Data mining as a hatchery process evaluation tool

Abstract

The hatchery is one of the most important segments of the poultry chain, and generates an abundance of data, which, when analyzed, allow for identifying critical points of the process. The aim of this study was to evaluate the applicability of the data mining technique to databases of egg incubation of broiler breeders and laying hen breeders. The study uses a database recording egg incubation from broiler breeders housed in pens with shavings used for litters in natural mating, as well as laying hen breeders housed in cages using an artificial insemination mating system. The data mining technique (DM) was applied to analyses in a classification task, using the type of breeder and house system for delineating classes. The database was analyzed in three different ways: original database, attribute selection, and expert analysis. Models were selected on the basis of model precision and class accuracy. The data mining technique allowed for the classification of hatchery fertile eggs from different genetic groups, as well as hatching rates and the percentage of fertile eggs (the attributes with the greatest classification power). Broiler breeders showed higher fertility (> 95 %), but higher embryonic mortality between the third and seventh day post-hatching (> 0.5 %) when compared to laying hen breeders' eggs. In conclusion, applying data mining to the hatchery process, selection of attributes and strategies based on the experience of experts can improve model performance.

Predicting hatchability of layer breeders and identifying effects of animal related and environmental factors

“…Precise prediction of hatchability may help the industry in proper prediction of hatchability of batches of eggs from the incubator (important for logistics) and possibilities to adjust incubation conditions to get more favorable outcomes. New technologies in the hatchery generate data about breeders, eggs, incubators, and other potentially important factors, that can be used for predicting performance of the hatchery ( Klein et al, 2020 ). This abundance of data, produced in hatcheries, may require new modeling techniques ( Ren et al, 2020 ).…”