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This paper introduces cycling in a variance exchange algorithm, a sequential search procedure for the construction of exact $D-$optimal designs done over a list of \(\tilde{X}\) candidate points and involves the iterative improvement of an initial $N-$trial design. Cycling occurs in this sequence at a certain step of the exchange when a point that was earlier removed from the design at the k-th step qualifies to return to the design at the (k+1)-th point with determinant of the information matrix equal to that of the k-th step or even that of the (k-1)-th step and therefore not guaranteeing the N-point exact D-optimal design. A method to overcome cycling is finally proposed

In some production and administrative processes, the occurrence of certain events is best described by a hyper-geometric distribution, which in turn should be pictorially depicted by what should be called a “hyper-geometric chart (Hg-chart)” in the field of Statistical Quality Control (SQC). However, this has never been the practice, since the existence of such a chart is absent; as such, prompting administrators and process engineers to make use of already existing charts for approximately depicting hyper-geometric processes. In this article, an SQC chart for any hyper-geometric process has been developed for the total number of events in a fixed number of units. This chart has been referred to as the Hg-chart. The center line (CC), lower control limit (LCL) and the upper control limit (UCL) have been obtained for the proposed chart with a sketch of how the proposed chart should be if used for simulation. It has been recommended that simulation should be used to test the proposed chart as this could prove to be more efficient and appropriate for describing hyper-geometric data rather than using an inappropriate chart to be an approximation for solving the problem.

Over 800 million people across the tropics rely on cassava as a major source of calories. While the root dry matter content (RDMC) of this starchy root crop is important for both producers and consumers, characterization of RDMC by traditional methods is time-consuming and laborious for breeding programs. Alternate phenotyping methods have been proposed but lack the accuracy, cost, or speed ultimately needed for cassava breeding programs. For this reason, we investigated the use of a low-cost, handheld NIR spectrometer for field-based RDMC prediction in cassava. Oven-dried measurements of RDMC were paired with 21,044 scans of roots of 376 diverse clones from 10 field trials in Nigeria and grouped into training and test sets based on cross-validation schemes relevant to plant breeding programs. Mean partial least squares regression model performance ranged from R2p = 0.62 - 0.89 for within-trial predictions, which is within the range achieved with laboratory-grade spectrometers in previous studies. Relative to other factors, model performance was highly impacted by the inclusion of samples from the same environment in both the training and test sets. Random forest variable importance analysis of root spectra revealed increased importance in a region previously identified as predictive of water content in plants (~950 - 990 nm). With appropriate model calibration, the tested spectrometer will allow for field-based collection of spectral data with a smartphone for accurate RDMC prediction and potentially other quality traits, a step that could be easily integrated into existing harvesting workflows of cassava breeding programs.CORE IDEASA low-cost, handheld near-infrared spectrometer was tested for phenotyping of cassava rootsPlant breeding-relevant cross-validation schemes were used for predictionsHigh prediction accuracies were achieved for cassava root dry matter contentA spectral region predictive of plant water content was identified as important

Key message More than 40 QTLs associated with 14 stress-related, quality and agro-morphological traits were identified. A catalogue of favourable SNP markers for MAS and a list of candidate genes are provided. Abstract Cassava (Manihot esculenta) is one of the most important starchy root crops in the tropics due to its adaptation to marginal environments. Genetic progress in this clonally propagated crop can be accelerated through the discovery of markers and candidate genes that could be used in cassava breeding programs. We carried out a genome-wide association study (GWAS) using a panel of 5130 clones developed at the International Institute of Tropical Agriculture—Nigeria. The population was genotyped at more than 100,000 SNP markers via genotyping-by-sequencing (GBS). Genomic regions underlying genetic variation for 14 traits classified broadly into four categories: biotic stress (cassava mosaic disease and cassava green mite severity); quality (dry matter content and carotenoid content) and plant agronomy (harvest index and plant type) were investigated. We also included several agro-morphological traits related to leaves, stems and roots with high heritability. In total, 41 significant associations were uncovered. While some of the identified loci matched with those previously reported, we present additional association signals for the traits. We provide a catalogue of favourable alleles at the most significant SNP for each trait-locus combination and candidate genes occurring within the GWAS hits. These resources provide a foundation for the development of markers that could be used in cassava breeding programs and candidate genes for functional validation.

