Characterization of genetic variation among Ethiopian barley (Hoerdeum vulgare L.) genotypes

Barley (Hordeum vulgare L.) is a major cereal crop in Ethiopia and accounts for 8% of the total cereal production based on cultivation area. Farmers may face unpredictable rainfall and drought stress patterns such as terminal drought where rainfall ends before crops have completed their physiological maturity, which then poses a challenge to crop production. The absence of efficient weather forecasts and a lack of efficient communication channels for resource-poor farmers ask for the development of varieties that are robust to such irregularities. A goal of plant breeding for areas with variable climate and limited resources for agricultural inputs is to produce stable varieties with higher average yield across diverse environments and growing conditions. Genotype by environment (G x E) interactions, however, frequently interfere with the selection of widely adapted genotypes. Knowledge about the yield stability of existing Ethiopian barley varieties and landraces under changing environmental variables is important for the future development of barley varieties with high and stable yields. In addition, yield components are quantitative with substantial influence of environment. Yield components also compensate each other in trait correlation dynamics. Since grain yield is a more complex trait than its components, environmental effects and genotype-by-environment (G x E) interactions for grain yield are stronger than for its components. Therefore, indirect selection of yield components may be more efficient than selection on grain yield per se to obtain higher yielding and stable cultivars. A study, therefore, was initiated to 1) characterize the response of a diverse set of barley genotypes to different locations and variable planting dates and identify genotypes with wide adaptation and stable performance and/or genotypes with specific altitude and planting date 2) determine traits that contribute to high and stable yields across a range of different environments and planting dates 3) determine the pattern of population structure and genetic parameters among genotypes conserved in Ethiopian and German gene banks in for different period of time as well as currently growing in farmers field. In order to meet the objectives 18 genotypes were tested at four different sowing dates with 15 days interval in different locations (Ambo and Jimma) and years (2012 and 2013). The tested genotypes revealed a wide variation for both static and dynamic yield stability measures. Compared to improved cultivars, farmers landraces displayed higher average static stability and similar superiority indices (dynamic stability). These landraces are therefore a source of germplasm for breeding resilient barley cultivars. Staggered planting proved to be a useful method for evaluating genotype stability across environmental factors beyond location and season. In addition, we also noticed that compensatory relationship between kernels per spike and thousand kernel weight in landraces. Kernels per spike and number of fertile tillers can be proposed as robust traits in barley breeding for a wider adaptation as they had significant and consistent positive total effects on grain yield. In order to determine the pattern of population structure and genetic parameters among genotypes of different origin and gene banks, DNA samples were subject to double-digest by ApeK1 and Hind III enzymes. After sequencing, raw read was checked for major quality parameters. Sequence reads were then filtered for sequencing artifacts and low quality reads (preprocessing). The pre-processed reads were aligned to genome of barley cultivar Morex to call SNPs. Values of observed heterozygosity (Ho) ranged from 0.250 to 0.337 and were higher than the expected heterozygosity (He) that varied from 0.180 to 0.242 in genotypes of all origins. The inbreeding coefficient (FIS) values that ranged between -0.240 and -0.639 across the regions were also higher and negative suggesting existence of excess outcrossing than expected. Based on the inferred clusters by the ADMIXTURE, high Fst values were observed between clusters suggesting high genetic differentiation among the genotypes tested though differentiation was not based on location. In addition, genetic differentiation computed based on the predetermined location, altitude and source of genotypes suggested weak differentiation among the groups. These results indicate that, in Ethiopia, barley genetic variation between regions and altitudes were less pronounced than within region and altitude variations. This calls for the germplasm collection strategies to be cautious in considering location and altitude as a main factor of variation thus strategies should focus on exploiting the within region variation also for better germplasm conservation and utilization. The static yield stability of landrace has to be utilized by breeders for their wider recommendations for those farmers who cannot afford use of farm inputs and specific cultivars. In addition, the relative robustness as well as plasticity of traits sorted by the current study can be incorporated in the breeding strategy of barley in Ethiopia.Gerste (Hordeumvulgare L.) ist eine bedeutende Getreideart in Äthiopien und macht 8% der gesamten Getreideerzeugung, in Bezug auf die