AI Drone for Sweetness Assessment in Cane Farms: Promoting Thai Agricultural Innovation & Advanced International Standard

Khon Kaen University, with cooperation of private and public sectors, has lately innovated a drone to detect sweetness of sugarcane and assess the product. At the press conference on Field Practice Solutions (FPS) Project, chaired by the acting rector of Khon Kaen University Assoc. Prof. Dr. Chanchai Panthongwiriyakul and the head of the project Assoc. Prof. Dr. Khwantri Saengprachathanarug said that the newly invented drone aimed to develop a model platform for less capital expenses but high product amount and upgraded quality of Thailand’s agricultural industries.

Assoc. Prof. Dr. Khwantri Saengprachathanarug

“Sugarcane’s Sweetness Assessment” is a robotic platform project for precision-dependent agriculture aiming to create a virtual large farm under the economic spearhead framework of National Council for Higher Education, Science, Research and Innovation Policy (NCHESRIT), National Science and Technology Development Agency (NSTDA), Khon Kaen University and private companies. To develop a non-driver aviation, collaboration was created with HG Robotics Co. Ltd., Global Crop Co. Ltd., Baanrai Sugar Industry Co. Ltd., Saraburi Sugarmill Co. Ltd. and Kaset Thai International Sugar Corporation Public Company Limited.

Assoc. Prof. Dr. Chanchai said that Khon Kaen University realized importance of innovation development and promotion of academic advancement among enterprises as well as cooperation with private and public sectors to improve commercially-based innovations so that they are nationally and internationally recognized. Thailand has higher capital cost of production than other countries, so reduction of the cost requires solution or as highly effective forms of resource management as possible.

Assoc. Prof. Dr. Chanchai Panthongwiriyakul

Development of the above-mentioned drone is a capacity that can mobilize the new S-curve in terms of reduction of production capital cost and upgrading Thailand’s agricultural management. In 2016, the research lab of Khon Kaen University realized how important the preparation for precision-dependent agriculture is in actual application. This includes technological development in Thailand and human resources

development of precision-dependent agriculture. Consequently, a research was carried out to predict production according to images taken by the drone.

Also, HG Robotics Co. Ltd., which is a company working on improvement of non-driver aviation for both hardware and software, as well as the Global Corps. Co. Ltd., which sells and provides services on agricultural chemical substances, have jointly developed explorer and spraying drones as well as initiated academic cooperation with a research lab since 2017.

Assoc. Prof. Dr. Khwantri added that, according to experiences on real-life technology application, major problems included how to use images taken from drones to reduce capital cost while increase agricultural products. This necessitates a system able to processing pictorial results and managing big data until it becomes decision making data so that both farmers and concerned people understand and use the results for decision-making on providing fertilizer, water management and formulating a timetable for high-product harvesting with low capital cost.

The Field Practice Solutions (FPS) will be useful in reducing costs, value and high efficiency in which of development in non-driver aviation for sugarcane’s sweetness assessment. The cost of the project is lower 20 times than competitor services in foreign countries as well as the most of accurate assessment, which is no more and no less than 1 in current services. To bring non-driver aviation or drone for advance with satellite imagery software, that owning by private, it could be analysed the sweetness, plant growth, plant disease, including one hundred thousand of sugarcane farms data analysis with fast and accurate time.

“Academics at Khon Kaen University are responsible for analysing satellite photographs in terms of algorithm. In other words, it is a methodology on analysis of plants’ photosynthesis and water absorption to come up with results of color intensity and proper sweetness, which is no more and no less than 1. The precision is highly correct due to AI robots which can recognize well where is soil, sugarcane and how high, sweet and healthy is the cane. With the robots, nothing is never easier,” explained Assoc. Prof. Dr. Khwantri.
In terms of responses from Thailand’s sugar mills and farm owners, Assoc. Prof. Dr. Khwantri said that they were interested in the said innovations because of problems on sugarcane prices and prediction about product harvest which costs higher than in other countries. As a result, everyone needs new technology to solve the problems and reduce expenses while increasing profits to factories and farm owners themselves.

The goal of the FPS project is to provide 3 types of services for which one can pay in an annual basis. The first one includes Farm Monitoring and Mapping Service (FMMS). It provides services on aerial detection of sugarcane farms from a drone in terms of product amount, sweetness, white leaf disease and needs for fertilizer.

The second type of service is Farm Robotic Solution (FRS). It focuses on designing and installing automatic or semi-automatic control systems and improving commanding AI.

The third type of service is Farm Business Intelligent (FBI). It refers to enabling the AI to plan and adjust work under current situation automatically, such as work on harvest and transport or providing fertilizer to all plants.

Regarding other research on development of AI innovations for sugarcane farms, Assoc. Prof. Dr. Khwantri said that Khon Kaen University had at present on-going research to improve AI innovations for assessing sugarcane products (tons per Rai), detecting white leaf disease and probing nutritional quality of soil for taking care of sugarcane before planting until after harvesting it. Doing so will facilitate sugar mills to provide trucks to transport sugarcane to the factories, hence profits for both farm owners and factories themselves.

In addition, thanks to support and encouragement of private and public sectors, researchers and developers would like to improve more technology on sweetness detection not only among sugarcane but for all types of plants like corn, cassava or rice. Doing so will promote AI technology to international standard.

In conclusion, to promote academic advancement among enterprises as well as cooperation with private and public sectors, the FPS project is useful for the country in terms of improvement of future technology and innovations of both upcoming 5G and AI systems. Farmers tend to be able to plant and manage sugarcane in a farm by themselves. The AI will soon become tangible and much favoured along with rapid development in various aspects.

For further information, please contact

Assoc. Prof. Dr. Khwantri Saengprachathanarug, the head of the Field Practice Solutions (FPS) project, Department of Agricultural Technology, Faculty of Agriculture, Khon Kaen University,
tel. 043 362148 or e-mail: khwantri@kku.ac.th.

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