ORIGINAL ARTICLE Genetic Resources (2025), 6 (11), 71–81 DOI: 10.46265/genresj.SCLC1551 https://www.genresj.org ISSN: 2708-3764 Phenotypic characterization of cattle breeds in Southern Ethiopia: Implications for breed differentiation and conservation Bergene Banjaw a, Habtamu Lemma Didanna a and Amine Mustefa *,b a College of Agriculture, Wolaita Sodo University, Wolaita, Ethiopia b Ethiopian Biodiversity Institute, Addis Ababa, Ethiopia Abstract: This study aimed to characterize and quantify the phenotypic relationship between Gamo and Gofa cattle breeds using nine morphometric measurements and 11 morphological traits. A total of 600 adult cattle (486 females and 114 males) were randomly selected from six purposively chosen districts. Univariate and multivariate analyses were conducted using Statistical Analysis Software. The univariate analysis revealed the morphometric values and morphological characteristics of both cattle breeds but did not show significant variations between them. The majority of the cattle exhibited uniformly patterned coat colour, upward-oriented, straight-shaped horns with black colour, laterally oriented ears with rounded edges, straight face profiles, small hump sizes, short coat hair, and medium tail length. In accordance with the phenotypic similarities observed in the univariate analysis, multivariate analysis also failed to identify significant differences between the two breeds. These results suggest that the two cattle breeds are phenotypically inseparable. However, these phenotypic similarities do not necessarily indicate genetic similarities. Therefore, further genetic characterization is recommended to assess the degree of genetic relationship between the breeds. In the meantime, it is advised to design breed-specific in situ conservation and genetic improvement programmes without separating the cattle breeds. Keywords: Gamo-Gofa, morphological traits, phenotypic characterization, univariate analysis Citation: Banjaw, B., Didanna, H. L., Mustefa, A. (2025). Phenotypic characterization of cattle breeds in Southern Ethiopia: Implications for breed differentiation and conservation. Genetic Resources 6 (11), 71–81. doi: 10.46265/genresj.SCLC1551. © Copyright 2025 the Authors. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Introduction Ethiopian indigenous cattle are vital to the livelihoods of smallholder farmers and significantly contribute to the nation’s economy, particularly through their role in the agricultural GDP (CSA, 2022). These cattle are primarily valued for milk, meat and draught power, while also serving as sources of income, manure and cultural capital (Zerabruk and Vangen, 2005; Genzebu et al, 2012; Yimamu, 2014; Kebede et al, 2017; Getachew et al, 2020). With an estimated population of 70.3 million cattle, Ethiopia hosts the largest cattle herd in Africa (CSA, 2022; Statista, 2024), underscoring their prominence within the livestock sector. ∗Corresponding author: Amine Mustefa (aminemustefa32@gmail.com) Genetic diversity, both within and among breeds, is a critical foundation for conservation and genetic improvement strategies. Indigenous breeds dominate Ethiopia’s cattle population, comprising 28 officially registered breeds (EBI, 2016; Mustefa, 2023). However, several gaps exist in breeds’ documentation and characterization. For instance, several phenotypically studied breeds – including Bonga, Fellata, Gamo and Qocherie – remain unregistered, while others (e.g. Adwa, Hamer and Smada) lack comprehensive phenotypic data despite formal registration (Mustefa, 2023). Addressing these inconsistencies is essential to establish a nationwide framework for breed-specific conservation and genetic improvement programmes. This study focused on two cattle breeds, Gamo and Gofa. The Gofa cattle breed, which was first studied by Rege and Tawa (1999), is officially registered in the Ethiopian indigenous cattle breeds database (EBI, Received: 06.02.2025 Accepted: 30.04.2025 Published online: 10.06.2025 https://www.genresj.org https://www.doi.org/10.46265/genresj.SCLC1551 https://www.genresj.org https://www.doi.org/10.46265/genresj.SCLC1551 mailto:aminemustefa32@gmail.com 72 Banjaw et al Genetic Resources (2025), 6 (11), 71–81 2016). Gofa cattle, primarily used for work, milk and meat, were categorized as Small East African Zebu (SEAZ) (Rege, 1999). According to Rege and Tawa (1999), Gofa cattle are one of the smallest strains not only among the Abyssinian zebu but also among all Ethiopian cattle. Small hump, small to medium horns and dominantly red colour are some of their qualitative characteristics (Rege and Tawa, 1999). The study by Kebede et al (2017) on Gofa cattle has also reported the existence of diverse coat colours, patterns and qualitative traits. The name Gofa cattle was first introduced by Rege and Tawa (1999) and then by Kebede et al (2017) after the ‘Gofa’ ethnic community which raised them. On the other hand, Gamo cattle, first studied by Chebo et al (2013), were not officially registered in the Ethiopian indigenous cattle breeds database (EBI, 2016). However, the study by Chebo et al (2013) showed the existence of potential cattle breeds in the area. According to Chebo et al (2013), the Gamo cattle were further divided into two subpopulations: the Gamo Highland and the Gamo Lowland. The Gamo Highland were relatively smaller with compact bodies compared to the medium-to-large-bodied Gamo lowland subpopulations. The name Gamo cattle was first introduced by Chebo et al (2013) after the ‘Gamo’ ethnic community which raised them. The production system of both Gamo and Gofa cattle breeds was reported to be similar, with cattle owners practising comparable husbandry methods. Own and communal grazing lands were the source of feed, while natural and controlled breeding were the common breeding systems among the owners of both cattle breeds (Chebo et al, 2013; Kebede et al, 2017; Zeleke et al, 2017). However, as mentioned above, the two cattle breeds were studied separately and at different times. This hindered the comparison of the two breeds, which further affected the breed registration as well as the development of breed- specific breeding programmes. Therefore, an inclusive phenotypic characterization study was mandatory to understand the relationships between the breeds. Thus, the current study aimed to conduct an on-farm phenotypic