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Herd monitoring to optimise fertility in the dairy cow: making the most of herd records, metabolic profiling and ultrasonography (research into practice)

Published online by Cambridge University Press:  08 April 2014

R. F. Smith ,
J. Oultram  and
H. Dobson
R. F. Smith*
Affiliation:
School of Veterinary Science, University of Liverpool, Leahurst Campus, Neston, Cheshire, CH64 7TE, UK
J. Oultram
Affiliation:
School of Veterinary Science, University of Liverpool, Leahurst Campus, Neston, Cheshire, CH64 7TE, UK
H. Dobson
Affiliation:
School of Veterinary Science, University of Liverpool, Leahurst Campus, Neston, Cheshire, CH64 7TE, UK
*
† E-mail: robsmith@liv.ac.uk
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Abstract

Fertility performance is intrinsically linked to the quality of the animal environment, overall management and nutrition. This review describes the use of dairy herd records, metabolic profiles and ultrasonographic findings at veterinary fertility examinations to monitor and manage dairy herd fertility. After calving, a cow has to overcome a series of physiological hurdles before establishing a pregnancy. The selection of timely key performance indicators (KPIs) that monitor specific events in the postpartum and service periods is vital to correctly identify problems and their potential causes that hopefully can be rectified. Cumulative sum charts are the timeliest monitors of efficiency of detection of oestrus, insemination outcome and relationship between postpartum events and fertility, with the point of inflection indicating when a change took place. Other KPIs use data from specific cohorts, adding an inherent delay to when change is indicated. Metabolic profiles and milk constituent data allow monitoring of nutritional adequacy and developments to offer new possibilities of on-farm systems for regular measurements of milk constituents (including progesterone) and energy status. Examination of the reproductive tract can be used to indicate individual and herd fertility status but the currently available detail is under used. Recent advances in ultrasonography can improve the diagnosis of reproductive tract pathophysiology still further but the clinical use of these methods in veterinary practice needs further evaluation. Development of new KPIs to exploit research findings are needed to ensure this knowledge is used to improve on-farm performance.

