Development of Decision Support System for Selecting Non-Destructive Durian Quality Inspection Technologies: An Integrated Approach for Elevating Thai Durian Industry to International Standards

The Thai durian industry is one of most important agricultural exports of the country, evidenced by its rapid growth and expanding demand in international markets. De-velopment of more advanced inspection technologies is therefore crucial for the in-dustry to ensure competitiveness toward global standards. This research aimed to de-velop an integrated decision support system (DSS) for selecting appropriate non-destructive testing (NDT) technologies for durian quality inspection. The study integrated Multi-Criteria Decision Analysis (MCDA), Analytic Hierarchy Process (AHP), Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), and Techno-Economic Analysis (TEA) to evaluate five NDT technologies, including Near-Infrared Spectroscopy (NIR), Hyperspectral Imaging (HSI), Acoustic Response Analysis (RSA), Electrical Impedance Spectroscopy (EIS), and X-ray Imaging. The evaluation criteria consisted of three dimensions: technical performance, economic viability, and operational feasibility. Results revealed that Near-Infrared Spectroscopy (NIR) has the highest suitability for large-scale industrial implementation, achieving the highest weighted score (4.57) and ranked first in the TOPSIS analysis with a Closeness Coefficient of 0.91. The findings suggested that selection of NDT technologies must balance technical accuracy with economic and operational viability. The proposed DSS framework can support the de-velopment of smart agro-industry systems and contribute to the sustainable advance-ment of Thailand’s durian export sector.