scholarly journals Risk factors for smallholder dairy cattle mortality in Tanzania

2010 ◽  
Vol 81 (4) ◽  
Author(s):  
E.S. Swai ◽  
E.D. Karimuribo ◽  
D.M. Kambarage
Keyword(s):  
Mortality Risk ◽  
Dairy Farms ◽  
Mortality Rates ◽  
Total Risk ◽  
Urban District ◽  
Cross Sectional ◽  
Young Stock ◽  
Management Interventions ◽  
Smallholder Dairy ◽  
Smallholder Dairy Farms

A retrospective cross-sectional study of mortality was conducted on smallholder dairy farms in 2 separate regions (Iringa and Tanga) of Tanzania during the period of January to April 1999. A total of 1789 cattle from 400 randomly sampled smallholder dairy farms (200 each from Iringa and Tanga regions) were included in the study. These animals contributed a total risk period of 690.4 and 653.95 years for Tanga and Iringa, respectively. The overall mortality rates were estimated to be 8.5 and 14.2 per 100 cattle years risk for Tanga and Iringa regions, respectively; 57.7 % of the reported deaths were of young stock less than 12 months old; 45 % of reported young stock deaths (≤12 months old) were due to tick-borne diseases, mainly East Coast Fever (ECF) and anaplasmosis. Disease events including ECF were reported to occur in all months of the year. Survival analysis using Cox proportional hazard models indicated that, in both regions, death rate and risk was higher in young stock less than 12 months than in older animals (relative risk RR=4.92, P <0.001 for Iringa; RR = 5.03 P = 0.005 for Tanga). In the Tanga region reported mortality rates were significantly higher for male animals (RR = 3.66, P = 0.001) and F2 compared with F1 animals (RR=3.04, P=0.003). In the Iringa region, reported mortality rates were lower for cattle on farms where the owner had attended a dairy development project training course (RR = 0.47, P = 0.012). Farms located in Iringa urban district and Pangani were associated with higher risk (mortality risk 21 % for Iringa urban and 34 % for Pangani). Our findings suggest that timely health and management interventions on these factors are necessary to alleviate losses from disease and emphasise that understanding variation in mortality risk within a population can enhance early response to potential outbreaks, reducing losses.

scholarly journals Major Causes of Calf Morbidity and Mortality in Smallholder Dairy Farms in Shashemene Town, Ethiopia

2021 ◽  
Vol 3 (2) ◽  
Author(s):  
Abdela Edao ◽  
Abdurahman Meribo
Keyword(s):  
Risk Factors ◽  
Management Practices ◽  
Dairy Farms ◽  
Cross Sectional Study ◽  
Morbidity And Mortality ◽  
Cross Sectional ◽  
Potential Risk Factors ◽  
Smallholder Dairy ◽  
Floor Condition ◽  
Smallholder Dairy Farms

A cross-sectional study was conducted to determine the major causes of calf morbidity and mortality in smallholder dairy farms and associated potential risk factors in Shashemene. A total of 187 calves from 46 farms were included in the present study. The overall crude morbidity and crude mortality rates were 27.8% and 6.4%, respectively. The most frequent disease syndrome was diarrhea with incidence rate of 28(15%) followed by pneumonia 8(4.3%), Gastrointestinal tract (GIT) disorder 8(4.3%) and septicemia 5(2.7%). In addition skin lesion, navel ill and unidentified cases were encountered. The main causes of death were diarrhea 6(3.2%), Septicemia 2(1.1%), GIT disorder 2(1.1%), pneumonia 1(0.5%) and others 1(0.5%). The most important risk factors associated with morbidity and mortality were housing hygiene, floor condition and calf size in farm. Out of 187 calves examined for GIT parasites; 63(33.3%) were positive for nematode eggs. Prevalence of helminthes parasite increased with increasing age, showing higher prevalence (P<0.05) in calves above 2 months than in calves below 2 months of age. Besides, majority of the calves, 48(25.7%) were found positive for coccidian oocyst. In general; diarrhea, pneumonia and septicemia were the major causes of calf morbidity and mortality. Interms of risk factors housing hygiene, floor condition, calf size in the farms, age and breed were identified major role players. Therefore, identifying major causes and improving management practices and breed should be given to emphasis by advisory of smallholder dairy farms.

Impact of management interventions on smallholder dairy farms of the western highlands of cameroon

2008 ◽  
Vol 41 (6) ◽  
pp. 907-912 ◽  
Author(s):  
P. H. Bayemi ◽  
E. C. Webb ◽  
A. Ndambi ◽  
F. Ntam ◽  
V. Chinda
Keyword(s):  
Dairy Farms ◽  
Management Interventions ◽  
Smallholder Dairy ◽  
Smallholder Dairy Farms

scholarly journals A cross-sectional study of the welfare of calves raised in smallholder dairy farms in Meru, Kenya, 2017

2018 ◽  
Vol 11 (8) ◽  
pp. 1094-1101 ◽  
Author(s):  
Emily K. Kathambi ◽  
John A. Van Leeuwen ◽  
George K. Gitau ◽  
Shawn L. McKenna
Keyword(s):  
Dairy Farms ◽  
Cross Sectional Study ◽  
Sectional Study ◽  
Cross Sectional ◽  
Smallholder Dairy ◽  
Smallholder Dairy Farms

scholarly journals Prevalence of Repeat Breeding Syndrome in Dairy Cattle in Selected Regions of Kenya