Anbaufläche, aus. Unvorhersehbaren Regen- und Dürreereignisse, wie z.B. Dürren, bei denen der Regen endet, bevor die Gerste ihre physiologische Reife erreicht hat, stellen die Pflanzenproduktion in Äthiopien vor große Herausforderungen. Der mangelnde Zugang für Landwirte zu effizienten Wettervorhersagesystemen und Kommunikationskanäle erfordern die Entwicklung von Sorten, die extremen Wetterereignissengegenüber tolerant sind. Ein Ziel der Pflanzenzüchtung, für Gebiete mit Extremwetterereignissen und begrenzten Ressourcen für landwirtschaftliche Betriebsmittel, ist die Erzeugung umweltstabiler Sorten mit höherem Durchschnittsertrag in unterschiedlichen Umwelten und unter verschiedenen Wachstumsbedingungen. Genotyp - Umwelt Interaktionen (G x E) erschweren jedoch häufig die Auswahl von Genotypen die sich an unterschiedliche Umweltbedingungen anpassen können. Das Wissen über die Ertragsstabilität bekannter äthiopischer Gerstensorten und Landsorten, unter sich ändernden Umweltbedingungen, ist für die zukünftige Entwicklung von Gerstensorten mit hohen und stabilen Erträgen wichtig. Darüber hinaus sind Ertragskomponenten, quantitative Merkmale,die stark von der Umwelt beeinflusst werden. Da der Kornertrag einkomplexeres Merkmal ist als die ertragsbestimmenden Komponenten, sind die Umwelteinflüsse und die Wechselwirkungen zwischen Genotyp und Umwelt (G x E) für denKornertrag stärker als für Komponenten die den Kornertrag bestimmen. Daher kann eine indirekte Selektionanhand vonErtragskomponenten effizienter sein als die per se Selektion auf Basis des Kornertrags, um Ertragreichere und stabilere Sorten zu erhalten. Daher wurde diese Studie initiiert um 1) die Reaktion verschiedener Gerstengenotypen auf verschiedene Standorte und Aussaattermine zu beurteilen und Genotypen mit einerweiten Anpassung und stabilen Leistung zu identifizieren, 2) Merkmale zu bestimmen, die zu hohen und stabilen Erträgen in einer Reihe unterschiedlicher Umwelten beitragen, 3) die Populationsstruktur und genetische Parameter von äthiopischen und deutschen Genbankakzessionen, sowie aktuellen Gerstensorten, zu erfassen. Um diese Ziele zu erreichen, wurden 18 Genotypen an vier verschiedenen Aussaatterminen im Abstand von 15 Tagen an verschiedenen Orten (Ambo und Jimma) und Jahren (2012 und 2013) getestet. Die getesteten Genotypen zeigen eine große Variation, sowohl für die statische als auch für die dynamische Messung der Ertragsstabilität. Im Vergleich zu aktuellen Sorten zeigen die Landrassen der Landwirte eine höhere durchschnittliche statische Stabilität und eine ähnliche dynamische Stabilität. Diese Landrassen sind daher ein wertvoller Genpool für die Züchtung von widerstandsfähigen Gerstensorten. Die zeitversetzteAussaat erwies sich als nützliche Methode zur Beurteilung der Stabilität von Genotypen über Umweltfaktoren hinweg. Darüber hinaus haben wir auch eine kompensatorische Beziehung zwischen Kornanzahl pro Ähre und Tausendkorngewicht in Landrassen festgestellt. Die Kornanzahl pro Ähre und die Anzahl der fruchtbaren Bestockungstriebeerwiesen sich als robuste Merkmale für eine breitere Adaption an unterschiedliche Umweltbedingungen, da sie einen signifikanten und beständig, positiven Effekt auf den Kornertrag haben. Um die Populationsstruktur und genetische Parameter zwischen Genotypen verschiedener Herkunft und Genbanken zu bestimmen, wurden DNA-Proben mit ApeK1- und HindIII-Enzymenbearbeitet. Nach der Sequenzierung wurde die Rohdaten auf wichtige Qualitätsparameter überprüft. Sequenzen wurden gefiltert, um Artefakte zu eliminieren und Sequenzen mit geringer Qualität zu entfernen (Vorverarbeitung). Die vorverarbeiteten Sequenzen wurden an dem Genom der Gerstensorte Morexausgerichtet, um SNPs zu identifizieren. Die Werte der beobachteten Heterozygosität (Ho) lagen im Bereich von 0,250 bis 0,337 und waren höher als die erwartete Heterozygosität (He), die in der gesamten Population von 0,180 bis 0,242 variierte. Die Werte für den Inzuchtkoeffizienten (FIS), liegen zwischen -0,240 und -0,639, sind ebenfalls höher und negativ, was auf eine übermäßige Auskreuzung als erwartet hindeutet. Basierend auf den von ADMIXTURE abgeleiteten Clustern wurden hohe Fst-Werte zwischen den Clustern beobachtet. Dies lässt auf eine hohe genetische Differenzierung zwischen den getesteten Genotypen schließen, jedoch ließ sich keine ortsabhängige Differenzierung feststellen. Darüber hinaus deutet die genetische Differenzierung, die basierend auf Ort, Höhe und Sortentyp berechnet wurde, auf eine schwache Differenzierung zwischen den Gruppen hin. Diese Ergebnisse zeigen, dass in Äthiopien die genetische Variation der Gerste zwischen Regionen und Höhenlagen weniger ausgeprägt war als innerhalb von Region und Höhenlagen. Dies erfordert, dass Strategien zur Sammlung von genetischen Ressourcen sich nicht nur an Standort und Höhenlage als Hauptvariationsfaktor ausrichten. Vielmehr sollten sich Strategien zum Erhalt des Gersten-Genpools darauf konzentrieren, die Variationen innerhalb der Regionenund Höhenlagen zu nutzen um die genetische Diversität aufrecht zu erhalten. Die statische Ertragsstabilität der Landsortensollte von Züchtern für ihre Empfehlungen für Landwirte berücksichtigt werden. Darüber hinaus kann empfohlen werden die relative Robustheit sowie die Plastizität von Merkmalen, die durch die aktuelle Studie identifiziert wurden, in die Züchtungsstrategie von Gerste in Äthiopien einzubeziehen

