A Compositional Data Approach to the Prediction of Dry Milling Yields
Date
Authors
Major Professor
Advisor
Committee Member
Journal Title
Journal ISSN
Volume Title
Publisher
Authors
Research Projects
Organizational Units
The Center for Agricultural and Rural Development (CARD) conducts innovative public policy and economic research on agricultural, environmental, and food issues. CARD uniquely combines academic excellence with engagement and anticipatory thinking to inform and benefit society.
CARD researchers develop and apply economic theory, quantitative methods, and interdisciplinary approaches to create relevant knowledge. Communication efforts target state and federal policymakers; the research community; agricultural, food, and environmental groups; individual decision-makers; and international audiences.
Journal Issue
Is Version Of
Versions
Series
Department
Abstract
The yield of products in the dry milling industry is largely determined by the physical properties of the corn kernel. The main objective of this paper is to investigate several statistical models of dry milling yield prediction based on physical characteristics of corn. Data consisting of one hundred corn samples representing a range of genetic traits and quality differences are used. For each corn sample, 16 physical and chemical properties plus six dry milling product yields were measured in a controlled laboratory environment.
For each corn sample, we consider a vector of dry milling product yields and a vector of physical corn characteristics. Several single product models are investigated, two of which implicitly take into account the simplex sample space of product yields. A multivariate model is considered that consists of mapping the sample space from a simplex to unrestricted Euclidean space. Comparison are performed using a jack-knife-like approach.