The term Malaria originates from medieval Italian; mal and aria meaning “bad air”. The disease was formally called “ague” or “marsh fever” due to its association with swamps and marsh land (Reither, 1999). The term first appeared in the English Literature about 1829 (Strong, Richard P, 1944). International Journal of Current Microbiology and Applied Sciences ISSN: 2319-7706 Volume 5 Number 4 (2016) pp. 825-835 Journal homepage: http://www.ijcmas.com

The study analysed Gender Preferred Traits and its effect on cassava production and processing value chain in Imo State, Nigeria. The study described the socio-economic characteristics of cassava farmers, ascertained the varietal preference of cassava and determined the factors affecting the production, processing and marketing of cassava in the study area. The study also identified gender based constraints on participation in production, processing and marketing of cassava, relative importance of cassava for men and women for food security and income and role men and women play in cassava production and processing activities. Two communities/locations were selected based on the intensity and importance of cassava production to the communities and ease of access. Focus Group discussion was carried out with a total of 27 women and 32 men (59) and 51 individual respondents. Results show that the study area was dominated by farmers whom are married, still strong and agile, educated with long years of farming experience, small household size and farm holdings. Results also show that women dominated in the production of, cassava which ranked the first most important source of income from crops in the two locations. Men and women carry out the same agricultural tasks with the exception of weeding-done exclusively by women and land clearing-done only by men. Seven local varieties were identified, four of which (chigazu, nwageri, nwocha and adanwankwo) were grown in the two locations. Women were clearly more knowledgeable than their male counterparts about cassava varieties. There were no strong or clear gender differences in varietal preferences, with both men and women mentioning both agronomic and cooking qualities. The female farmers harvested, processed, consumed and sold more cassava than their male counterparts. The results therefore call for policies aimed at encouraging younger farmers by granting them more access to land especially the females to enhance the cultivation and adoption of improved varieties. There is also need for increased access to processing facilities, extension contacts, formation of cooperatives and rehabilitation of rural road networks to enhance the adoption of improved cassava varieties.Keywords: Adoption, Production, Processing, Gender Roles and Preferred Traits

Cassava (Manihot esculenta L.) is one of the most important food crops in the tropics, but yields are far below their potential. The gene pool of cas- sava contains natural genetic diversity relevant to many important breeding goals, but breeding progress has been slow, partly because of insuf- ficient genomic resources. As a first step toward implementing genomewide genetic studies that will facilitate rapid genetic gain through breed- ing, we genotyped-by-sequencing a set of 182 full-sibs population of cassava that segregated in several traits: resistance to the cassava mosaic disease (CMD) and yield under CMD pressure; increased carotenoid content in storage roots; color of stem exterior and anthocyanin pigmen- tation in the petioles, inner root skin, and api- cal leaves. Employing a rare-cutting restriction enzyme, PstI, in a genotyping-by-sequencing (GBS) library preparation, we obtained 2478 segregating single nucleotide polymorphisms (SNPs), of which 1257 passed standard filter - ing for missing genotypes and deviation from expected genotypic frequencies. We mapped 772 SNPs across 19 linkage groups and anchored 313 unique scaffolds from the version 4.1 of the cassava genome assembly. Most of the stud- ied morphological traits as well as resistance to CMD and root carotenoid content showed quali- tative inheritance. As expected, quantitative trait loci analysis for these traits revealed single loci surrounded by small confidence intervals. Yield under CMD was associated with the CMD resis- tance locus. We show that GBS is a powerful genotyping tool that provides a sufficient number of markers for unraveling the genetic architecture of Mendelian traits in cassava in addition to the development of a robust genetic map that can help anchor unassembled genomic scaffolds.

Cross contamination arising from random natural processes and breeding errors is one of the prominent challenges to breeding in many crops including cassava ( Manihot esculenta ). This study attempts to identify molecular marker tools suitable for verifying the genetic purity of putative progenies of populations of cassava. It also proposes a rapid, high-throughput genomic DNA extraction protocol which is a modification of an existing extraction protocol adapted to the pace required for the DNA-based verification of often large population sizes. Three polymorphic simple sequence repeat (SSR) markers were selected from a total of 125 and used for genotyping three populations. The petiole color trait was also used to verify TMS 96/1089A X TME117 where the pink color of the male parent was dominant over the female’s green color. The pace of genomic analysis of populations used in the study was enhanced using a modified , quicker DNA isolation protocol which slashed extraction time by 60%. SSRY153 identified six false progenies in the selfed line, 1M18. Segregation patterns of In combination, both markers identified 2 selfed individuals out of a total of 207. NS890 identified two false hprogenies resulting from selfing in the female parent of the cross TMS 30001 X TMS 96/1089A, out of a total of 93, The principles described for verification using each of the SSR markers applied in this study can be extended to other SSR markers with corresponding nature of polymorphism in any population of the crop. Increased attention would go to the development of more efficient markers such as single nucleotide polymorphisms (SNPs) and other gene-based markers using new and advanced genomics techniques for routine integration of such quality control step in the breeding scheme. Key words: Cassava, simple sequence repeat (SSR), morphological trait, molecular markers, genomic DNA.