Research Collaboration Advances Climate Prediction for Thailand's Palm Oil Industry

Kasetsart University in Bangkok, Thailand, has partnered with Utah State University in a study recently published in Environmental Research Letters that aims to advance climate prediction capabilities to support Thailand's thriving palm oil industry.

Led by Parichart Promchote from Kasetsart University's Department of Agronomy, the research sheds new light on the crucial role of climatic conditions in oil palm productivity, highlighting the need for reliable prediction methods.

Authors of the study point out that palm oil is an important global commodity and Thailand's palm oil industry is a major economic force in the country. The industry has experienced average annual growth of 5% in recent years, driving economic development, job creation and increased government revenue. However, the industry faces challenges due to the influence of climatic factors, especially precipitation patterns. The research conducted by Promchote and her team aims to address these challenges and optimize palm oil yield through accurate seasonal predictions.

"Our investigation into the relationship between palm oil yield and climate underscores the potential of seasonal prediction as a valuable tool for securing the future of southern Thailand's palm oil industry,” Promchote said. “By using advanced models that integrate local meteorological factors with large-scale climate drivers, stakeholders can anticipate palm oil production more accurately, refine management strategies, and contribute to the long-term success and sustainability of the industry."

USU climate scientist Professor Simon Wang co-authored the study and emphasizes the significance of the collaborative research.

"Despite progress in El Niño-Southern Oscillation (ENSO) prediction, there is still a persistent gap between our understanding of climatic influences and reliable prediction methods,” he said. “Our study highlights the importance of bridging this gap and advocates for developing dynamic seasonal prediction models tailored for palm oil production. These models can enhance the industry's resilience and sustainability in the face of climate variability and change."

The study emphasizes the impact of El Niño events on palm oil productivity in Thailand, aligning with research in neighboring Malaysia. Wang added that ENSO events significantly influence palm oil yield, and advancements in ENSO prediction offer opportunities to enhance palm oil production management.

“By developing dynamic models to predict ENSO and Thailand's climate, we can incorporate local and global climate variables to improve yield predictions," Wang said.

The study’s findings underscore the need for further research and development of advanced models that can integrate comprehensive observational data, enhance the resolution and accuracy of predictions, and capture the complex interactions affecting palm oil yield.

Thailand's commitment to sustainable palm oil production is also highlighted in the research. The government has set a target of achieving 100% sustainable palm oil production by 2030, aligning with global efforts to promote environmental stewardship. As the palm oil industry continues to grow and evolve, investments in research and the increasing demand for sustainable palm oil provide a positive outlook for the future of Thailand's palm oil sector.

The collaborative research conducted by Kasetsart University and Utah State University paves the way for a more resilient and sustainable palm oil industry in Thailand, Promchote said.