Identification of Genomic Regions for Traits Associated with Flowering in Cassava (Manihot esculenta Crantz)

Flowering in cassava (Manihot esculenta Crantz) is crucial for the generation of botanical seed for breeding. However, genotypes preferred by most farmers are erect and poor at flowering or never flower. To elucidate the genetic basis of flowering, 293 diverse cassava accessions were evaluated for flowering-associated traits at two locations and seasons in Uganda. Genotyping using the Diversity Array Technology Pty Ltd. (DArTseq) platform identified 24,040 single-nucleotide polymorphisms (SNPs) distributed on the 18 cassava chromosomes. Population structure analysis using principal components (PCs) and kinships showed three clusters; the first five PCs accounted for 49.2% of the observed genetic variation. Linkage disequilibrium (LD) estimation averaged 0.32 at a distance of ~2850 kb (kilo base pairs). Polymorphism information content (PIC) and minor allele frequency (MAF) were 0.25 and 0.23, respectively. A genome-wide association study (GWAS) analysis uncovered 53 significant marker-trait associations (MTAs) with flowering-associated traits involving 27 loci. Two loci, SNPs S5_29309724 and S15_11747301, were associated with all the traits. Using five of the 27 SNPs with a Phenotype_Variance_Explained (PVE) ≥ 5%, 44 candidate genes were identified in the peak SNP sites located within 50 kb upstream or downstream, with most associated with branching traits. Eight of the genes, orthologous to Arabidopsis and other plant species, had known functional annotations related to flowering, e.g., eukaryotic translation initiation factor and myb family transcription factor. This study identified genomic regions associated with flowering-associated traits in cassava, and the identified SNPs can be useful in marker-assisted selection to overcome hybridization challenges, like unsynchronized flowering, and candidate gene validation.

Definition of sensory and instrumental thresholds of acceptability for selection of cassava genotypes with improved boiling properties

BACKGROUND

Consumers of boiled cassava in Africa, Latin America and Asia use specific preference criteria to evaluate its cooking quality, in terms of texture, colour and taste. To improve adoption rates of improved cassava varieties intended for consumption after boiling, these preference criteria need to be determined, quantified and integrated as post-harvest quality traits in the target product profile of boiled cassava, so that breeding programs may screen candidate varieties based on both agronomic traits and consumer preference traits.

RESULTS

Surveys of various end-user groups identified seven priority quality attributes of boiled cassava covering root preparation, visual aspect, taste and texture. Three populations of contrasted cassava genotypes, from good-cooking to bad-cooking, in three countries (Uganda, Benin, Colombia) were then characterized according to these quality attributes by sensory quantitative descriptive analysis (QDA) and by standard instrumental methods. Consumers' preferences of the texture attributes mealiness and hardness were also determined. By analysis of correlations, the consumers' preferences scores were translated into thresholds of acceptability in terms of QDA scores, then in terms of instrumental measurements (water absorption during boiling and texture analysis). The thresholds of acceptability were used to identify among the Colombian and Benin populations promising genotypes for boiled cassava quality.

CONCLUSION

This work demonstrates the steps of determining priority quality attributes for boiled cassava and establishing their corresponding quantitative thresholds of acceptability. The information can then be included in boiled cassava target product profiles used by cassava breeders, for better selection and adoption rates of new varieties. © 2024 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

The tricot approach: an agile framework for decentralized on-farm testing supported by citizen science. A retrospective

Matching crop varieties to their target use context and user preferences is a challenge faced by many plant breeding programs serving smallholder agriculture. Numerous participatory approaches proposed by CGIAR and other research teams over the last four decades have attempted to capture farmers' priorities/preferences and crop variety field performance in representative growing environments through experimental trials with higher external validity. Yet none have overcome the challenges of scalability, data validity and reliability, and difficulties in capturing socio-economic and environmental heterogeneity. Building on the strengths of these attempts, we developed a new data-generation approach, called triadic comparison of technology options (tricot). Tricot is a decentralized experimental approach supported by crowdsourced citizen science. In this article, we review the development, validation, and evolution of the tricot approach, through our own research results and reviewing the literature in which tricot approaches have been successfully applied. The first results indicated that tricot-aggregated farmer-led assessments contained information with adequate validity and that reliability could be achieved with a large sample. Costs were lower than current participatory approaches. Scaling the tricot approach into a large on-farm testing network successfully registered specific climatic effects of crop variety performance in representative growing environments. Tricot's recent application in plant breeding networks in relation to decision-making has (i) advanced plant breeding lines recognizing socio-economic heterogeneity, and (ii) identified consumers' preferences and market demands, generating alternative breeding design priorities. We review lessons learned from tricot applications that have enabled a large scaling effort, which should lead to stronger decision-making in crop improvement and increased use of improved varieties in smallholder agriculture.

