Genetic relationships of fertility traits with test-day milk yield and fat-to-protein ratio in tropical smallholder dairy farms

2015 ◽  
Vol 87 (5) ◽  
pp. 627-637 ◽  
Author(s):  
Sayan Buaban ◽  
Monchai Duangjinda ◽  
Mitsuyoshi Suzuki ◽  
Yutaka Masuda ◽  
Jureeratn Sanpote ◽  
...  
Keyword(s):  
Milk Yield ◽  
Genetic Relationships ◽  
Dairy Farms ◽  
Protein Ratio ◽  
Smallholder Dairy ◽  
Fertility Traits ◽  
Smallholder Dairy Farms

scholarly journals Assessment of Performance and Some Welfare Indicators of Cows in Vietnamese Smallholder Dairy Farms

Animals ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 674
Author(s):  
Nguyen N. Bang ◽  
Nguyen V. Chanh ◽  
Nguyen X. Trach ◽  
Duong N. Khang ◽  
Ben J. Hayes ◽  
...  
Keyword(s):  
Heat Stress ◽  
Milk Yield ◽  
Body Condition Score ◽  
Dairy Farms ◽  
Point Scale ◽  
The South ◽  
Lactating Cows ◽  
The North ◽  
Smallholder Dairy ◽  
Smallholder Dairy Farms

Smallholder dairy farms (SDFs) are distributed widely across lowland and highland regions in Vietnam, but data on the productivity and welfare status of these cows remains limited. This cross-sectional study was conducted to describe and compare the productivity and welfare status of SDF cows across contrasting regions. It was conducted in autumn 2017 on 32 SDFs randomly selected from four typical but contrasting dairy regions (eight SDFs per region); a south lowland, a south highland, a north lowland, and a north highland region. Each farm was visited over a 24-h period (an afternoon followed by a morning milking and adjacent husbandry activities) to collect data of individual lactating cows (n = 345) and dry cows (n = 123), which included: milk yield and concentrations, body weight (BW), body condition score (BCS, 5-point scale, 5 = very fat), inseminations per conception, and level of heat stress experienced (panting score, 4.5-point scale, 0 = no stress). The high level of heat stress (96% of lactating cows were moderate to highly heat-stressed in the afternoon), low energy corrected milk yield (15.7 kg/cow/d), low percentage of lactating cows (37.3% herd), low BW (498 and 521 kg in lactating and dry cows, respectively), and low BCS of lactating cows (2.8) were the most important productivity and welfare concerns determined and these were most serious in the south lowland. By contrast, cows in the north lowland, a relatively hot but new dairying region, performed similarly to those in the south highland; a region historically considered to be one of the most suitable for dairy cows in Vietnam due to its cool environment. This indicates the potential to mitigate heat stress through new husbandry strategies. Cows in the north highland had the highest BW (535 and 569 kg in lactating and dry cows, respectively) and the highest energy corrected milk yield (19.2 kg/cow/d). Cows in all regions were heat-stressed during the daytime, although less so in the highlands compared to the lowlands. Opportunities for research into improving the productivity and welfare of Vietnamese SDF cows are discussed.

scholarly journals Evaluation of Dairy Cattle Productivity in Smallholder Farms in Nyeri County, Kenya

2020 ◽  
Vol 2 (1) ◽  
Author(s):  
Peter Aweer Duot Ajak ◽  
Charles K. Gachuiri ◽  
Margaret M. M. Wanyoike
Keyword(s):  
Dairy Cattle ◽  
Milk Yield ◽  
Value Chain ◽  
Dairy Farms ◽  
Breeding Systems ◽  
Cattle Production ◽  
Feed Resources ◽  
The Mean ◽  
Smallholder Dairy ◽  
Smallholder Dairy Farms

Dairy cattle production contributes approximately 4.5% of the Kenyan National Gross Domestic Product, creates jobs along the value chain and plays a key role in food security. However, average milk yield per cow is still low under smallholder dairy production system despite concerted efforts to improve productivity. The purpose of this study was to evaluate the productivity of smallholder dairy farms in 2 sub-counties of Nyeri County. A semi structured questionnaire was administered to collect data on feed resources and feeding systems, breeds and breeding systems, calf management, age at first service (AFS), age at first calving (AFC), calving interval (CI), milk yield (MY) and lactation length (LL) in smallholder dairy farms. Data was analysed using Statistical Package for Social Sciences (SPSS). The dominant feed resources and feeding system were roughages (mostly Napier grass), concentrates and mineral supplements (87.2%) and stall feeding (74.2%). Majority of the farmers kept Friesians (82.2%) with (94.5%) using artificial insemination. Most of the farmers (83.5%) fed 2-4 litres of colostrum to the calves and the method of feeding was majorly bucket feeding (93.0%). High proportion of farmers (97.7%) fed the colostrum from 0-6 hours after calving and (59.6%) weaned calves at 3 months. The AFS was mainly 18-20 months and above, while the mean AFC, CI, and LL were 28.7±2.84, 15.2±5.11 and 10.0±4.90 months, respectively. The mean milk yield was 10.7±5.85 litres/cow/day. The main challenges to dairy cattle production were feed shortages (30.6%), low farmgate milk prices (28.3%) and high cost of concentrate feeds (17.8%). It was concluded that performance of dairy cattle in the study area was poor attributed mostly to feed shortages and low milk prices. To improve productivity, feed availability and cost together with farmgate price of milk should be addressed.

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

scholarly journals Impact Of Genotypes And Parity On Reproductive And Productive Attributes In Dairy Cattle Of Natore District, Bangladesh

1970 ◽  
Vol 6 ◽  
pp. 91-96
Author(s):  
M Saiful Islam ◽  
Susanta Kumar Kundu
Keyword(s):  
Dairy Cattle ◽  
Dairy Cows ◽  
Milk Yield ◽  
Dairy Farms ◽  
Gestation Length ◽  
Overall Performance ◽  
Daily Milk Yield ◽  
Better Than ◽  
Daily Milk ◽  
Smallholder Dairy Farms

Impact of genotypes and parity on some vital reproductive and productive attributes in the local (L×L, n = 100) and four crossbred cows (L×F, L×SL, L×JR and L×S; n = 318) raised in randomly selected smallholder dairy farms scattered all over Natore District and adjacent areas have been assessed during a period from September 2007 to June 2010. With regard to reproductive attributes, significant differences existed among the cattle genotypes (P<0.05) except for gestation length (GL) and age at weaning (AW). The lowest age at puberty (AP) was found for L×F (21.42±0.37 months), while the highest for L×L (31.67±0.74 months). In terms of productivity, L×F cows produced the highest daily milk yield (DMY; 6.22±0.13 L), coupled with the highest total lactation yield (TLY; 2163.43±47.77 L), while L×L produced the lowest values (1.49±0.04 L and 416.40±12.3 L, respectively) for the traits. The effect of parity on both reproductive and productive attributes showed that the middle-aged dairy cows of the 3rd and 4th parities performed better than the younger (1st and 2nd parities) or the older (5th and beyond) ones. Considering the overall performance, the L×F cows could be ranked as the best genotype followed by their L×SL, L×JR, L×S and L×L counterparts in the study area. DOI: http://dx.doi.org/10.3329/jles.v6i0.9727 JLES 2011 6: 91-96

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