Factors influencing intensification of dairy production systems in Ethiopia

2018 ◽  
Vol 47 (2) ◽  
pp. 133-140 ◽  
Author(s):  
Habtamu L Didanna ◽  
Ashenafi Mengistu Wossen ◽  
Tadesse Kuma Worako ◽  
Berhanu Kuma Shano
Keyword(s):  
Dairy Cows ◽  
Management Practices ◽  
Production Systems ◽  
Herd Size ◽  
Sub Saharan Africa ◽  
Manure Management ◽  
Dairy Production ◽  
Binary Logistic Regression Model ◽  
Forage Crops ◽  
Smallholder Dairy

Little is known of how dairy intensification driven by socioeconomic issues and dairy development efforts works as well as the challenges of changing production systems in developing countries, particularly in sub-Saharan Africa. A study was carried out to analyze factors determining intensification of dairy production systems and the present status of market-oriented smallholder dairy operations in Ethiopia. Data were collected through face-to-face interviews with 200 dairy farmers. The results revealed that 77% of respondents reared improved/crossbred dairy cows, 53.5% acquired good manure management besides crossbreeding, and 44% of the sampled rural households were involved in cultivating improved forage crops and crossbreeding practices. The binary logistic regression model output showed that herd size, farmland size, dairy training, and cooperative membership had significant effects on cultivating improved forages. Dairy production system, dairying experience, and herd size were significantly associated with rearing only crossbred dairy cows. Farmland size, dairy system, and awareness of manure handling were significantly associated with practicing good manure management. Further analysis of the extent of intensification indicated that mean daily milk yield per cow and household milk market share were significantly related to crossbreeding and manure management practices in combination. Thus, production systems–based dairy breeding and manure management, related input supply, and alternative formal marketing options are the key attributes of the intensification and improved productivity of smallholder dairy production that need to be considered while designing policy and intervention.

scholarly journals Context Specificity and Time Dependency in Classifying Sub-Saharan Africa Dairy Cattle Farmers for Targeted Extension Farm Advice: The Case of Uganda

Agriculture ◽  
2021 ◽  
Vol 11 (9) ◽  
pp. 836
Author(s):  
Elizabeth Ahikiriza ◽  
Joshua Wesana ◽  
Xavier Gellynck ◽  
Guido Van Huylenbroeck ◽  
Ludwig Lauwers
Keyword(s):  
Milk Production ◽  
Large Scale ◽  
Management Practices ◽  
Production Systems ◽  
Sub Saharan Africa ◽  
Small Scale ◽  
Dairy Production ◽  
Extension Services ◽  
Sub Saharan ◽  
Productive Systems

Despite the huge potential for milk production, interventions to improve productivity in sub-Saharan Africa (SSA) are barely based on specified farm classifications. This study aimed to develop robust and context-specific farm typologies to guide content of extension farm advice/services in Uganda. From a sample of 482 dairy farmers, we collected data on farmer socio-demographics, farm management practices, ownership of farm tools and facilities, willingness to pay for extension services, milk production, and marketing. Farm typologies were obtained based on principal component and cluster analyses. Thereby, of the three dairy production systems that emerged, small-scale, largely subsistence yet extensive and low productive farms were more prominent (82.6%). Farms that were classified as large-scale, less commercialized yet extensive with modest productive systems were more than the medium-scale commercial farms with intensive and highly productive systems. However, the later were considered to potentially transform dairy farming in Uganda. It was also predicted that the validity of our farm classification may persist until half of the farms have moved between clusters. The study gives new insights on dairy production systems in Uganda, which can be used to organize more targeted research on farmers’ extension needs for facilitating delivery of relevant and effective extension services and designing appropriate extension policies.

Characterisation of smallholder dairy production systems using animal welfare and milk quality

2012 ◽  
Vol 44 (7) ◽  
pp. 1429-1435 ◽  
Author(s):  
Bettie S. Kawonga ◽  
Mizeck G. G. Chagunda ◽  
Timothy N. Gondwe ◽  
Sera R. Gondwe ◽  
James W. Banda
Keyword(s):  
Animal Welfare ◽  
Production Systems ◽  
Milk Quality ◽  
Dairy Production ◽  
Smallholder Dairy ◽  
Smallholder Dairy Production

scholarly journals Antagonism in the carbon footprint between beef and dairy production systems

