Makinei L V, Hazarika M K
Department of Food Engineering and Technology, Tezpur University, Tezpur, India.
Curr Res Food Sci. 2022 Jun 11;5:1038-1046. doi: 10.1016/j.crfs.2022.05.015. eCollection 2022.
The flavour network-based analysis of food pairing was applied to the sub-cuisines from Northeast India to examine the food pairing behaviour in terms of the co-occurrence of ingredients with the shared flavouring compounds in food recipes. The method applied was based on an existing procedure in computational gastronomy, wherein the preference for positive pairing is attributed to dairy-based ingredients and negative pairing behaviour is attributed primarily to spice based ingredients. Recipe data was subjected to backbone extraction, projection of the recipe-ingredient-compound tri-partite network, and analysis for prevalence and authenticity of ingredients. Further, the average flavour sharing index of the cuisine was determined with the help of the flavour profiles of the ingredients. The extent of deviation for the original cuisine in comparison to a random cuisine was used to determine the degree of bias in the food pairing behaviour, with the sign as the indicator of the nature of pairing. The analysis identified the ingredients responsible to exhibit a positive or negative pairing pattern in the sub-cuisines. The ingredients from the spice category were the most prevalent and have resulted in the negative pairing behaviour in the cuisines. This role of spices in effecting a negative pairing behaviour is in line with the earlier reports for other Indian regional cuisines.
基于风味网络的食物搭配分析应用于印度东北部的地方菜系，以根据食物食谱中配料与共享调味化合物的共现情况来研究食物搭配行为。所应用的方法基于计算美食学中的现有程序，其中对正向搭配的偏好归因于乳制品类配料，而负向搭配行为主要归因于香料类配料。食谱数据经过主干提取、食谱 - 配料 - 化合物三方网络的投影以及配料的流行度和真实性分析。此外，借助配料的风味特征确定了该菜系的平均风味共享指数。将原始菜系与随机菜系相比的偏差程度用于确定食物搭配行为中的偏差程度，符号作为搭配性质的指标。该分析确定了在地方菜系中呈现正向或负向搭配模式的配料。香料类配料最为常见，并导致了这些菜系中的负向搭配行为。香料在产生负向搭配行为方面的这种作用与其他印度地方菜系的早期报道一致。
