A review of near infrared spectroscopy and chemometrics in pharmaceutical technologies.

By Y. Roggo, P. Chalus, Lene Maurer, Carmen Lema-Martinez, A. Edmond, N. Jent. Journal of Pharmaceutical and Biomedical Analysis, 2007

1,117 citations recorded by the source corpus.

Subfields: Analytical Chemistry, Biophysics, Spectroscopy

View Paper: https://www.semanticscholar.org/paper/cea9fe929d6dacb02b89ad2885049a0d1fb3bb8f

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In Analytical Chemistry

1. M. Vidal
2. Di Wu
3. José Manuel Amigo
4. Yang Yang
5. Yong He
6. Da‐Wen Sun

In Biophysics

1. M. Vidal
2. Di Wu
3. José Manuel Amigo
4. Yong He

In Spectroscopy

1. M. Vidal
2. José Manuel Amigo

Citations in the corpus

• Review of physicochemical properties and analytical characterization of lignocellulosic biomass (2017, methodology): “Principle component analysis (PCA), partial least squares (PLS), artificial neural networks (ANN), and support vector machines (SVM) are usually used for qualitative analysis [124].”
• Nondestructive Differentiation of Panax Species Using Visible and Shortwave Near-Infrared Spectroscopy (2011, positive): “Vis-SWNIR spectroscopy has been applied for pharmaceutical materials, agricultural products, and foods (Nicolaï et al. 2007; Roggo et al. 2007; Luypaert et al. 2007; Li and He 2008).”
• Pre-processing of hyperspectral images. Essential steps before image analysis (2012, methodology): “Usually, the hyperspectral images taken with any vibrational spectroscopic technique are called Chemical images [6–8].”
• Feasibility Study of the Use of Handheld NIR Spectrometer for Simultaneous Authentication and Quantification of Quality Parameters in Intact Pineapple Fruits (2019, background): “*e development of computers and software programmes is making chemometric techniques a very powerful tool for processing NIR spectra data as it overcomes the difficulty of multicollinearity and gives scientific statistical inferences for meaningful conclusions to experimental results [26, 27].”
• Qualitative and quantitative analysis of lignocellulosic biomass using infrared techniques: A mini-review (2013, methodology): “Infrared spectroscopy (IRS) has been widely used for qualitative and quantitative analysis in various areas such as the food and pharmaceutical industries [20–23]; for example, the composition of protein and oil in meat products, cereal crops, and food products was predicted successfully using near-”
• Support vector machines (SVM) in near infrared (NIR) spectroscopy: Focus on parameters optimization and model interpretation (2009, background): “NIR spectroscopy is widely used in food [1] and pharmaceutical industries [2] for analysis and quality control.”