2015 ◽  
Vol 44 (5) ◽  
pp. 17-20
Author(s):  
MM Scholtz ◽  
J Du Toit ◽  
FWC Neser
Keyword(s):  
Dairy Cows ◽  
Carbon Footprint ◽  
Production Systems ◽  
Beef Cows ◽  
Dairy Farming ◽  
Feed Water ◽  
Dairy Production ◽  
Pasture Production ◽  
Total Mixed Ration ◽  
Cow Calf

Primary beef cattle farming in South Africa is largely extensive, whereas dairy farming is based on both total mixed ration and pasture production systems. Under natural rangeland conditions, decomposition of manure is aerobic, which produces carbon dioxide (CO2), part of which is absorbed by the regrowth of vegetation rather than released into the atmosphere, and water (H2O) as end products. Thus the cow releases methane (CH4) and the manure CO2. This is in contrast to intensive cow-calf systems in large parts of Europe and North America, where large quantities of manure are stockpiled and undergo anaerobic decomposition and produce CH4. Thus both the cow and the manure release CH4, which result in a higher carbon footprint than the extensive cow-calf systems. In dairy farming, increasing cow efficiency through intensive feeding (same kg milk output by fewer animals) can reduce farm CH4 production by up to 15%. In addition, when differences in productivity are accounted for, pasture systems require more resources (land, feed, water, etc.) per unit of milk produced and the carbon footprint is greater than that of intensive systems. This raises the question as to why the carbon footprint of intensive dairy cow production systems is less, but the carbon footprint of intensive beef cow-calf production systems is higher. The explanation lies in the differences in production levels. In the case of beef cows the weight of the intensive cows will be ± 30% higher than that of the extensive cows, and the weaning weight of their calves will also differ by ± 30%. In the case of dairy cows the weight of the intensive cows will be ± 20% higher, but their milk production will be ± 60% higher. The higher increase in production (milk) of intensive dairy cows, compared to the increase in production (calf weight) of intensive beef cows, explains the antagonism in the carbon footprint between different beef and dairy production systems. Unfortunately, carbon sequestration estimates have been neglected and thus the quantitative effects of these differences are not known.Keywords: Cow-calf production, methane, pasture production, production levels, total mixed ration

Blueprints for Tropical Dairy Farming

2017 ◽  
Author(s):  
John Moran ◽  
Philip Chamberlain
Keyword(s):  
Developing Countries ◽  
Best Management Practices ◽  
Large Scale ◽  
Management Practices ◽  
Production Systems ◽  
Dairy Farming ◽  
Dairy Herds ◽  
Dairy Production ◽  
Wide Range ◽  
The Tropics

Blueprints for Tropical Dairy Farming provides insight into the logistics, infrastructure and management required for the development of small and large dairy farms in tropical developing countries. Farmers will learn how to improve the welfare, milk quality and productivity of their dairy herds. This book complements author John Moran’s five previous books on the principles of tropical dairy farming. The manual covers a wide range of topics related to ensuring the sustainability of dairy production systems in tropical developing countries, such as South and East Asia, Africa and Central America. It also provides guidelines for the best management practices of large-scale, more intensive dairy systems. While smallholder farms are the major suppliers of milk in the tropics, many larger farms are becoming established throughout the tropics to satisfy the increasing demands for fresh milk. Blueprints for Tropical Dairy Farming will be a valuable resource for farmers and stockpeople who want to improve the productive performance of their dairy herds, farm advisers who can assist farmers to achieve this aim, educators who develop training programs for farmers or who train dairy advisers in the basics of dairy production technology, and other stakeholders in tropical dairy production, such as local agribusiness, policy makers and research scientists. National and international agencies will learn new insights into the required long-term logistics for regional dairy development, while potential investors will acquire knowledge into intensive tropical dairy farming.

scholarly journals Risk factors associated with cows' lying time, stall and cows' own cleanliness in smallholder dairy farms in Kenya

2019 ◽  
Vol 12 (7) ◽  
pp. 1085-1092
Author(s):  
E. K. Kathambi ◽  
J. A. VanLeeuwen ◽  
G. K. Gitau ◽  
C. Kamunde
Keyword(s):  
Risk Factors ◽  
Management Practices ◽  
Production Systems ◽  
Cross Sectional Study ◽  
Cross Sectional ◽  
Farm Level ◽  
Logistic Regression Models ◽  
Factors Associated ◽  
The Mean ◽  
Smallholder Dairy

