Innovative Food Analysis

By Charis M. Galanakis

Innovative Food Analysis presents a modern perspective on the development of robust, effective and sensitive techniques to ensure safety, quality and traceability of foods to meet industry standards. Significant enhancements of analytical accuracy, precision, detection limits and sampling has expanded the practical range of food applications, hence this reference offers modern food analysis in view of new trends in analytical techniques and applications to support both the scientific community and industry professionals. This reference covers the latest topics across existing and new technologies, giving emphasis on food authenticity, traceability, food fraud, food quality, food contaminants, sensory and nutritional analytics, and more.

• Covers the last ten years of applications across existing and new technologies of food analytics
• Presents an emphasis on techniques in food authenticity, traceability and food fraud
• Discusses bioavailability testing and product analysis of food allergens and foodomics

• Language: English
• Publisher: Academic Press
• Release date: Nov 29, 2020
• ISBN: 9780128231555

Book preview

Innovative Food Analysis

Edited by

Charis M. Galanakis

Galanakis Laboratories, Chania, Greece Galanakis LaboratoriesChaniaGreece

King Saud University, Riyadh, Saudi Arabia King Saud UniversityRiyadhSaudi Arabia

Food Waste Recovery Group, Vienna, Austria Food Waste Recovery GroupViennaAustria

Table of Contents

Cover image

Title page

Copyright

List of Contributors

Preface

Chapter 1. Compositional and nutritional analysis

Abstract

1.1 Introduction

1.2 Carbohydrates

1.2.2 Labeling of carbohydrates in the EU

1.2.3 The importance of carbohydrate analysis

1.2.4 Traditional and emerging methods for sample preparation in carbohydrate analysis

1.2.5 Emerging technologies for carbohydrate analysis

1.2.6 Dietary fiber analysis

1.3 Fat and fatty acids

1.4 Minerals

1.5 Proteins

1.6 Water

1.7 Conclusions

References

Chapter 2. Bioactive component analysis

Abstract

2.1 Introduction

2.2 Polyphenols

2.3 Carotenoids

2.4 Vitamins

2.5 Omega-3 fatty acids

2.6 Organic acids

2.7 Nucleosides and nucleotides

2.8 Phytosterols

2.9 Conclusions and future perspectives

References

Chapter 3. Analytical technologies in sugar and carbohydrate processing

Abstract

3.1 Introduction

3.2 Analytical techniques for analyzing sugars and carbohydrates in sugar crops

3.3 Application of spectroscopy and chemometric data analyses for assessment of quality parameters of sugar commodities

3.4 Topical methods of extracting sugars and carbohydrates from sugar crops

3.5 Novel analytical technologies for determining the sugars and carbohydrates in secondary products

3.6 Research challenges in technologies applied for assessment of sugar contents in secondary products

3.7 Future perspectives and conclusions

References

Chapter 4. Sample preparation methods

Abstract

4.1 Introduction

4.2 Sample pretreatment techniques

4.3 Targeted sample pretreatment techniques with high specificity for target analytes

4.4 Quick, easy, cheap, effective, rugged, and safe methods

4.5 Conclusions

Abbreviations

References

Chapter 5. Flow-based food analytical methods

Abstract

5.1 Introduction

5.2 Flow-based methods of analysis

5.3 Representative applications of flow-based methods to food analysis

5.4 Conclusions

References

Chapter 6. Categories of food additives and analytical techniques for their determination

Abstract

6.1 Introduction

6.2 Food additives

6.3 Steps in the analysis of food additives

6.4 Analytical techniques used in food additive analysis

6.5 Conclusions

Acknowledgments

Dedication

References

Chapter 7. Analysis of food Additives

Abstract

7.1 Function of food additives

7.2 Classification of food additives

7.3 Examples of food additives

7.4 Regulation and measurements of food additives

7.5 Analysis of food additives

7.6 Analysis of other food additives

7.7 Prospects for the analysis of food additives

References

Chapter 8. Innovations in analytical methods for food authenticity

Abstract

8.1 Authentication of food products

8.2 Revision of analytical methods for food authentication

8.3 Conclusions

References

Chapter 9. Food traceability

Abstract

9.1 Introduction

9.2 Traceability systems

9.3 Traceability analysis

9.4 Conclusions

References

Chapter 10. Targeted and untargeted analytical techniques coupled with chemometric tools for the evaluation of the quality and authenticity of food products

