scholarly journals Effects of Calliandra and Sesbania on Daily Milk Production in Dairy Cows on Commercial Smallholder Farms in Kenya

2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
D. N. Makau ◽  
J. A. VanLeeuwen ◽  
G. K. Gitau ◽  
S. L. McKenna ◽  
C. Walton ◽  
...  
Keyword(s):  
Milk Production ◽  
Dairy Farms ◽  
Protein Supplementation ◽  
Smallholder Farms ◽  
Study Objective ◽  
Final Model ◽  
Smallholder Dairy ◽  
Daily Milk Production ◽  
Daily Milk ◽  
Smallholder Dairy Farms

There is a growing interest in protein supplementation of dairy-cow diets using leguminous shrubs. The study objective was to ascertain the association between diet supplementation with Calliandra calothyrsus and Sesbania sesban and milk production in dairy cattle on commercial smallholder farms. This trial involved 235 cows from 80 smallholder dairy farms in Kenya randomly allocated to 4 intervention groups: (1) receiving Calliandra and Sesbania and nutritional advice; (2) receiving reproductive medicines and advice; (3) receiving both group 1 and 2 interventions; and (4) receiving neither intervention. Farm nutritional practices and management data were collected in a questionnaire, and subsequent physical examinations, mastitis tests, and milk production of cows on the farm were monitored approximately monthly for 16 months. Descriptive and univariable statistical analyses were conducted, and multivariable mixed-model regression was used for identification of factors associated (P<0.05) with daily milk production. The mean milk production was 6.39 liters/cow/day (SD = 3.5). Feeding Calliandra/Sesbania to cows was associated (P<0.0005) with an increase in milk produced by at least 1 liter/cow/day with each kg fed. Other variables positively associated with ln daily milk production in the final model included feeding of Napier grass, amount of silage and dairy meal fed, body condition score, and appetite of the cow. Other variables negatively associated with ln daily milk production in the final model included amount of maize germ fed, days in milk, sudden feed changes, pregnancy, and subclinical mastitis. In conclusion, our field trial data suggest that use of Calliandra/Sesbania through agroforestry can improve milk production in commercial smallholder dairy farms in Kenya. Agroforestry land use systems can be adopted as a way for dairy farmers to cope with feed shortages and low crude protein in farm-available feeds for their cows.

Effect of feeding oat and vetch forages on milk production and quality in smallholder dairy farms in Central Kenya

2018 ◽  
Vol 50 (5) ◽  
pp. 1051-1057 ◽  
Author(s):  
Solomon W. Mwendia ◽  
Chris M. Mwungu ◽  
Stanley Karanja Ng’ang’a ◽  
David Njenga ◽  
An Notenbaert
Keyword(s):  
Milk Production ◽  
Dairy Farms ◽  
Smallholder Dairy ◽  
Effect Of Feeding ◽  
Central Kenya ◽  
Smallholder Dairy Farms

scholarly journals Variation in the carbon footprint of milk production on smallholder dairy farms in central Kenya

2020 ◽  
Vol 265 ◽  
pp. 121780
Author(s):  
Andreas Wilkes ◽  
Shimels Wassie ◽  
Charles Odhong’ ◽  
Simon Fraval ◽  
Suzanne van Dijk
Keyword(s):  
Milk Production ◽  
Carbon Footprint ◽  
Dairy Farms ◽  
Smallholder Dairy ◽  
Central Kenya ◽  
Smallholder Dairy Farms

scholarly journals Accuracy of estimates of milk production per lactation from limited test-day and recall data collected at smallholder dairy farms

2020 ◽  
Vol 232 ◽  
pp. 103911 ◽  
Author(s):  
S.A. Migose ◽  
A. van der Linden ◽  
B.O. Bebe ◽  
I.J.M. de Boer ◽  
S.J. Oosting
Keyword(s):  
Milk Production ◽  
Dairy Farms ◽  
Recall Data ◽  
Smallholder Dairy ◽  
Smallholder Dairy Farms

scholarly journals The incidence of Reproductive Disorders in Dairy Cows under Smallholder Farms

