Preferred Language
Articles
/
bsj-5999
Molecular Characterization of Potential Crop Pathogens Associated with Weeds as Endophytes in Uniilorin Plantations, Nigeria
...Show More Authors

Crop diseases are usually caused by inoculum of pathogens which might exist on alternate hosts or weeds as endophytes. These endophytes, cum pathogens, usually confer some beneficial attributes to these weeds or alternate hosts from protection against herbivores, disease resistance, stress tolerance to secondary metabolites production. This study was therefore carried out to isolate potential crop pathogens which exist as endophytes on weed species in the University of Ilorin plantations. Green asymptomatic leaves were collected from 10 weed species across the plantations, and processed for their endophytic fungi isolation. Isolates were purified into pure cultures and used for molecular identification using the internal transcribed spacer (ITS) region of the ribosomal DNA. Phylogenetic analysis of the fungal sequences using MEGA software revealed 9 fungal genera belonging to 13 species, with species in the genera Curvularia, Epicoccum and Daldinia occurring in more than one weed species, while other genera such as Alternaria, Fusarium, Chaetomium, Macrophomina, Arthrinium and Phomopsis occurred in just one weed species each. Daldinia eschscholtzii was isolated in this study as an endophyte from Loudetia arundinacea for the first time. This plant is very abundant in Nigeria and Africa where it is used majorly for thatching and feeding livestocks. This also represents the first endophytic fungi from the genus Loudetia. Potential relationship between the occurrences of these fungi as endophytes and as pathogens are discussed. These discoveries represent the first large-scale molecular identification and several first reports of endophytes from these weed species. These results also represent the first records of some of these fungi in Nigeria.

Scopus Clarivate Crossref
View Publication Preview PDF
Quick Preview PDF
Publication Date
Sat Dec 30 2023
Journal Name
Journal Of Economics And Administrative Sciences
The Cluster Analysis by Using Nonparametric Cubic B-Spline Modeling for Longitudinal Data
...Show More Authors

Longitudinal data is becoming increasingly common, especially in the medical and economic fields, and various methods have been analyzed and developed to analyze this type of data.

In this research, the focus was on compiling and analyzing this data, as cluster analysis plays an important role in identifying and grouping co-expressed subfiles over time and employing them on the nonparametric smoothing cubic B-spline model, which is characterized by providing continuous first and second derivatives, resulting in a smoother curve with fewer abrupt changes in slope. It is also more flexible and can pick up on more complex patterns and fluctuations in the data.

The longitudinal balanced data profile was compiled into subgroup

... Show More
View Publication Preview PDF
Crossref