Abstract

10.1 Introduction

10.2 Rheological methods

10.3 Chromatographic techniques

10.4 Thermal analysis methods

10.5 Fluorescence spectroscopy

10.6 Mid-infrared spectroscopy

10.7 Visible and near-infrared

10.8 Nuclear magnetic resonance

10.9 Microscopic methods

10.10 Conclusion

List of abbreviation

References

Chapter 11. Food pathogens

Abstract

11.1 Genome sequencing

11.2 RNA sequencing

11.3 Bioinformatics analysis

11.4 The application of innovative analysis on Enterobacter

11.5 The application of innovative analysis on Staphylococcus aureus

11.6 The application of innovative analysis on Pseudomonas

11.7 The application of innovative analysis on Bacillus

11.8 The application of innovative analysis on lactic acid bacteria

11.9 Analysis strategy for food pathogens

11.10 Conclusion

References

Further reading

Chapter 12. Sensory analysis using electronic tongues

Abstract

12.1 Electrochemical sensors in sensory analysis

12.2 Electrochemical devices

12.3 Conclusions and future perspectives

Acknowledgments

References

Chapter 13. Hyperspectral imaging techniques for noncontact sensing of food quality

Abstract

13.1 Introduction

13.2 Theory of near infrared-based techniques and fundamentals of hyperspectral imaging

13.3 Applications of hyperspectral imaging for food quality assessment

13.4 Future trends of hyperspectral imaging applications

13.5 Conclusions

Acknowledgments

References

Further reading

Index

Copyright

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List of Contributors

L. Arce,     Analytical Chemistry Department, Faculty of Science, University of Cordoba, Rabanales Campus, Cordoba, Spain Analytical Chemistry Department, Faculty of Science, University of Cordoba, Rabanales CampusCordobaSpain

Esra Capanoglu,     Department of Food Engineering, Faculty of Chemical and Metallurgical Engineering, Istanbul Technical University, Istanbul, Turkey Department of Food Engineering, Faculty of Chemical and Metallurgical Engineering, Istanbul Technical UniversityIstanbulTurkey

Nicola Caporaso

School of Biosciences, University of Nottingham, Sutton Bonington, Leicestershire, United Kingdom School of Biosciences, University of Nottingham, Sutton BoningtonLeicestershireUnited Kingdom

Campden BRI, Chipping Campden, Gloucestershire, United Kingdom Campden BRI, Chipping CampdenGloucestershireUnited Kingdom

Department of Agricultural Sciences, University of Naples Federico II, Naples (NA), Italy Department of Agricultural Sciences, University of Naples "Federico IINaples (NA)Italy

M.J. Cardador,     Analytical Chemistry Department, Faculty of Science, University of Cordoba, Rabanales Campus, Cordoba, Spain Analytical Chemistry Department, Faculty of Science, University of Cordoba, Rabanales CampusCordobaSpain

Susana Casal,     LAQV-REQUIMTE, Faculty of Pharmacy, University of Porto, Porto, Portugal LAQV-REQUIMTE, Faculty of Pharmacy, University of PortoPortoPortugal

Djenaine De Souza,     Laboratory of Electroanalytical Applied to Biotechnology and Food Engineering (LEABE), Multidisciplinary Research, Science and Technology Group (RMP-TC), Uberlândia Federal University, Patos de Minas, Brazil Laboratory of Electroanalytical Applied to Biotechnology and Food Engineering (LEABE), Multidisciplinary Research, Science and Technology Group (RMP-TC), Uberlândia Federal UniversityPatos de MinasBrazil

Anastasios Economou,     Department of Chemistry, National and Kapodistrian University of Athens, Athens, Greece Department of Chemistry, National and Kapodistrian University of AthensAthensGreece

Gamal ElMasry

Agricultural Engineering Department, Faculty of Agriculture, Suez Canal University, Ismailia, Egypt Agricultural Engineering Department, Faculty of Agriculture, Suez Canal UniversityIsmailiaEgypt

Institute of Agriculture and Food Research and Technology (IRTA), Monells, Spain Institute of Agriculture and Food Research and Technology (IRTA)MonellsSpain