Keywords

cattlefertility recordsmetabolicultrasound

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References

Acosta, TJ, Hayashi, KG, Matsui, M and Miyamoto, A 2005. Changes in follicular vascularity during the first follicular wave in lactating cows. Journal of Reproduction and Development 51, 273–280.CrossRefGoogle ScholarPubMed
Anon 1984. ADAS Dairy Herd Fertility. Her Majesty’s Stationary Office, London, UK.Google Scholar
Bollwein, H, Lüttgenau, J and Herzog, K 2012. Bovine luteal blood flow: basic mechanism and clinical relevance. Reproduction Fertility and Development 25, 71–79.Google Scholar
Brownlie, TS, Weir, AM, Tarbotton, I, Morton, JM, Heuer, C and McDougall, S 2011. Reproductive management of dairy herds in New Zealand: attitudes, priorities and constraints perceived by farmers managing seasonal-calving, pasture-based herds in four regions. New Zealand Veterinary Journal 59, 28–39.Google Scholar
Caraviello, DZ, Weigel, KA, Craven, M, Gianola, D, Cook, NB, Nordlund, KV, Fricke, PM and Wiltbank, MC 2006. Analysis of reproductive performance of lactating cows on large dairy farms using machine learning algorithms. Journal of Dairy Science 89, 4703–4722.Google Scholar
Chapinal, N, Carson, M, Duffield, TF, Capel, M, Godden, S, Overton, M, Santos, JE and LeBlanc, SJ 2011. The association of serum metabolites with clinical disease during the transition period. Journal of Dairy Science 94, 4897–4903.Google Scholar
Crowe, MA 2008. Resumption of ovarian cyclicity in post-partum beef and dairy cows. Reproduction in Domestic Animals 43 (suppl. 5), 20–28.Google Scholar
de Vries, A 2006. Economic value of pregnancy in dairy cattle. Journal of Dairy Science 89, 3876–3885.CrossRefGoogle ScholarPubMed
de Vries, A and Conlin, BJ 2003. Design and performance of statistical process control charts applied to estrous detection efficiency. Journal of Dairy Science 86, 1970–1984.CrossRefGoogle ScholarPubMed
de Vries, MAM, Bokkers, Dijkstra T, van Schaik, G and de Boer, IJM 2011. Invited review: associations between variables of routine herd data and dairy cattle welfare indicators. Journal of Dairy Science 94, 3213–3228.Google Scholar
Dobson, H, Smith, RF, Royal, MD, Knight, CH and Sheldon, IM 2007. The high-producing dairy cow and its reproductive performance. Reproduction in Domestic Animals 42 (suppl. 2), 17–23.Google Scholar
Douthwaite, R and Dobson, H 2000. Comparison of different methods of diagnosis of cystic ovarian disease in cattle and an assessment of its treatment with a progesterone-releasing intravaginal device. Veterinary Record 147, 355–359.Google Scholar
Duffield, TF and Lumsden, JH 1997. Use of test day milk fat and milk protein to detect subclinical ketosis in dairy cattle in Ontario. The Canadian Veterinary Journal 38, 713–718.Google Scholar
Friggens, NC, Bjerring, M, Ridder, C, Hojsgaard, S and Larsen, T 2008. Improved detection of reproductive status in dairy cows using milk progesterone measurements. Reproduction in Domestic Animals 43 (suppl. 2), 113–121.Google Scholar
Garnsworthy, PC 2006. Body condition score in dairy cows: targets for production and fertility. In Recent advances in animal nutrition (ed. PC Garnsworthy and J Wiseman), pp. 61–86. Nottingham University Press, Nottingham, UK.Google Scholar
Garcia, E, Hultgren, J, Fällman, P, Geust, J, Algers, B, Stilwell, G, Gunnarsson, S and Rodriguez-Martinez, H 2011. Intensity of oestrus signalling is the most relevant indicator for animal well-being in high-producing dairy cows. Veterinary Medicine International (Article ID 540830).Google Scholar
Gates, MC 2013. Evaluating the reproductive performance of British beef and dairy herds using national cattle movement records. Veterinary Record (doi: 10.1136/vr.101488 Record Published Online by BMJ 7 August 2013).Google Scholar
Ginther, OJ 1998. Ultrasonic imaging and animal reproduction: cattle. Equiservices Publishing, Cross Plains, Wisconsin, USA.Google Scholar
Ginther, OJ, Bashir, ST, Santos, VG and Beg, MA 2013. Contralateral ovarian location between the future ovulatory follicle and extant corpus luteum increases the length of the luteal phase and number of follicular waves in heifers. Theriogenology 79, 1130–1138.Google Scholar
Hayes, DP, Pfeiffer, DU and Morris, RS 1998. Production and reproductive responses to use of DairyMAN: a management information system for New Zealand dairy herds. Journal of Dairy Science 81, 2362–2368.CrossRefGoogle ScholarPubMed
