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.

An Economic Analysis of Milk Production and Profitability of Dairy Farms in Haryana

2021 ◽  
pp. 104-111
Keyword(s):  
Milk Production ◽  
Sampling Technique ◽  
Total Sample ◽  
Herd Size ◽  
Production Economics ◽  
Net Returns ◽  
Fresh Milk ◽  
Size Groups ◽  
Large Herd ◽  
Selection Of

The present study was carried out in the Sirsa and Bhiwani districts of Haryana state, purposively selected to work out milk production economics and its disposal pattern. The multistage stratified random sampling technique was used for the selection of the respondents. From Sirsa district 41 small, 36 medium and 23 large farmers were selected whereas from Bhiwani district 45 small, 39 medium and 16 large farmers were selected. Thus, in all 86 small farmers, 75 medium and 39 large farmers constituted the total sample of 200 respondents. Milk yield of crossbred cattle was found to be higher than the buffaloes. Net returns (?/animal/day) in the case of buffaloes and crossbred cow were highest in small, followed by medium and large herd size groups in both selected districts. On an average, 50.62 and 61.50 percent of the total milk produced was sold as fresh milk in Sirsa and Bhiwani district, respectively. Rest of the milk (38.76 percent) was used for family consumption and 10.62 for other purposes (conversion to ghee).

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.

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.

scholarly journals Adoption of Good Management Practices by the Gaushalas (Cow-shed) in Karnataka State, India

2020 ◽  
pp. 1-9
Author(s):  
Kalyan Mandi ◽  
S. Subash
Keyword(s):  
Milk Production ◽  
Management Practices ◽  
In Situ Conservation ◽  
Herd Size ◽  
Vital Role ◽  
General Management ◽  
Good Management ◽  
Large N ◽  
Karnataka State

Gaushalas play a vital role in safeguarding the cattle wealth of our country. It is primarily occupied with providing shelter to cows and is catering mostly the needs of non-lactating, weak, unproductive and stray cattle. However, a few fore front Gaushalas also maintain nucleus herd for in-situ conservation of indigenous purebred cows and produce quality males so as to enhance productivity of indigenous breeds. With this view, present study was undertaken with the objective of understanding the level of adoption of good management practices by the Gaushalas. The study was conducted in Karnataka State involving 40 out of 80 registered Gaushalas, categorized as small (n=12), medium (n=18) and large (n=10) Gaushalas based on the herd size. Good management practices play an important role in improving the production performances of cattle, enhancing efficiency of animals in Gaushalas. In the present study ‘adoption’ was operationalised as the degree to which the good management practices viz., breeding, feeding, healthcare, general management and hygienic milk production, were adopted in the Gaushalas.

scholarly journals Effect of Region, Herd Size, and Milk Production on Reasons Cows Leave the Herd

2000 ◽  
Vol 83 (12) ◽  
pp. 2980-2987 ◽  
Author(s):  
J.W. Smith ◽  
L.O. Ely ◽  
A.M. Chapa
Keyword(s):  
Milk Production ◽  
Herd Size

scholarly journals Effect of the scale of production on the cost-effectiveness of milk production systems belonging to the “Balde Cheio” program

2018 ◽  
Vol 39 (3) ◽  
pp. 1211
Author(s):  
Flávio De Moraes ◽  
Marcos Aurélio Lopes ◽  
Francisval De Melo Carvalho ◽  
Afonso Aurélio de Carvalho Peres ◽  
Fábio Raphael Pascoti Bruhn ◽  
...  
Keyword(s):  
Cost Effectiveness ◽  
Labor Force ◽  
Milk Production ◽  
Large Scale ◽  
Unit Cost ◽  
Small Scale ◽  
Total Cost ◽  
Medium Scale ◽  
Return On Capital ◽  
The Cost

This study investigates the cost-effectiveness of 20 demonstration units (DUs) belonging to the "Balde Cheio" program. The units in question are from the state of Rio de Janeiro, Brazil, dating from January to December 2011, and are sorted according to the scale of production (small, medium and large). The data were analyzed using Predictive Analytical software (PASW) 18.0. The scale of production influenced the total cost of milk production, and therefore profitability and cost-effectiveness. The large-scale stratum showed the lowest total unit cost. The positive results in medium and large scales in milk production lead to optimal conditions for long-term production, with the capitalization of cowmen. The items regarding the effective operating cost (EOC) with the biggest influence on the costs of dairy activity in the small scale stratum were food, energy and miscellaneous expenses. In the medium scale, these were food, labor force, and miscellaneous expenses. Finally, in the large scale, they were food, labor force and energy. In the small and large scale, the items regarding the total cost with the biggest influence on the costs of dairy activity were food, labor force, and return on capital, while in the medium scale, they were food, return on capital, and labor force. The average break-even point of 14 of the DUs was higher than the average daily production.