characterization of Gamo and Gofa cattle, assess their morphological diversity, and quantify the degree of phenotypic divergence between them. Materials and methods Study areas The study was carried out in the Gamo and the Gofa zones. Three districts were selected from each zone: Kucha, Daramalo and Dita districts from Gamo zone, as well as Zala, Denbagofa and Oyda districts from Gofa zone (Figure 1). Weather and agroecology-related information of the selected districts are presented in Table 1. Site and animal selection Representative samples of Gamo and Gofa cattle breeds were selected from their respective breeding areas. Information on their breeding regions and distribution zones was gathered using secondary sources. The Gamo cattle breed is reported to be native to the Gamo zone, with its distribution extending into the neighbouring Gofa zone (Rege and Tawa, 1999; Chebo et al, 2013). Thus, three districts – Kucha, Daramalo and Dita – were randomly chosen from Gamo zone to represent the indigenous Gamo cattle. Similarly, Gofa cattle are reported to be primarily found in Gofa zone, with their distribution reaching into the neighbouring Gamo zone (Rege and Tawa, 1999; Kebede et al, 2017). Accordingly, three districts – Zala, Denbagofa, and Oyda – were randomly selected from Gofa zone to represent the indigenous Gofa cattle. From each district, two sampling sites (known as ‘Kebeles,’ the smallest administrative units) were randomly chosen. Twenty-five households-raising cattle were then randomly selected from each sampling site. From each household, two unrelated adult cattle, aged four years and older, were randomly chosen. One male cattle was sampled every two households within each kebele. These animals were carefully monitored by their owners and trained labourers. Aggressive cattle that were unable to stand properly on flat ground were excluded from measurements. Data collection Morphometric and morphological data were collected following the FAO (2012) guidelines. Data collection was conducted in the morning to minimize the effects of feeding and watering on the measurements. Three researchers were involved in the data collection process: two handled the morphometric data, while the third recorded the morphological data. To minimize bias, the same researchers performed the data collection in all sites throughout the study. The animals were measured using a textile measuring tape in centimetres. A total of 600 cattle (486 females and 114 males) were subjected to nine morphometric measurements (Table 2) and 11 qualitative (morphological) traits (Figure 2, Table 3). For data analysis, the cattle were grouped into three age categories based on the classification by Tatum (2011): group one (3–5 years), group two (6–7 years) and group three (8 years and older). Data analysis The overall data analysis was carried out using the Statistical Analysis System (SAS) software 9.0 (SAS, 2002). UNIVARIATE procedure for data normality test, the frequency procedure for morphological (qualitative) data analysis, and the general linear model (GLM) procedure for morphometric (quantitative) data analysis were used. Data analysis was carried out using the following model: Yijk = µ + Xi +Yj +Zk + eijk where Genetic Resources (2025), 6 (11), 71–81 Characterization of Gamo and Gofa cattle in Ethiopia 73 Figure 1. Map of the studied areas Table 1. Weather and agroecology-related information of the selected districts (Gegnaw and Hadado, 2014; Leulalem et al, 2016; Kebede et al, 2017; Cholo et al, 2018; Chankalo, 2022; CSA, 2022; Kassa et al, 2022). Parameters Gamo zone Gofa zone Kucha Daramalo Dita Zala Dembagofa Oyda Human population 163,832 110,815 111,283 105,949 114,382 51,784 Cattle population 211,574 219,452 157,300 303,095 289,097 121,431 Temperature (ºC) 20–25 19–22 10–23 18–32 18–28 15–25 Rain fall (mm) 1,100–1,600 1,300–1,900 2,500–3,500 500–900 900–1,100 1,000–2,000 Altitude 800–2,250 1,217–2,700 1,800–3,500 1,194–1,484 800– 2,860 1,000–3,200 Agroecology (%) Lowland 49.4 29.2 - 90 75 27 Midland 50.6 33.3 40 10 15 40 Highland - 37.5 60 - 10 33 Table 2. Listof morphometric traits with their respective definitions. Measurements were conducted in centimetres (FAO, 2012). No. Morphometric traits Definitions 1 Body length Distance from shoulder point to pin bone 2 Heart girth Chest circumference right behind its front two legs 3 Height at withers Distance from ground to withers of the front foot 4 Pelvic width Distance between the two ends of the pelvic bone 5 Muzzle circumference Perimeter of the mouth 6 Ear length Distance from the root to the tip of the back side of the ear 7 Horn length Outer side distance between root and tip of the horn 8 Cannon bone length Distance between the fetlock joint (ankle) and the knee 9 Hock circumference Perimeter of the hock bone 74 Banjaw et al Genetic Resources (2025), 6 (11), 71–81 Yijk is an observation, µ is the overall mean, Xi is the fixed effect of breed (i = Gamo, Gofa), Yj is the fixed effect of sex (j = male, female), Zk is the fixed effect of age (k = 3–5, 6–7, ≥8 years) and eijk is the random error. However, the effect of age on all qualitative traits was found to be not significant; hence, it is omitted from the model. Additionally, the quantitative data were analyzed separately for each sex by fitting breed as a class variable. Means (LSM) were separated using the adjusted Tukey-Kramer (Tukey, 1953; Kramer, 1956). Multivariate analysis was carried out separately for each sex using both the morphometric and morphological traits at the same time. Prior to the analysis, the morphological traits were coded using discrete values. Stepwise discriminant analysis to detect morphometric traits that could better classify the cattle breeds, discriminant analysis to allocate individuals to known breeds and assess possibilities of misclassifications, and canonical discriminant analysis to deliver maximal separations between breeds were used. Graphic interpretation of breed differences was plotted using the scored canonical variables. Pairwise Mahalanobis distances between breeds were computed as D2 (i|j) = (xi − xj) ′ cov−1 (xi − xj). Where D2 (i|j) is the distance between breeds i and j, cov−1 is the inverse of the covariance matrix of measured variables, xi and xj are the means of variables in the ith and jth breeds. Results Qualitative characteristics The coat colour of