China Dairy ›› 2024, Vol. 0 ›› Issue (6): 31-39.doi: 10.12377/1671-4393.24.06.06

• FEEDING MANAGEMENT • Previous Articles     Next Articles

Research Progress on the Application of Intelligent Breeding Technology in Dairy Cattle Farming

WEI Danni, GUO Yongqing*   

  1. College of Animal Science,South China Agricultural University,Guangzhou Guangdong 510642
  • Online:2024-06-25 Published:2024-07-01

Abstract: With the development of large-scale dairy farms and modern information technology,intelligent breeding technology has been gradually applied to dairy cattle production,which has accelerated the transformation process of intelligent breeding. This paper reviewed the application and research progress of intelligent breeding technologies such as Internet of Things,big data,intelligent feeding,intelligent environmental control and remote monitoring in dairy cattle farming both domestically and internationally in recent years. The aim is to better utilize intelligent devices,improve production efficiency,achieve refined management of dairy farms,and provide references for the innovation and development of dairy cattle intelligent breeding technologies in China.

Key words: dairy cattle, intelligent breeding, application

[1] Zhang Y,Zhang Q,Zhang L,et al.Progress of machine vision technologies in intelligent dairy farming[J].Applied Sciences,2023,13(12):7052.
[2] 胡肄农,柏宗春,朱红宾,等.奶牛智慧养殖生态环境、生理健康与生长性能数字化表征指标体系研究[J].中国乳业,2023(8):46-49.
[3] Tedeschi L O,Greenwood P L,Halachmi I.Advancements in sensor technology and decision support intelligent tools to assist smart livestock farming[J].Journal of Animal Science,2021,99(2):1-11.
[4] Dzermeikaite K,Baceninaite D,Antanaitis R.Innovations in cattle farming:Application of innovative technologies and sensors in the diagnosis of diseases[J].Animals,2023,13(5):780.
[5] Liu D,Oczak M,Maschat K,et al.A computer vision-based method for spatial-temporal action recognition of tail-biting behaviour in group-housed pigs[J].Biosystems Engineering,2020,195(7):27-41.
[6] Salzer Y,Lidor G,Rosenfeld L,et al.Technical note:A nose ring sensor system to monitor dairy cow cardiovascular and respiratory metrics[J].Journal of Animal Science,2022,100(9):1-8.
[7] 于海波. 智能装备在奶牛养殖业上的应用及前景展望[J].中国畜牧业,2023(5):48-49.
[8] Menendez H M,Brennan J R,Gaillard C,et al.ASAS-NANP symposium:Mathematical modeling in animal nutrition:Opportunities and challenges of confined and extensive precision livestock production[J].Journal of Animal Science,2022,100(6):1-19.
[9] Neethirajan S.Artificial intelligence and sensor technologies in dairy livestock export:Charting a digital transformation[J].Sensors(Basel,Switzerland),2023,23(16):7045.
[10] 夏雪,侍啸,柴秀娟.人工智能驱动智慧奶牛养殖的思考与实践[J].中国乳业,2020(8):5-9.
[11] Waller B M,Julle-Daniere E,Micheletta J.Measuring the evolution of facial‘expression'using multi-species FACS[J].Neuroscience & Biobehavioral Reviews,2020,113(6):1-11.
[12] Xu B,Wang W,Guo L,et al.CattleFaceNet:A cattle face identification approach based on RetinaFace and ArcFace loss[J].Computers and Electronics in Agriculture,2022,193(2):106675.
[13] Weng Z,Fan L,Zhang Y,et al.Facial recognition of dairy cattle based on improved convolutional neural network[J].IEICE Transactions on Information and Systems,2022,E105.D(6):1234-1238.
[14] Peng Y,Kondo N,Fujiura T,et al.Dam behavior patterns in Japanese black beef cattle prior to calving:Automated detection using LSTM-RNN[J].Computers and Electronics in Agriculture,2020,169(2):105178.
[15] Yin X,Wu D,Shang Y,et al.Using an EfficientNet-LSTM for the recognition of single Cow’s motion behaviours in a complicated environment[J].Computers and Electronics in Agriculture,2020,177(10):105707.
[16] 李辉. 基于LoRaWAN和多传感器的奶牛计步及姿态检测系统设计[D].呼和浩特:内蒙古大学,2018.
[17] 王莉薇. 基于多源信息融合的奶牛反刍行为感知及分类识别研究[D].大庆:黑龙江八一农垦大学,2019.
[18] Antanaitis R,Juozaitienė V,Malašauskienė D,et al.Relation of automated body condition scoring system and inline biomarkers(milk yield,β-Hydroxybutyrate,lactate dehydrogenase and progesterone in milk) with cow’s pregnancy success[J].Sensors,2021,21(4):1414.
[19] Albornoz R I,Giri K,Hannah M C,et al.An improved approach to automated measurement of body condition score in dairy cows using a three-dimensional camera system[J].Animals(Basel),2021,12(1):72.
[20] Ruchay A,Kober V,Dorofeev K,et al.Accurate body measurement of live cattle using three depth cameras and non-rigid 3-D shape recovery[J].Computers and Electronics in Agriculture,2020,179(12):105821.
