P., J. Leloup, O. Penalba, M. Rusticucci, F. Lafon, and W. Vargas. 2005. Observed precipitation in the Parana-Plata hydrological basin: Long-term trends, extreme conditions and ENSO teleconnections. Clim. Dyn. 24:393–413. doi:10.1007/s00382-004-0514-x
6. Boulanger, J.-P., F. Martinez, and E.C. Segura. 2007. Projection of future climate change conditions using IPCC simulations, neural networks and Bayesian statistics. Part 2: Precipitation mean state and seasonal cycle in South America. Clim. Dyn. 28:255–271. doi:10.1007/s00382-006-0182-0.
7. Bruce, W.B., G.O. Edmeades, and T.C. Barker. 2002. Molecular and physiological approaches to maize improvement for drought tolerance. J. Exp. Bot. 53:13–25. doi:10.1093/jexbot/53.366.13.
8. Calvino, P.A., and J.P. Monzon. 2009. Farming systems of Argentina: Yield constraints and risk management. Crop physiology: Applications for genetic improvement and agronomy. Elsevier Academic Press, San Diego, CA.
9. Campos, H., M. Cooper, J.E. Habben, G.O. Edmeades, and J.R. Schussler. 2004. Improving drought tolerance in maize: A view from industry: Linking functional genomics with physiology for global change research. Field Crops Res. 90:19–34. doi:10.1016/j.fcr.2004.07.003.
10. Chimenti, C.A., M. Marcantonio, and A.J. Hall. 2006. Divergent selection for osmotic adjustment results in improved drought tolerance in maize (Zea mays L.) in both early growth and flowering phases. Field Crops Res. 95:305–315. doi:http://dx.doi.org/10.1016/j.fcr.2005.04.003.
11. Condon, A.G., R.A. Richards, G.J. Rebetzke, and G.D. Farquhar. 2002. Improving intrinsic water-use efficiency and crop yield. Crop Sci. 42:122–131. doi:10.2135/cropsci2002.0122.
12. Dardanelli, J.L., J.T. Ritchie, M. Calmon, J.M. Andriani, and D.J. Collino. 2004. An empirical model for root water uptake. Field Crops Res. 87:59-71. doi:http://dx.doi.org/10.1016/j.fcr.2003.09.008.
13. Delvenne, P., F. Vasen, and A.M. Vara. 2013. The “soy-ization” of Argentina: The dynamics of the “globalized” privatization regime in a peripheral context. Technol. Soc. 35:153–162. doi:10.1016/j.techsoc.2013.01.005.
14. Ferreyra, A., G. Podesta, C. Messina, D. Letson, J. Dardanelli, E. Guevara et al. 2001. A linked-modeling framework to estimate maize production risk associated with ENSO-related climate variability in Argentina. Agric. For. Meteorol. 107:177–192. doi:10.1016/S0168-1923(00)00240-9.
15. Giuliani, S., M.C. Sanguineti, R. Tuberosa, M. Bellotti, S. Salvi, and P. Landi. 2005. Root-ABA1, a major constitutive QTL, affects maize root architecture and leaf ABA concentration at different water regimes. J. Exp. Bot. 56:3061–3070. doi:10.1093/jxb/eri303.
16. Goddard, L., S.J. Mason, S.E. Zebiak, C.F. Ropelewski, R. Basher, and M.A. Cane. 2001. Current approaches to seasonal-to-interannual climate predictions. Int. J. Climatol. 21:1111–1152. doi:10.1002/joc.636.
17. Guevara, E., S. Meira, M. Maturano, and G. Coco. 1999. Maize simulation for different environments in Argentina. In: M. Donatelli, C. Stockle, F. Villalobos, and J.M. Villar Mir, editors, International Symposium: Modelling Cropping Systems. European Soc. of Agron., Univ. of Lleida, Catalonia, Spain. 21-23. June 1999. European Soc. of Agron., Montpellier, France. p. 193–194.
