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Surya Kumari, S.
- Variability Studies in Chilli (Capsicum annuum L.) with Reference to Yield Attributes
Abstract Views :213 |
PDF Views:151
Authors
Affiliations
1 Horticultural Research Station, Andhra Pradesh Horticultural University, Lam, Guntur-522 034, IN
2 Horticultural Research Station, Andhra Pradesh Horticultural University Lam, Guntur - 522 034, IN
1 Horticultural Research Station, Andhra Pradesh Horticultural University, Lam, Guntur-522 034, IN
2 Horticultural Research Station, Andhra Pradesh Horticultural University Lam, Guntur - 522 034, IN
Source
Journal of Horticultural Sciences, Vol 6, No 2 (2011), Pagination: 133-135Abstract
Field experiments were conducted at Regional Agricultural Research Station, Lam, Guntur, Andhra Pradesh during the rainy season 2004-2007, with ten chilli genotypes supplied by AICRP on vegetables (from different geographical sources). This was to study genetic variability, heritability and genetic advance as per cent mean for several economic characters to identify promising cultivars suitable for the Krishna-Godavari zone of Andhra Pradesh. Data were collected on eight characters, viz., plant height, plant spread and number of fruits per plant; fruit length, fruit girth, number of seeds per fruit, ripe-chilli yield and dry-chilli yield. Significant differences were observed among genotypes in respect of all the characters studied. Phenotypic Coefficient of Variation (PCV) was slightly higher than Genotypic Coefficient of Variation (GCV) for all the traits, indicating a low environmental influence on expression of these traits. High GCV and PCV were observed for ripe-chilli yield, dry-chilli yield, number of fruits per plant, number of seeds per fruit and fruit length indicating a higher magnitude of variability in these traits and, consequently, a greater scope for improvement through simple selection. Low GCV and PCV were recorded for plant height, plant spread and fruit girth suggesting a limited variability, for these traits. High heritability, coupled with high Genetic Advance as per cent mean, was observed for ripe-chilli yield, dry chilli yield, number of fruits per plant, number of seeds per fruit and fruit length, indicating the influence of additive genes. These characters-with high GCV, PCV, Heritability and Genetic Advance as per cent mean-should be considered as reliable selection criteria for crop improvement for yield and yield attributing characters in chilli.Keywords
Capsicum annuum, Variability, GCV, PCV, Heritability, Genetic Advance.- Productivity in Chilli (cv. LCA 334) as Influenced by Organic and Inorganic Nutrient Management in Vertisols
Abstract Views :185 |
PDF Views:107
Authors
Affiliations
1 Regional Agricultural Research Station, Lam, Guntur- 522034, IN
1 Regional Agricultural Research Station, Lam, Guntur- 522034, IN
Source
Journal of Horticultural Sciences, Vol 6, No 1 (2011), Pagination: 62-65Abstract
A field experiment was conducted at Regional Agricultural Research Station, Lam, Guntur during the kharif season of 2003-04 and 2004-05 in vertisols with an objective to assess effectiveness of organic nutrient package for yield sustainability and to assess inorganic nutrient management package vis-a-vis organic package for yield and quality in chilli cv. LCA 334. Farmers of this region generally use very high doses of inorganic fertilizers with improper nutrient balance which has led to deterioration of productivity and quality of both the produce soil. The experiment was carried out in randomized block design with ten treatments, in combinations of organic and inorganic sources. The organic sources used were: green manure (incorporation of pillipesara), neem cake, Azospirillum, phosphate solubilizing bacteria, VAM and burnt ash, and integrated with 50%, 75% and 100% recommended nitrogen in the form of chemical fertilizer. Results revealed that maximum dry chilli yield ( 5397kg ha-1) was recorded in combined application of green manure, neem cake, Azospirillum, phosphate solubilizing bacteria, burnt ash along with 100% recommended nitrogen.Keywords
Chilli, Organic, Inorganic Nutrient Management.- An Experimental Method for Clustering Sentiment using Data with Emoticons
Abstract Views :165 |
PDF Views:0
Authors
Affiliations
1 Department of Computer Science, S. V. University, Tirupathi – 517502, Andhra Pradesh, IN
1 Department of Computer Science, S. V. University, Tirupathi – 517502, Andhra Pradesh, IN