Bacterial diseases of dry beans in South Africa with special reference to common bacterial blight and its control

Please read the abstract in the section 00front of this documentThesis (PhD (Microbiology))--University of Pretoria, 2005.Microbiology and Plant Pathologyunrestricte

The role of genotype and production environment in determining the cooking time of dry beans (\u3ci\u3ePhaseolus vulgaris\u3c/i\u3e L.)

Dry bean (Phaseolus vulgaris L.) is a nutrient‐dense food rich in proteins and minerals. Although a dietary staple in numerous regions, including Eastern and Southern Africa, greater utilization is limited by its long cooking time as compared with other staple foods. A fivefold genetic variability for cooking time has been identified for P. vulgaris, and to effectively incorporate the cooking time trait into bean breeding programs, knowledge of how genotypes behave across diverse environments is essential. Fourteen bean genotypes selected from market classes important to global consumers (yellow, cranberry, light red kidney, red mottled, and brown) were grown in 10 to 15 environments (combinations of locations, years, and treatments), and their cooking times were measured when either presoaked or unsoaked prior to boiling. The 15 environments included locations in North America, the Caribbean, and Eastern and Southern Africa that are used extensively for dry bean breeding. The cooking times of the 14 presoaked dry bean genotypes ranged from 16 to 156 min, with a mean of 86 min across the 15 production environments. The cooking times of the 14 dry bean genotypes left unsoaked ranged from 77 to 381 min, with a mean cooking time of 113 min. The heritability of the presoaked cooking time was very high (98%) and moderately high for the unsoaked cooking time (~60%). The genotypic cooking time patterns were stable across environments. There was a positive correlation between the presoaked and unsoaked cooking times (r = .64, p \u3c 0.0001), and two of the fastest cooking genotypes when presoaked were also the fastest cooking genotypes when unsoaked (G1, Cebo, yellow bean; and G4, G23086, cranberry bean). Given the sufficient genetic diversity found, limited crossover Genotype × Environment interactions, and high heritability for cooking time, it is feasible to develop fast cooking dry bean varieties without the need for extensive testing across environments

The role of genotype and production environment in determining the cooking time of dry beans (\u3ci\u3ePhaseolus vulgaris\u3c/i\u3e L.)

Dry bean (Phaseolus vulgaris L.) is a nutrient‐dense food rich in proteins and minerals. Although a dietary staple in numerous regions, including Eastern and Southern Africa, greater utilization is limited by its long cooking time as compared with other staple foods. A fivefold genetic variability for cooking time has been identified for P. vulgaris, and to effectively incorporate the cooking time trait into bean breeding programs, knowledge of how genotypes behave across diverse environments is essential. Fourteen bean genotypes selected from market classes important to global consumers (yellow, cranberry, light red kidney, red mottled, and brown) were grown in 10 to 15 environments (combinations of locations, years, and treatments), and their cooking times were measured when either presoaked or unsoaked prior to boiling. The 15 environments included locations in North America, the Caribbean, and Eastern and Southern Africa that are used extensively for dry bean breeding. The cooking times of the 14 presoaked dry bean genotypes ranged from 16 to 156 min, with a mean of 86 min across the 15 production environments. The cooking times of the 14 dry bean genotypes left unsoaked ranged from 77 to 381 min, with a mean cooking time of 113 min. The heritability of the presoaked cooking time was very high (98%) and moderately high for the unsoaked cooking time (~60%). The genotypic cooking time patterns were stable across environments. There was a positive correlation between the presoaked and unsoaked cooking times (r = .64, p \u3c 0.0001), and two of the fastest cooking genotypes when presoaked were also the fastest cooking genotypes when unsoaked (G1, Cebo, yellow bean; and G4, G23086, cranberry bean). Given the sufficient genetic diversity found, limited crossover Genotype × Environment interactions, and high heritability for cooking time, it is feasible to develop fast cooking dry bean varieties without the need for extensive testing across environments

Seedling root architecture and its relationship with seed yield across diverse environments in \u3ci\u3ePhaseolus vulgaris\u3c/i\u3e

