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British Poultry Science Volume 44, 2003 - Issue 5
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Original Articles

Do heavy broiler chickens visit automatic weighing systems less than lighter birds?

A. Chedad Laboratory for Agricultural Buildings Research, Catholic University of Leuven, Leuven
,
J.-M. Aerts Laboratory for Agricultural Buildings Research, Catholic University of Leuven, Leuven
,
E. Vranken Laboratory for Agricultural Buildings Research, Catholic University of Leuven, Leuven
,
M. Lippens Ministry of Small Enterprises, Traders and Agriculture, Agricultural Research Centre—Ghent, Department for Animal Nutrition and Husbandry—Small Stock Husbandry, Merelbeke
,
J. Zoons Provincial Service for Agriculture and Horticulture, Antwerp, Belgium
&
D. Berckmans Laboratory for Agricultural Buildings Research, Catholic University of Leuven, LeuvenCorrespondence[email protected]
Pages 663-668 | Accepted 23 May 2003, Published online: 12 Jul 2010

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Ö. Cangar, J.-M. Aerts, E. Vranken & D. Berckmans. (2006) End-weight prediction in broiler growth. British Poultry Science 47:3, pages 330-335.
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Articles from other publishers (25)

Yuliang Zhao, Qijun Xiao, Jinhao Li, Kaixuan Tian, Le Yang, Peng Shan, Xiaoyong Lv, Lianjiang Li & Zhikun Zhan. (2023) Review on image-based animals weight weighing. Computers and Electronics in Agriculture 215, pages 108456.
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Peng Lyu, Jeongik Min & Juwhan Song. (2023) Application of Machine Learning Algorithms for On-Farm Monitoring and Prediction of Broilers’ Live Weight: A Quantitative Study Based on Body Weight Data. Agriculture 13:12, pages 2193.
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Boonsong Sutapun & Lawan Sampanporn. (2023) Chicken weight estimation using deep learning. Chicken weight estimation using deep learning.
Erdem Küçüktopçu, Bilal Cemek & Halis Simsek. (2023) Application of Mamdani Fuzzy Inference System in Poultry Weight Estimation. Animals 13:15, pages 2471.
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Helen Schomburg, Julia Malchow, Oliver Sanders, Jonas Knöll & Lars Schrader. (2023) Elevated platforms with integrated weighing beams allow automatic monitoring of usage and activity in broiler chickens. Smart Agricultural Technology 3, pages 100095.
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X. Yang, Y. Zhao, H. Gan, S. Hawkins, L. Eckelkamp, M. Prado, R. Burns, J. Purswell & T. Tabler. (2023) Modeling gait score of broiler chicken via production and behavioral data. animal 17:1, pages 100692.
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Yuping Peng, Zhixiong Zeng, Enli Lv, Xinyuan He, Boyang Zeng, Fan Wu, Jiaming Guo & Ziwei Li. (2022) A Real-Time Automated System for Monitoring Individual Feed Intake and Body Weight of Group-Housed Young Chickens. Applied Sciences 12:23, pages 12339.
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Katarzyna Olejnik, Ewa Popiela & Sebastian Opaliński. (2022) Emerging Precision Management Methods in Poultry Sector. Agriculture 12:5, pages 718.
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Weihong Ma, Qifeng Li, Jiawei Li, Luyu Ding & Qinyang Yu. (2021) A method for weighing broiler chickens using improved amplitude-limiting filtering algorithm and BP neural networks. Information Processing in Agriculture 8:2, pages 299-309.
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Innocent Nyalala, Cedric Okinda, Chen Kunjie, Tchalla Korohou, Luke Nyalala & Qi Chao. (2021) Weight and volume estimation of poultry and products based on computer vision systems: a review. Poultry Science 100:5, pages 101072.
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Simon V. Johansen, Martin R. Jensen, Bing Chu, Jan D. Bendtsen, Jesper Mogensen & Eric Rogers. (2021) Broiler FCR Optimization Using Norm Optimal Terminal Iterative Learning Control. IEEE Transactions on Control Systems Technology 29:2, pages 580-592.
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Dong Liu, Erik Vranken, Gijs van den Berg, Lenn Carpentier, Alberto Peña Fernández, Dongjian He & Tomas Norton. (2021) Separate weighing of male and female broiler breeders by electronic platform weigher using camera technologies. Computers and Electronics in Agriculture 182, pages 106009.
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Chun-Yao Wang, Ying-Jen Chen & Chen-Fu Chien. (2021) Industry 3.5 to empower smart production for poultry farming and an empirical study for broiler live weight prediction. Computers & Industrial Engineering 151, pages 106931.
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Simon V. Johansen, Jan D. Bendtsen & Jesper Mogensen. (2019) Broiler Slaughter Weight Forecasting using Dynamic Neural Network Models. Broiler Slaughter Weight Forecasting using Dynamic Neural Network Models.
Simon V. Johansen, Jan D. Bendtsen, Martin R.-Jensen & Jesper Mogensen. (2019) Broiler weight forecasting using dynamic neural network models with input variable selection. Computers and Electronics in Agriculture 159, pages 97-109.
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Ilan HalachmiMarcella GuarinoJeffrey BewleyMatti Pastell. (2019) Smart Animal Agriculture: Application of Real-Time Sensors to Improve Animal Well-Being and Production. Annual Review of Animal Biosciences 7:1, pages 403-425.
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Tom Van Hertem, Tomas Norton, Daniel Berckmans & Erik Vranken. (2018) Predicting broiler gait scores from activity monitoring and flock data. Biosystems Engineering 173, pages 93-102.
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Ilaria Fontana, Emanuela Tullo, Lenn Carpentier, Dries Berckmans, Andy Butterworth, Erik Vranken, Tomas Norton, Daniel Berckmans & Marcella Guarino. (2017) Sound analysis to model weight of broiler chickens. Poultry Science 96:11, pages 3938-3943.
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Cheng Wang, Hongqian Chen, Xuebin Zhang & Chaoying Meng. (2016) Evaluation of a laying-hen tracking algorithm based on a hybrid support vector machine. Journal of Animal Science and Biotechnology 7:1.
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Arda Aydin. (2016) Walking Behaviour and Spatial Use of Broiler Chickens. International Letters of Natural Sciences 54, pages 66-74.
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Arda Aydin. (2016) Walking Behaviour and Spatial Use of Broiler Chickens. International Letters of Natural Sciences 54, pages 66-74.
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Anders Krogh Mortensen, Pavel Lisouski & Peter Ahrendt. (2016) Weight prediction of broiler chickens using 3D computer vision. Computers and Electronics in Agriculture 123, pages 319-326.
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J Purswell & R Gates. 2013. Agricultural Automation. Agricultural Automation 205 230 .
Md. Bazlur R. Mollah, Md. A. Hasan, Md. A. Salam & Md. A. Ali. (2010) Digital image analysis to estimate the live weight of broiler. Computers and Electronics in Agriculture 72:1, pages 48-52.
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C.M. Wathes, H.H. Kristensen, J.-M. Aerts & D. Berckmans. (2008) Is precision livestock farming an engineer's daydream or nightmare, an animal's friend or foe, and a farmer's panacea or pitfall?. Computers and Electronics in Agriculture 64:1, pages 2-10.
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