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ASTM E 1790 : 2004

Superseded

Superseded

A superseded Standard is one, which is fully replaced by another Standard, which is a new edition of the same Standard.

View Superseded by

Standard Practice for Near Infrared Qualitative Analysis

Available format(s)

Hardcopy , PDF

Superseded date

11-11-2014

Language(s)

English

Published date

11-01-2004

US$75.00
Excluding Tax where applicable

CONTAINED IN VOL. 03.06, 2016 Specifies the use of near-infrared (NIR) spectroscopy for the qualitative analysis of liquids and solids.

Committee
E 13
DocumentType
Standard Practice
Pages
8
ProductNote
Reconfirmed 2004
PublisherName
American Society for Testing and Materials
Status
Superseded
SupersededBy
Supersedes

1.1 This practice covers the use of near-infrared (NIR) spectroscopy for the qualitative analysis of liquids and solids. The practice is written under the assumption that most NIR qualitative analyses will be performed with instruments designed specifically for this region and equipped with computerized data handling algorithms. In principle, however, the practice also applies to work with liquid samples using instruments designed for operation over the ultraviolet (UV), visible, and mid-infrared (IR) regions if suitable data handling capabilities are available. Many Fourier Transform Infrared (FTIR) (normally considered mid-IR instruments) have NIR capability, or at least extended-range beamsplitters that allow operation to 1.2 [mu]m; this practice also applies to data from these instruments.

1.2 This standard does not purport to address all of the safety concerns, if any, associated with its use. It is the responsibility of the user of this standard to establish appropriate safety and health practices and determine the applicability of regulatory limitations prior to use.

ASTM E 2898 : 2014 Standard Guide for Risk-Based Validation of Analytical Methods for PAT Applications
ASTM E 2617 : 2017 Standard Practice for Validation of Empirically Derived Multivariate Calibrations
ASTM E 2891 : 2013 Standard Guide for Multivariate Data Analysis in Pharmaceutical Development and Manufacturing Applications

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