The key factor in durian fruit trading is ripeness. Several studies have been conducted on non-destructive durian maturity classification using near-infrared (NIR) spectroscopy. However, most of these studies manually determined the most accurate measurement position, which was the durian's main fertile lobe center. This research aims to automate the stage of detecting this position of the durian by using UNet segmentation method, which leverages differences in rind texture between the center of the main fertile lobe and other areas (lobe grooves and stems), prior to conducting NIR measurements. The rough and non-uniform surface of the durian rind presents a significant challenge for segmentation. However, the large size of the durian spines in the main fertile lobe serves as an identification characteristic for the segmentation model. This study uses the Ri-6 durian in Vietnam as the sa...