scholarly journals Association analysis for seed yield and component traits in segregating populations of blackgram (Vigna mungo (L.) Hepper)

2018 ◽  
Vol 9 (2) ◽  
pp. 741
Author(s):  
P. Sathya ◽  
N. Manivannan ◽  
A. Mahalingam ◽  
V.K. Satya ◽  
C. Parameswari
Keyword(s):  
Association Analysis ◽  
Seed Yield ◽  
Vigna Mungo ◽  
Component Traits

Combining ability studies for seed yield and its component traits in urdbean [Vigna mungo (L.) Hepper]

2016 ◽  
Vol 17 (4) ◽  
pp. 729
Author(s):  
Shivani Balouria ◽  
R. K. Mittal ◽  
V. K. Sood ◽  
Shayla Bindra
Keyword(s):  
Seed Yield ◽  
Combining Ability ◽  
Vigna Mungo ◽  
Component Traits

Estimation of Genetic Parameters, Selection Indices and Association Analysis of Seed Yield and Its Component Traits in Chickpea (Cicer arietinum L.) 

2021 ◽  
Author(s):  
Amit Kumar ◽  
Hitesh Kumar ◽  
Vijay Sharma ◽  
Kamaluddin .
Keyword(s):  
Association Analysis ◽  
Seed Yield ◽  
Genetic Parameters ◽  
Genetic Advance ◽  
Selection Indices ◽  
Component Traits ◽  
Seed Index ◽  
Positive Direct ◽  
Pod Number ◽  
Number Of Seeds

Background: Chickpea is a second most important pulse crop grown in 56 countries and India rank first in production which shares 61.4% of the total world chickpea production however, productivity is very low as compared to other countries. Therefore, varietal development with inherent tolerance to biotic and abiotic stress is the prime objective to improve component productivity traits to get better yield in rainfed agro-climatic conditions.Methods: Ninety germplasm accessions of chickpea along with four check viz., JG 14, JG 16, JAKI 9218 and Radhey were evaluated in augmented block design at experimental research farm of Banda University of Agriculture and Technology, Banda, Uttar Pradesh, India. Phenotypic data were subjected to study the genetic parameters and association analysis of yield and its component traits using SPAR 2.0 Package and Windostat Version 9.2.Result: The significant variation was observed for all the traits except number of secondary branches, number of pod per plant, number of seeds per pod among the genotypes. The maximum GCV and PCV was observed for height of first pod (35.28 and 39.29), followed by seed yield per plant (29.77 and 40.32) and number of primary branches (25.63 and 31.44). The high magnitude of heritability with genetic advance was estimated for seed index (96.61%), while the high genetic advance as per cent of mean was recorded for first pod height (65.27%). The positive and significant association of seed yield with number of pods per plant, seed index, number of seeds per pod, number of secondary branches, number of primary branches and height of first pod indicating the importance of these traits in selection criteria. Path analysis identified that number of seeds per pod, number of pods per plants, seed index and number of secondary branches per plant as highly desirable component for direct effect on seed yield per plant. The genotypes ICVT-181106 had highest selection indices for seed yield followed by ICVT-181107, PUSA-1053, JG-218, GNG-1999, ICVT-181102 and HC-5. Therefore, high GCV and PCV, significant positive direct and indirect correlation and high estimate of selection indices for grain yield can be directly and indirectly used for chickpea breeding program. 

Nature of genetic diversity for seed yield and its component traits in urdbean [Vigna mungo (L.) Hepper]

2016 ◽  
Vol 50 (1) ◽  
Author(s):  
P. Y. Kamannavar ◽  
S. B. Revanappa ◽  
A. G. Vijaykumar ◽  
K. Basamma ◽  
Ganajaxi
Keyword(s):  
Genetic Diversity ◽  
Plant Height ◽  
Seed Yield ◽  
Morphological Traits ◽  
Vigna Mungo ◽  
Breeding Lines ◽  
Cluster Distance ◽  
Component Traits

Genetic diversity was assessed in thirty urdbean cultivars including advance breeding lines by Mahalanobis D<sup>2</sup> statistics using seed yield and its component morphological traits. Analysis of genetic diversity revealed considerable amount of diversity among the genotypes and led to their grouping into eight clusters. The cluster-I comprising 14 genotypes was the largest followed by cluster-II and III with 5 and 4 genotypes respectively. The remaining clusters were monogenotypic. Pods per plant (32.5%), seed yield per plant (30%) and plant height (21.5%) were mainly responsible for genetic diversity. Based on inter-cluster distance and mean performance of clusters for different traits, the crosses among genotypes like, DBG-5, DU-1, Manikya, KU-7638, and DBG-3 are expected to produce desirable segregants for yield and other yield related traits.

