Performance Evaluation of Solar-Powered DC Milking Machine for Dairy Cattle

This research practically evaluates the impact and performance of the solar-powered DC milking machine on dairy cattle. The milking machine was tested and evaluated on the Sokoto Gudali and Geurnsey cattle with respect to the milking time, milk yield, milking efficiency and energy efficiency. The environmental impact of the design was assessed using RETScreen software to ascertain the level of greenhouse gas emissions in comparison to conventional milking machine. The results indicated that both breeds of cattle takes approximately 8 – 15 minutes per day and 4 - 8minutes across morning and evening milking sessions. They produce 2.3 – 6.6litres of milk per day and 1.0 - 4.4litres of milk across the morning and evening milking session. Milking efficiency ranged from 0.26l/min - 0.62l/min while the energy efficiency was at the range of 0.15kJ/l - 0.36kJ/l. The environmental impact of the solar-powered DC milking machine showed to have a 93% significant reduction in gross annual greenhouse gas emissions.

Milking Time; Milk Yield; Milking Efficiency; Energy Efficiency; Milking Machine

1. Abdulhameed, B. O., Benyoh Emmanuel, K. N., Jong Wook, R., Dongjun, S., & Jeung-Soo, H. (2019). Validating the techno-economic and environmental sustainability of solar PV technology in Nigeria using RETScreen Experts to assess its viability, Sustainable Energy Technologies and Assessments, 36 (1) 100542, ISSN22131388 2019. 100542. [Google Scholar] [Crossref]

2. Basarir, A. (2002). Multidemensional goals of farmers in the beef cattle and dairy industries.LSUDoctoralDissertations. [Google Scholar] [Crossref]

3. Cogato, A., Brščić, M., Guo, H., Marinello, F., & Pezzuolo, A. (2021). Challenges and tendencies of automatic milking systems (AMS): A 20-years systematic review of literature and patents. Anim. (Basel); Anim. (Basel) 11 (2) 356.doi: 10.3390/ani11020356 [Google Scholar] [Crossref]

4. Dobbs, M. & Hamilton R. T. (2006) Small business growth: recent evidence and new directions. Int. J. Entrepreneurial Behaviour Res..13(1): 296-322. [Google Scholar] [Crossref]

5. Dohmen, W., Neijenhuis, F., & Hogeveen, H. (2010). Relationship between udder health and hygiene on farms with an automatic milking system. J Dairy Sci. Sep;93(9):4019-33. doi: 10.3168/jds.2009- 3028. [Google Scholar] [Crossref]

6. Edwards J. P, Williamson J. H, & Kuhn-Sherlock B. (2022). Improving parlor efficiency in block calving pasture-based dairy systems through the application of a fixed milking time determined by daily milk yield and milking frequency. J Dairy Sci. Sep;105(9):7513-7524. doi: 10.3168/jds.2022-21847. Epub 2022 Jul 22. [Google Scholar] [Crossref]

7. Gadekar, S. V., Karle, R., Surase, R. K., Handal, G. K., &. Kiran. M. P. (2017). Design and fabrication of cyclic operated milking machine. Internation Journal of Advance Research and Innovative Ideas in Education, 3(2): 3134-3140. [Google Scholar] [Crossref]

8. Gygax L, Neuffer I, Kaufmann C et al (2007) Comparison of functional aspects in two automatic milking systems and auto-tandem milking parlors. J Dairy Sci 90 (9) 4265–4274 [Google Scholar] [Crossref]

9. Hillerton J.E, Ohnstad I, Baines J.R & Leach K.A. (2000). Changes in cow teat tissue created by two types of milking cluster. J Dairy Res. Aug;67(3):309-17. doi:10.1017/s 0022029900004283. [Google Scholar] [Crossref]

10. Jacobs., J.A & Siegford J.M (2012) Lactating dairy cows adapt quickly to being milked by an automatic milking system. J Dairy Sci 95:1575–1584 [Google Scholar] [Crossref]

11. Jago, J. G., Davis, K. L. Newman, M. & Woolford M. W.. (2006). An economicevaluationofautomaticmilkingsystemsforNewZealand dairy farms. Proc. N.Z. Soc. Anim. Prod. 66:263–269 [Google Scholar] [Crossref]

12. Kaskous, S. (2016). MultiLactor milking system, a revolution in milking technology. In research report, Department of Research and Development; Siliconform: Türkheim, Germany; pp. 1–40. [Google Scholar] [Crossref]

13. Kaskous, S., & R. M. Bruckmaier. (2011). Best combination of pre- stimulation and latency period duration before cluster attachment for efficient oxytocin release and milk ejection in cows with low to high udder-filling levels. J. Dairy Res. 78: (1) 97–104. http://dx.doi. org/10.1017/S0022029910000816. [Google Scholar] [Crossref]

