Genotype selection based on multiple traits is a key issue in plant breeding; it has been dependent on setting a subjective weight for each trait in index selection and a subjective truncation point for each trait in independent culling, and the weights and truncation points can be highly subjective. In this paper we proposed and demonstrated a novel approach for genotype selection based on multiple traits, the genotype by yield*trait (GYT) biplot, where “trait” can be any breeding objective other than yield; it may be an agronomic trait, a grain quality, processing quality, or nutritional quality trait, or a disease resistance. The GYT biplot ranks genotypes based on their levels in combining yield with other target traits and at the same time shows their trait profiles, i.e., their strengths and weaknesses. Compared to existing methods, this approach is graphical, objective, effective, and straightforward. Underlying the GYT biplot approach is the paradigm shift that genotypes should be evaluated by their levels in combining yield with other traits as opposed to by their levels in individual traits. An oat dataset from multi-year multi-locations trials was used to demonstrate the GYT biplot approach.

Selected primitive and modern wheat species were evaluated on the basis of their carotenoid composition and effects of the genotype and environment on lutein using spectrometry and liquid chromatography. Carotenoids in the wheat extracts were identified and confirmed on the basis of their UV/vis and mass spectra compared with those of authentic standards. The protonated molecule (M + 1)+ at m/z 569 was the predominant ion for zeaxanthin compared to the fragment ion at m/z 551 for lutein. A similar carotenoid profile was obtained for the wheat species investigated, but significant differences were observed in the concentration of carotenoids. Einkorn (Triticum monococcum) exhibited the highest level of all-trans-lutein, averaging 7.41 microg/g with small amounts of all-trans-zeaxanthin, cis-lutein isomers, and beta-carotene. Durum, Kamut, and Khorasan (Triticum turgidum) had intermediate levels of lutein (5.41-5.77 microg/g), while common bread or pastry wheat (Triticum aestivum) had the lowest content (2.01-2.11 microg/g). Lutein in einkorn appeared to be influenced significantly by environmental growing conditions.

Breeding line selection, either for potential varieties or for useful parents, must be based on multiple breeding objectives (or traits). Varieties cannot have any major defects, while parents must have outstanding levels in at least one trait. Due to undesirable associations among breeding objectives, it is difficult to accomplish both tasks (variety selection and parent selection) through a single selection strategy. Additional complication results when a program is breeding for different end‐uses such that both high and low levels of a trait are desirable. The first purpose of this paper was to propose a comprehensive multitrait selection procedure that coherently combines independent selection, independent culling, and index selection so that all the aspects in breeding line selection are taken into consideration. A dataset of 150 oat (Avena sativa L.) breeding lines with values evaluated for four quality traits (groat, oil, protein, and beta‐glucan concentrations) was used for illustration. A genotype by trait biplot is a useful tool for exploring multiple trait data and can aid in multitrait selection because it graphically displays the trait associations across, and the trait profiles of, the genotypes. Procedures are outlined to avoid possible misinterpretation of such a biplot when the biplot does not fully display the patterns.

The success of a plant breeding program depends on many factors; one crucial factor is the selection of suitable breeding and testing locations. A test location must be discriminating so that genetic differences among genotypes can be easily observed, it must be representative of the target environments so that selected genotypes have the desired adaptation, and its representation of the target environment should also be repeatable so that genotypes selected in 1 yr will have superior performance in future years. Using the yield data of 2006 through 2010 Quebec Oat Registration and Recommendation Trials as an example, we presented a method to visualize the representativeness and repeatability of test locations based on a genotype main effect plus genotype × environment interaction (GGE) biplot. The repeatability of a test location could also be quantified by mean genetic correlations between years within the location. Based on representativeness and repeatability, four categories of test locations were classified and their usefulness in plant breeding discussed.

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The oat (Avena sativa L.) breeding program at the Eastern Cereal and Oilseed Research Centre of Agriculture & Agri‐Food Canada has the responsibility to breed new oat cultivars for producers in eastern Canada, which includes Ontario, Quebec, and the Atlantic provinces. A 3‐yr multilocation test was conducted to understand the genotype × location interaction patterns and the relationships among test locations in eastern Canada. A genotype + genotype × environment interaction biplot analysis of yield data revealed three distinct oat mega‐environments in eastern Canada: (i) northern Ontario, (ii) southern and eastern Ontario, and (iii) Quebec and Atlantic Canada. To breed for all mega‐environments, initial yield screening must be conducted at locations representing each of these mega‐environments. Based on the relationships among test locations, six essential test locations were identified: three in Ontario, two in Quebec, and one in Atlantic Canada. Testing at all six locations appeared to provide a good coverage of the whole oat‐growing area in eastern Canada. Based on these findings, a breeding and test strategy was developed. This includes conducting initial yield screening at three locations in Ontario, Quebec, and Atlantic Canada, followed by a formal yield test at all six essential test locations. Specifically adapted genotypes selected from this test will then be tested in the Registration Tests in their respectively adapted subregions.

Soybean [Glycine max (L.) Merr.] seeds contain a high concentration of the isoflavones daidzein and genistein, which are considered to be compounds beneficial to human health. Our objective was to determine the influence of breeding and selection for yield on the isoflavone concentration of short‐season cultivars. A collection of 14 historical cultivars released from 1934 to 1992 was grown at Ottawa for 12 yr under identical cultural conditions. Seed samples, taken at harvest, were examined using near‐infrared reflectance in conjunction with traditional chemical methods to measure the concentration of daidzein, genistein, and total isoflavones (TIF). A linear regression equation developed based on the changes across time of cultivar release was used to determine the improvement rates for various soybean parameters. Across the 58 yr of breeding history, yield and oil concentration increased by 0.43 and 0.24% per year, respectively, while protein concentration decreased by 0.15% per year. Across the same time period daidzein, genistein, and TIF increased by 1.04, 1.47, and 0.98% per year, respectively. Moderate broad sense heritabilities of 43, 45, and 44% were calculated for the aforementioned isoflavones. Genotype main effects + genotype × environment interaction biplots revealed that recent cultivars with high isoflavone concentration were more prone to environmental influence than older cultivars. In the short‐season region, plant breeders should be aware that selecting for higher yield may indirectly select for higher isoflavone concentration.

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