Abstract:
With the growing of population, the poultry industry is also growing simultaneously to
increase egg production. Therefore, maximum egg production in the poultry industry will
be beneficial for both vendors and consumers. There are some major factors such as feed
consumption, water intake, light intensity, disease, environmental factors, parasite
infestation, and numerous management which can affect egg production. So, this work
has focused on the impact of light intensity to get maximum egg production. Therefore,
we have observed at poultry layers egg production over four weeks in a light-controlled
house and collected the light intensity value for the duration of an average of 6-8 hours
each day. We have also increased and decreased light intensity after 3-4 days respectively
to monitor the egg production at various light intensities. So, our dataset contains light
intensities along with dates and times and for observation, we have developed a web
application and through the web application, we have recorded per day egg production
with respect to a specific date and we have also observed that when light intensity
remains 5-15 lux the egg production is higher than light intensity 15-30 lux. For the
purpose of predict the egg productions over different light intensities, we have used
several machine learning approaches such as linear regression, logistic regression,
support vector regression, and random forest regression which provides around 99% of
accuracy.
