scholarly journals A Longitudinal Study of Cattle Productivity in Intensive Dairy Farms in Central Ethiopia

2021 ◽  
Vol 8 ◽  
Author(s):  
Rea Tschopp ◽  
Gizachew Gemechu ◽  
James L. N. Wood
Keyword(s):  
Animal Movement ◽  
Addis Ababa ◽  
Dairy Farms ◽  
Herd Size ◽  
Time Interval ◽  
Central Ethiopia ◽  
Dairy Animals ◽  
Optimal Productivity ◽  
Animal Performances ◽  
Large Farms

Ethiopia is witnessing an emergence of intensive urban dairy farming. The aims of this study were to capture cattle productivity parameters in selected intensive dairy farms in and around Addis Ababa (Central Ethiopia). The study is a pre-requisite and baseline for further economic analysis of diseases such as bovine tuberculosis (BTB) and to assess some of the current challenges faced by farm owners for optimal animal performances. Hence, a 3-year longitudinal observational study was conducted for the first time in Ethiopia, in 24 dairy farms with intensive husbandry, including a total of 1,705 dairy animals. Herd characteristics, animal movement, and productivity parameters (fertility, morbidity, mortality) were recorded in a herd-book. Whereas, half the farms saw their animals increase in number over the 3 years, 37.5% (mainly large farms) saw their herd size decrease. Offtakes accounted for 76.6% of all animal exits. One hundred and ninety (11.1%) animals died of natural causes. Highest mortality was observed in young stock (13.9%). Overall, diseases were the leading cause for death (57.5%). The majority of calves (69%) that died, did so within the first week of life. Mean calving interval (CI) was 483.2 days. Successful conception after artificial insemination (AI) was 66.1% with Addis Ababa and smaller farms faring worst. Mean time interval from calving to first service was 152 days. Date of birth to first service was 592.2 days and date of birth to first calving was 794.7 days. In conclusion, the study showed sub-optimal productivity performances in intensive dairy cattle and highlighted some of the current gaps and challenges in urban dairy productivity.

scholarly journals The variable prevalence of bovine tuberculosis among dairy herds in Central Ethiopia provides opportunities for targeted intervention

PLoS ONE ◽  
2021 ◽  
Vol 16 (7) ◽  
pp. e0254091
Author(s):  
Gizat Almaw ◽  
Andrew J. K. Conlan ◽  
Gobena Ameni ◽  
Balako Gumi ◽  
Alemseged Alemu ◽  
...  
Keyword(s):  
Risk Factors ◽  
Bovine Tuberculosis ◽  
Significant Risk ◽  
Dairy Farms ◽  
Herd Size ◽  
P Value ◽  
Dairy Herds ◽  
Individual Animal ◽  
Central Ethiopia ◽  
High Prevalence

Bovine tuberculosis (bTB) is an important disease for dairy productivity, as well as having the potential for zoonotic transmission. Previous prevalence studies of bTB in the dairy sector in central Ethiopia have suggested high prevalence, however, they have been limited to relatively small scale surveys, raising concerns about their representativeness. Here we carried out a cross sectional one-stage cluster sampling survey taking the dairy herd as a cluster to estimate the prevalence of bTB in dairy farms in six areas of central Ethiopia. The survey, which to date is by far the largest in the area in terms of the number of dairy farms, study areas and risk factors explored, took place from March 2016 to May 2017. This study combined tuberculin skin testing and the collection of additional herd and animal level data by questionnaire to identify potential risk factors contributing to bTB transmission. We applied the single intradermal cervical comparative tuberculin (SICCT) test using >4mm cut-off for considering an individual animal as positive for bTB; at least one reactor animal was required for a herd to be considered bTB positive. Two hundred ninety-nine dairy herds in the six study areas were randomly selected, from which 5,675 cattle were tested. The overall prevalence of bTB after standardisation for herd-size in the population was 54.4% (95% CI 48.7–60%) at the herd level, and it was 24.5% (95% CI 23.3–25.8) at the individual animal level. A Generalized Linear Mixed Model (GLMM) with herd and area as random effect was used to explore risk factors association with bTB status. We found that herd size, age, bTB history at farm, and breed were significant risk factors for animals to be SICCT positive. Animals from large herds had 8.3 times the odds of being tuberculin reactor (OR: 8.3, p-value:0.008) as compared to animals from small herds. The effect of age was strongest for animals 8–10 years of age (the oldest category) having 8.9 times the odds of being tuberculin reactors (OR: 8.9, p-value:<0.001) compared to the youngest category. The other identified significant risk factors were bTB history at farm (OR: 5.2, p-value:0.003) and cattle breed (OR: 2.5, p-value: 0.032). Our study demonstrates a high prevalence of bTB in central Ethiopia but with a large variation in within-herd prevalence between herds, findings that lays an important foundation for the future development of control strategies.

