Automation and control system implementation in a smallholder crop production in Uganda: A review
Vol 5, Issue 2, 2024
VIEWS - 1571 (Abstract)
Download PDF
Abstract
This review paper explores the potential of automation and control systems in addressing critical challenges faced by agriculture in developing countries, with a specific focus on their applicability in Uganda. The study aims to comprehensively evaluate the role of these systems in enhancing agricultural practices, including the identification of adoption challenges, assessment of potential benefits, investigation of system effectiveness, and provision of evidence-based recommendations. The findings reveal that while there are notable obstacles such as high initial costs, limited technical expertise, and database constraints, there are also substantial opportunities, particularly through the integration of supportive information and communication technology (ICT) strategies and policies. Automation has demonstrated its effectiveness in various agricultural tasks, from mechanized tractors to food processing and livestock farming, offering promising prospects for value addition, irrigation, hydroponics, aquaponics, greenhouse farming, and livestock management. Despite the current modest adoption rates, the study provides compelling evidence supporting the need for increased utilization of automation and control systems in Uganda’s agriculture. Collaboration among stakeholders, formulation of supportive policies, development of comprehensive databases, prioritization of tailored ICT infrastructure, and facilitation of knowledge sharing are recommended to overcome challenges and harness the transformative capability of automation. In conclusion, embracing automation holds the key to enhancing the sustainability and food security of Uganda’s agriculture, offering valuable insights for policymakers and stakeholders in guiding the sector’s future advancement.
Keywords
References
1. Wanyama J, Banadda N, Kiyimba F, et al. Profiling agricultural engineering technologies for mechanizing smallholder agriculture in Uganda. AgricEngInt: CIGR Journal. 2016; 18, 4.
2. Sreekantha DK. Automation in agriculture: a study. International Journal of Engineering Science Invention Research & Development. 2016; 2(12).
3. Sundmaeker H, Verdouw C, Wolfert S, et al. Internet of Food and Farm 2020. In: Vermesan O, Friess P (editors). Digitising the Industry Internet of Things Connecting the Physical, Digital and VirtualWorlds. River Publishers; 2022. pp. 129-151. doi: 10.1201/9781003337966-4
4. Zziwa A, Okello AW, Kabenge I, et al. Optimizing Solar Drying: A Critical Review of Shapes, Orientation, and Future Prospects for Hybrid Solar Dryers. Journal of Power and Energy Engineering. 2023; 11, 44-63. doi: 10.4236/jpee.2023.1112004
5. Zarco-Tejada P, Hubbard N, Loudjani P. Precision Agriculture: An Opportunity for EU Farmers—Potential Support with the CAP 2014-2020. Available online: https://www.europarl.europa.eu/RegData/etudes/note/join/2014/529049/IPOL-AGRI_NT(2014)529049_EN.pdf (accessed on 1 March 2024).
6. MAAIF. The National Agricultural Extension Policy. Kampala: Ministry of Agriculture, Animal Industry and Fisheries. Available online: https://nutrition.opm.go.ug/wp-content/uploads/2017/06/National-Agriculture-Extension-Policy.pdf (accessed on 24 May 2019).
7. UBOS. National Population and Housing Census 2014 (Provisional results). Available online: https://www.ubos.org/onlinefiles/uploads/ubos/NPHC/NPHC%202014%20PROVISIONAL%20RESULTS%20REPORT.pdf (accessed on 11 April 2019).
8. van Dijk M, Morley T, Rau ML, Saghai Y. A meta-analysis of projected global food demand and population at risk of hunger for the period 2010–2050. Nature Food. 2021; 2(7): 494-501.
9. Arora NK. Impact of climate change on agriculture production and its sustainable solutions. Environmental Sustainability. 2019; 2(2): 95-96. doi: 10.1007/s42398-019-00078-w
10. Hertel TW, Rosch SD. Climate Change, Agriculture, and Poverty. Applied Economic Perspectives and Policy. 2010; 32(3): 355-385. doi: 10.1093/aepp/ppq016
11. Wing IS, De Cian E, Mistry MN. Global vulnerability of crop yields to climate change. Journal of Environmental Economics and Management. 2021; 109, 102462. doi: 10.1016/j.jeem.2021.102462
12. Daszkiewicz T. Food Production in the Context of Global Developmental Challenges. Agriculture. 2022; 12(6): 832. doi: 10.3390/agriculture12060832
13. Dachs B. The impact of new technologies on the labour market and the social economy. Available online: http://www.europarl.europa.eu/RegData/etudes/STUD/2018/614539/EPRS_STU(2018)614539_EN.pdf (accessed on 23 May 2019).