Rapid analysis of hydrogen cyanide in fresh cassava roots using NIRSand machine learning algorithms: Meeting end user demand for low cyanogenic cassava

This study focuses on meeting end-users' demand for cassava (Manihot esculenta Crantz) varieties with low cyanogenic potential (hydrogen cyanide potential [HCN]) by using near-infrared spectrometry (NIRS). This technology provides a fast, accurate, and reliable way to determine sample constituents with minimal sample preparation. The study aims to evaluate the effectiveness of machine learning (ML) algorithms such as logistic regression (LR), support vector machine (SVM), and partial least squares discriminant analysis (PLS-DA) in distinguishing between low and high HCN accessions. Low HCN accessions averagely scored 1-5.9, while high HCN accessions scored 6-9 on a 1-9 categorical scale. The researchers used 1164 root samples to test different NIRS prediction models and six spectral pretreatments. The wavelengths 961, 1165, 1403-1505, 1913-1981, and 2491 nm were influential in discrimination of low and high HCN accessions. Using selected wavelengths, LR achieved 100% classification accuracy and PLS-DA achieved 99% classification accuracy. Using the full spectrum, the best model for discriminating low and high HCN accessions was the PLS-DA combined with standard normal variate with second derivative, which produced an accuracy of 99.6%. The SVM and LR had moderate classification accuracies of 75% and 74%, respectively. This study demonstrates that NIRS coupled with ML algorithms can be used to identify low and high HCN accessions, which can help cassava breeding programs to select for low HCN accessions.

East African highland cooking banana: towards an efficient selection of hybrids with user-preferred food quality traits

BACKGROUND

Determinants of culinary qualities of East African highland cooking bananas (EAHCB) are not well known. This constrains the inclusion of user-preferred traits in breeding. The present study aimed to quantify key indicators of user-preferred characteristics to enable selection of acceptable hybrids.

RESULTS

Qualitative characteristics that drive preference were big bunches (15-34 kg), long straight/slightly curved fingers (12-23 cm), yellowness and soft texture. Descriptive sensory analysis of the intensity of colour and texture the 23 genotypes revealed that landraces Kibuzi, Mbwazirume, Nakitembe and Mpologoma had higher intensity of yellowness and lower intensity of hardness (softer) and a low score (≤ 1.0) of astringency taste. A preference test showed that they had higher acceptability scores. Biochemical, instrumental and sensory data revealed correlations between sensory firmness and instrumental hardness (r = 0.5), sensory firmness and amylopectin (r = -0.54), suggesting that qualitative descriptions can be predicted by instrumental and biochemical indicators. Significant (P < 0.05) variations in amylose and total starch content were observed in different varieties. Moderate correlations between instrumental hardness and firmness in mouth (r = 0.55), cohesiveness and firmness in the mouth (r = 0.57), and adhesiveness and firmness in the mouth (r = 0.64) were observed. Surprisingly, carotenoids content was not correlated with yellowness in cooked matooke. However, positive correlations were observed between chroma (b*) parameters of raw matooke and sensorial assessed color on cooked samples.

CONCLUSION

Qualitative characteristis; the bunch, pulp colour and texture; that drive users-preference in the EAHCB were quantified, paving way for breeders to use them to select genotypes with these attributes early in the breeding process. © 2023 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Development and validation of near-infrared spectroscopy procedures for prediction of cassava root dry matter and amylose contents in Ugandan cassava germplasm

BACKGROUND

Cassava utilization for food and/or industrial products depends on inherent properties of root dry matter content (DMC) and the starch fraction of amylose content (AC). Accordingly, in the present study, near-infrared reflectance spectroscopy (NIRS) models were developed to aid breeding and selection of DMC and AC as critical industrial traits taking care of root sample preparation and cassava germplasm diversity available in Uganda.

