ORIGINAL PAPER
 
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ABSTRACT
Digital livestock system through convergence of livestock production and information and communication technology (ICT) is being applied to livestock farms to improve animal behavior and welfare, production, and quality of animal food. In previously study, we noted that the egg production were greatly enhanced in laying hens using digital livestock system. The present study investigated effects of a digital livestock system on fatty acid profiles and cholesterol of eggs, animal behavior, and welfare of laying hens. A total of 300 laying hens (Hy-Line Brown) at 48 weeks old were divided into two treatment groups: conventional livestock system (CON) and digital livestock system (DLS) in a randomized complete block design for 10 weeks. Drinking, feather squatting, eating, moving, preening, and resting scores as behavior indicators of laying hens were significantly improved in the DLS group than in the CON group (all P < 0.05). Animal welfare scores such as appearance, feather condition, body condition, and health of laying hens were significantly higher in the DLS group than in the CON group (P < 0.05). Contents of oleic acid and unsaturated fatty acid of eggs were significantly increased in the DLS group compared to the CON group (P < 0.05). However, content of saturated fatty acid and n-6/n-3 fatty acid ratio of eggs of the DLS group were significantly lower than those in the CON group (P < 0.05). These results indicate that the digital livestock system can be used as a future livestock farming algorithm to significantly improve egg fatty acid profile, animal behavior, and welfare in laying hens.
ACKNOWLEDGEMENTS
This study was conducted by S.O. Park as a postdoctoral fellow at Warwick University UK 2017 under supervision of professor V.A. Zammit.
CONFLICT OF INTEREST
The Authors declare that there is no conflict of interest.
 
REFERENCES (45)
1.
Albentosa M.J., Cooper J.J., 2004. Effects of cage height and stocking density on the frequency of comfort behaviours performed by laying hens housed in furnished cages. Anim. Welfare. 13, 419–424, https://doi.org/10.7120/096272...
 
2.
Appleby M.C., Mench J.A., Hughes B.O., 2004. Poultry behaviour and welfare. CABI Publishing. Wallingford (UK)
 
3.
Baker D., Jackson E.L., Cook S., 2022. Perspectives of digital agriculture in diverse types of livestock supply chain systems. Making sense of uses and benefits. Front. Vet. Sci. 9, 992882, https://doi.org/10.3389/fvets....
 
4.
Beloretchkov, D., 2010. Welfare of table egg laying hens in closed and open systems of farming. Ptitsevudstvo. 4, 6–15, https://doi.https://doi.org/10...
 
5.
Blatchford R.A., Fulton R.M., Mench, J.A., 2016. The utilization of the welfare quality assessment for determining laying hen condition across three housing systems. Poult. Sci. 95, 154–163, https://doi.org/10.3382/ps/pev...
 
6.
Chen H.Q., Xin H.W., Teng G.H., Meng C.Y., Du X.D., Mao T.T., 2016. Cloud-based data management system for automatic real-time data acquisition from large-scale laying-hen farms. Int. J. Agric. Biol. Eng. 9, 106–115, https://doi.org/10.3965/j.ijab...
 
7.
Choukidar G.A., Dawande N.A., 2017. A survey on smart poultry farm automation and monitoring system. Int. J. Innov. Res. Sci. Eng. Technol. 6, 4806–4810, https://doi.org/10.15680/IJIRS...
 
8.
Corkery G., Wward S., Kenny C., Hemminway P., 2013. Incorporating smart sensing technologies into the poultry industry. J. World's Poult. Res. 3, 106–128
 
9.
Defra (Department for Environment, Food & Rural Affairs), 2010. Welfare of farmed animals (England) (Amendment) Regulations 2010 No. 3033. http://www.legislation.gov.uk/...
 
10.
FAWC (Farm Animal Welfare Committee), 2007. Opinion on enriched cages for laying hens. http://www.fawc. org.uk/pdf/enriched- cages.pdf
 
11.
Geetanjali A., Choukidar., Dawande N.A., 2017. Smart poultry farm automation and monitoring System. Published in: 2017 International Conference on Computing, Communication, Control and Automation (ICCUBEA). https://doi.org/10.1109/ICCUBE...
 
