Algorithms for Identifying Errors in Individual Feed Intake Data of Growing Pigs in Group-Housing

The present study describes algorithms for identifying errors in feed intake data of pigs, recorded with singlespacecomputerized feeding stations. Potential causes of errors are failed identification of pigs or an incorrect recording offeeder weight or time by the feeding station. Feed intake data of 250 pigs, divided into 30 groups, were analyzed. Datacontained 385,329 records on visits of which 0.95% had no identification. Nine algorithms were developed to check data forerrors caused by incorrect recordings. Algorithms focused on feed intake per visit, feeding rate per visit, or on the similarityof recorded feeder weights of subsequent visits. By using all nine algorithms, 6% of the visits were classified as beingincorrect. The numbers of errors needs to be kept small, as it is impossible to adjust feed intake data without bias. Resultsindicated several instances where a feeding station functioned sub-optimally during a period of days or weeks. Frequentchecking and correction of a feeding station function during recording would, therefore, reduce these errors. Expanding afeeding stations software with the editing system described herein would allow a daily check of recorded data for errors.Furthermore, frequent maintenance of feeding stations will probably reduce the number of incorrect recordings.