Genetic variability among some miscellaneous legumes for yield-related traits

Twenty-four (24) accessions of seven (7) legumes were planted to determine the relationship in their Agro-morphology and to estimate the heritability of plant character, using Randomize Complete Block Design (RCBD). The experiment was carried out at Teaching and Research Farms, Federal university of Agriculture, Abeokuta, Nigeria. Collection of data was carried out on plant height, stem girth, leaf length, leaf breadth, stem colour, flower colour, leaf shape, 100-seed weight, number of pod per plant, number of seed per pod and pod length. Data collected were subjected to Analysis of variance, inter-character association among the plant characters evaluated was determined using Pearson coefficient correlation analysis, while relatedness was done using dengrogram. Data analyses show significant effect among all the legumes indicating that there is possibility for selection. All plant characters evaluated show high heritability with genotypic variance higher than environmental effect. Number of pods per plant and number of seeds per pod were negatively correlated with all traits studied. Hundred seed weight was positively correlated with all traits studied except seedling emergence and number of pods per plant. The linkage clusters shows similarities at various percentage among the twenty-four accessions. All the accessions were distinct from each other at 0.0, while at a distance of 0.50 levels they formed four clusters. Legumes with high yield potential can be considered for selection, while characters with high heritability estimate can be used as criteria for selection during breeding programs. Accessions TVR-28, TVR-39 and TVR-86 with high number of seed per pod and TVA-1 and TVA-2 for pods per plant could be considered during selection and further breeding work.Keywords: Legumes, diversity, relatedness, dendogra

Genetic diversity in Amaranth (Amaranthus spp.) based on phenotypic and RAPD markers

Genetic similarities, which can be detected with phenotypic and molecular markers, are important for effective use of available germplasm. It provides information on genetic diversity for reliable gene recombination. Thirty accessions of amaranth were assessed for variation with 15 phenotypic characters and 10 random amplified polymorphic DNA (RAPD) primers. Significant (p < 0.05) phenotypic variation was observed among the accession at the vegetative phase and most of the accessions had leaves with green pigmentation. Sink factor such as leaf, stem and root weights, and dry matter, were homogenous traits which contributed significantly to diversity among the accessions. The RAPD primers produced 115 bands with 88 (77%) polymorphic loci. The DNA classification between some of the accessions was similar to the phenotypic diversity. Information on phenotypic diversity and traits contributing to the diversity can be used deductively with genetic diversity to guide effective hybrid program.Keywords: Accession, genetic divergence, Mahanalobis, oligonucleotide, polymorphism, UPGM

Genetic diversity in some Nigerian kenaf (Hibiscus cannabinus L.) genotypes as assessed by agro-morphological traits and seed protein markers

Identifying and assessing genetic diversity in kenaf (Hibiscus cannabinus L.) using agromorphological markers is problematic, thus, necessitating the use of biochemical markers. Thirty five kenaf genotypes were evaluated for genetic diversity using 13 agromorphological characters and seed proteins. The field experiment was laid out in a Randomized Complete Block Design with three replications; the data were subjected to Principal Component Analysis (PCA) and Cluster Analysis (CA) to group the genotypes. The observed genetic diversity among the genotypes based on Sodium dodecyl sulphate polyacrylamide gel electrophoresis (SDS-PAGE) of seed proteins was presented in the form of a dendrogram generated by the UPGMA cluster analysis. The relative effectiveness of the two types of markers in assessing the diversity among the genotypes was investigated. The CA grouped the 35 genotypes into eight clusters; the PCA revealed that the first three principal components accounted for 66.60% of the total variation among the genotypes. Plant height, stalk height, internode distance, number of seeds/pod, basal stem diameter, number of pods/plant, pod length and seed yield/plant were identified as traits that best described the genotypes. The seed protein dendrogram, in addition to grouping the 35 genotypes into four major clusters, was able to identify duplicates within the population.Keywords: Biochemical markers, principal components analysis, dendrogram, duplicate

Enhancing drought tolerance and Striga hermonthica resistance in maize using newly derived inbred lines from the wild maize relative, Zea diploperennis

