scholarly journals Phenotypic Diversity and Molecular diversity of Finger Millet Composite Collection and Identification of Trait Specific Germplasm for Use in Crop Improvement

2020 ◽  
Vol 107 ◽  
pp. 1-4
Author(s):  
Bharathi A ◽  
Keyword(s):  
Clustering Analysis ◽  
Finger Millet ◽  
Phenotypic Diversity ◽  
Crop Improvement ◽  
Principal Component ◽  
Head Length ◽  
Flowering Plant ◽  
Fodder Yield ◽  
Total Divergence ◽  
Peduncle Length

A composite collection of finger millet consisting of 1000 accessions representing the diversity of the entire germplasm at ICRISAT gene bank was developed, including 622 accessions of ICRISAT core collection. Phenotyping of the composite collection for 15 quantitative traits and 20 SSR markers genotyping data resulted in the identification of promising traitspecific accessions. Principal component analysis with seven components indicated relative importance of the traits (days to 50 % flowering, plant height, peduncle length, ear head length, and panicle exertion) to total divergence. Clustering analysis grouped biological races into three clusters wherein cultivated races vulgaris, plana, elongata, and compacta were grouped in Cluster I and wild races spontanea in Cluster II and africana in Cluster III. Accessions were identified as useful for important traits such as early flowering (34), high grain yield (38), fodder yield (19); more fingers (29); basal tiller number (25) and ear head length (28).

Diversity in jackfruit (Artocarpus heterophyllus Lam.): insights into fruit characterization for the identification of superior genotypes

2020 ◽  
pp. 1-9
Author(s):  
M.K. Dhakar ◽  
Bikash Das ◽  
P.K. Sarkar ◽  
Vishal Nath ◽  
A.K. Singh ◽  
...  
Keyword(s):  
Agricultural Research ◽  
Phenotypic Diversity ◽  
Crop Improvement ◽  
Fruit Size ◽  
Selection Procedure ◽  
Principal Component ◽  
Eastern Region ◽  
Artocarpus Heterophyllus ◽  
Commercial Cultivation ◽  
Wide Range

Abstract Jackfruit (Artocarpus heterophyllus Lam.) is a nutritious crop from the Moraceae family. The current study was undertaken to evaluate the phenotypic diversity of fruit characteristics using a set of 27 standardized fruit descriptors to describe 28 jackfruit genotypes. These data were used to identify the superior jackfruit genotype that could be used for commercial cultivation. The data revealed a wide range of differences among the genotypes for all the traits studied. Cluster analysis classified the genotypes into four major groups that confirmed the wide diversity among them. Principal component analysis (PCA) also revealed that 80.22% of the variability among the jackfruit genotypes was explained by the first five principal components (PCs). Based on the overall results, the Indian Council of Agricultural Research, Research Complex for Eastern Region (ICAR-RCER) JS 6/3 and 10/3 genotypes were found to be the most promising for table purposes (medium fruit size, pulp percentage >50 and total soluble solid (TSS) >20°Brix), whereas the ICAR-RCER JS 7/7 genotype with large fruit size, pulp percentage >50 and TSS >20°Brix was found to be suitable for processing. The coefficient of variation was the least for traits such as TSS (12.56%) and average seed length (13.56%). Hence, priority may also be given to the TSS and seed size when exploring promising genotypes and operating a selection procedure for crop improvement in jackfruit. The information generated under the study forms a potential baseline for fruit breeders to use in selecting genotypes with superior fruit qualities for jackfruit crop improvement programmes in the future.

scholarly journals Character association and path analysis for yield and its related traits in finger millet (Eleusine coracana (L.) Gaertn) genotypes

2017 ◽  
Vol 9 (3) ◽  
pp. 1624-1629
Author(s):  
Shivangi Negi ◽  
Arun Bhatt ◽  
Vineet Kumar
Keyword(s):  
Grain Yield ◽  
Seed Weight ◽  
Harvest Index ◽  
Finger Millet ◽  
Crop Improvement ◽  
Eleusine Coracana ◽  
Path Coefficient ◽  
Wide Range ◽  
Biological Yield ◽  
Peduncle Length

