Genetic Variation and Genotype × Environment Interaction for Yield and Other Agronomic Traits in Cassava in Nigeria

2007 ◽  
Vol 99 (4) ◽  
pp. 1137-1142 ◽  
Author(s):  
C. N. Egesi ◽  
P. Ilona ◽  
F. O. Ogbe ◽  
M. Akoroda ◽  
A. Dixon
Keyword(s):  
Genetic Variation ◽  
Agronomic Traits ◽  
Environment Interaction ◽  
Genotype Environment Interaction

scholarly journals Canaryseed (Phalaris canariensis L.) accessions from nineteen countries show useful genetic variation for agronomic traits

2011 ◽  
Vol 91 (1) ◽  
pp. 37-48 ◽  
Author(s):  
M. Cogliatti ◽  
F. Bongiorno ◽  
H. Dalla Valle ◽  
W J Rogers
Keyword(s):  
Genetic Variation ◽  
Grain Yield ◽  
Harvest Index ◽  
Agronomic Traits ◽  
Grain Weight ◽  
Environment Interaction ◽  
Grain Number ◽  
Harvest Maturity ◽  
Phalaris Canariensis ◽  
Late Sowing

Fifty-seven accessions of canaryseed (47 populations and 10 cultivars) from 19 countries were evaluated for agronomic traits in four field trials sown over 3 yr in the province of Buenos Aires, Argentina. Genetic variation was found for all traits scored: grain yield and its components (grain weight, grain number per square meter, grain number per head and head number per square meter), harvest index, percent lodging, and phenological characters (emergence to heading, emergence to harvest maturity and heading to harvest maturity). Although genotype × environment interaction was observed for all traits, the additive differences between accessions were sufficient to enable promising breeding materials to be identified. Accessions superior in performance to the local Argentinean population, which in general gave values close to the overall mean of the accessions evaluated, were identified. For example, a population of Moroccan origin gave good yield associated with elevated values of the highly heritable character grain weight, rather than with the more commonly observed grain number per square meter. This population was also of relatively short stature and resistant to lodging, and, although it performed best when sown within the normal sowing date, tolerated late sowing fairly well. Other accessions were also observed with high grain weight, a useful characteristic in itself, since large grains are desirable from a quality point of view. Regarding phenology, the accessions showed a range of 160 degree days (8 calendar days in our conditions) in maturity, which, while not large in magnitude, may be of some utility in crop rotation management. Some accessions were well adapted to late sowing. Grain yield in general was strongly correlated with grain number per square meter. Principal components analysis (PCA) carried out for all characteristics provided indications of accessions combining useful characteristics and identified three components that explained approximately 70% of the phenotypic variation. Furthermore, a second PCA plus regression showed that approximately 60% of the variation in grain yield could be explained by a component associated with harvest index and grain number per square meter. Pointers were provided to possible future breeding targets.Key words: Phalaris canariensis, canaryseed, accessions, yield, phenology, genetics, breeding

Inheritance of resistance to Mal de Río Cuarto (MRC) disease in Zea mays (L.)

2002 ◽  
Vol 139 (1) ◽  
pp. 47-53 ◽  
Author(s):  
M. A. DI RENZO ◽  
N. C. BONAMICO ◽  
D. D. DÍAZ ◽  
J. C. SALERNO ◽  
M. M. IBAÑEZ ◽  
...  
Keyword(s):  
Zea Mays ◽  
Plant Height ◽  
Disease Severity ◽  
Agronomic Traits ◽  
Severity Index ◽  
Point Estimate ◽  
Environment Interaction ◽  
Disease Severity Index ◽  
Evaluation Activity ◽  
Genotype Environment Interaction

