Volatile compounds (VOCs) present in the oil extracted from yellow horn seeds were first analyzed using GC-IMS and GC-O-MS at varying roasting temperatures. A total of 97 VOCs were detected using GC-IMS, while 77 were tentatively identified using GC-O-MS. Moreover, both methods allowed the identification of 24 VOCs, of which the type of aldehydes is the most abundant. Combining the results of GC-IMS, GC-O-MS, OAVs, and VIP, it was concluded that hexanal, 2,5-dimethylpyrazine, heptanal, 2-pentylfuran, 1-hexanol, and 1-octen-3-ol were the key aroma compounds. The PLS-DA and OPLS-DA models have demonstrated the ability to discriminate between different oil roasting temperatures with high accuracy. The roasting temperature of 160 °C was found to yield the highest content of main aroma substances, indicating its optimality for yellow horn seed oil production. These findings will prove beneficial for optimizing industrial production and enhancing oil aroma control.

Energy transport in low-dimensional systems or systems with long-range interactions shows unusual properties not observed in conventional three-dimensional materials. Trapped linear ion chains have been proposed as an ideal platform to study such phenomena, but many predicted features have not been demonstrated yet and the existing experiments mainly focus on the weak excitation limit where the dynamics can be described by linearized phonon modes. Here, we study the energy transport in a chain of ${}^{174}\mathrm{Yb}^{+}$ ions using a focused heating laser beam. Nontrivial effects are observed such as a nonmonotonic energy distribution with reflection symmetry, oscillatory heating dynamics, and a change in the heating pattern due to the competition between the external driving and interion coupling. Our work deepens the understanding about transport in low-dimensional systems and also provides guidelines for the sympathetic cooling of long ion chains, with applications in quantum information processing and precision measurement.