R Rajendran

Dr. R Rajendran


Research Focus & Metrics

Academic Career Length

5Years (2022-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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17 December 2022 in Tropical Animal Health and Production
Verified
Journal Article
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A.K. ThiruvenkadanA.K. Thiruvenkadan
A.K. Thiruvenkadan
Muralidharan JMuralidharan J
Muralidharan J
RRR Rajendran
R Rajendran
BCBandeswaran Chinnaondi
Bandeswaran Chinnaondi
SISatish Kumar Illa
Satish Kumar Illa
Sunday Olusola PetersSunday Olusola Peters
Sunday Olusola Peters

1 January 2024 in Indian Journal of Small Ruminants (The)
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Journal Article
Closed access
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ACA.B. Chaudhari
A.B. Chaudhari
RRR Rajendran
R Rajendran
VRV. Ragothaman
V. Ragothaman
SSS. Meenakshi Sundaram
S. Meenakshi Sundaram
Reproduction data of 4527 Nilagiri and 5950 Nilagiri Synthetic breeding ewes maintained at Sheep Breeding Research Station, Sandynallah (Tamil Nadu), spread over 27 years (1989 to 2015) were used to evaluate the replacement rate, reproduction rate, flock structure and dynamics. The replacement rate was significantly higher (P<0.001) in Nilagiri (0.29) than Nilagiri Synthetic sheep (0.26). The age-specific death rate ranged from 0.026 (3.5 to 4.5 years) to 0.191 (6.5 to 7.5 years) with highest of 0.191 and 0.134 in Nilagiri and Nilagiri Synthetic sheep from 1.5 to 7.5 years of age, respectively. The retention period of five years of age with a net reproduction rate of 1.024 in Nilagiri and six years of age with a net reproduction rate of 1.196 in Nilagiri Synthetic was found ideal to meet replacement requirement of flock. Nilagiri ewes in intermediate ages had more multiple births and older ewes weaned more lambs. The retention of Nilagiri ewes up to fifth lambing and Nilagiri Synthetic ewes up to third lambing in the flock was found ideal to maintain flock strength. The results of Ro and rm showed that the flock must consist of six age groups to maintain its size and replacement. It may be recommended to cull the breeding ewe at the age of six years to accelerate genetic improvement. Based on the findings, suitable breeding policy of selection and culling should be formulated.

11 August 2023 in Research Square
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Preprint
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Arth Bhaljibhai ChaudhariArth Bhaljibhai Chaudhari
Arth Bhaljibhai Chaudhari
RRR Rajendran
R Rajendran
VRVenkataramanan Ragothaman
Venkataramanan Ragothaman
KGK.V. Gowrimanokari
K.V. Gowrimanokari
The objective of this study was to assess the effect of non-genetic and genetic factors and to estimate the genetic parameters and trends for reproduction and fitness traits of threatened Nilagiri sheep reared under semi-intensive management system. Data used in the present study were collected over a years from 1989 to 2013 (25 years). A total of 6001 individual phenotypic information from about 1129 ewes with variable number of records for each reproduction and fitness traits were used. The reproduction and fitness traits were analysed for the effects of genetic and non-genetic factors, respectively. Fixed effect analysis was carried out using general linear model procedures using SPSS. Variance components and genetic parameters were estimated with univariate analysis by fitting Restricted Maximum Likelihood Method (REML) using WOMBAT programme, by fitting an animal model for all the traits. Three different animal models were fitted by including or excluding maternal effects was used to estimates genetic parameters. Nilagiri sheep had overall mean for all reproduction and fitness traits were estimated. Based on best fitted univariate models, direct heritability estimates, for reproduction and fitness traits ranges from 0.04 to 0.258 were, respectively. Whereas, genetic and phenotypic correlation coefficients between litter size and birth and litter size at weaning were 1.00 ± 0.077 and 0.89 ± 0.007 in Nilagiri sheep which implies the possibility of indirect selection. Genetic changes over the selection period (genetic parameters and genetic trend over the years) suggested that the genetic selection and appropriate management can lead to improvement of Nilagiri sheep.

