1st Edition

Mass Spectrometry Imaging in Food Analysis

Edited By Leo Nollet Copyright 2020
    214 Pages 22 Color & 25 B/W Illustrations
    by CRC Press

    214 Pages 22 Color & 25 B/W Illustrations
    by CRC Press

    Food contains various compounds and many technologies exist to analyze those molecules of interest. However, the analysis of the spatial distribution of those compounds using conventional technology, such as liquid chromatography-mass spectrometry or gas chromatography-mass spectrometry is difficult.

    Mass spectrometry imaging (MSI) is a mass spectrometry technique to visualize the spatial distribution of molecules, as biomarkers, metabolites, peptides or proteins by their molecular masses. Despite the fact that MSI has been generally considered a qualitative method, the signal generated by this technique is proportional to the relative abundance of the analyte and so quantification is possible.

    Mass Spectrometry Imaging in Food Analysis, a volume in the Food Analysis and Properties Series, explains how the novel use of matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) will be an ideal complementary approach. MALDI-MSI is a two-dimensional MALDI-MS technology that can detect compounds in a tissue section without extraction, purification, separation, or labeling. It can be used to visualize the spatial distribution of biomolecules in foods.


    • Explains the novel use of matrix-assisted laser desorption/ionization mass spectrometry imaging in food analysis
    • Describes how MALDI-MSI will be a useful technique for optical quality assurance.
    • Shows how MALDI-MSI detects food contaminants and residues
    • Covers the historical development of the technology

    While there are a multitude of books on mass spectrometry, none focus on food applications and thus this book is ideally suited to food scientists, food industry personnel engaged in product development, research institutions, and universities active in food analysis or chemical analysis.

    Also available in the Food Analysis and Properties Series:

    Food Aroma Evolution: During Food Processing, Cooking, and Aging, edited by

    Matteo Bordiga and Leo M.L. Nollet (ISBN: 9781138338241)

    Ambient Mass Spectroscopy Techniques in Food and the Environment, edited by Leo M.L. Nollet and Basil K. Munjanja (ISBN: 9781138505568)

    Hyperspectral Imaging Analysis and Applications for Food Quality, edited by N.C. Basantia, Leo M.L. Nollet, and Mohammed Kamruzzaman (ISBN: 9781138630796)

    For a complete list of books in this series, please visit our website at:



    Series Preface vii

    About the Editor ix

    List of Contributors xi

    Introduction xiii


    Chapter 1 Mass Spectrometry Imaging 3

    Leo M.L. Nollet

    Chapter 2 Imaging Mass Spectrometry for Small Molecules 13

    Fangbiao Li


    Chapter 3 Matrix-Assisted Laser Desorption Ionization (MALDI)

    and Atmospheric Pressure-MALDI (AP-MALDI) 37

    Nrusingha Charan Basantia

    Chapter 4 MALDI IMS for Proteins and Biomarkers 51

    Michelle L. Reyzer and Richard M. Caprioli

    Chapter 5 Secondary-Ion Mass Spectrometry 73

    Leo M.L. Nollet

    Chapter 6 Desorption Electrospray Ionization Mass Spectrometry

    Imaging in Food Applications 81

    Semih Ötleş and Vasfiye Hazal Özyurt

    Chapter 7 Liquid Extraction Surface Analysis 91

    Leo M.L. Nollet

    Chapter 8 Laser Ablation Inductively Coupled Plasma Mass

    Spectrometry 95

    Leo M.L. Nollet

    Chapter 9 Different Mass Spectrometry Imaging Methods 103

    Sadaf Jamal Gilani, Chandrakala, and Md. Taleu Zzaman


    Chapter 10 Introduction to Ambient Mass Spectrometry Techniques 119

    Raquel Sero, Maria Teresa Galceran, Encarnacion Moyano, and

    Leo M.L. Nollet

    Chapter 11 Use of an “Intelligent Knife” (iknife), Based on the Rapid

    Evaporative Ionization Mass Spectrometry Technology, for

    Authenticity Assessment of Pistachio Samples 159

    Francesca Rigano, Sara Stead, Domenica Mangraviti, Renata

    Jandova, Davy Petit, Nino Marino, and Luigi Mondello


    Chapter 12 Comparison of Machine Learning Algorithms for Predictive

    Modeling of Beef Attributes Using Rapid Evaporative

    Ionization Mass Spectrometry (REIMS) Data 181

    Devin A. Gredell, Amelia R. Schroeder, Keith E. Belk, Corey D.

    Broeckling, Adam L. Heuberger, Soo-Young Kim, D. Andy King,

    Steven D. Shackelford, Julia L. Sharp, Tommy L. Wheeler, Dale R.

    Woerner, and Jessica E. Prenni

    Index 195


    Leo M.L. Nollet