scholarly journals Least-Cost Livestock Production Rations

1974 ◽  
Vol 6 (2) ◽  
pp. 41-45 ◽  
Author(s):  
John R. Allison ◽  
D. M. Baird
Keyword(s):  
Mathematical Programming ◽  
Livestock Production ◽  
Animal Nutrition ◽  
Total Cost ◽  
Livestock Species ◽  
Feed Cost ◽  
Nutrition Research ◽  
Working Together

Animal scientists and agricultural economists have been working together to answer the question, “What is the least-cost feed mix for a given set of prices?” In the 1950's sophisticated mathematical programming via computers generated a renewed interest in ration formulation. Since then, animal scientists and agricultural economists have been intrigued with determing least-cost rations for various livestock species. But this research has been devoted to determining the least-cost rations rather than minimizing feed cost per pound of gain or pound of product produced and/or minimizing total cost per pound of gain or product produced. Answering the latter question is a prime goal of animal nutrition research.

scholarly journals 141 A nutrigenomics approach using RNA sequencing technology to study nutrient-gene interactions in agricultural animals

2019 ◽  
Vol 97 (Supplement_3) ◽  
pp. 135-135
Author(s):  
Shengfa F Liao ◽  
Shamimul Hasan ◽  
Jean M Feugang
Keyword(s):  
Gene Expression ◽  
Rna Sequencing ◽  
Gene Interactions ◽  
Animal Nutrition ◽  
Rna Seq ◽  
Bottom Line ◽  
Holistic View ◽  
Nutrition Research ◽  
Dietary Nutrients ◽  
A Genome

Abstract Animal life essentially is a set of gene expression processes. Thorough understanding of these processes driven by dietary nutrients and other environmental factors can be regarded as a bottom line of modern advanced animal nutrition research for improving animal growth, development, health, production, and reproduction performance. Nutrigenomics, a genome-wide approach using the knowledge and techniques obtained from the disciplines of genomics (including transcriptomics) and molecular biology, is to study the effects of dietary nutrients on cellular gene expression, cellular metabolic responses and, ultimately, the phenotypic changes of a living organism. Transcriptomics can be applied to investigate animal tissue transcriptome at a defined physiological or nutritional state, which provides a holistic view of the intracellular expression of RNA, especially mRNA. As a novel, promising transcriptomics approach, RNA sequencing (RNA-Seq) technology can monitor all-gene expressions simultaneously in response to dietary intervention. The principle and history of RNA-Seq technology will be briefly reviewed, and the three principal steps of this methodology, including the laboratory analysis of tissue samples, the bioinformatics analysis of the generated sequence data, and the subsequent biological interpretation of the data, will be described. The application of RNA-Seq technology in different areas of animal nutrition research, which include maternal nutrition, feeding strategy and gut microbiota, will be summarized. Lastly, the application of RNA-Seq technology in swine science and nutrition research will also be discussed. In short, to further improve animal feeding or production efficiency, RNA-Seq technology holds a great potential to be employed to explore the new insights into better understanding of nutrient-gene interactions in agricultural animals, and it is expected that the application of this cutting-edge technology in animal nutrition research will continue to grow in the foreseeable future. This research was supported in part by a USDA-NIFA Multistate Project (No. 1007691).

A survey of some in vitro methods used for animal nutrition research and extension work in Europe: the differences between the references and the truth

1998 ◽  
Vol 22 ◽  
pp. 338-340
Author(s):  
C. R. Mills
Keyword(s):  
Crude Protein ◽  
Rumen Fluid ◽  
Animal Nutrition ◽  
Concerted Action ◽  
In Vitro Methods ◽  
Nutrition Research ◽  
Extension Work ◽  
Nutritional Needs

As animal nutritionists are generally very cautious about using chemical analysis only for defining nutritional needs for livestock and as in vivo experiments are long, costly and subject to animal welfare legislation, much emphasis is placed on various in vitro analyses which are often regarded as being very informative in the absence of in vivo data. In vitro analyses may be applied to dry- (DMD) and organic-matter (OMD) digestibility and crude protein (CP) degradability (DG) and may involve ‘live’ cultures such as rumen fluid or gastric juices or ‘dead’ extracts containing enzymes. As part of an EU-funded Concerted Action (see Acknowledgements), a survey of the methods adopted for in vitro determinations (in vitro OMD, in vitro DG) for ruminants, pigs and poultry is underway: this paper presents a progress report of the information received to date concerning ruminant methods.The participants in the Concerted Action were asked to provide details of the in vitro methods actually in use in their countries, with particular attention to the methods used by the so-called Feed Information Centres (i.e. Feed Evaluation Units) for routine analyses (i.e. not experimental work). The participants supplied details of modifications and/or references to methods and this information was collated and circulated for checking and comment.

