Management, productivity and livelihood effects on Kenyan smallholder dairy farms from interventions addressing animal health and nutrition and milk quality

2011 ◽  
Vol 44 (2) ◽  
pp. 231-238 ◽  
Author(s):  
John A. VanLeeuwen ◽  
Teresa Mellish ◽  
Colleen Walton ◽  
Ayub Kaniaru ◽  
Regina Gitau ◽  
...  
Author(s):  
R.H. Mdegela ◽  
R. Ryoba ◽  
E.D. Karimuribo ◽  
E.J. Phiri ◽  
T. Loken ◽  
...  

A cross sectional study was conducted during October and November 2006 on 69 smallholder dairy farms with lactating cows in Mvomero and Njombe districts Tanzania, to determine the prevalence of mastitis and to assess the milk quality on the study farms. Clinical mastitis was investigated using clinical changes of udder and milk at animal level. Cow-side California Mastitis Test (CMT) and microbiological cultures were used to assess subclinical mastitis at quarter level. Milk quality was determined on bulk milk samples at herd level using alcohol and acidity tests, butter fat content, total solids, ash content as well as Delvotest® for antimicrobial residues. Overall prevalence of clinical mastitis at herd level in both districts was 21.7 % (n = 69). Based on CMT, prevalence of subclinical mastitis at animal level was 51.6 % (n = 91). Prevalence of bacterial isolates at animal level was 35.2 % (n = 91) while for fungal it was 16.7 % (n = 90). Based on CMT results, prevalence of subclinical mastitis at quarter level was 30 % (n = 353), while for bacteria and fungi it was 16 % and 6 % respectively. Contamination of milk with antimicrobial residues was 4.5 % (n =67). The milk quality parameters for most of the milk samples were within acceptable levels. Findings in this study have demonstrated high prevalence of subclinical mastitis that may contribute to low productivity of dairy cattle in both districts. About 20 % of CMT subclinical cases had no involvement of microbial pathogens that suggested the need for minimal interventions with antimicrobial agents. These findings call for use of udder disinfectants and improved milking hygiene as intervention strategies to control mastitis on the smallholder dairy farms in Tanzania.


2020 ◽  
Vol 10 (1) ◽  
pp. 1792033
Author(s):  
Garima Sharma ◽  
Florence Mutua ◽  
Ram Pratim Deka ◽  
Rajeshwari Shome ◽  
Samiran Bandyopadhyay ◽  
...  

Author(s):  
Titis Apdini ◽  
Windi Al Zahra ◽  
Simon J. Oosting ◽  
Imke J. M. de Boer ◽  
Marion de Vries ◽  
...  

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.


2015 ◽  
Vol 98 (7) ◽  
pp. 4990-4998 ◽  
Author(s):  
S. Buaban ◽  
M. Duangjinda ◽  
M. Suzuki ◽  
Y. Masuda ◽  
J. Sanpote ◽  
...  

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 ◽  
...  

2013 ◽  
Vol 155 (2-3) ◽  
pp. 197-204 ◽  
Author(s):  
R. Pilachai ◽  
J.Th. Schonewille ◽  
C. Thamrongyoswittayakul ◽  
S. Aiumlamai ◽  
C. Wachirapakorn ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document