طراحی و ارزیابی باسکول برای وزن کشی جداگانه اندام حرکتی به منظور شناسایی گاوهای لنگ
محورهای موضوعی : سایر علوم وابسته
احمدرضا محمدنیا
1
*
,
عليرضا عبدالحسيني
2
,
امیرفرهنگ هوشنگی
3
1 - گروه علوم درمانگاهی، دانشکده دامپزشکی، دانشگاه فردوسی، مشهد، ایران
2 - دانشجو
3 - دانشیار دانشگاه آزاد اسلامی، واحد شبستر، ایران
کلید واژه: وزنگیری, وزن‌کشی, اسکور حرکتی, لنگش, باسکول ,
چکیده مقاله :
زمینه و نوع مطالعه: لنگش مشکلی پرهزینه و گسترده بهداشتی و رفاهی در تولید انبوه شیر است و روش‌های خودکار قابل اعتماد برای تشخیص لنگش مورد نیاز است. لنگش ممکن است از طریق اندازه‌گیری نحوه توزیع وزن گاو ها در بین 4 اندام تشخیص داده شود، که نیاز به درک چگونگی توزیع مجدد وزن در پاسخ به درد در یک یا چند اندام دارد.
هدف: این تحقیق با هدف ارزیابی وزنگیری روی هر یک از اندام‌های حرکتی در موارد لنگش و دامهای سالم با طراحی و ساخت باسکولی برای وزن کشی هر اندام حرکتی به صورت جداگانه انجام پذیرفت.
روش کار: شصت و یک راس گاو غیرلنگ در یک گاوداری صنعتی انتخاب شدند و میانگین فاصله بین دواندام جلویی، دو اندام عقبی و همچنین اندام‌های جلویی و عقبی به منظور طراحی یک باسکول با چهار صفحه وزن‌کشی اندازه‌گیری شد. ابعاد هر صفحه 100*50 سانتی متر و با توان اندازه‌گیری حداقل ۱۰۰گرم و حداکثر ۴5۰ کیلوگرم برای هر صفحه که وزن هر یک از چهار اندام حرکتی را جدا گانه محاسبه کرده و به صورت مجزا بر روی چهار صفحه نمایشگر نشان می‌دهد، طراحی شد. درمرحله دوم بعد از طراحی مطالعه در دو گروه 25 راسی گاوهای لنگ (مبتلا به جراحات انگشتی و اسکور حرکتی بالا) و غیر لنگ (بدون جراحات انگشتی و اسکورحرکتی پایین) برای ارزیابی توانایی دستگاه در تشخیص لنگش انجام گرفت. گزارش اطلاعات به شکل توصیفی و همچنین مقایسه گروه ها با بهره گیری از آزمون های Pair t-test و پراش یکطرفه (One way ANOVA) انجام شد و مقادیر P<0.05 به عنوان معنی دار شناخته شد.
نتایج: میزان وزنگیری بر روی اندام بیمار 23/21±35/127کیلوگرم و میزان وزنگیری روی اندام سالم مقابل اندام بیمار 19/12±28/196 کیلوگرم و همچنین میزان وزن گیری روی اندام سالم ضربدری اندام بیمار 99/11±24/193 کیلوگرم بود و این میزان در اندام سالم مقابل اندام بیمار96/15±93/198 کیلوگرم بود که نشانگر وزنگیری کمتر در اندام لنگ درمقایسه با سایر اندامها بود. همچنین توزیع وزن بر روی اندامها در دامهای لنگ (اسکورحرکتی بالا) به شکل معنی‌داری متفاوت بود، حال آنکه این یافته در دامهای غیر لنگ (اسکور پایین حرکتی) تفاوت معنی داری نشان نداد.
نتیجه‌گیری: وزنگیری متفاوت برروی اندام های حرکتی می‌تواند مولفه‌‌ای برای تشخیص لنگش در نظر گرفته شود. این تفاوت توزیع وزن تکنیک مفیدی برای تشخیص لنگش ارائه می‌دهد.
Background: lameness is a costly and widespread health and welfare problem in intensive dairy production, and reliable automated methods to detect lameness are needed. Lameness may be detected through the measurement of weight in each limb that requires an understanding of how caws redistribute their weight in response to pain in one or more limbs.
Objectives: This research was conducted with the aim of the Evaluation of weight distribution on each limb in lame and healthy cows by designing a splitted scale for weighing each limb.
Methods: Sixty one sound cows were selected in an industrial farm and the distance between forelimbs, hind limbs and forelimbs and hind limbs were measured for designing a 4 plate scale, base to preliminary results dimension of each plate were d 100 x 50 cm and each plate were capable of weighing from 100 grams up to 450 kilograms and display the results in separate screens. In second step two groups of Lame (25 cows affected by digital injuries in last month) and Nongame (25 sound cows without any history of digital injuries during past three month) were weighed by designed scale for evaluation the possible different weight distribution among the limbs. Data reported descriptively and also numerical measurements were compared by Pair t-test and One way ANOVA, P value less than 0.05 consider as significant.