The present investigation was conducted during Kharif, 2014 at Research Block, Department of Crop Improvement, College of Forestry, Ranichauri Campus, V.C.S.G. Uttarakhand University of Horticulture and Forestry. The thirty-five diverse genotypes of finger millet, Eleusine coracana (L.) including three checks viz., PRM-1, PRM-2 and VL-149 laid out in Randomized Complete Block Design with replication. The data on 14 quantitative traits viz., days to 50 per cent flowering, days to maturity, plant height (cm), flag leaf area (cm2), peduncle length (cm), number of leaves on main culm, number of productive tillers per plant, number of fingers per ear, finger length (cm), ear length (cm), biological yield per plant (g), harvest index (%), 1000 seed weight, grain yield per plant (g) were collect-ed randomly from 5 plants form each genotypes. Analysis of variance revealed highly significant differences among all thirty five genotypes with a wide range of mean values for different characters. Grain yield per plant exhibited very strong positive association with biological yield per plant (0.6196, 0.6805), harvest index (0.4370, 0.3624), number of productive tillers per plant (0.3950, 0.4477), 1000 seed weight (0.3697, 0.3972) and peduncle length (0.2473, 0.2694) at phenotypic and genotypic level. Path-coefficient analysis indentified biological yield per plant (0.8983, 1.1590) and harvest index (0.7390, 0.9162) as major direct contributors towards grain yield per plant at phenotypic and genotypic level. The characters identified above merit due consideration in formulating effective selection strategy in finger millet for developing high yielding varieties.

scholarly journals Genetic variability of panicle architecture in traditional finger millets from Koraput valley of Eastern Ghats for crop improvement

2021 ◽  
Author(s):  
Debabrata Panda ◽  
Amrita Tanty ◽  
Prafulla K Behera ◽  
Aloukika Panda ◽  
Kartik Lenka
Keyword(s):  
Grain Yield ◽  
Leaf Area ◽  
Finger Millet ◽  
Crop Improvement ◽  
Principal Component ◽  
Eastern Ghats ◽  
Panicle Length ◽  
Improvement Program ◽  
Panicle Number ◽  
Panicle Weight

Abstract Panicle phenotyping is most demanding targets in crop breeding programs as panicle is an important plant parts that influences the grain yield. Diversity of panicle traits were analyzed in 20 traditional finger millet genotypes and three hybrid varieties from Koraput valley of Eastern Ghats. Significant difference of panicle characteristics like panicle length, panicle number, panicle weight, flag leaf area, panicle angle and grain yield were observed in experimented finger millet genotypes. In regards to principal component analysis, the first two axis of principal component obtained 52.97% of total variation and reflected huge difference between explored genotypes. Highest positive loading was observed for leaf weight followed by panicle number, panicle weight and panicle length and leaf area and are the major determinant for phenotypic variability. All the studied traits showed maximized phenotypic coefficient of variation (PCV) over genotypic variation (GCV) and lower differences found among them. The genotypes showed maximum broad-sense of heritability value for grain yield (82.27%) and panicle weight (75.96%) compared to other traits. In addition, genetic advance as mean% (GAM) ranged from 11.01–29.26% and high GAM was recorded for panicle angle, leaf area, panicle weight, panicle number and yield. It revealed that these characters can be used as selection criteria in crop improvement program for improving grain yield. Traditional finger millet genotypes such as Bhadi, Murda, Telgu and Chilli recorded superior panicle traits and Limca and Kalia showed better grain yield at par with the hybrids, which can be utilized in future crop improvement program.

scholarly journals Genetic Variability Studies for Yield and Yield Contributing Traits in Rabi sorghum (Sorghum bicolor L. Moench) in Relation to Drought Tolerance

2021 ◽  
pp. 130-137
Author(s):  
Kesoju Ravali ◽  
J. E. Jahagirdar ◽  
Chetana Singin ◽  
Sheetal Tirkey ◽  
S. S. Deshmukh
Keyword(s):  
Genetic Variability ◽  
Plant Height ◽  
Coefficient Of Variation ◽  
Crop Improvement ◽  
Breeding Program ◽  
Flowering Plant ◽  
Research Station ◽  
Total Biomass ◽  
Genetic Advance ◽  
Fodder Yield