14. Miranda J, Ponce P, Molina A, et al. Sensing, smart and sustainable technologies for Agri-Food 4.0. Computers in Industry. 2019; 108: 21-36. doi: 10.1016/j.compind.2019.02.002
15. Shepon A, Henriksson PJG, Wu T. Conceptualizing a Sustainable Food System in an Automated World: Toward a “Eudaimonian” Future. Frontiers in Nutrition. 2018; 5. doi: 10.3389/fnut.2018.00104
16. Sanchez-Bayo F. Impacts of Agricultural Pesticides on Terrestrial Ecosystems. Ecological Impacts of Toxic Chemicals (Open Access). 2011; 63-87. doi: 10.2174/978160805121210063
17. Adeyemi AA, Mafimisebi TE. Assessment of the performance of a subsurface drip irrigation system under different water quality in a humid tropical environment. Agricultural Water Management, 2017; 187: 24-34.
18. UN Department of Economic and Social Affairs. World Population Prospects 2019: Highlights. United Nations. Available online: https://population.un.org/wpp/Publications/Files/WPP2019_Highlights.pdf (accessed on 23 May 2019).
19. Sylvester G. E-agriculture in action: Drones for agriculture. Food and Agriculture Organization of the United Nations and International Telecommunication Union; 2018.
20. Kempenaar C, Been T, Booij J, et al. Advances in Variable Rate Technology Application in Potato in The Netherlands. Potato Research. 2017; 60(3-4): 295-305. doi: 10.1007/s11540-018-9357-4
21. Pedersen SM, Fountas S, Blackmore S. Agricultural robots—Applications and economic perspectives. In: Takahashi Y (editor). Service Robot Applications. IntechOpen; 2008. pp. 369-382. doi: 10.5772/6048
22. Twomlow SJ, Steyn JT, Du Preez CC. Dryland Farming in Southern Africa. Dryland Agriculture. Published online October 26, 2015: 769-836. doi: 10.2134/agronmonogr23.2ed.c19
23. Kushwaha HL, Sinha JP, Khura TK, et al. Status and Scope of Robotics in Agriculture. In: Proceedings of the International Conference on Emerging Technologies in Agricultural and Food Engineering; 27-30 December 2016; Kharagpur, India. pp. 264-277.
24. Tainika B, Şekeroğlu A, Duman M, Şentürk Y. Poultry Production in Uganda: Challenges and Opportunities. In: Proceedings of the 1st International Congress of the Turkish Journal of Agriculture—Food Science and Technology (International Congress of TURJAF); 8-10 November 2019; Antalya, Turkey.
25. Pack M, Mehta K. Design of Affordable Greenhouses for East Africa. In: Proceedings of the 2012 IEEE Global Humanitarian Technology Conference; 21-24 October 2012; Seattle, WA, USA. pp. 104-110. doi: 10.1109/ghtc.2012.66
26. Nakyeyune M. Uganda’s floriculture export earnings rise. The East African. 2020.
27. Kasumba J. Development and Performance Evaluation of a Microcontroller-Based Low-Cost Greenhouse Environment Monitoring and Control System for Tomato Production. Advances in Agriculture. 2020; 1-12.
28. Adebiyi OA, Adeola AT, Osinowo OA, et al. Effects of Feeding Hydroponics Maize Fodder on Performance and Nutrient Digestibility of Weaned Pigs. Applied Ecology and Environmental Research, 2018, 16(3): 2415-2422. doi: 10.15666/aeer/1603
29. Balcom P. Irrigation and Aquaponics Technologies to improve the quality of life in Developing Nations. Wise Journal of Public Policy. 2015.
30. Okemwa E. Effectiveness of aquaponic and hydroponic gardening to traditional gardening. International Journal of Scientific Research and Innovative Technology. 2015; 2(12): 21-52.
31. Palande V, Zaheer A, George K. Fully Automated Hydroponic System for Indoor Plant Growth. Procedia Computer Science. 2018; 129: 482-488. doi: 10.1016/j.procs.2018.03.028
32. Wanyama J, Soddo P, Nakawuka P, et al. Development of a solar powered irrigation control system kit. Smart Agricultural Technology Journal. 2023; 5: 100273. doi: 10.1016/j.atech.2023.100273
33. Soumendra B, Abhijeet S, Aditya VS, et al. Design of Temperature Controlled Solar Dryer, International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering. 2015; 4: 11.
34. Zziwa A, Matsapwe D, Ssempira EJ, Kizito SS. Transforming Agriculture: Innovations in Sustainable Wastewater Reuse—A review. International Journal of Scientific Advances (IJSCIA). 2023; 4(6): 1038-1048.
35. Wanyama J. Profiling agricultural engineering technologies for mechanizing smallholder agriculture in Uganda. Agricultural Engineering International: CIGR Journal. 2016; 18(4): 40-51.
