Dataset of Sensory Profiles RATA (Rate all that Apply) of two geographical regions in Mexico.
Description
This dataset provides a comprehensive sensory characterization of Tenate cheese, a traditional, artisanal Mexican product. Utilizing the Rate-All-That-Apply (RATA) methodology, sensory profiles were collected in March 2026 from a consumer panel consisting of 318 individuals across two distinct geographic and economic regions in Mexico: Aguascalientes (n=149) and the Guadalajara Metropolitan Area (n=169). We believe this data is highly relevant to the readership of Data in Brief due to its high quality and multifaceted utility:
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Steps to reproduce
This dataset contains detailed information about a sensory analysis conducted using the RATA (Rate-All-That-Apply) methodology. The study appears to compare sensory perceptions between two zones (likely Guadalajara - ZMG and Aguascalientes - AGS) regarding a food product (possibly dairy, given its attributes). The main tables are described below: 1. RATA Data (Main Table) This is the raw data source with 320 records and 22 columns. It contains judges' evaluations of various attributes: Identifiers: Judge, Zone. Visual Attributes: White color and homogeneous appearance. Aroma/Odor Attributes: Fruity, floral, lactic, putrid, body, chemical, and herbal. Taste/Flavor Attributes: Umami, acidity, bitterness, sweetness, saltiness, and metallic. Texture Attributes: Firmness, stickiness, granularity, smoothness, and elasticity. 2. Statistical Results: The dataset includes three tables of derived analyses performed using XLSTAT software: Mann-Whitney U test: Contains non-parametric tests to compare the differences between the two zones (ZMG vs. AGS) for each sensory attribute. RATA ANOVA: Presents an Analysis of Variance to determine if there are significant differences in the mean scores of the attributes according to the zone or the judge. PCA (Principal Component Analysis): Shows dimensionality reduction to visualize how the sensory attributes are grouped and how they relate to the evaluated samples. In summary, the dataset is structured to create a complete comparative sensory profile, allowing the identification of which characteristics distinguish the products evaluated in each region.