M. Esteki,     Department of Chemistry, University of Zanjan, Zanjan, Iran Department of Chemistry, University of ZanjanZanjanIran

Pere Gou,     Institute of Agriculture and Food Research and Technology (IRTA), Monells, Spain Institute of Agriculture and Food Research and Technology (IRTA)MonellsSpain

Burcu Guldiken,     Department of Food and Bioproduct Sciences, University of Saskatchewan, Saskatoon, SK, Canada Department of Food and Bioproduct Sciences, University of SaskatchewanSaskatoonSKCanada

N. Jurado-Campos,     Analytical Chemistry Department, Faculty of Science, University of Cordoba, Rabanales Campus, Cordoba, Spain Analytical Chemistry Department, Faculty of Science, University of Cordoba, Rabanales CampusCordobaSpain

Senem Kamiloglu,     Science and Technology Application and Research Center (BITUAM), Bursa Uludag University, Gorukle, Bursa, Turkey Science and Technology Application and Research Center (BITUAM), Bursa Uludag University, GorukleBursaTurkey

Simge Karliga,     Department of Food Engineering, Faculty of Chemical and Metallurgical Engineering, Istanbul Technical University, Istanbul, Turkey Department of Food Engineering, Faculty of Chemical and Metallurgical Engineering, Istanbul Technical UniversityIstanbulTurkey

Romdhane Karoui,     Université d’Artois, UMR BIOECOAGRO 1158, Institut Régional en Agroalimentaire et Biotechnologie Charles Viollette, Faculté des Sciences Jean-Perrin, Lens, France Université d’Artois, UMR BIOECOAGRO 1158, Institut Régional en Agroalimentaire et Biotechnologie Charles Viollette, Faculté des Sciences Jean-PerrinLensFrance

Birthe V. Kjellerup,     Department of Civil and Environmental Engineering, University of Maryland, College Park, MD, USA Department of Civil and Environmental Engineering, University of Maryland, College ParkMDUSA

Junyan Liu

School of Food Science and Engineering, Guangdong Province Key Laboratory for Green Processing of Natural Products and Product Safety, South China University of Technology, Guangzhou, China School of Food Science and Engineering, Guangdong Province Key Laboratory for Green Processing of Natural Products and Product Safety, South China University of TechnologyGuangzhouChina

Department of Civil and Environmental Engineering, University of Maryland, College Park, MD, USA Department of Civil and Environmental Engineering, University of Maryland, College ParkMDUSA

Yuting Luo,     School of Food Science and Engineering, Guangdong Province Key Laboratory for Green Processing of Natural Products and Product Safety, South China University of Technology, Guangzhou, China School of Food Science and Engineering, Guangdong Province Key Laboratory for Green Processing of Natural Products and Product Safety, South China University of TechnologyGuangzhouChina

L.S. Magwaza,     Discipline of Crop and Horticultural Science, University of KwaZulu-Natal, Scottsville, South Africa Discipline of Crop and Horticultural Science, University of KwaZulu-NatalScottsvilleSouth Africa

A. Martín-Gómez,     Analytical Chemistry Department, Faculty of Science, University of Cordoba, Rabanales Campus, Cordoba, Spain Analytical Chemistry Department, Faculty of Science, University of Cordoba, Rabanales CampusCordobaSpain

Fernanda C.O.L. Martins,     Laboratory of Electroanalytical Applied to Biotechnology and Food Engineering (LEABE), Multidisciplinary Research, Science and Technology Group (RMP-TC), Uberlândia Federal University, Patos de Minas, Brazil Laboratory of Electroanalytical Applied to Biotechnology and Food Engineering (LEABE), Multidisciplinary Research, Science and Technology Group (RMP-TC), Uberlândia Federal UniversityPatos de MinasBrazil

Ítala M.G. Marx

Centro de Investigação de Montanha (CIMO), Instituto Politécnico de Bragança, Bragança, Portugal Centro de Investigação de Montanha (CIMO), Instituto Politécnico de BragançaBragançaPortugal

LAQV-REQUIMTE, Faculty of Pharmacy, University of Porto, Porto, Portugal LAQV-REQUIMTE, Faculty of Pharmacy, University of PortoPortoPortugal

Francesca Melini,     CREA Research Centre for Food and Nutrition, Rome, Italy CREA Research Centre for Food and NutritionRomeItaly

