Degradation of Crude Oil in the Rhizosphere of Sorghum Bicolor,

ABSTRACT Dissipation of petroleum contaminants in the rhizosphere is likely the result of enhanced microbial degradation. Plant roots may encourage rhizosphere microbial activity through exudation of nutrients and by providing channels for increased water flow and gas diffusion. Phytoremediation of crude oil in soil was examined in this study using carefully selected plant species monitored over specific plant growth stages. Four sorghum (Sorghum bicolor L.) genotypes with differing root characteristics and levels of exudation were established in a sandy loam soil contaminated with 2700 mg crude oil/kg soil. Soils were sampled at three stages of plant growth: five leaf, flowering, and maturity. All vegetated treatments were associated with higher remediation efficiency, resulting in significantly lower total petroleum hydrocarbon concentrations than unvegetated controls. A relationship between root exudation and bioremediation efficiency was not apparent for these genotypes, although the presence of all sorghum genotypes resulted in significant removal of crude oil from the impacted soil

From traits to typologies: Piloting new approaches to profiling trait preferences along the cassava value chain in Nigeria

Breeding programs are increasing efforts towards demand-led breeding approaches to ensure that cultivars released meet the needs of end users including processors, traders, and consumers, and that they are adopted by farmers. To effectively deploy these approaches, new tools are required to better understand and quantify the degree of preference differences among alternative trait changes competing for measurement and selection effort. The purpose of this study was to present a method of quantifying preferences and developing typologies according to breeding priorities by applying an online trait preference survey approach to cassava (Manihot esculenta Crantz). This paper presents a conjoint analysis based on Potentially All Pairwise RanKings of all possible Alternatives (PAPRIKA) to help guide breeding programs in understanding trait preferences across value chain roles and social contexts and set breeding priorities that represent diverse interests. Trait preferences were assessed using a comprehensive survey and analysis package incorporating a core adaptive conjoint method (1000minds, 2020). Trait selection was based on a trade-off of 11 cassava traits carried out with 792 cassava value chain actors in four geopolitical regions in Nigeria. Principal component and cluster analyses revealed three clusters (typologies) of respondents according to their trait preferences. The results demonstrate the usefulness of this methodology that innovates on previous trait preference approaches to address the expanding needs of plant breeding programs within smallholder contexts. © 2021 The Authors. Crop Science © 2021 Crop Science Society of Americ

Data management in multi-disciplinary African RTB crop breeding programs

Quality phenotype and genotype data are important for the success of a breeding program. Like most programs, African breeding programs generate large multi-disciplinary phenotypic and genotypic datasets from several locations, that must be carefully managed through the use of an appropriate database management system (DBMS) in order to generate reliable and accurate information for breedingdecisions. A DBMS is essential in data collection, storage, retrieval, validation, curation and analysis in plant breeding programs to enhance the ultimate goal of increasing genetic gain. The International Institute of Tropical Agriculture (IITA), working on the roots, tubers and banana (RTB) crops like cassava, yam, banana and plantain has deployed a FAIR-compliant (Findable, Accessible, Interoperable, Reusable) database; BREEDBASE. The functionalities of this database in data management and analysis have been instrumental in achieving breeding goals. Standard Operating Procedures (SOP) for each breeding process have been developed to allow a cognitive walkthrough for users. This has further helped to increase the usage and enhance the acceptability of the system. The wide acceptability gained among breeders in global cassava research programs has resulted in improvements in the precision and quality of genotype and phenotype data, and subsequent improvement in achievement of breeding program goals. Several innovative gender responsive approaches and initiatives have identified users and their preferences which have informed improved customer and product profiles. A remaining bottleneck is the effective linking of data on preferences and social information of crop users with technical breeding data to make this process more effective

Genome-Wide Association Mapping of Correlated Traits in Cassava: Dry Matter and Total Carotenoid Content

Article purchased; Published online: 3 August 2017Cassava (Manihot esculenta (L.) Crantz) is a starchy root crop cultivated in the tropics for fresh consumption and commercial processing. Dry matter content and micronutrient density, particularly of provitamin A, traits that are negatively correlated, are among the primary selection objectives in cassava breeding. This study aimed at identifying genetic markers associated with these traits and uncovering the potential underlying cause of their negative correlation - whether linkage and/or pleiotropy. A genome-wide association mapping using 672 clones genotyped at 72,279 SNP loci was carried out. Root yellowness was used indirectly to assess variation in carotenoid content. Two major loci for root yellowness was identified on chromosome 1 at positions 24.1 and 30.5 Mbp. A single locus for dry matter content that co-located with the 24.1 Mbp peak for carotenoid content was identified. Haplotypes at these loci explained a large proportion of the phenotypic variability. Evidence of mega-base-scale linkage disequilibrium around the major loci of the two traits and detection of the major dry matter locus in independent analysis for the white- and yellow-root subpopulations suggests that physical linkage rather that pleiotropy is more likely to be the cause of the negative correlation between the target traits. Moreover, candidate genes for carotenoid (phytoene synthase) and starch biosynthesis (UDP-glucose pyrophosphorylase and sucrose synthase) occurred in the vicinity of the identified locus at 24.1 Mbp. These findings elucidate on the genetic architecture of carotenoids and dry matter in cassava and provides an opportunity to accelerate genetic improvement of these traits