Results: The weight on the injured limb recorded as 127.35±21.23 kg and healthy limb was against the diseased limb, 127.345±21.225 and the weight on contra-lateral limb recorded as 196.28±12.19, on diagonal limb recorded as 193.24±11.99 kg and on opposite limb recorded as 198.93±15.96. All data shows a significant less weight distribution on injured limb. Also distribution of the weight among high locomotion scored cows revealed a significant difference in weight bearing as the distribution were not significant in cows with less scores.
Conclusion: Different weight distribution on limbs can be considered as a diagnostic tool for lameness. Weight distribution measurements may provide useful in-field techniques for lameness detection.
1. Mohamadnia AR. Lameness as a basis for economic flow in dairy herds. 8th Convention of Iranian Veterinary Clinicians, Shiraz, Iran; 2013. P: 1-6.
2. Adams AE, Lombard JE, Fossler CP, Román-Muñiz IN, Kopral CA. Associations between housing and management practices and the prevalence of lameness, hock lesions, and thin cows on US dairy operations. J Dairy Sci. 2017; 100(3): 2119-2136. https://doi.org/10.3168/jds.2016-11517
3. Brookhart JM, Parmeggiani PL, Petersen WA, Stone SA. Postural stability in the dog. Am J Physiol. 1965; 208: 1047–1057. https://doi.org/10.1152/ajplegacy.1965.208.6.1047
4. Browne, N, Hudson CD, Crossley RE, Sugrue K, Kennedy E, Huxley JN, Conneely M. Lameness prevalence and management practices on Irish pasture-based dairy farms. Ir Vet J. 2022; 75(1): 14. doi.org/10.1186/s13620-022-00221-w
5. Chapinal N, De Passillé AM, Rushen J. Weight distribution and gait in dairy cattle are affected by milking and late pregnancy. J Dairy Sci. 2009; 92(2): 581-588. https://doi.org/10.3168/jds.2008-1533
6. Chapinal N, Tucker CB. Validation of an automated method to count steps while cows stand on a weighing platform and its application as a measure to detect lameness. J Dairy Sci. 2012; 95 (11): 6523-28. https://doi.org/10.3168/jds.2012-5742
7. De Vries A, Marconde, MI. Review: Overview of factors affecting productive lifespan of dairy cows. Animal. 2020; 14(1): 155-164. https://doi.org/10.1017/S1751731119003264
8. Di Fabio RP. Postural supporting mechanisms during spontaneous single movement in the cat. Neurosci. 1983; 40: 133–138. https://doi.org/10.1016/0304-3940(83)90291-4
9. Dufosse´ M, Macpherson J, Massion J. Biomechanical and electromyographical comparison of two supporting mechanisms in the cat. Exp Brain Res. 1982: 45, 38–44. https://doi.org/10.1007/BF00235761
10. Faezi M, Sangtarash R. Epidemiology of lameness; economic importance, prevalence and incidence. Eltiam. 2019; 6(2): 14-34.
11. Flower FC, Weary DM. Effect of hoof pathologies on subjective assessments of dairy cow gait. J Dairy Sci. 2006; 89(1): 139–146. https://DOI: 10.3168/jds.S0022-0302(06)72077-X
12. Green LE, Hedges VJ, Schukken YH, Blowey RW, Packington AJ. The Impact of Clinical Lameness on the Milk Yield of Dairy Cows. J Dairy Sci. 2002; 85(9): 2250-6. https://doi.org/10.3168/jds.S0022-0302(02)74304-X
13. Hood DM, Wagner P, Taylor DD, Brumbaugh GW, Chaffin MK. Voluntary limb-load distribution in horse with acute and chronic laminitis. Am J Vet Res. 2001; 62: 1393–1398. • https://DOI: 10.2460/ajvr.2001.62.1393
14. Jevens DJ, De Camp CE, Hauptman JG, Braden TD, Richter M, Robinson R. Use of force-plate analysis of gait to compare two surgical techniques for treatment of cranial cruciate ligament rupture in dogs. Am J Vet Res. 1996; 57: 389–393. PMID: 8669774
15. Kharitonov E, Cherepanov G, Ostrenko K. In Silico Predictions on the Productive Life Span and Theory of Its Developmental Origin in Dairy Cows. Animals. 2022; 12(6): 684. https://doi.org/10.3390/ani12060684
16. Kohansal F, Ebrahimi AR, Faezi M, Mohamadnia AR. Association of Brisket Board Height and Neck-Rail Position in Freestall Barns with Some Comfort Indices in Dairy Cows. J Vet Res. 2024; 79(1): 29-40. https://doi.org/10.22059/jvr.2023.362608.3369
17. Mohamadnia AR. Lameness an increased risk in dairy farms. In: Proceedings of the 14th Iranian National Veterinary Congress Razi Hall, Tehran, Iran. 2005; p. 138-150.