36. Pardhi CB, Bhagoria JL. Development and performance evaluation of mixed-mode solar dryer with forced convection. International Journal of Energy and Environmental Engineering. 2013; 4(1): 23. doi: 10.1186/2251-6832-4-23
37. Namayengo FM, Raymonds M, Alex A, et al. Techno Economic Analysis of Refractance Window Drying of Fruits: A Case of Small-Medium Scale Agro Processors in Uganda. International Journal of Scientific Advances. 2021; 2(5). doi: 10.51542/ijscia.v2i5.23
38. Sebuuwufu CI, Kagoro GR, Kauffman B. Focusing on Chain Actor Practices to Improve Post- Harvest Product Handling: The Case of the Pineapple Value Chain in South Western Uganda. 2019; 8(2): 718-723.
39. Tiwari M, Pandey H, Mukherjee A, et al. Artificial Intelligence in Food Processing. In: Chhikara N, Panghal A, Chaudhary G (editors). Novel Technologies in Food Science. Scrivener Publishing; 2022. pp. 511-550. doi: 10.1002/9781119776376.ch14
40. Chang Y, Hsueh M, Hung S, et al. Prediction of specialty coffee flavors based on near‐infrared spectra using machine‑ and deep‐learning methods. Journal of the Science of Food and Agriculture. 2021; 101(11): 4705-4714. doi: 10.1002/jsfa.11116
41. Arah IK, Ahorbo GK, Anku EK, et al. Postharvest Handling Practices and Treatment Methods for Tomato Handlers in Developing Countries: A Mini Review. Advances in Agriculture. 2016; 2016: 1-8. doi: 10.1155/2016/6436945
42. Narendra VG, Hareesh KS. Prospects of Computer Vision Automated Grading and Sorting Systems in Agricultural and Food Products for Quality Evaluation. International Journal of Computer Applications. 2010; 1(4): 1-12. doi: 10.5120/111-226
43. Pandey R, Naik S, Marfatia R. Image Processing and Machine Learning for Automated Fruit Grading System: A Technical Review. International Journal of Computer Applications. 2013; 81(16): 29-39. doi: 10.5120/14209-2455
44. Uganda Bureau of Statistics. 2020 Statistical Abstract. Available online: https://www.ubos.org/wp-content/uploads/publications/11_2020STATISTICAL__ABSTRACT_2020.pdf (accessed on 1 March 2024).
45. Kunes R, Bartos P, Iwasaka GK, et al. In-Line Technologies for the Analysis of Important Milk Parameters during the Milking Process: A Review. Agriculture. 2021; 11(3): 239. doi: 10.3390/agriculture11030239
46. Kakani V, Nguyen VH, Kumar BP, et al. A critical review on computer vision and artificial intelligence in food industry. Journal of Agriculture and Food Research. 2020; 2: 100033. doi: 10.1016/j.jafr.2020.100033
47. Corbett J. How Artificial Intelligence Improves Agricultural Productivity and Sustainability: A Global Thematic Analysis. 2020; 3: 5202–5211.
48. Ahikiriza E, Wesana J, Gellynck X, et al. Context Specificity and Time Dependency in Classifying Sub-Saharan Africa Dairy Cattle Farmers for Targeted Extension Farm Advice: The Case of Uganda. Agriculture. 2021; 11(9): 836. doi: 10.3390/agriculture11090836
49. Kasozi KI. Near-infrared spectroscopy for rapid prediction of fat, protein, and lactose contents in raw milk. Food Chemistry. 2017; 221: 1256-1262.
50. Agyekum AA. Automation and control systems in meat processing and packaging: Current insights. Food Control. 2015; 55: 1-13.
51. Muyanja CMBK. Automation and control systems in the dairy industry: A review. Journal of Food Science and Technology. 2017; 54(10): 2997-3010.
52. Brown M. Smart Farming-Automated and Connected Agriculture. [web post] Available online: https://www.engineering.com/DesignerEdge/DesignerEdgeArticles/ArticleID/16653/Smart-FarmingAutomated-and-Connected-Agriculture.aspx (accessed on 19 April 2019).
53. IFC. Access to Finance for Smallholder Farmers: Learning from the Experiences of Microfinance Institutions in Latin America. Washington DC: International Finance Corporation. The World Bank Group. Available online: https://www.ifc.org/wps/wcm/connect/071dd78045eadb5cb067b99916182e35/A2F+for+Smallholder+Farmers-Final+English+Publication.pdf?MOD=AJPERES (accessed on 24 May 2019).
54. Kasekende L. Louis Kasekende: Deputy Governor, Bank of Uganda. At the High-Level Meeting on Agricultural Financing in Uganda, Kampala. Available online: https://www.bis.org/review/r161020b.pdf (accessed on 24 May 2019).