18. Hall, A.J., C.M. Rebella, C.M. Ghersa, and J.-P. Culot. 1992. Field crops systems of the Pampas. In: C.J. Pearson, editor, Field crops systems: Ecosystems of the world. Elsevier, Amsterdam. p. 413–449.
19. Hall, A.J., and R.A. Richards. 2013. Prognosis for genetic improvement of yield potential and water-limited yield of major grain crops. Field Crops Res. 143:18–33. doi:http://dx.doi.org/10.1016/j.fcr.2012.05.014.
20. Hammer, G.L., S. Chapman, E. van Oosterom, and D.W. Podlich. 2005. Trait physiology and crop modelling as a framework to link phenotypic complexity to underlying genetic systems. Aust. J. Agric. Res. 56:947-960. doi:http://dx.doi.org/10.1071/AR05157.
21. Hammer, G.L., Z. Dong, G. McLean, A. Doherty, C. Messina, J. Schussler et al. 2009. Can changes in canopy and/or root system architecture explain historical maize yield trends in the U.S. Corn Belt? Crop Sci. 49:299-312. doi:10.2135/cropsci2008.03.0152.
22. Hoogenboom, G., P.W. Wilkens, P.K. Thornton, J.W. Jones, L.A. Hunt, and D.T. Imamura. 1999. Decision support system for agrotechnology transfer v3.5. In: G. Hoogenboom, P.W. Wilkens, and G.Y. Tsuji, editors, DSSAT version 3. Vol. 4. Univ. of Hawaii, Honolulu. p. 1–36.
23. Jones, C.A., W.L. Bland, J.T. Ritchie, and J.R. Williams. 1991. Simulation of root growth. In: J. Hanks and J.T. Ritchie, editors, Modeling plant and soil systems. ASA, CSSA, and SSSA, Madison, WI. p. 91–123.
24. Jones, C.A., and J.R. Kiniry, editors. 1986. CERES-Maize: A simulation model of maize growth and development. Texas A&M Univ. Press, College Station.
25. Jones, J.W., and B. Zur. 1984. Simulation of possible adaptive mechanisms in crops subjected to water stress. Irrig. Sci. 5:251–264. doi:10.1007/BF00258178.
26. Jordan, W.R., W.A. Dugas Jr., and P.J. Shouse. 1983. Strategies for crop improvement for drought-prone regions. Agric. Water Manage. 7:281–299. doi:http://dx.doi.org/10.1016/0378-3774(83)90090-2.
27. Kato, Y., J. Abe, A. Kamoshita, and J. Yamagishi. 2006. Genotypic variation in root growth angle in rice (Oryza sativa L.) and its association with deep root development in upland fields with different water regimes. Plant Soil 287:117–129. doi:10.1007/s11104-006-9008-4.
28. Leguizamon, A. 2014. Modifying Argentina: GM soy and socio-environmental change. Geoforum 53:149–160. doi:10.1016/j.geoforum.2013.04.001.
29. Lilley, J.M., and J.A. Kirkegaard. 2011. Benefits of increased soil exploration by wheat roots. Field Crops Res. 122:118–130. doi:http://dx.doi. org/10.1016/j.fcr.2011.03.010.
30. Lorens, G.F., J.M. Bennett, and L.B. Loggale. 1987a. Differences in drought resistance between two corn hybrids. I. Water relations and root length density. Agron. J. 79:802–807. doi:10.2134/agronj1987.00021962007900050009x
31. Lorens, G.F., J.M. Bennett, and L.B. Loggale. 1987b. Differences in drought resistance between two corn hybrids. II. Component analysis and growth rates. Agron. J. 79:808–813. doi:10.2134/agronj1987.00021962007900050010x.
32. Ludlow, M.M., and R.C. Muchow. 1990. A critical evaluation of traits for improving crop yields in water-limited environments. In: N.C. Brady, editor, Advances in agronomy. Academic Press, San Diego, CA. p. 107–153.
