Broccoli yield response to environmental factors in sustainable agriculture

European Journal of Agronomy

Volumn 72, Issue , 2016, Pages 1-9

  Ciancaleoni, Simona ^a   Onofri, Andrea ^a   Torricelli, Renzo ^a   Negri, Valeria ^a  

^a UNIVERSITY OF PERUGIA   (Italy)

Author keywords

Brassica oleracea L.; Broccoli; GE interaction; Landrace; Reduced rank factorial regression; Synthetic varieties

Indexed keywords

AGRICULTURAL MANAGEMENT; AGRONOMY; ALTERNATIVE AGRICULTURE; CLIMATE CONDITIONS; ENVIRONMENTAL CHANGE; ENVIRONMENTAL FACTOR; GENOTYPE-ENVIRONMENT INTERACTION; LEAFY VEGETABLE; NITROGEN; RAINFALL; YIELD RESPONSE;

ITALY;

BRASSICA OLERACEA; BRASSICA OLERACEA VAR. ITALICA;

EID: 84943409914     PISSN: 11610301     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eja.2015.09.009     Document Type: Article

References (62)

1. Abush T. Genotype environment interaction in landrace derived advanced lines of Sorghum (Sorghum bicolor L. Moench). Dissertation 2001, Alemaya University of Agriculture, School of Graduate Studies, Alemaya, Ethiopia.
2. Admassu S., Nigussie M., Zelleke H. Genotype-environment interaction and stability analysis for grain yield of maize (Zea mays L.) in Ethiopia. Asian J. Plant Sci. 2008, 7:163-169.
3. Ajibade S.R., Ogunbodede B.A., Oyejola B.A. AMMI analysis of genotype x environment interaction in open pollinated maize varieties evaluated in the major agro-ecologies of Nigeria. Maize revolution in West and Central Africa 2003, 130-141. West and Central Africa Collaborative Maize Research Network, Nigeria. B. Badu-Apraku, M.A.B. Fakorede, M. Ouedraogo, R.J. Carsky, A. Menkir (Eds.).
4. Akaike H. A new look at the statistical model identification. IEEE Trans. Autom. Control 1974, 19:716-723.
5. Alberts M.J.A. Comparison of Statistical Methods to Describe Genotype Environment Interaction and Yield Stability in Multi-location Maize Trials 2004, University of the Free State.
6. Annicchiarico P. Genotype x Environment interaction challenge and opportunities for plant breeding and cultivar recommendation. FAO Plant Production and Protection 2002, Food and Agriculture Organization (FAO), Rome.
7. Baril C.P., Denis J.B., Wustman R., van Eeuwijk F.A. Analysing genotype by environment interaction in Dutch potato variety trials using factorial regression. Euphytica 1995, 84:23-29.
8. Bates, D., Maechler, M., Bolker, B., Walker, S., 2013. lme4: Linear Mixed-effects Models Using Eigen and S4. R Package Cersion 1. 0-5. http://CRAN.R-project.org/package=lme4.
9. Branca F. Cauliflower and broccoli. Vegetables I 2008, 151-186. Springer, New York, NY. J. Prohens, F. Nuez (Eds.).
10. Brancourt-Hulmel M., Denis J.B., Lecomte C. Determining environmental covariates which explain genotype environment interaction in winter wheat through probe genotypes and biadditive factorial regression. Theor. Appl. Genet. 2000, 100:285-298.
11. Brancourt-Humel M., Doussinault G., Lecomte C., Berard P., Le Buance B., Trottet M. Genetic improvement of agronomic traits of winter wheat cultivars released in France from 1946 - 1992. Crop Sci . 2003, 43:37-45.
12. Braun H.J., Atlin G., Payne T. Multi-location testing as a tool to identify plant response to global climate change. Climate Change and Crop Production 2010, 115-138. CABI Publishers, Wallingford, UK. M.P. Reynolds (Ed.).
13. Carr P.M., Kandel H.J., Porter P.M., Horsley R.D., Zwinger S.F. Wheat cultivar performance on certified organic fields in Minnesota and North Dakota. Crop Sci. 2006, 46:1963-1971.
14. Ceccarelli S. Positive interpretation of genotype by environment interaction in relation to sustainability and biodiversity. Plant Adaptation and Crop Improvement 1996, CABI, Wallingford, UK. M. Cooper, G.L. Hammer (Eds.).
15. Ciancaleoni S., Chiarenza G.L., Raggi L., Branca F., Negri V. Diversity characterisation of broccoli (Brassica oleracea L. var. italica Plenck) landraces for their on-farm (in situ) safeguard and use in breeding programs. Genet. Resour. Crop Evol. 2013, 61:451-464.
