Establishment and Verification of a Three-Dimensional Quantitative Evaluation System for Nature Bias of Plant-Derived Food Materials

Objective: To address the long-standing problems of "subjectivity, lack of standards for special groups, and poor cross-scenario adaptability" in the traditional evaluation of nature bias (cool-warm property) of plant-derived food materials, this study aimed to construct a full-scenario quantitative tool applicable to both "daily dietary" and "medicinal" scenarios.Methods: A three-dimensional framework integrating the "environmental habits-metabolic characteristics-growth cycle" was established. The core indicator thresholds of each dimension, exclusive correction rules for special groups (fungi, parasitic plants, lichens, high-altitude plants), and cross-dimensional arbitration logic were clarified. The feasibility of the system was verified using 485 core plant-derived samples, which were stratified and selected from a total sample library of 987 species (417 daily plant food materials + 570 Chinese medicinal materials). The core samples covered 4 categories of daily food materials, 4 special groups of Chinese medicinal materials, and 3 types of extreme habitats based on "biological group + ecotype".Results: The system covered more than 95% of common plant groups used in daily life and medicine. The consistency rate between daily food materials and traditional literature on "warm-cool nature" reached 98%, and the consistency rate of special groups of Chinese medicinal materials after correction reached 96% (with intensity error ≤15% for partially consistent samples). The repeated detection error rate was ±3.2% (excluding neutral food materials). Core indicator thresholds were cross-validated by authoritative references such as FAO Guidelines and international journals, which were consistent with the "environment-metabolism synergy" logic. The adaptability rate to nondeep-sea extreme habitats (high altitude, saline‒alkali land, extreme acidity) was 100%, which could explain the differences in the natural bias of medicinal materials from genuine producing areas.Limitations: Only deep-sea kelp showed deviations due to the lack of a multifactor model, and supplementary optimization with various deep-sea samples is planned.Conclusions: This three-dimensional quantitative evaluation system achieves a key breakthrough in the nature bias of plant-derived food materials from "qualitative description" to "quantitative calculation". It is not only suitable for the balanced matching of nature bias in daily dietary therapy but also supports the standardized determination of nature bias of medicinal plants, laying a rule foundation for subsequent extended studies such as the correlation between nature bias and efficacy of Chinese medicinal materials and scenario optimization for deep-sea/genetically modified plants.