33. Manschadi, A., G. Hammer, J. Christopher, and P. deVoil. 2008. Genotypic variation in seedling root architectural traits and implications for drought adaptation in wheat (Triticum aestivum L.). Plant Soil 303:115-129. doi:10.1007/s11104-007-9492-1.
34. Manschadi, A.M., J. Christopher, P. deVoil, and G.L. Hammer. 2006. The role of root architectural traits in adaptation of wheat to water-limited environments. Funct. Plant Biol. 33:823–837. doi:http://dx.doi. org/10.1071/FP06055.
35. Manuel-Navarrete, D., G. Gallopin, M. Blanco, M. Diaz-Zorita, D. Ferraro, H. Herzer et al. 2009. Multi-causal and integrated assessment of sustainability: The case of agriculturization in the Argentine Pampas. Environ. Dev. Sustain. 11:621–638. doi:10.1007/s10668-007-9133-0.
36. McKenzie, B.M., A.G. Bengough, P.D. Hallett, W.T.B. Thomas, B. Forster, and J.W. McNicol. 2009. Deep rooting and drought screening of cereal crops: A novel field-based method and its application. Field Crops Res. 112:165–171. doi:http://dx.doi.org/10.1016/j.fcr.2009.02.012.
37. Mercau, J.L., E.H. Satorre, M.E. Otaegui, G.A. Maddoni, J. Carcova, R. Ruiz et al. 2001. Evaluacion a campo del comportamiento del modelo Ceres en cultivos de maiz del norte de la provincia de Buenos Aires. In: Asoc. de Ingenieros Agronomos del Norte de la Provincia de Buenos Aires, editor, Proceedings of VII Congreso Nacional de Maiz, Pergamino, Argentina. 1–7. Nov. 2001. Asoc. de Ingenieros Agronomos del Norte de la Provincia de Buenos Aires, Pergamino, Buenos Aires, Argentina.
38. Minetti, J.L., W. Vargas, A.G. Poblete, L.R. Acuna, and G. Casagrande. 2003. Non-linear trends and low frequency oscillations in annual precipitation over Argentina and Chile, 1931–1999. Atmosfera 16:119–135.
39. Morgan, J., and A. Condon. 1986. Water use, grain yield, and osmoregulation in wheat. Funct. Plant Biol. 13:523–532. doi:http://dx.doi.org/10.1071/PP9860523.
40. Nagore, M.L., L. Echarte, F.H. Andrade, and A. Della Maggiora. 2014. Crop evapotranspiration in Argentinean maize hybrids released in different decades. Field Crops Res. 155:23–29. doi:http://dx.doi.org/10.1016/j.fcr.2013.09.026.
41. Paruelo, J.M., J.P. Guerschman, and S.R. Veron. 2005. Expansion agricola y cambios en el uso del suelo. Cienc. Hoy 15:14–23.
42. Passioura, J.B. 1983. Roots and drought resistance. In: J.F. Stone and W.O. Willis, editors, Plant production and management under drought conditions. Elsevier, Amsterdam. p. 265–280.
43. Passioura, J.B. 1996. Drought and drought tolerance. Plant Growth Regul. 20:79–83. doi:10.1007/BF00024003.
44. Passioura, J.B. 2006. Increasing crop productivity when water is scarce—From breeding to field management. Agric. Water Manage. 80:176–196. doi:http://dx.doi.org/10.1016/j.agwat.2005.07.012.
45. Passioura, J.B. 2012. Phenotyping for drought tolerance in grain crops: When is it useful to breeders? Funct. Plant Biol. 39:851–859. doi:http://dx.doi. org/10.1071/FP12079.
46. Podestá, G., F. Bert, B. Rajagopalan, S. Apipattanavis, C. Laciana, E. Weber et al. 2009. Decadal climate variability in the Argentine Pampas: Regional impacts of plausible climate scenarios on agricultural systems. Clim. Res. 40:199–210. doi:10.3354/cr00807.
