The invention discloses a
big data based low-cost laying hen breeding method. The method comprises steps as follows: each
cell of hen coop is taken as a unit in the egg producing period, and daily total egg yield, daily total
water intake and daily total feed intake are acquired; the temperature and the
humidity are controlled, the size of each hen coop, the number of laying hens and the average age in days are recorded; after the end of the egg production period, the total egg yield and the return rate are counted; an experience sample is selected, the size of each hen coop, the average age in days, the number of the laying hens, the temperature, the
humidity, the egg yield and the return rate are taken as an input layer, the daily total
water intake and the daily total feed intake are taken as an output layer, and a neural network is constructed; training samples are selected for training the neural network, and a neural
network model is obtained; ideal egg yield and ideal return rate are counted; next batches of laying hens are bred, the size of each hen coop, the ideal egg yield, the ideal return rate, intraday temperature and
humidity, the average age in days and the number ofthe laying hens are input into the neural
network model, and the intraday total
water intake and the daily total feed intake are obtained; the laying hens are fed. The method has the benefits that the feeding amount is reduced and low-cost breeding is realized.