Yajuvendra Singh
National Dairy Research Institute
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Featured researches published by Yajuvendra Singh.
Animal Science Journal | 2011
Yajuvendra Singh; Surender Singh Lathwal; A K Chakravarty; A. K. Gupta; Tushar Kumar Mohanty; T.V. Raja; Roshan Lal Dangi; Biplob Kumer Roy
In present study production performance of 96 lame cows was compared with 67 healthy cows. No significant effect of parity and year of calving on milk yield were observed but the effect of season of calving was significant (P < 0.01). Effect of lameness on milk yield at the second, third and fourth months and 305 days was highly significant (P < 0.01), and was also significant (P < 0.05) on lactation yield of the fifth and tenth months. The effect of lameness on monthly and 305-day milk yield was significant (P < 0.01) only for those cows diagnosed lame before calving and during the first month of lactation. The differences in mean monthly yield were highly significant (P < 0.01) at the second, third and fourth months; and significant (P < 0.05) in the first and fifth months. The loss in the first lactation month of cows which were diagnosed as lame in the second month, was found to be significant (P < 0.05). Thus the yield of the month previous to the diagnosis (sub-clinical stage) was also affected. A significant (P < 0.01) total loss of 498.95 kg of milk yield was observed during a period of 305 days.
Indian Journal of Animal Research | 2015
Man Singh; S.S. Lathwal; Yajuvendra Singh; T. K. Mohanty; A.P.Ruhil; Navav Singh
The present study was carried out to predict various categories of lameness by using percent body weight distribution to all the four limbs of lactating Karan Fries crossbred cows. Load sensors were able to detect an abnormal distribution of body weight to individual limbs. Among the cows, 22.97% were afflicted with mild, 14.19% with moderate, 21.62% with lame, 6.75% with severe and rest with no lameness. Prediction of 5-point scale of lameness based on percent body weight distribution to all four limbs of cows through multi-nominal logistic regression could be done with an accuracy of 70.6, 47.1, 0.0, 50.0 and 0.0% into no lame, mild, moderate, lame and severe lame categories. Cox and Snell, Nagelkerke and McFadden pseudo R2 values for the present model in prediction of various categories of 5-point scale of lameness using percent body weight distribution to all four limbs was observed to be 32.0, 33.7 and 12.9% respectively while these values for 3-point scale were observed to be 46.0, 54.0 and 32.3%, respectively. The percent correct classification of no lame, mild and severe lame category in 3-point scale was observed to be 91.8, 0.0 and 73.8%, respectively. The overall percentage of correct classification rate of 3-point scale was much higher (73.6%) as compared to 5-point scale (45.9%).
Indian Journal of Plant Genetic Resources | 2014
Yajuvendra Singh; Ss Gaurav; Dinesh Kumar
The objective of this study was to estimate gene effects and identification of transgressive segregants for five quantitative traits of seven crosses of Ocimum basilicum L. viz. EC388788 × IC333322, EC387893 × IC326711, EC388896 × IC369247, EC388887 × IC386833, EC387837 × EC338785, IC369247 × IC370846 and IC344681 × IC326735 by generation mean analysis. In cases both type of epistasis (complementary and duplicate) model was sufficient to explain variation in generation means. Generation mean analysis with three parameter model with χ2 test indicated that additive-dominance model was inadequate for all the traits like number of inflorescence, length of inflorescence, fresh herb yield, dry herb yield and oil content in all the crosses used of six parameter models to estimate the gene effects. The observed frequencies of transgressive segregants for trait oil content (4.942), fresh herb yield (11.824), dry herb yield (13.97) and length of inflorescence (5.820). A comparison of generation mean analysis for observed and predicted frequencies of transgressive segregants indicated that the potential crosses for transgressive segregants were those that had additive and dominance gene effects. The adequacies of certain models of inheritance as well as the importance and significance of gene effects and identifications of transgressive segregants for analyzed traits were dependent upon the particular crossing combination and experimental site. The present study indicated that early generation selection is effective and should be practiced for future breeding programme.
Indian Journal of Animal Sciences | 2008
Sunit Kumar; Yajuvendra Singh; DHrriENDRA Kumar
international conference on pattern recognition | 2012
Om D. Deshmukh; Nitendra Rajput; Yajuvendra Singh; Surender Singh Lathwal
Indian Journal of Animal Sciences | 2012
Man Singh; S.S. Lathwal; Yajuvendra Singh; Anil Kumar; Arti Gupta; T. K. Mohanty; T.V. Raja; Rashik Gupta; V. P. Sharma; Gulab Chandra; Muneendra Kumar
Indian Journal of Animal Research | 2017
Archana Yadav; Yajuvendra Singh; Garima Shukla; P.K. Shukla; Rajneesh Sirohi; Muneendra Kumar; Dilip Swain; Mamta
Indian Journal of Animal Research | 2016
Archana Yadav; Yajuvendra Singh; Garima Shukla; P.K. Shukla; Muneendra Kumar; D.N. Singhand Ajay Kumar
Annals of Agricultural Research | 2016
Deepak Kumar; Rajbala Singh; Yajuvendra Singh
Indian Journal of Animal Sciences | 2015
Yajuvendra Singh; S.S. Lathwal; Indu Devi; A.P.Ruhil; Nitendra Rajput; T.V. Raja; Muneendra Kumar; Rashik Gupta