Seedling root phenotypes may have important impacts on fitness and are more easily measured than mature root phenotypes. We phenotyped the roots of 577 genotypes of common bean (Phaseolus vulgaris), representing the bulk of the genetic diversity for recent cultivars and landraces in this species. Root architectural phenotypes of seedlings germinated for nine days were compared to root architectural phenotypes in the field as well as seed yield across 51 environments with an array of abiotic stresses including drought, nutrient deficiency, and heat, as well as non-stress conditions. We observed repeatability ranging from 0.52–0.57 for measures of root phenotypes in seedlings, significant variation in root phene states between gene pools and races, relationships between seedling and field phenotypes, and varying correlations between seedling root phenes and seed yield under a variety of environmental conditions. Seed yield was significantly related to seedling basal root number in 22% of environments, seedling adventitious root abundance in 35% of environments, and seedling taproot length in 12% of environments. Cluster analysis grouped genotypes by their aggregated seedling root phenotype, and variation in seed yield among these clusters under non-stress, drought, and low fertility conditions was observed. These results highlight the existence and influence of integrated root phenotypes for adaptation to edaphic stress, and suggest root phenes have value as breeding targets under real-world conditions

Seedling root architecture and its relationship with seed yield across diverse environments in \u3ci\u3ePhaseolus vulgaris\u3c/i\u3e

Seedling root phenotypes may have important impacts on fitness and are more easily measured than mature root phenotypes. We phenotyped the roots of 577 genotypes of common bean (Phaseolus vulgaris), representing the bulk of the genetic diversity for recent cultivars and landraces in this species. Root architectural phenotypes of seedlings germinated for nine days were compared to root architectural phenotypes in the field as well as seed yield across 51 environments with an array of abiotic stresses including drought, nutrient deficiency, and heat, as well as non-stress conditions. We observed repeatability ranging from 0.52–0.57 for measures of root phenotypes in seedlings, significant variation in root phene states between gene pools and races, relationships between seedling and field phenotypes, and varying correlations between seedling root phenes and seed yield under a variety of environmental conditions. Seed yield was significantly related to seedling basal root number in 22% of environments, seedling adventitious root abundance in 35% of environments, and seedling taproot length in 12% of environments. Cluster analysis grouped genotypes by their aggregated seedling root phenotype, and variation in seed yield among these clusters under non-stress, drought, and low fertility conditions was observed. These results highlight the existence and influence of integrated root phenotypes for adaptation to edaphic stress, and suggest root phenes have value as breeding targets under real-world conditions

Seedling root architecture and its relationship with seed yield across diverse environments in \u3ci\u3ePhaseolus vulgaris\u3c/i\u3e

Seedling root phenotypes may have important impacts on fitness and are more easily measured than mature root phenotypes. We phenotyped the roots of 577 genotypes of common bean (Phaseolus vulgaris), representing the bulk of the genetic diversity for recent cultivars and landraces in this species. Root architectural phenotypes of seedlings germinated for nine days were compared to root architectural phenotypes in the field as well as seed yield across 51 environments with an array of abiotic stresses including drought, nutrient deficiency, and heat, as well as non-stress conditions. We observed repeatability ranging from 0.52–0.57 for measures of root phenotypes in seedlings, significant variation in root phene states between gene pools and races, relationships between seedling and field phenotypes, and varying correlations between seedling root phenes and seed yield under a variety of environmental conditions. Seed yield was significantly related to seedling basal root number in 22% of environments, seedling adventitious root abundance in 35% of environments, and seedling taproot length in 12% of environments. Cluster analysis grouped genotypes by their aggregated seedling root phenotype, and variation in seed yield among these clusters under non-stress, drought, and low fertility conditions was observed. These results highlight the existence and influence of integrated root phenotypes for adaptation to edaphic stress, and suggest root phenes have value as breeding targets under real-world conditions

Seedling root architecture and its relationship with seed yield across diverse environments in \u3ci\u3ePhaseolus vulgaris\u3c/i\u3e

Seedling root phenotypes may have important impacts on fitness and are more easily measured than mature root phenotypes. We phenotyped the roots of 577 genotypes of common bean (Phaseolus vulgaris), representing the bulk of the genetic diversity for recent cultivars and landraces in this species. Root architectural phenotypes of seedlings germinated for nine days were compared to root architectural phenotypes in the field as well as seed yield across 51 environments with an array of abiotic stresses including drought, nutrient deficiency, and heat, as well as non-stress conditions. We observed repeatability ranging from 0.52–0.57 for measures of root phenotypes in seedlings, significant variation in root phene states between gene pools and races, relationships between seedling and field phenotypes, and varying correlations between seedling root phenes and seed yield under a variety of environmental conditions. Seed yield was significantly related to seedling basal root number in 22% of environments, seedling adventitious root abundance in 35% of environments, and seedling taproot length in 12% of environments. Cluster analysis grouped genotypes by their aggregated seedling root phenotype, and variation in seed yield among these clusters under non-stress, drought, and low fertility conditions was observed. These results highlight the existence and influence of integrated root phenotypes for adaptation to edaphic stress, and suggest root phenes have value as breeding targets under real-world conditions