27 July 2023 in Research Square
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Arth Bhaljibhai ChaudhariArth Bhaljibhai Chaudhari
Arth Bhaljibhai Chaudhari
RRR Rajendran
R Rajendran
VRVenkataramanan Ragothaman
Venkataramanan Ragothaman
Background The Nilagiri Synthetic was evolved at the Sheep Breeding Research Station, Sandynallah, The Nilgiris, by crossing Nilagiri with Merino and Rambouillet sheep in the year 1986 and performances evaluated by Iyue in the year 1993. Nilagiri Synthetic sheep are maintained for mutton and fine wool production. The presence of FecB mutation, which increases fecundity, has been confirmed recently in Nilagiri Synthetic breed. Methods To find out the scope for utilizing this mutation in the breeding programme to exploit the population, evaluation of effect of this mutation on litter traits was carried out. Litter sizes were compared between non-carrier wild type (++) and carrier (B+) ewes. Result The litter size at birth was 1.09 ± 0.10 and 1.60 ± 0.10, respectively. The litter size at weaning was 1.09 ± 0.11 and 1.56 ± 0.12, respectively. The litter size at birth, litter size at weaning and lifetime traits of litter size were higher among carrier animals. These results indicate scope for utilising the FecB mutation to improve prolificacy in the Nilagiri Synthetic breed.

8 March 2023
Verified
Book Chapter
Open access
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RRR Rajendran
R Rajendran
ATA. K. Thiruvenkadan
A. K. Thiruvenkadan
MKM. R. Kishore
M. R. Kishore
Internet of Things (IoT) is a collective network of real-world objects with sensors and connectivity. Lot of data is obtained through the sensor and networks to analyse the behaviour of the subject involved. Smart farming involves monitoring and managing of animal farms using modern ICT and data tools to increase production efficiency. With increasing population and the food requirement, optimised and sustainable production has become the need of hour. From Farm management, field handling to research scenarios, IoT plays various roles in enhancing the outcome of intended production. Areas like animal identification, animal health, vital monitoring, whereabout tracking, disease intelligence, production quality and quantity monitoring have scope for improvement using IoT. The data generated gives visibility and perspectives that are not so clear or new paradigms may emerge in production efficiency. The data defined approach improves production and management efficiency by enabling quick and easy decisions in farm control and management. These are a big leap from conventional farming and they bring certainty and predictability to farming whose future will be technology driven. Being in the early stages of the digital transformation in animal husbandry, there is still a long way to go in the path demanding collaboration from various domain stakeholders like animal sciences and information technology for holistic and sustainable improvement.

29 August 2023 in Research Square
Verified
Preprint
Open access
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Arth Bhaljibhai ChaudhariArth Bhaljibhai Chaudhari
Arth Bhaljibhai Chaudhari
RRR Rajendran
R Rajendran
VRVenkataramanan Ragothaman
Venkataramanan Ragothaman
SSS. Meenakshi Sundaram
S. Meenakshi Sundaram
Reproduction data of 4648 Nilagiri and 6542 Nilagiri Synthetic ewe records spreads over 27 years (from 1989 to 2015) representing 4530 Nilagiri and 5950 Nilagiri Synthetic breeding ewes were used in this study. Flocks belonged to the Sheep Breeding Research Station, Sandynallah, India. Flock dynamics of six age groups (1.5–7.5 yrs) were assessed. Ultimate objective of this research work was to evaluate the replacement rate, reproduction rate, flock structure and dynamics of Nilagiri and Nilagiri Synthetic sheep breeds. Three parameters were used to evaluate flock dynamics, age specific replacement rate, net reproduction rate and intrinsic rate of increase or innate capacity for increase of population. The replacement rate estimated was significantly higher (P value < 0.002) in Nilagiri (0.289) than Nilagiri Synthetic sheep (0.260). The age-specific death rates ranged from 0.026 (3.5–4.5 years) to 0.191 (6.5–7.5 years) with highest 0.191 and 0.134 in Nilagiri and Nilagiri Synthetic sheep from 1.5 to 7.5 years of age, respectively. The replacement requirements will be met if the ewes are kept in the flock until five years of age with a net reproduction rate of 1.024 in Nilagiri and if the ewes are kept in the flock until six years of age with a net reproduction rate of 1.196 in Nilagiri Synthetic. Nilagiri ewes in intermediate ages had more multiple births and older ewes weaned more lambs. The flock strength was not maintained unless the ewes were kept till the fifth lambing Nilagiri, third lambing in Nilagiri Synthetic sheep. All estimates tended to increase with dams age up to six years and decreased thereafter. The results of Ro and rm showed that the studied flock must consist of 6 age groups to maintain its size and replace itself. It may be recommended to cull the breeding ewe at the age of 6 years to accelerate genetic improvement. Based on the findings it is concluded that suitable breeding policy of selection and culling of such flock should be formulated.