the two studied breeds and sexes is presented in Figure 2. The coat colour was not significantly affected by breed, but it was affected by their sex. The majority of the studied cattle possessed red and light red coat colour. Sex-wise results revealed a high proportion of red-coloured females, while males possessed a light-red coat colour. The effect of breed and sex on the qualitative characteristics of Gamo and Gofa cattle breeds is presented in Table 3 along with the respective chi- square values and levels of significance. Relatively, breed affected more morphological traits than sex: three out of the ten morphological traits were affected significantly by the breed of the animals, while sex affected only one trait. Accordingly, the majority of the studied cattle populations possessed uniformly- patterned coat colour, upward-oriented straight-shaped horns with black colour, laterally-oriented round edge ears, straight face profile, small hump size, short coat hair size, and medium tail length. Morphometric traits Tables 4 and 5 present the least square means, standard errors and pairwise comparisons showing the effect of breed, sex and age on the morphometric traits of the studied cattle populations. Breed affected two out of the nine morphometric traits, with Gofa cattle exhibiting greater pelvic width and horn length measurements compared to Gamo cattle. However, the effect of breed on the morphometric measurements was found to be sex-dependent. Breed significantly affected pelvic width and horn length measurements of the females, with values higher in Gofa females. However, these measurements of the male cattle populations were not significantly affected by breed differences. On the other hand, the heart girth measurement of the males was significantly affected by breed, with Gamo males having higher measurements than their counterparts from Gofa. However, the heart girth measurement of the females was not significantly affected by breed. Similarly, sex affected seven out of the nine morphometric traits, with males exhibiting larger measurements than females in most of the traits except for ear and horn length. Age affected five of the nine morphometric traits, with most measurements increasing as the animal grew older. Body length and heart girth measurements were found to be stable after the age of six years. However, muzzle circumference and horn length measurements of middle-aged animals were found to be the highest among the compared age groups. Multivariate analysis Stepwise discriminant analysis Ten out of the 20 morphometric and morphological traits were used to discriminate the female cattle populations while six traits were used to discriminate the males. The three most important morphometric variables used in discriminating the cattle breeds were horn length, pelvic width and coat colour pattern among females, and horn shape and horn length among males (Table 6). The overall results show the existence of low partial R- Square and F-values. Discriminant analysis Results of the discriminant analysis showed moder- ate classification of individual animals into their cor- responding breed (Table 7). The highest classification into their respective breed was observed in Gamo males, while the lowest classification was observed in Gofa females. Canonical discriminant analysis Canonical correlations and eigenvalues for both male and female cattle populations are shown in Table 8. In line with the low partial R-Square and F-value outputs in Table 6, the eigenvalues were also small enough to discriminate between the two cattle breeds in both sexes. However, relatively higher Eigenvalues were observed for males than females. Similarly, the canonical correlation, which was used to build the canonical variate 1 (Can 1) from the used traits, was also low. However, a relatively higher canonical correlation was observed for males than females. Pairwise squared Mahalanobis distances between the breeds were calculated as 1.43 for females and Genetic Resources (2025), 6 (11), 71–81 Characterization of Gamo and Gofa cattle in Ethiopia 75 Table 3. Percentages of qualitative characteristics of cattle populations by sex and breed. Qualitative traits Cattle Breed Sex Gamo (300) Gofa (300) χ 2 value P Males (114) Females (486) χ2 value P Coat colour pattern Uniform 85.3 78.0 5.4 NS 82.5 81.5 0.27 NS Patchy 9.7 14.0 10.5 12.1 Spotted 5.0 8.0 7.0 6.4 Horn shape Straight 69.3 59.0 7.0 ** 65.8 63.8 0.16 NS Curved 30.7 41.0 34.2 36.2 Horn orientation Lateral 8.7 14.7 7.3 NS 15.8 10.7 13.2 * Upward 69.7 68.7 63.2 70.6 Downward 10.0 7.7 14.0 7.6 Forward 10.0 8.3 4.4 10.3 Backward 1.6 0.6 2.6 0.8 Horn colour Black 59.3 59.3 5.2 NS 50.9 60.7 4.6 NS Brown 9.0 6.3 9.6 7.2 White 28.0 33.7 35.1 29.8 Black + white 3.7 1.7 4.4 2.3 Ear shape Round edged 93.0 94.7 0.72 NS 91.2 94.4 1.7 NS Straight edged 7.0 5.3 8.8 5.6 Ear orientation Erect 16.3 20.0 10.5 ** 18.4 18.1 2.0 NS Lateral 78.7 68.7 70.2 74.5 Dropping 5.0 11.3 11.4 7.4 Face profile Straight 83.7 90.7 7.0 * 89.5 86.6 1.5 NS Concave 13.0 8.0 9.6 10.7 Convex 3.3 1.3 0.9 2.7 Hump size Absent 5.3 3.3 2.7 NS 7.9 3.5 0.27 NS Small 61.3 59.7 54.4 61.9 Medium 32.3 35.0 35.1 33.3 Large 1.1 2.0 2.6 1.3 Coat hair length Short 93.7 94.0 0.03 NS 93.9 93.8 1.6 NS Medium 5.3 5.0 6.1 5.0 Long 1.0 1.0 0 1.2 Tail length Short 4.3 6.0 0.86 NS 2.6 5.8 1.9 NS Medium 74.0 73.0 76.3 72.8 Long 21.7 21.0 21.1 21.4 Table 4. The effect of breed on the cattle morphometric measurements by sex. Measurements are in centimetres. N, number of animals sampled; BL, Body length; HG, Heart girth; HW, Height at withers; PW, Pelvic width; MC, Muzzle circumference; EL, Ear length; HL, Horn length; CBL, Cannon bone length; HC, Hock circumference; *, p < 0.05; **, p < 0.01; ***, p < 0.0001; NS, Not significant. Traits Aggregate sex Females Males Gamo Gofa Sig. Gamo Gofa Sig. Gamo Gofa Sig. N 300 300 249 237 51 63 BL 109.1±0.37 109.4±0.35 NS 106.9±0.33 107.3±0.34 NS 111.4±0.87 111.1±0.81 NS HG 137.3±0.40 137.1±0.39 NS 134.1±0.36 135.4±0.37 NS 142.9±0.86 136.0±0.80 *** HW 108.9±0.43 108.8±0.41 NS 106.2±0.38 106.2±0.39 NS 112.2±1.13 111.4±1.05 NS PW 31.3±0.21 32.9±0.21 *** 30.7±0.18 32.4±0.18 *** 32.0±0.61 33.0±0.57 NS MC 36.9±0.15 36.8±0.14 NS 36.4±0.14 36.3±0.14 NS 37.2±0.34 37.1±0.31 NS EL 17.0±0.11 17.3±0.11 NS 17.3±0.10 17.7±0.11 NS 16.9±0.22 16.6±0.20 NS HL 16.5±0.21 19.0±0.21 *** 17.2±0.20 20.1±0.20 *** 16.6±0.41 17.6±0.38 NS CBL 25.8±0.15 25.7±0.14 NS 25.7±0.14 25.6±0.14 NS 25.7±0.31 25.8±0.29 NS HC 30.4±0.17 30.6±0.17 NS 30.2±0.16 30.4±0.17 NS 30.8±0.37 30.9±0.35 NS 76 Banjaw et al Genetic Resources (2025), 6 (11), 71–81 Table 5. The effect of sex and age on the cattle morphometric measurements. Measurements are in centimetres. N, number of animals sampled; BL, Body length; HG, Heart girth; HW, Height at withers; PW, Pelvic width; MC, Muzzle circumference; EL, Ear length; HL, Horn length; CBL, Cannon bone length; HC, Hock circumference; *, p < 0.05; **, p < 0.01; ***, p < 0.0001; NS, Not significant. Traits Sex Age Males Females Sig. < 6 6–7 > 7 Sig. N 114 486 169 234 197 BL 111.3±0.51 107.1±0.25 *** 107.8±0.44b 109.7±0.38a 110.1±0.45a ** HG 139.6±0.56 134.8±0.27 *** 135.9±0.48b 137.8±0.42a 137.8±0.50a ** HW 111.4±0.60 106.3±0.29 *** 107.5±0.51b 108.7±0.45b 110.4±0.53a *** PW 32.6±0.30 31.6±0.14 ** 31.7±0.26 32.4±0.22 32.3±0.26 NS MC 37.3±0.21 36.3±0.10 *** 36.3±0.17b 37.4±0.15a 36.7±0.18b *** EL 16.9±0.15 17.5±0.07 ** 17.2±0.13 17.1±0.12 17.2±0.14 NS HL 16.9±0.30 18.6±0.14 *** 16.4±0.26c 19.0±0.22a 17.8±0.26b *** CBL 25.9±0.20 25.7±0.10 NS 25.7±0.17 25.9±0.15 25.7±0.18 NS HC 30.7±0.24 30.2±0.12 NS 30.5±0.21 30.4±0.18 30.5±0.21 NS Table 6. Order of traits used in discriminating between the two cattle populations using a stepwise discriminant analysis (STEPDISC). Sex Step Variables entered Partial R-Square F value Pr > F Wilks’ Lambda Pr < Lambda Females 1 Horn length 0.1630 94.25 < 0.0001 0.8370 < 0.0001 2 Pelvic width 0.0522 26.60 < 0.0001 0.7933 < 0.0001 3 Coat colour pattern 0.0121 5.91 0.0154 0.7837 < 0.0001 4 Canon bone length 0.0099 4.79 0.0291 0.7760 < 0.0001 5 Face profile 0.0085 4.12 0.0428 0.7694 < 0.0001 6 Body length 0.0096 4.63 0.0319 0.7620 < 0.0001 7 Horn shape 0.0076 3.64 0.0570 0.7562 < 0.0001 8 Muzzle circumference 0.0074 3.55 0.0600 0.7506 < 0.0001 9 Hair length 0.0065 3.10 0.0792 0.7458 < 0.0001 10 Horn orientation 0.0047 2.22 0.1368 0.7423 < 0.0001 Males 1 Heart girth 0.2461 35.25 < 0.0001 0.7539 < 0.0001 2 Horn shape 0.1164 14.10 0.0003 0.6661 < 0.0001 3 Horn length 0.0585 6.58 0.0117 0.6272 < 0.0001 4 Hump size 0.0497 5.49 0.0210 0.5960 < 0.0001 5 Pelvic width 0.0388 4.19 0.0431 0.5729 < 0.0001 6 Hock circumference 0.0315 3.35 0.0701 0.5548 < 0.0001 Table 7. Number and (percentage) of observations classified into breed. Sex Breed Gamo Gofa Total Females Gamo 187 (75.10) 62 (24.90) 249 (100) Gofa 80 (33.76) 157 (66.24) 237 (100) Error rate 0.2490 0.3376 0.2933 Males Gamo 43 (86.00) 7 (14.00) 50 (100) Gofa 16 (26.67) 44 (73.33) 60 (100) Error rate 0.1400 0.2667 0.2033 Genetic Resources (2025), 6 (11), 71–81 Characterization of Gamo and Gofa cattle in Ethiopia 77 Figure 2. Effect of breed on coat colour (chi-square value 11.2, p = 0.0836), and effect of sex on coat colour (chi-square value 15.9, p = 0.0142). 3.68 for male cattle, indicating that males were more distantly related than females. However, both distances were small and insufficient to indicate a significant distance between the breeds. The overall multivariate analysis results showed low and non- significant distances between Gamo and Gofa cattle breeds. Plots of the first two canonical variables to discrimi- nate the cattle breeds are presented in Figure 3. In line with the result of the Mahalanobis distances, the stud- ied Gamo and Gofa breeds were found to be inseparable and categorized in the same group, while a relative sep- aration was observed between the males. Discussion Qualitative characteristics Qualitative traits, due to their easily observable nature, are valuable for distinguishing between cattle breeds. Coat colour and coat colour patterns are among the most easily observed traits used to differentiate breeds. However, in this study, these traits did not distinguish the Gamo and Gofa cattle breeds, as most animals from both breeds exhibited uniformly patterned red and light red coat colours. The similarities in coat colour and pattern, along with other morphological and morphometric similarities between the breeds, may suggest genetic relatedness (Mustefa et al (2021) for Table 8. Multivariate statistics outputs of the canonical structures. Multivariate Statistics Females Males Canonical correlation 0.5140 0.7087 Eigen value 0.3591 0.9060 Raya cattle; Getachew et al (2014) and Mustefa et al (2023) for Ogaden cattle). Therefore, the observed similarities in coat colour and pattern between Gamo and Gofa cattle imply phenotypic resemblance, which may reflect underlying genetic similarities. These findings, however, should be validated through genetic analysis. The red-dominant coat colour observed in this study aligns with the findings of Rege and Tawa (1999), who identified red as the primary coat colour in Gofa cattle. Similarly, Kebede et al (2017) also reported that red and white were the most common coat colours in Gofa cattle. In agreement with these findings, Chebo et al (2013) reported that dark and light red were the predominant coat colours in Gamo cattle. The farmers’ preference for red coat colour in both breeds may be linked to farmers’ selection criteria, as red is a preferred colour in the studied areas. According to Kebede et al (2017), coat colour was a significant selection criterion for farmers, following milk yield. Similarities in other qualitative traits, such as horn, ear, hump, face, hair, and tail lengths, were also observed between the Gamo and Gofa cattle breeds, which challenges their classification as distinct breeds. The minor differences observed could be attributed to variations within the breeds. Such intra-breed variations across different sampling locations were also reported by Terefe et al (2015) in Mursi cattle, Mustefa et al (2021) in Raya cattle, and Mustefa (2023) in Harar cattle. Morphometric traits Morphometric measurements, in conjunction with qual- itative traits, provide reliable information for assessing the degree of relationship between breeds. Most of the 78 Banjaw et al Genetic Resources (2025), 6 (11), 71–81 Figure 3. Plots of canonical discriminant analysis based on morphometric traits. A, females; B, males. Breed is indicated by numbers: 1, Gamo; 2, Gofa. morphometric measurements were similar between the two cattle breeds, which supports the observed qualita- tive similarities. Consequently, no significant differences were found between