2020 ◽  
pp. 22-27
Author(s):  
Muhammad Yusuf ◽  
Abdul Latief Toleng ◽  
Djoni Prawira Rahardja ◽  
Su Thanh Long
Keyword(s):  
Dairy Cattle ◽  
Dairy Cows ◽  
Dairy Farms ◽  
Reproductive Disorders ◽  
Smallholder Farms ◽  
Dairy Heifers ◽  
Holstein Friesian ◽  
Reproductive Disorder ◽  
Smallholder Dairy ◽  
Smallholder Dairy Farms

The objective of this study was to know the incidence of reproductive disorders in smallholder dairy farms. The study was conducted in 12 small dairy farms in Enrekang Regency, Indonesia.  A total of 80 dairy Holstein Friesian cattle consisted of 51 dairy cows and 29 dairy heifers were used in the present study. All dairy cattle at each farm were housed in tie-stall barns.  Reproductive examination was conducted to determine the incidence of reproductive disorders both vaginoscopy and palpation per rectum. The incidence of reproductive disorders was 30.0%; 31.0% in dairy heifers and 29.4% in dairy cows. Uterine infection was the most reproductive disorder suffered to the dairy cattle (12.5%), followed by inactive ovaries and cyst (10% and 5%, respectively). The dairy cattle suffered from reproductive disorders increased the likelihood to mate (artificial insemination; AI) greater than three times as well as to become pregnant. In the population of dairy cattle, 48% AI was conducted greater than three times. The pregnancy rate for the dairy cattle suffered from reproductive disorders was only 20%, with interval from calving to conception was 550 days in average. It can be concluded that high incidence of reproductive disorders in smallholder dairy farms. The occurrence of reproductive disorders decreased the reproductive performance of the dairy cattle in smallholder farms.

scholarly journals Prevalence of Repeat Breeding Syndrome in Dairy Cattle in Selected Regions of Kenya

2021 ◽  
Vol 10 (2) ◽  
pp. 114-118
Keyword(s):  
Dairy Cattle ◽  
Farming Systems ◽  
Dairy Farms ◽  
Cross Sectional Study ◽  
Cross Sectional ◽  
Study Objective ◽  
Farm Level ◽  
Smallholder Dairy ◽  
Extensive Farming ◽  
Smallholder Dairy Farms

The optimum production in dairy cows aims at getting a calf per cow per year. This, however, is limited by repeat breeding syndrome (RBS), which has multiple etiologies that cause either fertilization failure or early embryonic death. This study objective was to determine the prevalence of repeat breeding syndrome in dairy cattle within the selected regions of Kenya. A cross-sectional study design was carried out in 205 smallholder dairy farms in Makueni, Kakamega and Nandi counties. A total of 553 cows/heifers were recruited and examined per rectal to determine their reproductive status. Information on the breeding history of the cow and heifer was acquired at the farm. The results revealed that cross bred cattle were most affected by RBS at 38.9% followed by Jersey, Guernsey Ayrshire and least in Frisians at 21.1, 16.7, 25 and 14%, respectively. The overall animal level prevalence of RBS in cattle in the three counties was at 18.4%, while the overall farm-level prevalence was 58.3%. However, per county prevalence’s were different with animal level prevalence at 31.9, 20.9 and 12.5% in Makueni, Kakamega and Nandi, respectively. The farm-level prevalence’s at the counties were 75.4, 58.3 and 48.4% in Makueni, Kakamega and Nandi counties, respectively. Cattle kept in the zero-grazing/intensive system had the highest level of RBS at 30.1% compared to semi-intensive and extensive farming systems. The prevalence of RBS was also higher in multipara at 76% in comparison to primipara cows. Finally cows over four years which were in third or more parities had the highest prevalence of RBS, accounting for 65%) of the cases. In conclusion, the prevalence of RBS is significantly high in the Kenyan smallholder dairy farms. Further research should be undertaken to identify risk factors and appropriate intervention approaches for RBS to enhance its management.

scholarly journals The performance of smallholder dairy farms in West Java

2021 ◽  
Vol 892 (1) ◽  
pp. 012098
Author(s):  
T B Purwantini ◽  
H P Saliem ◽  
E Ariningsih ◽  
Erwidodo ◽  
I S Anugrah ◽  
...  
Keyword(s):  
Milk Production ◽  
Crop Production ◽  
Dairy Herd ◽  
Dairy Farms ◽  
Dairy Farming ◽  
Small Scale ◽  
West Java ◽  
Lactating Cows ◽  
Smallholder Dairy ◽  
Smallholder Dairy Farms

