Wiesław Mądry

Evaluation of cucumber (Cucumis sativus) cultivars grown in Eastern Europe and progress in breeding for resistance to angular leaf spot (Pseudomonas syringae pv. lachrymans)

Increased occurrence of cucumber angular leaf spot, Pseudomonas syringae pv. lachrymans, has caused significant losses in cucumber, Cucumis sativus, yield in Poland in recent years. These losses necessitated evaluation of the level of resistance in cucumber cultivars of mainly Polish breeding, cultivated in Eastern Europe, and initiation of a breeding programme for resistance to this disease. Screening for resistance was performed on 84 cucumber accessions under growth chamber conditions using a highly aggressive strain of P. syringae pv. lachrymans. Most of the screened accessions were either susceptible or displayed intermediate resistance. The screening resulted in the identification of five F1 hybrid cultivars moderately resistant to angular leaf spot. The identified F1 hybrids were self-pollinated up to the F4 generation. Individuals resistant to angular leaf spot were identified. These individuals can be used as a source of resistance to angular leaf spot in future breeding efforts.

Note on Yield Component Analysis

A discussion on yield component analysis is presented in the paper. The discussion regards such issues as inappropriateness of a linear model in application to yield component analysis, correct measurement of yield and its components, sequential and nonsequential development of the components, and a choice of a statistical analysis method to provide a view on a relationship between yield and its components.

Scheffé-Caliński and Shukla Models

SUMMARY In this paper, we compared the theoretical aspects and applications of two-way mixed models, viz., Scheffé-Calinskis (S-C) model and Shuklas (Sh) model. Both models were considered in their basic form and as multiplicative, joint regression models. Despite the different observed covariance matrices in pairs of both basic and regression models, they adequately described performance (stability) of genotypes in randomly chosen environments. The statistical tools (estimators and tests) developed in the respective models (both basic and joint regression) are optimal or have desirable properties. The models may be regarded as pairs of alternative, realistic, and of similar statistical and practical efficiency, approaches to analyzing genotype means (across environments) and phenotypic stability of two-way data.

Ontogenetic-based sequential path analysis of grain yield and its related traits in several winter wheat cultivars

Studies that provide representative insights for determining yield through its related traits during the ontogeny of modern cultivars subjected to sources of environmental variation are limited for different crops, including wheat. Most of the empirical evidence on the relationships between the yield of small grain cereal crops and its contributing traits has been obtained under dry or semidry conditions. The aims of this paper were to (1) illustrate how an path analysis can be used to clarify and interpret the relationships between grain yield (GY), yield components, and other yield-related traits of 25 winter wheat cultivars subjected to sources of environmental variation and (2) determine how the yield-related traits contribute to the yield variation. The data used in this analysis were generated from multi-environment trials across wheat-growing areas in Poland. Using Ward’s clustering procedure was capable of identifying the most critical predictor traits of the yield components and their contributions to cultivar-focused GY variation. Our findings document, confirm, and improve the basic biological understanding of how to grow modern wheat cultivars for high GY through effectively stimulating the improvement of yield-related traits through the optimization of developmental stage-based agronomic strategies. Our results confirmed empirically that modern European wheat cultivars grown in a temperate climate require favorable conditions, the use of appropriate N fertilizer and growth regulators, and the application of fungicide to protect against leaf diseases and to provide conditions that effectively increase the time to anthesis, the Leaf Area Index per spike at anthesis, and the grain filling duration, and reduce plant height and flag leaf disease severity, thus leading to a high GY. A high yield level is obtained by the performance of preferred yield-related traits that can maintain the three yield components at relatively high levels.

Multivariate assessment of cultivars' biodiversity among the Polish strawberry core collection.

Sieczko L., Masny A., Pruski K., Żurawicz E., Mądry W . (2015): Multivariate assessment of cultivars’ biodi versity among the Polish strawberry core collection . Hort. Sci. (Prague), 42: 83–93. The diversity of parental genotypes has a major impact on the progress of plant breeding. This study assessed phenotypic biodiversity of 91 strawberry genotypes in the core collection of the Research Institute of Horticulture in Skierniewice, Poland, using multivariate statistical methods. The assessment was carried out from 2008 through 2010 for 13 traits describing plant growth vigour, flowering and fruit ripening times, fruit yield, fruit appearance and quality (position of the calyx in relation to the surface of the fruit, fruit size and firmness, skin and flesh colour, fruit glossiness, intensity of the fruit’s aroma and sweetness), as well as the genotypes’ capacity for repeat-fruiting during the summer-autumn period. A principal component analysis using a hierarchical cluster analysis reduced the number of dimensions of more than a dozen traits describing the diversity of the assessed cultivars and identified six homogeneous groups, each consisting of cultivars with similar traits; this will simplify mate selection in the hybridization program and may reduce the size of the core collection.