RESULTS

Upon undertaking calibrations and cross-validations, best models were adopted for validation. DMC in calibration samples ranged from 20 to 45 g 100g-1 , whereas, for amylose content, it ranged from 14 to 33 g 100g-1 . In the validation set, average DMC was 29.5 g 100g-1 , whereas, for amylose content, it was 24.64 g 100g-1 . For DMC, a modified partial least square regression model had regression coefficients (R2 ) of 0.98 and 0.96, respectively, in the calibration and validation set. These were also associated with low bias (-0.018) and ratio of performance deviation that ranged from 4.7 to 5.0. In addition, standard error of prediction values ranged from 0.9 g 100g-1 to 1.06 g 100g-1 . For AC, the regression coefficient was 0.91 for the calibration set and 0.94 for the validation set. A bias equivalent to -0.03 and a ratio of performance deviation of 4.23 were observed.

CONCLUSION

These findings confirm the robustness of NIRS in the estimation of dry matter content and amylose content in cassava roots and thus justify its use in routine cassava breeding operations. © 2023 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Contrasting effects of polysaccharide components on the cooking properties of roots, tubers and bananas

BACKGROUND

Consumer preferences for boiled or fried pieces of roots, tubers and bananas (RTBs) are mainly related to their texture. Different raw and cooked RTBs were physiochemically characterized to determine the effect of biochemical components on their cooking properties.

RESULTS

Firmness in boiled sweetpotato increases with sugar and amylose contents but no significant correlation was observed between other physicochemical characteristics and cooking behaviour. Hardness of boiled yam can be predicted by dry matter (DM) and galacturonic acid (GalA) levels. For cassava, no significant correlation was found between textural properties of boiled roots and DM, but amylose and Ca2+ content were correlated with firmness, negatively and positively, respectively. Water absorption of cassava root pieces boiled in calcium chloride solutions was much lower, providing indirect evidence that pectins are involved in determining cooking quality. A highly positive correlation between textural attributes and DM was observed for fried plantain, but no significant correlation was found with GalA, although frying slightly reduced GalA.

CONCLUSION

The effect of main components on texture after cooking differs for the various RTBs. The effect of global DM and major components (i.e. starch, amylose) is prominent for yam, plantain and sweetpotato. Pectins also play an important role on the texture of boiled yam and play a prominent role for cassava through interaction with Ca2+ . © 2023 Bill and Melinda Gates Foundation. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

A labeled spectral dataset with cassava disease occurrences using virus titre determination protocol

In this work, we present a novel dataset composed of spectral data and images of cassava crops with and without diseases. Together with the description of the dataset, we describe the protocol to collect such data in a controlled environment and in an open field where pests are not controlled. Crop disease diagnosis has been done in the past through the analysis of plant images taken with a smartphone camera. However, in some cases, disease symptoms are not visible. Furthermore, for some cassava diseases, once symptoms have manifested on the aerial part of the plant, the root which is the edible part of the plant has been totally destroyed. The goal of collecting this multimodality of the crop disease is early intervention, following the hypothesis that diseased crops without visible symptoms can be detected using spectral information. We collected visible and near-infrared spectra captured from leaves infected with two common cassava diseases namely; Cassava Brown Streak Disease and Cassava Mosaic Disease, as well as from healthy plants. Together, we also captured leaf imagery data that corresponds to the spectral information. In our experiments, biochemical data is collected and taken as the ground truth. Finally, agricultural experts provided a disease score per plant leaf from 1 to 5, 1 representing healthy and 5 severely diseased. The process of disease monitoring and data collection took 19 and 15 consecutive weeks for screenhouse and open field, respectively, until disease symptoms were visibly seen by the human eye.

Flowering and fruit-set in cassava under extended red-light photoperiod supplemented with plant-growth regulators and pruning

BACKGROUND

Cassava (Manihot esculenta Crantz) is staple food and major source of calories for over 500 million people in sub-Saharan Africa. The crop is also a source of income for smallholder farmers, and has increasing potential for industrial utilization. However, breeding efforts to match the increasing demand of cassava are impeded by its inability to flower, delayed or unsynchronized flowering, low proportion of female flowers and high fruit abortions. To overcome these sexual reproductive bottlenecks, this study investigated the effectiveness of using red lights to extend the photoperiod (RLE), as a gateway to enhancing flowering and fruit set under field conditions.

MATERIALS AND METHODS

Panels of cassava genotypes, with non- or late and early flowering response, 10 in each case, were subjected to RLE from dusk to dawn. RLE was further evaluated at low (LL), medium (ML) and high (HL) red light intensities, at ~  ≤ 0.5; 1.0 and 1.5PFD (Photon Flux Density) in µmol m^-2 s^-1 respectively. Additionally, the effect of a cytokinin and anti-ethylene as plant growth regulators (PGR) and pruning under RLE treatment were examined.