Combining Ability Analysis of Maize Inbred Lines in Ethiopia

The study was initiated to estimate combining ability of maize inbred lines and crosses using line by tester analysis. Fifty entries consists 48 F1 single crosses developed from 24 inbred lines and 2 testers using line x tester design and two commercial check hybrids used in the study. The experiment was conducted using alpha lattice design with two replications. Analysis of variance revealed existence of significant genetic variation among genotypes for all studied traits except for plant aspect (PA). Location x entry interaction for most of the traits was not significant which suggests hybrid performance was consistent across tested locations. Line x tester analysis of variance showed that mean squares due to GCA of lines were significant (p< 0.01 or p< 0.05) for all studied traits. Mean squares of tester GCA and SCA were significant for most of studied traits. This indicates that both additive and non-additive gene effects had contributed for the variation of the crosses. However, higher proportional contribution of additive gene action for all studied traits was obtained. Several lines and crosses were identified as good general and specific combiners for yield and yield related traits. Lines L23, L11, L15 and crosses L2xT1, L3xT1, L8xT1, L11xT1, L23xT1 and L13xT2 were found to be good general and specific combiners, respectively. In conclusion, the stated inbred lines with desirable gca effects and cross combinations with desirable sca effects for grain yield and yield related traits could be used as useful genetic material

