NIR quantitative model trans-scale calibration from small scale to pilot scale via directed DOSC-SBC algorithm

校准 比例(比率) 算法 计算机科学 数据集 放大 数学 统计 人工智能 物理 量子力学 经典力学
作者
Xinyuan Zhang,Yang Pei,Yinxue Hao,Yuanlin Li,Shuyu Wang,Xueyan Zhan
出处
期刊:Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy [Elsevier]
卷期号:288: 122133-122133
标识
DOI:10.1016/j.saa.2022.122133
摘要

In order to solve the problem of inapplicability of NIR quantitative models due to the large difference between the modeling samples and the samples to be tested, Directed DOSC-SBC(DDOSC-SBC)algorithm is proposed in this paper based on Direct Orthogonal Signal Correction combined with Slope/Bias Correction (DOSC-SBC) algorithm. To obtain the suitable spectral matrix transfer parameters for the test set during DDOSC spectral preprocessing, several representative test samples in the test set were selected, then the spectral systematic errors between the modeling set and the test set were corrected with the SBC method in order to realize the trans-scale prediction of the NIR quantitative model. NIR data and the critical quality attributes(CQAs)were detected in the small scale and pilot scale pharmaceutical process of the fluidized bed granulation of dextrin and water extraction of honeysuckle. After the small scale model was calibrated via the directed DOSC-SBC algorithm which was guided by representative pilot scale samples, the small scale model was able to predict the pilot scale test samples more accurately. The NIR quantitative model trans-scale calibration from small scale to pilot scale was also successfully realized with a RPD value higher than 3.5 and RSEP value lower than 10%. DDOSC-SBC algorithm is a successful model trans-scale calibrated method that can be applied to NIR real-time monitoring of CQAs in the preparation process of Chinese herbal medicine.

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
Gauss应助正直小蚂蚁采纳,获得50
1秒前
2秒前
ghj完成签到 ,获得积分10
3秒前
鸡蛋黄完成签到,获得积分10
3秒前
蓝天白云发布了新的文献求助10
3秒前
3秒前
4秒前
心灵美的不斜完成签到 ,获得积分10
4秒前
所所应助彩色一手采纳,获得30
4秒前
11111关注了科研通微信公众号
5秒前
超帅元珊完成签到,获得积分10
6秒前
哇哇哇完成签到 ,获得积分10
7秒前
英俊的铭应助科研通管家采纳,获得10
7秒前
王伟轩应助科研通管家采纳,获得10
7秒前
tiptip应助科研通管家采纳,获得10
7秒前
7秒前
tiptip应助科研通管家采纳,获得10
7秒前
7秒前
7秒前
7秒前
王伟轩应助科研通管家采纳,获得10
7秒前
CodeCraft应助科研通管家采纳,获得10
7秒前
深情安青应助科研通管家采纳,获得10
7秒前
KLAY应助科研通管家采纳,获得20
8秒前
王伟轩应助科研通管家采纳,获得10
8秒前
PAPA完成签到,获得积分10
8秒前
大模型应助科研通管家采纳,获得10
8秒前
FashionBoy应助科研通管家采纳,获得10
8秒前
zz发布了新的文献求助10
8秒前
8秒前
8秒前
英俊的铭应助科研通管家采纳,获得10
8秒前
徐堂翔完成签到,获得积分10
8秒前
8秒前
8秒前
情怀应助科研通管家采纳,获得10
8秒前
8秒前
8秒前
大个应助科研通管家采纳,获得10
8秒前
8秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Modern Epidemiology, Fourth Edition 5000
Handbook of pharmaceutical excipients, Ninth edition 5000
Aerospace Standards Index - 2026 ASIN2026 2000
Digital Twins of Advanced Materials Processing 2000
Weaponeering, Fourth Edition – Two Volume SET 2000
Social Cognition: Understanding People and Events 1000
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 纳米技术 有机化学 物理 生物化学 化学工程 计算机科学 复合材料 内科学 催化作用 光电子学 物理化学 电极 冶金 遗传学 细胞生物学
热门帖子
关注 科研通微信公众号,转发送积分 6032051
求助须知:如何正确求助?哪些是违规求助? 7717334
关于积分的说明 16198766
捐赠科研通 5178758
什么是DOI,文献DOI怎么找? 2771503
邀请新用户注册赠送积分活动 1754776
关于科研通互助平台的介绍 1639840