@article {3672, title = {BRIEF COMMUNICATION: Conventional or Albrecht-Kinsey fertiliser approach in a commercial-scale dairy farm systems comparison}, journal = {New Zealand Journal of Animal Science and Production}, volume = {79}, year = {2019}, month = {07/2019}, pages = {100-102}, address = {Palmerston North}, abstract = {Long-standing questions around application of nutrients other than N, P and K (such as Mg and Ca), to meet either plant or soil requirements have been tested for the first time at a commercial dairy-farm-scale. Two dairy farms with similar soil type and soil management history were used to compare physical and financial productivity when the fertiliser regime followed either a conventional plant requirement approach (CON) or an Albrecht-Kinsey soil requirement approach (A-K). A longitudinal study commencing in 2012/13 included measurements of pasture and animal production, fertility and quality, and animal health. After six years there are no apparent impacts of fertiliser regime on milk yield or pasture growth, although less N fertiliser was applied on the A-K farm and this farm grew more clover. Though not statistically significant, there were more in-calf cows and fewer metabolic problems pre- and post- calving in the A-K farm system compared with the CON system. Setting up and maintaining the soils at target parameters cost more (+$532/ha fertiliser costs in the first year; +$197 in the last two years), but animal health costs were on average $56/ha/yr lower.}, issn = {1176-5283}, author = {Bryant RH and Zwart T and Greer G and Casey J and Solly K and Pinxterhuis I and Horrocks A and Gillespie R and Pellow R} } @conference {78982, title = {An evaluation of a progesterone-based diagnostic as an aid to re-insemination decisions in a seasonal, pasture-grazed dairy cow herd}, booktitle = {Proceedings of the New Zealand Society of Animal Production}, volume = {72}, year = {2012}, month = {Jan}, pages = {35-37}, publisher = {New Zealand Society of Animal Production}, organization = {New Zealand Society of Animal Production}, address = {Christchurch}, abstract = {

Progesterone-based diagnostic tests are commercially available to predict pregnancy status 19 to 23 days following an insemination, thus providing decision-making support for artificial breeding. The study objective was to evaluate the likely performance of such a test in a pasture-grazed, seasonal dairy farm. Progesterone was determined in milk samples collected twice weekly from 553 cows at the Lincoln University Dairy Farm. Receiver operating characteristic analysis was applied to these data to determine sensitivity, false positive rate and the positive predictive value using a range of progesterone threshold values for detecting non-pregnant cows. The gold standard was non-pregnancy as measured by ultrasonography. At an optimised threshold of 4.1 ng/mL, the sensitivity, false positive rate and positive prediction rate were 78\%, 2.6\% and 96\% for detecting non-pregnant cows on Days 19 to 23. A major source of inaccuracy was the 28 cows with elevated levels of progesterone in milk on Days 19 to 23 after first insemination that were subsequently diagnosed non-pregnant. Another source of error was the inherent variance in progesterone concentration profiles among individuals. At a current cost of about $5 per test, this technology would have limited appeal for detecting non-pregnant cows in dairy systems where a satisfactory level of oestrus detection performance can be achieved.

}, issn = {1176-5283}, author = {Burke CR and Kamphuis C and Meier S and Pellow R} } @conference {78984, title = {Use of progesterone profiling to investigate factors affecting conception rates in a large, pasture-grazed dairy herd}, booktitle = {Proceedings of the New Zealand Society of Animal Production}, volume = {72}, year = {2012}, month = {Jan}, pages = {45-50}, publisher = {New Zealand Society of Animal Production}, organization = {New Zealand Society of Animal Production}, address = {Christchurch}, abstract = {

A study was conducted at the Lincoln University Dairy Farm to investigate factors influencing conception rate (CR). Relative to the planned start of mating date (Day 0), milk progesterone (MP4) concentrations were determined weekly from Day -20 to 0, twice weekly from Day 0 to 42, and then weekly to Day 70 in 666 cows. Trough-like patterns among individual profiles were identified and defined as periovulatory events. Pre-mating ovulatory status was a predictor (P \< 0.01) of first service CR (FSCR), with anovulatory cows having a lower FSCR (37.4\%) compared with {\textquoteleft}late{\textquoteright} (47.3\%) and {\textquoteleft}early{\textquoteright} (56.4\%) ovulating cows. In turn, interval from calving to Day 0 was a significant determinant for pre-mating ovulatory status. Oestrus detection was performed to a high standard, even though 5\% of the 850 artificial inseminations were coincident with a lack of ovulation. MP4 profiles also indicated that 4\% of cows that conceived during the 37-day artificial breeding period subsequently lost these pregnancies. A 2.6\% error rate for diagnosing pregnancies on Day 78 was detected, mostly due to incorrectly attributing pregnancies following artificial breeding. Findings indicate the critical importance of managerial strategies that promote a high prevalence of cows having ovulated at least 21 days before mating starts.

}, issn = {1176-5283}, author = {Burke CR and Meier S and Pellow R} }