RESULTS

RLE stimulated earlier flower initiation in all genotypes, by up to 2 months in the late-flowering genotypes. Height and number of nodes at first branching, particularly in the late-flowering genotypes were also reduced, by over 50%. Number and proportion of pistillate flowers more than doubled, while number of fruits and seeds also increased. Number of branching levels during the crop season also increased by about three. Earlier flowering in many genotypes was most elicited at LL to ML intensities. Additive effects on flower numbers were detected between RLE, PGR and pruning applications. PGR and pruning treatments further increased number and proportion of pistillate flowers and fruits. Plants subjected to PGR and pruning, developed bisexual flowers and exhibited feminization of staminate flowers. Pruning at first branching resulted in higher pistillate flower induction than at second branching.

CONCLUSIONS

These results indicate that RLE improves flowering in cassava, and its effectiveness is enhanced when PGR and pruning are applied. Thus, deployment of these technologies in breeding programs could significantly enhance cassava hybridizations and thus cassava breeding efficiency and impact.

Phenotype based clustering, and diversity of common bean genotypes in seed iron concentration and cooking time

Common bean is the world's most important directly consumed legume food crop that is popular for calories, protein and micronutrients. It is a staple food in sub-Saharan Africa, and a significant source of iron for anemic people. However, several pests, soil and weather challenges still impede its production. Long cooking time, and high phytic acid and polyphenols that influence bioavailable iron also limit the health benefits. To inform population improvement strategies and selection decisions for resilient fast cooking and iron biofortified beans, the study determined diversity and population structure within 427 breeding lines, varieties, or landraces mostly from Alliance Uganda and Columbia. The genotypes were evaluated for days to flowering and physiological maturity, yield, seed iron (FESEED) and zinc (ZNSEED) and cooking time (COOKT). Data for all traits showed significant (P≤0.001) differences among the genotypes. Repeatability was moderate to high for most traits. Performance ranged from 52 to 87 ppm (FESEED), 23-38 ppm (ZNSEED), 36-361 minutes (COOKT), and 397-1299 kg/ha (yield). Minimal differences existed between the gene pools in the mean performance except in yield, where Mesoamerican beans were better by 117 kg/ha. The genotypes exhibited high genetic diversity and thus have a high potential for use in plant breeding. Improvement of FESEED and ZNSEED, COOKT and yield performance within some markets such as red and small white beans is possible. Hybridization across market classes especially for yellow beans is essential but this could be avoided by adding other elite lines to the population. Superior yielding and fast cooking, yellow and large white beans were specifically lacking. Adding Fe dense elite lines to the population is also recommended. The population was clustered into three groups that could be considered for specific breeding targets based on trait correlations.

Validation of KASP markers associated with cassava mosaic disease resistance, storage root dry matter and provitamin A carotenoid contents in Ugandan cassava germplasm

INTRODUCTION

The intrinsic high heterozygosity of cassava makes conventional breeding ineffective for rapid genetic improvement. However, recent advances in next generation sequencing technologies have enabled the use of high-density markers for genome-wide association studies, aimed at identifying single nucleotide polymorphisms (SNPs) linked to major traits such as cassava mosaic disease (CMD) resistance, dry matter content (DMC) and total carotenoids content (TCC). A number of these trait-linked SNPs have been converted to Kompetitive allele-specific polymerase chain reaction (KASP) markers for downstream application of marker assisted selection.

METHODS

We assayed 13 KASP markers to evaluate their effectiveness in selecting for CMD, DMC and TCC in 1,677 diverse cassava genotypes representing two independent breeding populations in Uganda.

RESULTS

Five KASP markers had significant co-segregation with phenotypes; CMD resistance (2), DMC (1) and TCC (2), with each marker accounting for at least 30% of the phenotypic variation. Markers located within the chromosomal regions for which strong marker-trait association loci have been characterised (chromosome 12 markers for CMD, chromosome 1 markers for DMC and TCC) had consistently superior ability to discriminate the respective phenotypes.

DISCUSSION

The results indicate varying discriminatory abilities of the KASP markers assayed and the need for their context-based use for MAS, with PSY2_572 particularly effective in selecting for high TCC. Availing the effective KASP markers on cost-effective genotyping platforms could facilitate practical implementation of marker-assisted cassava breeding for accelerated genetic gains for CMD, DMC and provitamin A carotenoids.

