红茶感官品质分级评价特征定义数据集

1、数据采集：从大量茶叶评价标准获取评价红茶的维度，从历史评价记录中获取各维度的评价文本； 2、数据处理：从评价文本中，根据自然语言处理（NLP）技术方法，获取具体维度的关键词；评价维度包括：外形、汤色、香气、滋味、叶底； 生成包括：外形（细嫩、挺秀、金毫显露、均匀、油润匀亮等）、汤色（红艳、明亮、艳红、赤红、清澈等）、香气（毫香、祁门香、甜香、薯香、蜜香等）、滋味（鲜醇、甘爽、醇厚、绵醇等）、叶底（细嫩、柔软、明亮、柔滑、纯正等）关键词特征集合。 3、数据应用：可以用于红茶的品质评价评级，通过关联感官关键词与标准，建模型实现自动打分评价；优化茶园管理，分析环境对品质影响，优化种植方案；规范采摘时间与标准，从源头控鲜叶品质。1. Data Collection: Extract the evaluation dimensions for black tea from a large number of tea evaluation standards, and acquire evaluation texts corresponding to each dimension from historical evaluation records. 2. Data Processing: Extract keywords for specific dimensions from the evaluation texts using natural language processing (NLP) techniques. The evaluation dimensions include: appearance, liquor color, aroma, taste, and infused leaves. The generated keyword feature sets are as follows: Appearance (tender and slender, erect and elegant, covered with golden tips, uniform, lustrous and evenly bright, etc.); Liquor Color (deep red and bright, bright, bright red, crimson, clear, etc.); Aroma (downy aroma, Keemun aroma, sweet aroma, potato-like aroma, honey-like aroma, etc.); Taste (fresh and mellow, refreshing and sweet, rich and mellow, velvety mellow, etc.); Infused Leaves (tender and slender, soft, bright, smooth, pure, etc.). 3. Data Application: This dataset can be applied to black tea quality evaluation and grading: build models to achieve automatic scoring evaluation by correlating sensory keywords with official standards; optimize tea garden management by analyzing the impact of environmental factors on tea quality and refining planting schemes; standardize picking time and standards to control the quality of fresh tea leaves from the source.

搜集汇总

背景与挑战

背景概述

该数据集是一个红茶感官品质分级评价特征定义数据集，通过自然语言处理技术提取了红茶感官评价的关键词，用于构建茶叶品质智能评价系统，优化茶园管理和规范采摘标准。