Open Access Journal; Published online: 18 Jan 2021Recurrent drought and Striga hermonthica (Del.) Benth parasitism constrains maize production in sub-Saharan Africa (SSA). Transfer of resistance genes from wild relatives can improve resistance to drought and Striga in tropical maize. The objectives of this study were to (i) determine the combining ability of 12 extra-early yellow maize inbreds derived from Zea diploperennis and tropical maize germplasm; (ii) classify the inbreds into heterotic groups using heterotic grouping based on the general combining ability (GCA) of multiple traits (HGCAMT) method; (iii) examine hybrid performance under contrasting environments; and (iv) examine the stability of hybrid combinations involving the inbreds. Sixty-six diallel crosses involving the inbreds plus four checks were evaluated for two years under drought, Striga-infested and rainfed environments in Nigeria. Significant differences (p < 0.05) were observed for the effects of genotype, environment, genotype × environment, GCA and specific combining ability (SCA) on grain yield and other measured traits. Inbred lines such as TZdEEI 7 × TZEEI 63 derived from Z. diploperennis and tropical germplasm exceeded the checks by a range of 28 to 41%. Across environments, the hybrid TZdEEI 1 × TZdEEI 7, which was derived from Z. diploperennis, was the highest-yielding with a grain yield of 4302 kg ha−1. The results revealed the predominance of GCA over SCA effects for most measured traits, suggesting that additive gene action governed the inheritance of Striga resistance and drought tolerance related traits in the inbreds. The 12 inbreds were classified into three heterotic groups, while TZEEI 79 and TZdEEI 7 were identified as inbred testers and TZdEEI 7 × TZEEI 12 as a single-cross tester across environments. Hybrid TZdEEI 9 × TZEEI 79 was the highest-yielding and most stable. Other promising hybrids were TZdEEI 7 × TZEEI 79, TZdEEI 1 × TZdEEI 7 and TZdEEI 12 × TZEEI 95. These hybrids should be extensively tested on-farm for potential commercialization in SSA. Overall, our results highlighted the importance of harnessing beneficial alleles from wild relatives of maize for improvement of resistance to Striga and tolerance to drought in adapted maize germplasm

RELATIVE DISCRIMINATING POWERS OF GGE AND AMMI MODELS IN THE SELECTION OF TROPICAL SOYBEAN GENOTYPES

Selection of crops is preceded by multi-locational testing in plant breeding; however, it becomes difficult for breeders to determine which genotypes should be selected in the presence of genotype by environment (GEI). Six genotypes of soybean ( Glycine max (L.) Merr.) were evaluated at ten locations in Nigeria for grain yield and stability. The analysis of variance revealed significant (P 640.05) GEI effect. Mean grain yield of the soybean genotypes ranged from 1148 kg ha-1 for genotype M351 to 1584 kg ha-1 for TGx 1448-2E. Ilorin in the southern guinea savanna of Nigeria was the most variable with high interaction principal component axes (IPCA); while Bauch in the northern guinea savanna was identified as more stable location in evaluating the soybean genotype. Mega-environments and the best yielding soybean genotypes in each mega-environment were revealed by the GGE biplot analysis. Furthermore, TGx 1448-2E and TGx 1440-1E, were established as the most promising, and stable genotypes across the test locations. Stability model of GGE biplot was superior, effective and informative in mega-environment analysis compared to AMMI analysis.La s\ue9lection des cultures est pr\ue9c\ue9d\ue9e de tests multilocaux en am\ue9lioration des plantes; cependant, il appara\ueet difficile pour les am\ue9liorateurs de d\ue9terminer quels types de g\ue9notypes s\ue9lectionner en pr\ue9sence du g\ue9notype x environnement (GEI). Six g\ue9notypes du Soja ( Glycine max (L.) Merr.) \ue9taient \ue9valu\ue9s dans dix milieux au Nigeria pour le rendement en grains et la stabilit\ue9. L\u2019analyse de la variance a r\ue9v\ue9l\ue9 un effet significatif (P 64 0.05) du GEI. Le rendement moyen en grains des g\ue9notypes du soja variait de 1148 kg ha-1 pour le g\ue9notype M351 \ue0 1584 kg ha-1 pour TGx 1448-2E. Ilorin au sud de la savanne guin\ue9enne au Nigeria \ue9tait le plus variable avec une interaction \ue9lev\ue9e des axes de la composante principale (IPCA); pendant que Bauch dans le nord de la savanne guinn\ue9enne \ue9tait identifi\ue9 comme milieu le plus stable dans l\u2019\ue9valuation du g\ue9notype du soja. Les Mega-environments et le meilleur g\ue9notype du soja du point de vue rendement dans chaque mega-environment \ue9taient r\ue9v\ue9l\ue9s par l\u2019analyse du biplot. En plus, TGx 1448-2E et TGx 1440-1E, \ue9taient jug\ue9s les plus promettants et g\ue9notypes stables \ue0 travers le test de milieu. Le mod\ue8le de stabilit\ue9 du biplot GGE \ue9tait sup\ue9rieur, effective et informative dans l\u2019analyse m\ue9ga-environmentale en comparaison avec l\u2019analyse du AMMI