the Gamo and Gofa cattle breeds that could serve to differentiate them. As mentioned in the qualitative section, the slight differences observed may reflect within-breed variations. These variations are crucial for designing conservation and genetic improve- ment programmes. Terefe et al (2015) in Mursi cat- tle, Mustefa et al (2021) in Raya cattle, and Mustefa (2023) in Harar cattle also reported morphometric vari- ations within the same breed across different locations. In comparison with the previous study on Gofa cattle by Kebede et al (2017), the Gofa females in this study showed similar body length, heart girth and wither height. However, they had larger muzzle and hock circumferences, and lower ear and horn lengths. In contrast, the Gofa males in this study exhibited comparable body length but lower values for other morphometric measurements. These findings suggest a reduction in body size of Gofa males over the past seven years, possibly due to negative selection practices by farmers. Similarly, most of the morphometric measurements for the cattle breeds in this study were lower than those reported by Chebo et al (2013) for Gamo cattle, but comparable to those reported by Zeleke et al (2017). The Gamo and Gofa cattle breeds were found to be smaller than many other Ethiopian indigenous cat- tle breeds. This observation is consistent with Rege and Tawa (1999) description of Gofa cattle as the smallest strain of Ethiopian cattle. Their morphomet- ric measurements were smaller than those of breeds such as Afar (Tadesse et al, 2008), Begait (Ftiwi, 2015), Begaria (Getachew et al, 2020), Fogera (Girma et al, 2016), Gojjam Highland (Getachew and Ayalew, 2014), Harar (Mustefa, 2023), Kereyu (Nigatu and Tadesse, 2020), Mursi (Terefe et al, 2015), Nuer (Min- uye et al, 2018), Ogaden (Mustefa, 2023) and Raya cattle (Mustefa et al, 2021). However, their measure- ments were larger than those of Abergelle and Irob cattle breeds (Zegeye et al, 2021). Similar morphometric traits Genetic Resources (2025), 6 (11), 71–81 Characterization of Gamo and Gofa cattle in Ethiopia 79 were also observed in Arado (Genzebu et al, 2012) and Horro cattle (Bekele, 2015). Multivariate analysis High partial R-Square and F-values are necessary to demonstrate significant discrimination between popu- lations. Additionally, low error rates are essential to show the distinctiveness of separate breeds. However, the results from the stepwise analysis (Table 6) exhib- ited low partial R-Square and F-values, indicating weak discriminatory potential of the morphometric traits. Fur- thermore, high error rates (Table 7) were observed, indicating greater similarities between the cattle pop- ulations, which lowers the likelihood of classifying the breeds into separate clusters. In contrast, lower error rates would indicate distinct differences between the breeds. For example, an error rate of 1% was reported in the classification of phenotypically unrelated Harar and Ogaden cattle breeds (Mustefa, 2023). An eigenvalue greater than 1 is required for breed discrimination. If the value falls below 1, discrimination between the studied animals is not significant. The lowest eigenvalues observed in both sexes (Table 8) failed to distinguish the cattle populations into separate clusters, suggesting the absence of two distinct breeds. Similarly, high Mahalanobis distances between breeds are needed for clear cluster separation, but the Mahalanobis distance results in this study were low, with males showing slightly higher distances. This could be attributed to the smaller sample size of oxen. The accuracy of the analysis improves with larger sample sizes. Due to the low eigenvalue (< 1) and short Mahalanobis distances in the multivariate analysis, the studied cattle breeds were found to be phenotypically inseparable. However, phenotypic similarities do not necessarily imply genetic similarities between breeds (Zechner et al, 2001). Effect of sex and age Sex and age had minimal effects on the qualitative traits of the studied cattle populations since qualitative traits are typically controlled by fewer genes (Falconer, 1989). Therefore, successive planned selection activities are required to bring changes to the qualitative traits. On the other hand, the morphometric traits were influenced by both sex and age, because quantitative traits are influenced by a greater number of genes (Falconer, 1989). This means a few natural or artificial selection activities can produce significant changes to the quantitative traits. Accordingly, males were generally larger than females in most morphometric traits of both breeds, aligning with Rensch’s rule (Rensch, 1950), which suggests that females of a species are usually smaller than males. These differences could be attributed to testosterone, which promotes the development of skeletal and muscle mass in males (Baneh and Hafezian, 2009). The effect of the endocrine system on growth was also significant, with estrogen’s influence on growth being more limited in females (Chriha and Ghadri, 2001; Baneh and Hafezian, 2009). Similar findings, showing male dominance in size, were reported by Mustefa (2023) for Harar and Ogaden cattle breeds, Mustefa et al (2021) for Raya cattle, and Terefe et al (2015) for Mursi cattle. Age significantly affected five morphometric traits. Body length and heart girth measurements showed sta- ble body development from the middle-aged group, while muzzle circumference and horn length measure- ments indicated the middle-aged group as optimal for these traits. Significantly different breeds need to be registered separately, while the same breed should be registered only once. This is because our next step as a country is to design breeding programmes that include both con- servation and genetic improvement activities for each breed individually. Therefore, conducting these pro- grammes separately for breeds without significant dif- ferences would be inappropriate. The currently observed differences among these breeds can be considered as within-breed variation; however, this needs to be sup- ported by further genetic characterization studies. Conclusion In accordance to the observed similarities in morpholog- ical and morphometric traits between Gamo and Gofa cattle breeds, multivariate analysis failed to identify significant differences, suggesting that the two breeds are