A Review on the Cooking Attributes of African Yam Bean (<em>Sphenostylis stenocarpa</em>)

African yam bean, an underutilized legume usually cultivated for its edible tubers and seeds, is known for its nutrition-rich qualities; however, the crop’s level of consumption is low. The underutilization of the crop could be attributed to several constraints, including long cooking hours of up to 24 hours. Cooking time is an important food trait; it affects consumers’ choices, nutrients content, and anti-nutrient conditions. Additionally, foods requiring long cooking hours are non-economical in terms of energy usage and preparation time. The prolonged cooking time associated with AYB places enormous limitations on the invaluable food security potentials of the crop. Therefore, the availability of AYB grains with a short cooking time could lift the crop from its present underused status. To efficiently develop AYB grains with reduced cooking time, information on the crop’s cooking variables is a prerequisite. This review presents available information on variations in cooking time, cooking methods, and processing steps used in improving cooking time and nutrient qualities in AYB. Likewise, the review brings to knowledge standard procedures that could be explored in evaluating AYB’s cooking time. This document also emphasizes the molecular perspectives that could pilot the development of AYB cultivars with reduced cooking time

Assessment of Cassava Utilization Patterns, Postharvest Handling Practices, and Productivity Influencing Factors in South and Southwest Ethiopia

Cassava (Manihot esculenta Crantz) is mainly produced to supplement food security by providing food for smallholder farmers year round. However, its production is constrained by various factors. Thus, the aim of this research was to assess cassava utilization patterns, postharvest handling practices, and the factors that influence productivity. Data were gathered from primary and secondary sources, and a multistage sampling procedure was used to select 200 HHs. A multiple regression model and descriptive statistics were used to analyze the data. The regression model revealed that the education level, family size, land holding size, cropping system, crop rotation, earthing up rate, maturity, variety type, training, and plant population variables were significantly and positively correlated with cassava productivity. This implies that if any of these variables increases, cassava productivity will increase while the other variables remain constant. Topography and pest variables showed a significant negative correlation, indicating that an undulating topography or being attacked by pests could reduce cassava productivity by 60.00%. The descriptive statistics results for the utilization proportion showed that 51.87% of the farmers utilized for home consumption, 43.68% for the market, and 4.26% for animal feed. The consumption pattern indicated that 46.50% was boiled roots, 15.00% was flour cooked, and 38.50% was boiled roots and flour cooked. As postharvest handling practices showed, 10.00% of the farmers immediately processed to powder, 18.00% immediately processed to sliced (chips), 61.00% left them to root in the soil, and 11.00% did nothing. This indicates that the farmers’ consumption patterns and processing methods are very traditional. Therefore, the study suggested that the farmers’ different practices should be further supported by research through the generation of multiple food forms, postharvest handling practices, and production technology. Proper attention should also be given to address the identified productivity-influencing factors as well as postharvest handling practices. These could sustain the farming system of the crop and help to increase cassava productivity for smallholder farmers

AMMI and GGE Biplot Analyses for Mega Environment Identification and Selection of Some High-Yielding Cassava Genotypes for Multiple Environments

