1. bookVolume 57 (2020): Issue 2 (December 2020)
Journal Details
License
Format
Journal
eISSN
2199-577X
First Published
17 Aug 2013
Publication timeframe
2 times per year
Languages
English
access type Open Access

A meta-analysis of genotype × environment interaction on sugar beet performance

Published Online: 31 Dec 2020
Volume & Issue: Volume 57 (2020) - Issue 2 (December 2020)
Page range: 221 - 236
Journal Details
License
Format
Journal
eISSN
2199-577X
First Published
17 Aug 2013
Publication timeframe
2 times per year
Languages
English
Summary

The evaluation of sugar beet genotypes under different climate conditions is a principal goal of breeding programs. In most studies, environment has a high influence on the qualitative and quantitative traits of sugar beet. Therefore, data collected from different environments may contribute to more accurate genotype selection. In this study, the effect of different environments on sugar beet genotypes’ performance was evaluated using a meta-analysis method based on Hedges’ technique. Data were collected from 149 trials conducted in twelve regions in Iran over 15 years (2003–18). For all trials, the value of the traits was weighted, and subsequently the effect size, reaction ratio and confidence interval were estimated. Among the studied environments, Khoy had a positive effect on root yield, sugar content, sugar yield and white sugar yield. As could be expected, the effect of environment on final yield formation was high, so that the Shiraz environment had a negative effect on root yield and sugar yield. Overall, the ranking of environments based on the meta-analysis results was quite different from that obtained by comparison of mean results.

Keywords

Asher M.C.J. (1993): Rhizomania. In Cooke D.A. and Scott R.K. (eds.), The sugar beet crop. Chapman & Hall, London: 312-346.10.1007/978-94-009-0373-9_9Search in Google Scholar

Barker H.L., Holeski L.M., Lindroth R.L. (2019): Independent and interactive effects of plant genotype and environment on plant traits and insect herbivore performance: A meta-analysis with Salicaceae. Funct Ecol. 33(3): 422-435.10.1111/1365-2435.13249Search in Google Scholar

Bengtsson J., Ahnsrtom J., Weibull A. (2005): The effects of organic agriculture on biodiversity and abundance: a meta-analysis. J Appl Ecol. 42: 261-269.10.1111/j.1365-2664.2005.01005.xSearch in Google Scholar

Bloch D., Hoffmann C.M., Marlander B. (2006): Solute accumulation as cause for quality losses in sugar beet submitted to continuous and temporary drought stress. J Agron Crop Sci. 192: 17–24.10.1111/j.1439-037X.2006.00185.xSearch in Google Scholar

Cohn L.D., Becker B.J. (2003): How meta-analysis increases statistical power. Psychol Methods 8(3): 243.Search in Google Scholar

De Biaggi M., Stevanato P., Trebbi D., Saccomani M., Biancardi E. (2010): Sugar beet resistance to rhizomania: State of the art and perspectives. Sugar Tech 12 (3-4): 238-242.10.1007/s12355-010-0047-zSearch in Google Scholar

Fasahat P., Aghaeezadeh M., Jabbari L., Hemayati S.S., Townson P. (2018): Sucrose accumulation in sugar beet: from fodder beet selection to genomic selection. Sugar Tech 20(6): 635-644.10.1007/s12355-018-0617-zSearch in Google Scholar

Fasahat P., Khayamim S., Soltani IJ., Darabi S., Pedram A., Hasanai M., Jalilian A., Babaei B. (2020): Stability Analysis of Genotype × Environment Interaction Effect on Sugar Yield in Sugar Beet Hybrids. Journal of Crop Breeding 11(32): 33-40.Search in Google Scholar

Fasahat P., Muhammad K., Abdullah A., Rahman B.M.A., Siing N.M., Gauch J.H.G., Ratnam W. (2014): Genotype × environment assessment for grain quality traits in rice. Communications in Biometry and Crop Science 9(2): 71-82.Search in Google Scholar

Freckleton R.P., Watkinson A.R., Webb D.J., Thomas T.H. (1999): Yield of sugar beet in relation to weather and nutrients. Agr Forest Meteorol. 93(1): 39-51.10.1016/S0168-1923(98)00106-3Search in Google Scholar

