West African donkey's liveweight estimation using body measurements

Feed balances for ruminant livestock: gridded estimates for data-constrained regions

Demand for animal-source foods and livestock feed are forecast to increase across sub-Saharan Africa. In this context, there is a need to estimate the availability of livestock feed to support decision-making at local, sub-national and national levels. In this study, we assess feed balances for ruminant livestock in Ethiopia and Burkina Faso. Feed availability was estimated using remotely sensed products and detailed feed composition data. Feed requirements were estimated for maintenance, growth, lactation, gestation and locomotion using a data-intensive model. Biomass available as animal feed was estimated to be 8.6 tonnes of DM per hectare in the Ethiopian highlands and midlands, 3.2 tonnes DM per hectare in the Ethiopian lowlands, 2.9 tonnes DM per hectare in Burkina Faso's Sudanian agro-ecological zone and 1.0 tonne DM per hectare in the Sahel. The energy requirements of lactating cows were estimated to be 62.1 Megajoules (MJs) per animal per day in the Ethiopian highlands and midlands, 62.7 MJ in the Ethiopian lowlands, 88.5 MJ in Burkina Faso's Sudanian agro-ecological zone and 53.1 MJ per animal per day in the Sahel. Feed scarcity hotspots are most prominently located in the Ethiopian highlands and the Sahelian agro-ecological zone of Burkina Faso. Demand-side policy and investment initiatives can address hotspots by influencing herd sizes, nutritional requirements and herd mobility. Supply-side policy and investment initiatives can secure existing feed resources, develop new sources of feed and incentivise trade in feed resources. Improving feed balances will be of value to decision-makers with the aims of optimising livestock productivity, minimising exposure to climatic shocks and minimising greenhouse gas emission intensity.

Investigation of the Relationships between Coat Colour, Sex, and Morphological Characteristics in Donkeys Using Data Mining Algorithms

This study was carried out in order to determine the morphological characteristics, body coat colour distribution, and body dimensions of donkeys raised in Turkey, as well as to determine the relationships between these factors. For this reason, the predictive performance of various machine learning algorithms (i.e., CHAID, Random Forest, ALM, MARS, and Bagging MARS) were compared, utilising the biometric data of donkeys. In particular, mean measurements were taken from a total of 371 donkeys (252 male and 119 female) with descriptive statistical values as follows: height at withers, 100.7 cm; rump height, 103.1 cm; body length, 103.8 cm; chest circumference, 112.8 cm; chest depth, 45.7 cm; chest width, 29.1 cm; front shin circumference, 13.5 cm; head length, 55 cm; and ear length, 22 cm. The body colour distribution of the donkeys considered in this study was calculated as 39.35% grey, 19.95% white, 21.83% black, and 18.87% brown. Model fit statistics, including the coefficient of determination (R²), mean square error, root-mean-square error (RMSE), mean absolute percentage error (MAPE), and standard deviation ratio (SD ratio), were calculated to measure the predictive ability of the fitted models. The MARS algorithm was found to be the best model for defining the body length of donkeys, with the highest R² value (0.916) and the lowest RMSE, MAPE, and SD ratio values (2.173, 1.615, and 0.291, respectively). The experimental results indicate that the most suitable model is the MARS algorithm, which provides a good alternative to other data mining algorithms for predicting the body length of donkeys.

Assessment of Phenotypic Characteristics and Work Suitability for Working Donkeys in the Central Highlands in Kenya

The study aimed to assess the phenotypic characteristics of donkeys and their suitability for work. Data were collected on age, sex, coat color, height at withers, body length, and heart girth from 360 randomly sampled donkeys raised in a highland agroecological system in Kenya between the months of June and September 2018. Data were analyzed using descriptive statistics and ANOVA with the sex of the donkey and age group treated as sources of variation. The weight of donkeys was estimated using a formulae incorporating body length and heart girth. The study reveals that the average weight of the working donkey in the central highlands of Kenya was 155.5 kgs ± SE 1.71. Their height at withers was 99.7 cm ± SEM 0.50, with a heart girth of 113.7 cm ± SEM 0.43 and a body length of 113.2 cm ± SEM 0.58. All these body measurements varied significantly by sex and age group (P < 0.001). Therefore, donkeys raised in Kenya had the same height but heavier, with longer body lengths and heart girth measurements when compared to other domesticated working donkeys in different parts of the world indicating genetic diversity, differences in ecogeographical conditions and husbandry practices. The majority (86%) of the donkeys were in good welfare conditions with moderate to ideal 86% body condition scores, minimal body lesions 5%, and lameness 18%. The results are useful for extension agents and donkey users when estimating optimal pack or cart loads in line with their welfare. The findings provide opportunities for future research on the reasons for phenotypic diversity between donkeys raised in Kenya and other parts of the world.