Seedling root architecture and its relationship with seed yield across diverse environments in \u3ci\u3ePhaseolus vulgaris\u3c/i\u3e

Seedling root phenotypes may have important impacts on fitness and are more easily measured than mature root phenotypes. We phenotyped the roots of 577 genotypes of common bean (Phaseolus vulgaris), representing the bulk of the genetic diversity for recent cultivars and landraces in this species. Root architectural phenotypes of seedlings germinated for nine days were compared to root architectural phenotypes in the field as well as seed yield across 51 environments with an array of abiotic stresses including drought, nutrient deficiency, and heat, as well as non-stress conditions. We observed repeatability ranging from 0.52–0.57 for measures of root phenotypes in seedlings, significant variation in root phene states between gene pools and races, relationships between seedling and field phenotypes, and varying correlations between seedling root phenes and seed yield under a variety of environmental conditions. Seed yield was significantly related to seedling basal root number in 22% of environments, seedling adventitious root abundance in 35% of environments, and seedling taproot length in 12% of environments. Cluster analysis grouped genotypes by their aggregated seedling root phenotype, and variation in seed yield among these clusters under non-stress, drought, and low fertility conditions was observed. These results highlight the existence and influence of integrated root phenotypes for adaptation to edaphic stress, and suggest root phenes have value as breeding targets under real-world conditions

South African Ebola diagnostic response in Sierra Leone : a modular high biosafety field laboratory

BACKGROUND : In August 2014, the National Institute for Communicable Diseases (NICD) in South Africa established a modular high-biosafety field Ebola diagnostic laboratory (SA FEDL) near Freetown, Sierra Leone in response to the rapidly increasing number of Ebola virus disease (EVD) cases. METHODS AND FINDINGS : The SA FEDL operated in the Western Area of Sierra Leone, which remained a ªhotspotº of the EVD epidemic for months. The FEDL was the only diagnostic capacity available to respond to the overwhelming demand for rapid EVD laboratory diagnosis for several weeks in the initial stages of the EVD crisis in the capital of Sierra Leone. Furthermore, the NICD set out to establish local capacity amongst Sierra Leonean nationals in all aspects of the FEDL functions from the outset. This led to the successful hand-over of the FEDL to the Sierra Leone Ministry of Health and Sanitation in March 2015. Between 25 August 2014 and 22 June 2016, the laboratory tested 11,250 specimens mostly from the Western Urban and Western Rural regions of Sierra Leone, of which 2,379 (21.14%) tested positive for Ebola virus RNA. CONCLUSIONS : he bio-safety standards and the portability of the SA FEDL, offered a cost-effective and practical alternative for the rapid deployment of a field-operated high biocontainment facility. The SA FEDL teams demonstrated that it is highly beneficial to train the national staff in the course of formidable disease outbreak and accomplished their full integration into all operational and diagnostic aspects of the laboratory. This initiative contributed to the international efforts in bringing the EVD outbreak under control in Sierra Leone, as well as capacitating local African scientists and technologists to respond to diagnostic needs that might be required in future outbreaks of highly contagious pathogens.S1 Video. ªHotº processing of Ebola clinical specimens, PPE and decontamination procedures in South African modular, field-operated biocontainment facility in Sierra Leone.Janusz T Paweska was supported by funding from National Research Foundation and the Global Disease Detection Programmehttp://www.plosntds.orgam2017Microbiology and Plant Patholog

Distribution and severity of bacterial brown spot on dry beans in South Africa: An update

Bacterial brown spot (BBS) of common bean (Phaseolus vulgaris) is a seed-borne bacterial disease caused by Pseudomonas syringae pv. syringae (Pss). Dry bean is an important field crop in South Africa and all commercially available South African dry bean cultivars are susceptible to BBS. The aim of this study was to determine the current distribution and severity of BBS in the dry bean production areas of South Africa. We surveyed 31 locations in five provinces. Disease severity was evaluated on selected plots on a 0–9 scale in four different farming systems: commercial and subsistence farms and strip and national cultivar trials. Leaves with typical BBS symptoms were harvested and transferred to the laboratory. Bacteria were isolated following standard procedure using King’s B medium. Identification of pure isolates was done using physiological and biochemical techniques. Incidence and severity values were used to calculate a disease index. BBS was observed in 88% of locations. BBS incidence was recorded in 54% to 100% of all the farming systems surveyed during the 2008/2009 and 2010/2011 seasons combined. BBS was more severe in the strip and national cultivar trials than on subsistence and commercial farms during the 2008/2009 season and more severe on the commercial farm and in national cultivar trials than on subsistence farms and strip trials during the 2010/2011 season. Findings of this study signal the importance of developing BBS-resistant dry bean cultivars for South Africa