Background and Aim: The welfare of animals kept in livestock production systems has raised concerns around the world. Adult dairy cattle require adequate rest and spend approximately 12 h/day lying down. This cross-sectional study aimed to determine the stall factors and management practices affecting cows' lying time, stall cleanliness, and cows' cleanliness (udder and upper leg), in smallholder dairy cows in Meru County of Kenya. Materials and Methods: A total of 106 milking cows from 73 farms were assessed for daily lying time and cleanliness. Data loggers were used to record the lying time of cows for 3 days. Stall, udder, and upper leg cleanliness were assessed using a 5-score system: 1 (very clean) to 5 (very dirty). Management information was acquired using a questionnaire that was administered face-to-face to the farmers in their native Kimeru language. Univariable and multivariable linear and logistic regression models were fit to determine factors associated with cows' lying time and dichotomized stall and cows' own cleanliness, respectively. Results: The mean daily lying time was 10.9±2.2 h, and the mean stall cleanliness score was 2.4±1.0. The mean average cleanliness scores of the udder and upper legs were 1.9±0.7 and 2.5±1.1, respectively. Overall, 35% of the stalls were categorized as dirty (>2.5), whereas 13% and 47% of the cows had udder and leg cleanliness scores >2.5, respectively. From the final multivariable models (p<0.05), daily lying time increased by 1.0 h for cows older than 5.25 years versus younger cows. Conversely, lying time decreased by 1.0 h with stall cleanliness scores >2.5 and by 1.6 h with poorly positioned neck rails. In an interaction term, addition of new bedding at least once a day without removing stall manure at least once a day decreased the daily lying time of the cows by 1.5 h, whereas failure to add new bedding at least once a day but removing stall manure at least once a day decreased the lying time of the cows by 1.2 h. Farm-level risk factors for stall dirtiness (>2.5) included delayed cleaning of the alley (odds ratio [OR]=6.6, p=0.032), lack of bedding (OR=4.9, p=0.008), and standing idle and/or backward in the stall (OR=10.5, p=0.002). Stalls categorized as dirty (OR=2.9, p=0.041) and lack of bedding (OR=2.7, p=0.065) were cow- and farm-level risk factors for dirtiness of the udder (>2.5), respectively, whereas the stall being dirty (OR=2.3, p=0.043) was the only risk factor (cow level) for dirtiness of the upper legs (>2.5). Conclusion: It was recommended that farmers should pay attention to the specific factors identified regarding the stall design (e.g., neck rail position) and bedding/manure management that impact the cleanliness of cows and their lying time.

scholarly journals Typology of dairy production systems from West Parana State based on production indices and feed used

2016 ◽  
Vol 37 (3) ◽  
pp. 1565
Author(s):  
Marcelo Eduardo Neumann ◽  
Maximiliane Alavarse Zambom ◽  
Maichel Jhonattas Lange ◽  
Ferenc Istvan Bankuti ◽  
Deise Dalazen Castagnara ◽  
...  
Keyword(s):  
Management Practices ◽  
Production Systems ◽  
Principal Component ◽  
Hierarchical Cluster ◽  
Dairy Production ◽  
Structured Interviews ◽  
Explanatory Variables ◽  
Concentrate Supplementation ◽  
Feeding Management ◽  
Fermented Feed

The dairy industry is characterised by a wide diversity of production systems. In this diverse environment, some of the difficulties can be minimised through the grouping of production units through the study of typology. The objective was to characterise the systems of milk production from West Parana State by considering production rates, area, power, facilities, and marketing of milk. To this end, 735 semi-structured interviews with dairy farmers were performed by using a questionnaire for management practices and feed that is used on the farms. To obtain the explanatory variables used for principal component analysis (PCA) and hierarchical cluster analysis (HCA), a homogeneous division of 735 farmers in five groups was used. Ten per cent of producers were randomly selected for the performance of field visits to the properties, where a new questionnaire was applied with specific points regarding feeding management on the property, and feed was collected to determine its composition. The collected data were tabulated and feed was ranked based on the classification proposed by the NRC (2001). Analyses of feed were carried out in the Laboratory of Animal Nutrition of Unioeste. The West Parana State has five groups of dairy production systems. There is great variability in the fresh forages that are used, but maize silage is the main forage utilised for fermented feed, and concentrate supplementation is adopted by more than 60% of farms during both seasons. Changes in the levels of feed components are high among systems.

