A high‐precision method evaluating color quality of Sichuan Dark Tea based on colorimeter combined with multi‐layer perceptron

色度计 人工智能 色差 模式识别(心理学) 多层感知器 颜色分析 感知器 数学 主成分分析 计算机科学 人工神经网络 计算机视觉 光学 物理 GSM演进的增强数据速率
作者
Yao Zou,Wanjun Ma,Qian Tang,Wei Xu,Liqiang Tan,Deyang Han,Yun Tian,Yue Yuan
出处
期刊:Journal of Food Process Engineering [Wiley]
卷期号:43 (8) 被引量:10
标识
DOI:10.1111/jfpe.13444
摘要

Abstract Instrumental examination of Sichuan Dark Tea (SDT) quality instead of human panel sensory evaluation is important for quality control. This study attempted to create a high‐precision method to rapidly and accurately evaluate SDT color quality. Colorimeter combined with multi‐layer perceptron (MLP) was utilized to extract CIELAB color parameters of dried tea, liquor, and infused tea, respectively, and established the prediction models of color attributes scores with the optimal color parameters selected by a principal component analysis (PCA). MLP models established could accurately predict color total scores of SDT, the glossiness of dried tea, and chroma of infused tea ( R p = 0.889–0.989; RMSEP = 0.393–0.631). Besides, models based on tea pigments could accurately predict infused tea color total scores ( R p = 0.920, RMSEP = 0.531). Parameter a * was significantly correlated with almost all of the color evaluation factors of SDT and seemed to be the characteristic color parameter. The color quality of Sichuan Dark Tea can be excellently estimated by the method utilizing colorimeter coupled with MLP. Practical applications To meet the requirement of dark tea production and the costumer's expectation, this study attempted to create a high‐precision method quickly and accurately evaluating color quality of SDT. Usually, in the massive production, tea color evaluated by eyesight is time‐consuming, subjective, and has poor accuracy due to visual fatigue of human. In this work, we optimized color parameters with PCA to improve the performance of MLP models established. The results can provide a theoretical basis for the evaluation of tea color quality by instrument, and make SDT quality control more convenient, accurate, and time‐saving.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
大幅提高文件上传限制,最高150M (2024-4-1)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
聪明的破茧完成签到,获得积分10
刚刚
1秒前
curtain发布了新的文献求助10
2秒前
3秒前
奋斗的青春完成签到,获得积分10
4秒前
qqdm完成签到 ,获得积分10
5秒前
眼圆广志完成签到,获得积分10
5秒前
CpatainDM12138完成签到,获得积分10
6秒前
绿色催化发布了新的文献求助10
6秒前
兴奋海雪发布了新的文献求助30
7秒前
小刘完成签到,获得积分10
8秒前
想发sci发布了新的文献求助20
9秒前
一瓶牛完成签到 ,获得积分10
10秒前
10秒前
大个应助喜悦小刺猬采纳,获得10
11秒前
Cher1she发布了新的文献求助20
13秒前
14秒前
Accept2024完成签到,获得积分10
15秒前
充电宝应助wujun采纳,获得10
17秒前
纯纯纯纯完成签到,获得积分10
18秒前
中中发布了新的文献求助10
19秒前
大伟完成签到,获得积分10
19秒前
Dr.YYF.发布了新的文献求助10
20秒前
Akim应助sfwer采纳,获得10
24秒前
tuotuo发布了新的文献求助200
25秒前
华仔应助lion_wei采纳,获得10
29秒前
31秒前
杀毒武器胡完成签到,获得积分10
33秒前
fujun0095发布了新的文献求助10
33秒前
cindy完成签到,获得积分10
34秒前
愉快的枕头完成签到,获得积分10
35秒前
35秒前
11111完成签到,获得积分10
36秒前
wentian完成签到,获得积分20
38秒前
39秒前
orixero应助杀毒武器胡采纳,获得10
39秒前
一路高飛完成签到,获得积分10
39秒前
洋山芋完成签到,获得积分10
40秒前
午见千山应助yichun采纳,获得30
41秒前
安之完成签到,获得积分10
41秒前
高分求助中
The Oxford Handbook of Social Cognition (Second Edition, 2024) 1050
Kinetics of the Esterification Between 2-[(4-hydroxybutoxy)carbonyl] Benzoic Acid with 1,4-Butanediol: Tetrabutyl Orthotitanate as Catalyst 1000
The Young builders of New china : the visit of the delegation of the WFDY to the Chinese People's Republic 1000
юрские динозавры восточного забайкалья 800
English Wealden Fossils 700
Handbook of Qualitative Cross-Cultural Research Methods 600
Chen Hansheng: China’s Last Romantic Revolutionary 500
热门求助领域 (近24小时)
化学 医学 生物 材料科学 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 基因 遗传学 催化作用 物理化学 免疫学 量子力学 细胞生物学
热门帖子
关注 科研通微信公众号,转发送积分 3140041
求助须知:如何正确求助?哪些是违规求助? 2790931
关于积分的说明 7797066
捐赠科研通 2447278
什么是DOI,文献DOI怎么找? 1301808
科研通“疑难数据库(出版商)”最低求助积分说明 626340
版权声明 601194