Design and Fabrication of an Automated Potato Tuber Germination Machine
Abstract
Potato is a staple food for millions of people around the world. However, the germination of potato tubers is a complex process that is sensitive to a variety of environmental factors. This can make it difficult to achieve faster and consistent germination rates, which could lead to losses in crop yield. To overcome difficulties farmers face in tuber sprouting, researchers are increasingly focusing on automated solutions for improving potato tuber germination. Automation can be used to monitor and control the environmental conditions in which potato tubers are germinated, ensuring that they are optimal for germination. The objective of this research was to design and fabricate an automated potato tuber germination machine. The machine was equipped with Arduino Uno Rev 3 with sensors to monitor and control the environmental conditions in which the potato tubers were germinated. An algorithm to control the temperature to remain within 16 -30 and humidity range of 80% - 95% for optimum tubers germination was developed for the Microcontroller. The lighting characteristic of germination chamber was done with Far-red light Led. The primary results showed that the algorithm controlled the temperature and humidity for optimum tuber germination, indicating that the automated tuber germination machine functioned well in monitoring and controlling the sensors and actuators. Both the Shangi and Unica potato varieties sprouted faster, as evidenced by the significant difference observed between these two varieties in the machine compared to those grown by the farmers’. The findings of this research will have the potential to improve the germination rates of potato tubers as the sprouting rate was greatly improved, leading to increased crop yields.
Fields of Study & Subjects
Smart Agriculture and AI
Agricultural Engineering and Mechanization
Arduino and IoT Applications
Publication details
- Journal / source
- Africa journal of technical and vocational education and training.
- Volume
- 11
- Issue
- 1
- Pages
- 125–139
- Publication date
- 28 January 2026
- Language
- EN