47. Podestá, G.P., C.D. Messina, M.O. Grondona, and G.O. Magrin. 1999. Associations between grain crop yields in central-eastern Argentina and El Nino–Southern Oscillation. J. Appl. Meteorol. 38:1488–1498. doi:10.1175/1520-0450(1999)0382.0.CO;2.
48. Rebetzke, G.J., A.G. Condon, R.A. Richards, and G.D. Farquhar. 2002. Selection for reduced carbon isotope discrimination increases aerial biomass and grain yield of rainfed bread wheat. Crop Sci. 42:739–745. doi:10.2135/cropsci2002.0739.
49. Reboratti, C.E. 2010. Un mar de soja: La nueva agricultura en Argentina y sus consecuencias. Revista de Geografia Norte Grande 45:63–76.
50. Richards, R.A. 2006. Physiological traits used in the breeding of new cultivars for water-scarce environments. Agric. Water Manage. 80:197–211. doi:http://dx.doi.org/10.1016/j.agwat.2005.07.013.
51. Robertson, M.J., S. Fukai, G.L. Hammer and M.M. Ludlow. 1993. Modelling root growth of grain sorghum using the CERES approach. Field Crops Res. 33:113–130. doi:http://dx.doi.org/10.1016/0378-4290(93)90097-7.
52. Ropelewski, C.F. and M.S. Halpert. 1987. Global and regional scale precipitation patterns associated with the El Nino/Southern Oscillation. Mon. Weather Rev. 115:1606–1626. doi:10.1175/1520-0493(1987)1152.0.CO;2.
53. Ropelewski, C.F., and S. Halpert. 1989. Precipitation patterns associated with the high index phase of the Southern Oscillation. J. Clim. 2:268–284. doi:10.1175/1520-0442(1989)0022.0.CO;2.
54. Rusticucci, M., and O. Penalba. 2000. Interdecadal changes in the precipitation seasonal cycle over Southern South America and their relationship with surface temperature. Clim. Res. 16:1–15. doi:10.3354/cr016001.
55. Salih, A.A., I.A. Ali, A. Lux, M. Luxova, Y. Cohen, Y. Sugimoto et al. 1999. Rooting, water uptake, and xylem structure adaptation to drought of two sorghum cultivars. Crop Sci. 39:168–173. doi:10.2135/cropsci1999.0011 183X003900010027x
56. Sinclair, T.R., and R.C. Muchow. 2001. System analysis of plant traits to increase grain yield on limited water supplies. Agron. J. 93:263–270. doi:10.2134/agronj2001.932263x
57. Singh, P., S. Nedumaran, P.C.S. Traore, K.J. Boote, H.F.W. Rattunde, P.V.V. Prasad et al. 2014. Quantifying potential benefits of drought and heat tolerance in rainy season sorghum for adapting to climate change. Agr. Forest Meteorol. 185:37–48. doi:http://dx.doi.org/10.1016/j. agrformet.2013.10.012.
58. Singh, V., E. Oosterom, D. Jordan, C. Messina, M. Cooper, and G. Hammer. 2010. Morphological and architectural development of root systems in sorghum and maize. Plant Soil 333:287–299. doi:10.1007/s11104-010-0343-0.
59. Skansi, M.M., S.E. Nunez, G.P. Podesta, and N. Garay. 2009. La sequia del ano 2008 en la region humeda argentina descripta a traves del Indice de Precipitacion Estandarizado. CONGREMET 2009. Centro Argentino de Meteorologos, Buenos Aires, Argentina.
60. Tardieu, F. 2012. Any trait or trait-related allele can confer drought tolerance: Just design the right drought scenario. J. Exp. Bot. 63:25–31. doi:10.1093/jxb/err269.
61. Tollefson, J. 2011. Drought-tolerant maize gets US debut. Nature (London) 469:144. doi:10.1038/469144a
62. Wan, C., W. Xu, R. Sosebee, S. Machado, and T. Archer. 2000. Hydraulic lift in drought-tolerant and-susceptible maize hybrids. Plant Soil 219:117–126. doi:10.1023/A:1004740511326