Determination of body measurements of Turkish grey cattle with different image processing methods

Year 2024, Volume: 8 Issue: 4, 805 - 810

Ahmet Refik Önal , Muhittin Özder

https://doi.org/10.31015/jaefs.2024.4.9

Abstract

Twenty heads one-year-old Turkish Grey Cattle Breed, which were protected as part of the conservation of native genetic resources at the Sheep Breeding Research Institute, were evaluated as a material. Body measurements for each animal were determined using the classical method (CM) and six different image processing methods: Fixed Scale Photography (FSP), Fixed Object Photography (FOP), Laser Pointer Photography (LPP), Fixed Scale Video (FSV), Fixed Object Video (FOV), and Laser Pointer Video (LPV), and the methods were compared. The correlation coefficients between CM and FSV, FOV, and LPV were calculated as 0.906 (p<0.01), 0.906 (p<0.01), and 0.909 (p<0.01), respectively for withers height (WH). For back height (BH), the correlation coefficients between CM and the same methods were calculated as 0.879 (p<0.01), 0.950 (p<0.01), and 0.944 (p<0.01), respectively. In terms of rump height (RH), the highest measurement difference was observed between CM and FSV with 3.11%, and the lowest difference was observed between CM and FOV with 0.07%. It was determined that Image Processing Methods (IPMs) could be used as an alternative to classical measurement methods for determining WH, BH, RH, and chest deepth (CD) of each type. It was determined that all IPMs could be used as alternative instead of CM for determining the body measurements of Turkish Grey cattle.

Keywords

Morphometric Measurements, Withers Height, Image Processing, Live Weight, Turkish Grey Cattle

Ethical Statement

The study was compiled from the Doctoral Thesis, and it was decided that Ethics Committee Approval was not needed in the Thesis Study Plan. Additionally, no direct studies were conducted on animals within the scope of the research. IACUC number: 2837713 AALAS Learning Lab. 10/1/2013

References

• Aktan S (2004). Sayısal Görüntü Analizinin (Digital Image Analysis) Hayvancılıkta Kullanım Olanakları ve Metodolojisi. 4. Ulusal Zootekni Bilim Kongresi, 01-03 Eylül, S.D. Üniversitesi, http://4uzbk.sdu.edu.tr/4UZBK/HYB/4UZBK_025.pdf (Erişim Tarihi:10 Nisan 2011) p:160-165. Isparta.
• Bianconi G, Negretti P (1999). Image analysis for linear morphological evaluation. Bianco Nero, 2:30-32.
• Core S, Miller S, Kelly M (2008). Development of the laser remote caliper as a method to estimate surface area and body weight in beef cattle. Studies by Undergraduate Researchers at Guelph. V1, N2:57-72.
• Diekman L (1991). Exterieurbewertung starker vereinheitlichen. Der Tierzüchter 43(8):338-339
• Düzgüneş O, Kesici T, Gürbüz F (1993). İstatistik Metotlar. Ankara Üniversitesi Ziraat Fakültesi Yayınları:1291, Ders Kitabı: 369-II. Baskı, s:218, Ankara.
• Grashorn MA, Komender P (1991). Breast muscle weight estimated by real-time ultrasonic scanner. Misset World Poultry, 7(6):40-41.
• Ilaslan M, Karabulut A, Aşkın Y, İzgi AN (1983). Yerli mandalarda vücut yapısı döl ve süt verimi üzerine araştırmalar. Afyon Zirai Araştırma istasyonu Yayın No:14, Afyon.
• Kuchida K, Yamagishi T, Takeda H, Yamaki K (1995). Live Body Volume and Density Measuring Method for Estimation of Carcass Traits in Japanese Black Steers by Computer Image Analysis. Animal Science and Technology, V66, N:1.
• Maroti-Agóts A, Bodò I, Jàvorka L, Gera I (2005). Comparison of body measurements of Hungarian Grey and Maremman cattle breed. 2005 World Congress of Italian Beef Cattle Breeds, abst. Gubbio-Italy.
• Negretti P, Bianconi G, Angelo AD, Gaviraghi A, Noè L (2004). Application of the opto-informatic BHstem to the morpho-weighted evaluation of goats: Preliminary Communication. 39th Simposio Internazionale di Zootecnia “Meat Science and Research” Rome-Italy, p:433-440.
• Nilipour AH, Butcher CD (1997). Data collection is important in poultry integrations. Misset World Poultry, 13(8): 19-20.
• Onal AR, Ozder M (2008). The Effectiveness Of A Visual Image Analysis BHstem For Estimate Body Measurements of Turkgeldi Sheep, New trends for Innovation in the Mediterranean Animal Production, Abstract. 6-8 November 2008, Corte-France.
• Ozder M, Onal AR (2008). Using of Laser Pointer Referance For Estimates of Body Measurements Of Cattle By Visual Image Process, New trends for Innovation in the Mediterranean Animal Production, Abstract. 6-8 November 2008, Corte-France.
• Ozkaya S (2006). Estimating Live Weight and Carcass Performance in Beef Cattle Using Digital Image Analysis and Comparing with Prediction Models. Master's Thesis. Süleyman Demirel University, Institute of Natural and Applied Sciences, S:73, Isparta.
• Polak P, Sakowski T, Blanco REN, Huba J, Krupa E, Tomka J, Peskovicova D, Oravcova M, Strapak P (2007). Use of computer image analysis for in vivo estimates of the carcass quality of bulls. Czech Journal of Animal Science, v:52, 12:430-436.
• Şekerden O, Tapki İ (2003). Growth Characteristics of Anatolian Buffaloes under Village Conditions in Hatay Province. A.U. Faculty of Agriculture Journal, c34(1):51-55.
• Tozsér J, Sutta J, BedO S (2000). The evaluation of video pictures for measurements of cattle. Állatteny Takarm. 49:385–392.
• Zehender G, Cordella LP, Chianese A, Ferrara L, Del Pozzo A, Barbera S, Bosticco A, Negretti P, Bianconi G, Balestra GF, Tonielli R (1996). Image analysis in morphological animal evaluation: a group for the development of new techniques in zoometry. AGRI 20:71-79.