scholarly journals Farm data analysis for lifetime performance components of sows and their predictors in breeding herds

2020 ◽  
Vol 6 (1) ◽  
Author(s):  
Yuzo Koketsu ◽  
Ryosuke Iida
Keyword(s):  
High Efficiency ◽  
Herd Size ◽  
High Fertility ◽  
Herd Health ◽  
Herd Level ◽  
Lifetime Performance ◽  
Sow Longevity ◽  
Large Herd ◽  
Mating Interval ◽  
The Impact

Abstract Our objectives in this review are 1) to define the four components of sow lifetime performance, 2) to organize the four components and other key measures in a lifetime performance tree, and 3) to compile information about sow and herd-level predictors for sow lifetime performance that can help producers or veterinarians improve their decision making. First, we defined the four components of sow lifetime performance: lifetime efficiency, sow longevity, fertility and prolificacy. We propose that lifetime efficiency should be measured as annualized piglets weaned or annualized piglets born alive which is an integrated measure for sow lifetime performance, whereas longevity should be measured as sow life days and herd-life days which are the number of days from birth to removal and the number of days from date of first-mating to removal, respectively. We also propose that fertility should be measured as lifetime non-productive days, whereas prolificacy should be measured as lifetime pigs born alive. Second, we propose two lifetime performance trees for annualized piglets weaned and annualized piglets born alive, respectively, and show inter-relationships between the four components of the lifetime performance in these trees. Third, we describe sow and herd-level predictors for high lifetime performance of sows. An example of a sow-level predictor is that gilts with lower age at first-mating are associated with higher lifetime performance in all four components. Other examples are that no re-service in parity 0 and shorter weaning-to-first-mating interval in parity 1 are associated with higher fertility, whereas more piglets born in parity 1 is associated with higher prolificacy. It appears that fertility and prolificacy are independent each other. Furthermore, sows with high prolificacy and high fertility are more likely to have high longevity and high efficiency. Also, an increased number of stillborn piglets indicates that sows have farrowing difficulty or a herd health problem. Regarding herd-level predictors, large herd size is associated with higher efficiency. Also, herd-level predictors can interact with sow level predictors for sow lifetime performance. For example, sow longevity decreases more in large herds than small-to-mid herds, whereas gilt age at first-mating increases. So, it appears that herd size alters the impact of delayed gilt age at first-mating on sow longevity. Increased knowledge of these four components of sow lifetime performance and their predictors should help producers and veterinarians maximize a sow’s potential and optimize her lifetime productivity in breeding herds.

scholarly journals Associations between milking technology, herd size and milk production parameters on commercial dairy cattle farms

2020 ◽  
Vol 70 (2) ◽  
pp. 103-111
Author(s):  
Dorottya Ivanyos ◽  
László Ózsvári ◽  
István Fodor ◽  
Csaba Németh ◽  
Attila Monostori
Keyword(s):  
Dairy Cattle ◽  
Milk Production ◽  
Milk Yield ◽  
Linear Models ◽  
Herd Size ◽  
Exact Test ◽  
Production Parameters ◽  
Daily Milk Yield ◽  
Cattle Farms ◽  
Daily Milk

The aim of the study was to survey the milking technology and to analyse the associations between milking parlour type, herd size, and milk production parameters on dairy cattle farms. The milking technology was surveyed by using a questionnaire in 417 Hungarian dairy herds with 177,514 cows in 2017, and it was compared with their official farm milk production data. The surveyed farms were categorized according to their size (1-50, 51-300, 301-600, and &gt;600 cows) and to their milking parlour types (herringbone, parallel, carousel, and others). The relationships were analysed by multivariate linear models, one-way ANOVA, and Fisher’s exact test. Pairwise comparisons were performed by Tukey’s post hoc tests. The prevailing type of milking parlour was herringbone (71.0 %), but on larger farms the occurrence of parallel and carousel parlours increased (p&lt;0.001). The number of milking stalls per farm increased with herd size (p&lt;0.001). Farms with herringbone parlour had significantly smaller number of milking stalls than that of parallel (p=0.022) and carousel (p&lt;0.001) parlours, and the cows were mostly milked two times, while in carousel milking parlours mostly three times a day. As the herd size increased, so did daily milk yield (p&lt;0.001) and daily milk production per cow (p&lt;0.001). Herd size was associated with somatic cell count (p&lt;0.001). The type of milking parlour showed significant association with daily milk yield (p=0.039) and dairy units with herringbone milking system had the lowest milk quality. Our findings show that herd size has greater impact on milk production parameters than milking technologies.

