Süt Sığırlarında Vücut Kondisyon Skorlaması
Özet
Bu bölümde, süt sığırlarında beslenme yeterliliğinin değerlendirilmesinde kullanılan temel parametreler olan vücut kondisyon skoru, lokomosyon skoru, rumen doluluğu ve dışkı skorlaması ele alınmaktadır. Süt sığırlarında verimlilik, sağlık ve üreme performansı, rasyonun kalitesi ve miktarıyla doğrudan ilişkilidir. Beslenme, rumenin etkin çalışmasını ve sindirim sağlığını destekleyecek şekilde planlanmalıdır.
Vücut kondisyon skoru, enerji dengesi ve uzun dönemli beslenme düzeyini yansıtırken; lokomosyon skoru, ayak ve bacak sağlığı ile yem tüketimini etkileyen konfor durumunu değerlendirir. Rumen doluluğu, kısa dönemli yem alımı ve rumen fonksiyonunun izlenmesinde; dışkı skoru ise rasyonun sindirilebilirliği ve rumen fermentasyon dengesinin değerlendirilmesinde kullanılır. Bu parametreler, sürüde beslenme stratejilerinin doğruluğunu ve olası metabolik ya da sindirim sorunlarının erken tanısını sağlayan temel göstergelerdir. Değerlendirme, sayısal ve niteliksel yöntemlerle yapılarak, sapmaların sıklığı ve şiddeti dikkate alınır.
This section focuses on the key parameters used to evaluate nutritional adequacy in dairy cows: body condition score, locomotion score, rumen fill, and fecal scoring. Productivity, health, and reproductive performance in dairy cattle are closely linked to diet quality and quantity. Feeding programs must support efficient rumen function and overall digestive health.
Body condition score reflects energy balance and long-term nutritional status, whereas locomotion score evaluates hoof and leg health, which impacts feed intake and cow comfort. Rumen fill serves as a short-term indicator of feed intake and rumen function, while fecal scoring provides insight into diet digestibility and rumen fermentation balance. These metrics serve as essential tools for assessing the effectiveness of feeding strategies and for early detection of metabolic or digestive issues. Evaluations integrate quantitative and qualitative methods, considering both the frequency and severity of deviations from normal.
Referanslar
Petrovski KR, Cusack P, Malmo J, Cockcroft P. The Value of ‘Cow Signs’ in the Assessment of the Quality of Nutrition on Dairy Farms. Animals. 2022;12(11):1352. doi:10.3390/ani12111352
Ortenzi L, Violino S, Costa C, et al. An innovative technique for faecal score classification based on RGB images and artificial intelligence algorithms. J Agric Sci. 2023;161(2):291-296. doi:doi.org/10.1017/S0021859623000114
Kononoff P, Heinrichs J, Varga G. Using manure evaluation to enhance dairy cattle nutrition. Penn State Coll Agric Sci Dep Dairy Anim Sci. Published online 2002:1-5.
Hall M. Carbohydrate nutrition and manure scoring. Part II: Tools for monitoring rumen function in dairy cattle. In: Proceedings of Minnesota Dairy Health Conference, May 15, 2007, St. Paul, Minnesota. ; 2007:81-86.
Atkinson O. Guide to the rumen health visit. In Pract. 2009;31(7):314-325. doi:10.1136/inpract.31.7.314
Poppi DP, Norton BW, Minson DJ, Hendricksen RE. The validity of the critical size theory for particles leaving the rumen. J Agric Sci. 1980;94(2):275-280. doi:10.1017/S0021859600028859
Jalali AR, Weisbjerg MR, Nadeau E, et al. Effects of forage type, animal characteristics and feed intake on faecal particle size in goat, sheep, llama and cattle. Anim Feed Sci Technol. 2015;208:53-65. doi:10.1016/j.anifeedsci.2015.07.003
Klopčič M, Hamoen A, Bewley J. Body Condition Scoring of Dairy Cows. (Klopčič M, Kuipers A, eds.). Biotechnical Faculty, Department of Animal Science Ljubljana, Slovenia; 2011.
Heinrichs J, Jones CM, Ishler VA. Body-condition scoring as a tool for dairy herd management. Coop Extension, Coll Agric Pennsylvania State Univ. 2023;363:1-5.
Koçyiğit R. Determination of body condition score (BCS) for dairy cattle and usage of ultrasounds for measurement of back fat thickness. Atatürk Univ, J Agric Fac. 2017;48(2):139-144.