An Estimation of Total Factor Productivity and its Determinants among Peri-Urban Dairy Farms of Odisha

2020 ◽  
pp. 467-471
Keyword(s):  
Total Factor Productivity ◽  
Coastal Plain ◽  
Dairy Farms ◽  
Herd Size ◽  
Factor Productivity ◽  
Cross Sectional ◽  
Crossbred Cows ◽  
Large Farms ◽  
Productivity Ratio ◽  
Crossbred Cow

The study was conducted in East and South-eastern coastal plain zone of Odisha. Total factor productivity (TFP) in milk production and its determinants were estimated using cross-sectional data obtained from 120 sampled peri-urban dairy farms. The study revealed that TFP was highest for large farms (0.2801) and crossbred cows (0.1328) which meant increase in scale of production and adoption of crossbred cow would be helpful increasing productivity of dairy farms. Herd size and productivity ratio were found to be significantly affecting TFP. An increasing herd size by adopting a greater number of crossbred cows and a proper balanced nutrition would ultimately enhance the productivity of peri-urban dairy farms in Odisha.

scholarly journals Chemical composition and mineral profile of concentrate feeds from dairy farms of Varanasi, India

2018 ◽  
Author(s):  
Satya Prakash Yadav ◽  
Vinod Kumar Paswan ◽  
Prity Singh ◽  
Basant Kumar Bhinchhar ◽  
Pankaj Kumar Gupta
Keyword(s):  
Dairy Farms ◽  
Nutritional Intervention ◽  
Major Protein ◽  
Minimum Concentration ◽  
Three Samples ◽  
Mineral Profile ◽  
Linseed Cake ◽  
Dairy Animals ◽  
Maize Grain ◽  
Cattle Feeds

One hundred twenty-three samples of 13 different concentrate feeds were collected from 45 dairy farms distributed all over the Varanasi municipal Corporation and these concentrate feeds were analyzed for proximate composition, fibre fractions, macro and micro mineral profilesto explore the suitable nutritional intervention for optimum production of dairy animals. It was observed that, mustard cake and linseed cakes were the major protein source for dairy farms. Linseed cake had comparatively high protein content than mustard cake (30.95 vs. 27.58%). Samples of compounded cattle feeds collected from study area had maximum CF (13.95%) and AIA (2.58%) content. Rice Bran had the maximum NDF and hemicelluloses while mustard cake contained highest ADF, cellulose and lignin levels. Wheat bran contained least NDF and hemicelluloses while maize grain contained least ADF, cellulose and lignin among all the concentrates. Maize grain was found to contain minimum concentration of several macro and micro minerals like Mg, Na, K, Cu, Zn, Mn and Co. Among all the concentrate feeds, compounded cattle feeds had maximum concentration of major minerals viz., Ca, P, Mg and Na while K and S and micro minerals like Cu, Zn, Mn, Fe, Co, Mo and Se were in optimum concentration in it. This is attributed to additional supplementation of these minerals while formulating the compounded feeds. Different, concentrate feed contained varying amount of one or the other macro and micro mineral and therefore, individual concentrate ingredient was always deficient in some minerals which always demands additional supplementation of these minerals even when concentrate ration is fed to livestock.