Using Linear Mathematical Programming Model To Reduce Feed Cost Of Broiler Farms

2020 ◽  
pp. 31
Author(s):  
مايا يوسف العبدالله ◽  
صفوان معذى أبو عساف ◽  
عفراء جلال سلوم
Keyword(s):  
Mathematical Programming ◽  
Programming Model ◽  
Mathematical Programming Model ◽  
Feed Cost

Canadian Regional Agriculture Model: Positive Mathematical Programming Applied to the Beef Sector in Canada

2020 ◽  
pp. 1-8
Keyword(s):  
Mathematical Programming ◽  
New Brunswick ◽  
Herd Size ◽  
Total Cost ◽  
Cost Curves ◽  
Breeding Herd ◽  
Positive Mathematical Programming ◽  
Beef Herd ◽  
The Impact ◽  
Beef Sector

This paper describes the Positive Mathematical Programming (PMP), the method for calibrating models of agricultural livestock production and resource use using a nonlinear total cost function. The PMP method is applied to agricultural sectoral models to study changes in policy and market signals. The Canadian Regional Agriculture Model (CRAM) is a regional, multi-sectoral, comparative static, partial equilibrium, mathematical programming model developed and maintained by Agriculture and Agri-Food Canada (AAFC) since mid-eighties. The PMP process converts a linear model using flexibility constraints into a nonlinear model in the absence of the flexibility constraints. A component of CRAM is the beef sector. The elements of the set of total cost curves are defined as quadratic function in terms of the number of cows and calves in the beef production activities. The marginal cost curves are then approximated using the shadow values from linear programming solution with linear curves. Once the flexibility constraints were removed, the model automatically calibrates to the base year production levels. The results from four scenarios indicated the beef sector of CRAM could predict the impact of the scenarios on the size of beef herd. In Scenario 1 where cash costs were increased by 10 percent, the breeding herd size decreased from 3.73 percent in New Brunswick to 0.0 percent in Ontario and Quebec. In Scenario 2 where barley costs were decreased by 10 percent, the breeding herd size increased from 0 percent for British Columbia, Alberta, Ontario, Quebec, Prince Edward Island and Nova Scotia to 1.93 percent for New Brunswick. In Scenario 3 where carcass weight per beef cow could be increased by 10 percent, the increase in beef herd size ranged from 0 percent for Ontario and Quebec to 2.56 percent for New Brunswick. In Scenario 4 where world beef prices were increased by 10 percent increase in beef herd size ranged from 4.48 percent for Manitoba to 25.78 percent for New Brunswick.

Canadian Regional Agriculture Model: PMP Applied to the Beef Sector in Canada

2020 ◽  
pp. 1-8
Keyword(s):  
Mathematical Programming ◽  
New Brunswick ◽  
Quadratic Function ◽  
Herd Size ◽  
Total Cost ◽  
Cost Curves ◽  
Breeding Herd ◽  
Beef Herd ◽  
The Impact ◽  
Beef Sector

This paper describes the Positive Mathematical Programming (PMP), the method for calibrating models of agricultural livestock production and resource use by a nonlinear total cost function. The PMP method is applied to agricultural sectoral models to study changes in policy and market signals. The Canadian Regional Agriculture Model (CRAM) is a regional, multi-sectoral, comparative static, partial equilibrium, mathematical programming model developed and maintained by Agriculture and Agri-Food Canada (AAFC) since mid-eighties. The PMP process converts a linear model using flexibility constraints into a nonlinear model in the absence of the flexibility constraints. A component of CRAM is the beef sector. The elements of the set of total cost curves are defined as quadratic function in terms of the number of cows and calves in the beef production activities. The marginal cost curves were then approximated using the shadow values from linear programming solution with linear curves. Once the flexibility constraints were removed, the model automatically calibrates to the base year production levels. The results from four scenarios indicated the beef sector of CRAM could predict the impact of the scenarios on the size of beef herd. In Scenario 1 where cash costs were increased by 10 percent, the breeding herd size decreased from 3.73 percent in New Brunswick to 0.0 percent in Ontario and Quebec. In Scenario 2 where barley costs were decreased by 10 percent, the breeding herd size increased from 0 percent for British Columbia, Alberta, Ontario, Quebec, Prince Edward Island and Nova Scotia to 1.93 percent for New Brunswick. In Scenario 3 where carcass weight per beef cow could be increased by 10 percent, the increase in beef herd size ranged from 0 percent for Ontario and Quebec to 2.56 percent for New Brunswick. In Scenario 4 where world beef prices were increased by 10 percent increase in beef herd size ranged from 4.48 percent for Manitoba to 25.78 percent for New Brunswick.

