Phenotypic evaluation of cassava (Manihot esculenta crantz) genotypes for enhanced breeding efficiency at NRCRI, Umudike

Two hundred and twenty-five cassava genotypes were evaluated for fresh root yield, dry matter content and other agronomic traits in 2015-2016 growing season at the research station of National Root Crops Research institute (NRCRI), Umudike in Nigeria. The study was conducted to determine genotypes with higher yield and dry matter content. The results of the analysis of variance (ANOVA) showed significant difference among the genotypes evaluated for fresh root yield (FYLD) at p≤0.001 and dry matter content (DMC) at p≤0.05. DMC ranged from 23.4 to 60.7% with a mean of 35.6%. FYLD varied from 27.1 to 60.3 t/ha with a mean of 27.1 t/ha. Genotype NR110386 had the highest DMC of 60.7%. The highest mean yield was recorded for genotype NR110512 (60.25 t/ha), while genotype NR100245 had the highest shoot weight of 17.5kg. There were high levels of variability among the genotypes for all the traits studied that will be useful for cassava breeding and for subsequent release to farmers in Nigeria.Keywords: Cassava, fresh root yield, dry matter content and phenotyp

ON THE IDENTIFICATION OF CORE DETERMINANTS OF POVERTY: A LOGISTIC REGRESSION APPROACH

This study carried out a logistic regression modelling of poverty status of households in Nigeria to identify possible determinants of poverty using the 2003/2004 National Living Standard Survey (NLSS) data. This approach differs from classical regression methods that place inappropriate restrictions on the residuals of the model. The results of the logistic regression showed that household size and educational group for highest level attained by the household head were the most significant determinants of poverty. Others include sex of the household head, age in years of the household head, father’s education level, father’s work, mother’s work, and occupation group of the household head. It strongly recommends that moderate household size and acquiring of formal education be encouraged to reduce poverty prevalence. Keywords: poverty incidence, multidimensional concept, lack of representation and freedom, household's consumption expenditure, classical  regression methods, logistic regression mode

Breedbase: a digital ecosystem for modern plant breeding

Modern breeding methods integrate next-generation sequencing (NGS) and phenomics to identify plants with the best characteristics and greatest genetic merit for use as parents in subsequent breeding cycles to ultimately create improved cultivars able to sustain high adoption rates by farmers. This data-driven approach hinges on strong foundations in data management, quality control, and analytics. Of crucial importance is a central database able to 1) track breeding materials, 2) store experimental evaluations, 3) record phenotypic measurements using consistent ontologies, 4) store genotypic information, and 5) implement algorithms for analysis, prediction and selection decisions. Because of the complexity of the breeding process, breeding databases also tend to be complex, difficult, and expensive to implement and maintain. Here, we present a breeding database system, Breedbase (https://breedbase.org/). Originally initiated as Cassavabase (https://cassavabase.org/) with the NextGen Cassava project (https://www.nextgencassava.org/), and later developed into a crop-agnostic system, it is presently used by dozens of different crops and projects. The system is web-based and is available as open source software. It is available on GitHub (https://github.com/solgenomics/) and packaged in a Docker image for deployment (https://dockerhub.com/breedbase/). The Breedbase system enables breeding programs to better manage and leverage their data for decision making within a fully integrated digital ecosystem