Computer vision-based weight estimation of livestock: a systematic literature review

References

• Anglart D. 2014. Automatic estimation of body weight and body condition score in dairy cows using 3D imaging technique [Master Thesis]. Swedish University of Agricultural Sciences, Faculty of Veterinary Medicine and Animal Science, Department of Animal Nutrition and Management.
   Google Scholar
• Bikker JP, Van Laar H, Rump P, Doorenbos J, Van Meurs K, Griffioen GM, Dijkstra J. 2014. Evaluation of an ear-attached movement sensor to record cow feeding behavior and activity. Journal of Dairy Science. 97(5):2974–2979.
   PubMed Web of Science ®Google Scholar
• Brownlee J. 2019. Deep learning for computer vision: image classification, object detection, and face recognition in python. Vermont: Machine Learning Mastery.
   Google Scholar
• Cang Y, He H, Qiao Y. 2019. An intelligent pig weights estimate method based on deep learning in sow stall environments. IEEE Access. 7:164867–75.
   Web of Science ®Google Scholar
• Cominotte A, Fernandes AF, Dórea JR, Rosa GJ, Ladeira MM, van Cleef EH, Pereira GL, Baldassini WA, Neto OM. 2020. Automated computer vision system to predict body weight and average daily gain in beef cattle during growing and finishing phases. Livestock Science. 232:103904.
   Web of Science ®Google Scholar
• Dingwell RT, Wallace MM, McLaren CJ, Leslie CF, Leslie KE. 2006. An evaluation of two indirect methods of estimating body weight in Holstein calves and heifers. Journal of Dairy Science. 89(10):3992–3998.
   PubMed Web of Science ®Google Scholar
• Fernandes AF, Dórea JR, Fitzgerald R, Herring W, Rosa GJ. 2019. A novel automated system to acquire biometric and morphological measurements and predict body weight of pigs via 3D computer vision. Journal of Animal Science. 97(1):496–508.
   PubMed Web of Science ®Google Scholar
• Frizzo LS, Zbrun MV, Soto LP, Signorini ML. 2011. Effects of probiotics on growth performance in young calves: A meta-analysis of randomized controlled trials. Animal Feed Science and Technology. 169(3-4):147–156.
   Web of Science ®Google Scholar
• Gomes RA, Monteiro GR, Assis GJ, Busato KC, Ladeira MM, Chizzotti ML. 2016. Estimating body weight and body composition of beef cattle trough digital image analysis. Journal of Animal Science. 94(12):5414–5422.
   PubMed Web of Science ®Google Scholar
• Hansen MF, Smith ML, Smith LN, Jabbar KA, Forbes D. 2018. Automated monitoring of dairy cow body condition, mobility and weight using a single 3D video capture device. Computers in Industry. 98:14–22.
   PubMed Web of Science ®Google Scholar
• Heinrichs AJ, Lammers B. 1998. Monitoring dairy heifer growth. Pennsylvania: PennState, College of Agricultural Sciences.
   Google Scholar
• Heinrichs AJ, Losinger WC. 1998. Growth of Holstein dairy heifers in the United States. Journal of Animal Science. 76(5):1254–1260.
   PubMed Web of Science ®Google Scholar
• Heinrichs AJ, Rogers GW, Cooper JB. 1992. Predicting body weight and wither height in Holstein heifers using body measurements. Journal of Dairy Science. 75(12):3576–3581.
   PubMed Web of Science ®Google Scholar
• Heinrichs AJ, Wells SJ, Losinger WC. 1995. A study of the use of milk replacers for dairy calves in the United States. Journal of Dairy Science. 78(12):2831–2837.
   PubMed Web of Science ®Google Scholar
• Jalali S, Wohlin C. 2012. Systematic literature studies: database searches vs. backward snowballing. Proceedings of the 2012 ACM-IEEE international symposium on empirical software engineering and measurement; pp. 29–38. IEEE.
   Google Scholar
• Jun K, Kim SJ, Ji HW. 2018. Estimating pig weights from images without constraint on posture and illumination. Computers and Electronics in Agriculture. 153:169–176.