inseparable. However, phenotypic similarities do not necessarily indicate genetic similarity. Therefore, fur- ther genetic characterization is recommended to assess the genetic relationship between these breeds. In the meantime, the studied cattle populations should not be regarded as separate breeds. Breed-specific in situ con- servation and genetic improvement programmes should consider the cattle populations as a single entity. Addi- tionally, a unified breed name that can represent both populations is recommended for consideration by the country’s National Advisory Steering Committee for Ani- mal Genetic Resources. Acknowledgments The authors are highly indebted to the Ethiopian Biodiversity Institute (EBI) and Wolita Sodo University for covering some of the budget for this work. Our special appreciation also goes to the smallholder farmers/breeders for providing their animals to this work for free. We also take this opportunity to thank the animal science experts and development agents for their endless help during data collection. References Baneh, H. and Hafezian, S. H. (2009). Effect of environmental factor on growth traits in Ghezel sheep. African Journal of Bio-technology 8, 2903–2907. url: https://www.ajol.info/index.php/ ajb/article/view/60943. https://www.ajol.info/index.php/ajb/article/view/60943 https://www.ajol.info/index.php/ajb/article/view/60943 80 Banjaw et al Genetic Resources (2025), 6 (11), 71–81 Bekele, D. T. (2015). On-farm phenotypic characteri- zation of indigenous cattle and their production sys- tems in Bako Tibe and Gobu Sayo districts of Oro- mia Region, Ethiopia. MSc thesis, Haramaya Univer- sity, Haramaya, Ethiopia. Chankalo, T. H. (2022). Species composition and relative abundance of medium and large- sized mammals in Woyde Woshe Commu- nity Reserve forest areas. Journal of Ecology and The Natural Environment 13(1), 1–8. url: https://academicjournals.org/journal/JENE/article- in-press-abstract/species composition and relative abundance of medium and large sized mammals in woyde woshe community reserve forest areas kucha alpha woreda gamo zone southern ethiopia. Chebo, C., Ayalew, W., and Wuletaw, Z. (2013). On-farm phenotypic characterization of indigenous cattle populations of Gamo Goffa zone, Southern Ethiopia. Animal Genetic Resource Information Bulletin 52, 71–82. doi: https://doi.org/10.1017/ S207863361200046X Cholo, T. C., Fleskens, L., Sietz, D., and Peerlings, J. (2018). s Land Fragmentation Facilitating or Obstructing Adoption of Climate Adaptation Measures in Ethiopia? Sustainability 10(2120). doi: https://doi. org/10.3390/su10072120 Chriha, A. and Ghadri, G. (2001). Caprine in the Arab world. 2. ed. Department of Livestock Production. Fateh University: Libby Conservation of Biodiversity and Environments in the Arab Countries 478p. CSA (2022). Agricultural Sample Survey 2021/22 (2014 E.C). Report on Livestock and Livestock Characteristics Statistical Bulletin No. 594 volume II. (Addis Ababa, Ethiopia: Federal Democratic Republic of Ethiopia Central Statistical Agency), 219p. EBI (2016). Ethiopian National Strategy and Plan of Action for conservation and uti- lization of Animal Genetic Resources. url: https://www.ebi.gov.et/wp-content/uploads/2021/ 10/Ethiopian-National-Strategy-and-Plan-of-Action- for-Conservation-Sustainable-Use-and-Development- of-Animal-Genetic-Resources-.pdf. Falconer, D. S. (1989). Introduction to Quantitative Genetics (New York: Longman), 3rd edition, 438p. FAO (2012). Phenotypic characterization of animal genetic resources. FAO Animal Production and Health Guidelines number 11 (Rome: FAO). url: https:// www.fao.org/3/a1404e/a1404e.pdf. Ftiwi, M. (2015). Production system and phenotypic characterization of Begait cattle, and effects of supplementation with concentrate feeds on milk yield and composition of Begait cows in Humera ranch, Western Tigray, Ethiopia. Ph.D. thesis, Addis Ababa University, Debre Zeit, Ethiopia. Gegnaw, S. T. and Hadado, T. T. (2014). Genetic diversity of qualitative traits of barley (Hordeum Vulgare L.) landrace populations collected from Gamo Highlands of Ethiopia. International Journal of Biodiversity and Conservation 6(9), 663–673. doi: https://doi.org/10.5897/IJBC2014.0718 Genzebu, D., Hailemariam, M., and Belihu, K. (2012). Morphometric characteristics and livestock keeper perceptions of “Arado” cattle breed in Northern Tigray, Ethiopia. Livestock Research for Rural Development 24(6). url: https://www.lrrd.org/lrrd24/ 1/hail24006.htm. Getachew, F., Abegaz, S., Misganaw, M., and Fekansa, T. (2014). On-farm phenotypic char- acterization of Ogaden cattle populations of Jigjiga zone, southeastern Ethiopia. Ethiopian Journal of Animal Production 14, 66–83. url: https://www.researchgate.net/publication/ 325011260 On-farm phenotypic characterization of Ogaden cattle populations of Jigjiga zone southeastern Ethiopia. Getachew, F., Assefa, A., Getachew, T., Abegaz, S. K., Hailu, A., Mesganaw, M., Emishaw, Y., and Tessema, M. (2020). On-Farm phenotypic characterization of Begaria cattle population and their production system in Guba district. Ethiopian Journal of Animal Production 20(1), 1– 17. url: https://www.researchgate.net/publication/ 349625372 On-Farm Phenotypic Characterization of Begaria Cattle Population and Their Production System in Guba District North Western Ethiopia. Getachew, F. K. and Ayalew, W. (2014). On- farm phenotypic characterization of indigenous cattle populations of Awi, East and West Gojjam Zones of Amhara Region. Ethiopia. Research Journal of Agriculture and Environmental Management 3(4), 227–237. Girma, E., Alemayehu, K., Abegaze, S., and Kebede, D. (2016). Phenotypic characterization, population structure, breeding management and recommend breeding strategy for Fogera cattle (Bos indicus) in Northwestern Amhara, Ethiopia. Animal Genetic Resources 58, 13–29. doi: https://doi.org/10.1017/ S2078633616000035 Kassa, G., Bekele, T., Demissew, S., and Abebe, T. (2022). Above- and belowground biomass and biomass carbon stocks in home garden agroforestry systems of different age groups at three sites of southern and southwestern Ethiopia. Carbon Management 13(1), 531–549. doi: https://doi.org/10. 