Description
Breeding seeds to include desirable traits (increased yield, drought/temperature resistance, etc.) is a growing and important method of establishing food security. However, besides breeder intuition, few decision-making tools exist that can provide the breeders with credible evidence to make decisions on which seeds to progress to further stages of development. This thesis attempts to create a chance-constrained knapsack optimization model, which the breeder can use to make better decisions about seed progression and help reduce the levels of risk in their selections. The model’s objective is to select seed varieties out of a larger pool of varieties and maximize the average yield of the “knapsack” based on meeting some risk criteria. Two models are created for different cases. First is the risk reduction model which seeks to reduce the risk of getting a bad yield but still maximize the total yield. The second model considers the possibility of adverse environmental effects and seeks to mitigate the negative effects it could have on the total yield. In practice, breeders can use these models to better quantify uncertainty in selecting seed varieties
Download count: 2
Details
Title
- Chance-constrained optimization models for agricultural seed development and selection
Contributors
- Ozcan, Ozkan Meric (Author)
- Armbruster, Dieter (Thesis advisor)
- Gel, Esma (Thesis advisor)
- Sefair, Jorge (Committee member)
- Arizona State University (Publisher)
Date Created
The date the item was original created (prior to any relationship with the ASU Digital Repositories.)
2019
Subjects
- Operations Research
- Agriculture engineering
- Sustainability
- Chance-constrained optimization
- Environmental effects
- Operations Research
- Optimization
- Seed breeding
- Stochastic Optimization
- Selection (Plant breeding)
- Knapsack problem (Mathematics)
- Constrained Optimization
- Stochastic Processes
- Seeds--Development.
- Decision making--Mathematical models.
Resource Type
Collections this item is in
Note
- thesisPartial requirement for: M.S., Arizona State University, 2019
- bibliographyIncludes bibliographical references (pages 45-47)
- Field of study: Industrial engineering
Citation and reuse
Statement of Responsibility
by Ozkan Meric Ozcan