A comparison of winter wheat cultivar rankings in groups of Polish locations

The grouping of locations from local-scale multi-environmental trials (METs) into mega-environments has been criticized. Some European countries, e.g. the Czech Republic, Poland and Germany, have been characterized as possessing homogeneous environmental conditions. For aligned environmental conditions, it has been assumed that cultivar rankings will be similar and consequently cannot be used to designate mega-environments. An example of METs at the local scale is the Polish Post Registration Variety Testing System. The objective of this study was to determine groups of test sites within 16 Polish regions which are characterized by similar yield ranking of 50 winter wheat cultivars over three growing seasons (2011–2013). The compatibility of these cultivar yield rankings across regions was evaluated using Pearson correlation coefficients. Thereby, the 16 regions were divided into six groups (mega-environments) of locations. Regions within each group have similar cultivar rankings, whereas between groups, we observed different cultivar rankings, indicating crossover interactions. Besides similar cultivar yield responses the regions within mega-environments were characterized also by similar environmental (soil and/or climate) conditions.

Response of winter wheat cultivars to crop management and environment in post-registration trials

Mądry W., Derejko A., Studnicki M., Paderewski J., Gacek E. (2017): Response of winter wheat cultivars to crop management and environment in post-registration trials. Czech J. Genet. Plant Breed., 53: 76−82. In order to deliver essential information related to flexible cultivar recommendations, the cultivars which have been released have to be evaluated under different crop management treatments across agro-ecosystems using two-factorial post-registration multi-environment trials. The objective of this study was to evaluate the yield adaptive patterns of 24 winter wheat cultivars tested across 20 trial locations and three consecutive cropping seasons. The evaluated winter wheat cultivars from many Western European countries and Poland showed different adaptive responses to the Polish agro-ecosystems under each of the crop management intensities. Under the high-input management, the cultivars Rapsodia, (UK) Bogatka and Nadobna (Poland) showed a wide adaptation. The cultivars Alcazar (France), Anthus (Germany), Batuta (Poland) and Boomer (UK) were the best adapted to lower-productive environments and poorly adapted to highly productive conditions under both management treatments.

Four-way data analysis within the linear mixed modelling framework

Cultivars have to be evaluated under different crop management systems across agro-ecosystems and years using multi-environment trials (MET) before releasing them to the market. Frequently, data collected in METs are arranged according to cultivar (G), management (M), location, (L) and year (Y) combinations in a four-way G x M x L x Y data table that is highly unbalanced for cultivars across locations and time. Therefore, we present the restricted maximum likelihood method (REML) for linear mixed models (LMM) with a factor analytic variance-covariance matrix for assessing cultivar adaptation to crop management systems and environments based on unbalanced datasets. Such a multi-environmental trial system has been in operation in Poland for winter wheat (Triticum aestivum L.) in the form of the Post-registration Variety Testing System (PVTS). This study aimed to illustrate the use of LMM in the analysis of unbalanced four-way G x M x L x Y data. LMM analysis provided adjusted means of grain yield for 51 winter wheat cultivars bred in different regions in Europe, tested across 18 trial locations and seven consecutive cropping seasons in two crop management intensities. The application of the four-way LMM with a factor analytic variance-covariance matrix is a complementary and effective tool for evaluating the unbalanced G x M x L x Y table. Cultivars tested had different adaptive responses to the Polish agro-ecosystems separately for each of the crop management intensities. Wide adaptation in both crop management systems was exhibited by cultivars Mulan and Jenga bred in Germany.

Measures of Genotype Wide Adaptation Level and their Relationships in Winter Wheat

Three new concepts of genotype wide adaptation levels I, II and III are presented and shown to the adequate describing quantitatively by measures such as superiority measure, Pi, Eskridge’s yield reliability measure, Ri and Eskridge’s yield reliability function, Ri(d). These indices have been called quantitative measures of genotype wide adaptation levels I, II and III, respectively. Relationships (consistency) between the three measures were studied using data for grain yield of winter wheat advanced lines from 15 preliminary multi-environment trials carried out across Polish test locations in the years 1993–2007. The quantitative measures are simple to interpret and useful quantitative characteristics of genotype wide adaptation levels I, II and III. High Spearman rank correlation coefficients were found between each of the pairs of the quantitative measures of genotype wide adaptation levels I, II and III within all sets of winter wheat genotypes. Then, for evaluating wheat genotype wide adaptation level in each aspect only one of the considered measures could be sufficient. The studies delivered new results on the usefulness of quantitative measures of genotype wide adaptation level for winter wheat. These findings indicate that those measures could be also useful for comparative evaluation of genotype wide adaptation level in other crops.

Yielding of old and modern Polish wheat cultivars under different nitrogen inputs as assessed by combined using AMMI and cluster analyses

Yielding of old and modern Polish wheat cultivars under different nitrogen inputs as assessed by combined using AMMI and cluster analyses The experimental material consisted of 15 winter wheat cultivars (14 Polish-bred cultivars and one British cultivar) representing the results of over 100 years of breeding. The cultivars were tested in two-factor field experiments (cultivars were one factor and nitrogen fertilization rates, the other factor) carried out in split-plot design across two consecutive years. This paper demonstrates a combined using AMMI and cluster analyses for effective and efficient estimate of grain-yield response to investigated environments (combinations of 2 years x 3 nitrogen fertilization rates). First, homogenous groups of cultivars were identified in terms of their genotypic profile of AMMI(s) estimates of GEI effects using Wards method of cluster analysis. Then, these groups were divided into separate homogenous subgroups with respect to genotype means. The cultivars in each subgroup have a similar grain yield response to the environments and, then, similar adaptation pattern, although the genotype groups differed in adaptation to these environments.