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BS Shrestha, DMU SP Neopane, NPC NP Shrestha, NC

Dairy Cattle Improvement Project (TCP/NEP/3105D): Preliminary Results, Lesson Learnt and Problems Encountered. BS Shrestha, DMU SP Neopane, NPC NP Shrestha, NC. Presentation- outline. Background DCIP – Introduction and Current Status Some Preliminary Results Lesson Learnt

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BS Shrestha, DMU SP Neopane, NPC NP Shrestha, NC

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  1. Dairy Cattle Improvement Project (TCP/NEP/3105D): Preliminary Results, Lesson Learnt and Problems Encountered BS Shrestha, DMU SP Neopane, NPC NP Shrestha, NC

  2. Presentation- outline Background DCIP – Introduction and Current Status Some Preliminary Results Lesson Learnt Problems Encountered Way forward

  3. Background • 7 Million cattle population • 7 Native breeds • one extinct • few endangered • More than 70% HH involvement

  4. Background…Cattle Improvement initiatives • Potential of indigenous cattle (lactation)-poor-other function important (draft, manure, religious) • Breed replacement, cross breeding, or upgrading – the option of choice for improvement • Introduction of some European cattle breed in Rana regimes – 150 yrs ago • Importation of Red Sindhi, Sahiwal, Jersey, HF, Brown Swiss • Importation of frozen semen and AI • AI with warm semen • Frozen semen production and utilization in country

  5. Proportion of indigenous and improved cattle • Despite of all • No sustainable dairy animal genetic improvement program in the country • Non existence of PPRS and unknown bull (merit) used for semen collection &NS

  6. DCIP- Introduction • Joint Project of NARC and DLS supported by FAO • Implemented Since July 2008 with the main objective of sustainable genetic improvement of dairy cattle in the country through: • Initiation of PPRS and Identification of potential bull mothers and production of bulls for AI and NS • Capacity enhancement of trainers/extension workers through training on Feeding and management • Supporting herd book establishment for Jersey and HF • Identifying suitable breed/s for different eco-zones and mgmt system • Developing strategies that will help private sector to undertake PPRS for sustainability and AI privatization

  7. DCIP- Implementation • Steering committee chaired by DG, DLS • Project management committee (NPC, NPCC, NC) • ICBG- Technical support for database management and analysis • ICFM-Technical Support for capacity enhancement of trainers in feeding and management • NC- Project Implementation Support and coordination with FAOR/Nepal • Programme Officer, FAOR- project facilitation • NLBC- semen and LN handling and distribution • DMU- data management, analysis and information flow • District supervisor and Technicians • Recorders and farmers • Overall coordination and technical support- LTO

  8. Major Activities/ Accomplishment Inception Workshop, July 2008

  9. TOT and Initiation of PPRS

  10. PPRS……

  11. Recorders’ and Technicians’ Training

  12. Database management system development

  13. Training on Animal Breeding and Genetics and PPRS data analysis

  14. Milk Sample Analysis Facility Establishment

  15. TOT on Dairy Cattle Feeding and Management

  16. Farmers’ Training and Meet • AI of PPRS herd cows with imported semen • Preliminary data analysis • Initiation of planned mating of selected potential bull mothers with proven sire semen

  17. Procurement of Necessary Materials • Frozen semen 5000+5000 doses from New Zealand (HF and Jersey) • Lacto scans • Computers and printer • LN Container, referees • Tags and tagging machine • Weighing machine and tapes • Milk sampler, preservatives, sampling bottle

  18. Current Status of DCIP

  19. District Coverage under DCIP

  20. Expansion of PPRS- herd coverage 604 4

  21. District-wise herds under PPRS 604

  22. Base Animals under PPRS 4600+

  23. Expansion of PPRS- No of Milking Animals 2000+

  24. Some Preliminary Results and Implications

  25. Results…. • Average herd size : 8 (2-117) • Average milking animals/ herd : 4-5 (1-74)

  26. Production performance Daily milk production (N1800) Mean Yield- 9.07±3.97 l

  27. Milk fat content Milk Fat content ( %) Mean- 4.43±1.47

  28. Milk Protein content Milk protein content (%) Mean - 3.3±0.49

  29. Conductivity Conductivity Mean- 6.6±0.85

  30. Results of calculation of part lactation

  31. Breeding value estimation Fixed factors considered • Herd • Age as regressor variable • Breed* • Year of calving* • Season of calving* • Parity* • Feeding and management ??

  32. Estimated Breeding Values (100 days V solids) 100 Day Part Lactation Parameter n Milk Yield Fat % Protein % Conductivity Valuable Solids Mean 377 1164.78 4.13 3.36 6.50 87.15 St. Deviation 421.89 0.81 0.23 0.47 32.31 District: Chitwan ID ID_Herd Date-calv Milk Fat% Prot% vSolid age sireBr damBr ID_Br EBV Farmers’ Name

  33. New born calves under PPRS

  34. Lesson Learnt • All stakeholders convinced on importance of DCIP • Should have been initiated long back- However, late better than never • Sustainability- Government support- Programme built on in NARC and DLS from current FY • Commitment from stakeholders essential – for long term breeding project • Inadequate project duration for this kind of work • Sincerity of recorders and farmers cooperation - essential • Strong and functional linkage between Research and Extension for achieving DCIP goal- an absolute necessity • Exist potential within the country for improvement • Immediate benefit for farmers- vaccination, drenching for their support ?? • Genetic improvement- track opened- gravelling, black topping essential- ensure for not washing away in monsoon- some sort of support necessary

  35. Problem Encountered At Farmers’ level • Animal exit from herd and frequent movement • Why s/he and why not me (herd size) • Fate of male calves Related to Recordings and Recorders • Small and scattered herd size • Production situation – early morning milking • Remuneration against hardship • Recorder leaving job Related to Data management • Timely flow of records (both way) • Incomplete format from recorders • Mismatching herds and animal identifications • Date conversion inconvenience

  36. Problem….. Lab and semen handling • Some unbelievable analysis report • Lacto scan maintenance (instances- breakdown of machine) • Off time work for semen handler at district (with no remuneration) • Inadequate facility to handle semen properly (12 sire lines) AI Technician Level • Conflict of interest among technicians • Reading bull identification number in straw Unforeseen • Frequent strike and road blockade • FMD outbreaks- Farmers’ superstition • Unlucky incidence– more male calves born from DCIP- faith of farmers toward DCIP

  37. Some adjustment suggested • Initial feedback to the farmers’ from Lab via recorders (particularly for conductivity) to enable farmers to take immediate correction measures as the current flow of information is lengthy (farmers- district lab- DMU- district-farmer) • Decentralization of data recording • Cooperatives involvement in PPRS

  38. The way forward • Data quality improvement • Breed establishment and Genetic Improvement • Holstein Derivatives-Nepalese Holstein • Jersey Derivatives-Nepalese Jersey • Saving potential male calves- • Evaluation of future bulls (growth, conformity, reproductive disease free status, chromosomal aberration) • Extensive AI in non descript breed • External support

  39. Thank You

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