The use of genotype main effect (G) plus genotype‐by‐environment (GE) interaction (G+GE) biplot analysis by plant breeders and other agricultural researchers has increased dramatically during the past 5 yr for analyzing multi‐environment trial (MET) data. Recently, however, its legitimacy was questioned by a proponent of Additive Main Effect and Multiplicative Interaction (AMMI) analysis. The objectives of this review are: (i) to compare GGE biplot analysis and AMMI analysis on three aspects of genotype‐by‐environment data (GED) analysis, namely mega‐environment analysis, genotype evaluation, and test‐environment evaluation; (ii) to discuss whether G and GE should be combined or separated in these three aspects of GED analysis; and (iii) to discuss the role and importance of model diagnosis in biplot analysis of GED. Our main conclusions are: (i) both GGE biplot analysis and AMMI analysis combine rather than separate G and GE in mega‐environment analysis and genotype evaluation, (ii) the GGE biplot is superior to the AMMI1 graph in mega‐environment analysis and genotype evaluation because it explains more G+GE and has the inner‐product property of the biplot, (iii) the discriminating power vs. representativeness view of the GGE biplot is effective in evaluating test environments, which is not possible in AMMI analysis, and (iv) model diagnosis for each dataset is useful, but accuracy gain from model diagnosis should not be overstated.

With the development of genetic maps and the identification of the most-likely positions of quantitative trait loci (QTLs) on these maps, molecular markers for lodging resistance can be identified. Consequently, marker-assisted selection (MAS) has the potential to improve the efficiency of selection for lodging resistance in a breeding program. This study was conducted to identify genetic loci associated with lodging resistance, plant height and reaction to mycosphaerella blight in pea. A population consisting of 88 recombinant inbred lines (RILs) was developed from a cross between Carneval and MP1401. The RILs were evaluated in 11 environments across the provinces of Manitoba, Saskatchewan and Alberta, Canada in 1998, 1999 and 2000. One hundred and ninety two amplified fragment length polymorphism (AFLP) markers, 13 random amplified polymorphic DNA (RAPD) markers and one sequence tagged site (STS) marker were assigned to ten linkage groups (LGs) that covered 1,274 centi Morgans (cM) of the pea genome. Six of these LGs were aligned with the previous pea map. Two QTLs were identified for lodging resistance that collectively explained 58% of the total phenotypic variation in the mean environment. Three QTLs were identified each for plant height and resistance to mycosphaerella blight, which accounted for 65% and 36% of the total phenotypic variation, respectively, in the mean environment. These QTLs were relatively consistent across environments. The AFLP marker that was associated with the major locus for lodging resistance was converted into the sequence-characterized amplified-region (SCAR) marker. The presence or absence of the SCAR marker corresponded well with the lodging reaction of 50 commercial pea varieties.

Hard white wheat (Triticum aestivum L.) is a value-added product because of its processing advantages over red wheat; however, white wheat tends to be more susceptible to pre-harvest sprouting (PHS). To identify quantitative trait loci (QTLs) associated with PHS tolerance, we developed a doubled haploid (DH) mapping population from the cross AC Domain (red seeded) 9 White-RL4137 (white seeded). A genetic map was constructed using microsatellite markers located on chromosome groups 3, 4, 5 and 6. A population of 174 DH lines was characterized for important aspects of PHS including sprouting index, germination index, Hagberg falling number and seed coat colour. A total of 11 QTLs were identified on group 3 chromosomes and on chromosome 5D. Seven QTLs associated with the PHS traits were found to be co-incident with seed coat colour on chromosomes 3A, 3B and 3D. The 5D PHS QTL was notable because it is independent of seed coat colour.

Cereal Chem. 76(4):582-586Data on the quality of durum wheat genotypes grown under eight environments (site-year combinations) were evaluated to determine the relative effects of genotype and environment on quality characteristics associated with gluten strength, protein content, and pasta texture. The 10 durum wheat genotypes assessed in this study represented a range of gluten strength types from the very strong U.S. desert durum genotype, Durex, to the medium strength Canadian genotype, Plenty. Considerable genetic variability was detected for all quality characteristics studied. Genotype-environment interaction was significant for all quality parameters evaluated, with the exception of mixograph development time. Genotypeenvironment interaction was most important in determining protein content and least important in determining gluten index, gluten viscoelasticity, and SDS sedimentation volume. The nature of the genotype-environment interaction was evaluated by determining the number of significant crossover (rank change) interactions. There was at least one significant crossover interaction between pairs of genotypes and environments for five of eight quality traits tested. Of 45 genotype pairs, eight and six showed significant crossover interactions for protein content and pasta disk viscoelasticity, respectively. Significant crossover interactions were at least partially due to the differential response of Canadian genotypes as compared with U.S. genotypes. With the exception of protein content and pasta disk viscoelasticity, our results suggest that among the selected sample of 10 genotypes, genotype-environment interactions were minor and due primarily to changes in magnitude rather than changes in rank.

. 2007. Yield and quality of canola seed as affected by stage of maturity at swathing. Can. J. Plant Sci. 87: 13-26. Swathing is an important canola (Brassica napus L.) harvest operation in western Canada. The determination of the optimum timing for this operation is worth considering, as premature swathing may lead to reduced seed yield and quality. Seed yield and quality of three canola cultivars (44A89, AC Excel and Ebony), as affected by two seeding dates and several harvest times (six or eight swathing times and one direct combined treatment) was investigated on a Black Chernozem silty loam soil at Melfort, Saskatchewan, Canada, during 1998, 2000and 2001. Seed yield, weight, protein content (oil-free meal basis) and oil content generally increased with seed development and swathing time. Early seeding was more conducive to achieving higher seed yield, especially in good growing conditions, and resulted in heavier mature seeds with higher oil content. Seed oil composition also changed during seed development. The proportion of oleic (C18:1) and linolenic (C18:3) acids increased, while that of myristic (C14:0), palmitic (C16:0), palmitoleic (C16:1), stearic (C18:0), linoleic (C18:2) and arachidic (C20:0) acids decreased. The levels of the long chain fatty acids eicosenoic (C20:1) and erucic (C22:1) acids were unaffected. However, the overall amount of fatty acids synthesized (mg 100 seeds -1 ) increased as seeds matured. Swathing was advantageous over direct combining in preventing weather-induced shattering. . En général, le rendement grainier, le poids, la teneur en protéines (tourteau délipidé) et celle en huile s'améliorent avec le degré de maturité de la graine et le moment où a lieu l'andainage. Des semis hâtifs favorisent un meilleur rendement grainier, surtout quand les conditions de croissance sont propices à cette culture, et donnent des graines plus lourdes et plus riches en huile à maturité. La composition de l'huile évolue également avec le développement de la graine. Ainsi, la proportion des acides oléique (C18:1) et linolénique (C18:3) augmente tandis que celle des acides myristique (C14:0), palmitique (C16:0), palmitoléique (C16:1), stéarique (C18:0), linoléique (C18:2) et arachidique (C20:0) diminue. La concentration des acides gras à chaîne longue comme les acides éicosénoïques (C20:1) et érucique (C22:1) n'est cependant pas affectée. La quantité globale d'acides gras synthétisés (mg par centaine de semences) augmente néanmoins avec la maturité des graines. L'andainage s'avère plus utile que la récolte directe pour prévenir l'égrenage prématuré attribuable aux intempéries.