Generation of Micro-mutants for Yield and Component Traits in Horse Gram [Macrotyloma uniflorum (Lam.) Verdc.]

2021 ◽  
Author(s):  
S. Priyanka ◽  
R. Sudhagar ◽  
C. Vanniarajan ◽  
K. Ganesamurthy ◽  
J. Souframanien
Keyword(s):  
Electron Beam ◽  
Gamma Rays ◽  
Mean Value ◽  
Yield Component ◽  
Yield Potential ◽  
Single Plant ◽  
Plant Yield ◽  
Mean Values ◽  
Horse Gram ◽  
Component Traits

Background: Induced mutagenesis was employed in horse gram cv. CRIDA 1-18R with an objective of evolving mutants with increased yield potential. Methods: Based on preliminary study, the variety has been irradiated with desirable doses of gamma rays (200 Gy and 300 Gy), electron beam (100 Gy and 200 Gy) and its combination (100 Gy) and the material were forwarded to M2 generation following parent-progeny row basis. The genotypes exhibiting superior yield than control were further forwarded to M3 generation. Multivariate analyses were performed to determine the induction of micro-mutants for 11 quantitative traits.Result: The reduction in mean value over control was observed for most of the yield component traits at M2 generation. Among the mutagenic treatments, combination of gamma rays with electron beam registered high mean values for pod length (5.05 cm), number of pods per plant (54.42) and single plant yield (25.68 g) at M3 generation. Non-significant skewness and / or kurtosis at M3 population denoted the absence of epistatic interactions for plant yield. An increase in variability pattern, H2 and GAM at M3 generation indicated the scope for trait (plant height, number of seeds per pod, number of clusters per plant, number of pods per plant, biological yield and single plant yield) improvement through selection.

scholarly journals Evaluating Genotype × Environment Interactions of Yield Traits and Adaptability in Rice Cultivars Grown under Temperate, Subtropical and Tropical Environments

Agriculture ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 558
Author(s):  
Xing Huang ◽  
Su Jang ◽  
Backki Kim ◽  
Zhongze Piao ◽  
Edilberto Redona ◽  
...  
Keyword(s):  
Yield Component ◽  
Yield Potential ◽  
High Yield ◽  
Environment Interaction ◽  
Accurate Identification ◽  
Rice Varieties ◽  
Panicle Number ◽  
Tropical Conditions ◽  
Component Traits ◽  
Yield Component Traits

Rice yield is a complex trait that is strongly affected by environment and genotype × environment interaction (GEI) effects. Consideration of GEI in diverse environments facilitates the accurate identification of optimal genotypes with high yield performance, which are adaptable to specific or diverse environments. In this study, multiple environment trials were conducted to evaluate grain yield (GY) and four yield-component traits: panicle length, panicle number, spikelet number per panicle, and thousand-grain weight. Eighty-nine rice varieties were cultivated in temperate, subtropical, and tropical regions for two years. The effects of both GEI (12.4–19.6%) and environment (23.6–69.6%) significantly contributed to the variation of all yield-component traits. In addition, 37.1% of GY variation was explained by GEI, indicating that GY performance was strongly affected by the different environmental conditions. GY performance and genotype stability were evaluated using simultaneous selection indexing, and 19 desirable genotypes were identified with high productivity and broad adaptability across temperate, subtropical, and tropical conditions. These optimal genotypes could be recommended for cultivation and as elite parents for rice breeding programs to improve yield potential and general adaptability to climates.

Quantitative variation induced by gamma rays, ethyl methane sulphonate, and hydrazine hydrate in mung bean (Phaseolus aureus Roxb.)

