Predictive Farming Platform to predict Thai agricultural products cover a whole country

Interviewee | Dr. Noppadon Khiripet, Senior Researcher
Knowledge Elicitation and Archiving Research Team, Data Science and Analytics Research Group
National Electronics and Computer Technology Center (NECTEC)

Agriculture plays a crucial role in Thailand’s economy. More than 30 percent of Thailand’s labor force (13.48 million people of a total labor force of 38.76 million people) works in agriculture. [1] The farm economy decreased by 3.3 percent in 2020 compared to in 2019. [2]

There are several factors that negatively impact Thailand’s agricultural industry. For one, the sector is highly dependent on predictable weather patterns. A prolonged drought or short rainy season can devastate farmland. Second, the practice of relying on a single crop or livestock — known as monoculture — leaves the sector vulnerable to pathogens and diseases. Third, an epidemic or pandemic, like Covid-19, can lead to sharp declines in domestic demand for food products and cause supply chain disruptions. And fourth, a global economic recession can lead to a decline in exports.

To help overcome these obstacles, technology will play an ongoing important role in agricultural development, with high investments necessary in plantation management. Agricultural technology — precision farming in particular — is an important technique in helping farmers increase productivity, yield and profits. Collecting and analyzing data will be very useful in order to effectively launch an efficient agricultural policy that focuses in part on precision farming.

The National Electronics and Computer Technology Center (NECTEC) sees precision farming as one of eight target development technologies. The agency has supported research projects to enhance efficient farming management, while continuously investing technology accessibility opportunities for large and small farmers.

NECTEC is currently using the analytics of precision farming to enhance the predictive farming platform being implemented throughout the country.

From precision farming to a predictive farming platform

According to the industry foresight innovation report 2016, a key principle of precision agriculture is the use of a variable rate application (VRA), a tool that allows farmers to apply fertilizer, water, chemicals, and seed at different rates across a field. VRA uses sensors that measure soil properties and crop characteristics that allow the farmer to make adjustments based on environmental factors. Therefore, plantation management must be distinctively suitable for specific crops that are rotated based on environmental conditions.

A well-developed plantation management system will interpret data collected by these sensors that will then suggest a proper crop to farmers. It also will control automated machines that can plant seeds and properly spray and water the fields, resulting in reduced labor costs and a better yield.

Data is at the heart of precision agriculture. The equipment needed to collect that data includes sensors, IoT, weather stations, satellites and drones, which then feeds data to artificial intelligence and data analytics technology.

The big data of precision farming technology is also a foundation that paves the way for crop prediction and precision farming development.

Predictive Farming Platform

Predictive farming is not new to Thailand. At the annual Royal Ploughing Ceremony, which heralds the start of the new rice-growing season, a sacred oxen predicts whether the year’s harvest will be bountiful or not. Although more traditional than scientific, the significance of and belief in the annual ceremony continues today.

A predictive farming platform embraces three major groups of data including weather, soil, and crop health through the use of remote and embedded sensors, and drones. Four benefits created by this technology are:

1. Crop yield prediction
Better crop yield predictions based on data measuring soil condition and water absorption levels, weather, and diseases as well as other factors related to crop growth.
2. Crop management
Better crop management, which helps farmers reach productivity targets through the automatization of applying water, fertilizers and other chemicals, ensuring proper inputs based on the soil and crop needs.
3. Crop recommendations
Crop recommendations can be made based on market demand and economic factors, cost, return and so forth.
4. Crop insurance
The use of crop yield data aids financial institutions in pinpointing agricultural interest rates by considering market demand vs. crop yields along with other factors.

However, the capability of predictive farming at the national level requires a great deal of resources, especially in technology. The NECTEC are collaborating with Thai and international partners in securing predictive farming technology such as high-performance computing technology, analytics, unmanned aerial vehicles (UAV) and cloud computing.

Target of the predictive farming platform

The predictive farming platform will provide a significant amount of data allowing the government to develop a more efficient farming policy that focuses on production, management, and budget allocation based on the needs of the market and the readiness and quality of farmland. This will enhance Thai farming production and food exports, help protect food security and lead to a better brand image for Thailand’s farming sector.

Precision farming data will be beneficial to the private sector for futures contracts, price control and special crop plantation — for example energy crops, such as sugarcane, cassava, palm, etc, in which fuel prices are an important factor in production planning.

The NECTEC fully hopes that the platform will become a starting point for developers and startup businesses in developing new products to help build the ecosystem of the Thai agriculture sector through the use of advanced technology.

Contact

Knowledge Elicitation and Archiving Research Team
Data Science and Analytics Research Group
National Electronics and Computer Technology Center (NECTEC)
Email : kea[at]nectec.or.th

References

[1] National Statistical Office. (2021). Thai Working Conditions Survey (December 2020). Retrieved from https://www.nso.go.th/
[2] Office of Agricultural Economics. (2020). Thailand Agricultural Economic Conditions in 2020 and Outlook for 2021. Retrieved from https://www.oae.go.th/