scholarly journals Technologies used at advanced dairy farms for optimizing the performance of dairy animals: A review

2021 ◽  
Vol 19 (4) ◽  
pp. e05R01-e05R01
Author(s):  
Amit K. Singh ◽  
Keyword(s):  
Dairy Farms ◽  
Substantial Improvement ◽  
Health Care Facilities ◽  
Livestock Farming ◽  
Prime Concern ◽  
World Demand ◽  
Labour Requirement ◽  
Dairy Animals ◽  
Size Of Animals ◽  
The Cost

Superior germplasm, better nutrition strategies, health care facilities and improved dairy husbandry practices have boosted milk yield and its quality with a rapid rate. Per cow productivity has risen up sharply with considerable increase in the population of dairy animals. Recent era has witnessed the extension of large dairy farms around the world. Demand for high quality and increased quantity of milk is of the prime concern for all the dairy farms. With an increase in the size of animals in a farm, the labour requirement also rises up. Availability of skilled labour at low wage rate is becoming difficult. In last couple of decades, the cost of microprocessors has been reduced to an affordable level. The economic availability of engineered processors, artificial intelligence, improved data statistics combined with expert suggestions has created a revolution in livestock farming. Advanced engineered devices have become alternative to reduce high labour cost. This review focuses on latest knowledge and emerging developments in animal’s welfare focused biomarker activities and activity-based welfare assessment like oestrus, lameness and others. Use of enhanced sensors and data technologies with expert based solutions is anticipated to bring out a substantial improvement in existing dairy farming practices.

scholarly journals Assessment of Influential Factors for Scours Associated with Cryptosporidium sp., Rotavirus and Coronavirus in Calves from Argentinean Dairy Farms

Animals ◽  
2021 ◽  
Vol 11 (9) ◽  
pp. 2652
Author(s):  
Emiliano Bertoni ◽  
Adrián A. Barragán ◽  
Marina Bok ◽  
Celina Vega ◽  
Marcela Martínez ◽  
...  
Keyword(s):  
Management Practices ◽  
Dairy Farms ◽  
Herd Size ◽  
Influential Factors ◽  
Dairy Calves ◽  
Farm Size ◽  
Common Disease ◽  
Contributing Factors ◽  
Fecal Samples ◽  
Logistic Regression Models

Scours is the most common disease in dairy calves, and it is a multifactorial syndrome complex. Cryptosporidium sp. (C. sp.), rotavirus group A (RVA), and bovine coronavirus (BCoV) are the three main pathogens associated with scours. The objective of this study was to identify potential factors associated with scours, C. sp., RVA, and BCoV infections in preweaned dairy calves from Lerma Valley in Salta Province, Argentina. A total of 488 preweaned calves from 19 dairy farms located in the Lerma Valley were enrolled in this observational study. One fecal sample was collected from each calf between one week and two months of age for assessment of C. sp., RVA, and BCoV infection status. Cryptosporidium sp. oocysts and RVA and BCoV antigens in fecal samples were assessed using microscopic observation and indirect enzyme-linked immune sorbent assay (iELISA), respectively. A voluntary questionnaire was developed and used to collect data regarding management practices from the participants’ farms. The data were analyzed using multivariable logistic regression models. Scours incidence was 35.4%, and a greater proportion of calves younger than 20 days were affected. Of the fecal samples, 18% and 9.5% tested were positives for C. sp. and RVA, respectively, while BCoV was detected only in two calves. Furthermore, 84.2% and 63.1% of the farms tested positive for Cryptosporidium sp. and RVA, respectively. In addition, the following variables were associated with higher odds of having scours: (1) herd size (>300 milking cows; OR = 1.7), (2) calf age (<20 days of age; OR = 2.2), (3) RVA and C. sp. test (positive test; RVA OR = 2.6; C. sp. OR = 3), calf feeding practices (feeding milk replacer; OR = 1.81), and newborn calf management practices (calf moved from maternity pen <6 h after calving; OR = 1.7). Concerning RVA infection, calves less than 20 days of age (OR = 2.6) had a higher chance of testing positive for RVA, while calves that remained in the calving pen for less than 6 h after calving had a lower chance (OR = 0.3). On the other hand, for C. sp. infection, large farm size (>300 milking cows; OR = 1.2) and young calf age (<20 days of age; OR = 4.4) indicated a higher chance of testing positive for C. sp., while calves belonging to farms that fed frozen colostrum (OR = 0.2) had a lower chance of becoming infected with C. sp. The result of this study indicated that scours is a prevalent disease in farms of the Lerma Valley, Salta, Argentina, and that RVA and C. sp. infections, along with specific farm management practices, might be important contributing factors that could increase the chance of NCS in dairy farms.