Francois L.E., Grieve C.M., Maas E.V., Lesch S.M. (1994): Time of salt stress affects growth and yield components of irrigated wheat. Agron J. 86(1): 100-107.10.2134/agronj1994.00021962008600010019xSearch in Google Scholar

Gurevitch J., Hedges L.V. (1999): Statistical issues in ecological Meta-Analysis. Ecology 80: 1142-1149.10.1890/0012-9658(1999)080[1142:SIIEMA]2.0.CO;2Search in Google Scholar

Hedges LV (1992): Modeling publication selection effects in meta-analysis. Stat Sci. 246-255.10.1214/ss/1177011364Search in Google Scholar

Hedges L.V., Gurevitch J., Curtis P.S. (1999): The meta-analysis of response ratios in experimental ecology. Ecology 80(4): 1150-1156.10.1890/0012-9658(1999)080[1150:TMAORR]2.0.CO;2Search in Google Scholar

Heijbroek W. (1988): Dissemination of rhizomania by soil, beet seeds and stable manure. Nethe J Plant Pathol 94(1): 9-15.10.1007/BF01999803Search in Google Scholar

Hoffmann C.M., Huijbregts T., van Swaaij N., Jansen R. (2009): Impact of different environments in Europe on yield and quality of sugar beet genotypes. Europ J Agron. 30(1): 17-26.10.1016/j.eja.2008.06.004Search in Google Scholar

Huang S., Zeng Y., Wu J., Shi Q., Pan X. (2013): Effect of crop residue retention on rice yield in China: A meta-analysis. Field Crop Res. 154: 188-194.10.1016/j.fcr.2013.08.013Search in Google Scholar

ITB (2008): Diagnostic d’automne des betteraves maladies. La Technique Betteravière n°899 4.Search in Google Scholar

Kenter C., Hoffmann C.M., Marlander B. (2006): Effects of weather variables on sugar beet yield development (Beta vulgaris L.). European J Agron. 24(1): 62-69.10.1016/j.eja.2005.05.001Search in Google Scholar

King B.A., Tarkalson D.D. (2017): Irrigated sugarbeet sucrose content in relation to growing season climatic conditions in the northwest US. Journal of Sugar Beet Research 54(1&2): 60-74.10.5274/jsbr.54.1.60Search in Google Scholar

Linquist B.A., Liu L., van Kessel C., van Groenigen K.J. (2013): Enhanced efficiency nitrogen fertilizers for rice systems: Meta-analysis of yield and nitrogen uptake. Field Crop Res. 154: 246-254.10.1016/j.fcr.2013.08.014Search in Google Scholar

Lipsey M.W., Wilson D.B. (2001): Practical meta-analysis. SAGE publications, Inc.Search in Google Scholar

Mack G., Hoffmann C.M. (2006): Organ-specific adaptation to low precipitation in solute concentration of sugar beet. Europ J Agron. 25: 270–279.10.1016/j.eja.2006.06.004Search in Google Scholar

Owen F.V. (1945): Cytoplasmically inherited male-sterility in sugar beets. J Agr Res. 71: 423-440.Search in Google Scholar

Research Performance Report of SBSI. (2018): Technical reports, Sugar Beet Seed Institute publication, Karaj, Alborz, pp. 13-17.Search in Google Scholar

Rosenberg M.S., Garrett K.A., Su Z., Bowden R.L. (2004): Metaanalysis in plant pathology: synthesizing research results. Phytopathology 94: 1013–1017.10.1094/PHYTO.2004.94.9.1013Search in Google Scholar

Soltani E., Soltani A. (2015): Meta-analysis of seed priming effects on seed germination, seedling emergence and crop yield: Iranian studies. Int J Plant Prod. 9(3): 413-432.Search in Google Scholar

Taleghani D., Moharammzadeh M., Gohari J., Kashani A., Tohidloo Q., Chegini M.A. (2000): Study of correlation between reduction of sugar content and leaf re-growth of sugar beet in Moghan region. Sugar Beet 16(2): 13-30.Search in Google Scholar

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