2009
DOI: 10.1016/j.eja.2008.06.004
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Impact of different environments in Europe on yield and quality of sugar beet genotypes

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Cited by 104 publications
(79 citation statements)
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“…This increased production in roots can be due either to the increased beet cycle length (226 vs 201 days), and to a more favourable weather, with particular regard to the rain (467 vs 157 mm). The highest yield recorded under fresh water was similar to the production levels reported in literature (Pidgeon et al, 2001;Hoffmann, et al, 2009;Shrestha et al, 2010) in different European sites. However literature does not report results regarding the effect of wastewaters on the sugar beet root yield.…”
Section: Resultssupporting
confidence: 74%
“…This increased production in roots can be due either to the increased beet cycle length (226 vs 201 days), and to a more favourable weather, with particular regard to the rain (467 vs 157 mm). The highest yield recorded under fresh water was similar to the production levels reported in literature (Pidgeon et al, 2001;Hoffmann, et al, 2009;Shrestha et al, 2010) in different European sites. However literature does not report results regarding the effect of wastewaters on the sugar beet root yield.…”
Section: Resultssupporting
confidence: 74%
“…However, by resisting the temptation to conduct trials only under optimum conditions, and with judicious site selection in combination with advanced statistical tools, breeders can obtain additional useful information on genotype performance using data from multilocation trials that span the range of environments likely to be encountered in practice (Pidgeon et al 2006). In another study examining nine varieties under more mild conditions, genotype x environment interactions, though significant, were small (Hoffmann et al 2009). …”
Section: Present Situationmentioning
confidence: 93%
“…If a genotype has the same direction as a certain environment in the bivariate plot, it is considered to be specially suited for that environment. 20) To explore the effect of geographic-climate factors on bioactive components traits, five bioactive components and nine geographic-climate factors in two years were analyzed by stepwise regression analysis (SRA) with SPSS 16.0. Geographic-climate factors were independent variables (i.e., X 1 , sunshine duration; X 2 , mean annual temperature; X 3 , mean temperature in July; X 4 , min.…”
Section: Analysis Of Bioactive Componentsmentioning
confidence: 99%