12.
Goswami M., Bhatt K., 2017. IOT based smart greenhouse and poultry farm environment monitoring and controlling using LAMP server and mobile application. Int. J. Adv. Res. Innov. Ideas Educ. 3, 4114–4124
 
13.
GroherK T., Heitkämper K., Umstätte C., 2020. Digital technology adoption in livestock production with a special focus on ruminant farming. Animal 14, 2404–2413
 
14.
Hitimana E., Bajpal, G., Musabe, R., Sibomana, L., 2018. Remote monitoring and control of poultry farm using IoT techniques. Int. J. Latest Technol. Eng. Management Appl. Sci. 7, 87–90
 
15.
Holt P.S., Davies R.H., Dewulf J., Gast R.K., Huwe J.K., Jones D.R., Waltman D., Willian K.R., 2011. The impact of different housing systems on egg safety and quality. Poult. Sci. 90, 251–262, https://doi.org/10.3382/ps.201...
 
16.
Husted K.S., Bouzinova E.V., 2016. Review. The importance of n-6/n-3 fatty acids ratio in the major depressive disorder. Medicina. 52, 139–147, https://doi.org/10.1016/j.medi...
 
17.
Jones T.A., Donnelly C.A., Dawkins, M.S., 2005. Environmental and management factors affecting the welfare of chickens on commercial farms in the UK and Denmark stocked at five densities. Poult. Sci. 84, 1155–1165, https://doi.org/10.1093/ps/84....
 
18.
Kim S.D., Lee S.E., 2015. Little core based system on chip platform for internet of thing. Int. J. Electric. Computer Eng. 5, 695–700
 
19.
Lay D.C., Fluton, R.M., Hester P.Y., 2011. Hen welfare in different housing systems. Poult Sci. 90, 278–294, https://doi.org/10.3382/ps.201...
 
20.
Mahale R.B., Sonavane S.S., 2016. Smart poultry farm monitoring using IOT and wireless sensor networks. Int. J. Adv. Res. Comput. Sci. 7, 187–190, https://doi.org/10.26483/ijarc...
 
21.
Mansor H., Gunawan T.S., Kamal M.M., Hashim A.Z., 2018. Development of smart chicken poultry farm. Indonesian J. Electric. Eng. Computer. Sci. 10, 498–505, http://doi.org/10.1111591/ijee...
 
22.
Meseret S., 2016. A review of poultry welfare in conventional production system. Livestock Res. Rural Development 28. Available from: http://www.lrrd.org/lrrd28/12/...
 
23.
Muttha R.I., Deshpande S.N., Chaudhari M.A., Wagh N.P., 2014. PLC based poultry automation system. Int. J. Sci. Res. 3, 149–152, https://doi.org/10.15373/22778...
 
24.
Neethirajan S., 2020. The role of sensors, big data and machine learning in modern animal farming. Sens. Bio-Sens. Res. 29, 100367–100375, https://doi.org/10.1016/j.sbsr...
 
25.
Neethirajan S., Kemp B., 2021. Digital livestock farming. Sensing and Bio-Sensing Res. 32, 100408–100421, https://doi.org/10.1016/j.sbsr...
 
26.
NRC (National Research Council), 1994. Nutrient Requirements of Poultry. 9th Revised Edition. The National Academies Press. Washington, DC (USA), https://doi.org/10.17226/2114
 
27.
NRC (National Research Council), 2011. Guide for the Care and Use of Laboratory Animals. 8th Edition. The National Academies Press. Washington, DC (USA), https://doi.org/10.17226/12910
 
28.
Park B.S., 2010. Effect of feeding Korean red pine bark extract on the levels of fatty acid and cholesterol in chicken meats. J. Korean Appl. Sci. 27, 76–81, https://doi.org/10.12925/jkocs...
 
29.
Park B.S., Park S.O., 2012. The consumption of low animal food with low n-6/n-3 ratio reduce LDL cholesterol in humans. Res. J. Med. Sci. 6, 107–112, https://doi.org/10.3923/rjmsci...
 