1080/17583004.2022.2133743 Kebede, H., Jimma, A., Getiso, A., and Zelke, B. (2017). Characterization of Gofa cattle population, production system, production and reproduction performance in Southern Ethiopia. Journal of Fisheries and Livestock Production 5(3), 237. doi: http://doi.org/10.4172/ 2332-2608.1000237 Kramer, C. Y. (1956). Extension of Multiple Range Tests to Group Means with Unequal Number of Replications. Biometrics 12, 307–310. doi: https://doi. org/10.2307/3001469 https://academicjournals.org/journal/JENE/article-in-press-abstract/species_composition_and_relative_abundance_of_medium_and_large_sized_mammals_in_woyde_woshe_community_reserve_forest_areas_kucha_alpha_woreda_gamo_zone_southern_ethiopia https://academicjournals.org/journal/JENE/article-in-press-abstract/species_composition_and_relative_abundance_of_medium_and_large_sized_mammals_in_woyde_woshe_community_reserve_forest_areas_kucha_alpha_woreda_gamo_zone_southern_ethiopia https://academicjournals.org/journal/JENE/article-in-press-abstract/species_composition_and_relative_abundance_of_medium_and_large_sized_mammals_in_woyde_woshe_community_reserve_forest_areas_kucha_alpha_woreda_gamo_zone_southern_ethiopia https://academicjournals.org/journal/JENE/article-in-press-abstract/species_composition_and_relative_abundance_of_medium_and_large_sized_mammals_in_woyde_woshe_community_reserve_forest_areas_kucha_alpha_woreda_gamo_zone_southern_ethiopia https://academicjournals.org/journal/JENE/article-in-press-abstract/species_composition_and_relative_abundance_of_medium_and_large_sized_mammals_in_woyde_woshe_community_reserve_forest_areas_kucha_alpha_woreda_gamo_zone_southern_ethiopia https://doi.org/10.1017/S207863361200046X https://doi.org/10.1017/S207863361200046X https://doi.org/10.3390/su10072120 https://doi.org/10.3390/su10072120 https://www.ebi.gov.et/wp-content/uploads/2021/10/Ethiopian-National-Strategy-and-Plan-of-Action-for-Conservation-Sustainable-Use-and-Development-of-Animal-Genetic-Resources-.pdf https://www.ebi.gov.et/wp-content/uploads/2021/10/Ethiopian-National-Strategy-and-Plan-of-Action-for-Conservation-Sustainable-Use-and-Development-of-Animal-Genetic-Resources-.pdf https://www.ebi.gov.et/wp-content/uploads/2021/10/Ethiopian-National-Strategy-and-Plan-of-Action-for-Conservation-Sustainable-Use-and-Development-of-Animal-Genetic-Resources-.pdf https://www.ebi.gov.et/wp-content/uploads/2021/10/Ethiopian-National-Strategy-and-Plan-of-Action-for-Conservation-Sustainable-Use-and-Development-of-Animal-Genetic-Resources-.pdf https://www.fao.org/3/a1404e/a1404e.pdf https://www.fao.org/3/a1404e/a1404e.pdf https://doi.org/10.5897/IJBC2014.0718 https://www.lrrd.org/lrrd24/1/hail24006.htm https://www.lrrd.org/lrrd24/1/hail24006.htm https://www.researchgate.net/publication/325011260_On-farm_phenotypic_characterization_of_Ogaden_cattle_populations_of_Jigjiga_zone_southeastern_Ethiopia Getachew, F., Assefa, A., Getachew, T., Abegaz, S.K., Hailu, A., Mesganaw, M., https://www.researchgate.net/publication/325011260_On-farm_phenotypic_characterization_of_Ogaden_cattle_populations_of_Jigjiga_zone_southeastern_Ethiopia Getachew, F., Assefa, A., Getachew, T., Abegaz, S.K., Hailu, A., Mesganaw, M., https://www.researchgate.net/publication/325011260_On-farm_phenotypic_characterization_of_Ogaden_cattle_populations_of_Jigjiga_zone_southeastern_Ethiopia Getachew, F., Assefa, A., Getachew, T., Abegaz, S.K., Hailu, A., Mesganaw, M., https://www.researchgate.net/publication/325011260_On-farm_phenotypic_characterization_of_Ogaden_cattle_populations_of_Jigjiga_zone_southeastern_Ethiopia Getachew, F., Assefa, A., Getachew, T., Abegaz, S.K., Hailu, A., Mesganaw, M., https://www.researchgate.net/publication/325011260_On-farm_phenotypic_characterization_of_Ogaden_cattle_populations_of_Jigjiga_zone_southeastern_Ethiopia Getachew, F., Assefa, A., Getachew, T., Abegaz, S.K., Hailu, A., Mesganaw, M., https://www.researchgate.net/publication/349625372_On-Farm_Phenotypic_Characterization_of_Begaria_Cattle_Population_and_Their_Production_System_in_Guba_District_North_Western_Ethiopia https://www.researchgate.net/publication/349625372_On-Farm_Phenotypic_Characterization_of_Begaria_Cattle_Population_and_Their_Production_System_in_Guba_District_North_Western_Ethiopia https://www.researchgate.net/publication/349625372_On-Farm_Phenotypic_Characterization_of_Begaria_Cattle_Population_and_Their_Production_System_in_Guba_District_North_Western_Ethiopia https://www.researchgate.net/publication/349625372_On-Farm_Phenotypic_Characterization_of_Begaria_Cattle_Population_and_Their_Production_System_in_Guba_District_North_Western_Ethiopia https://doi.org/10.1017/S2078633616000035 https://doi.org/10.1017/S2078633616000035 https://doi.org/10.1080/17583004.2022.2133743 https://doi.org/10.1080/17583004.2022.2133743 http://doi.org/10.4172/2332- 2608.1000237 http://doi.org/10.4172/2332- 2608.1000237 https://doi.org/10.2307/3001469 https://doi.org/10.2307/3001469 Genetic Resources (2025), 6 (11), 71–81 Characterization of Gamo and Gofa cattle in Ethiopia 81 Leulalem, S. B., Alemayehu, A., Elias, G., Assefa, G., Yegelilaw, E., and Temesgen, L. (2016). Ground- water Investigation for Domestic Purpose Zala Woreda. International Journal of Engineering Sci- ence and Computing 6(7), 1869–1881. url: https: //www.researchgate.net/publication/321392194 Groundwater Investigation for Domestic Purpose Zala Woreda Gamo Gofa Zone Southern Ethiopia. Minuye, N., Abebe, G., and Dessie, T. (2018). On-farm description and status of Nuer (Abigar) cattle breed in Gambella Regional State, Ethiopia. International Journal of Biodiversity and Conservation 10(6), 292– 302. doi: https://doi.org/10.5897/IJBC2017.1168 Mustefa, A. (2023). Implication of phenotypic and molecular characterization to breed differentiation of Ethiopian cattle. A review. Ecological Genetics and Genomics 29(100208). doi: https://doi.org/10.1016/ j.egg.2023.100208 Mustefa, A., Aseged, T., Sinkie, S., Getachew, F., Fekensa, T., Misganaw, M., and Hailu, A. (2023). Phenotypic diversity between and within Harar and Ogaden cattle breeds in eastern Ethiopia: The first step for conservation. Genetic Resources 4(7), 56–67. doi: https://doi.org/10.46265/genresj.IXPJ9541 Mustefa, A., Belayhun, T., Melak, A., Hayelom, M., Tadesse, D., Hailu, A., and Assefa, A. (2021). Phenotypic characterization of Raya cattle in northern Ethiopia. Tropical Animal Health and Production 53(48). doi: https://doi.org/10.1007/s11250-020- 02486-1 Nigatu, Y. M. and Tadesse, Y. (2020). Morphological Variations of Arsi, Kereyu and their Crossbred Cattle