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Thailand: AI-Powered Detection for Strawberry Disease

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In the healthcare industry, technology has become a key element in assisting healthcare professionals with diagnosing patients before determining treatment steps. This advancement provides high accuracy in determining the patient’s health condition, enabling more objective and precise medical interventions.

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Using technology in the healthcare industry as a foundational idea opens opportunities to be applied in the agricultural sector. This concept can allow for the implementation of similar technological solutions to assist farmers in diagnosing and managing their crop conditions more effectively.

By leveraging technological innovations, farmers can obtain more accurate information about plant health, facilitating more precise and efficient decision-making in agricultural management, particularly in Thailand.

Thailand has been consistently advancing its agricultural sector through the strategic integration of digital technology. In this ongoing phase of agricultural modernisation, Thailand has now undertaken a pioneering initiative focusing on cultivating strawberries.

Strawberry is one of Thailand’s economically significant crops, providing income for farmers in the northern region through the sale of fresh fruits, processed products, and revenue generated by tourism activities, such as strawberry picking. Strawberries in Thailand are primarily grown in Chiang Mai’s and Chiang Rai’s northern provinces, where the cool climate from December to March allows for production.

However, one of the challenges strawberry farmers face is diseases that can severely impact production if addressed promptly. Therefore, Thailand has to undertake an approach towards early detection as a pivotal strategy in effectively managing these diseases.

National Electronics and Computer Technology Centre under the National Science and Technology Development Agency (NECTEC-NSTDA), in collaboration with the Royal Project Foundation, developed the ‘Strawberry Disease Bot.’ This chatbot facilitates the diagnosis of strawberry diseases through images and provides recommendations for disease control.

Mr Wasin Sinthupinyo, a researcher associated with the Artificial Intelligence Research Group at NECTEC, expounded upon the project’s inception. It is noteworthy that Mr Wasin’s team, in collaboration with Kasetsart University, had previously pioneered the development of the Rice Disease Bot, an innovative image-based chatbot service designed for diagnosing diseases in rice crops. The success and media recognition the Rice Disease Bot garnered prompted the Royal Project Foundation, a non-profit organisation built by King Bhumibol Adulyadej for his charitable initiatives and research, to approach the research team with keen interest.

The foundation expressed interest in exploring the creation of a disease diagnosis chatbot service tailored for temperate crops, aiming to provide crucial support to farmers in the northern region. This collaborative effort signifies a strategic expansion of the research team’s capabilities, highlighting the increasing significance of harnessing artificial intelligence for advancements in agriculture.

The decision to focus on strawberries for research and development was influenced by their economic importance and the existence of a comprehensive database. The resulting Strawberry Disease Bot is now poised for testing by farmers, a phase expected to refine its performance further.

Operable on one of the instant messaging application platforms, the Strawberry Disease Bot offers user-friendly functionality. Farmers can capture images of diseased strawberry plants and submit them via an instant messaging application platform. These images are then transmitted to the cloud system, where artificial intelligence employs deep learning for disease diagnosis. Within 3-5 seconds, the results and recommendations for disease control are relayed back to the farmers.

Currently, the chatbot can diagnose five diseases affecting strawberry cultivation in Thailand: anthracnose, leaf blight, grey mould, powdery mildew, and leaf spot. Although the system currently achieves an accuracy level of 60-70%, anticipations of improvement exist as more data is gathered through active farmer participation.

Farmers are assured of the chatbot’s reliability by acknowledging the initial modest accuracy since technicians at the Royal Project Foundation are available to verify results. Emphasising the importance of early detection in disease management and reducing chemical usage, Mr Wasin highlighted that increased farmer utilisation would contribute more images to the database, enhancing the overall diagnostic performance.

In the future, the transformative impact of digital technology on agriculture in Thailand extends beyond disease diagnosis. Precision farming, IoT-enabled devices, and smart agriculture practices will likely become more prevalent, offering farmers greater control and efficiency in managing their crops. These advancements not only enhance productivity but also contribute to resource optimisation and the overall resilience of the agricultural ecosystem.

The Strawberry Disease Bot is an exemplary application of digital technology in agriculture, embodying the modernisation of farming practices and aligning with the principles of the Bio-Circular-Green Economy (BCG) model. Accessible through a QR code, the chatbot represents a significant stride towards sustainable and technologically-driven agricultural practices.


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