Predictive Time Model of an Anglia Autoflow Mechanical Chicken Catching System
Date
2003-10
Journal Title
Journal ISSN
Volume Title
Publisher
Department of Food and Resource Economics
Abstract
In this project, a predictive time model was developed for an Anglia Autoflow mechanical
chicken catching system. At the completion of poultry growout, hand labor is currently used to
collect the birds from the house, although some integrators are beginning to incorporate
mechanical catching equipment. Several regression models were investigated with the objective
of predicting the time taken to catch the chicken. A regression model relating distance to total
time (sum of packing time, catching time, movement to catching and movement to packing)
provided the best performance. The model was based on data collected from poultry farms on the
Delmarva Peninsula during a six-month period. Statistical Analysis System (SAS) and
NeuroShell Easy Predictor were used to build the regression and neural network models
respectively. Model adequacy was established by both visual inspection and statistical
techniques. The models were validated with experimental results not incorporated into the initial
model.
Description
Keywords
Anglia autoflow, Chicken, Poultry, Models