Productive and reproductive performance of crossbred and indigenous dairy cows at smallholdings in selected towns of Jimma Zone, Ethiopia

2021 ◽  
Vol 61 (1) ◽  
pp. 92
Author(s):  
Belay Duguma
Keyword(s):  
Dairy Cattle ◽  
Dairy Cows ◽  
Milk Yield ◽  
Reproductive Performance ◽  
Management Practices ◽  
Production Systems ◽  
Management Strategies ◽  
Factors Affecting ◽  
Jimma Zone ◽  
Improvement Programs

Context Evaluation of the performance of dairy cows kept in different production systems is essential for the development of appropriate breeding strategies. Aims To examine milk production and reproductive performance of crossbred (CB) and indigenous (I) dairy cows, farmers’ traits preference for CB and I breeding females, and factors affecting the performance of dairy cattle on smallholdings in selected towns of Jimma Zone, Ethiopia. Methods In total, 52 smallholder dairy cattle farmers were randomly sampled and data were collected through individual face-to-face interviews by using structured questionnaires. The traits studied were daily milk yield (DMY), lactation milk yield (LMY), lactation length (LL), age at first service (AFS), age at first calving (AFC), calving interval (CI), days open (DO), and number of service per conception (NSC), all being factors affecting performance of dairy cattle and farmers’ preferred dairy traits. Results On average, CB cows had significantly (P &lt; 0.05) higher DMY (6.0 ± 0.33 vs 1.8 ± 0.07 L/cow), LMY (1466.7 ± 1.13 vs 376.0 ± 21.02 L (L)), LL (8.1 ± 0.41 vs 6.9 ± 0.22 months), and lower AFS (2.69 ± 0.1 vs 3.3 ± 0.07 years), AFC (3.7 ± 0.13 vs 4.3 ± 0.07 years) and CI (21.2 ± 1.37 vs 29.8 ± 1.30 months) than did I cows. However, DO and NSC were not significantly (P &gt; 0.05) affected by genotype. In order of perceived importance, high milk yield (mean rank = 0.306), LL (0.292) and fertility (0.199) were farmers’ most preferred traits for CB breeding cows, and the corresponding preferred traits for I cows were high milk yield (0.253), adaptability (0.229) and LL (0.192). The most important factors perceived by farmers affecting the performance of dairy cattle were breed, nutrition, diseases, breeding and management practices Conclusions The findings of the study indicated that even though CB cows performed better, the performance of both breeds of dairy cows in the study area was found to be generally low due to delayed AFS, late AFC, long CI, shorter LL, low daily and LMY and high NSC. Implications The study highlighted that there is a potential for increasing the performance of dairy cows in the study area, through improved management strategies leading to shorter AFS, AFC, CI and lower NSC. Furthermore, future breed-improvement programs should take into consideration farmers’ trait preferences in design of sustainable improvement programs.

scholarly journals 121 The impact of changing consumer preferences on production and management practices at cow-calf level

2020 ◽  
Vol 98 (Supplement_3) ◽  
pp. 49-49
Author(s):  
Robbi H Pritchard
Keyword(s):  
Management Practices ◽  
Performance Metrics ◽  
Production Systems ◽  
Consumer Preferences ◽  
Well Being ◽  
Herd Size ◽  
Major Step ◽  
Cow Calf ◽  
Calving Season ◽  
The Impact

Abstract Changes in cow-calf operations and management need to be deliberate and focus on consumer preferences that are substantive and enduring. For the sake of argument these preference changes could include: 1) continued erosion of the image of the cattle industry; 2) growth in demand of high quality grade beef, likely branded, and available at an affordable price; 3) production systems that yield improvements in cattle health, have a lesser environmental impact, and demonstrate prudent animal care and well-being; 4) Specification systems that may or may not include stipulations such as grass fed or non-implanted. At the ranch level there will be continued pressure to pursue rapid, efficient growth, marbling, structural soundness, and immunocompetence via genetic selection. A major step to reduce health problems is to reduce co-mingling. To achieve this goal breeding programs will change to improve the genetic and phenotypic uniformity and possibly the heterosis of the calf crop on each ranch. The National calving season needs to be more uniformly distributed throughout the year. New, more relevant cattle performance metrics will be developed. Calves that fit a branded production stream will have more value. Production streams that require Verified processes will be inequitably distributed across herd size because of associated costs, forcing smaller herds to either coop, vertically integrate, or accept generic cattle prices. Because of the diversity of environments and corresponding compatible bio-types of cows, identifying the profitable combination of specific branded systems with the genetics, calving season, labor, resource management and nutrition program of the ranch is very complicated. It will be increasingly necessary to put incremental response assessments in the context of the greater production-product system. Successful adaptors will place a much greater reliance on strong technical support in the areas of genetics, nutrition, growth, animal handling, documentation, and branded production streams.

Sign in / Sign up

Export Citation Format

Share Document