55. Wagan SA, Jingdong L, Shuanxi X, et al. Significance of Agricultural Finance in Agricultural and Rural Development of Pakistan “A Case Study of Qambar Shahdadkot District”. Research Journal of Finance and Accounting. 2016; 7(9): 89-94.
56. Aleksandrova M. IoT in Agriculture: 5 Technology use cases for smart farming (and 4 Challenges to consider). Available online: https://easternpeak.com/blog/iot-in-agriculture-5-technology-use-cases-for-smart-farming-and-4-challenges-to-consider/ (accessed on 28 May 2019).
57. UIRI. Industrial Automation Project. Technology Development Center. Available online: https://www.uiri.go.ug/content/technology-development-center (accessed on 20 July 2023).
58. Lunner-Kolstrup C, Hörndahl T, Karttunen JP. Farm operators’ experiences of advanced technology and automation in Swedish agriculture: a pilot study. Journal of Agromedicine. 2018; 23(3): 215-226. doi: 10.1080/1059924x.2018.1458670
59. Ochwa-Echel J. Private universities in Uganda: issues and challenges. International Journal of Education and Social Science. 2016; 3(3): 7-18.
60. Antle JM, Jones JW, Rosenzweig CE. Next generation agricultural system data, models and knowledge products: Introduction. Agricultural Systems. 2017; 155: 186-190. doi: 10.1016/j.agsy.2016.09.003
61. Wolfert S, Ge L, Verdouw C, Bogaardt MJ. Big data in smart farming–a review. Agricultural Systems. 2017; 153, 69-80.
62. Gillwald A, Mothobi O, Ndiwalana A, Tusubira F. The state of ICT in Uganda. Available online: https://researchictafrica.net/wp/wp-content/uploads/2019/05/2019_After-Access-The-State-of-ICT-in-Uganda.pdf (accessed on 20 August 2021).
63. MoICT. The National Broadband Policy. Kampala: Ministry of Information, Communication Technology and National Guidance. Available online: https://www.ucc.co.ug/wp-content/uploads/2017/09/National-Broadband-Policy-2018_Final.pdf (accessed on 24 May 2019).
64. Mutungi F, Baguma R. Use of mobile technologies in monitoring delivery of public health services in Uganda. In: Proceedings of the 6th International Conference on M4D Mobile Communication Technology for Development- M4D 2018; 15-16 November 2018; Kampala, Uganda.
65. UN Foundation and ASD. Health facility energy needs assessment: Uganda country summary report. Available online: http://energyaccess.org/wp-content/uploads/2016/01/Annex-Nyarugote-Uganda-facility-report.pdf (accessed on 15 April 2019).
66. GET FiT Uganda. Annual report 2017. Available online: https://www.getfit-uganda.org/app/download/29825733/GET-FiT+Annual+Report+2017.pdf (accessed on 13 April 2019).
67. Nsabagwa M, Byamukama M, Kondela E, et al. Towards a robust and affordable Automatic Weather Station. Development Engineering. 2019; 4: 100040. doi: 10.1016/j.deveng.2018.100040.
68. Udimal TB, Jincai Z, Mensah OS, Caesar AE. Factors Influencing the Agricultural Technology Adoption: The Case of Improved Rice Varieties (Nerica) in the Northern Region, Ghana. Journal of Economics and Sustainable Development. 2017; 8(8): 137-148.
Refbacks
- There are currently no refbacks.
Copyright (c) 2024 Ahamada Zziwa, Joshua Wanyama, David Matsapwe, Simon Savio Kizito, Tadeo Mibulo, Emmanuel Baidhe
License URL: https://creativecommons.org/licenses/by/4.0/
This site is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
Prof. Zhengjun Qiu
Zhejiang University, China
Cheng Sun
Academician of World Academy of Productivity Science; Executive Chairman, World Confederation of Productivity Science China Chapter, China
Processing Speed
-
-
-
- ＜5 days from submission to initial review decision;
- 64% acceptance rate
-
-
Modern agricultural technology is evolving rapidly, with scientists collaborating with leading agricultural enterprises to develop intelligent management practices. These practices utilize advanced systems that provide tailored fertilization and treatment options for large-scale land management.
This journal values human initiative and intelligence, and the employment of AI technologies to write papers that replace the human mind is expressly prohibited. When there is a suspicious submission that uses AI tools to quickly piece together and generate research results, the editorial board of the journal will reject the article, and all journals under the publisher's umbrella will prohibit all authors from submitting their articles.
Readers and authors are asked to exercise caution and strictly adhere to the journal's policy regarding the usage of Artificial Intelligence Generated Content (AIGC) tools.
Asia Pacific Academy of Science Pte. Ltd. (APACSCI) specializes in international journal publishing. APACSCI adopts the open access publishing model and provides an important communication bridge for academic groups whose interest fields include engineering, technology, medicine, computer, mathematics, agriculture and forestry, and environment.