Effectiveness of genomic selection for improving provitamin A carotenoid content and associated traits in cassava

Global efforts are underway to develop cassava with enhanced levels of provitamin A carotenoids to sustainably meet increasing demands for food and nutrition where the crop is a major staple. Herein, we tested the effectiveness of genomic selection (GS) for rapid improvement of cassava for total carotenoids content and associated traits. We evaluated 632 clones from Uganda's provitamin A cassava breeding pipeline and 648 West African introductions. At harvest, each clone was assessed for level of total carotenoids, dry matter content, and resistance to cassava brown streak disease (CBSD). All clones were genotyped with diversity array technology and imputed to a set of 23,431 single nucleotide polymorphic markers. We assessed predictive ability of four genomic prediction methods in scenarios of cross-validation, across population prediction, and inclusion of quantitative trait loci markers. Cross-validations produced the highest mean prediction ability for total carotenoids content (0.52) and the lowest for CBSD resistance (0.20), with G-BLUP outperforming other models tested. Across population, predictions showed low ability of Ugandan population to predict the performance of West African clones, with the highest predictive ability recorded for total carotenoids content (0.34) and the lowest for CBSD resistance (0.12) using G-BLUP. By incorporating chromosome 1 markers associated with carotenoids content as independent kernel in the G-BLUP model of a cross-validation scenario, prediction ability slightly improved from 0.52 to 0.58. These results reinforce ongoing efforts aimed at integrating GS into cassava breeding and demonstrate the utility of this tool for rapid genetic improvement.

Near-infrared spectroscopy applications for high-throughput phenotyping for cassava and yam: A review

The review aimed to identify the different high‐throughput phenotyping (HTP) techniques that used for quality evaluation in cassava and yam breeding programmes, and this has provided insights towards the development of metrics and their application in cassava and yam improvements. A systematic review of the published research articles involved the use of NIRS in analysing the quality traits of cassava and yam was carried out, and Scopus, Science Direct, Web of Sciences and Google Scholar were searched. The results of the review established that NIRS could be used in understanding the chemical constituents (carbohydrate, protein, vitamins, minerals, carotenoids, moisture, starch, etc.) for high‐throughput phenotyping. This study provides preliminary evidence of the application of NIRS as an efficient and affordable procedure for HTP. However, the feasibility of using mid‐infrared spectroscopy (MIRS) and hyperspectral imaging (HSI) in combination with the NIRS could be further studied for quality traits phenotyping.

Identification of cassava quality attributes preferred by Ugandan users along the food chain

This study aimed to identify cassava quality attributes preferred by users along the food chain, in order to provide breeders with criteria for prioritisation. Survey and consumer‐testing studies were conducted within Apac and Luwero districts in Uganda. Additionally, sensory evaluation by trained panellists was conducted to determine descriptors for assessing quality of boiled roots. Results revealed softness of boiled roots and in‐ground storability as key attributes influencing varietal preference besides high yield, non‐bitter roots, disease resistance, early maturity and drought resistance. For some attributes like in‐ground storability, preference differed significantly between locations and showed differentiation by gender. Local varieties were found to be superior in quality attributes. From sensory evaluation, twenty‐one descriptors associated with appearance, texture, taste and aroma of boiled roots were determined. Findings from this study are vital for breeders to adopt gender‐responsive approaches in order to develop varieties that meet the needs and preferences of end users.

Assessment of end user traits and physicochemical qualities of cassava flour: a case of Zombo district, Uganda

Cassava breeding programmes in Uganda do not currently select materials based on flour making quality, explaining in part the low adoption rates of many released varieties. In this study, we describe end user trait preferences, processing qualities and physicochemical properties of cassava flour. We found that higher proportion of women than men showed preference for most attributes of cassava flour quality evaluated in this study. Preference for colour was 66% and 52% among women and men, respectively, while that for stickiness of Kwon was 26% (women) and 15% (men). Ease of peeling and stickiness of Kwon were key processing traits. Heap fermented flour had higher pasting temperatures, but lower viscosities than sun-dried flour, and had lower amylose content compared to fresh root starch. The results demonstrate the importance of gender sensitive participatory evaluation of breeding materials, in tandem with physicochemical evaluation during selection of best possible candidate breeding lines.