Combining ability and heterosis studies across environments in linseed (Linum usitatissimum L.)

2011 ◽  
Vol 59 (1) ◽  
pp. 87-102 ◽  
Author(s):  
S. Sood ◽  
N. Kalia ◽  
S. Bhateria
Keyword(s):  
Seed Yield ◽  
Linum Usitatissimum ◽  
Combining Ability ◽  
Yield Components ◽  
Block Design ◽  
Linum Usitatissimum L ◽  
Randomized Block Design ◽  
Component Traits ◽  
Parental Lines ◽  
Fibre Yield

Combining ability and heterosis were calculated for fourteen lines of linseed in a line × tester mating design using twelve lines and two diverse testers in two different environments. The hybrids and parental lines were raised in a completely randomized block design with three replications to investigate seed and fibre yield and their component traits. Genetic variation was significant for most of the traits over environments. Combining ability studies revealed that the lines KL-221 and LCK-9826 were good general combiners for seed yield and most of its components, whereas LMH-62 and LC-2323 were good general combiners for yield components only. Moreover, KL-221 was also a good general combiner for fibre yield. Similarly, B-509 and Ariane were good general combiners for fibre yield and most of its components. Among the specific cross combinations, B-509 × Flak-1 was outstanding for seed yield per plant and B-509 × KL-187 and LC-2323 × LCK-9826 for fibre yield per plant, with high SCA effects. In general, the hybrids excelled their respective parents and the standard checks for most of the characters studied. Based on the comparison of mean performance, SCA effects and the extent of heterosis, the hybrids LC-2323 × LCK-9826 and B-509 × KL-221 appeared to be the most promising for both seed and fibre yield. Other promising combinations were LC-2323 × KL-210 and B-509 × Ariane for seed and fibre yield, respectively. The superiority of LC-2323, LCK-9826, KL-221, B-509 and Ariane as good general combiners was further confirmed by the involvement of these parents in the desirable cross combinations.

Study onGenetic Variability, Heritability and Genetic Advance for Seed Yield and Component Traits in Rice

2017 ◽  
Vol 4 (03) ◽  
Author(s):  
PUNIT KUMAR ◽  
VICHITRA KUMAR ARYA ◽  
PRADEEP KUMAR ◽  
LOKENDRA KUMAR ◽  
JOGENDRA SINGH
Keyword(s):  
Grain Yield ◽  
Plant Height ◽  
Seed Yield ◽  
Flag Leaf ◽  
Grain Weight ◽  
Major Influence ◽  
Genetic Advance ◽  
Component Traits ◽  
Biological Yield ◽  
1000 Grain Weight

A study on genetic variability, heritability and genetic advance for seed yield and component traits was made in 40 genotypes of riceduring kharif 2011-2012 at SHIATS, Allahabad. The analysis of variance showed highly significant differences among the treatments for all the 13 traits under study.The genotypes namely CN 1446-5-8-17-1-MLD4 and CR 2706 recorded highest mean performance for panicles per hill and grain yield. The highest genotypic and phenotypic variances (VG and VP) were recorded for spikelets per panicle (3595.78 and 3642.41) followed by biological yield (355.72 and 360.62) and plant height (231.48 and 234.35).High heritability (broad sense) coupled with high genetic advance was observed for plant height, flag leaf length, panicles per hill, tillers per hill, days to maturity, spikelet’s per panicle, biological yield, harvest index, 1000 grain weight and grain yield, indicating that selection will be effective based on these traits because they were under the influence of additive and additive x additive type of gene action. Highest coefficient of variation (PCV and GCV) was recorded for tillers per hill (18.42% and 17.23%), panicle per hill (19.76 % and 18.68%), spikelet’s per panicle (34.30 and34.07 %), biological yield (28.31 % and 28.12 %), 1000 grain weight (15.57 % and 15 31 %) and grain yield (46.66% and 23.54 %), indicating that these traits are under the major influence of genetic control, therefore the above mentioned traits contributed maximum to higher grain yield compared to other traits, indicating grain yield improvement through the associated traits.

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