Valentina Melini,     CREA Research Centre for Food and Nutrition, Rome, Italy CREA Research Centre for Food and NutritionRomeItaly

K. Ncama,     Department of Crop Science, North West University, Mmabatho, South Africa Department of Crop Science, North West UniversityMmabathoSouth Africa

Tugba Ozdal,     Department of Food Engineering, Faculty of Engineering, Istanbul Okan University, Istanbul, Turkey Department of Food Engineering, Faculty of Engineering, Istanbul Okan UniversityIstanbulTurkey

José A. Pereira,     Centro de Investigação de Montanha (CIMO), Instituto Politécnico de Bragança, Bragança, Portugal Centro de Investigação de Montanha (CIMO), Instituto Politécnico de BragançaBragançaPortugal

António M. Peres,     Centro de Investigação de Montanha (CIMO), Instituto Politécnico de Bragança, Bragança, Portugal Centro de Investigação de Montanha (CIMO), Instituto Politécnico de BragançaBragançaPortugal

Renata Raina-Fulton,     Department of Chemistry & Biochemistry, University of Regina, Regina, SK, Canada Department of Chemistry & Biochemistry, University of ReginaReginaSKCanada

Michelle A. Sentanin,     Food Analysis and Chemistry Laboratory, Chemical Engineering Faculty, Uberlândia Federal University, Patos de Minas Campus, Patos de Minas, Brazil Food Analysis and Chemistry Laboratory, Chemical Engineering Faculty, Uberlândia Federal University, Patos de Minas CampusPatos de MinasBrazil

J. Simal-Gandara,     Nutrition and Bromatology Group, Department of Analytical and Food Chemistry, Faculty of Food Science and Technology, University of Vigo, Ourense Campus, Ourense, Spain Nutrition and Bromatology Group, Department of Analytical and Food Chemistry, Faculty of Food Science and Technology, University of Vigo, Ourense CampusOurenseSpain

Merve Tomas,     Department of Food Engineering, Faculty of Engineering and Natural Sciences, Istanbul Sabahattin Zaim University, Istanbul, Turkey Department of Food Engineering, Faculty of Engineering and Natural Sciences, Istanbul Sabahattin Zaim UniversityIstanbulTurkey

Ana C.A. Veloso

Instituto Politécnico de Coimbra, ISEC, DEQB, Coimbra, Portugal Instituto Politécnico de Coimbra, ISEC, DEQBCoimbraPortugal

CEB – Centre of Biological Engineering, University of Minho, Braga, Portugal CEB – Centre of Biological Engineering, University of MinhoBragaPortugal

Long Wu,     College of Bioengineering and Food, Hubei University of Technology, Wuhan, Hubei, 430068, P.R. China College of Bioengineering and Food, Hubei University of TechnologyWuhanHubei430068P.R. China

Zhenbo Xu

School of Food Science and Engineering, Guangdong Province Key Laboratory for Green Processing of Natural Products and Product Safety, South China University of Technology, Guangzhou, China School of Food Science and Engineering, Guangdong Province Key Laboratory for Green Processing of Natural Products and Product Safety, South China University of TechnologyGuangzhouChina

College of Pharmacy, University of Tennessee Health Science Center, Memphis, TN, USA College of Pharmacy, University of Tennessee Health Science CenterMemphisTNUSA

Perihan Yolci-Omeroglu,     Department of Food Engineering, Faculty of Agriculture, Bursa Uludag University, Bursa, Turkey Department of Food Engineering, Faculty of Agriculture, Bursa Uludag UniversityBursaTurkey

Preface

Nowadays, food analysis includes the development of sensitive, effective, and robust methodologies in order to ensure foods’ quality, traceability, and safety as well as to comply with legislation and meet the demands of consumers. The classic techniques of wet chemistry have in many cases been replaced with instrumental ones that are able to reduce the detection limits, improve precision and accuracy, and enhance sample throughput. It is thus important to understand deeper the recent advances in detecting and determining food components. Subsequently, food chemists and analysts need more insights on new techniques, their advantages and disadvantages, and, of course, assistance in practical issues.