Prospects for Genomic Selection in Cassava Breeding

Article purchased; Published online: 28 Sept 2017Cassava (Manihot esculenta Crantz) is a clonally propagated staple food crop in the tropics. Genomic selection (GS) has been implemented at three breeding institutions in Africa to reduce cycle times. Initial studies provided promising estimates of predictive abilities. Here, we expand on previous analyses by assessing the accuracy of seven prediction models for seven traits in three prediction scenarios: cross-validation within populations, cross-population prediction and cross-generation prediction. We also evaluated the impact of increasing the training population (TP) size by phenotyping progenies selected either at random or with a genetic algorithm. Cross-validation results were mostly consistent across programs, with nonadditive models predicting of 10% better on average. Cross-population accuracy was generally low (mean = 0.18) but prediction of cassava mosaic disease increased up to 57% in one Nigerian population when data from another related population were combined. Accuracy across generations was poorer than within-generation accuracy, as expected, but accuracy for dry matter content and mosaic disease severity should be sufficient for rapid-cycling GS. Selection of a prediction model made some difference across generations, but increasing TP size was more important. With a genetic algorithm, selection of one-third of progeny could achieve an accuracy equivalent to phenotyping all progeny. We are in the early stages of GS for this crop but the results are promising for some traits. General guidelines that are emerging are that TPs need to continue to grow but phenotyping can be done on a cleverly selected subset of individuals, reducing the overall phenotyping burden

High-resolution linkage map and chromosome-scale genome assembly for cassava (Manihot esculenta Crantz) from 10 populations

Cassava (Manihot esculenta Crantz) is a major staple crop in Africa, Asia, and South America, and its starchy roots provide nourishment for 800 million people worldwide. Although native to South America, cassava was brought to Africa 400–500 years ago and is now widely cultivated across sub-Saharan Africa, but it is subject to biotic and abiotic stresses. To assist in the rapid identification of markers for pathogen resistance and crop traits, and to accelerate breeding programs, we generated a framework map for M. esculenta Crantz from reduced representation sequencing [genotyping-by-sequencing (GBS)]. The composite 2412-cM map integrates 10 biparental maps (comprising 3480 meioses) and organizes 22,403 genetic markers on 18 chromosomes, in agreement with the observed karyotype. We used the map to anchor 71.9% of the draft genome assembly and 90.7% of the predicted protein-coding genes. The chromosome-anchored genome sequence will be useful for breeding improvement by assisting in the rapid identification of markers linked to important traits, and in providing a framework for genomic selectionenhanced breeding of this important crop.Bill and Melinda Gates Foundation (BMGF) Grant OPPGD1493. University of Arizona. CGIAR Research Program on Roots, Tubers, and Bananas. Next Generation Cassava Breeding grant OPP1048542 from BMGF and the United Kingdom Department for International Development. BMGF grant OPPGD1016 to IITA. National Institutes of Health S10 Instrumentation Grants S10RR029668 and S10RR027303.http://www.g3journal.orghb201

Improving Genomic Prediction in Cassava Field Experiments Using Spatial Analysis

Cassava (Manihot esculenta Crantz) is an important staple food in sub-Saharan Africa. Breeding experiments were conducted at the International Institute of Tropical Agriculture in cassava to select elite parents. Taking into account the heterogeneity in the field while evaluating these trials can increase the accuracy in estimation of breeding values. We used an exploratory approach using the parametric spatial kernels Power, Spherical, and Gaussian to determine the best kernel for a given scenario. The spatial kernel was fit simultaneously with a genomic kernel in a genomic selection model. Predictability of these models was tested through a 10-fold cross-validation method repeated five times. The best model was chosen as the one with the lowest prediction root mean squared error compared to that of the base model having no spatial kernel. Results from our real and simulated data studies indicated that predictability can be increased by accounting for spatial variation irrespective of the heritability of the trait. In real data scenarios we observed that the accuracy can be increased by a median value of 3.4%. Through simulations, we showed that a 21% increase in accuracy can be achieved. We also found that Range (row) directional spatial kernels, mostly Gaussian, explained the spatial variance in 71% of the scenarios when spatial correlation was significant

Revegetation of waste fly ash landfills in a semiarid environment

This study investigated vegetation strategies for a fly ash landfill in a semi-arid environment. Ten plant species adapted to the local climate were initially evaluated for their germination characteristics in various mixtures of Tivoli fine sand, fly ash, and cattle manure. Alkali sacaton (native, Sporobolus airoides (Torr.) Torr.), blue grama (native, Bouteloua gracilis (H.B.K.) Lag. Ex Griffiths), a forage sorghum (variety Canex, Sorghum bicolor (L.) Moench), sand bluestem (variety Woodward, Andropogon hallii Hack.), and sideoats grama variety El Reno, Bouteloua curtipendula (michx.) Torr.) were selected for further evaluation. Concurrently, mixtures were evaluated to determine the effects of the soil amendments on soil saturated paste electrical conductivity (EC) and pH. The addition of even 50 g kg-1 fly ash increased EC values above 4.0 dS m-1, indicating salt tolerant species may be needed. Six mixtures were selected for use in a greenhouse study and for further study of moisture retention characteristics. Using an X/Y format, where X is fly ash content and Y is manure content (g kg-1) and the balance of the mixture was Tivoli fine sand, those mixtures were 0/0, 200/0, 200/100, 200/200, 100/100, and 300/100. The addition of manure provided ample quantities of plant nutrients. Alkali sacaton was the only plant specie not adversely affected by the addition of fly ash. For biomass production, height, vigor and leaf tip burn, all remaining species had significantly better growth or ratings with 0/0 as compared to any other mixture. Soil moisture retention characteristics of the Tivoli fine sand can be significantly changed through amendment with fly ash or manure. Sixty cm of Tivoli sand was estimated to have the same available water holding capacity as 45 cm of 200/0, 39 cm of 200/100, 34 cm of 200/200, 47 cm of 100/100, and 33 cm of 300/100.The Journal of Range Management archives are made available by the Society for Range Management and the University of Arizona Libraries. Contact [email protected] for further information.Migrated from OJS platform August 202