Abstract Small farmers dominate dairy farming in Indonesia, and the average productivity is low. An understanding of the performance of farmers and dairy farming businesses is needed to formulate policies for developing small-scale dairy farms. This study aims to provide information about the performance of dairy farms and recommend policies or measures to develop smallholder dairy farms in West Java. The data used in this paper is taken from the IndoDairy Smallholder Household Survey (ISHS) database, covering 600 dairy farm households selected randomly in Bandung, Garut, Cianjur, and Bogor Districts. Data collection took place between August and September 2017. A purposive and proportional random sampling method was utilized to select the samples. Data were analyzed by using descriptive statistical analysis. The results show that the main income activity of households (80%) was dairy farming. In addition to dairy farming, households received 10% of their income from off-farm activities, 8% from horticultural production, 2% from other livestock, and 1% from crop production. On average, dairy herd sizes were 5.6 cows per farm, of which the highest found in Bogor (7.7) and lowest in Garut (3.1). The results also show that milk production per cow ranged from 14.1 to 15.2 liters/day/lactating cows, with an average of 14.9 liters/day/lactating cows. Policies and efforts to increase milk production, productivity, and quality of fresh milk through improving feed technology and better dairy farming management are critically important to increasing smallholder dairy farmers’ income in Indonesia, especially in West Java.

scholarly journals Risk Factors Associated With Mastitis in Smallholder Dairy Farms in Southeast Brazil

Animals ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 2089
Author(s):  
Aline Callegari Silva ◽  
Richard Laven ◽  
Nilson Roberti Benites
Keyword(s):  
Risk Factors ◽  
Potential Risk ◽  
Dairy Farms ◽  
Subclinical Mastitis ◽  
Clinical Mastitis ◽  
Smallholder Farms ◽  
Increased Risk ◽  
Potential Risk Factors ◽  
Smallholder Dairy ◽  
Smallholder Dairy Farms

The aim of this study was to investigate the potential risk factors for clinical and subclinical mastitis in smallholder dairy farms in Brazil. A prospective, repeated cross-sectional study was carried out between May 2018 and June 2019 on 10 smallholder dairy farms. Potential risk factors for subclinical and clinical mastitis at the herd and cow level were recorded through interviewing the owner and by observation. A combination of clinical udder examination and the Tamis (screened mug with a dark base) test (Tadabras Indústria e Comércio de Produtos Agrovetereinário LTDA, Bragrança Paulista, SP, Brazil) were applied to observe clinical mastitis, and the California Mastitis Test (Tadabras Indústria e Comércio de Produtos Agrovetereinário LTDA, Bragrança Paulista, SP, Brazil) was used to determine subclinical mastitis. A total of 4567 quarters were tested, 107 (2.3%) had clinical mastitis, while 1519 (33.2%) had subclinical mastitis. At the cow level, clinical mastitis risk was highest in mid-lactation (50–150 days in milk) with OR 2.62 with 95% confidence interval (CI) of 1.03–6.67, while subclinical mastitis was highest in late lactation (> 150 days in milk) with OR 2.74 (95% CI 2.05–3.63) and lower in primiparous (OR 0.54, 95% CI 0.41–0.71) than multiparous cows. At the herd level, using dry-cow treatment (OR 4.23, 95% CI 1.42–12.62) was associated with an increased risk of clinical mastitis. Milking clinical (OR 0.37, 95% CI 0.24–0.56) and subclinical cases last (OR 0.21, 95% CI 0.09–0.47) and cleaning the milking parlor regularly (OR 0.27, 95% CI 0.15–0.46) had decreased odds for subclinical mastitis, while herds with optimized feed had greater odds (OR 9.11, 95% CI 2.59–31.9). Prevalence of clinical mastitis was at its lowest at the first visit in June/July and highest at the last visit in April/June (OR 3.81, 95% CI 1.93–7.52). Subclinical mastitis also presented increased odds in the last visit (OR 2.62, 95% CI 2.0–3.36). This study has identified some risk factors for mastitis on smallholder farms but further research on more farms across more areas of Brazil is required to develop a targeted mastitis control program for smallholder farms.

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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