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Determinants of barley grain yield in a wide range of Mediterranean environments
Authors:Enrico Francia  Alessandro Tondelli  Fulvia Rizza  Franz W Badeck  Orazio Li Destri Nicosia  Taner Akar  Stefania Grando  Adnan Al-Yassin  Abdelkader Benbelkacem  William TB Thomas  Fred van Eeuwijk  Ignacio Romagosa  A Michele Stanca  Nicola Pecchioni
Institution:1. Department of Agricultural and Food Sciences, University of Modena and Reggio Emilia, Via Amendola, 2 – Pad. Besta, I-42122 Reggio Emilia, Italy;2. CRA – Genomic Research Center, Fiorenzuola d’Arda (PC), Italy;3. PIK – Potsdam Institute for Climate Impact Research, Potsdam, Germany;4. CRA – Cereal Research Center, Foggia, Italy;5. CRIFC, Ankara, Turkey;6. ICARDA, Aleppo, Syria;g NCARE, Amman, Jordan;h ITGC, Constantine, Algeria;i SCRI, Invergowrie, Dundee, UK;j Biometrics – Applied Statistics, Wageningen University, Wageningen, The Netherlands;k Centre UdL–IRTA, Universitat de Lleida, Lleida, Spain
Abstract:Barley grain yield in rainfed Mediterranean regions can be largely influenced by terminal drought events. In this study the ecophysiological performance of the ‘Nure’ (winter) × ‘Tremois’ (spring) barley mapping population (118 Doubled Haploids, DHs) was evaluated in a multi-environment trial of eighteen site–year combinations across the Mediterranean Basin during two consecutive harvest years (2004 and 2005). Mean grain yield of sites ranged from 0.07 to 5.43 t ha−1, clearly dependent upon both the total water input (rainfall plus irrigation) and the water stress index (WSI) accumulated during the growing season. All DHs were characterized for possessing molecular marker alleles tagging four genes that regulate barley cycle, i.e. Vrn-H1, Vrn-H2, Ppd-H2 and Eam6. Grain yield differences were initially interpreted in terms of mean differences between genotypes (G), environments (E), and for each combination of genotype and environment (GE) through a “full interaction” ANOVA model. Variance components estimates clearly showed the greater importance of GE over G, although both were much lower than E. Alternative linear and bilinear models of increasing complexity were used to describe GE. A linear model fitting allelic variation at the four genes explained genotype main effect and genotype × environment interaction much better than growth habit itself. Adaptation was primarily driven by the allelic constitution at three out of the four segregating major genes, i.e. Vrn-H1, Ppd-H2 and Eam6. In fact, the three genes together explained 47.2% of G and 26.3% of GE sum of squares. Grain yield performance was more determined by the number of grains per unit area than by the grain weight (phenotypic correlation across all genotypic values: r = 0.948 and 0.559, respectively). The inter-relationships among a series of characters defining grain yield and its components were also explored as a function of the length of the different barley developmental phases, i.e. vegetative, reproductive, and grain filling stages. In most environments, the best performing (adapted) genotypes were those with faster development until early occurrence of anthesis. This confirmed the crucial role of the period defining the number of grains per unit area in grain yield determination under Mediterranean environments.
Keywords:Barley  Yield adaptation  Mediterranean environment  GE interaction  Phenology  Developmental genes
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