3 research outputs found
ANALYSIS OF GENETIC DIVERSITY IN TWELVE CULTIVARS OF PEA BASED ON MORPHOLOGICAL AND SIMPLE SEQUENCE REPEAT MARKERS
Pea(Pisum sativum L.)is the second most important legume crop worldwide after chickpea (Cicer arietinum L.) and valuable resources for their genetic improvement. This study aimed to analyze genetic diversity of pea cultivars through morphological and molecular markers. The present investigation was carried out with 12 pea cultivars using 28 simple sequence repeat markers. A total of 60 polymorphic bands with an average of 2.31 bands per primer were obtained. The polymorphic information content, diversity index and resolving power were ranged from 0.50 to 0.33, 0.61 to 0.86 and 0.44 to 1.0 with an average of 0.46, 0.73 and 0.76, respectively. The 12 pea cultivars were grouped into 3 clusters obtained from cluster analysis with a Jaccardd’s similarity coefficient range of 0.47-0.78, indicating the sufficient genetic divergence among these cultivars of pea. The principal component analysis showed that first three principal components explained 86.97% of the total variation, suggesting the contribution of quantitative traits in genetic variability. The contribution of 32.59% for number of seeds per plant, stem circumference, number of pods per plant and number of seeds per pod in the PC1 leads to the conclusion that these traits contribute more to the total variation observed in the 12 pea cultivars and would make a good parental stock material. Overall, this SSR analysis complements morphological characters of initial selection of these pea germplasms for future breeding program
Renewable energy generating employment specially in Indian agriculture
The present review explains that renewable energy generates opportunity in field of agriculture. The renewable energy is solar energy, wind energy, water energy and biogas energy. This energy generates employment of manufacturing, design, construction, installation, operation, maintainance, supply chain, multitasking, research, development and administration. The solar industry employs 21,000 people in 2016-17 and 25,000 people in 2017-18. The solar manufacturing industries and solar products will produce various opportunities by 2022 in India. The wind energy provides 4,40,000 employments into onshore and offshore grid system in 2008. The wind mill industry will create 74,000 employments by 2020 in India. The water energy provides employment into hydro electric power station, manufacturing industry and others area. Biogas energy utilizes into motor vehicle as fuel. It saves petrol worth about 0.66 million per annum and also generate employment for 12 persons. The Biogas industry will set up 19 districts of the Maharashtra state to employment generation by 2020. Renewable energy protects the earth planet. It provides employment to rural as well as urban areas. It will improve standard of living and per capita income of people. It will introduce employment to poor and literate persons. It would advocate gender uniformity and doubling of farmer income. It will improve and strengthens Gross Domestic Product and Agriculture shares in India. This energy would encourage huge transition into future era in India
Analysis of Genetic Diversity in Twelve Cultivars of Pea Based on Morphological and Simple Sequence Repeat Markers
Pea(Pisum sativum L.)is the second most important legume crop worldwide after chickpea (Cicer arietinum L.) and valuable resources for their genetic improvement. This study aimed to analyze genetic diversity of pea cultivars through morphological and molecular markers. The present investigation was carried out with 12 pea cultivars using 28 simple sequence repeat markers. A total of 60 polymorphic bands with an average of 2.31 bands per primer were obtained. The polymorphic information content, diversity index and resolving power were ranged from 0.50 to 0.33, 0.61 to 0.86 and 0.44 to 1.0 with an average of 0.46, 0.73 and 0.76, respectively. The 12 pea cultivars were grouped into 3 clusters obtained from cluster analysis with a Jaccardd's similarity coefficient range of 0.47-0.78, indicating the sufficient genetic divergence among these cultivars of pea. The principal component analysis showed that first three principal components explained 86.97% of the total variation, suggesting the contribution of quantitative traits in genetic variability. The contribution of 32.59% for number of seeds per plant, stem circumference, number of pods per plant and number of seeds per pod in the PC1 leads to the conclusion that these traits contribute more to the total variation observed in the 12 pea cultivars and would make a good parental stock material. Overall, this SSR analysis complements morphological characters of initial selection of these pea germplasms for future breeding program