Cassava (Manihot esculenta Crantz) is a staple food and generates income for smallholder farmers in southern Ethiopia. The performance of cassava genotypes varies in different growing environments; thus, the evaluation of genotypes tested in various environments plays an essential role in developing strategies to delineate environments, explore unstable genotypes in target environments, and identify stable genotypes for multiple environments. In this regard, there needs to be more information on the identification of mega-environments and stable genotypes with high yields for wide adaptation. Thus, this study aimed to identify mega-environment and high-yielding cassava genotypes for multiple environments using AMMI and GGE biplots. A total of 25 genotypes were evaluated in six environments using a RCBD during the 2020–2021 cropping season. The AMMI analysis of variances revealed that environments, genotypes, and genotype-environment interaction had a significant (P≤0.001) influence on cassava fresh storage root yield (t·ha−1), showing genetic variability among genotypes by changing environments. The genotype-by-environment interaction showed a 61.36% contribution to the total treatment SS variation, while the environment and genotype effects explained 28.16% and 10.48% of the total treatment SS, respectively. IPCA1 and IPCA2 accounted for 33.42% and 23.5% of the GE interactions SS, respectively. The GGE biplot showed that the six environments used in this study were delineated into three mega-environments, namely, the first (Tarcha and Disa), the second (Wara and Areka), and the third (Jimma and Bonbe). Those mega-environments could be helpful for genotype evaluation and effective breeding. The GGE biplot indicated that the vertex genotypes were G16, G17, and G25. They are regarded as specifically adapted genotypes since they are more responsive to environmental change. The GGE biplot also revealed that Tarcha was ideal, having the most discriminating and representative environment, while G10 was the ideal and the overall winning genotype for the current study. Moreover, the genotypes G10 and G14 were identified as being the most stable, with a higher fresh storage root yield than the grand mean. Thus, G10 and G14 were selected as superior genotypes that could be promoted to advanced yield trials to develop stable cultivars with better storage root yield of cassava

Phenotypic Characterization, Evaluation, and Classification of Cassava (Manihot esculenta Crantz) Accessions in Ethiopia

Cassava has a crucial role in benefiting smallholder farmers as the main food and income source in southern Ethiopia. Characterization accessions are crucial for assessing variation, classifying, and identifying desirable accessions for crop improvement and conservation. In this regard, there needs to be more information on the morphological characterization and classification cassava accessions. Thus, the aim of this research was to systematically characterize, evaluate, and classify cassava accessions using qualitative characters to provide useful information for breeding program and conservation. A total of 64 accessions were planted using a simple lattice design during the 2020-2021 cropping season. Thirty qualitative data were collected at 3, 6, 9, and 18 months after planting and analyzed using the SAS and R-software packages. The high variable characteristics were the shape of the central leaflet, petiole color, leaf retention, branching habit, the color of the stem epidermis, the color of the stem exterior, the external color of the storage root, and the color of the root pulp towards frequency distribution analysis. The Shannon–Weaver diversity index ranged from 0.24 to 1.47, with an overall mean of 0.84. The first three dimensions in the multiple correspondent method explained approximately 39.39% of the total variation, with Dim 1 accounting for 20.77% and Dim 2 accounting for 9.98%, while petiole color and texture of the root epidermis were the leading contributors to the total variation, respectively. In clustering analysis, 64 accessions were classified into 4 clusters of varying sizes. The distribution of accessions in each cluster revealed that 52 accessions were in cluster I, 6 in cluster II, 5 in cluster III, and 1 in cluster IV. Each cluster was varied by a major group characteristic that it represented. Furthermore, the study identified the desirable accessions for desired storage root characteristics such as root constrictions, the external color of the storage root, the color of root pulp, the color of the root cortex, and cortex peeling tendency. In conclusion, the various analyses performed indicated the existence of sufficient genetic variability for the characteristics evaluated, which could be attributed to the dissimilar genetic backgrounds of the evaluated accessions. Thus, these could be utilized for breeding work and conservation

Genetic variability and divergence analysis in cassava (Manihot esculenta Crantz) accessions for storage root yield and other agronomic characters

