Genetic Diversity and Trait Association among Some Yield Parameters of Wheat Elite Lines Genotypes under Rainfed Conditions

2013 ◽  
Vol 1 (2) ◽  
pp. 23
Author(s):  
Muhammad Zeeshan ◽  
Keyword(s):  
Genetic Diversity ◽  
Trait Association ◽  
Yield Parameters ◽  
Rainfed Conditions

Multivariate Analysis, Genetic Diversity and Phenotypic Correlation of Nineteen Exotic Groundnut Accessions

2016 ◽  
Vol 3 (1) ◽  
Author(s):  
YPJ AMARASINGHE ◽  
G . WIJESINGHE ◽  
R W PUSHPAKUMARA
Keyword(s):  
Genetic Diversity ◽  
Principal Component Analysis ◽  
Growth Parameters ◽  
Principal Component ◽  
Phenotypic Correlation ◽  
Clustering Method ◽  
Yield Parameters ◽  
Arachis Hypogaea L ◽  
Semi Arid ◽  
Number Of Branches

19 Groundnut ( Arachis hypogaea L. ) genotypes receiv ed from International Crops Research Institute for Semi Arid T ropics (ICRISA T) India w ere ev aluated in a non replicated trial and the characters w ere subjected to multiv ariate analysis to study the v ariability within the genotypes. The first 5 axes of the principal component analysis captured 78% of the total v ariability and identified yield parameters such as number of pods per plant, pod w eight per plant and growth parameters such as number of branches per plant, plant spread, and pod characteristics as the characters contributing most to total v ariation. Phenotypic correlation analysis rev ealed that the yield has positiv e correlation with the characters such as number of pods per plant and number of branches per plant. W ards clustering method has grouped the genotypes into 3 distinct clusters. The results can be applied in order to strengthen the breeding program

scholarly journals Integrated Nutrient Management Improves the Growth and Yield of Rice and Greengram in a Rice—Greengram Cropping System under the Coastal Plain Agro-Climatic Condition

Plants ◽  
2022 ◽  
Vol 11 (1) ◽  
pp. 142
Author(s):  
Satyabrata Mangaraj ◽  
Rabindra Kumar Paikaray ◽  
Sagar Maitra ◽  
Shriram Ratan Pradhan ◽  
Lalita Mohan Garnayak ◽  
...  
Keyword(s):  
Leaf Area ◽  
Nutrient Management ◽  
Nutrient Balance ◽  
Cropping System ◽  
Plant Nutrients ◽  
Recommended Dose ◽  
Aromatic Rice ◽  
Integrated Nutrient Management ◽  
Yield Parameters ◽  
Rainfed Conditions

Continuous mono-cropping of rice has resulted in decline or stagnation of yield output due to the occurrence of multiple nutrient deficiencies and worsening of soil physicochemical properties accompanying increased pressure of insect pests and diseases. The basic concept of integrated nutrient management (INM) is maintenance or adjustment of soil fertility and supply of plant nutrients to an optimum level for sustaining the desired crop productivity through optimisation of benefits from all possible sources of plant nutrients in an integrated way. Augmenting a rice-based cropping system with pulses is a prevalent and indigenous cropping system under rainfed conditions. Considering the above facts, experiments were conducted to evaluate the impacts of integrated nutrient management on productivity of aromatic rice–greengram cropping system and nutrient balance of the post-harvest soil for agricultural sustainability under rainfed conditions in two consecutive years (2017–2018 and 2018–2019) with six main plots and three subplots. The experimental findings revealed that the treatment comprised of 50% recommended dose of fertiliser (RDF) through chemicals + 50% recommended dose of nitrogen (RDN) through farmyard manure (FYM) increased the plant height, tillers, dry matter accumulation, leaf area and leaf area duration, and yield parameters in short grain aromatic rice. Similarly, preceding application of 50% RDF + 50% RDN through FYM to rice and further application 75% RDF + Rhizobium+ phosphate solubilizing bacteria (PSB) to greengram increased the growth characteristics and yield parameters—such as pods/plant, seeds/pod, grain yield, stover yield, and harvest index—in greengram. It was concluded that the treatment consisting of 50% RDF (chemical fertiliser) + 50% RDN (FYM) to rice and 75% RDF + Rhizobium + PSB to greengram increased the productivity of the rice–greengram cropping system. Furthermore, the adoption of INM has positively impacted post-harvest soil nutrient balance.

