Spectral Imaging

Italian scientists have used their new method for reducing the size of the data produced by NIR hyperspectral imaging to identify bruised apples.

Study the label of almost any food product and you’re likely to see the rather vague warning “May contain peanuts” somewhere on there, unless of course it’s a product that definitely does contain peanuts. As now revealed in a paper in the latest issue of JNIRS—Journal of Near Infrared Spectroscopy, these warnings of peanut contamination could soon lose much of their uncertainty, thanks to NIR hyperspectral imaging.

This year, to help all of you with time to fill over the Christmas and New Year break, we have decided to offer a data analysis challenge. The problem to be solved is described in the text and the dataset may be downloaded from the Internet.

Big data represents both an opportunity and a challenge for scientists. The huge amount of data that can be generated by the latest scientific instruments could lead to important scientific discoveries, but only if scientists can efficiently process that data. A recent European project called Computis, has come up with a range of new tools for efficiently processing mass spectrometry imaging data.

PANalytical Boulder is accepting submissions for the 2015 Alexander Goetz Instrument Support Program and the deadline for submissions is 15 October 2014.

Selected students pursuing a master’s or doctoral degree with innovating research proposals will be awarded a FieldSpec® 4 Standard-Res spectroradiometer or a FieldSpec HandHeld 2 spectroradiometer for a specified period of time. The spectroradiometers can be used by the students for a wide range of field research applications such as image interpretation, ground truthing, materials classification and ecological impact analyses.

Chinese food scientists have used NIR hyperspectral imaging to identify tough and chewy prawns.