Energy balance changes in cows and matching calving seasons with forage availability - PowerPoint PPT Presentation

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Energy balance changes in cows and matching calving seasons with forage availability

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Energy balance changes in cows and matching calving ... Crossbred of Holstein x Brahman. 2nd lactation. Age --- 65 mo. CI --- 420days. Dry periods 150 days ... – PowerPoint PPT presentation

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Title: Energy balance changes in cows and matching calving seasons with forage availability


1
Energy balance changes in cows and matching
calving seasons with forage availability
  • TIES Seminar
  • Kotaro Baba

2
1. Tedeschi, L. O., D. G. Fox, M. J. Baker.2004
Unveiling the production efficiency of the beef
cow A systematic approach using nutrition models
modification of paper presented at the NY beef
cattle winter management meeting. Jan.2004
  • 2.Reynoso-Campos, O., D. G. Fox, R. W. Blake,M.
    C. Barry,L. O. Tedeschi. C. F. Nicholson, H. M.
    Kaiser, P. A. Oltenacu.2004.
    Predicting nutritional requirements and lactation
    performance of dual-purpose cows using a dynamic
    model. Agricultural Systems. 8067-83

3
PAPER 1Tedeschi., L. O., D. G. Fox, M. J.
Baker.2004 Unveiling the production
efficiency of the beef cow A systematic
approach using nutrition models
modification of paper
  • Increase beef production
  • -Enhance reproduction indexes
  • -Enhance nutrition concepts
  • -Enhance genetic selection
  • - Enhance ranch management

4
This paper introduces a model (CVDS) which
Tedeschi is developing.
  • The objectives of the model
  • Computing the energy requirements of individual
    beef cows each day of the year and simulating the
    growth of the nursing calf given the information
    available
  • Computing energy balances for the herd each day
    of the year to evaluate the balance between herd
    numbers and requirements with the forage
    available
  • Identifying differences in efficiency among
    individual beef cows in a herd

5
The brief description of the model
  • This model is based on those developed at Cornell
    as described by
  • Reynoso-Campos et al.(2004)
  • Fox et al. (1988)

6
An evaluation of the model, as the peak milk
yield increases, the weaning weight increases.
  • Paste figure 3

7
An evaluation of the model, energy efficiency of
the cows
  • Paste figure 3 B

8
Tedeschi implies
  • Forage availability, milk yield, calf growth, and
    calving interval
  • -The milk level should be based on forage
    available.

9
A practical application of the model
10
A practical application of the model
11
Hints from the Tedeschis paper for our Yucatan
case
  • 1. The milk level should be based on forage
    available.
  • 2. Matching breeding and calving seasons with
    availability of forage.

12
Reynoso-Campos et al
Reynoso-Campos, O., D. G. Fox, R. W. Blake,M. C.
Barry,L. O. Tedeschi. C. F. Nicholson, H. M.
Kaiser, P. A. Oltenacu.2004. Predicting
nutritional requirements and lactation
performance of dual-purpose cows using a dynamic
model. Agricultural Systems. 8067-83
13
  • Animal nutrition
  • Cornell Net Carbohydrate and Protein
    System(CNCPS)
  • -Milk production
  • -ME balance
  • -MP balance
  • -BW change
  • -Changes in Body reserve
  • through the reproductive cycle.

14
Look at table 1. Page 70-71.
  • Table 1 is nicely summarized nutritional
    constraints and strategies for intensifying
    dual-purpose cattle systems in the tropics.
  • This table is related to our Yucatan beef project
    very much.

15
Objectives of this study 1
  • 1.
  • Describe a dynamic application of the CNCPS
    model that was developed to account for the
    cyclical changes in energy and protein balances
    that occur during the reproductive cycle of
    dual-purpose cows in the tropics.

16
Objectives of this study 2
  • 2.
  • Demonstrate the use of this dynamic
    application of the CNCPS model in evaluating
    dual-purpose cow performance over the
    reproductive cycle in specific production
    situations.

17
Inputs for the simulation
  • Crossbred of Holstein x Brahman
  • 2nd lactation
  • Age --- 65 mo
  • CI --- 420days
  • Dry periods150 days
  • Weight --- 470 kg
  • Calf BW--- 31.5 kg
  • Temperature
  • -Previous 26C
  • -Current 26C
  • Milk
  • -Production 11.5
  • kg/day
  • -Fat 4.1
  • -Protein 3.9
  • Rolling herd average
  • --- 2500 kg/270 day lactation with the
    CI of 420 days

18
Feed information
  • Lactating cows
  • -Graze forage Star grass (Cynodon
  • plectostachyus)
  • - 2 kg of commercial supplement
    (Both energy and protein concentrates)
  • Non-lactating
  • -Only grazed forage

19
Chemical components of Star grassJuarez et al.,
1999
  • Lactating (fertilized)
  • NDF --- 71.6
  • CP --- 10
  • Lignin 7.3
  • NDF digestion rate
  • --- 7.0 /h
  • Dry (unfertilized)
  • NDF --- 78.3
  • CP --- 6.6
  • Lignin 7.6
  • NDF digestion rate
  • --- 5.0 /h

20
Source , Reynoso-Campos et al.,2004
21
Source, Reynoso-Campos et al.,2004
22
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23
Source, Reynoso-Campos et al.,2003
24
Comparison of ME allowable milk with and without
ME contribution from mobilized body tissue
25
Conclusion by Reynoso et al
  • The CNCPS analyzes and integrates the
    nutritional and productive performance of cows on
    a dynamic basis throughout a calving interval.
  • Changes in the predicted nutritional status of
    animals reflect dynamic, cyclic processes of
    tissue mobilization and repletion associated with
    variation in production requirements and nutrient
    availability during the CI

26
Hints from the Reynosos paper for our Yucatan
case
  • The CNCPS is a useful tool to monitor energy
    balance through the calving interval.
  • The CNCPS can show the tissue mobilization and
    repletion in the prediction of nutrient
    requirement

27
My conclusion
  • Energy balance, protein balance, and body
    condition score are different from physiological
    stages (early or late lactation, and early or
    late pregnancy), and feed quality and quantity.
    Not accounting for the fluxes of body tissue
    leads to unrealistic predictions of dietary
    requirements.
  • It is important to think about forage
    availability, and energy requirements for each
    physiological stage

28
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