Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

    We have a manual that explains all the features 

Record number 364642
Title Grain Yield Variation in Malting Barley Cultivars in Uruguay and Its Consequences for the Design of a Trials Network
Author(s) Ceretta, S.S.E.; Eeuwijk, F.A. van
Source Crop Science 48 (2008). - ISSN 0011-183X - p. 167 - 180.
Department(s) Biometris (WU MAT)
Publication type Refereed Article in a scientific journal
Publication year 2008
Keyword(s) multi-environment trials - spring barley - ecophysiological analyses - high-temperature - bilinear models - short periods - wheat - genotype - selection - variety
Abstract The efficiency of cultivar trial networks is an important subject in official cultivar testing. We investigated this efficiency for malting barley (Hordeum vulgare L.) in Uruguay, using data on 213 cultivars tested across an eight-year period at six locations. The variance-components approach was used to quantify the effects of years, locations, sowing dates and replicates on the precision of cultivar mean comparisons. The relationships among testing environments and genotypic adaptation patterns were explored via biplots. Factorial regression was used to model genotype x environment interaction (GEI) directly in relation to measured environmental variables. Variance components indicated that both the number of locations and sowing dates could be reduced. Biplot analysis identified some repeatable GEI patterns. Factorial regression showed that mean daily temperature during the emergence-heading period and daily minimum temperature at heading explained 20% of GEI. Still, the majority of the GEI appeared to be highly nonrepeatable. A future network should focus on wide adaptation while enhancing the chances to exploit specific adaptation to the prevalent temperature conditions by sampling contrasting sowing dates at different locations.
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