16. Ciancaleoni S., Raggi L., Negri V. Genetic outcomes from a farmer-assisted landrace selection programme to develop a synthetic variety of broccoli. Plant Genet. Res. 2014, 12:349-352.
17. Das R.R., Anil Kumar V., Rakshit S., Maraboina R., Panwar S., Savadia S., Rathore A. Interpreting genotype by environment interaction using weather covariate. J. Stat. Appl. 2012, 10:45-62.
18. Denis J.B. Analyse de regression factorielle. Biom. Praxim. 1980, 20:1-34.
19. Denis J.B. Two way analysis using covariates. Statistics 1988, 19:123-132.
20. Eberhart S.A., Russell W.A. Stability parameters for comparing varieties. Crop Sci. 1966, 6:36-40.
21. FAOSTAT, 2011. (accessed 07.09.14.). http://faostat3.fao.org/home/index.html.
22. Finlay K., Wilkinson G. The analysis of adaptation in a plant-breeding programme. Aust. J. Agric. Res. 1963, 14:742-754.
23. Gauch H.G.J. Statistical Analysis of Regional Yield Trials: AMMI Analysis of Factorial Designs 1992, Elsevier Science Publishers.
24. Gollob H.F. A statistical model which combines features of factor analytic and analysis of variance techniques. Psychometrika 1968, 33:73-115.
25. Hammer K., Gladis T., Laghetti G., Pignone D. The wild and the grown-remarks on Brassica. Int. J. AgriSci. 2013, 3(6):453-480.
26. Husson, F., Josse, J., Le, S, Mazet, J., 2013. FactoMineR: Multivariate Exploratory Data Analysis and Data Mining with R. R Package Version 1.2. Retrieved from: . http://CRAN.R.project.org/package=FactoMineR.
27. ISTAT, 2011. (accessed 07.09.14.). http://agri.istat.it/sag_is_pdwout/jsp/NewDownload.jsp%3Fid=15A18A28A&anid=2011.
28. Jump A.S., Marchant R., Penuelas J. Environmental change and the option value of genetic diversity. Trends Plant Sci. 2009, 14:51-58.
29. Kitchen J.L., McDonald G.K., Shepherd K.W., Lorimer M.F., Graham R.D. Comparing wheat grown in South Australian organic and conventional farming systems. 1. Growth and grain yield. Aust. J. Agric. Res. 2003, 54:889-901.
30. Kogbe J.O.S., Adediran J.A. Influence of nitrogen, phosphorus and potassium application on the yield of maize in the Savanna zone of Nigeria. Afr. J. Biotechnol. 2004, 2:345-349.
31. Lasa J.M., Igartua E., Ciudad F.J., Codesal P., Garcíaa E.V., Gracia M.P., Montoya J.L. Morphological and agronomical diversity patterns in the Spanish barley core collection. Hereditas 2001, 135:217-225.
32. Legendre P., Legendre L. Numerical Ecology 1998, 853. Elsevier.
33. Lopes M.S., Reynolds M.P., Jalal-Kamali M.R., Moussa M., Feltaous Y., Tahir I.S.A., Barma N., Vargas M., Mannes Y., Baum M. The yield correlations of selectable physiological traits in a population of advanced spring wheat lines grown in warm and drought environments. Field Crops Res. 2012, 128:129-136.
34. Mandel J. A new analysis of variance model for non-additive data. Technometrics 1971, 13:1-18.
35. Marjanović-Jeromela A., Nagl N., Gvozdanović-Varga J., Hristov N., Kondić-Špika A., Marinković M.V.R. Genotype by environment interaction for seed yield per plant in rapeseed using AMMI model. Pesqui. Agropecu. Bras. 2011, 46(2):174-181.
36. Negri V., Pacicco L., Bodesmo M., Torricelli R. The first Italian inventory of in situ maintained landraces 2013, Morlacchi Editrice, Perugia, IT, CD-ROM. ISBN 978-88-6074-279-7.
37. Oksanen, J., Blanchet, F.G., Kindt, R., Legendre, P., Minchin, P.R., O'Hara, R.B., Simpson, G.L., Solymos, P., Stevens, M.H.H., Wagner, H., 2013. Vegan: Community Ecology Package. R Package Version 2. 0-10. http://CRAN.R-project.org/package=vegan.
38. Perkins J.M., Jinks J.L. Environmental and genotype-environmental components of variability III. Multiple lines and crosses. Heredity 1968, 23:339-356.
39. Pinheiro J., Bates D. Mixed-effects models in S and S-Plus 2000, Springer-Verlag Inc., New York.
40. Poutala R.T., Korva J., Varis E. Spring wheat cultivar performance in ecological and conventional cropping systems. J. Sustain. Agric. 1993, 3:63-84.
41. R Development Core Team., 2013. R: a Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria. Retrieved from: . http://www.R-project.org.
