Intelligent pulsed ultraviolet c radiation sterilization system: A cleaner solution of raw ready-to-eat aquatic products processing

灭菌(经济) 环境科学 工艺工程 原材料 食物腐败 计算机科学 废物管理 制浆造纸工业 工程类 化学 业务 生物 遗传学 财务 有机化学 细菌 外汇市场 汇率
作者
You Li,Luwei Zhang,Yanfu He,Xiaoshuan Zhang,Xingxing Liu
出处
期刊:Journal of Cleaner Production [Elsevier BV]
卷期号:427: 139281-139281 被引量:9
标识
DOI:10.1016/j.jclepro.2023.139281
摘要

The sterilization of raw ready-to-eat aquatic products is a crucial method for ensuring their safety for consumption after production. However, achieving intelligent decision-making and higher sterilization efficiency remains a technical challenge. In this paper, an intelligent ultraviolet c radiation (UVC) pulse sterilization system for raw ready-to-eat aquatic products processing lines is presented. The objective of intelligently classifying and grading aquatic products in an automated production line and then sterilizing them is attained. On the basis of the thermal radiation perspective factor method, an irradiation prediction model for the columnar pulsed UVC field is developed, and an automated decision model for the UVC sterilization level is developed in conjunction with the hierarchical analysis method. Automatic control of the UVC lamp is achieved with precision. Using a combination of direct measurements and simulation calculations, the accuracy of the prediction structure is verified. In addition, the system's key model, the UVC intensity decision model, was evaluated, and the results indicated that the decision model had an error rate of 13.3% in the sterilization of raw ready-to-eat aquatic products and that the system's sterilization rate could reach approximately 95%. Additionally, the economics of implementation and overall performance of the sterilization system were evaluated and determined to be effective in reducing spoilage rates and human resource losses, thereby promoting sustainable and clean production in the raw food fish processing industry.
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
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
蔡俊辉完成签到,获得积分10
1秒前
进击的小羊完成签到,获得积分10
1秒前
biofresh发布了新的文献求助10
1秒前
meng发布了新的文献求助10
2秒前
科研通AI6.3应助鲤鱼平蓝采纳,获得10
2秒前
ZZ完成签到 ,获得积分10
3秒前
3秒前
华仔应助优秀的凝雁采纳,获得10
4秒前
laber应助SAIL采纳,获得50
4秒前
可爱多完成签到,获得积分10
5秒前
6秒前
赘婿应助好运的哈哈鸭采纳,获得10
6秒前
深情安青应助huzhennn采纳,获得10
8秒前
JamesPei应助科研通管家采纳,获得10
8秒前
leeap完成签到 ,获得积分10
8秒前
8秒前
Hello应助科研通管家采纳,获得10
8秒前
8秒前
香蕉觅云应助科研通管家采纳,获得10
8秒前
Owen应助科研通管家采纳,获得10
8秒前
乐乐应助科研通管家采纳,获得10
8秒前
我是老大应助科研通管家采纳,获得30
8秒前
领导范儿应助科研通管家采纳,获得10
8秒前
Lucas应助周子淦采纳,获得10
8秒前
SciGPT应助科研通管家采纳,获得10
8秒前
没耐心坏小猫完成签到,获得积分10
9秒前
无忧应助科研通管家采纳,获得10
9秒前
FashionBoy应助科研通管家采纳,获得10
9秒前
damapd应助科研通管家采纳,获得10
9秒前
研友_VZG7GZ应助科研通管家采纳,获得10
9秒前
赘婿应助科研通管家采纳,获得30
9秒前
wanci应助科研通管家采纳,获得10
9秒前
李爱国应助科研通管家采纳,获得10
9秒前
情怀应助科研通管家采纳,获得10
9秒前
9秒前
学术混混应助科研通管家采纳,获得10
9秒前
无忧应助科研通管家采纳,获得10
9秒前
9秒前
molihuakai应助科研通管家采纳,获得10
9秒前
隐形曼青应助科研通管家采纳,获得10
9秒前
高分求助中
Psychopathic Traits and Quality of Prison Life 1000
Chemistry and Physics of Carbon Volume 18 800
The formation of Australian attitudes towards China, 1918-1941 660
Signals, Systems, and Signal Processing 610
天津市智库成果选编 600
Forced degradation and stability indicating LC method for Letrozole: A stress testing guide 500
全相对论原子结构与含时波包动力学的理论研究--清华大学 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6451729
求助须知:如何正确求助?哪些是违规求助? 8263452
关于积分的说明 17608388
捐赠科研通 5516377
什么是DOI,文献DOI怎么找? 2903719
邀请新用户注册赠送积分活动 1880647
关于科研通互助平台的介绍 1722664