Impact of field fertility clinic on dairy production in peri urban areas of Chittagong District

1970 ◽  
Vol 39 (1-2) ◽  
pp. 183-190
Author(s):  
MS Islam ◽  
MSI Sikder ◽  
MM Hossain ◽  
M Akteruzzaman ◽  
M Shamsuddin
Keyword(s):  
Production Function ◽  
Milk Yield ◽  
Dairy Cow ◽  
Function Analysis ◽  
Paddy Straw ◽  
Total Cost ◽  
Net Return ◽  
Feed Cost ◽  
Fertility Clinic ◽  
Douglas Production Function

The study was undertaken to compare the relative profitability of dairy farming under Field Fertility Clinic (FFC) member and non-members. A total of 130 samples were selected randomly of which 100 were members and 30 were non-members. Total cost of raising dairy cow was estimated at Tk. 142.04 and Tk. 158.21/day for member and non-member farmers. Feed cost constituted about 71.64 per cent and 69.94 per cent of total cost for member and non-member farmers respectively. Concentrate occupied the largest share out of total feed cost. In case of member, net return per day per cow was Tk. 96.02 while in the case of non-member it was Tk. 65.94. Return from per dairy cow of the members was higher by Tk. 30.08 than the non-members. The average milk yield was 6.06 liters and 5.81 liters respectively for member and non-member farmers. Cobb-Douglas production function analysis was done to determine the effects of variables inputs such as concentrate feed, paddy straw, green grass, human labour, veterinary cost and FFC intervention on milk yield. The finding showed that all of the selected variables except paddy straw had significant impact on milk yield. Key words: Field fertility clinic; Milk yield; Cobb-Douglas production function; Net return DOI: http://dx.doi.org/10.3329/bjas.v39i1-2.9694 Bang. J. Anim. Sci. 2010, 39(1&2): 183-190

The role of biotechnology in enhancing the digestion of forage cell walls by ruminants (jerry hughes scholarship)

1995 ◽  
Vol 1995 ◽  
pp. 73-73
Author(s):  
E. R. Deaville
Keyword(s):  
Genetic Engineering ◽  
Nutritive Value ◽  
Genetic Manipulation ◽  
Animal Health ◽  
Significant Proportion ◽  
Livestock Production ◽  
Service Industries ◽  
Animal Nutrition ◽  
Rumen Microbes

The term biotechnology has been defined as the application of biological organisms, systems or processes to manufacture and service industries (Anon, 1980) and is, therefore, more than the application of ‘genetic engineering’ techniques alone. The potential application of biotechnology to the agricultural livestock industry includes many wide ranging areas: animal health; breeding; livestock production; livestock nutrition and the nutritive value of feeds. The role of biotechnology in animal nutrition and feeding is of particular importance since feed costs account for a significant proportion of the total variable costs in any livestock production system (e.g. milk, meat). The potential implications of biotechnology in animal nutrition has been reviewed by Armstrong (1986) and includes references to the improvement of the nutritive value of feeds through, for example, genetic manipulation of feed sources (cereals), appropriate supplementation and the use of biological inoculants with or without enzymes as silage additives and to improvements in the ability of the animal to obtain nutrients from feeds through the addition of enzymes to feeds and modification of rumen microbes through genetic engineering.

Contributions of animal nutrition research in rostock to energetic feed evaluation

1998 ◽  
Vol 51 (2-3) ◽  
pp. 95-110 ◽  
Author(s):  
M. Beyer ◽  
W. Jentsch ◽  
A. Chudy ◽  
P. Junghans ◽  
M. Klein
Keyword(s):  
Animal Nutrition ◽  
Nutrition Research
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