Peanut oil is favored by consumers due to its rich nutritional value and unique flavor. This study used headspace solid-phase microextraction (HS-SPME) combined with gas chromatography (GC) and gas chromatography–mass spectrometry (GC-MS) to examine the differences in the peanut oil aroma on the basis of variety, roasting temperatures, and pressing components. The results revealed that the optimal conditions for extracting peanut oil were achieved through the use of 50/30 μm DVB/CAR/PDMS fibers at 60 °C for 50 min. The primary compounds present in peanut oil were pyrazines. When peanuts were roasted, the temperature raised from 120 °C to 140 °C and the content of aldehydes in peanut oil increased; however, the content of aldehydes in No. 9 oil at 160 °C decreased. The components of peanut shell oil varied depending on the peanut variety. The most marked difference was observed in terms of the main compound at the two roasting temperatures. This compound was a pyrazine, and the content increased with the roasting temperature in hekei oils. When the roasting temperature was lower, No. 9 oil contained more fatty acid oxidation products such as hexanal, heptanal, and nonanal. When the roasting temperature increased, No. 9 oil contained more furfural and 5-methylfurfural. Heren oil was easier to oxidize and produced nonanal that possessed a fatty aroma.

Arachis hypogaea L. ‘Tainan 14’ has purple skin characteristics. This study investigated the effects of different materials (shelled or unshelled peanuts) and temperatures (120 or 140 °C) on the properties of extracted peanut oil. The results show that its antioxidant components (total flavonoid, α–tocopherol, and γ-tocopherol) and oxidative stability were mainly affected by the roasting temperature (p < 0.05). Fifty-eight volatile compounds were identified by peanut oil oxidation and divided into three main groups during the roasting process using principal component analysis. The volatile formation changes of different materials and temperatures were assessed by agglomerative hierarchical clustering analysis. These results provide useful reference information for peanut oil applications in the food industry.