30.
Park B.S., Um K.H., Park S.O., Zammit V.A., 2018. Effect of stocking density on behavioral traits, blood biochemical parameters and immune responses in meat ducks exposed to heat stress. Arch. Anim. Breed. 61, 425–432, https://doi.org/10.5194/aab-61...
 
31.
Park S.O., 2022. Application strategy for sustainable livestock production with farm animal algorithms in response to climate change up to 2050: A review. Czech J. Anim. Sci. 67, 11, 425–441, https://doi.org/10.17221/172/2...
 
32.
Pickel T., Scholz B., Schrader L., 2010. Perch material and diameter affects particular perching behaviours in laying hens. Appl. Anim. Behav. Sci. 127, 37–42, https://doi.org/10.1016/j.appl...
 
33.
Risso S.J., Carelli A.A., 2017. Effects of conservation method and time on fatty acid composition, taste and microstructure of southern king crab (Lithodes santolla Molina, 1782) meat. J. Aquatic Food Product Technol. 26, 731–743, https://doi.org/10.1080/104988...
 
34.
Riu X., Zhao H.L., Thessen S., House J.D., Jones O.J.H., 2010. Effect of plant sterol-enriched diets on plasma and egg yolk cholesterol concentrations and cholesterol metabolism in laying hens. Poult. Sci. 89, 270–275, https://doi.org/10.3382/ps.200...
 
35.
Sosnówka-Czajka E., Herbut E., Skomorucha I., 2010. Effect of different housing systems on productivity and welfare of laying hens. Ann. Anim. Sci. 10, 349–360, http://psjc.icm.edu.pl
 
36.
Sözcü A., Ipek A., O˘guz Z., Gunnarsson S., Riber A.B., 2022. Comparison of behavioral time budget and welfare indicators in two local laying hen genotypes (Atak-S and Atabey) in a free-range system. Animals 12, 46–57, https://doi.org/.org/10.3390/a...
 
37.
Tactacan G.B., Guenter W., Lewis N.J., Rodriguez-Lecompte J.C., House J.D., 2009. Performance and welfare of laying hens in conventional and enriched cages. Poult. Sci. 88, 698–707, https://doi.org/10.3382/ps.200...
 
38.
Um K.H., Zammit V.A., Park, S.O., 2020. Utilization of ICT-based feeding system on egg production, egg quality, blood parameters and caecal microflora in laying hens. Anim. Nutr. Feed Technol. 20, 289–300, https://doi.org/10.5958/0974-1...
 
39.
Wang K.H., Shi S.R., Dou T.C., Sun H.J., 2009. Effect of a free-range raising system on growth performance, carcass yield, and meat quality of slow-growing chicken. Poult. Sci. 88, 2219–2223, https://doi.org/10.3382/ps.200...
 
40.
Webster A.B., 2004. Welfare implications of avian osteoporosis. Poult. Sci. 83, 184–192, https://doi.org/10.1093/ps/83....
 
41.
Welfare Quality., 2009, Assessment protocol for poultry. ASG Veehouderij BV. Laeyatad (The Netherlands)
 
42.
Widowski T.M., Caston. L.J., Hunniford, M.E., Cooley, L., Torrey. S., 2017. Effect of space allowance and cage size on laying hens housed in furnished cages, Part I: Performance and well-being. Poult. Sci. 96, 3805–3815, https://doi. org/10.3382/ps/pex197
 
43.
Yildirim M.I., Taskin A.I., 2017. The effects of environmental enrichment on some physiological and behavioral parameters of broiler chicks. Brazilian J. Poult. Sci. 19, 355–362, https://doi.org/10.1590/1806-9...
 
44.
Zammit V.A., Park S.O., 2020. Effect of smart poultry on growth performance, blood biochemistry parameters and cecal fermentation indices of broiler chickens. Anim. Nutr. Feed Technol. 20, 419–432, https://doi.org/10.5958/0974-1...
 
45.
Zaninelli M., Redaelli V., Tirloni E., Bernardi C., Dell’Orto V., Savoini C., 2016. First results of a detection sensor for the monitoring of laying hens reared in a commercial organic egg production farm based on the use of infrared technology. Sensors 16, 1757–1769, https://doi.org/10.3390/s16101...
 
 
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ISSN:1230-1388
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