# An Ontology-Based Expert System for Rice Disease Identification and Control Recommendation
## 5 RiceMan: Ontology and System Evaluation
### RiceMan Application Usability Evaluation  
Based on the proposed RiceMan system architectural design, the application was developed with the UI in both English and Thai languages. The usability evaluation was then conducted with two groups of participants: senior-year agricultural students and junior agromists. The first group of participants were five senior-year undergraduate students (Chulalongkorn University, School of Agriculture Resources) who were knowledgeable in rice diseases and paddy insects from their degree program's coursework, but did not have direct experience in real-world practice. The students used RiceMan via their mobile phones to complete four provided tasks. For tasks #1 and #2, the participants were asked to identify rice diseases from a given single observation and multiple observations, respectively. For tasks #3 and #4, they were asked to identify biological and chemical controls from the returned diseases. After their completion, the participants provided their opinions by answering ten questions based on System Usability Scale (SUS) [49] (cf. Table A3 in the Appendix A for more information). The average SUS score among the students was 70.5. Since it was above 68, then RiceMan was acceptable from the agricultural students' viewpoints. The participants were interested in applying ontology reasoning techniques to identify diseases and treatments. The feedback shows that the application can support their study and improve the search in many real-life use cases. Since they had experience in farm work, they believed that the application can benefit the farmers, especially those interested in using new technologies to support their works. However, most users were facing difficulties with using the application due to some graphical interfaces.  
The second group of participants were ten junior agromists from Ayutthaya Rice Research Center, who worked on transferring technologies to farmers, focused on rice variety research and development, and advised farmers. Similarly, they performed the same four tasks on their mobile phones, and then answered a SUS questionnaire. The average SUS score obtained was 64.3, close to the standard average of SUS.  
Although the score was less than the standard average, the participants agreed that the application could significantly help them identify diseases and treatments, compared with searching through manuals and websites. It shows that RiceMan is applicable for use from the participants' viewpoints since it offers helpful and sufficient functionalities for real-life situations even though the current version seems challenging for farmers to use. We summarize our lessons learned as follows:  
**UI/UX design:**  
1. The design of the observation data input form should be improved to make it more human-friendly for use and to support various kinds of abnormality appearances.
2. Since RiceMan is built as a responsive web application, its input form varies among iOS and Android devices. Here, the participants who used an iOS device faced some difficulty as the input form was a picker instead of a drop-down box.
3. The treatment names shown on RiceMan should be italicized for easy-looking.  
**Displayed information:**  
1. The participants preferred to have photos of plant parts to support the observation data input forms and photos of diseases and insects on the result page.
2. The control names should be translated into Thai and provided with the product/brand names.
3. Some agromists were specialists in insects. Therefore, they preferred RiceMan to contain more knowledge of paddy insects.