Food Waste Recovery Group has published numerous books that deal with sustainable food systems, food waste recovery technologies, bio-based products and industries, valorization of different food processing by-products (e.g., from olive, grape, cereals, coffee, and meat), saving food actions, innovation in traditional foods, nutraceuticals and nonthermal processing, and innovation strategies in the food and environmental science. The group has also provided insights into shelf life and food quality, nonalcoholic drinks, personalized nutrition, as well as detailed guides for food components such as carotenoids, polyphenols, lipids, glucosinolates, dietary fiber, and proteins. The current book covers new trends and analytical techniques in food analysis. It aims at supporting chemists, analysts, scientists, and professionals that develop new methodologies in the analytical laboratories.

The book consists of 13 Chapters. Chapter 1 deals with compositional and nutritional analysis. In particular, conventional and emerging analytical methods for the determination of carbohydrates, dietary fiber, lipids and fatty acids, proteins and amino acids, minerals, and water content are described. The newly developed methods are fast, demand little or no sample preparation, are not destructive for the sample, generate no risks to the operator, and produce no toxic waste. In Chapter 2, spectrophotometric, fluorometric, chromatographic, enzymatic, and electrophoretic methods that are used to analyze bioactive compounds among others are presented along with the required pretreatments. In addition, the advantages and disadvantages of the existing analysis methods are highlighted. Chapter 3 provides more target information on common analytical methods for the determination of sugars and carbohydrates, their efficacy and limitations, extent of application, and future perspectives that need research attention to advance the industry.

Chapter 4 reviews sample preparation methods used for foods from obtaining a subsample for subsequent analysis to extraction and cleanup of extracts for both multiresidue and targeted analysis. Modified QuEChERS continue to have wide use in food analysis with a large range of modifications including cryogenic processing, selection of salts, organic solvent, buffers, or other conditions selected for phase separation or to enhance recoveries. Chapter 5 presents an overview of flow-based methods for food analysis. It briefly describes the main operational modes of flow analysis and brings together several representative applications for the determination of nutrients (sugars, amino acids, and vitamins), antinutrients, inorganic species (cations and anions), additives, preservatives, adulterants, pesticides, acidity, antioxidant capacity, pharmaceuticals, and several other compounds in food samples.

Chapter 6 deals with the different categories of food additives, indicating their respective functions, main compounds in each class, foodstuff applications, and possible adverse human health effects. In addition, it introduces analytical techniques for their determination. In Chapter 7, traditional and new rapid analytical methods for the analysis of food additives are discussed in detail, with an ultimate goal to assist readers to facilitate food safety and quality in compliance with legislation and consumers’ demands.

Classification of different food products is based on authenticity indicators, providing insight into future developments. To this line, Chapter 8 explores current critical concepts of foods’ traceability and labeling, followed by a systematic discrimination of authentication on different food products. It also presents common analytical techniques used for authenticity assessment, including their operation, advantages, and drawbacks. Chapter 9 deals with food traceability techniques including document-based systems, information and communication technologies, alphanumerical codes, barcodes, holograms, radio-frequency identification (RFID), nuclear techniques, and nanotechnology. In addition, immunoassays, DNA-PCR methods, omics, and isotope ratio analysis are also highlighted.

Chapter 10 explores targeted and untargeted analytical techniques coupled with chemometric tools for the evaluation of the quality and authenticity of food products. This chapter starts by presenting some traditional methods comprising textural, high-performance liquid chromatography and gas chromatography. The spectroscopic techniques determining the structure at the molecular level, namely, front face fluorescence, near-infrared, and mid-infrared spectroscopies and nuclear magnetic resonance and microscopic levels such as X-ray tomography, scanning electron microscopy, and transmission electron microscopy are presented.

Chapter 11 describes the innovative analysis strategies for food pathogens and spoilage microorganisms, mainly including genome sequencing, RNA sequencing, and bioinformatics analysis. It describes the different steps during genome sequencing, RNA sequencing, and bioinformatics analysis prior to explaining their application on different food pathogens and spoilage microorganisms, including Enterobacter, Staphylococcus, Pseudomonas, Bacillus, and lactic acid bacteria.

Chapter 12 discusses the main research advances reported in the last decade regarding the electronic tongues’ applications as taste sensors, being focused on the operating principles and types of devices. The main advantages and limitations of these fast, accurate, bioinspired potentiometric, voltammetric, and/or amperometric green sensor-based tools are addressed, aiming to make an overview of the recent and future challenges toward industrial and commercial applications. Finally, Chapter 13 describes hyperspectral imaging techniques for noncontact sensing of food quality. The theory, fundamentals, and principles of such a system and all accompanying methods associated with the development of robust image processing algorithms of hyperspectral images are explored and reported.