Morphometric Characteristics of the Extreme Eastern Algerian Domestic Donkey (Equus asinus)

The aim of this study was to define the morphometric variability of the extreme Eastern Algerian donkeys. The study was carried out from June to December 2018 in El-Tarf, Souk-Ahras, and Tebessa provinces. The study population involved 65 individuals (32 jacks and 33 jennies) between the ages of 3 and 16 years old. In total, 13 body measurements were used, and 5 zootechnical indexes were calculated. The quantitative and qualitative characteristics were studied in order to establish an ethnic and functional classification of this particular subspecies. The qualitative data demonstrated that the coat colour was variable. Bay and greyish colours were dominant with a respective rate of 61.5 % and 38.5 %, respectively. The head, the nose, as well as the eyes contour colours were mainly grey with 52.3 %, 58.5 % and 50.8 % respectively. The partial absence of the coat particularities was observed. The population presented a significate relationship between the quantitative characters (P < 0.05). The donkeys were longilinear, of a rectilinear profile, compact with massive trends. They had a hyper-metric format. The animals are good for meat production. The General Linear Model (GLM) showed that the body measurements were variable by sex and body mass. The principal component analysis (PCA), the multiple correspondence analyses (MCA) and the ascending hierarchical classification (AHC) revealed that the population was composed of 2 clusters representing 4 animal classes. This study was the first report on the phenotypic characterization of donkeys in the extreme Eastern Algerian area, based on corporal measurements. The results indicated the existence of heterogeneity and suggested the possibilities of genetic improvement within the species.

Estimation of Live Weight by Body Measurements in the Miranda Donkey Breed

The use of the measurement of heart girth (HG), in locations where a scale is not available, with the application of weight estimation formulas or special weight tapes, is well established as a practical and accurate way to estimate the live weight (LW). Although several studies were performed to correlate donkey body measurements and LW, none of these was done in the large frame European donkey breeds. When using smaller frame breeds formulas, the tendency was to underestimate the live weight of larger frame breeds. The sample used in this study consisted of 65 Miranda breed donkeys, with ages ranging from 4 days to 15.4 years (6.6 ± 4.4 years). The studied population mean LW was 280.8 ± 106.1 kg (32.5-475.5 kg); the mean height was 127.4 ± 14.7 cm (69-157.5 cm); the mean body length (BL) was 131.4 ± 25.3 cm (59-184 cm); and the mean HG was 143.8 ± 23.1 cm (71-175 cm). All the correlations between LW and the body measurements taken were statistically significant (P < .001), but the degree of accuracy was higher in the HG (r = 0.937) than in the BL (r = 0.915) or height (r = 0.894). The formula that best estimates the LW was performed by Quadratic model and was based on the HG measurement: LW = 98.138-3.0386 × HG + 0.0293 × HG² (LW in kilogram; HG in centimeter). The formula found can be used to create a weighing tape, adapted to large frame European donkey breeds, to be used to estimate weight and better adapt medication dosages and carried load for each animal.

Ergonomic study of donkeys administered with Pycnogenol® and subjected to packing during the hot-dry season in Northern Nigeria

The aim of the study was to determine some ergonomic parameters of donkeys administered with Pycnogenol® (PYC) and subjected to packing during the hot-dry season in northern Nigeria. Fifteen donkeys served as experimental subjects. Group 1 (n = 5) donkeys were subjected to trekking only (control), group 2 (n = 5) donkeys were subjected to packing (P-PYC), and group 3 (n = 5) were administered with PYC (10 mg/kg) and subjected to packing (P+PYC). Each group covered a distance of 10 km. Some ergonomic parameters were evaluated. The duration of work in control, P-PYC, and P+PYC donkeys were 170.0 ± 10 min (2.8 h), 126.6 ± 6.7 min (2.1 h), and 112.0 ± 3.9 min (1.9 h), respectively. The energy expenditure obtained for P-PYC group (88.3 ± 9.8 KJ/s) was significantly higher than the values of 28.3 ± 3.7 KJ/s and 73.5 ± 9.9 KJ/s obtained in control and P+PYC groups, respectively. The output was significantly higher in P+PYC group with the value of 5263.2 ± 135 m/h. In conclusion, packing the donkeys during the hot-dry season was stressful; however, PYC may have served as a potent antifatigue agent to reduce the stress.