REPRODUCTIVE EFFICIENCY OF ARTIFICIALLY BRED HOLSTEINS IN QUEBEC

1979 ◽  
Vol 59 (2) ◽  
pp. 419-425 ◽  
Author(s):  
A. K. W. TONG ◽  
B. W. KENNEDY ◽  
J. E. MOXLEY ◽  
R. L. CHICOINE ◽  
G. L. ROY
Keyword(s):  
Milk Production ◽  
Variance Components ◽  
Error Variance ◽  
Herd Size ◽  
Maximum Likelihood Estimates ◽  
Reproductive Efficiency ◽  
Net Energy ◽  
Conception Rates ◽  
Net Energy Intake ◽  
Days Open

A total of 2216 lactations, initiated between July 1973 and June 1976, of 1382 Holstein cows in 36 herds from the Nicolet, Rock Forest and St-Hyacinthe regions of Quebec were studied. All cows were bred exclusively by AI. Mean services per conception, percent conception on first service, days from calving to first service and days open were 1.97 services, 47%, 88 days and 121 days, respectively. Based on maximum likelihood estimates of cow and error variance components, repeatabilities of services per conception, days from calving to first service and days open were 0.04, 0.09 and 0.07, respectively. Cows calving in spring had better reproductive performance than those calving during other times of the year. Reproductive efficiency was lower among both 2-yr-old and mature cows compared to intermediate aged cows. Lower reproductive efficiency was also associated with cows at high milk production levels. As herd size increased, conception rates declined. Herds feeding at high levels of net energy had higher conception rates than herds with low and medium net energy intake levels. Dairymen who managed their labor efficiently for milk production had herds with high reproductive efficiency.

A DAIRY RECORDS STUDY OF THE EFFECTS OF FEEDING LEVELS ON MILK YIELD AND COMPOSITION

1976 ◽  
Vol 56 (3) ◽  
pp. 513-522
Author(s):  
A. K. W. TONG ◽  
B. W. KENNEDY ◽  
J. E. MOXLEY
Keyword(s):  
Milk Yield ◽  
Milk Fat ◽  
Variance Components ◽  
Dairy Herd ◽  
Error Variance ◽  
Energy Concentration ◽  
Net Energy ◽  
Linear Effects ◽  
Net Energy Intake ◽  
Quadratic Effects

A total of 139,720 Holstein and 17,259 Ayrshire 305-day lactation records from the Dairy Herd Analysis Service were studied to estimate linear and quadratic effects of net energy intakes from silage, hay, pasture and meal and effects of silage:hay ratio, roughage:meal ratio and energy concentration on milk yield and composition. Effects of correcting for feeding levels on estimates of herd and cow variance components were studied also. Linear effects of increased net energy intakes from silage, hay, pasture and meal on milk, fat and protein yields were positive (P <.01) for both breeds. For Holsteins, all quadratic effects on milk yield were also positive (P <.01). Quadratic effects of each roughage source on fat and protein yield were negative, but meal had a positive quadratic effect (P <.01). Quadratic effects were inconsistent for the Ayrshires. Both linear and quadratic effects of feeding levels on fat and protein percent were inconsistent for the two breeds. For both breeds, greater silage:hay ratios and energy concentrations increased yields, and greater roughage:meal ratios decreased yields and fat percent (P <.01). Correcting records for net energy intake reduced estimates of herd, cow and error variance components. Repeatability estimates of yield traits were also reduced, but percentage trait repeatabilities were not altered.