14. Lightfoot, C., & Mulvany .J. (2002). Farming Systems for Automatic MilkinginAustralia.OccasionalreportpreparedforDairyAustra- lia, Melbourne, Australia. [Google Scholar] [Crossref]

15. Mein G.A. (2012). The role of the milking machine in mastitis control. Vet Clin North Am Food Anim Pract. Jul;28(2):307-20. doi: 10.1016/j.cvfa.2012.03.004. Epub 2012 Apr 18. [Google Scholar] [Crossref]

16. Neal M (2014) Mobile milking: potential application and spatial land use implications. In: Roberts J, Charters S, Trotter M (eds) Proceedings of the 2014 Australian and New Zealand Spatially Enabled Livestock Management Symposium, Hamilton, New Zealand, 18th November 2014, Faculty of Environment Society and Design, Lincoln University: Canterbury, New Zealand [Google Scholar] [Crossref]

17. Ouweltjes W, & de Koning C.J.A.M (2004) Demands and opportunities for operational management support. In: Meijering A, Hogeveen H, de Koning CJAM (eds) Proceedings of the International Symposium Automatic Milking, A Better Understanding. Wageningen Academic Publishers, Wageningen, pp 433–442 [Google Scholar] [Crossref]

18. Pervanchon, F., Bockstaller, C. & Girardin, P., (2002). Assessment of energy use in arable farming systems by means of an agro-ecological indicator: the energy indicator. Agricultural Systems, Vol. 72, Number 2, 149-172 (24). [Google Scholar] [Crossref]

19. Porter, Michael E., & Mark R. Kramer. (2011) "Creating shared value: How to reinvent capitalism and unleash a wave of innovation and growth." Harvard business review 89.(1-2): 62-77. [Google Scholar] [Crossref]

20. Qazi, A., Hussain, F., Rahim, N. A., Hardaker, G., Alghazzawi, D., Shaban, K., & Haruna, K. (2019). Towards sustainable energy: a systematic review of renewable energy sources, technologies, and public opinions. IEEE access, 7, 63837-63851 [Google Scholar] [Crossref]

21. Rasmussen, M. D. (1993). Influence of switch level of automatic cluster removers on milking performance and udder health. J. Dairy Res. 60 (3) 287–297. https: / / doi .org/ 10 .1017/ S0022029900027631. [Google Scholar] [Crossref]

22. Revenko, I., & Medvedskyi, O. (2010). The perspectives of Milking Mechanization on Small Farms. National Bulletin of the National University of Bioresources and Land Management of Ukraine: Machinery and Power Economy of AIC, Vol, 144, Iss 4, pp. 82–87. [Google Scholar] [Crossref]

23. Sagi, R. (1978). Milk flow rate and end of milking detectors.Pages 328–334 in Proc. 17th Natl. Mastitis Counc. Ann. Mtg., Louisville, KY. Natl. Mastitis Counc.Inc., Madison, WI. [Google Scholar] [Crossref]

24. Sefeedpari, Paria, Shokoohi, Zeinab, Seyyed, Hassan, & Pishgar-Komleh. (2020). Dynamic energy efficiency assessment of dairy farming system in Iran: Application of window data envelopment analysis, Journal of Cleaner Production, Volume 275 , 124178, ISSN0959-6526 2020. 124178. [Google Scholar] [Crossref]

25. Siewert, J., Salfer, J., & Endres, M. (2019). Milk yield and milking station visits of primiparous versus multiparous cows on automatic milking system farms in the Upper Midwest United States. J. Dairy Sci. 102 (4) 3523–3530. doi: 10.3168/jds.2018-15382 [Google Scholar] [Crossref]

26. Singh A, Spellman ME, Somula H, & Wieland M. (2024). Effects of flow-responsive pulsation on teat tissue condition and milking performance in Holstein dairy cows. J Dairy Sci. 2024 Sep;107(9):7337-7351. doi: 10.3168/jds.2023-24605. Epub Apr 19. [Google Scholar] [Crossref]

27. Swastika D.K.S (2011).Building food independence and sovereignty to lift farmers out of poverty. Agricultural Innovation Development 4: 103- 107 [Google Scholar] [Crossref]

28. Wesseler, J. H. H., & Zilberman, D. (2021). Biotechnology, bioeconomy, and sustainable life on land. In Transitioning to sustainable life on land (Vol. 15, pp. 415–435). MDPI. Xepapadeas, A. (2011). The economics of non-point-source pollution. Annual Review of Resource Economics, 3(1), 355–373. [Google Scholar] [Crossref]

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