   Web of Science ®Google Scholar
• Kashiha M, Bahr C, Ott S, Moons CP, Niewold TA, Ödberg FO, Berckmans D. 2014. Automatic weight estimation of individual pigs using image analysis. Computers and Electronics in Agriculture. 107:38–44.
   Web of Science ®Google Scholar
• Kitchenham B, Brereton OP, Budgen D, Turner M, Bailey J, Linkman S. 2009. Systematic literature reviews in software engineering–a systematic literature review. Information and Software Technology. 51(1):7–15.
   Web of Science ®Google Scholar
• Kongsro J. 2014. Estimation of pig weight using a Microsoft Kinect prototype imaging system. Computers and Electronics in Agriculture. 109:32–35.
   Web of Science ®Google Scholar
• Kuzuhara Y, Kawamura K, Yoshitoshi R, Tamaki T, Sugai S, Ikegami M, Kurokawa Y, Obitsu T, Okita M, Sugino T, Yasuda T. 2015. A preliminarily study for predicting body weight and milk properties in lactating Holstein cows using a three-dimensional camera system. Computers and Electronics in Agriculture. 111:186–193.
   Web of Science ®Google Scholar
• Le Cozler Y, Allain C, Xavier C, Depuille L, Caillot A, Delouard JM, Delattre L, Luginbuhl T, Faverdin P. 2019. Volume and surface area of Holstein dairy cows calculated from complete 3D shapes acquired using a high-precision scanning system: Interest for body weight estimation. Computers and Electronics in Agriculture. 165:104977.
   Web of Science ®Google Scholar
• Lowder SK, Skoet J, Raney T. 2016. The number, size, and distribution of farms, smallholder farms, and family farms worldwide. World Development. 87:16–29.
   Web of Science ®Google Scholar
• Martins BM, Mendes AL, Silva LF, Moreira TR, Costa JH, Rotta PP, Chizzotti ML, Marcondes MI. 2020. Estimating body weight, body condition score, and type traits in dairy and manual body measurements. Livestock Science. 236:104054.
   Web of Science ®Google Scholar
• Mollah MB, Hasan MA, Salam MA, Ali MA. 2010. Digital image analysis to estimate the live weight of broiler. Computers and Electronics in Agriculture. 72(1):48–52.
   Web of Science ®Google Scholar
• Mourits MCM, Zom RLG, Derks AJJ, Evers AG, de Haan MHA, Steeneveld W, Hogeveen H. 2013. Jongveeopfok in bedrijfsverband= Heifer rearing; failure costs and profit opportunities (No. 705). Wageningen UR Livestock Research.
   Google Scholar
• Nasirahmadi A, Edwards SA, Sturm B. 2017. Implementation of machine vision for detecting behaviour of cattle and pigs. Livestock Science. 202:25–38.
   Web of Science ®Google Scholar
• NASS U. 2017. Census of agriculture. United States summary and state data. United States Department of Agriculture, National Agriculture Statistics Service. Available from: https://www.nass.usda.gov/Publications/AgCensus/2017/Full_Report/Volume_1,_Chapter_1_US/usv1.pdf.
   Google Scholar
• Netherlands S. 2016. Agriculture; crops, livestock and land use by general farm type, region.
   Google Scholar
• Nishide R, Yamashita A, Takaki Y, Ohta C, Oyama K, Ohkawa T. 2018. Calf robust weight estimation using 3D contiguous cylindrical model and directional orientation from stereo images. Proceedings of the Ninth International Symposium on information and Communication technology; pp. 208–215.
   Google Scholar
• Norouzzadeh MS, Nguyen A, Kosmala M, Swanson A, Palmer MS, Packer C, Clune J. 2018. Automatically identifying, counting, and describing wild animals in camera-trap images with deep learning. Proceedings of the National Academy of Sciences. 115(25):E5716–E5725.
   PubMed Web of Science ®Google Scholar
• Ozkaya S, Bozkurt Y. 2008. The relationship of parameters of body measures and body weight by using digital image analysis in pre-slaughter cattle. Archives Animal Breeding. 51(2):120–128.
   Web of Science ®Google Scholar
• Pezzuolo A, Guarino M, Sartori L, González LA, Marinello F. 2018. On-barn pig weight estimation based on body measurements by a Kinect v1 depth camera. Computers and Electronics in Agriculture. 148:29–36.