In conclusion, this book assists food chemists, analysts, and scientists working with food analysis, quality assurance, and safety, as well as researchers, academics, food technologists, and new product developers working in the food and laboratory sector. It could be used for ancillary reading in undergraduates and postgraduate level multidiscipline courses dealing with food chemistry, foodomics, food analytics, food science and technology, and food and nutrition.

I would like to acknowledge and thank one by one all authors for their fruitful collaboration. I highly appreciate their acceptance of my invitation as well as their harmonization with guidelines and timeline schedule. I am fortunate to have had the opportunity to work together with different experts from so many countries, namely, Brazil, Canada, China, Egypt, France, Greece, Italy, Iran, Portugal, South Africa, Spain, Turkey, and United Kingdom. I would also like to thank the acquisition editor Patricia Osborn, the book manager Laura Okidi, and Elsevier’s publication team for their help during production of this book. Last but not least, a message for every single reader. Such collaborative editing project contains hundreds and thousands of words and the final manuscript could contain some errors. Comments and suggestions are always welcome, so please do not hesitate to contact me to discuss relevant issues.

Charis M. Galanakis¹, ², ³, ¹Research & Innovation Department, Galanakis Laboratories, Chania, Greece Research & Innovation Department, Galanakis LaboratoriesChaniaGreece , ²College of Sciences, King Saud University, Riyadh, Saudi Arabia College of Sciences, King Saud UniversityRiyadhSaudi Arabia , ³Food Waste Recovery Group, ISEKI Food Association, Vienna, Austria Food Waste Recovery Group, ISEKI Food AssociationViennaAustria

[e-mail]

Chapter 1

Compositional and nutritional analysis

Valentina Melini and Francesca Melini,    CREA Research Centre for Food and Nutrition, Rome, Italy CREA Research Centre for Food and NutritionRomeItaly

Abstract

Food composition and nutritional analysis aims at providing data on the content of macro- and micro-nutrients, and/or other components in food products. It is important in implementing food composition databases, developing public health policies, assessing food quality and safety, and in nutritional labeling and science. Methods based on wet-chemistry are currently outdated, and they have been increasingly replaced by powerful instrumental techniques enabling significant improvements in analytical accuracy, precision and detection limits. Emerging technologies have overcome the main disadvantages of conventional methods, such as laborious sample preparation, time-consuming analysis and production of great amount of toxic wastes, in compliance with the principles of green chemistry. In this chapter, conventional and emerging analytical methods for determination of carbohydrates, dietary fiber, lipids and fatty acids, proteins and amino acids, minerals and water content are described and discussed. The newly developed methods are fast, demand little or no sample preparation, are not destructive for the sample, generate no risks for the operator and produce no toxic waste. They thus meet the emerging need for green chemistry and represent a promising tool for the modern global food distribution system.

Keywords

Carbohydrates; dietary fiber; lipids and fatty acids; proteins and amino acids; minerals; water content; green chemistry; food analysis

1.1 Introduction

Food composition and nutritional analysis aims at providing data on the content of macro- and micronutrients, and/or other components in food products. It is the cornerstone of food composition databases, nutrition science and labeling, public health policies, and food quality and safety assessment. Basically, food composition data are necessary for nutritional labeling of prepacked foods, and nutrition label is a tool that enables consumers to make informed and conscious choices when buying foods. Food composition data are also included in food composition databases, which are basic elements in assessing the nutritional adequacy of a diet and in evaluating population nutritional status. Hence, food composition data are essential tools in nutrition science and in the development of public health policies. Food composition analysis also contributes to evaluating the safety of a product. Some components are not admitted by law or can be present in amounts higher than safe thresholds, other components may also form during processing and storage.Detection of these compounds can thus be used as a tool to evaluate what processing the food underwent or the occurrence of degradation and spoilage.

A new frontier of food analysis is guaranteeing that allergens occur at concentrations lower than those harmful for human health and established by law. Hence, the concept of food analysis has increasingly grown in complexity and has followed up on new public health issues, new international regulations and standards, emerging consumer demands, novel safety emergencies, and globalization of the food market.

