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Open access

Bogna Zawieja, Sylwia Lewandowska, Tomasz Mikulski and Wiesław Pilarczyk

Summary

An analysis is made of results from early stages of testing of promising hybrids. The data consist of single-replicate trials performed by Norddeutsche Pflanzenzucht in 6 locations (5 in Poland and one in Germany). In total 165 hybrids were tested with 3 standard varieties. The subject of the analysis was the seed yield. Three measures of stability were used. The yield of tested hybrids is expressed as percentage of that of standard varieties. Wricke’s ecovalence expressed as a contribution to G x E interaction was used as a measure of stability. Additional characterization of the tested hybrids was performed by regressing hybrid yield on the mean yields of the experiment, as described by Finlay and Wilkinson and by Eberhart and Russel. The methods applied enabled selection of the most promising hybrids for further yield testing.

Open access

Moawia Alghalith

Summary

We develop a simple method that completely eliminates the specification error and spurious relationships in regression. Furthermore, we introduce a stronger test of causality. We apply our method to oil prices.

Open access

Iwona Mejza, Katarzyna Ambroży-Deręgowska, Jan Bocianowski, Józef Błażewicz, Marek Liszewski, Kamila Nowosad and Dariusz Zalewski

Summary

The main purpose of this study was the model fitting of data deriving from a three-year experiment with barley malt. Two linear models were considered: a fixed linear model with fixed effects of years and other factors, and a mixed linear model with random effects of years and fixed effects of other factors. Two cultivars of brewing barley, Sebastian and Mauritia, six methods of nitrogen fertilization and four germination times were analyzed. Three quantitative traits were observed: practical extractivity of the malt, malting productivity, and a quality coefficient Q. The starting point for the statistical analyses was the available experimental material, which consisted of barley grain samples destined for malting. The analyses were performed over a series of years with respect to fixed or random effects of years. Due to the strong differentiation of the years of the study and some significant interactions of factors with years, annual analyses were also carried out.

Open access

Kiyotaka Iki, Hiroshi Nakano and Sadao Tomizawa

Summary

For square contingency tables with ordered categories, Iki, Tahata and Tomizawa (2012) considered a measure to represent the degree of departure from marginal homogeneity. However, the maximum value of this measure cannot distinguish two kinds of marginal inhomogeneity. The present paper proposes a measure which can distinguish two kinds of marginal inhomogeneity. In particular, the proposed measure is useful for representing the degree of departure from marginal homogeneity when the marginal cumulative logistic model holds.

Open access

M. Iwańska, A. Oleksy, M. Dacko, B. Skowera, T. Oleksiak and E. Wójcik-Gront

Summary

Wheat is one of the modern world’s staple food sources. Its production requires good environmental conditions, which are not always available. However, agricultural practices may mitigate the effects of unfavorable weather or poor-quality soils. The influence of environmental and crop management variables on yield can be evaluated only based on representative long-term data collected on farms through well-prepared surveys.The authors of this work analyzed variation in winter wheat yield among 3868 fields in western and eastern Poland for 12 years, as dependent on both soil/weather and crop management factors, using the classification and regression tree (CART) method. The most important crop management deficiencies which may cause low wheat yields are insufficient use of fungicides, phosphorus deficiency, non-optimal date of sowing, poor quality of seeds, failure to apply herbicides, lack of crop rotation, and use of cultivars of unknown origin not suitable for the region. Environmental variables of great importance for the obtaining of high yields include large farm size (10 ha or larger) and good-quality soils with stable pH. This study makes it possible to propose strategies supporting more effective winter wheat production based on the identification of characteristics that are crucial for wheat cultivation in a given region.

Open access

Paulo C. Rodrigues

Summary

Genotype-by-environment interaction (GEI) is frequently encountered in multi-environment trials, and represents differential responses of genotypes across environments. With the development of molecular markers and mapping techniques, researchers can go one step further and analyse the whole genome to detect specific locations of genes which influence a quantitative trait such as yield. Such a location is called a quantitative trait locus (QTL), and when these QTLs have different expression across environments we talk about QTL-by-environment interaction (QEI), which is the basis of GEI. Good understanding of these interactions enables researchers to select better genotypes across different environmental conditions, and consequently to improve crops in developed and developing countries. In this paper we present an overview of statistical methods and models commonly used to detect and to understand GEI and QEI, ranging from the simple joint regression model to complex eco-physiological genotype-to-phenotype simulation models.

Open access

Tadeusz Caliński and Idzi Siatkowski

Summary

The main estimation and hypothesis testing procedures are presented for experiments conducted in nested block designs of a certain type. It is shown that, under appropriate randomization, these experiments have the convenient orthogonal block structure. Due to this property, the analysis of experimental data can be performed in a comparatively simple way. Certain simplifying procedures are indicated. The main advantage of the presented methodology concerns the analysis of variance and related hypothesis testing procedures. Under the adopted approach one can perform these analytical methods directly, not by combining the results from analyses based on stratum submodels. The application of the presented theory is illustrated by three examples of real experiments in relevant nested block designs. The present paper is the second in the planned series concerning the analysis of experiments with orthogonal block structure.

Open access

Alessandro Magrini

Summary

Linear regression with temporally delayed covariates (distributed-lag linear regression) is a standard approach to lag exposure assessment, but it is limited to a single biomarker of interest and cannot provide insights on the relationships holding among the pathogen exposures, thus precluding the assessment of causal effects in a general context. In this paper, to overcome these limitations, distributed-lag linear regression is applied to Markovian structural causal models. Dynamic causal effects are defined as a function of regression coefficients at different time lags. The proposed methodology is illustrated using a simple lag exposure assessment problem.

Open access

Ewa Skotarczak, Anita Dobek and Krzysztof Moliński

Summary

Data arranged in a two-way contingency table can be obtained as a result of many experiments in the life sciences. In some cases the categorized trait is in fact conditioned by an unobservable continuous variable, called liability. It may be interesting to know the relationship between the Pearson correlation coefficient of these two continuous variables and the entropy function measuring the corresponding relation for categorized data. After many simulation trials, a linear regression was estimated between the Pearson correlation coefficient and the normalized mutual information (both on a logarithmic scale). It was observed that the regression coefficients obtained do not depend either on the number of observations classified on a categorical scale or on the continuous random distribution used for the latent variable, but they are influenced by the number of columns in the contingency table. In this paper a known measure of dependency for such data, based on the entropy concept, is applied.

Open access

Anna Budka

Summary

The consequences of the growing demand for water include a significant deterioration in its quality and a drastic decline in biodiversity, which is a serious threat to the hydrological and biocenotic balance of freshwater ecosystems. A good indicator of aquatic environment quality is macrophytes. Studies on macrophytes are one of the primary elements in the ecological status assessment of surface waters, in accordance with the guidelines of the Water Framework Directive. In Poland, research on the ecological status of rivers with regard to macrophytes has been carried out since 2008, using the Macrophyte Index for Rivers (MIR), which takes into account the number and coverage of macrophyte taxa. An analysis of numbers of species that need to be indicated at a site for valid assessment of the ecosystem was conducted on the basis of studies on macrophytes from 2008–2013, at 60 sites in small lowland rivers with a sandy substrate, of which 20 sites were selected on the most diverse watercourses: the least clean (quality class V), moderate (quality class III), and the cleanest (quality class I). The results of the botanical studies served to assess the completeness of the samples (the number of species recorded at a site) used to evaluate the ecological status of a river. The proposed analyses enabled estimation of the approximate number of species required to determine the MIR for rivers in each quality class.