No genetic estimates for resistance to Mal de Río Cuarto (MRC) disease in Zea mays (L.) are currently available in the literature. Therefore, the objectives of this investigation were (i) to estimate the variance and heritability of partial resistance to MRC disease and of other agronomic traits from maize families and (ii) to examine associations among MRC disease severity values across different environments and between MRC and other agronomic traits. These estimations, obtained in an endemic area, could contribute to the design of efficient enhancement programmes and evaluation activity for the improvement of MRC resistance. The research was conducted by testing 227 F3 derived-lines from a cross between a susceptible dent line, Mo17, and a partially resistant flint line, BLS14, for MRC disease at two Río Cuarto locations in each of 2 years. The resistance of the lines, measured with a disease severity index (DSI), was normally distributed across environments. Genotypic variances were highly significant on all scoring environments. Estimates of genotype–environment interaction were also significant, suggesting that certain genotypes have little stability over different environments. For disease severity index all estimates demonstrated moderate heritabilities ranging from 0.44 to 0.56 and were similar when based on individual environments or across environment. Confidence interval widths ranged from 34.88 to 50.30% as large as the heritability point estimate. The correlations between environments were small enough to indicate that families did not rank similarly in individual environments for MRC resistance. Disease severity index correlated significantly (P<0.01) with plant height, leaf surface, leaf border, leaf length and tassel type. Heritability estimates for plant height and tassel type were 0.48 and 0.38 respectively and for the various leaf traits heritability values were very low. On the basis of the substantial genotype–environment interaction and the little association between DSI values in the different environments, selection for an increased resistance to MRC disease would require evaluation of germplasm across multiple years and locations. Tassel type would be a useful predictor of DSI and can be used effectively to improve screening procedures.

scholarly journals Multiple layers of cryptic genetic variation underlie a yeast complex trait

2018 ◽  
Author(s):  
Jonathan T Lee ◽  
Alessandro L V Coradini ◽  
Amy Shen ◽  
Ian M Ehrenreich
Keyword(s):  
Genetic Variation ◽  
Complex Trait ◽  
Environment Interaction ◽  
Coding Region ◽  
Cryptic Genetic Variation ◽  
Genotype Environment Interaction ◽  
Genetic Perturbations ◽  
In Cis ◽  
The Relationship ◽  
Surface Gene

Cryptic genetic variation may be an important contributor to heritable traits, but its extent and regulation are not fully understood. Here, we investigate the cryptic genetic variation underlying a Saccharomyces cerevisiae colony phenotype that is typically suppressed in a cross of the lab strain BY4716 (BY) and a derivative of the clinical isolate 322134S (3S). To do this, we comprehensively map the trait's genetic basis in the BYx3S cross in the presence of three different genetic perturbations that enable its expression. This allows us to detect and compare the specific loci harboring cryptic genetic variants that interact with each perturbation. In total, we identify 21 loci, all but one of which interacts with just a subset of the perturbations. Beyond impacting which loci contribute to the trait, the genetic perturbations also influence the extent of additivity, epistasis, and genotype-environment interaction among the detected loci. Additionally, we show that the single locus interacting with all three perturbations corresponds to the coding region of the cell surface gene FLO11. Nearly all of the other loci influence FLO11 transcription in cis or trans. However, the perturbations reveal cryptic genetic variation in different pathways and sub-pathways upstream of FLO11, suggesting that multiple layers of cryptic genetic variation with highly contextual effects underlie the trait. Our work demonstrates an abundance of cryptic genetic variation in transcriptional regulation and illustrates how this cryptic genetic variation complicates efforts to study the relationship between genotype and phenotype.

scholarly journals Interpretation of Genotype × Environment Interaction in Agronomic Traits in 24 Potato Cultivars Using AMMI and GGE Biplot Analysis

2018 ◽  
Vol 50 (2) ◽  
pp. 90-103
Author(s):  
Su Jeong Kim ◽  
Whang Bae Sohn ◽  
Min Woo Park ◽  
Dong Chil Chang ◽  
Su Young Hong ◽  
...  
Keyword(s):  
Agronomic Traits ◽  
Potato Cultivars ◽  
Environment Interaction ◽  
Gge Biplot ◽  
Biplot Analysis ◽  
Genotype Environment Interaction

scholarly journals Genome-based trait prediction in multi- environment breeding trials in groundnut

2020 ◽  
Vol 133 (11) ◽  
pp. 3101-3117 ◽  
Author(s):  
Manish K. Pandey ◽  
Sunil Chaudhari ◽  
Diego Jarquin ◽  
Pasupuleti Janila ◽  
Jose Crossa ◽  
...  
Keyword(s):  
Complex Traits ◽  
Prediction Accuracy ◽  
Agronomic Traits ◽  
Total Yield ◽  
Snp Array ◽  
Interaction Model ◽  
Cost Effective ◽  
Environment Interaction ◽  
Genotype Environment Interaction ◽  
Main Effects

