P. Raghuram Reddy
Central Research Institute for Dryland Agriculture
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Featured researches published by P. Raghuram Reddy.
Plant Genetic Resources | 2009
N. Sunil; N. Sivaraj; S. R. Pandravada; V. Kamala; P. Raghuram Reddy; K. S. Varaprasad
Nine characters contributing to seed yield were measured on 20 accessions of horse gram (Macrotyloma uniflorum (Lam.) Verd), and subjected to genetic divergence analysis using Mahalanobis statistic and mapping using DIVA-GIS. The accessions were collected from two eco-geographical regions of Andhra Pradesh (India) – North Coastal and Rayalaseema. Based on D 2 values the genotypes were grouped into five clusters. Genetic diversity was not related to eco-geographical distribution. The greatest inter-cluster distance separated clusters II and V, followed by clusters IV, and V, III and IV. Entries in clusters V and II appear suitable as parents for horse gram improvement. The Rayalaseema region is the source of useful variation for days to flowering, maturity and yield.
Helia | 2013
M. Vanaja; G.R. Maruthi Sankar; M. Maheswari; P. Raghuram Reddy; N. Jyothi Lakshmi; S. K. Yadav; G. Archana; B. Venkateswarlu
SUMMARY A study was conducted in the Open Top Chambers (OTCs) to assess the influence of cool and warm season conditions on the response of sunflower (KBSH-1) to two elevated CO2 levels (550 and 700 ppm) and compare them with the response to an ambient level (390 ppm). The effect of elevated CO2 levels on biomass accumulation, seed yield and yield components were quantified in two seasons. Apart from the main effects of CO2 and different seasons, a significant interaction effect between CO2 levels and seasons was also observed. The CO2 levels differed significantly in influencing biomass accumulation, seed yield and number of seeds. Four Principal Components (PC) based on PC analysis explained about 85% of the variability in the response of traits influenced by CO2 levels in winter and summer seasons. In order to predict total dry weight, seed yield and harvest index obtained in winter and summer seasons, regression models of these variables were also calibrated and used through PC scores of different components. The analysis indicated that significant predictions could be made at ambient level with 550 ppm, compared to 700 ppm of CO2 level. The plant traits with a significantly higher loading of more than ± 0.70 on PCs were identified and have been recommended for future research in genetic improvement of sunflower, taking into account the change of climate due to elevated CO2 and temperature levels.
Plant Soil and Environment | 2018
M. Vanaja; P. Raghuram Reddy; N. Jyothi Lakshmi; M. Maheswari; P. Ratnakumar; M. Jyothi; B. Venkateswarlu
Plant Soil and Environment | 2018
M. Vanaja; M. Jyothi; P. Ratnakumar; P. Raghuram Reddy; N. Jyothi Lakshmi; M Maheshwari; B. Venkateswarlu
Plant Soil and Environment | 2018
M. Vanaja; P. Vagheera; P. Ratnakumar; N. Jyothi Lakshmi; P. Raghuram Reddy; Suresh Yadav; M. Maheswari; B. Venkateswarlu
Indian Journal of Agricultural Sciences | 2013
N. Jyothi Lakshmi; M. Vanaja; S. K. Yadav; M. Maheswari; P. Vagheera; P. Raghuram Reddy; B. Venkateswarlu
Indian Journal of Genetics and Plant Breeding | 2005
G. R. Maruthi Sankar; P. Raghuram Reddy
Journal of Sustainable Agriculture | 2008
V. Maruthi; K. Srinivas; G. Subba Reddy; B. Sanjeeva Reddy; K.S. Reddy; P. Raghuram Reddy; R. Sudhakar; Y. S. Ramakrishna
Legume Research | 2017
V. Maruthi; P. Raghuram Reddy; K.S. Reddy; B.M.K. Reddy; Salini; D.G.M. Saroja
Journal of Food Legumes | 2009
N. Jyothi Lakshmi; M. Vanaja; M. Maheswari; S. K. Yadav; P. Raghuram Reddy; B. Venkateswarlu