Dr. Xuedian Zhang Profile

Dr. Xuedian Zhang

at Tianjin Univ

SPIE Involvement:

Author

Publications (1)

This will count as one of your downloads.

You will have access to both the presentation and article (if available).

DOWNLOAD NOW

This content is available for download via your institution's subscription. To access this item, please sign in to your personal account.

Email or Username Forgot your username?

Password Forgot your password?

Show

Keep me signed in

No SPIE account? Create an account

Proceedings Article | 15 October 2004 Paper

Method of multirange models by near-infrared spectral analysis for nonlinear optics of organic materials

Xuedian Zhang, Min Chang, Kexin Xu

Proceedings Volume 5517, (2004) https://doi.org/10.1117/12.559078

KEYWORDS: Calibration, Statistical modeling, Data modeling, Near infrared, Systems modeling, Organic materials, Near infrared spectroscopy, Proteins, Nonlinear optics, Spectroscopy

Read Abstract +

Near-infrared (NIR) spectroscopy has gained wide spread acceptance in recent years as a powerful diagnostic tool, particularly for the concentrations of Components of Organic Materials. Unfortunately, most systems in practice are not perfectly linear; they show non-linear behavior of different types. Any model's capacity of information is not infinity, and it is founded that the calibration model is of a strong selectivity caused by non-linear, i.e. the model will provide satisfactory predict results for the samples in the appropriate ranges of the measurements, but make poor ones for the samples in the regions, especially for the extremes of the measurements. Reality has thus created a need for methods that can handle such non-linearities. A new technique of Multi-Region Model (MRM) instead of unique model is presented in the work. To validate the calibration, 198 milk samples were employed in this study, the comparison with the MRM method was based on the root mean square error of prediction (RMSEP) and Correlation coefficient (R2). The study result shows that the MRM accuracy for individual component's prediction is reliable. The predicted results of MRM exhibit values of R2 of 98.63% and 95.07%, and RMSEP of 0.116% and 0.101% for fat and protein, respectively.

My Library

You currently do not have any folders to save your paper to! Create a new folder below.

Folder Name

Folder Description

View contact details

UPDATE YOUR PROFILE

Is this your profile? Update it now.

Sign into your SPIE.org account

Don’t have a profile and want one?

Create an account on SPIE.org

Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks. You are receiving this notice because your organization may not have SPIE eBooks access.*

*Shibboleth/Open Athens users─please sign in to access your institution's subscriptions.

To obtain this item, you may purchase the complete book in print or electronic format on SPIE.org.

ORGANIZATIONAL
Sign in with credentials provided by your organization.

Organizational Username

Organizational Password

Show/Hide Password

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members:

Non-members: ADD TO CART

Keywords/Phrases

Search In:

Publication Years