A method for weighing broiler chickens using improved amplitude-limiting filtering algorithm and BP neural networks

作     者：Weihong Ma Qifeng Li Jiawei Li Luyu Ding Qinyang Yu Weihong Ma;Qifeng Li;Jiawei Li;Luyu Ding

作者机构：Beijing Research Center for Information Technology in AgricultureBeijing 100097China National Engineering Research Center for Information Technology in AgricultureBeijing 100097China Key Laboratory of Agri-informaticsMinistry of AgricultureBeijing 100097China Beijing Engineering Research Center of Agriculture Internet of ThingsBeijing 100097China 

出 版 物：《Information Processing in Agriculture》 (农业信息处理（英文）)

年 卷 期：2021年第8卷第2期

页      面：299-309页

核心收录：

学科分类：12[管理学] 0907[农学-林学] 0908[农学-水产] 08[工学] 0710[理学-生物学] 0830[工学-环境科学与工程（可授工学、理学、农学学位）] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 0905[农学-畜牧学] 0707[理学-海洋科学] 081104[工学-模式识别与智能系统] 0906[农学-兽医学] 0829[工学-林业工程] 0901[农学-作物学] 0835[工学-软件工程] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：supported by Key Technologies Research and Development Program(CN),funding number,2018YFE0108500 the International Cooperation Fund Project of Beijing Academy of Agriculture and Forestry Sciences,funding number 2019HP002 Beijing Science and Technology Planning,funding number Z191100004019007 

主　　题：Weighing of broiler chickens Improved amplitude-limiting filtering algorithm BP neural networks Dynamic weighing 

摘      要：Broiler chickens are traditionally weighed by steelyard or platform scale,which is timeconsuming and *** chickens usually exhibit stress-related behavior during *** 3D camera-based weighing system for broiler chickens can only weigh the broiler chicken in the monitoring ***,it makes poor weight prediction due to poor segmentation especially when the broiler chicken is flapping its *** solve these issues,we developed one simple and low-cost weighing system with high stability and accuracy.A validity value extraction method from dynamic weighing was ***,an improved amplitude-limiting filtering algorithm and a BP neural networks model were developed to avoid accidental *** BP neural networks model used daily weight gain,day-age,average velocity,and the weight data after filtering algorithm as the input *** weighing system was tested in a commercial Beijing Fatty Chickens house with Beijing Fatty *** tested thirteen groups of Beijing Fatty Chickens of different weights,from 500 g to 1800 g in intervals of 100 g,using the three different methods:no filtering algorithm or BP neural networks,only the improved amplitude-limiting filtering algorithm and a hybrid of the improved amplitude-limiting filtering algorithm and BP neural *** results showed that the hybrid algorithm had a better performance in minimizing the error,lowering from the original 6%down to 3%.The accurate weight data was transmitted to the remote service platform for further decision-making,such as activity analysis,feeding management,and health alerts.