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The Effect of Inputs on Poultry Production Output

Date Issued
May 1, 2021
Author(s)
Wolaver, Ty M  
Advisor(s)
Dr. Jada Thompson
Additional Advisor(s)
Tom Gill
Burt English
Edward Yu
Permanent URI
https://trace.tennessee.edu/handle/20.500.14382/42507
Abstract

To combat poverty and malnutrition, Feed the Future Tworore Inkoko, Twunguke (TI) has set out to teach Rwandan farmers how to grow broilers as additional income for the farmers and an additional protein source within the community to combat malnutrition. Throughout this program, the inputs and outputs of the farmers were recorded, and the goal is to determine an efficiency score for each flock raised and use that information to determine what factors contributed to a higher flock efficiency. A data envelopment analysis (DEA) is used to determine the efficiency score of each flock. Using these efficiency scores, a regression will be estimated using the characteristics of the farmers that raised the flocks and the characteristics of the farms and flocks themselves. The results show that as the program advanced, newer farmers increased in efficiency more quickly when the entire trend was observed. The main source of protein for commercial broilers is obtained from soybean meal. With a high protein percentage and low anti-nutrient properties, soybean meal is a complete, low-cost source of protein. However, solely relying on one type of protein meal leaves broiler producers open to price volatility. It is beneficial to have an alternative protein meal source available to lower the overall feed cost or reduce price volatility risk. Camelina meal offers a way to supplement the protein meal in broiler feed to solve this problem. To identify the demand of camelina meal for broiler finisher feed, a linear programming model was constructed that determines how much camelina meal would be selected for multiple price points in relation to soybean meal price. To consider the distribution of protein around both camelina meal and soybean meal, the stochastic LP model will be estimated at 5000 iterations per price point with each iteration randomly selecting from the distributions of camelina meal and soybean meal. The results show that the average amount of camelina meal continues increasing until the price of camelina meal is 60% relative to the price of soybean meal with the maximum amount of camelina meal selected in the best-case-scenario also being reached at this price level.

Subjects

Rwanda

DEA

Camelina

@Risk

Poultry

Efficiency

Disciplines
Agribusiness
Econometrics
Economic Theory
Degree
Master of Science
Major
Agricultural Economics
File(s)
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Wolaver__Ty_Final_Thesis_04.13.docx

Size

471.83 KB

Format

Microsoft Word XML

Checksum (MD5)

7b632a3f4e04827a76b6849578941552

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auto_convert.pdf

Size

609.69 KB

Format

Adobe PDF

Checksum (MD5)

c665992c46488a67d0809e9a845f9e32

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