Genetic variability studies were useful for effective selection in a crop species. Presence of desirable variation and the amount of that variation which is heritable is the primary requirement of any breeding program for the crop improvement. Therefore any breeding program for crop improvement depends majorly on the knowledge pertaining to genetic variability, heritability and genetic advance. The genetic variability study was carried out for yield and yield contributing traits in thirty-seven genotypes of rabi sorghum with three checks namely M 35-1, Phule Suchitra and CSV-22-R at Sorghum Research Station, V.N.M.K.V., Parbhani during rabi 2019. A randomized block design was used with three replications and these treatments were evaluated and data pertaining to eleven traits were recorded with the objective to estimate the genetic variability for the quantitative traits. This investigation revealed presence of highly significant differences among the genotypes indicating presence of large amount of variability in all the eleven characters studied. The study indicated presence of higher estimates of phenotypic coefficient of variation (PCV) for all the traits when compared to genotypic coefficient of variation (GCV) and these estimates are of lower magnitude. Among the forty genotypes studied VJV 107, VJV 106, PEC 30, RSV 1921, RSV 1945 and RSV 1984 were considered as the superior genotypes as these recorded better performance. Higher estimates of GCV and PCV were recorded for the traits; days to 50 per cent flowering, plant height, panicle length, panicle width, fodder yield per plant, biological yield per plant, harvest index and grain yield per plant indicating selection for higher values of these traits of sorghum would be effective. Whereas high heritability coupled with moderate to high genetic advance was observed for traits like plant height, fodder yield per plant and total biomass per plant.

Microsatellite Marker: Importance and Implications of Cross-genome Analysis for Finger Millet (Eleusine coracana (L.) Gaertn)

2020 ◽  
Vol 9 (3) ◽  
pp. 160-170
Author(s):  
Thumadath P.A. Krishna ◽  
Maharajan Theivanayagam ◽  
Gurusunathan V. Roch ◽  
Veeramuthu Duraipandiyan ◽  
Savarimuthu Ignacimuthu
Keyword(s):  
Molecular Marker ◽  
Microsatellite Markers ◽  
Ssr Markers ◽  
Genome Analysis ◽  
Related Species ◽  
Finger Millet ◽  
Crop Improvement ◽  
Human Beings ◽  
Closely Related Species ◽  
Genome Amplification

Finger millet is a superior staple food for human beings. Microsatellite or Simple Sequence Repeat (SSR) marker is a powerful tool for genetic mapping, diversity analysis and plant breeding. In finger millet, microsatellites show a higher level of polymorphism than other molecular marker systems. The identification and development of microsatellite markers are extremely expensive and time-consuming. Only less than 50% of SSR markers have been developed from microsatellite sequences for finger millet. Therefore, it is important to transfer SSR markers developed for related species/genus to finger millet. Cross-genome transferability is the easiest and cheapest method to develop SSR markers. Many comparative mapping studies using microsatellite markers clearly revealed the presence of synteny within the genomes of closely related species/ genus. Sufficient homology exists among several crop plant genomes in the sequences flanking the SSR loci. Thus, the SSR markers are beneficial to amplify the target regions in the finger millet genome. Many SSR markers were used for the analysis of cross-genome amplification in various plants such as Setaria italica, Pennisetum glaucum, Oryza sativa, Triticum aestivum, Zea mays and Hordeum vulgare. However, there is very little information available about cross-genome amplification of these markers in finger millet. The only limited report is available for the utilization of cross-genome amplified microsatellite markers in genetic analysis, gene mapping and other applications in finger millet. This review highlights the importance and implication of microsatellite markers such as genomic SSR (gSSR) and Expressed Sequence Tag (EST)-SSR in cross-genome analysis in finger millet. Nowadays, crop improvement has been one of the major priority areas of research in agriculture. The genome assisted breeding and genetic engineering plays a very crucial role in enhancing crop productivity. The rapid advance in molecular marker technology is helpful for crop improvement. Therefore, this review will be very helpful to the researchers for understanding the importance and implication of SSR markers in closely related species.

Spatial clustering analysis of green economy based on knowledge graph

2021 ◽  
pp. 1-10
Author(s):  
Shiyuan Zhou ◽  
Xiaoqin Yang ◽  
Qianli Chang
Keyword(s):  
Spatial Data ◽  
Clustering Analysis ◽  
Spatial Clustering ◽  
Evaluation Model ◽  
Principal Component ◽  
Green Economy ◽  
Membership Degree ◽  
Two Dimensional ◽  
Dimensional Graph ◽  
Improved Algorithm