1984 ◽  
Vol 26 (4) ◽  
pp. 492-496 ◽  
Author(s):  
Irfan A. Khan
Keyword(s):  
Gamma Rays ◽  
Seed Weight ◽  
Genetic Advance ◽  
Ethyl Methane Sulphonate ◽  
Ethyl Methane ◽  
Plant Yield ◽  
Mean Values ◽  
Methane Sulphonate ◽  
The Mean ◽  
100 Seed Weight

Induced variability was studied in the quantitative characters of mung bean (Phaseolus aureus Roxb.) after treatment with gamma rays, ethyl methane sulphonate (EMS), and hydrazine hydrate (HZ) in M1, M2, and M3 generations. The characters evaluated were seeds per pod, 100-seed weight, and total plant yield. The variability increased in almost all of the characters in the M1 generation. The mean number of seeds per pod and 100-seed weight decreased, whereas the plant yield did not show any particular trend. There was an increase in the mean values after gamma irradiation and EMS treatments in the M2 generation. However, HZ fails to show the same response. However, the mean values increased in the M3 generation. Estimates of heritability were higher for 100-seed weight, followed by plant yield, and then seeds per pod in the M3 generation. Coefficient of genotypic variation and genetic advance were high for the plant yield in M2 and M3 generations. In general, the genotypic coefficient of variation values, heritability, and genetic advance increased more in M3 as compared with M2, indicating that the significant gain could possibly be achieved through selection in M3 generation.Key words: quantitative, heritability, mutagenesis.

Studies on Variability, Heritability, Correlation and Path Analysis in Segregating Population of Black Gram [Vigna mungo (L.) Hepper]

2021 ◽  
Author(s):  
D. Gomathi ◽  
D. Shoba ◽  
V. Ramamoorthy ◽  
M. Arumugam Pillai
Keyword(s):  
Breeding Program ◽  
Yield Potential ◽  
Black Gram ◽  
Single Plant ◽  
Number Of Clusters ◽  
Plant Yield ◽  
Back Ground ◽  
Correlation And Path Analysis ◽  
Efficient Breeding ◽  
Positive Direct

Back ground: Pulses are an important source of protein in the human diet and black gram is a popular pulse crop in India. The black gram breeding program faces various drawbacks due to narrow genetic diversity accompanied by biotic and abiotic diseases which seriously affect the yield potential of the crop. Hence it is important to understand the gene action and to frame the efficient breeding program in black gram for yield improvement.Methods: The present experiment was conducted during 2018-2019. Sixty-nine F2 plants of the cross ADT3 x KKB14-052 were raised and nine biometrical traits were recorded. Genetic variability and association analysis were carried out.Result: High PCV and GCV were obtained for the traits viz., number of primary branches/ plant, number of clusters/plant, number of pods/plant and single plant yield. High heritability and high GAM were obtained for the traits viz., plant height, number of primary branches/plant, number of clusters/plant, number of pods/plant, hundred seed weight, pod length and single plant yield. All the characters under the study were significantly positive correlation with yield except days to 50% flowering. Number of pods/plant showed a high positive, direct effect on single plant yield. Hence, these characters would be mainly focused in black gram breeding programs for yield improvement.

scholarly journals Genetic diversity of Guar genotypes (Cyamopsis tetragonoloba (L.) Taub.) based on Agro-Morphological traits

2015 ◽  
Vol 44 (1) ◽  
pp. 59-65 ◽  
Author(s):  
A Manivannan ◽  
CR Anandakumar ◽  
R Ushakumari ◽  
GS Dahiya
Keyword(s):  
Morphological Traits ◽  
Geographic Origin ◽  
Principal Component ◽  
Yield Potential ◽  
Cyamopsis Tetragonoloba ◽  
Single Plant ◽  
Early Maturity ◽  
Plant Yield ◽  
Analysis Of Variation ◽  
Pod Length

Twelve quantitative characters were taken under observation to estimate substantial variation and relationship among Guar (Cyamopsis tetragonoloba (L.)Taub.,Fam.: Fabaceae) genotypes and to identify the best performing lines suited to southern parts of India, where the potential of growing the guar crop throughout the year. Analysis of variation for such quantitative traits in diverse line showed considerable and dissimilar level of variability. The largest variation was found for days to maturity, plant height, pods per plant and cluster per plant. Single plant yield was significant positively correlated with primary branches per plant, secondary branch per plant, cluster per plant, pods per cluster, pods per plant, however pod length was significant but negatively correlated with single plant yield. Principal component analysis showed the amount of variation by principal components 1 to 5 viz., 38, 16.4, 12.5, 9.5 and 6.6%, respectively. Clustering analysis based on various morphological traits assorted 42 guar genotypes into four main groups and six subclusters. Dendrogram based on hierarchal clustering grouped genotypes based on their morphological traits rather than geographic origin. Grouping of genotypes based on morphological traits is not always associated with their geographical origin. Out performed genotypes based higher yield potential, 100-seed weight, pods per plant and early maturity are identified for guar variety development and future breeding programme suited for South India. DOI: http://dx.doi.org/10.3329/bjb.v44i1.22724 Bangladesh J. Bot. 44(1): 59-65, 2015 (March)

