Laboratory of Nanomaterials, Skolkovo Institute of Science and Technology, 3 Nobel St., 121205 Moscow, Russia.
Center for Computational and Data-Intensive Science and Engineering, Skolkovo Institute of Science and Technology, 3 Nobel Str., 121205 Moscow, Russia.
Food Chem. 2021 May 30;345:128747. doi: 10.1016/j.foodchem.2020.128747. Epub 2020 Dec 1.
Determination of food doneness remains a challenge for automation in the cooking industry. The complex physicochemical processes that occur during cooking require a combination of several methods for their control. Herein, we utilized an electronic nose and computer vision to check the cooking state of grilled chicken. Thermogravimetry, differential mobility analysis, and mass spectrometry were employed to deepen the fundamental insights towards the grilling process. The results indicated that an electronic nose could distinguish the odor profile of the grilled chicken, whereas computer vision could identify discoloration of the chicken. The integration of these two methods yields greater selectivity towards the qualitative determination of chicken doneness. The odor profile is matched with detected water loss, and the release of aromatic and sulfur-containing compounds during cooking. This work demonstrates the practicability of the developed technique, which we compared with a sensory evaluation, for better deconvolution of food state during cooking.
食物的熟度判断对于烹饪行业的自动化来说仍然是一个挑战。烹饪过程中发生的复杂物理化学过程需要几种方法的组合来进行控制。在这里，我们利用电子鼻和计算机视觉来检查烤鸡的烹饪状态。热重分析、差分迁移率分析和质谱分析被用来深入了解烧烤过程。结果表明，电子鼻可以区分烤鸡的气味特征，而计算机视觉可以识别鸡肉的变色。这两种方法的结合对鸡肉熟度的定性判断具有更高的选择性。气味特征与检测到的水分损失相匹配，并且在烹饪过程中释放出芳香族和含硫化合物。这项工作展示了所开发技术的实用性，我们将其与感官评价进行了比较，以更好地分解烹饪过程中的食物状态。
