Grain yield increase in cereal variety mixtures: A meta-analysis of field trials

Field Crops Research

Volumn 114, Issue 3, 2009, Pages 361-373

  Kiær, Lars P ^a,b   Skovgaard, Ib M ^b   Østergård, Hanne ^a  

^a TECHNICAL UNIVERSITY OF DENMARK   (Denmark)

^b UNIVERSITY OF COPENHAGEN   (Denmark)

Author keywords

Barley; Crop diversity; Cultivar mixtures; Genotype environment interactions; Heterogeneous environments; Meta regression; Relative mixing effect; Wheat

Indexed keywords

BARLEY; CROP YIELD; CROPPING PRACTICE; ECOLOGICAL THEORY; META-ANALYSIS; SEED; WHEAT;

HORDEUM; HORDEUM VULGARE SUBSP. VULGARE; TRITICUM AESTIVUM;

EID: 70350591054     PISSN: 03784290     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.fcr.2009.09.006     Document Type: Article

References (53)

1. Adams D.C., Gurevitch J., and Rosenberg M.S. Resampling tests for meta-analysis of ecological data. Ecology 78 (1997) 1277-1283
2. 2) effects on soybean (Glycine max) physiology, growth and yield. Global Change Biol. 8 8 (2002) 695-709
3. Clay R.E., and Allard R.W. A comparison of performance of homogeneous and heterogeneous barley populations. Crop Sci. 9 (1969) 407-412
4. Cochran W.G. The combination of estimates from different experiments. Biometrics 10 (1954) 101-129
5. Cowger C., and Weisz R. Winter wheat blends (mixtures) produce a yield advantage in north Carolina. Agron. J. 100 (2008) 169-177
6. Dhima K.V., and Eleftherohorinos I.G. Influence of nitrogen on competition between winter cereals and sterile oat. Weed Sci. 49 1 (2001) 77-82
7. Duval S.J., and Tweedie R.L. A non-parametric 'trim and fill' method of assessing publication bias in meta-analysis. J. Stat. Am. Soc. 95 409 (2000) 89-98
8. Egger M., Smith G.D., Schneider M., and Minder C. Bias in meta-analysis detected by a simple, graphical test. Br. Med. J. 315 (1997) 629-634
9. Finckh M.R., Gacek E.S., Goyeau H., Lannou C., Merz U., Mundt C.C., Munk L., Nadziak J., Newton A.C., de Vallavieille-Pope C., and Wolfe M.S. Cereal variety and species mixtures in practice, with emphasis on disease resistance. Agronomie 20 (2000) 813-837
10. Finckh M.R., and Mundt C.C. Plant competition and disease in genetically diverse wheat populations. Oecologia 91 (1992) 82-92
11. Finckh M.R., and Wolfe M.S. The use of biodiversity to restrict plant diseases and some consequences for farmers and society. In: Jackson L.E. (Ed). Ecology in Agriculture (1997), Academic Press, San Diego, CA 199-233
12. Fischbeck G. Variability in winter wheat and spring barley yields in Bavaria. In: Anderson J.R., and Hazell P.B.R. (Eds). Variability in Grain Yields: Implications for Agricultural Research and Policy in Developing Countries (1989), International Food Policy Research Institute, The Johns Hopkins University Press, Baltimore 118-124 Chapter 9
13. Gini C. Variabilità e mutabilità. In: Pizetti E., and Salvemini T. (Eds). Memorie di metodologica statistica (1955), Libreria Eredi Virgilio Veschi, Rome
14. Glass G.V. Primary, secondary, and meta-analysis of research. Educ. Res. 5 (1976) 3-8
15. Gurevitch J., and Hedges L.V. Statistical issues in ecological meta-analyses. Ecology 80 (1999) 1142-1149
16. Gurevitch J., Morrow L.L., Wallace A., and Walsh J.S. A meta-analysis of competition in field experiments. Am. Nat. 140 (1992) 539-572
17. Harlan J.R. Crops and Man (1975), ASA, CSSA, Madison, WI
18. Hedges L.V., and Olkin I. Statistical Methods for Meta-analysis (1985), Academic Press, San Diego, CA
19. Higgins J.P.T., and Thompson S.G. Quantifying heterogeneity in a meta-analysis. Stat. Med. 21 (2002) 1539-1558
20. Higgins J.P.T., Thompson S.G., Deeks J.J., and Altman D.G. Measuring inconsistency in meta-analyses. Br. Med. J. 327 (2003) 557-560
21. Huhn M. Theoretical studies on the necessary number of components in mixtures. 1. Number of components and yield stability. Theor. Appl. Genet. 70 (1985) 383-389
22. Jedel P.E., Helm J.H., and Burnett P.A. Yield, quality and stress tolerance of barley mixtures in central Alberta. Can. J. Plant Sci. 78 (1998) 429-436
23. Jennions M.D., and Møller A.P. Publication bias in ecology and evolution: an empirical assessment using the 'trim and fill' method. Biol. Rev. Cambridge Philos. Soc. 77 2 (2002) 211-222
24. Juskiw P.E., Helm J.H., and Burnett P.A. Three-component barley mixtures: ratio effects in replacement series. Can. J. Plant Sci. 81 (2001) 651-656
25. Kaut A.H.E.E., Mason H.E., Navabi A., O'Donovan J.T., and Spaner D. Organic and conventional management of mixtures of wheat and spring cereals. Agron. Sustain. Dev. 28 (2008) 363-371