Alvarez JR, Arroqui M, Mangudo P, et al. Body condition estimation on cows from depth images using Convolutional Neural Networks. Comput Electron Agric. 2018;155:12-22. doi:10.1016/j.compag.2018.09.039
Halachmi I, Klopčič M, Polak P, Roberts DJ, Bewley JM. Automatic assessment of dairy cattle body condition score using thermal imaging. Comput Electron Agric. 2013;99:35-40. doi:10.1016/j.compag.2013.08.012
Bercovich A, Edan Y, Alchanatis V, et al. Development of an automatic cow body condition scoring using body shape signature and Fourier descriptors. J Dairy Sci. 2013;96(12):8047-8059. doi:10.3168/jds.2013-6568
Halachmi I, Polak P, Roberts DJ, Klopcic M. Cow body shape and automation of condition scoring. J Dairy Sci. 2008;91(11):4444-4451. doi:10.3168/jds.2007-0785
Çevik KK. Deep learning based real-time body condition score classification system. IEEE Access. 2020;8:213950-213957. doi:10.1109/ACCESS.2020.3040805
O’Mahony N, Krpalkova L, Sayers G, Krump L, Walsh J, Riordan D. Two-and three-dimensional computer vision techniques for more reliable body condition scoring. Dairy. 2022;4(1):1-25. doi:10.3390/dairy4010001
Siachos N, Lennox M, Anagnostopoulos A, et al. Development and validation of a fully automated 2-dimensional imaging system generating body condition scores for dairy cows using machine learning. J Dairy Sci. 2024;107(4):2499-2511. doi:10.3168/jds.2023-23894
Burfeind O, Sepúlveda P, Von Keyserlingk MAG, Weary DM, Veira DM, Heuwieser W. Evaluation of a scoring system for rumen fill in dairy cows. J Dairy Sci. 2010;93(8):3635-3640. doi:10.3168/jds.2009-3044
Zaaijer D, Noordhuizen JPTM. A novel scoring system for monitoring the relationship between nutritional efficiency and fertility in dairy cows. Ir Vet J. 2003;56(3):145-151.
Lean IJ, Golder HM, Hall MB. Feeding, evaluating, and controlling rumen function. Vet Clin Food Anim Pract. 2014;30(3):539-575. doi:10.1016/j.cvfa.2014.07.003
Robinson PH, Juarez ST. Locomotion scoring your cows: use and interpretation. In: Proc Mid-South Nutrition Conference, Texas. ; 2003:49-58.
Schlageter-Tello A, Bokkers EAM, Koerkamp PWGG, et al. Manual and automatic locomotion scoring systems in dairy cows: A review. Prev Vet Med. 2014;116(1-2):12-25. doi:10.1016/j.prevetmed.2014.06.006
Schlageter-Tello A, Bokkers EAM, Koerkamp PWGG, et al. Relation between observed locomotion traits and locomotion score in dairy cows. J Dairy Sci. 2015;98(12):8623-8633. doi:10.3168/jds.2014-9059
Bicalho RC, Cheong SH, Cramer G, Guard CL. Association between a visual and an automated locomotion score in lactating Holstein cows. J Dairy Sci. 2007;90(7):3294-3300. doi:10.3168/jds.2007-0076
Whay H. Locomotion scoring and lameness detection in dairy cattle. In Pract. 2002;24(8):444-449. doi:10.1136/inpract.24.8.444
Referanslar
Petrovski KR, Cusack P, Malmo J, Cockcroft P. The Value of ‘Cow Signs’ in the Assessment of the Quality of Nutrition on Dairy Farms. Animals. 2022;12(11):1352. doi:10.3390/ani12111352
Ortenzi L, Violino S, Costa C, et al. An innovative technique for faecal score classification based on RGB images and artificial intelligence algorithms. J Agric Sci. 2023;161(2):291-296. doi:doi.org/10.1017/S0021859623000114
Kononoff P, Heinrichs J, Varga G. Using manure evaluation to enhance dairy cattle nutrition. Penn State Coll Agric Sci Dep Dairy Anim Sci. Published online 2002:1-5.
Hall M. Carbohydrate nutrition and manure scoring. Part II: Tools for monitoring rumen function in dairy cattle. In: Proceedings of Minnesota Dairy Health Conference, May 15, 2007, St. Paul, Minnesota. ; 2007:81-86.