Abstract Key message Comparative assessment identified naïve interaction model, and naïve and informed interaction GS models suitable for achieving higher prediction accuracy in groundnut keeping in mind the high genotype × environment interaction for complex traits. Abstract Genomic selection (GS) can be an efficient and cost-effective breeding approach which captures both small- and large-effect genetic factors and therefore promises to achieve higher genetic gains for complex traits such as yield and oil content in groundnut. A training population was constituted with 340 elite lines followed by genotyping with 58 K ‘Axiom_Arachis’ SNP array and phenotyping for key agronomic traits at three locations in India. Four GS models were tested using three different random cross-validation schemes (CV0, CV1 and CV2). These models are: (1) model 1 (M1 = E + L) which includes the main effects of environment (E) and line (L); (2) model 2 (M2 = E + L + G) which includes the main effects of markers (G) in addition to E and L; (3) model 3 (M3 = E + L + G + GE), a naïve interaction model; and (4) model 4 (E + L + G + LE + GE), a naïve and informed interaction model. Prediction accuracy estimated for four models indicated clear advantage of the inclusion of marker information which was reflected in better prediction accuracy achieved with models M2, M3 and M4 as compared to M1 model. High prediction accuracies (> 0.600) were observed for days to 50% flowering, days to maturity, hundred seed weight, oleic acid, rust@90 days, rust@105 days and late leaf spot@90 days, while medium prediction accuracies (0.400–0.600) were obtained for pods/plant, shelling  %, and total yield/plant. Assessment of comparative prediction accuracy for different GS models to perform selection for untested genotypes, and unobserved and unevaluated environments provided greater insights on potential application of GS breeding in groundnut.

scholarly journals Genotype-environment interaction and the maintenance of genetic variation: an empirical study of Lobelia inflata (Campanulaceae)

2020 ◽  
Vol 7 (3) ◽  
pp. 191720 ◽  
Author(s):  
Kristen Côté ◽  
Andrew M. Simons
Keyword(s):  
Genetic Variation ◽  
Balancing Selection ◽  
Rank Order ◽  
Empirical Test ◽  
Heterozygote Advantage ◽  
Environment Interaction ◽  
Fluctuating Selection ◽  
Long Term Study ◽  
Genotype Environment Interaction ◽  
Lobelia Inflata

High levels of genetic variation are often observed in natural populations, suggesting the action of processes such as frequency-dependent selection, heterozygote advantage and variable selection. However, the maintenance of genetic variation in fitness-related traits remains incompletely explained. The extent of genetic variation in obligately self-fertilizing populations of Lobelia inflata (Campanulaceae L.) strongly implies balancing selection. Lobelia inflata thus offers an exceptional opportunity for an empirical test of genotype-environment interaction (G × E) as a variance-maintaining mechanism under fluctuating selection: L. inflata is monocarpic and reproduces only by seed, facilitating assessment of lifetime fitness; genome-wide homozygosity precludes some mechanisms of balancing selection, and microsatellites are, in effect, genotypic lineage markers. Here, we find support for the temporal G × E hypothesis using a manipulated space-for-time approach across four environments: a field environment, an outdoor experimental plot and two differing growth-chamber environments. High genetic variance was confirmed: 83 field-collected individuals consisted of 45 distinct microsatellite lineages with, on average, 4.5 alleles per locus. Rank-order fitness, measured as lifetime fruit production in 16 replicated multilocus genotypes, changed significantly across environments. Phenotypic differences among microsatellite lineages were detected. Results thus support the G × E hypothesis in principle. However, the evaluation of the effect size of this mechanism and fitness effects of life-history traits will require a long-term study of fluctuating selection on labelled genotypes in the field.

Genotype × environment interaction and genetic association of grain iron and zinc content with other agronomic traits in RIL population of pearl millet

2018 ◽  
Vol 69 (11) ◽  
pp. 1092
Author(s):  
Tripti Singhal ◽  
C. Tara Satyavathi ◽  
Aruna Kumar ◽  
S. Mukesh Sankar ◽  
S. P. Singh ◽  
...  
Keyword(s):  
Pearl Millet ◽  
Agronomic Traits ◽  
Pennisetum Glaucum ◽  
Recombinant Inbred Lines ◽  
Selection Index ◽  
Principal Component ◽  
Zinc Content ◽  
Environment Interaction ◽  
Genotype Environment Interaction ◽  
Zn Content