18. Mohamadnia A R. Risk factors for cattle lameness. Eltiam. 2019; 6 (2): 35-54.
19. Mohamadnia AR, Mohamaddoust M, Shams N, Kheiri S, Sharifi S. Study on the Prevalence of dairy cattle Lameness and its effects of Production Indices in Iran, A Locomotion Scoring Base Study. Pak J Biol Sci. 2008; 11(7): 1047-50. https://10.3923/pjbs.2008.1047.1050
20. Mohamadnia AR, Nejati A. Lameness, an ongoing threat to dairy farms. Eltiam. 2019; 6 (2): 1-13.
21. Neveux S, Oostra J, De Passille AM, Rushen J. Validating on-farm tools for their ability to detect lameness in dairy cows. Proc. 37th Int. Congr ISAE Abano Terme, Italy, International Society for Applied Ethology, Brescia, Italy. 2003; 89(7): 2503-2509. https://doi.org/10.3168/jds. S0022-0302(06)72325-6.
22. Neveux S, Weary DM, Rushen J, Von Keyserlingk, MA, de Passillé AM. Hoof discomfort changes how dairy cattle distribute their body weight. J Dairy Sci. 2006; 89(7): 2503–2509.
23. Nuss K, Müller J, Wiestner T. Effects of induced weight shift in the hind limbs on claw loads in dairy cows. J Dairy Sci. 2019; 102(7): 6431–6441. https://doi.org/10.3168/jds.S0022-0302(06)72325-6.
24. Ózsvári L. Economic Cost of Lameness in Dairy Cattle Herds. J Dairy Vet. 2017: 6(2), 00176 https://doi.org/10.3168/jds.2022-22446.
25. Pastell ME, Hänninen L, De Passillé AM, Rushen J. Measures of weight distribution of dairy cows to detect lameness and the presence of hoof lesions. J Dairy Sci. 2010; 93: 954-60. https://doi.org/10.3168/jds.2009-2385.
26. Pastell ME, Kujala M. A probabilistic neural network model for lameness detection. J Dairy Sci. 2007; 90: 2283-2292. https://doi.org/10.3168/jds.2006-267.
27. Pastell ME, Takko H, Grohn H, Hautala M, Poikalainen V, Praks J, Veermae I, Kujala M, Ahokas J. Assessing cows’ welfare: Weighing the cow in a milking robot. Biosyst Eng. 2006; 93: 81-7. https://doi.org/10.3168/jds.2009-2385.
28. Radostits OM. Herd Health: food animal production medicine. 3rd ed. Philadelphia: W.B. Saunders Company. 2001.
29. Rajkondawar PG, Tasch U, Lefcourt AM, Erez B, Dyer RM, Varner MA. A system for identifying lameness in dairy cattle. Appl Eng Agric. 2002; 18: 87–96. https://doi: 10.13031/2013.7707.
30. Rushen J, Pombourcq E, de Passillé AM. Validation of two measures of lameness in dairy cows. Anim Behav Sci. 2007; 106: 173-177. https://doi.org/10.1016/j.applanim.2006.07.001.
31. Salem SE, Mesalam A, Monir AA. cross-sectional study of the prevalence of lameness and digital dermatitis in dairy cattle herds in Egypt. BMC Vet Res. 2023; 19(1): 68. https://doi.org/10.1186/s12917-023-03620-5.
32. Sangtarash R, Faezi M. Hoof trimming as a part of lameness control in dairy farms. Eltiam. 2019; 8(2): 1-13.
33. Silva SR, Araujo JP, Guedes C, Silva F, Almeida M, Cerqueira JL. Precision Technologies to Address Dairy Cattle Welfare: Focus on Lameness, Mastitis and Body Condition. Animals. 2021; 11(8): 2253. https://doi.org/10.3390/ani11082253.
34. Sprecher DJ, Hostetler DE, Kaneene JB. A lameness scoring system that uses posture and gait to predict dairy cattle reproductive performance. Theriogenology. 1997; 47: 1179-87. https://doi.org/10.1016/S0093-691X(97)00098-8.
35. Thomsen PT, Shearer JK, Houe H. Prevalence of lameness in dairy cows: A literature review. Vet J. 2023; 295: 105975. https://doi.org/10.1016/j.tvjl.2023.105975.
36. Van Nuffel A, Zwertvaegher I, Pluym L, Van Weyenberg S, Thorup V, Pastell M, et al. Lameness Detection in Dairy Cows: Part 1. How to Distinguish between Non-Lame and Lame Cows Based on Differences in Locomotion or Behavior. Animals. 2015; 5(3): 838–860. https://doi.org/10.3390/ani5030387.
37. Weaver AD, Jean G, Steiner A. Bovine surgery and lameness. 2nd ed. United Kingdom: Blackwell Publishing Ltd. 2005.
38. Whay HR, Main DC, Green LE, Webster AJ. Assessment of the welfare of dairy cattle using animal-based measurements: Direct observations and investigation of farm records. Vet Rec. 2003; 153: 197-202. https://doi.org/10.1136/vr.153.7.197.