Aggregate Efficiency Dynamics in Lithuanian Dairy Farms

2021 ◽  
Vol 70 (4) ◽  
pp. 251-264
Author(s):  
Tomas Balezentis ◽  
Giannis Karagiannis
Keyword(s):  
Decision Making ◽  
Structural Changes ◽  
Dairy Farms ◽  
Family Farms ◽  
Efficiency Change ◽  
Empirical Application ◽  
Level Data ◽  
Covariance Term ◽  
Large Farms ◽  
Decision Making Units

In this paper, we attempt to identify the major groups of decision making units (dairy farms) contributing to the aggregate efficiency change. We also suggest identifying influential peers in order to gain more insights into possible development strategies within a sector. The empirical application focuses on specialist dairy farms in Lithuania. The farm-level data cover the period 2004-2016. The results indicate the presence of structural changes and resulting shifts in the aggregate efficiency. Based on the results of decomposition of the covariance term and identification of the influential peers, two models can be followed by Lithuanian dairy farms, namely “pure” family farms with lower operational scale and large farms involving hired labour.

scholarly journals Fertility parameters in German dairy herds: Associations with milk yield and herd size

2019 ◽  
Vol 64 (No. 11) ◽  
pp. 459-464
Author(s):  
Jörn Rethmeier ◽  
Michael Wenzlau ◽  
Martin Wagner ◽  
Steffi Wiedemann ◽  
Lisa Bachmann
Keyword(s):  
Pregnancy Rate ◽  
Milk Yield ◽  
Reproductive Performance ◽  
Dairy Farms ◽  
Herd Size ◽  
Pregnancy Rates ◽  
Conception Rate ◽  
Service Rate ◽  
Dairy Herds ◽  
Key Factor

Fertility in dairy cows has decreased over the last fifty years while milk production per cow has increased. Furthermore, dairy herds become larger resulting in fewer employees per cow, which might also influence reproductive performance. To elucidate the situation in Germany, selected parameters (conception rate, service rate, pregnancy rate, days to first insemination and days open) were studied using data on 148 herds. For statistical analysis the herds were categorized concerning milk yield: (1) &lt; 30 kg, (2) 30‒35 kg, and (3) &gt; 35 kg/cow/day as well as concerning herd size: (1) &lt; 200, (2) 200‒400, (3) 400‒1000 and (4) &gt; 1000 milking cows. There was no difference in conception rate among herds. That means on dairy farms of larger size or with high milk yield the chance of an inseminated cow to become pregnant is the same as in small herds or in herds with low milk yield. Small herds (&lt; 200 cows) had lower pregnancy rates than larger herds (200–400 cows). The pregnancy rate in herds with different milk yield was not statistically different. Though there was a trend that dairy farms with higher milk yield (&gt; 30 kg) had higher pregnancy rates. The statistical differences and trends of pregnancy rates are due to higher service rate in larger herds as well as in herds with high milk yield. Therefore, service rate is the key factor for high reproductive performance on dairy farms. Poor fertility is not associated with high milk yield on herd basis or large herd size but may represent inappropriate farm management.

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