Understanding the character of genetic variability and diversity is crucial to enhancing selection efficiency in plant breeding programs. This study aimed to estimate the magnitude of genetic variability and diversity among 64 accessions based on quantifiable characteristics to provide valuable information for breeding programs and conservation. The 64 accessions were evaluated in the two locations using an 8x8 lattice design. Analysis of variance showed a significant difference among the tested accessions for the characters studied, indicating the presence of variability and the possibility of character selection and improvement. The highest genotypic coefficient of variation revealed for the aboveground biomass, storage root yield, and storage root number indicates that the possibility of selection of those characters might be effective for their improvement. High heritability along with high genetic advance as a percent of the mean was observed for number of storage roots, length of storage roots, storage root yield, aboveground biomass, and harvest index, suggesting the existence of additive gene effects. The first three principal components explained 49 % of the total variation, with PC I accounting for 22.5 %, PC II for 15.6 %, and PC III for 10.9 % of the total variation. The 64 accessions were grouped into five clusters, and the number of accessions in each cluster was varied from 3 in cluster V to 31 in cluster II. The maximum inter-cluster diversity was found between IV and V (82.60), while cluster V (6.12) had the highest intra-cluster diversity. Accessions G8, G16, G40, G43, G46, G53, and G57 have been identified as the best candidates for the breeding program in terms of storage root yield. The various analyses performed in the present study confirmed the presence of wide variability &amp; diversity among accessions, which could be used to develop cassava cultivars with optimal storage root yield through effective selection

Genomic selection in tropical perennial crops and plantation trees: a review

International audienceTo overcome the multiple challenges currently faced by agriculture, such as climate change and soil deterioration, more efficient plant breeding strategies are required. Genomic selection (GS) is crucial for the genetic improvement of quantitative traits, as it can increase selection intensity, shorten the generation interval, and improve selection accuracy for traits that are difficult to phenotype. Tropical perennial crops and plantation trees are of major economic importance and have consequently been the subject of many GS articles. In this review, we discuss the factors that affect GS accuracy (statistical models, linkage disequilibrium, information concerning markers, relatedness between training and target populations, the size of the training population, and trait heritability) and the genetic gain expected in these species. The impact of GS will be particularly strong in tropical perennial crops and plantation trees as they have long breeding cycles and constrained selection intensity. Future GS prospects are also discussed. High-throughput phenotyping will allow constructing of large training populations and implementing of phenomic selection. Optimized modeling is needed for longitudinal traits and multi-environment trials. The use of multi-omics, haploblocks, and structural variants will enable going beyond single-locus genotype data. Innovative statistical approaches, like artificial neural networks, are expected to efficiently handle the increasing amounts of heterogeneous multi-scale data. Targeted recombinations on sites identified from profiles of marker effects have the potential to further increase genetic gain. GS can also aid re-domestication and introgression breeding. Finally, GS consortia will play an important role in making the best of these opportunities

Genome properties of key oil palm (Elaeis guineensis Jacq.) breeding populations

International audienceA good knowledge of the genome properties of the populations makes it possible to optimize breeding methods, in particular genomic selection (GS). In oil palm (Elaeis guineensis Jacq), the world's main source of vegetable oil, this would provide insight into the promising GS results obtained so far. The present study considered two complex breeding populations, Deli and La Me, with 943 individuals and 7324 single-nucleotide polymorphisms (SNPs) from genotyping-by-sequencing. Linkage disequilibrium (LD), haplotype sharing, effective size (N-e), and fixation index (F-st) were investigated. A genetic linkage map spanning 1778.52 cM and with a recombination rate of 2.85 cM/Mbp was constructed. The LD at r(2)=0.3, considered the minimum to get reliable GS results, spanned over 1.05 cM/0.22 Mbp in Deli and 0.9 cM/0.21 Mbp in La Me. The significant degree of differentiation existing between Deli and La Me was confirmed by the high F-st value (0.53), the pattern of correlation of SNP heterozygosity and allele frequency among populations, and the decrease of persistence of LD and of haplotype sharing among populations with increasing SNP distance. However, the level of resemblance between the two populations over short genomic distances (correlation of r values between populations >0.6 for SNPs separated by 40% for haplotypes <3600 bp/0.20 cM) likely explains the superiority of GS models ignoring the parental origin of marker alleles over models taking this information into account. The two populations had low N-e (<5). Population-specific genetic maps and reference genomes are recommended for future studies