By organically combining principal component analysis, spatial autocorrelation algorithm and two-dimensional graph theory clustering algorithm, the comprehensive evaluation model of regional green economy is explored and established. Based on the evaluation index system of regional green economy, this paper evaluates the development of regional green economy comprehensively by using principal component analysis, and evaluates the competitive advantage of green economy and analyzes the spatial autocorrelation based on the evaluation results. Finally, the green economy and local index score as observed values, by using the method of two-dimensional graph clustering analysis of spatial clustering. In view of the fuzzy k –modes cluster membership degree measure method without considering the defects of the spatial distribution of object, double the distance and density measurement of measure method is introduced into the fuzzy algorithm of k –modes, thus in a more reasonable way to update the membership degree of the object. Vote, MUSH-ROOM and ZOO data sets in UCI machine learning library were used for testing, and the F value of the improved algorithm was better than that of the previous one, indicating that the improved algorithm had good clustering effect. Finally, the improved algorithm is applied to the spatial data collected from Baidu Map to cluster, and a good clustering result is obtained, which shows the feasibility and effectiveness of the algorithm applied to spatial data. Results show that the development of green economy using the analysis method of combining quantitative analysis and qualitative analysis, explores the connotation of green economy with space evaluation model is feasible, small make up for the qualitative analysis of the green economy in the past, can objective system to reflect the regional green economic development level, will help policy makers scientific formulating regional economic development strategy, green integrated development of regional green economy from the macroscopic Angle, the development of network system.

Multivariate analyses of indigenous bread wheat (Triticum aestivum L.) landraces of Oman

2021 ◽  
pp. 483
Author(s):  
Ali Hussain Al Lawati ◽  
Saleem Kaseemsaheb Nadaf ◽  
Nadiya Abubakar Al Saady ◽  
Saleh Ali Al Hinai ◽  
Almandhar Almamari ◽  
...  
Keyword(s):  
Triticum Aestivum ◽  
Bread Wheat ◽  
Multivariate Analyses ◽  
Crop Improvement ◽  
Winter Season ◽  
Principal Component ◽  
Triticum Aestivum L ◽  
Plant Parts ◽  
Improvement Programs ◽  
D Values

Oman is endowed with enormous diversity of important food crops that have global significance for food security and has ancient history of cultivation of bread wheat (Triticum aestivum L.) with its divergent landraces, which are useful in crop improvement. 55 indigenous Omani accessions conserved at the USDA were evaluated in the winter season (November to April) of the years 2017-2018 and 2018-2019 on loamy soil under sprinklers in augmented design with 5 check varieties in 5 replications following crop husbandry practices as per national recommendations using 9 quantitative (descriptors) and 6 qualitative traits (anthocyanin pigmentation on plant parts). The data on traits were subjected not only for PC values and D values after varimax rotation through Kaiser normalization in Principal Component Analysis (PCA) but also for Agglomerative Hierarchical Clustering (AHC). The results indicated that indigenous bread wheat accessions were significantly different (p>0.05) for all the quantitative traits except number of tillers. The multivariate analyses led to formation of four diverse clusters from PCA analyses corresponding to four quadrants of bi-plot graphs and three clusters from AHC analysis corresponding to main clades of dendrogram. The parents were selected from common accessions of distinct clusters in all the multivariate analyses for hybridization for improving characters of growth for higher yield or productivity with pigmentation on one or two plant parts useful for DUS test of varieties. The indigenous bread wheat landraces / accessions were genetically diverse and have potential for use in national crop improvement programs for earliness and higher grain productivity with distinct identification markers.

scholarly journals Clustering analysis of the distribution characteristics of unobserved economic regions in China——Based on multi-indicator panel data

2021 ◽  
Vol 275 ◽  
pp. 01072
Author(s):  
Yang Fan
Keyword(s):  
Panel Data ◽  
Clustering Analysis ◽  
Principal Component ◽  
Entropy Method ◽  
Practical Significance ◽  
Economic Governance ◽  
Factors Affecting ◽  
Use Of Resources ◽  
Economic Regions ◽  
Component Feature

The existence of unobserved economy is one of the important factors affecting GDP calculation. This paper uses the provincial panel data from 2010 to 2019 in China, and adopts the method of principal component feature extraction to carry out cluster analysis on the multi-indicator panel data. This method preserves the dynamic characteristics of the panel data, calculates the comprehensive score of each eigenvalue, and gives weight to the eigenvalue by using the entropy method, so as to optimize the clustering results representing the eight indicators of the unobserved economy. Through the analysis, it is found that the regional development of China’s unobserved economy is obviously different, and each type has different influencing factors. This result has important practical significance for different regions in China to formulate differentiated unobserved economic governance policies. This also helps to make better use of resources and develop an energy-saving economy.

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