The response of pea (Pisum sativum) genotypes to ascochyta blight disease and the effect of disease severity on yield components were evaluated in a 4-year trial under field conditions. Peas were inoculated with Ascochyta pinodes, the anamorph of Mycosphaerella pinodes, or with Phoma pinodella separately and with a mixture of both species. Mean infection ratings of all inoculation treatments we...

Effects of climate change on productivity of agricultural crops in relation to diseases that attack them are difficult to predict because they are complex and nonlinear. To investigate these crop-disease-climate interactions, UKCIP02 scenarios predicting UK temperature and rainfall under high- and low-CO(2) emission scenarios for the 2020s and 2050s were combined with a crop-simulation model pr...

We consider learning a causal ordering of variables in a linear non-Gaussian acyclic model called LiNGAM. Several existing methods have been shown to consistently estimate a causal ordering assuming that all the model assumptions are correct. But, the estimation results could be distorted if some assumptions actually are violated. In this paper, we propose a new algorithm for learning causal or...

We generalize Shimizu et al’s (2006) ICA-based approach for discovering linear non-Gaussian acyclic (LiNGAM) Structural Equation Models (SEMs) from causally sufficient, continuous-valued observational data. By relaxing the assumption that the generating SEM’s graph is acyclic, we solve the more general problem of linear non-Gaussian (LiNG) SEM discovery. LiNG discovery algorithms output the dis...

Blackleg, also known as Phoma stem canker, caused by Leptosphaeria maculans (Phoma lingam), is one of the most serious diseases of canola worldwide. In this study, the mean disease severity (Ds) and incidence (Di) of canola cv. Westar plants infected at the cotyledon, three-leaf, and six-leaf stages by pycnidiospores of L. maculans were monitored in the greenhouse after infection of the plants ...

A linear non-Gaussian structural equation model called LiNGAM is an identifiable model for exploratory causal analysis. Previous methods estimate a causal ordering of variables and their connection strengths based on a single dataset. However, in many application domains, data are obtained under different conditions, that is, multiple datasets are obtained rather than a single dataset. In this ...

Causal discovery is the task of finding plausible causal relationships from statistical data. Such methods rely on various assumptions about the data generating process to identify it from uncontrolled observations. We have recently proposed a causal discovery method based on independent component analysis (ICA) called LiNGAM, showing how to completely identify the data generating process under...

The fungal pathogen Phoma clematidina is used as a biological agent to control the invasive plant species Clematis vitalba in New Zealand. Research conducted on P. clematidina as a potential biocontrol agent against C. vitalba, led to the discovery of two perithecial-forming strains. To assess the diversity of P. clematidina and to clarify the teleomorph-anamorph relationship, phylogenetic anal...