Effect of first 60-day cumulative milk yield on days open in Holstein dairy cows in Iran

2007 ◽  
Vol 2007 ◽  
pp. 148-148
Author(s):  
A. Heravi Moussavi ◽  
M. Danesh Mesgaran ◽  
T. Vafa
Keyword(s):  
Dairy Cattle ◽  
Dairy Cows ◽  
Milk Production ◽  
Milk Yield ◽  
Dairy Farm ◽  
Reproductive Efficiency ◽  
Root Cause ◽  
Principal Factors ◽  
Days Open ◽  
Holstein Dairy Cows

Reproduction and milk production are the principal factors that are influencing dairy farm profitability. The dairy industry in Iran has changed dramatically in the last decade. The shift toward more productive cows and larger herds in Iran is associated with a decrease reproductive efficiency (Heravi Moussavi et al., 2004). Increased knowledge about the principal causes of reduced fertility is essential. The root cause of the declining fertility is probably a combination of a variety of physiological and management factors that have an additive effect on reproductive efficiency. Dairy cattle are inseminated and pregnancy is established while dairy cows are lactating. Based on the analyses of large datasets, there is clearly an antagonistic relationship between milk production and reproduction in dairy cattle (Lucy, 2001). It was shown that the hazard ratio for cumulative first 60-day milk yield and conception in high producer cows was 8 percent less than the others and also high milk yield was a risk factor for several reproductive disorders (Grohn and Rajala-Schultz, 2000). The objective of this study was to evaluate the effect of first 60-day cumulative milk yield on days open in Iranian Holstein dairy cows.

scholarly journals Genomic evaluation of milk yield in a smallholder crossbred dairy production system in India

2021 ◽  
Vol 53 (1) ◽  
Author(s):  
Mohammad Al Kalaldeh ◽  
Marimuthu Swaminathan ◽  
Yuvraj Gaundare ◽  
Sachin Joshi ◽  
Hassan Aliloo ◽  
...  
Keyword(s):  
Milk Production ◽  
Milk Yield ◽  
Smallholder Farmers ◽  
Genetic Correlations ◽  
Error Variance ◽  
Herd Size ◽  
Production Environment ◽  
Clear Trend ◽  
Production Environments ◽  
High Production

Abstract Background India is the largest milk producer globally, with the largest proportion of cattle milk production coming from smallholder farms with an average herd size of less than two milking cows. These cows are mainly undefined multi-generation crosses between exotic dairy breeds and indigenous Indian cattle, with no performance or pedigree recording. Therefore, implementing genetic improvement based on genetic evaluation has not yet been possible. We present the first results from a large smallholder performance recording program in India, using single nucleotide polymorphism (SNP) genotypes to estimate genetic parameters for monthly test-day (TD) milk records and to obtain and validate genomic estimated breeding values (GEBV). Results The average TD milk yield under the high, medium, and low production environments were 9.64, 6.88, and 4.61 kg, respectively. In the high production environment, the usual profile of a lactation curve was evident, whereas it was less evident in low and medium production environments. There was a clear trend of an increasing milk yield with an increasing Holstein Friesian (HF) proportion in the high production environment, but no increase above intermediate grades in the medium and low production environments. Trends for Jersey were small but yield estimates had a higher standard error than HF. Heritability estimates for TD yield across the lactation ranged from 0.193 to 0.250, with an average of 0.230. The additive genetic correlations between TD yield at different times in lactation were high, ranging from 0.846 to 0.998. The accuracy of phenotypic validation of GEBV from the method that is believed to be the least biased was 0.420, which was very similar to the accuracy obtained from the average prediction error variance of the GEBV. Conclusions The results indicate strong potential for genomic selection to improve milk production of smallholder crossbred cows in India. The performance of cows with different breed compositions can be determined in different Indian environments, which makes it possible to provide better advice to smallholder farmers on optimum breed composition for their environment.

A meta-analysis of milk production responses to increased net energy intake in Scandinavian dairy cows

2015 ◽  
Vol 175 ◽  
pp. 59-69 ◽  
Author(s):  
Charlotte Jensen ◽  
Søren Østergaard ◽  
Ingunn Schei ◽  
Jan Bertilsson ◽  
Martin Riis Weisbjerg
Keyword(s):  
Dairy Cows ◽  
Energy Intake ◽  
Milk Production ◽  
Meta Analysis ◽  
Net Energy ◽  
Net Energy Intake