scholarly journals ANALISIS USAHA HOME INDUSTRI KERUPUK RAMBAK

2017 ◽  
Vol 11 (1) ◽  
pp. 35-45
Author(s):  
Syarifah Aini ◽  
Erlin Widya Fatmawati
Keyword(s):  
Variable Cost ◽  
Fixed Cost ◽  
Business Activity ◽  
Total Cost ◽  
Total Variable Cost ◽  
Cost Of Production ◽  
The Government ◽  
The Cost ◽  
Breakeven Point

The purpose of this research is to know the amount of cost, acceptance, profit, profitability, and R / C Ratio from home industry crackers rambak in Sembon Village Satreyan District Kanigoro Blitar District. The result of this research shows that the total variable cost at rambak cracker agroindustry center is equal to Total variable cost Rp 1,139,783, - per day, total fixed cost Rp 4,953, - per day. So the total total cost of production is Rp 1,144,076, - per month. The breakeven point or BEP unit is 3 units. BEP Rp for RP 16,017, -. BEP revenue of Rp 16,017, - per day. Received revenue of Rp 1.650.000, - so the profit earned by employers is amounted to Rp 505,924, -. While the profitability of business is 44% which means this business is profitable. Home industry that run during this efficiency has been shown with R / C ratio of more than 1 that is equal to 1.44. Based on the criteria used, this business has been efficient because the efficiency value of more than 1. This means that every Rp 1.00 issued by the entrepreneur at the beginning of the business activities will get 1.44 times revenue from the cost incurred at the end of the business activity. This can be interpreted that home industry crackers rambak said Eligible to run. From this research it is suggested that entrepreneurs do creations by adding a sense of the product, so that the quality of the product can be increased and not less competitive with similar entrepreneurs from other regions. For the government, the Government of Blitar Regency through the Department of Industry and Trade and other related agencies should try to help develop the business crackers rambak by providing low-interest capital loans to entrepreneurs agro-industry crackers rambak.

scholarly journals Socio-personal and economic characteristics of buffalo owners in Maharashtra

2020 ◽  
Vol 15 (2) ◽  
pp. 66-73
Author(s):  
S.R. Avhad ◽  
Mahesh Chander ◽  
V.K. Basunathe ◽  
A.K. Verma
Keyword(s):  
Milk Production ◽  
Family Size ◽  
Middle Age ◽  
Animal Husbandry ◽  
Herd Size ◽  
Young Age ◽  
Annual Income ◽  
Social Category ◽  
Nuclear Families ◽  
Livestock Rearing

For the present study total 240 respondents were randomly selected from purposively selected four districts of two divisions in Maharashtra State to explore the sociopersonal and economic characteristics of buffalo owners. The study revealed that about 37.10 per cent of the farmers belonged to middle age followed by old (36.30%) and young age (26.70%) categories. Majority of the respondents were male, educated, Hindu (97.10%) and belonged to nuclear families (74.60%). About social category 37.9 per cent belonged to OBCs followed by General (36.70%), Scheduled Caste (12.10%) and Scheduled Tribes (13.30%). Mean family size was 6.65±0.17 members. The agriculture was main occupation for majority (58.80%) of the respondents while, 41.2 per cent were dependent on animal husbandry farming for main occupation. Landholding ranged from zero to 12 ha with mean land holding of 1.98±0.14 ha. About 28.80 per cent respondents belonged to semi-medium farmer category, followed by landless (20.40%), marginal (18.30%), small (16.70%), medium (14.60%) and large (1.30%). Majority of the respondents had medium livestock rearing experience (12-29 years), small herd size (7.28-22.81 SAUs), low milk production (13-52 liters) and low annual income (Rs. 1,00,000- Rs. 3,20,000).

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