Systems Analysis for Designing Reproductive Management Programs to Increase Production and Profit in Dairy Herds

Oltenacu, P.A.; Rounsaville, T. R.; Milligan, Robert A.; Foote, R.H.

doi:10.3168/jds.s0022-0302(81)82813-5

Cited by 54 publications

(18 citation statements)

References 11 publications

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“…[8][9][10][11][12] The economic effects of a sound reproductive program include increased milk by returning cows sooner to the earlier, more profitable phase of their lactation, increased numbers of replacement heifers and bull calves born, reduced costs of reproductive disease and reduced costs from culling, reduced nonproductive days due to extended dry periods, and increased rate of genetic gain.…”

Section: General Goals Of a Reproductive Programmentioning

confidence: 99%

Reproductive Health Programs for Dairy Herds: Analysis of Records for Assessment of Reproductive Performance

Fetrow¹,

Stewart²,

Eicker³

et al. 2007

Current Therapy in Large Animal Theriogenology

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Section: General Goals Of a Reproductive Programmentioning

confidence: 99%

Reproductive Health Programs for Dairy Herds: Analysis of Records for Assessment of Reproductive Performance

Fetrow¹,

Stewart²,

Eicker³

et al. 2007

Current Therapy in Large Animal Theriogenology

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“…In general, large decreases in EDE were detected earlier than smaller decreases. Large decreases in EDE are also associated with higher losses per day (Oltenacu et al, 1981). Therefore, in this study we provide estimates of the economic value of timely detection of decreases in EDE with Shewhart and cumulative sum (cusum) control charts that monitor EDR.…”

Section: Introductionmentioning

confidence: 99%

Economic Value of Timely Determination of Unexpected Decreases in Detection of Estrus Using Control Charts

Vries¹,

Conlin

2003

Journal of Dairy Science

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Total economic effects of decreased estrus detection efficiency (EDE) are a function of the economic loss per day and the length of the decrease. A stochastic dynamic dairy herd simulation model was used to determine whether estimates from permanently different EDE rates in herds of 100 and 1000 cows could approximate net returns due to temporary decreases in EDE. The default EDE was 65% and was either permanently or temporarily decreased to 55, 45, or 35%. Temporary decreases in EDE were assumed to continue until identified using cumulative sum or Shewhart control charts. Marginal changes in net return were greater at lower permanent rates of EDE, with losses ranging from 0.73 to 1.24 dollars per extra day open. Temporary decreases in EDE typically yielded smaller effects on net return than permanent decreases, but estimates were not consistently significantly different. However, temporary (30 to 960 d) decreases in EDE affected projected herd economic performance for several years after EDE was reset to 65%. Total losses in net return due to temporary decreases in EDE ranged from 4.44 dollars (accepting more false alarms) to 12.53 dollars (fewer false alarms) per cow for the 100-cow herd. For the 1000-cow herd, total losses in net return ranged from 0.95 to 10.43 dollars per cow. Total losses were not dependent on magnitude of decreased EDE because lower EDE could be detected earlier, thereby compensating for higher daily losses; for example, 35% EDE resulted in lower total losses than 55% EDE. Decreases to 55% EDE were detected sooner by cumulative sum charts, whereas decreases to 35% EDE were detected earlier by Shewhart charts. Both control charts used together can identify unexpected decreases in EDE more efficiently, thereby minimizing potential economic losses.

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“…Expected milk yield is predicted by an equation (units not stated, presumed to be kg/d) based on Oltenacu et al (1981), Marsh et al (1988) …”

Section: Prediction Of Milk Yieldmentioning

confidence: 99%

A critique of the Cornell Net Carbohydrate and Protein System with emphasis on dairy cattle. 3. The requirements model

Alderman¹,

France²,

Kebreab³

2001

J. Anim. Feed Sci.

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The Cornell Net Carbohydrate and Protein System (CNCPS) adopts energy requirements as Meals of metabolizable energy (ME) largely as NRC (1988), which are to be used with feed ME values as measured at the maintenance level of feeding. However, the model inserts calculated production level ME values into these NRC standards, equivalent to an upwards correction of about 5% to the estimates of ME requirements adopted. The energy accounting of the model is therefore flawed. The maintenance requirement of all breeds of dairy cattle, other than Holstein, are increased by a factor of 1.2, based on work with beef suckler cows. The efficiency of ME use for milk synthesis is also raised to a constant 0.65 from the normal range of 0.62 to 0.64 specified in NRC (1988). The net effect on the adopted ME requirements at milk yields of 30 kg/d is small, but both slope and intercept of the equation differ from NRC (1988). The model includes no effect of diet amount and composition upon nutrient partitioning between milk and body. Neither is there any effect of diet composition upon predicted milk composition, which is either an input to the model or a function of day of lactation. The body composition of growing heifers and cows up to four years of age is predicted by a function which has a maximum body fat content of 22.5%, only 0.86 of the total body fat recorded in recent body composition measurements in Friesian dairy cows. Associated estimates of maximum mobilizable body fat are one half or more below recent measurements with dairy cows. The handling of energy losses and gains during lactation uses condition score as a measure and ignores liveweight change. This is also based on research with suckler beef cows, and shown to over-estimate the energy equivalent of a unit change in condition score of Holstein dairy cows. Prediction of dry matter intakes is closer to actual than other prediction functions available and the lag in intake in early lactation is also accommodated well. The consequence of using mismatched energy requirements (as ME) is that the model predicts significantly lower milk yields at zero energy balance (or lower energy 362 CORNELL SYSTEM FOR DAIRY CATTLE balances if milk yield is given) compared to both NRC (1988) and AFRC (1993). However, field tests of the model have shown that predicted milk yields are closer to actual than those from other models.

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Systems Analysis for Designing Reproductive Management Programs to Increase Production and Profit in Dairy Herds

Cited by 54 publications

References 11 publications

Reproductive Health Programs for Dairy Herds: Analysis of Records for Assessment of Reproductive Performance

Reproductive Health Programs for Dairy Herds: Analysis of Records for Assessment of Reproductive Performance

Economic Value of Timely Determination of Unexpected Decreases in Detection of Estrus Using Control Charts

A critique of the Cornell Net Carbohydrate and Protein System with emphasis on dairy cattle. 3. The requirements model

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