scholarly journals Association between milk urea nitrogen and first service conception in smallholder dairy farms under heat and humidity stress

2018 ◽  
pp. 1604-1608
Author(s):  
Suppada Kananub ◽  
John A. VanLeeuwen ◽  
Pipat Arunvipas
Keyword(s):  
Dairy Farms ◽  
Humid Climate ◽  
Urea Nitrogen ◽  
Service Conception ◽  
Milk Urea ◽  
The Mean ◽  
Smallholder Dairy ◽  
Pe Ratio ◽  
Smallholder Dairy Farms ◽  
Milk Urea Nitrogen

Aim: The study was to evaluate the relationship between the first service conception (FSC) and milk urea nitrogen (MUN) in smallholder dairy farms under heat and humidity stress. Materials and Methods: Dairy cows from 43 dairy farms giving birth between November 2014 and April 2015 (n=295) contributed to the study. All cows were sampled monthly to measure milk compositions, and we collected additional farm data from farmers through a questionnaire. The first service during the first 120 days of lactation was the outcome of interest in this study. Multivariable logistic regression determined significant associations with FSC. Results: The overall FSC was 22% and the mean MUN concentration was 11.55 mg/dl. The final FSC model included MUN concentration, the season of breeding, and protein energy ratio (PE ratio) in the diet. The odds of FSC were reduced by approximately 10% for each mg/dl higher MUN on the day of the milk sample that was nearest to the artificial insemination (AI) day. The odds of FSC were nearly 3 times higher when the first insemination occurred in winter compared to summer first services. Taking into account the nutritional factors, the odds of FSC were nearly 70% higher with an increase in PE ratio of 10 g of crude protein/Mcal from the mean of 35.90 g. Conclusion: This study of smallholder dairy farmers in the hot and humid climate of Thailand confirmed that season, nutritional management, and MUN concentration were associated with FSC. MUN appears to be a useful indicator to monitor the effects of diet on reproductive performance from this study.

Evaluation of influence of milk urea nitrogen on reproductive performance in smallholder dairy farms

2020 ◽  
Vol 98 (8) ◽  
pp. 375-379
Author(s):  
S Kananub ◽  
P Pechkerd ◽  
J VanLeeuwen ◽  
H Stryhn ◽  
P Arunvipas
Keyword(s):  
Reproductive Performance ◽  
Dairy Farms ◽  
Urea Nitrogen ◽  
Milk Urea ◽  
Smallholder Dairy ◽  
Smallholder Dairy Farms ◽  
Milk Urea Nitrogen

scholarly journals Milk Urea Nitrogen and Fertility in Dairy Farms

2010 ◽  
Vol 9 (10) ◽  
pp. 1519-1525 ◽  
Author(s):  
Mohammad Nourozi ◽  
Alireza Heravi Moussavi ◽  
Mehran Abazari ◽  
Mohammad Raiisian Zadeh
Keyword(s):  
Dairy Farms ◽  
Urea Nitrogen ◽  
Milk Urea ◽  
Milk Urea Nitrogen

Factors Affecting the First Service Conception Rate of Cows in Smallholder Dairy Farms in Bangladesh

2012 ◽  
Vol 48 (3) ◽  
pp. 500-505 ◽  
Author(s):  
MAR Siddiqui ◽  
ZC Das ◽  
J Bhattacharjee ◽  
MM Rahman ◽  
MM Islam ◽  
...  
Keyword(s):  
Dairy Farms ◽  
Conception Rate ◽  
Factors Affecting ◽  
Service Conception ◽  
Smallholder Dairy ◽  
Smallholder Dairy Farms

scholarly journals Impact of calf feeding practices on calf growth and health in smallholder dairy farms in Nyeri County, Kenya

2020 ◽  
Vol 1 (3) ◽  
Author(s):  
Silvia Situma ◽  
George K. Gitau ◽  
John VanLeeuwen ◽  
Charles M. Mulei ◽  
Dr. Peter Kimeli
Keyword(s):  
Body Condition Score ◽  
Positive Association ◽  
Dairy Farms ◽  
Feeding Practices ◽  
Milk Intake ◽  
Daily Weight Gain ◽  
Weight Gains ◽  
The Mean ◽  
Smallholder Dairy ◽  
Smallholder Dairy Farms

The objective of this study was to assess potential impact of selected enhanced feeding practices on growth of smallholder dairy calves. In the period between May and August 2012, 36 privately owned Kenyan smallholder dairy farms with new-born calves were purposively selected to participate in a randomized control trial. The calves were randomly allocated to one of nine feed intervention groups based on three groups of Calf Starter Intake (CSI; 20% protein) and three groups of Milk Intake (MI): control, half, and full. Full CSI intake involved lead feeding to achieve up to 1 kg/day feed intake at weaning, half CSI was to maximize intake at 0.5kg/day at weaning, while control CSI was the farmers’ normal practice (0-0.2 kg/day). Full MI was 4 Liters/day and half milk intake was 2 Liters/day, while control MI was the farmers’ normal practice (2-10 Liters/day). Each of the nine intervention groups had four calves per group (one calf died during the 1st week) resulting in 35 calves. Data on calf weight and height were collected weekly through farm visits for a period of eight weeks, and management data were collected through an in-person questionnaire. The results showed significant differences in the mean average daily weight gains across the different feed intervention groups at P (<0.001). All full CSI groups had weight gains over 0.5 kg/day. The full CSI + control MI had a positive association with the mean average daily weight gain at (0.61 kg/day), higher than the other two full CSI groups because of higher MI in this small group. In mixed multivariable linear regression analyses, weekly calf weights were higher with calf age and body condition score, a normal gastrointestinal tract, and amount of calf starter consumed per day, along with feeding sweet potato vines.  

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.

1184 Trends in milk urea nitrogen, milk composition, and milk yield in dairy farms in the Northeast U.S

2016 ◽  
Vol 94 (suppl_5) ◽  
pp. 568-568
Author(s):  
A. N. Hristov ◽  
M. T. Harper ◽  
J. Oh ◽  
F. Giallongo ◽  
J. C. Lopes ◽  
...  
Keyword(s):  
Milk Yield ◽  
Dairy Farms ◽  
Milk Composition ◽  
Urea Nitrogen ◽  
Milk Urea ◽  
Milk Urea Nitrogen

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.

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