Sources and uses of information on a West Coast dairy farm

2002 ◽  
pp. 31-32
Author(s):  
C. Van der Geest
Keyword(s):  
Milk Production ◽  
Time Pressure ◽  
Data Gathering ◽  
Technical Information ◽  
Dairy Farm ◽  
Farming System ◽  
Herd Size ◽  
Financial Benefit ◽  
Nitrogen Response ◽  
Directional Information

I am a 30-year-old sharemilker on my parent's 600 cow developing farm near Blackball on the western side of the Grey Valley. Earlier this year I competed in the National Young Farmer of the Year competition and finished a close third. So what is information? There are two types of information that I use. There is data gathered from my farm to help fine tune the running of the day to day operations on the farm And directional information This is the information that arrives in papers and directs the long-term direction and plans of the farm and farming businesses. Due to the variability in weather on the Coast there is a greater need to monitor and adjust the farming system compared to an area like Canterbury. This was shown last year (2001/02) when the farm was undergoing a rapid period of development and I was under time restraints from increasing the herd size, building a new shed as well as developing the farm. The results of the time pressure was that day to day information gathering was lower resulting in per cow production falling by 11% or around $182 per cow. So what information was lacking that caused this large drop in profit. • Pasture growth rates • Cow condition • Nitrogen requirements • Paddock performance • Milk production • Pre-mating heat detection As scientists and advisers I hear you say that it is the farmer's responsibility to gather and analyse this information. You have the bigger topics to research and discover, gene marking, improving pasture species, sexing of sperm and ideas that I have not even contemplated yet. This is indeed very valuable research. Where would farming be without the invention of electric fences, artificial breeding and nitrogen research? But my problem is to take a farm with below average production to the top 10% in production with the existing technology and farming principles. I have all the technical information I need at the end of a phone. I can and do ring my consultant, fertiliser rep, vet, neighbour and due to the size and openness of New Zealand science, at present if they do not know I can ring an expert in agronomy, nutrition, soils and receive the answer that I require. I hope that this openness remains as in a time of privatisation and cost cutting it is a true advantage. I feel that for myself the next leap in information is not in the growing of grass or production of milk but in the tools to collect, store and utilise that information. This being tied to a financial benefit to the farming business is the real reason that I farm. Think of the benefits of being able to read pasture cover on a motorbike instantly downloaded, overlaying cow intake with milk production, changes in cow weight, daily soil temperature and predicted nitrogen response. Telling me low producing cows and poor producing paddocks, any potential feed deficits or surpluses. This would be a powerful information tool to use. The majority of this information is already available but until the restraints of time and cost are removed from data gathering and storage, this will not happen.

COST OF MILK PRODUCTION AND BREAK EVEN ANALYSIS OF MEMBER AND NON MEMBER OF DAIRY COOPERATIVE SOCIETY FOR MILCH ANIMALS (COW & BUFFALO) IN DISTRICT ETAWAH OF U.P.

2014 ◽  
Vol 2 (1) ◽  
pp. 30-37
Author(s):  
Ashish Chandra ◽  
Dr. A. K. Dubey ◽  
Dr. Sachin Kumar Srivastava
Keyword(s):  
Milk Production ◽  
Herd Size ◽  
Total Cost ◽  
Minimum Quantity ◽  
Cooperative Society ◽  
Point Analysis ◽  
Large Herd ◽  
Breakeven Point

This study covered 150 cooperative member milk producers and 150 non-member milk producers which were post- stratified into Landless, Marginal, small, medium and large herd size categories. Breakeven point is a point where no profit no loss status achieved where MR = MC. In this study breakeven point analysis was done to estimate the minimum quantity milk to be produced to cover the total cost on all categories (members and nonmembers) of households of milch animals (Cow and buffalo). And also in this study the researchers have find out the Total cost of milk production per liter for member and non member categories. This study is helpful to find out the total cost of milk production in all categories as well as members and nonmembers of dairy cooperative society are able to find out the breakeven point of the whole business.