Hayes, EP, Christley, RM and Dobson, H 2012. Effects of periparturient events on subsequent culling and fertility in eight UK dairy herds. Veterinary Record 170, 540.Google Scholar
Heppelmann, M, Krüger, L, Leidl, S and Bollwein, H 2013. Transrectal Doppler sonography of uterine blood flow during the first two weeks after parturition in Simmenthal heifers. Journal of Veterinary Science 14, 323–327.Google Scholar
Heuer, C, Schukken, YH and Dobbelaar, P 1999. Postpartum body condition score and results from the first test day milk as predictors of disease, fertility, yield, and culling in commercial dairy herds. Journal of Dairy Science 82, 295–304.CrossRefGoogle ScholarPubMed
Higgins, HM, Ferguson, E, Smith, RF and Green, MJ 2013. Using hormones to manage dairy cow fertility: the clinical and ethical beliefs of veterinary practitioners. PLoS One 8, e62993.Google Scholar
Holman, A, Thompson, J, Routly, JE, Cameron, J, Jones, DN, Grove-White, D, Smith, RF and Dobson, H 2011. Comparison of oestrus detection methods in dairy cattle. Veterinary Record 169, 47.Google Scholar
Jackson, RA, Wills, JR, Kendall, NR, Green, MJ, Murray, RD and Dobson, H 2011. Energy metabolites in pre- and post-partum dairy cattle as predictors of reproductive disorders including cystic ovarian disease, endometritis and abnormal commencement of luteal activity. Veterinary Record 168, 562.CrossRefGoogle Scholar
Kurykin, J, Waldmann, A, Tiirats, T, Kaart, T and Jaakma, U 2011. Morphological quality of oocytes and blood plasma metabolites in repeat breeding and early lactation dairy cows. Reproduction in Domestic Animals 46, 253–260.Google Scholar
Lane, EA, Crowe, MA, Beltman, ME and More, SJ 2013. The influence of cow and management factors on reproductive performance of Irish seasonal calving dairy cows. Animal Reproduction Science 141, 34–41.Google Scholar
Löf, E, Gustafsson, H and Emanuelson, U 2012. Evaluation of two dairy herd reproductive performance indicators that are adjusted for voluntary waiting period. Acta Veterinaria Scandinavica 54, 5.Google Scholar
López-Gatius, F, García-Ispierto, I, Santolaria, P, Yániz, J, Nogareda, C and López-Béjar, M 2006. Screening for high fertility in high-producing dairy cows. Theriogenology 65, 1678–1689.Google Scholar
López-Helguera, I, López-Gatius, F and Garcia-Ispierto, I 2012. The influence of genital tract status in postpartum period on the subsequent reproductive performance in high producing dairy cows. Theriogenology 77, 1334–1342.Google Scholar
Lopez-Gatius, F, Santolaria, P, Yániz, JL, Garbayo, JM and Hunter, RH 2004. Timing of early foetal loss for single and twin pregnancies in dairy cattle. Reproduction in Domestic Animals 39, 429–433.Google Scholar
Macrae, AI, Whitaker, DA, Burrough, E, Dowell, A and Kelly, JM 2006. Use of metabolic profiles for the assessment of dietary adequacy in UK dairy herds. Veterinary Record 159, 655–661.Google Scholar
McArt, JA, Nydam, DV, Oetzel, GR, Overton, TR and Ospina, PA 2013. Elevated non-esterified fatty acids and β-hydroxybutyrate and their association with transition dairy cow performance. Veterinary Journal 198, 560–570.Google Scholar
Mee, JF, Buckley, F, Ryan, D and Dillon, P 2009. Pre-breeding ovaro-uterine ultrasonography and its relationship with first service pregnancy rate in seasonal-calving dairy herds. Reproduction in Domestic Animals 44, 331–337.Google Scholar
Michaelis, I, Hasenpusch, E and Heuwieser, W 2013. Estrus detection in dairy cattle: changes after the introduction of an automated activity monitoring system? Tierärztliche Praxis Ausgabe G, Grosstiere/Nutztiere 41, 159–165.CrossRefGoogle ScholarPubMed
Neves, RC, Leslie, KE, Walton, JS and Leblanc, SJ 2012. Reproductive performance with an automated activity monitoring system versus a synchronized breeding program. Journal of Dairy Science 95, 5683–5693.Google Scholar
Nyman, AK, Lindberg, A and Sandgren, CH 2011. Can pre-collected register data be used to identify dairy herds with good cattle welfare? Acta Veterinaria Scandinavica 53 (suppl. 1), S8.Google Scholar
Opsomer, G, Grohn, YT, Hertl, J, Coryn, M, Deluyker, H and de Kruif, A 2000. Risk factors for postpartum ovarian dysfunction in high producing dairy cows in Belgium: a field study. Theriogenology 53, 841–857.CrossRefGoogle ScholarPubMed