Genetic divergence, variability and correlation studies in black gram [Vigna mungo (L.) Hepper]

2019 ◽  
Author(s):  
L. Priya . ◽  
M. Arumugam Pillai ◽  
D. Shoba
Keyword(s):  
Plant Height ◽  
Genetic Divergence ◽  
Mean Value ◽  
Black Gram ◽  
Single Plant ◽  
Plant Yield ◽  
Cluster Distance ◽  
Breeding Programmes ◽  
High Heritability ◽  
Selection Of

A field experiment was conducted to estimate genetic divergence, variability and correlation in 104 black gram genotypes for nine quantitative characters. Genetic diversity using Mahalanobis D2 technique was studied for yield and yield contributing traits. Out of eight clusters, high inter cluster distance was recorded between clusters VI and VIII. Cluster V had low mean value for days to 50% flowering and cluster VII had high mean value for plant height, number of primary branches per plant and number of seeds per plant. The genotypes present in these clusters could be utilized for hybridization programmes. High heritability coupled with GAM was observed for plant height, number of primary branches per plant, number of clusters per plant, number of pods per plant and single plant yield. From the association analysis, single plant yield had positive and significant association with plant height and number of primary branches per plant. Hence, simultaneous selection of the above traits would be more rewarding to bring genetic improvement in black gram breeding programmes.

scholarly journals Development of Novel Blackgram (Vigna mungo (L.) Hepper) Mutants and Deciphering Genotype × Environment Interaction for Yield-Related Traits of Mutants

Agronomy ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 1287
Author(s):  
Manickam Dhasarathan ◽  
Seshadri Geetha ◽  
Adhimoolam Karthikeyan ◽  
Datchinamoorthy Sassikumar ◽  
Narayanapillai Meenakshiganesan
Keyword(s):  
Gamma Rays ◽  
Clustering Analysis ◽  
Vigna Mungo ◽  
Environment Interaction ◽  
Gge Biplot ◽  
Single Plant ◽  
Plant Yield ◽  
Genotype Environment Interaction ◽  
Genetic Stocks ◽  
Direct Association

Blackgram (Vigna mungo (L.) Hepper) yields are noticeably poor due to a shortage of improved varieties and an aggravated narrow genetic base. An attempt was made to isolate novel blackgram mutants by selecting for yield-related traits derived through gamma irradiation and testing the mutant genotype’s stability across the different environments. The irradiated blackgram populations M1-M5 were established in the background of cultivars ADT 3, Co 6, and TU 17-9. Desirable mutants were selected from M3 to M5 generations. It was observed in M2 and M3 that gamma rays showed higher mutagenic efficacy and generated good inherited variance for the yield-related traits. M4 established three divergent groups in each blackgram cultivar revealed by clustering analysis. The number of pods per plant, number of clusters per plant, and number of pods per cluster showed a strong direct association with single plant yield and could be considered as selection traits. G × E interactions were higher than the variation due to genotype for single plant yield. Limited environmental interaction was observed for the genotypes G24, G16, G36, G30, and G17, as revealed by AMMI, and the genotypes G18 and G29, as revealed by GGE. GGE biplot revealed the environment-specific genotypes G13 for E1 (Aduthurai), G7 for E2 (Kattuthottam), and G34 for E3 (Vamban) and also portrayed the highly discriminating (E3) and representative (E2) environments. Selected novel blackgram genotypes from this research are useful genetic stocks for genetic improvement and breeding.

scholarly journals Application of machine learning and genetic optimization algorithms for modeling and optimizing soybean yield using its component traits

PLoS ONE ◽  
2021 ◽  
Vol 16 (4) ◽  
pp. e0250665
Author(s):  
Mohsen Yoosefzadeh-Najafabadi ◽  
Dan Tulpan ◽  
Milad Eskandari
Keyword(s):  
Machine Learning ◽  
Yield Components ◽  
Soybean Seed ◽  
Complex Trait ◽  
Yield Component ◽  
Yield Potential ◽  
Coefficient Of Determination ◽  
Soybean Yield ◽  
Component Traits ◽  
Yield Component Traits