[21] Qiao Y,Kong H,Clark C,et al.Intelligent perception for cattle monitoring:A review for cattle identification,body condition score evaluation,and weight estimation[J].Computers and Electronics in Agriculture,2021,185(6):106143.
[22] Gardenier J,Underwood J,Weary D M,et al.Pairwise comparison locomotion scoring for dairy cattle[J].Journal of Dairy Science,2021,104(5):6185-6193.
[23] Zheng Z,Zhang X,Qin L,et al.Cows' legs tracking and lameness detection in dairy cattle using video analysis and Siamese neural networks[J].Computers and Electronics in Agriculture,2023,205(2):107618.
[24] Li Q,Chu M,Kang X,et al.Temporal aggregation network using micromotion features for early lameness recognition in dairy cows[J].Computers and Electronics in Agriculture,2023,204(1):107562.
[25] Piette D,Norton T,Exadaktylos V,et al.Individualised automated lameness detection in dairy cows and the impact of historical window length on algorithm performance[J].Animal,2020,14(2):409-417.
[26] Taneja M,Byabazaire J,Jalodia N,et al.Machine learning based fog computing assisted data-driven approach for early lameness detection in dairy cattle[J].Computers and Electronics in Agriculture,2020,171(4):105286.
[27] Neculai-Valeanu A S,Ariton A M.Udder health monitoring for prevention of bovine mastitis and improvement of milk quality[J].Bioengineering(Basel),2022,9(11):608.
[28] Lee M,Seo S.Wearable wireless biosensor technology for monitoring cattle:A review[J].Animals,2021,11(10):2779.
[29] Haddadi S,Koziel J A,Engelken T J.Analytical approaches for detection of breath voc biomarkers of cattle diseases —A review[J]. Analytica chimica Acta,2022,1206(114):339565.
[30] Gierschner P,Küntzel A,Reinhold P,et al.Crowd monitoring in dairy cattle—real-time VOC profiling by direct mass spectrometry[J].Journal of Breath Research,2019,13(4):46006.
[31] 席瑞谦,王娟,李正义,等.奶牛智能饲喂关键技术研究[J].中国农机化学报,2021,42(2):190-196.
[32] 刘光照,魏元振,陈美舟,等.TMR饲料制备技术探讨与装备试验[J].农业装备与车辆工程,2019,57(11):72-75.
[33] 白宇,李亚鹏.TMR技术应用探究[J].现代盐化工,2015(4):27-29,37.
[34] 陈玉华,田富洋,闫银发,等.国内外TMR饲喂技术及其制备机的研究进展[J].中国农机化学报,2017,38(12):19-29.
[35] 刘浩,彭华,付玲芳,等.我国奶牛场智能管理系统应用现状调研报告[J].中国乳业,2023(11):2-6.
[36] 卢颖. 奶牛智慧牧场技术的应用[J].中国畜牧业,2023(5):50-51.
[37] Oliveira B R,Ribas M N,Machado F S,et al.Validation of a system for monitoring individual feeding and drinking behaviour and intake in young cattle[J].Animal(Cambridge, England),2018,12(3):634-639.
[38] 白文怀. 基于供应链的智慧奶牛养殖场管理综述[J].当代畜禽养殖业,2020(11):21-23.
[39] 石成成. 犊牛精确饲喂装备自动控制系统的设计[D].石河子:石河子大学, 2016.
[40] Zagidullin L R,Khisamov R R,Kayumov R R,et al.Dairy robotic milking system[J].BIO Web of Conferences,2023,71(16):1004.
[41] Kondratieva O,Fedorov A,Slinko O,et al.Improving the technological support of dairy cattle breeding[J].BIO Web of Conferences,2021,37(9):90.
[42] Gastélum-Barrios A,Soto-Zarazúa G M,Escamilla-García A,et al.Optical methods based on ultraviolet,visible,and near-infrared spectra to estimate fat and protein in raw milk:A review[J].Sensors(Basel,Switzerland),2020,20(12):3356.
[43] Markov N,Stoycheva S,Hristov M,et al.Smart dairy farm —Digitalization and innovation[C].IEEE,2022:1-4.
[44] 户如霞,张力,李广臣,等.智能监控系统对大型牧场奶牛繁殖性能影响的研究[J].中国乳业,2020(8):39-43.
[45] Guo Y,Zhang Z,He D,et al.Detection of cow mounting behavior using region geometry and optical flow characteristics[J].Computers and Electronics in Agriculture,2019,163(8):104828.
[46] Reith S,Hoy S.Review:Behavioral signs of estrus and the potential of fully automated systems for detection of estrus in dairy cattle[J].Animal(Cambridge, England),2018,12(2):398-407.
[47] Cho Y,Kim J.AI-based intelligent monitoring system for estrus prediction in the livestock industry[J].Applied Sciences,2023,13(4):2442.
[48] Qu Y,Sun G,Zheng B,et al.Environment monitoring system of dairy cattle farming based on multi parameter fusion[J].Information(Basel),2021,12(7):273.
[49] 刘晶,金红伟,王明磊,等.智能化管理装备实现多层次、全覆盖信息化管理——农业农村部畜禽养殖机械化典型案例之三[J].中国奶牛,2021(7):54-56.
[50] Ji B,Du J,Qi H,et al.Retracted:Harmless treatment and comprehensive utilization of dairy farming waste based on artificial intelligence[J].Journal of Physics.Conference Series,2021,1744(2):22004.
[51] Wu D,Wang Y,Han M,et al.Using a CNN-LSTM for basic behaviors detection of a single dairy cow in a complex environment[J].Computers and Electronics in Agriculture,2021,182(3):106016.
[52] 王政,宋怀波,王云飞,等.奶牛运动行为智能监测研究进展与技术趋势[J].智慧农业,2022,4(2):36-52.
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