   Web of Science ®Google Scholar
• Pradana ZH, Hidayat B, Darana S. 2016. Beef cattle weight determine by using digital image processing. 2016 International Conference on Control, Electronics, Renewable Energy and Communications (ICCEREC); pp. 179–184; IEEE.
   Google Scholar
• Segerkvist KA, Höglund J, Österlund H, Wik C, Högberg N, Hessle A. 2020. Automatic weighing as an animal health monitoring tool on pasture. Livestock Science. 240:104157.
   Web of Science ®Google Scholar
• Shearer PS. 2019. 2017 Census: Number of farms decreasing, size increasing. [cited 2020 August 14]. Available from: https://www.nationalhogfarmer.com/agenda/2017-census-number-farms-decreasing-size-increasing.
   Google Scholar
• Shi C, Teng G, Li Z. 2016. An approach of pig weight estimation using binocular stereo system based on LabVIEW. Computers and Electronics in Agriculture. 129:37–43.
   Web of Science ®Google Scholar
• Song X S, Bokkers EA, van der Tol PP, Koerkamp PG, van Mourik S. 2018. Automated body weight prediction of dairy cows using 3-dimensional vision. Journal of Dairy Science. 101(5):4448–4459.
   PubMed Web of Science ®Google Scholar
• Song X, Schuttea J, van der Tol P, van Halsema F, Koerkampa PG. 2014. Body measurements of dairy calf using a 3-D camera in an automatic feeding system. Ininternational Conference of Agricultural Engineering; pp. 6–10.
   Google Scholar
• Stajnko D, Brus M, Hočevar M. 2008. Estimation of bull live weight through thermographically measured body dimensions. Computers and Electronics in Agriculture. 61(2):233–240.
   Web of Science ®Google Scholar
• Suwannakhun S, Daungmala P. 2018. Estimating pig weight with digital image processing using deep learning. 2018 14th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS); pp. 320–326; IEEE.
   Google Scholar
• Swanson EW. 1960. Effect of rapid growth with fattening of dairy heifers on their lactational ability. Journal of Dairy Science. 43(3):377–387.
   Web of Science ®Google Scholar
• Tasdemir S, Urkmez A, Inal S. 2011a. Determination of body measurements on the Holstein cows using digital image analysis and estimation of live weight with regression analysis. Computers and Electronics in Agriculture. 76(2):189–197.
   Web of Science ®Google Scholar
• Tasdemir S, Urkmez A, Inal S. 2011b. A fuzzy rule-based system for predicting the live weight of Holstein cows whose body dimensions were determined by image analysis. Turkish Journal of Electrical Engineering & Computer Sciences. 19(4):689–703.
   Web of Science ®Google Scholar
• Tummers J, Kassahun A, Tekinerdogan B. 2019. Obstacles and features of farm management information systems: a systematic literature review. Computers and Electronics in Agriculture. 157:189–204.
   Web of Science ®Google Scholar
• Wang Y, Yang W, Winter P, Walker L. 2008. Walk-through weighing of pigs using machine vision and an artificial neural network. Biosystems Engineering. 100(1):117–125.
   Web of Science ®Google Scholar
• Wongsriworaphon A, Arnonkijpanich B, Pathumnakul S. 2015. An approach based on digital image analysis to estimate the live weights of pigs in farm environments. Computers and Electronics in Agriculture. 115:26–33.
   Web of Science ®Google Scholar
• Wurtz K, Camerlink I, D’Eath RB, Fernández AP, Norton T, Steibel J, Siegford J. 2019. Recording behaviour of indoor-housed farm animals automatically using machine vision technology: A systematic review. PloS one. 14(12):e0226669.
   PubMed Web of Science ®Google Scholar
• Yamashita A, Ohkawa T, Oyama K, Ohta C, Nishide R, Honda T. 2017. Estimation of calf weight from fixed-point stereo camera images using three-dimensional successive cylindrical model. Proceedings of the 5th IIAE International Conference on Intelligent Systems and Image Processing; pp. 247–254.
   Google Scholar