Devising selection strategy for increase in sesame yield based on variability heritability and genetic advance studies

Background: Recognizing and promoting the factors that affect the self-management behaviors of diabetes leads to a reduction in the number of patients and an improvement in the quality of care. The ecological approach focuses on the nature of people's interactions with their physical and socio-cultural environments. Objective: The purpose of this study was to identify the predictors of self-management behaviors with a comprehensive approach in these patients. Methods: The Keywords were investigated in the relevant national and international databases, including PubMed, Google Scholar, Science Direct, Scopus, and Scientific Information Database, Magiran, and Iran Medex to obtain the articles published from 2009 to 2019. The search and article selection strategy was developed based on the Prisma checklist and was carried out in three steps. Results: Most studies have shown that personal factors had the highest prediction power for the self-management of diabetes. Then, the interpersonal factors, society and policy-making factors, and group and organization factors were most frequently reported predictors of self-management behaviors in diabetic patients. Conclusion: Self-management of diabetes is necessary for controlling it because 95% of care is done by the patient. When designing self-management interventions, factors based on the individual level that increasing self-management behaviors should be taken into account.

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Genetic Evaluation and Bi-plot Analysis in Okra Hybrids for Yield, Quality Components and YVMV Resistance

Journal of AgriSearch ◽

10.21921/jas.5.4.5 ◽

2018 ◽

Vol 5 (04) ◽

Author(s):

SS SOLANKEY ◽

ANIL K SINGH

Keyword(s):

Genetic Divergence ◽

Principal Component ◽

F1 Hybrids ◽

Genetic Advance ◽

Economic Traits ◽

Cross Combination ◽

Plot Analysis ◽

Eigen Value ◽

Coefficient Of Variability ◽

Yield Quality

Fifty one okra F1 hybrids (using 17 lines as female and 3 testers as male parent) were evaluated in RCBD design during two different consecutive seasons (summer and rainy). Phenotypic coefficient of variability (PCV) was higher than genotypic coefficient of variability (GCV) for all studied character exhibiting environmental effects on the expression of characters. Heritability (h2b) along with genetic advance per cent of mean was found highest for character YVMV (86.95% and 150.61%). All the 51 okra hybrids were grouped into 4 distinct clusters in which Cluster II was the largest cluster having 28 F1s (54.90% of total F1s) followed by Cluster I with 14 F1s (27.45% of total F1s). Out of the major 6 PCs, 4 principal components (PC1, PC2, PC3 and PC4) accounted with proportionate values of 22.61, 17.22, 11.87 and 10.63%, respectively and contributed 62.33 % of the cumulative variation having Eigen value more than one. Moreover, based on PCs and genetic divergence in Cluster I and Cluster IV for plant height, YVMV and number of fruit per plant is important to identify the best cross combination (Arka Abhay × Arka Anamika) in okra. Therefore, the best cross combinations for improvement in various economic traits can be recommended on the basis of genetic divergence and principal component analysis in okra.

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

Journal of AgriSearch ◽

10.21921/jas.v4i03.9017 ◽

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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