Hydrogen-oxidizing bacteria from lentil field

Non-Peer Reviewe

Denitrifying bacterial communities vary with soil N in canola fields

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Abundance and diversity of AM fungal communities associated with agricultural factors

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Agronomic practices influence soil biodiversity with strong feedback to plant growth

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A mixture partial credit model for identifying latent classes responsible for differential item functioning

AIMS : Ideally, the item response probability to a quality of life (QoL) questionnaire should only depend on the respondents’ QoL level. If such a probability also depends on other characteristics such as ethnicity, gender or socioeconomic status, differential item functioning (DIF) may be present. Identifying DIF plays a key role in verifying measurement invariance when validating questionnaires. Moreover, being able to take into account DIF allows limiting measurement biases when analyzing patient-reported ouctomes (PRO) data. Several methodologies have been proposed for dealing with DIF, one of the most flexible and powerful being the IRT-based likelihood ratio test. With such a method, the covariate suspected to be responsible for DIF on a given item can be identified. For this purpose, nested models (with and without DIF) are compared: one constrained to be DIF-free for the suspected item, and one considering DIF by including interactions between the item parameter and the considered covariate. The best model is then chosen for analyzing data, allowing taking into account DIF if necessary. However, some problems can occur when covariates responsible for DIF are not well identified. Multiple covariates can be wrongly suspected, leading in multiple comparisons thus in type I error rate inflation. Moreover, the covariate truly responsible for DIF might not be identified because it is not a directly observed covariate but a latent variable. METHODS : We propose an adaptation of the IRT likelihood ratio test based on mixture partial credit models (PCM). With these models, items parameters are considered as fixed effects and both the latent trait to be analyzed (for example QoL) and the covariate responsible for DIF are considered as continuous and categorical latent variables, respectively. Latent classes can finally be constructed based on such categorical latent variables using individual posterior probabilities, and then described using observed data. RESULTS : We illustrate the properties of such likelihood ratio test based on mixture PCM using both simulated data and observed data from the Pays-de-la-Loire Workers Surveillance Program (France), and provide a MPlus based macro-program working under Stata for performing such a procedure. CONCLUSIONS : We believe that such program may facilitate the use of these methods by researchers.

Multiple case-study analysis of quality management practices within UK Six Sigma and non-Six Sigma manufacturing small- and medium-sized enterprises

This paper examines multiple case-study analysis of quality management practices within UK Six Sigma and non-Six Sigma manufacturing small- and medium-sized enterprises

Fungicide effects on N2-fixing bacteria and N2-fixation in chickpea

Non-Peer ReviewedFungicide application in field crops have unexpected non-target effects on the agroecosystem. Molecular methods (polymerase chain reaction – denaturing gradient gel electrophoresis and cloning technology) were used to test the effects of four fungicide application programs targeting Ascochyta blight (Ascochyta rabiei) on the N2-fixing bacterial communities associated with two chickpea cultivars, and on chickpea nodulation. Treatments were replicated four times in complete blocks in the field, in 2008 and 2009. Results showed the richness of the N2-fixing bacterial communities did not change significantly (P > 0.05, data didn’t shown) with fungicide application, but different intensities of fungicide application selected different dominant N2-fixing taxa, as revealed by Correspondence Analysis (CA) of DNA sequences. Genotypes of chickpea cultivars significantly affected both the richness and composition of the N2-fixing bacterial communities, as revealed by results of CA. Both fungicide and crop genotype affected nodulation scores of chickpea based on ANOVA results (P < 0.001 for nodulation scores test and P = 0.04 for fixed N test), reflecting impacts on nitrogen fixation. Redundancy analysis (RDA) also revealed significant relationships (P = 0.014) among fixed nitrogen, nodulation scores and identified rhizosphere N2-fixing bacteria. Based on these results, we conclude that both the foliar fungicide applications and chickpea genotype can affect the composition and function of N2-fixing bacterial community in chickpea field

Association of chickpea root with soil fungi: a comparison of cultivars

Non-Peer ReviewedField crops influence soil microbiota, impacting the health status and productivity of cropping systems. We conducted a two year field experiment using thirteen genotypes of chickpea and applied deep amplicon pyrosequencing to verify whether plant genetics control the fungal community of the root endosphere. We obtained 63796 sequences of ITS1F/ITS2 and 52129 of 18S rDNA gene clustered into 127 non-mycorrhizal and 89 mycorrhizal operational taxonomic units (OTUs), respectively. Plant genotype and year (soil and weather) had significant effects on the fungal community of chickpea root endosphere. The desi genotypes had higher levels of mycorrhizal and non-mycorrhizal fungal richness and diversity than kabuli genotypes. This study reveals a "genotype effect" of chickpea on the soil microbiota and indicates the possibility to improve the performance of this crop through the selection of genotypes with improved root fungal communities

The effects of dark septate endophytic fungi on chickpea drought tolerance

Non-Peer ReviewedDark septate endophytic (DSE) fungi represent a diverse group of root-colonizing fungal species that are common in environments with strong abiotic stress, such as semiarid prairie regions where their abundance in roots can exceed mycorrhizal fungi. Some DSE fungal species have the ability to benefit host plant growth under water stress conditions. Here we tested the effects of 49 DSE species on chickpea biomass growing under water limiting condition. Three DSE fungal species including Hypocrea lixii, Geomyces vinaceus and Mortierella alpina significantly increased the biomass of chickpea. However the majority of the DSE species did not significantly affect plant biomass and some species decreased that

A study of fungal biodiversity in the root of durum wheat, chickpea, and pea in agro-ecosystems of Saskatchewan

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