Comparative compositional analysis of cassava brown streak disease resistant 4046 cassava and its non-transgenic parental cultivar

Compositional analysis is an important component of an integrated comparative approach to assessing the food and feed safety of new crops developed using biotechnology. As part of the safety assessment of cassava brown streak disease resistant 4046 cassava, a comprehensive assessment of proximates, minerals, amino acids, fatty acids, vitamins, anti-nutrients, and secondary metabolites was performed on leaf and storage root samples of 4046 cassava and its non-transgenic parental control, TME 204, collected from confined field trials in Kenya and Uganda over two successive cropping cycles. Among the 100 compositional components that were assessed in samples of 4046 and control TME 204 cassava roots (47 components) and leaves (53 components), there were no nutritionally relevant differences noted. Although there were statistically significant differences between the transgenic and control samples for some parameters, in most cases the magnitudes of these differences were small (<20%), and in every case where comparative literature data were available, the mean values for 4046 and control cassava samples were within the range of normal variation reported for the compositional component in question. Overall, no consistent patterns emerged to suggest that biologically meaningful adverse changes in the composition or nutritive value of the leaves or storage roots occurred as an unintended or unexpected consequence of the genetic modification resulting in 4046 cassava. The data presented here provide convincing evidence of the safety of 4046 cassava with respect to its biochemical composition for food and feed, and it could be considered as safe as its non-transgenic control.

Starch quality traits of improved provitamin A cassava (Manihot esculenta Crantz)

Provitamin A cassava clones were analysed for starch yield and critical starch quality attributes, to understand possible applications in the food industry. Total carotenoids content in the test clones ranged from 0.03-11.94 μg g^-1 of fresh root. Starch yield ranged from 8.4-33.2 % and correlated negatively (r = -0.588, P < 0.001) with carotenoids content. Amylose content (16.4–22.1%) didn't differ significantly (P ≤ 0.05) among the cassava clones. Meanwhile, total carotenoid content had significant negative correlations (P ≤ 0.05) with starch pasting temperature, peak time, setback viscosities and peak area. The reduced peak time and pasting temperatures in high-carotenoid cassava signifies reduction in energy requirements in yellow-fleshed roots when compared to white-fleshed cassava. This attribute is desirable for the food industry as it would reduce the overall cost of processing the cassava. Furthermore, final viscosities of starch from carotenoid-rich cassava were lower than those of white-fleshed roots, making provitamin A cassava suitable for soft food processing.

Eleven years of breeding efforts to combat cassava brown streak disease

Cassava (Manihot esculenta Crantz) production is currently under threat from cassava brown streak disease (CBSD), a disease that is among the seven most serious obstacles to world's food security. Three issues are of significance for CBSD. Firstly, the virus associated with CBSD, has co-evolved with cassava outside its center of origin for at least 90 years. Secondly, that for the last 74 years, CBSD was only limited to the low lands. Thirdly, that most research has largely focused on CBSD epidemiology and virus diversity. Accordingly, this paper focuses on CBSD genetics and/or breeding and hence, presents empirical data generated in the past 11 years of cassava breeding in Uganda. Specifically, this paper provides: 1) empirical data on CBSD resistance screening efforts to identify sources of resistance and/or tolerance; 2) an update on CBSD resistance population development comprising of full-sibs, half-sibs and S1 families and their respective field performances; and 3) insights into chromosomal regions and genes involved in CBSD resistance based on genome wide association analysis. It is expected that this information will provide a foundation for harmonizing on-going CBSD breeding efforts and consequently, inform the future breeding interventions aimed at combating CBSD.

Bio-ethanol production from non-food parts of cassava (Manihot esculenta Crantz)

Global climate issues and a looming energy crisis put agriculture under pressure in Sub-Saharan Africa. Climate adaptation measures must entail sustainable development benefits, and growing crops for food as well as energy may be a solution, removing people from hunger and poverty without compromising the environment. The present study investigated the feasibility of using non-food parts of cassava for energy production and the promising results revealed that at least 28% of peels and stems comprise dry matter, and 10 g feedstock yields >8.5 g sugar, which in turn produced >60% ethanol, with pH ≈ 2.85, 74-84% light transmittance and a conductivity of 368 mV, indicating a potential use of cassava feedstock for ethanol production. Thus, harnessing cassava for food as well as ethanol production is deemed feasible. Such a system would, however, require supportive policies to acquire a balance between food security and fuel.