Net Energy vs. T.D.N. in Evaluating the Efficacy of an All-Alfalfa Hay Ration for Milk Production

1951 ◽  
Vol 10 (4) ◽  
pp. 947-960 ◽  
Author(s):  
H. M. Irvin ◽  
J. C. Shaw ◽  
P. Saarinen ◽  
L. A. Moore
Keyword(s):  
Milk Production ◽  
Net Energy ◽  
Alfalfa Hay

Immunodetection of Ostertagia ostertagi in Cattle Milk Samples in Wasit Province

2017 ◽  
Vol 1 (28) ◽  
pp. 637-648
Author(s):  
Abbas Hassan Khlaty Al-Sray
Keyword(s):  
Milk Production ◽  
Herd Size ◽  
Elisa Test ◽  
Production Factor ◽  
Size Factor ◽  
Ostertagia Ostertagi ◽  
Milk Samples ◽  
Management Group ◽  
Breed Group ◽  
Age Factor

The aim of present study was to detect the seroprevalence of Ostertagia ostertagi specific antibodies in cattle milk samples in Wasit province, by using the indirect ELISA test for first time in Iraq. For this purpose, an overall 368 dairies cow was submitted for study and the results were revealed that 51 (13.86 %) of tested cows were positive, and the mean optic density ratios (ODRs) of ELISA test values in seropositive cattle were 0.58. Also, this study aimed to investigate an association of seropositive results with some epidemiological risk factors. Hence, the positive results, according to these factors, were as follow: in milk production factor, 6.32 % for ³18 liters/day group, 14.29 % for ³10-18 liters/day group, and 25 % for < 10 liters/day group; in age factor, 13.41% for ³3-6 years group, and 14.75% for >6 years group; in breed factor, 18.27% for local breed group, 12.17% for cross-breed group, and 12% for pure breed group; in farm management factor, 21.35% for bad management group, and 5.68% for good management group; and in herd size factor, 11.59% for <25 (cow/herd) group, and 17.78% for ³ 25 (cow/herd) group. Statistically, the significant differences (P£ 0.05) were observed among related groups of milk production, breed, husbandry management, and herd size factors; while it’s not reported among groups of age factor.

The effects of days-open on milk yield and on breeding policy post partum

1979 ◽  
Vol 29 (1) ◽  
pp. 109-119 ◽  
Author(s):  
R. Bar-Anan ◽  
M. Soller
Keyword(s):  
Milk Production ◽  
Milk Yield ◽  
Post Partum ◽  
Economic Value ◽  
Total Yield ◽  
Annual Production ◽  
Initial Yield ◽  
Days Open

ABSTRACTThe effects of days-open on milk yields in current lactations and in following lactations were estimated from 71 911 current and 68 693 following lactation records. Yields were expressed as 305-day, total and annual records, where annual record = 365 × (total yield/days between calvings).The data were grouped according to current days-open, corrected for initial yield differences and analysed separately for heifers and cows in Moshav (moderate-yielding) and Kibbutz (high-yielding) herds. Current 305-day records increased by 15 to 18 kg milk/day-open up to 90 days-open, and 2 to 3 kg/day-open thereafter. In contrast, the effects of increasing days-open on annual yields were generally small and negative, being positive only for heifers up to 90 days-open. Thus 305-day records heavily under-rated annual yields of fertile cows. For current lactations, 70 to 100 days-open for heifers and 30 to 50 days-open for cows resulted in the highest annual production. Yields in following lactations were positively associated with days-open in the previous lactation. The effect was highest in high-yielding herds, suggesting that high-yielding cows respond positively to some rest between calvings.Combining the effects of days-open on current and following lactation yields and on the calf crop: in high-yielding herds heifers had the highest productivity when mated not earlier than 70 days post partum, while in moderately-yielding herds days-open did not affect productivity. Cows in high-yielding herds achieved highest productivity at 41 to 90 days-open, while cows in moderately-yielding herds were most productive when mated as early as possible.A comparison of the economic value of sire fertility and sire transmitting ability for milk production showed that fertility may often be over-rated.

Sign in / Sign up

Export Citation Format

Share Document