Improving genetic yield potential in major food grade crops such as soybean (Glycine max L.) is the most sustainable way to address the growing global food demand and its security concerns. Yield is a complex trait and reliant on various related variables called yield components. In this study, the five most important yield component traits in soybean were measured using a panel of 250 genotypes grown in four environments. These traits were the number of nodes per plant (NP), number of non-reproductive nodes per plant (NRNP), number of reproductive nodes per plant (RNP), number of pods per plant (PP), and the ratio of number of pods to number of nodes per plant (P/N). These data were used for predicting the total soybean seed yield using the Multilayer Perceptron (MLP), Radial Basis Function (RBF), and Random Forest (RF), machine learning (ML) algorithms, individually and collectively through an ensemble method based on bagging strategy (E-B). The RBF algorithm with highest Coefficient of Determination (R2) value of 0.81 and the lowest Mean Absolute Errors (MAE) and Root Mean Square Error (RMSE) values of 148.61 kg.ha-1, and 185.31 kg.ha-1, respectively, was the most accurate algorithm and, therefore, selected as the metaClassifier for the E-B algorithm. Using the E-B algorithm, we were able to increase the prediction accuracy by improving the values of R2, MAE, and RMSE by 0.1, 0.24 kg.ha-1, and 0.96 kg.ha-1, respectively. Furthermore, for the first time in this study, we allied the E-B with the genetic algorithm (GA) to model the optimum values of yield components in an ideotype genotype in which the yield is maximized. The results revealed a better understanding of the relationships between soybean yield and its components, which can be used for selecting parental lines and designing promising crosses for developing cultivars with improved genetic yield potential.

Seasonal trends in the stable isotopic composition of snow and meltwater runoff in a subarctic catchment at Okstindan, Norway

2004 ◽  
Vol 35 (2) ◽  
pp. 119-137 ◽  
Author(s):  
S.D. Gurney ◽  
D.S.L. Lawrence
Keyword(s):  
Isotopic Composition ◽  
Mean Value ◽  
Mean Values ◽  
Stable Isotopic Composition ◽  
Meltwater Runoff ◽  
Stable Isotopic ◽  
The Mean ◽  
The Difference ◽  
Δ18o And Δd

Seasonal variations in the stable isotopic composition of snow and meltwater were investigated in a sub-arctic, mountainous, but non-glacial, catchment at Okstindan in northern Norway based on analyses of δ18O and δD. Samples were collected during four field periods (August 1998; April 1999; June 1999 and August 1999) at three sites lying on an altitudinal transect (740–970 m a.s.l.). Snowpack data display an increase in the mean values of δ18O (increasing from a mean value of −13.51 to −11.49‰ between April and August), as well as a decrease in variability through the melt period. Comparison with a regional meteoric water line indicates that the slope of the δ18O–δD line for the snowpacks decreases over the same period, dropping from 7.49 to approximately 6.2.This change points to the role of evaporation in snowpack ablation and is confirmed by the vertical profile of deuterium excess. Snowpack seepage data, although limited, also suggest reduced values of δD, as might be associated with local evaporation during meltwater generation. In general, meltwaters were depleted in δ18O relative to the source snowpack at the peak of the melt (June), but later in the year (August) the difference between the two was not statistically significant. The diurnal pattern of isotopic composition indicates that the most depleted meltwaters coincide with the peak in temperature and, hence, meltwater production.

Effectiveness and efficiency of electron beam in comparison with gamma rays and ethyl methane sulfonate mutagens in cowpea

2021 ◽  
Vol 171 ◽  
pp. 109640
Author(s):  
Vijayakumar Eswaramoorthy ◽  
Thangaraj Kandasamy ◽  
Kalaimagal Thiyagarajan ◽  
Chockalingam Vanniarajan ◽  
Souframanien Jegadeesan
Keyword(s):  
Electron Beam ◽  
Gamma Rays ◽  
Ethyl Methane Sulfonate ◽  
Methane Sulfonate ◽  
Ethyl Methane ◽  
Effectiveness And Efficiency
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