42. Ramburan M., Zhou M., Labuschagne M. Interpretation of genotype×environment interactions of sugarcane: identifying significant environmental factors. Field Crops Res. 2011, 124:392-399.
43. Smith S.E. Breeding synthetic cultivars. Encyclopedia of Plant & Crop Science 2004, 205-206. Marcel Dekker, Inc., New York. R.M. Goodman (Ed.).
44. Sneller C.H., Norquest L.K., Dombek D. Repeatability of yield stability statistics in soybean. Crop Sci. 1997, 37:383-390.
45. Stagnari F., Onofri A., Codianni P., Pisante M. Durum wheat varieties in N-deficient environments and organic farming: a comparison of yield, quality and stability performances. Plant Breed. 2013, 132:266-275.
46. Stalenga J., Jończyk K. Yielding and selected leaf diseases of old winter wheat cultivars in the organic system. 16th IFOAM Organic World Congress 2008, 504-507.
47. Taye G., Getachew T., Bejiga G. AMMI adjustment for yield estimate and classification of genotypes and 25 environments in field pea (P. sativum L.). J. Genet. Breed. 2000, 54:183-191.
48. Torricelli R., Ciancaleoni S., Negri V. Performance and stability of homogeneous and heterogeneous broccoli (Brassica oleracea L. var. italica Plenck) varieties in organic and low-input conditions. Euphytica 2014, 199:385-395.
49. van Eeuwijk F.A. Interpreting genotype-by-environment interaction using redundancy analysis. Theor. Appl. Genet. 1992, 85:89-100.
50. van Eeuwijk F.A. Linear and bilinear models for the analysis of multi-environment trials: I. An inventory of models. Euphytica 1995, 84:1-7.
51. van Eeuwijk F.A., Keizer L.C.P., Bakker J.J. Linear and bilinear models for the analysis of multi-environment trials: II. An application to data from the Dutch maize variety trials. Euphytica 1995, 84:9-22.
52. van Eeuwijk F.A., Denis J.B., Kang M.S. Incorporating additional information on genotypes and environments in models for two-way genotype by environment tables. Genotype-by-environment Interaction 1996, CRC Press, Boca Raton, Florida. S. Kang, H.G. Gauch (Eds.).
53. van Oosterom E.J., Ceccarelli S., Peacock J.M. Yield response of barley to rainfall and temperature in Mediterranean environments. J. Agric. Sci. 1993, 121:307-313.
54. Venables W.N., Ripley B.D. Modern applied statistics with S 2002, Springer, New York, ISBN 0-387-95457-0. Fourth ed.
55. Voltas J., van Eeuwijk F.A., Sombrero A. Integrating statistical and ecophysiological analyses of genotype by environment interaction for grain filling of barley I: Individual grain weight. Field Crop Res. 1999, 62:63-74.
56. Voltas J., van Eeuwijk F.A., Iguarta E., Garcia del Morales L.F., Molina-Cano J.L., Ramagosa I. Genotype by environment interaction and adaptation in barley breeding: basic concepts and methods of analysis. Barley Science: Recent Advances from Molecular Biology to Agronomy of Yield and Quality 2002, Food Product Press, New York, ISBN 1-56022-909-8. G.A. Slafer, J.L. Molina-Cano, R. Savin, J.L. Arais, I. Ramagosa (Eds.).
57. Voltas J., López-Córcoles H., Borrás G. Use of biplot analysis and factorial regression for the investigation of superior genotypes in multi-environment trials. Eur. J. Agron. 2005, 22:309-324.
58. Yahiaoui S., Cuesta-Marcos A., Gracia M.P., Medina B., Lasa J.M., Casas A.M., Igartua E. Spanish barley landraces outperform modern cultivars at low-productivity sites. Plant Breed. 2014, 133:218-226.
59. Yan W., Hunt L.A., Sheng Q., Szlavnics Z. Cultivar evaluation and mega-environment investigation based on the GGE biplot. Crop Sci. 2000, 40:597-605.
60. Yates F., Cochran W.G. The analysis of groups of experiments. J. Agric. Sci. 1938, 28:556-580.
61. Zand E., Beckie H.J. Competitive ability of hybrid and open-pollinated canola (Brassica napus) with wild oat (Avena fatua). Can. J. Plant Sci. 2002, 82:473-480.
62. Zar J.H. Multiple repression and correlation. Biostatistical Analysis 1996, 407-445. Prentice-Hall International, Upper Saddle River, NJ. J.H. Zar (Ed.).