Screening of compound feeds using NIR hyperspectral data

By J. Pierna, V. Baeten, P. Dardenne. 2006

60 citations recorded by the source corpus.

Subfields: Analytical Chemistry, Biomedical Engineering, Biophysics

View Paper: https://www.semanticscholar.org/paper/9204f5ae5449e881454ab70de9ccfd83b6e39159

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Analytical Chemistry

1. M. Whitworth
2. Nicola Caporaso
3. Ian D Fisk

In Biomedical Engineering

1. M. Whitworth
2. Nicola Caporaso
3. Ian D Fisk

In Biophysics

1. M. Whitworth
2. Nicola Caporaso
3. Ian D Fisk

Citations in the corpus

• Support vector machines (SVM) in near infrared (NIR) spectroscopy: Focus on parameters optimization and model interpretation (2009, methodology): “The SVM have been introduced in chemometrics only recently [5] and have been successfully applied for mid and near infrared classification tasks, such as material identification [6,7] and food discrimination [8–11].”
• Near-Infrared spectroscopy and hyperspectral imaging for non-destructive quality assessment of cereal grains (2018, methodology): “For instance, Fern andez-Pierna, Baeten and Dardenne (90) applied a method for rapid screening of compound feeds by HSI in the NIR region 900–1700 nm. 13 different vegetal ingredients were evaluated in mixture: barley, coconut, corn, flax, lucerne, manioc, palm, rapeseed, soya bean, sugar beet, sunf”