Bivariate models for the analysis of internal nitrogen use efficiency: mixture models as an exploratory tool.
Files
Date
2014
Authors
Munoz Santa, Isabel
Editors
Advisors
Kravchuck, Olena
Marschner, Petra
Marschner, Petra
Journal Title
Journal ISSN
Volume Title
Type:
Thesis
Citation
Statement of Responsibility
Conference Name
Abstract
Ratios are commonly used among plant and soil scientists, in particular to express the plant nutrient utilisation efficiency of macro- and micro-nutrients. The internal nutrient efficiency can be understood in terms of maximising yield per a unit of nutrient in the plant. At present, IEɴ data are usually collected from designed field trials where different treatments are applied (e.g. fertiliser treatments) and analysed by univariate linear mixed models. However, univariate linear models on the ratio do not maintain information on the original traits, including their correlation, which presents a challenge when interpreting the effect of agronomic practices or environmental conditions on the process of nutrient conversion into grain. Moreover, the distributional properties of ratios do not comply with the assumptions of these linear models favoured in the area of soil and plant science research. A more suitable approach is to collect the traits of interest and to use bivariate analyses. These analyses preserve the information on the original traits and avoid issues associated with the ratio distributional properties. If the data comes from field studies, different experimental and environmental conditions may lead to the presence of patterns (groups) in the data in addition or concurrently with designed treatments. Researchers in plant and soil sciences may be interested in identifying those conditions, for example to understand the nature of genotype-by-environment interactions. The inspection of the groups may reveal the factors defining them, thus gaining insight into the experimental or environmental drivers of the biological traits. Among bivariate analyses, bivariate mixture models of Gaussian distributions are an appropriate methodology for identifying clusters in the nutrient efficiency data, assuming that the traits are jointly normal. Studying this methodology for the analysis of the internal nitrogen use efficiency traits is the focus of the present thesis. The application of bivariate mixture models is suggested here as a complementary analysis to bivariate mixed models in designed field trials and for exploratory purposes only. The exploratory and supplementary character of the mixture analysis is due to the potential violation of the independence assumption when the data are collected from designed field trials. In this project, bivariate mixed and mixture models are applied to a real-life designed field trial on non-irrigated rice in Thailand for the analysis of grain yield (GY ) and plant nitrogen uptake (NU) data. The univariate counterparts of these analyses are also applied on the ratio of these two traits (the internal nitrogen use efficiency). The advantages of the bivariate analyses are discussed in comparison to the univariate analyses on the ratio. In this case study, the bivariate mixture approach revealed that soil water availability post -flowering and N supply in soil are the potential factors defining the mixture groups. The present work can be readily extended to the analysis of other similar traits in agriculture when the objective is to explore potential environmental conditions affecting the traits under study. In order to fully exploit the proposed methodology, field survey is suggested as a more appropriate sampling procedure for the application of mixture models than collecting data from designed field trials.
School/Discipline
School of Agriculture, Food and Wine
Dissertation Note
Thesis (M.App.Sc.) -- University of Adelaide, School of Agriculture, Food and Wine, 2014
Provenance
This electronic version is made publicly available by the University of Adelaide in accordance with its open access policy for student theses. Copyright in this thesis remains with the author. This thesis may incorporate third party material which has been used by the author pursuant to Fair Dealing exceptions. If you are the owner of any included third party copyright material you wish to be removed from this electronic version, please complete the take down form located at: http://www.adelaide.edu.au/legals