Genome-wide association studies of Striga resistance in extra-early maturing quality protein maize inbred lines

Open Access JournalIdentification of genes associated with Striga resistance is invaluable for accelerating genetic gains in breeding for Striga resistance in maize. We conducted a genome-wide association study to identify genomic regions associated with grain yield and other agronomic traits under artificial Striga field infestation. One hundred and forty-one extra-early quality protein maize inbred lines were phenotyped for key agronomic traits. The inbred lines were also genotyped using 49,185 DArTseq markers from which 8,143 were retained for population structure analysis and genome wide-association study. Cluster analysis and population structure revealed the presence of 3 well-defined genetic groups. Using the mixed linear model, 22 SNP markers were identified to be significantly associated with grain yield, Striga damage at 10 weeks after planting, number of emerged Striga plants at 8 and 10 weeks after planting and ear aspect. The identified SNP markers would be useful for breeders for marker-assisted selection to accelerate the genetic enhancement of maize for Striga resistance in sub-Saharan Africa after validation

RELATIVE DISCRIMINATING POWERS OF GGE AND AMMI MODELS IN THE SELECTION OF TROPICAL SOYBEAN GENOTYPES

Selection of crops is preceded by multi-locational testing in plant breeding; however, it becomes difficult for breeders to determine which genotypes should be selected in the presence of genotype by environment (GEI). Six genotypes of soybean ( Glycine max (L.) Merr.) were evaluated at ten locations in Nigeria for grain yield and stability. The analysis of variance revealed significant (P ≤0.05) GEI effect. Mean grain yield of the soybean genotypes ranged from 1148 kg ha-1 for genotype M351 to 1584 kg ha-1 for TGx 1448-2E. Ilorin in the southern guinea savanna of Nigeria was the most variable with high interaction principal component axes (IPCA); while Bauch in the northern guinea savanna was identified as more stable location in evaluating the soybean genotype. Mega-environments and the best yielding soybean genotypes in each mega-environment were revealed by the GGE biplot analysis. Furthermore, TGx 1448-2E and TGx 1440-1E, were established as the most promising, and stable genotypes across the test locations. Stability model of GGE biplot was superior, effective and informative in mega-environment analysis compared to AMMI analysis.La sélection des cultures est précédée de tests multilocaux en amélioration des plantes; cependant, il apparaît difficile pour les améliorateurs de déterminer quels types de génotypes sélectionner en présence du génotype x environnement (GEI). Six génotypes du Soja ( Glycine max (L.) Merr.) étaient évalués dans dix milieux au Nigeria pour le rendement en grains et la stabilité. L’analyse de la variance a révélé un effet significatif (P ≤ 0.05) du GEI. Le rendement moyen en grains des génotypes du soja variait de 1148 kg ha-1 pour le génotype M351 à 1584 kg ha-1 pour TGx 1448-2E. Ilorin au sud de la savanne guinéenne au Nigeria était le plus variable avec une interaction élevée des axes de la composante principale (IPCA); pendant que Bauch dans le nord de la savanne guinnéenne était identifié comme milieu le plus stable dans l’évaluation du génotype du soja. Les Mega-environments et le meilleur génotype du soja du point de vue rendement dans chaque mega-environment étaient révélés par l’analyse du biplot. En plus, TGx 1448-2E et TGx 1440-1E, étaient jugés les plus promettants et génotypes stables à travers le test de milieu. Le modèle de stabilité du biplot GGE était supérieur, effective et informative dans l’analyse méga-environmentale en comparaison avec l’analyse du AMMI