Biofortification of lines of pearl millet (Pennisetum glaucum (L.) R.Br.) with increased iron (Fe) and zinc (Zn) will have great impact because pearl millet is an indispensable component of food and nutritional security of inhabitants of arid and semi-arid regions. The aim of the present study was to assess the stability of Fe and Zn content in recombinant inbred lines (RILs) developed for grain Fe and Zn content, and to use these lines in developing micronutrient-rich pearl millet hybrids. A mapping population consisting of 210 RILs along, with parents and checks, was assessed in three consecutive years (2014–16) under rainfed conditions at the same experimental location in an alpha design with two repetitions. Significant differences were observed in genotype, environment and genotype × environment interaction mean squares for all variables, particularly grain micronutrients. The first two principal components of an interaction principal component analysis cumulatively explained 100% of the total variation; respective contributions of the first and second components were 64.0% and 36.0% for Fe, and 58.1% and 41.9% for Zn. A positive and moderately high correlation (0.696**) between Fe and Zn contents suggests good prospects of simultaneous improvement for both micronutrients. Among the 210 RILs, RIL 69, RIL 186, RIL 191, RIL 149 and RIL 45 were found to be more stable with higher mean micronutrient content, additive main effects and multiplicative interaction stability value (ASV) and genotype selection index (GSI) under rainfed condition. These RILs are promising and can be tested further for their combining ability for yield as well as grain micronutrient content for developing superior biofortified, heterotic pearl millet hybrids.

Detection and estimation of components of genetic variation and genotype × environment interaction in three wheat crosses

1984 ◽  
Vol 103 (3) ◽  
pp. 543-547 ◽  
Author(s):  
S. Singh ◽  
M. S. Dahiya
Keyword(s):  
Genetic Variation ◽  
Grain Yield ◽  
Plant Height ◽  
Environment Interaction ◽  
Gene Effects ◽  
Genotype Environment Interaction ◽  
Additive Component ◽  
Spike Number ◽  
Additive Gene ◽  
1000 Grain Weight

SummaryThe data obtained from 360 progeny families produced by crossing 40 F2 plants from each of three wheat crosses HD 2009 × HD 1949, Raj 821 × WH 147 and NP 876 × HD 1949, to three testers (the testers being the two parents of each original cross and their F1 in each case) were subjected to triple test cross analysis for detecting and estimating additive, dominance and epistatic components of genetic variation and interaction of these components with environment for plant height, spike length, number of tillers per plant, number of spikelets per spike, number of grains per spike, 1000-grain weight, number of days from sowing to heading and to maturity, grain yield per plant and grain yield/above ground dry matter ratio (harvest index). Epistasis was an important element for plant height, number of tillers per plant, number of grains per spike and grain yield per plant in all three crosses. Both the i type and j and l type epistasis were equally important. In general, the magnitude of additive component was larger than that of dominance component. The additive gene effects were more sensitive to environmental change than the dominance gene effects. Similarly, j and l type epistasis was relatively more sensitive to environment than the i type epistasis.

Genotype by environment interactions in cowpea (Vigna unguiculata L. Walp.) grown in the Iberian Peninsula

2017 ◽  
Vol 68 (11) ◽  
pp. 924 ◽  
Author(s):  
Marina Martos-Fuentes ◽  
Juan A. Fernández ◽  
Jesús Ochoa ◽  
Márcia Carvalho ◽  
Valdemar Carnide ◽  
...  
Keyword(s):  
Iberian Peninsula ◽  
Agronomic Traits ◽  
Environmental Stability ◽  
Environment Interaction ◽  
Time Model ◽  
Cowpea Cultivars ◽  
Genotype By Environment ◽  
Genotype Environment Interaction ◽  
Thermal Time Model ◽  
Pod Length

The aim of this work was to determine the variance components and genetic and environmental stability of 12 cowpea genotypes at three locations (South-east of Spain: Cartagena, South and North of Portugal: Elvas and Vila Real, respectively) in the Iberian Peninsula in two consecutive years (2015 and 2016). The genotype, the environment and the genotype × environment interaction significantly influenced all the morphological and agronomical parameters evaluated. For both years, the highest yields were observed at Elvas, whereas Cartagena and Vila real were the most suitable places to obtain crop precocity. Cartagena was the place where the filling of the seed was the fastest, probably due to the higher temperatures and radiation. The thermal time model (effective degree-days) could be used to predict the period of cowpea development, therefore predict flowering and pod maturity date. Correlation analysis showed that days to flowering, days to maturity and the seed yield vs protein content exhibited negative correlations. The highest heritability was found for plant height and pod length at Cartagena and for 100-seed weight at Elvas and Vila Real. In conclusion, the variations that exist in the studied accessions could give rise to a breeding program to develop cowpea cultivars with interesting agronomic traits.

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