Atkinson O. Guide to the rumen health visit. In Pract. 2009;31(7):314-325. doi:10.1136/inpract.31.7.314
Poppi DP, Norton BW, Minson DJ, Hendricksen RE. The validity of the critical size theory for particles leaving the rumen. J Agric Sci. 1980;94(2):275-280. doi:10.1017/S0021859600028859
Jalali AR, Weisbjerg MR, Nadeau E, et al. Effects of forage type, animal characteristics and feed intake on faecal particle size in goat, sheep, llama and cattle. Anim Feed Sci Technol. 2015;208:53-65. doi:10.1016/j.anifeedsci.2015.07.003
Klopčič M, Hamoen A, Bewley J. Body Condition Scoring of Dairy Cows. (Klopčič M, Kuipers A, eds.). Biotechnical Faculty, Department of Animal Science Ljubljana, Slovenia; 2011.
Heinrichs J, Jones CM, Ishler VA. Body-condition scoring as a tool for dairy herd management. Coop Extension, Coll Agric Pennsylvania State Univ. 2023;363:1-5.
Koçyiğit R. Determination of body condition score (BCS) for dairy cattle and usage of ultrasounds for measurement of back fat thickness. Atatürk Univ, J Agric Fac. 2017;48(2):139-144.
Alvarez JR, Arroqui M, Mangudo P, et al. Body condition estimation on cows from depth images using Convolutional Neural Networks. Comput Electron Agric. 2018;155:12-22. doi:10.1016/j.compag.2018.09.039
Halachmi I, Klopčič M, Polak P, Roberts DJ, Bewley JM. Automatic assessment of dairy cattle body condition score using thermal imaging. Comput Electron Agric. 2013;99:35-40. doi:10.1016/j.compag.2013.08.012
Bercovich A, Edan Y, Alchanatis V, et al. Development of an automatic cow body condition scoring using body shape signature and Fourier descriptors. J Dairy Sci. 2013;96(12):8047-8059. doi:10.3168/jds.2013-6568
Halachmi I, Polak P, Roberts DJ, Klopcic M. Cow body shape and automation of condition scoring. J Dairy Sci. 2008;91(11):4444-4451. doi:10.3168/jds.2007-0785
Çevik KK. Deep learning based real-time body condition score classification system. IEEE Access. 2020;8:213950-213957. doi:10.1109/ACCESS.2020.3040805
O’Mahony N, Krpalkova L, Sayers G, Krump L, Walsh J, Riordan D. Two-and three-dimensional computer vision techniques for more reliable body condition scoring. Dairy. 2022;4(1):1-25. doi:10.3390/dairy4010001
Siachos N, Lennox M, Anagnostopoulos A, et al. Development and validation of a fully automated 2-dimensional imaging system generating body condition scores for dairy cows using machine learning. J Dairy Sci. 2024;107(4):2499-2511. doi:10.3168/jds.2023-23894
Burfeind O, Sepúlveda P, Von Keyserlingk MAG, Weary DM, Veira DM, Heuwieser W. Evaluation of a scoring system for rumen fill in dairy cows. J Dairy Sci. 2010;93(8):3635-3640. doi:10.3168/jds.2009-3044
Zaaijer D, Noordhuizen JPTM. A novel scoring system for monitoring the relationship between nutritional efficiency and fertility in dairy cows. Ir Vet J. 2003;56(3):145-151.
Lean IJ, Golder HM, Hall MB. Feeding, evaluating, and controlling rumen function. Vet Clin Food Anim Pract. 2014;30(3):539-575. doi:10.1016/j.cvfa.2014.07.003
Robinson PH, Juarez ST. Locomotion scoring your cows: use and interpretation. In: Proc Mid-South Nutrition Conference, Texas. ; 2003:49-58.
Schlageter-Tello A, Bokkers EAM, Koerkamp PWGG, et al. Manual and automatic locomotion scoring systems in dairy cows: A review. Prev Vet Med. 2014;116(1-2):12-25. doi:10.1016/j.prevetmed.2014.06.006
Schlageter-Tello A, Bokkers EAM, Koerkamp PWGG, et al. Relation between observed locomotion traits and locomotion score in dairy cows. J Dairy Sci. 2015;98(12):8623-8633. doi:10.3168/jds.2014-9059
Bicalho RC, Cheong SH, Cramer G, Guard CL. Association between a visual and an automated locomotion score in lactating Holstein cows. J Dairy Sci. 2007;90(7):3294-3300. doi:10.3168/jds.2007-0076
Whay H. Locomotion scoring and lameness detection in dairy cattle. In Pract. 2002;24(8):444-449. doi:10.1136/inpract.24.8.444