26. Leimu R., and Koricheva J. A meta-analysis of tradeoffs between plant tolerance and resistance to herbivores: combining the evidence from ecological and agricultural studies. Oikos 112 (2006) 1-9
27. Mann C. Meta-analysis in the breech. Science 249 (1990) 476-480
28. Miguez F.E., and Bollero G.A. Review of corn yield response under winter cover cropping systems using meta-analytic methods. Crop Sci. 45 (2005) 2318-2329
29. Mundt C.C. Use of multiline cultivars and cultivar mixtures for disease management. Annu. Rev. Phytopathol. 40 (2002) 381-410
30. Newton A.C., Ellis R.P., Hackett C.A., and Guy D.C. The effect of component number on Rhynchosporium secalis infection and yield in mixtures of winter barley cultivars. Plant Pathol. 46 (1997) 930-938
31. Newton A.C., and Guy D.C. The effects of uneven, patchy cultivar mixtures on disease control and yield in winter barley. Field Crop Res. 110 (2009) 225-228
32. Olkin I., and Shaw D.V. Meta-analysis and its applications in horticultural science. Hortscience 30 7 (1995) 1343-1348
33. Østergård, H., Jensen, J.W. 2005. Increased yield and yield stability in variety mixtures of spring barley. DARCOF enews 3. Sep 2005. Website: www.icrofs.org.
34. Paul P.A., Lipps P.E., and Madden L.V. Relationship between visual estimates of Fusarium head blight intensity and deoxynivalenol accumulation in harvested wheat grain: a meta-analysis. Phytopathology 95 10 (2005) 1225-1236
35. Paul P.A., Lipps P.E., and Madden L.V. Meta-analysis of regression coefficients for the relationship between fusarium head blight and deoxynivalenol content of wheat. Phytopathology 96 (2006) 951-961
36. Paul P.A., Lipps P.E., Hershman D.E., McMullen M.P., Draper M.A., and Madden L.V. A quantitative review of tebuconazole effect on fusarium head blight and deoxynivalenol content in wheat. Phytopathology 97 (2007) 211-220
37. Piepho H.P. Methods for comparing the yield stability of cropping systems-a review. J. Agron. Crop Sci. 180 (1998) 193-213
38. R Development Core Team. R: A Language and Environment for Statistical Computing (2009), R Foundation for Statistical Computing, Vienna, Austria. http://www.r-project.org/ ISBN: 3-900051-07-0, http://www.R-project.org
39. Rosenberg M.S., Garrett K.A., Su Z., and Bowden R.L. Meta-analysis in plant pathology: synthesizing research results. Phytopathology 94 (2004) 1013-1017
40. Rotundo J.L., and Westgate M.E. Meta-analysis of environmental effects on soybean seed composition. Field Crop Res. 110 (2009) 147-156
41. Sarandon S.J., and Sarandon R. Mixture of cultivars-pilot field trial of an ecological alternative to improve production or quality of wheat (Triticum aestivum). J. Appl. Ecol. 32 (1995) 288-294
42. Satorre E.H., and Snaydon R.W. A comparison of root and shoot competition between spring cereals and Avena Fatua L. Weed Res. 32 1 (1992) 45-55
43. Shah D.A., and Dillard H.R. Yield loss in sweet corn caused by Puccinia sorghi: a meta-analysis. Plant Dis. 90 (2006) 1413-1418
44. Simmonds N.W. Variability in crop plants, its use and conservation. Biol. Rev. 37 (1962) 422-465
45. Smithson J.B., and Lenné J.M. Varietal mixtures: a viable strategy for sustainable productivity in subsistence agriculture. Ann. Appl. Biol. 128 (1996) 127-158
46. Stanley T.D. Beyond publication bias. J. Econ. Surveys 19 3 (2005) 309-345
47. Tonitto C., David M.B., and Drinkwater L.E. Replacing bare fallows with cover crops in fertilizer-intensive cropping systems: a meta-analysis of crop yield and N dynamics. Agr. Ecosyst. Environ. 112 (2006) 58-72
48. Viechtbauer W. Bias and efficiency of meta-analytic variance estimators in the random-effects model. J. Educ. Behav. Stat. 30 (2005) 261-293
49. Vila M., Williamson M., and Lonsdale M. Competition experiments on alien weeds with crops: lessons for measuring plant invasion impact?. Biol. Invas. 6 (2004) 59-69
50. Web of Science, 2008. URL: www.isiknowledge.com. Thomson Reuters.
51. Web of Science, 2009. URL: www.isiknowledge.com. Thomson Reuters (assessed on 14 May 2009).
52. Webster P., and Williams N.T. Variability in wheat and barley production in Southeast England. In: Anderson J.R., and Hazell P.B.R. (Eds). Variability in Grain Yields: Implications for Agricultural Research and Policy in Developing Countries (1989), International Food Policy Research Institute, The Johns Hopkins University Press, Baltimore 107-117 Chapter 8
53. Wolfe M.S., Baresel J.P., Desclaux D., Goldringer I., Hoad S., Kovacs G., Loeschenberger F., Miedaner T., Østergård H., and van Bueren E.T.L. Developments in breeding cereals for organic agriculture. Euphytica 163 3 (2008) 323-346