BRIN develops AI-based research to identify superior chili phenotypes

Jakarta (ANTARA) - The National Research and Innovation Agency (BRIN) is developing research to identify superior chili varieties' phenotypes more quickly, objectively, and consistently using artificial intelligence (AI) and computer vision.

Eka Prakasa, Head of the BRIN Data Science and Information Research Center, stated in an online discussion in Jakarta on Wednesday that applying the technology can accelerate the variety characterization process, which previously relied on manual observation.

"In the long term, the technology is expected to strengthen Indonesia's digital agricultural ecosystem, increase national seed productivity and competitiveness, and support food security through the use of data-driven technology," he said.

Prakasa said applying the technology supports seed purity testing, assists selection in plant breeding programs, and increases efficiency in variety certification.

Furthermore, he continued, the AI-based system can be used as a decision-making tool by researchers, breeders, seed producers, and government agencies, thereby making the process of developing superior varieties more effective.

Meanwhile, BRIN researcher Wiwin Suwarningsih stated that the need for fast, accurate, and consistent variety identification is increasing to support plant breeding, seed certification, plant variety protection, and germplasm management.

According to her, developments in AI, particularly computer vision and deep learning, open up opportunities for automated plant phenotype identification through analyzing leaf images and other morphological characteristics.

"The technology is capable of extracting visual patterns that are difficult to recognize manually, thereby increasing the accuracy and efficiency of the identification process," Suwarningsih said.

"Therefore, the research was conducted to develop an AI-based chili phenotype identification system that can support the digitalization of the chili variety characterization process in Indonesia," she added.

Suwarningsih explained that the goal of the research is to produce a fast, objective, accurate, and consistent chili variety identification method.

Furthermore, the research is expected to integrate phenotype information with AI technology to support the automated variety characterization process.

"It can also serve as a recommendation for the application of AI technology to support plant breeding, seed purity testing, varietal certification, and plant variety protection in Indonesia," Suwarningsih said.

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Translator: Sean Filo Muhamad, Cindy Frishanti Octavia

Editor: Arie Novarina

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