Assessment of molecular divergence using microsatellite markers linked to drought-yield QTLs of rice (Oryza sativa L.)

2020 ◽  
Vol 57 (2) ◽  
pp. 94-99
Author(s):  
ND Rathan ◽  
SK Singh ◽  
RK Singh ◽  
PR Vennela
Keyword(s):  
Genetic Diversity ◽  
Oryza Sativa ◽  
Oryza Sativa L ◽  
Polymorphic Marker ◽  
Polymorphic Markers ◽  
Rainfed Conditions ◽  
Transgressive Segregants ◽  
Rice Genotypes ◽  
Contemporary Study ◽  
Selection Of

The drought stress is the major limitation for the production and yield stability in the rice (Oryza sativa L.) growing areas particularly under rainfed conditions. The assessment of genetic diversity among the rice genotypes using molecular markers linked to drought-yield QTLs will help in the selection of divergent parents to produce superior recombinants and transgressive segregants to develop high yielding cultivars for drought conditions. So the current study was conducted to estimate the genetic diversity among the set of twenty four advanced drought tolerent rice genotypes and commercial checks using SSR markers linked to major drought-yield QTLs. A total of 31 alleles were detected by 13 polymorphic markers across 24 rice genotypes with a mean of 1.94 alleles per polymorphic marker. Among the polymorphic markers, 11 markers formed 2 alleles each, 2 markers have produced 3 alleles each. The PIC value observed in the contemporary study ranged from 0.239 to 0.499 with an average PIC value of 0.346. The dendrogram displayed a total five clusters on the basis of dissimilarity coefficient values, the cluster II had maximum ten genotypes followed by cluster IB-a with five genotypes and clusters IA-a, IA-b, IB-b with three genotypes each. IR 82475-110-2-2-1-2 and IR92937-178-2-2 (R-155) were found to be the most divergent genotypes.

scholarly journals Genetic Diversity, Population Structure and Marker-Trait Association for 100-Seed Weight in International Safflower Panel Using SilicoDArT Marker Information

Plants ◽  
2020 ◽  
Vol 9 (5) ◽  
pp. 652 ◽  
Author(s):  
Fawad Ali ◽  
Muhammad Azhar Nadeem ◽  
Muzaffer Barut ◽  
Ephrem Habyarimana ◽  
Hassan Javed Chaudhary ◽  
...  
Keyword(s):  
Genetic Diversity ◽  
Population Structure ◽  
Seed Weight ◽  
Mixed Linear Model ◽  
Oilseed Crop ◽  
Trait Association ◽  
Information Index ◽  
Expected Heterozygosity ◽  
Two Populations ◽  
100 Seed Weight

Safflower is an important oilseed crop mainly grown in the arid and semi-arid regions of the world. The aim of this study was to explore phenotypic and genetic diversity, population structure, and marker-trait association for 100-seed weight in 94 safflower accessions originating from 26 countries using silicoDArT markers. Analysis of variance revealed statistically significant genotypic effects (p < 0.01), while Turkey samples resulted in higher 100-seed weight compared to Pakistan samples. A Constellation plot divided the studied germplasm into two populations on the basis of their 100-seed weight. Various mean genetic diversity parameters including observed number of alleles (1.99), effective number of alleles (1.54), Shannon’s information index (0.48), expected heterozygosity (0.32), and unbiased expected heterozygosity (0.32) for the entire population exhibited sufficient genetic diversity using 12232 silicoDArT markers. Analysis of molecular variance (AMOVA) revealed that most of the variations (91%) in world safflower panel are due to differences within country groups. A model-based structure grouped the 94 safflower accessions into populations A, B, C and an admixture population upon membership coefficient. Neighbor joining analysis grouped the safflower accessions into two populations (A and B). Principal coordinate analysis (PCoA) also clustered the safflower accessions on the basis of geographical origin. Three accessions; Egypt-5, Egypt-2, and India-2 revealed the highest genetic distance and hence might be recommended as candidate parental lines for safflower breeding programs. The mixed linear model i.e., the Q + K model, demonstrated that two DArTseq markers (DArT-45483051 and DArT-15672391) had significant association (p < 0.01) for 100-seed weight. We envisage that identified DArTseq markers associated with 100-seed weight will be helpful to develop high-yielding cultivars of safflower through marker-assisted breeding in the near future.

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