under current climate change in mid Rift Valley of Oromia, Ethiopia. Academic Research Journal of Agricultural Science and Research 8(6), 630–648. doi: http://doi.org/10.14662/ARJASR2020.440 Rege, J. E. O. (1999). The state of African cattle genetic resources I. Classification framework and identification of threatened and extinct breeds. Animal Genetic Resources Information 25, 1–25. doi: https://doi.org/10.1017/S1014233900003448 Rege, J. E. O. and Tawa, C. L. (1999). The state of African cattle genetic resources II. Geographical distribution, characteristics and uses of present- day breeds and strains. Animal Genetic Resources Information 26, 1–25. doi: https://doi.org/10.1017/ S1014233900001152 Rensch, B. (1950). Die Abhangigkeit der relative sexual differenz von der korpergrosse. Bonner Zoologische Beitrage 1, 58–69. url: https://www. biodiversitylibrary.org/partpdf/119381. SAS (2002). Statistical Analysis System. Version 9.0 for windows. SAS Institute Inc., Cary NC, USA. url: https://www.sas.com/enus/home.html. Statista (2024). Africa: countries with largest cattle population 2024. url: https://www.statista.com/ statistics/1290046/cattle-population-in-africa-by- country/. Tadesse, D., Ayalew, W., and Hegde, B. P. (2008). On-farm Phenotypic Characterization of Cattle Genetic Resources in South and North Wollo Zones of Amhara Region. Ethiopian Journal of Animal Production 8(1), 22–38. url: https:// www.researchgate.net/publication/284724322 On- farm Phenotypic Characterization of Cattle Genetic Resources in South and North Wollo Zones of Amhara Region North Eastern Ethiopia. Tatum, J. D. (2011). Animal age, physiological maturity, and associated effects on beef tenderness. White paper Research and Knowledge Management. Terefe, E., Dessie, T., Haile, A., Mulatu, W., and Mwai, O. (2015). On-farm phenotypic characterization of Mursi cattle in its production environment in South Omo Zone, Southwest Ethiopia. Animal Genetic Resources 57, 15–24. doi: https://doi.org/10.1017/ S2078633615000132 Tukey, J. W. (1953). The problem of multiple comparisons. Unpublished manuscript (Princeton University) . Yimamu, C. (2014). In situ phenotypic characterization and production system study of Arsi cattle type in Arsi highland of Oromia Region, Ethiopia. MSc thesis, Haramaya University, Haramaya, Ethiopia. Zechner, P., Zohman, F., Solkner, J., Bodo, I., Habe, F., Marti, E., and Brem, G. (2001). Morphological description of the Lipizzan horse population. Livestock Production Science 69, 163–177. doi: https://doi.org/ 10.1007/s11250-021-02652-z Zegeye, T., Belay, G., and Hanotte, O. (2021). Multivari- ate characterization of phenotypic traits of five native cattle populations from Tigray, Northern Ethiopia. Tropical Animal Health and Production 53(212). doi: https://doi.org/10.1007/s11250-021-02652-z Zeleke, B., Getachew, M., and Worku, K. (2017). Phenotypic characterization of indigenous cattle populations in Gamo Gofa Zone, Southwestern Ethiopia. European Journal of Biological Sciences 9(3), 124–130. doi: http://dx.doi.org/10.5829/idosi.ejbs. 2017.124.130 Zerabruk, M. and Vangen, O. (2005). The Abergelle and Irob cattle breeds of North Ethiopia: description and on-farm characterization. Animal Genetic Resources Information Bulletin 36, 7–20. doi: https://doi.org/10. 1017/S101423390000184X https://www.researchgate.net/publication/321392194_Groundwater_Investigation_for_Domestic_Purpose_Zala_Woreda_Gamo_Gofa_Zone_Southern_Ethiopia https://www.researchgate.net/publication/321392194_Groundwater_Investigation_for_Domestic_Purpose_Zala_Woreda_Gamo_Gofa_Zone_Southern_Ethiopia https://www.researchgate.net/publication/321392194_Groundwater_Investigation_for_Domestic_Purpose_Zala_Woreda_Gamo_Gofa_Zone_Southern_Ethiopia https://www.researchgate.net/publication/321392194_Groundwater_Investigation_for_Domestic_Purpose_Zala_Woreda_Gamo_Gofa_Zone_Southern_Ethiopia https://doi.org/10.5897/IJBC2017.1168 https://doi.org/10.1016/j.egg.2023.100208 https://doi.org/10.1016/j.egg.2023.100208 https://doi.org/10.46265/genresj.IXPJ9541 https://doi.org/10.1007/s11250-020-02486-1 https://doi.org/10.1007/s11250-020-02486-1 http://doi.org/10.14662/ARJASR2020.440 https://doi.org/10.1017/S1014233900003448 https://doi.org/10.1017/S1014233900001152 https://doi.org/10.1017/S1014233900001152 https://www.biodiversitylibrary.org/partpdf/119381 https://www.biodiversitylibrary.org/partpdf/119381 https://www.sas.com/enus/home.html https://www.statista.com/statistics/1290046/cattle-population-in-africa-by-country/ https://www.statista.com/statistics/1290046/cattle-population-in-africa-by-country/ https://www.statista.com/statistics/1290046/cattle-population-in-africa-by-country/ https://www.researchgate.net/publication/284724322_On-farm_Phenotypic_Characterization_of_Cattle_Genetic_Resources_in_South_and_North_Wollo_Zones_of_Amhara_Region_North_Eastern_Ethiopia https://www.researchgate.net/publication/284724322_On-farm_Phenotypic_Characterization_of_Cattle_Genetic_Resources_in_South_and_North_Wollo_Zones_of_Amhara_Region_North_Eastern_Ethiopia https://www.researchgate.net/publication/284724322_On-farm_Phenotypic_Characterization_of_Cattle_Genetic_Resources_in_South_and_North_Wollo_Zones_of_Amhara_Region_North_Eastern_Ethiopia https://www.researchgate.net/publication/284724322_On-farm_Phenotypic_Characterization_of_Cattle_Genetic_Resources_in_South_and_North_Wollo_Zones_of_Amhara_Region_North_Eastern_Ethiopia https://www.researchgate.net/publication/284724322_On-farm_Phenotypic_Characterization_of_Cattle_Genetic_Resources_in_South_and_North_Wollo_Zones_of_Amhara_Region_North_Eastern_Ethiopia https://doi.org/10.1017/S2078633615000132 https://doi.org/10.1017/S2078633615000132 https://doi.org/10.1007/s11250-021-02652-z https://doi.org/10.1007/s11250-021-02652-z https://doi.org/10.1007/s11250-021-02652-z http://dx.doi.org/10.5829/idosi.ejbs.2017.124.130 http://dx.doi.org/10.5829/idosi.ejbs.2017.124.130 https://doi.org/10.1017/S101423390000184X https://doi.org/10.1017/S101423390000184X Introduction Materials and methods Study areas Site and animal selection Data collection Data analysis Results Qualitative characteristics Morphometric traits Multivariate analysis Stepwise discriminant analysis Discriminant analysis Canonical discriminant analysis Discussion Qualitative characteristics Morphometric traits Multivariate analysis Effect of sex and age Conclusion