Peake, KA, Biggs, AM, Argo, CM, Smith, RF, Christley, RM, Routly, JE and Dobson, H 2011. Effects of lameness, subclinical mastitis and loss of body condition on the reproductive performance of dairy cows. Veterinary Record 168, 301.Google Scholar
Rauch, A, Krüger, L, Miyamoto, A and Bollwein, H 2008. Colour Doppler sonography of cystic ovarian follicles in cows. Journal of Reproduction and Development 54, 447–453.Google Scholar
Rehman, T, McKemey, K, Yates, CM, Cooke, RJ, Garforth, CJ, Tranter, RB, Park, JR and Dorward, PT 2007. Identifying and understanding factors influencing the uptake of new technologies on dairy farms in SW England using the theory of reasoned action. Agricultural Systems 94, 281–293.Google Scholar
Ribadu, AY, Ward, WR and Dobson, H 1994. Comparative evaluation of ovarian structures in cattle by palpation per rectum, ultrasonography and plasma progesterone concentration. Veterinary Record 135, 452–457.Google Scholar
Roche, JR, Kay, JK, Friggens, NC, Loor, JJ and Berry, DP 2013. Assessing and managing body condition score for the prevention of metabolic disease in dairy cows. Veterinary Clinics of North America Food Animal Practice 29, 323–336.Google Scholar
Roelofs, JB, Van Eerdenburg, FJCM, Hazeleger, W, Soede, NM and Kemp, B 2006. Relationship between progesterone concentrations in milk and blood and time of ovulation in dairy cattle. Animal Reproduction Science 91, 337–343.Google Scholar
Rowlands, GJ, Little, W and Kitchenham, BA 1977. Relationships between blood composition and fertility in dairy cows — a field study. Journal Dairy Research 44, 1–7.Google Scholar
Saint-Dizier, M and Chastant-Maillard, S 2012. Towards an automated detection of oestrus in dairy cattle. Reproduction on Domestic Animals 47, 1056–1061.Google Scholar
Scully, S, Maillo, V, Duffy, P, Kelly, A, Crowe, M, Rizos, D and Lonergan, P 2013. The effect of lactation on post-partum uterine involution in Holstein dairy cows. Reproduction in Domestic Animals 48, 888–892.Google Scholar
Senosy, W, Uchiza, M, Tameoka, N, Izaike, Y and Osawa, T 2011. Impact of ovarian and uterine conditions on some diagnostic tests output of endometritis in postpartum high-yielding dairy cows. Reproduction in Domestic Animals 46, 800–806.Google Scholar
Sheldon, IM, Price, SB, Cronin, J, Gilbert, RO and Gadsby, JE 2009. Mechanisms of infertility associated with clinical and subclinical endometritis in high producing dairy cattle. Reproduction in Domestic Animals 44 (suppl. 3), 1–9.Google Scholar
Silva, LA and Ginther, OJ 2010. Local effect of the conceptus on uterine vascular perfusion during early pregnancy in heifers. Reproduction 139, 453–463.Google Scholar
Siqueira, LG, Torres, CA, Amorim, LS, Souza, ED, Camargo, LS, Fernandes, CA and Viana, JH 2009. Interrelationships among morphology, echotexture, and function of the bovine corpus luteum during the estrous cycle. Animal Reproduction Science 115, 18–28.Google Scholar
Smith, ST, Ward, WR and Dobson, H 1998. Use of ultrasonography to help to predict observed oestrus in dairy cows after the administration of prostaglandin F2 alpha. Veterinary Record 142, 271–274.Google Scholar
Sreenan, JM and Diskin, MG 1983. Early embryonic mortality in the cow: its relationship with progesterone concentration. Veterinary Record 112, 517–521.Google Scholar
Sveberg, G, Refsdal, AO, Erhard, HW, Kommisrud, E, Aldrin, M, Tvete, IF, Buckley, F, Waldmann, A and Ropstad, E 2011. Behavior of lactating Holstein—Friesian cows during spontaneous cycles of estrus. Journal of Dairy Science 94, 1289–1301.Google Scholar
Thorup, VM, Højsgaard, S, Weisbjerg, MR and Friggens, NC 2013. Energy balance of individual cows can be estimated in real-time on farm using frequent liveweight measures even in the absence of body condition score. Animal 7, 1631–1639.Google Scholar
Westwood, CT, Lean, IJ and Kellaway, RC 1998. Indications and implications for testing of milk urea in dairy cattle: a quantitative review. Part 2. Effect of dietary protein on reproductive performance. New Zealand Veterinary Journal 46, 123–130.Google Scholar
Williams, ME and Esslemont, RJ 1993. A decision support system using milk progesterone tests to improve fertility in commercial dairy herds. Veterinary Record 132, 503–506.Google Scholar
Zehetmeier, M, Baudracco, J, Hoffmann, H and Heißenhuber, A 2012. Does increasing milk yield per cow reduce greenhouse gas emissions? A system approach. Animal 6, 154–166.Google Scholar