2021 ◽  
Vol 10 (2) ◽  
pp. 114-118
Keyword(s):  
Dairy Cattle ◽  
Farming Systems ◽  
Dairy Farms ◽  
Cross Sectional Study ◽  
Cross Sectional ◽  
Study Objective ◽  
Farm Level ◽  
Smallholder Dairy ◽  
Extensive Farming ◽  
Smallholder Dairy Farms

The optimum production in dairy cows aims at getting a calf per cow per year. This, however, is limited by repeat breeding syndrome (RBS), which has multiple etiologies that cause either fertilization failure or early embryonic death. This study objective was to determine the prevalence of repeat breeding syndrome in dairy cattle within the selected regions of Kenya. A cross-sectional study design was carried out in 205 smallholder dairy farms in Makueni, Kakamega and Nandi counties. A total of 553 cows/heifers were recruited and examined per rectal to determine their reproductive status. Information on the breeding history of the cow and heifer was acquired at the farm. The results revealed that cross bred cattle were most affected by RBS at 38.9% followed by Jersey, Guernsey Ayrshire and least in Frisians at 21.1, 16.7, 25 and 14%, respectively. The overall animal level prevalence of RBS in cattle in the three counties was at 18.4%, while the overall farm-level prevalence was 58.3%. However, per county prevalence’s were different with animal level prevalence at 31.9, 20.9 and 12.5% in Makueni, Kakamega and Nandi, respectively. The farm-level prevalence’s at the counties were 75.4, 58.3 and 48.4% in Makueni, Kakamega and Nandi counties, respectively. Cattle kept in the zero-grazing/intensive system had the highest level of RBS at 30.1% compared to semi-intensive and extensive farming systems. The prevalence of RBS was also higher in multipara at 76% in comparison to primipara cows. Finally cows over four years which were in third or more parities had the highest prevalence of RBS, accounting for 65%) of the cases. In conclusion, the prevalence of RBS is significantly high in the Kenyan smallholder dairy farms. Further research should be undertaken to identify risk factors and appropriate intervention approaches for RBS to enhance its management.

scholarly journals Understanding variability in greenhouse gas emission estimates of smallholder dairy farms in Indonesia

2021 ◽  
Author(s):  
Titis Apdini ◽  
Windi Al Zahra ◽  
Simon J. Oosting ◽  
Imke J. M. de Boer ◽  
Marion de Vries ◽  
...  
Keyword(s):  
Greenhouse Gas ◽  
Rainy Season ◽  
Greenhouse Gas Emission ◽  
Dairy Farms ◽  
Dry Season ◽  
Enteric Fermentation ◽  
Tropical Regions ◽  
Population Mean ◽  
Smallholder Dairy ◽  
Smallholder Dairy Farms

Abstract Purpose Life cycle assessment studies on smallholder farms in tropical regions generally use data that is collected at one moment in time, which could hamper assessment of the exact situation. We assessed seasonal differences in greenhouse gas emissions (GHGEs) from Indonesian dairy farms by means of longitudinal observations and evaluated the implications of number of farm visits on the variance of the estimated GHGE per kg milk (GHGEI) for a single farm, and the population mean. Methods An LCA study was done on 32 smallholder dairy farms in the Lembang district area, West Java, Indonesia. Farm visits (FVs) were performed every 2 months throughout 1 year: FV1–FV3 (rainy season) and FV4–FV6 (dry season). GHGEs were assessed for all processes up to the farm-gate, including upstream processes (production and transportation of feed, fertiliser, fuel and electricity) and on-farm processes (keeping animals, manure management and forage cultivation). We compared means of GHGE per unit of fat-and-protein-corrected milk (FPCM) produced in the rainy and the dry season. We evaluated the implication of number of farm visits on the variance of the estimated GHGEI, and on the variance of GHGE from different processes. Results and discussion GHGEI was higher in the rainy (1.32 kg CO2-eq kg−1 FPCM) than in the dry (0.91 kg CO2-eq kg−1 FPCM) season (P < 0.05). The between farm variance was 0.025 kg CO2-eq kg−1 FPCM in both seasons. The within farm variance in the estimate for the single farm mean decreased from 0.69 (1 visit) to 0.027 (26 visits) kg CO2-eq kg−1 FPCM (rainy season), and from 0.32 to 0.012 kg CO2-eq kg−1 FPCM (dry season). The within farm variance in the estimate for the population mean was 0.02 (rainy) and 0.01 (dry) kg CO2-eq kg−1 FPCM (1 visit), and decreased with an increase in farm visits. Forage cultivation was the main source of between farm variance, enteric fermentation the main source of within farm variance. Conclusions The estimated GHGEI was significantly higher in the rainy than in the dry season. The main contribution to variability in GHGEI is due to variation between observations from visits to the same farm. This source of variability can be reduced by increasing the number of visits per farm. Estimates for variation within and between farms enable a more informed decision about the data collection procedure.

Forage availability and its quality in the dry season on smallholder dairy farms in Tanzania

2008 ◽  
Vol 58 (4) ◽  
pp. 196-204 ◽  
Author(s):  
E. J. Mtengeti ◽  
E. C. J. H. Phiri ◽  
N. A. Urio ◽  
D. G. Mhando ◽  
Z. Mvena ◽  
...  
Keyword(s):  
Dairy Farms ◽  
Dry Season ◽  
Forage Availability ◽  
Smallholder Dairy ◽  
Smallholder Dairy Farms
Sign in / Sign up

Export Citation Format

Share Document