Abstract：
We compared the performance of three food categorisation metrics in predicting palatability (taste pleasantness) using a dataset of 52 foods, each rated virtually (online) by 72-224 participants familiar with the foods in question, as described in Appetite 193 (2024) 107124. The metrics were nutrient clustering, NOVA, and nutrient profiling. The first two of these metrics were developed to identify, respectively: \'hyper-palatable\' foods (HPFs); and ultra-processed foods (UPFs), which are claimed to be \'made to be hyper-palatable\'. The third metric categorises foods as high fat, sugar, salt (HFSS) foods versus non-HFSS foods. There were overlaps, but also significant differences, in categorisation of the foods by the three metrics: of the 52 foods, 35 (67%) were categorised as HPF, and/or UPF, and/or HFSS, and 17 (33%) were categorised as none of these. There was no significant difference in measured palatability between HPFs and non-HPFs, nor between UPFs and non-UPFs (p ≥ 0.412). HFSS foods were significantly more palatable than non-HFSS foods (p = 0.049). None of the metrics significantly predicted food reward (desire to eat). These results do not support the use of hypothetical combinations of food ingredients as proxies for palatability, as done explicitly by the nutrient clustering and NOVA metrics. To discover what aspects of food composition predict palatability requires measuring the palatability of a wide range of foods that differ in composition, as we do here.
摘要：
我们使用52种食物的数据集，比较了三种食物分类指标在预测适口性（味道愉悦）方面的表现，每个人都有72至224名熟悉相关食物的参与者虚拟(在线)评分，如食欲193(2024)107124中所述。指标是营养聚类，NOVA,和营养分析。前两个指标是为了识别，分别是：“超美味”食品(HPFs)；和超加工食品(UPFs)，据称“被制成超级美味”。第三个指标将食物归类为高脂肪，糖,盐（HFSS）食品与非HFSS食品。有重叠，但也有显著的差异，根据三个指标对食物进行分类：在52种食物中，35人(67%)被归类为HPF，和/或UPF，和/或HFSS，17人(33%)被归类为这些都不是。HPF和非HPF之间测量的适口性没有显着差异，也不在UPFs和非UPFs之间（p≥0.412）。HFSS食品比非HFSS食品更可口（p<0.049）。这些指标都没有显著预测食物奖励(想要吃)。这些结果不支持使用假设的食品成分组合作为适口性的代理，正如通过营养素聚类和NOVA指标明确完成的那样。为了发现食物成分的哪些方面可以预测适口性，需要测量各种不同成分的食物的适口性。就像我们在这里一样。