Methods based on wet-chemistry are currently outdated, and have been increasingly replaced by powerful instrumental techniques that enable significant enhancements in analytical accuracy, precision, and detection limits. The emerging technologies overcome the main disadvantages of conventional methods, such as laborious sample preparation, time-consuming analysis, and production of great amount of toxic wastes, so as to comply with the principles of green chemistry.

In this chapter, an overview of the conventional and emerging methods mostly applied to the analysis of macronutrients and minerals is provided, with a focus on green techniques and some of the current issues that food analysis has to face.

1.2 Carbohydrates

1.2.1 Definition of dietary carbohydrates and classification thereof

Carbohydrates are organic compounds chemically composed of carbon, hydrogen, and oxygen. They are produced by plants from carbon dioxide (CO2) and water, using energy harnessed from sunlight. Dietary carbohydrates are almost exclusively from plants. Cereals, legumes, potatoes, roots, fruit, and vegetables are the major sources of food carbohydrates. Milk is a valuable source, as well.

Besides occurring as natural food components, carbohydrates can be added to food products to improve the texture and quality thereof. Carbohydrates provide foods with a number of peculiar properties. They are responsible for the sweet taste of foods and for the generation of flavors and aromas of bakery products; they provide stability to emulsions and foams, and to freezing and thawing; they have gelling properties and provide desirable textures, such as crispness or smooth. Moreover, thanks to their ability of lowering water activity, carbohydrates improve food shelf life.

Dietary carbohydrates may have different physiological fates, depending on their chemical identity and/or their exposure to food processing. In human body, they take part in several physiological functions:

• provide energy;

• partake in the control of blood glucose and insulin metabolism;

• contribute to satiety and gastric emptying and participate in the metabolism of cholesterol and triglyceride (TG); and

• influence gastrointestinal processes, such as laxation and fermentation.

Carbohydrates can be primarily classified according to their chemical features (Gerschenson, Rojas, & Fissore, 2017XXX). Based on their degree of polymerization (DP), they are categorized into three groups: sugars, oligosaccharides, and polysaccharides, as shown in Table 1.1.

Table 1.1

Sugars have a DP ranging from 1 to 2 and comprise:

1. monosaccharides, such as glucose, galactose, and fructose;

2. disaccharides, such as sucrose, lactose, maltose, and trehalose; and

3. polyols, such as sorbitol and mannitol.

The DP of oligosaccharides ranges from 3 to 9. They include maltooligosaccharides, mainly obtained from starch hydrolysis, and other oligosaccharides such as raffinose, stachyose, and fructooligosaccharides (FOS).

Polysaccharides have a DP higher than 9. They may be subgrouped into starch and nonstarch polysaccharides. The formers comprise amylose, amylopectin, and modified starches, while the latters include a varied group of compounds, such as cellulose, hemicellulose, pectins, and hydrocolloids that are not digested by human body.

While the Joint FAO/WHO Expert Consultation Report (1998)XXX includes polyols in the sugar group, Regulation (EU) No. 1169/2011 clearly states that polyols are excluded from sugars. Hence, the definition of sugar includes only monosaccharides and disaccharides. Food polyols may be naturally occurring or chemically synthesized. The latter are used as sweeteners, since they are not absorbed in the small intestine (Lunn & Buttriss, 2007XXX).

Pertaining to their physiological and nutritional role, carbohydrates can be classified into available carbohydrates and unavailable carbohydrates. Carbohydrates that are hydrolyzed to monosaccharides, are absorbed in the small intestine, and enter the pathways of carbohydrate metabolism, thanks to the activity of enzymes in the human gastrointestinal system, are referred to as available carbohydrates. They commonly comprise starch polymers. In contrast, carbohydrates that are not hydrolyzed by endogenous human enzymes and are fermented in the large intestine are referred to as unavailable carbohydrates. The fermentable short chain carbohydrates and polyols poorly absorbed by the small intestine are referred to as FODMAPs (Fermentable Oligosaccharides, Disaccharides, Monosaccharides and Polyols).

In 2010 the European Food Safety Authority (EFSA) provided a scientific opinion on dietary reference values (DRVs) for carbohydrates and dietary fiber (DF; EFSA, 2010). In this document, carbohydrates have been classified as glycemic carbohydrates and dietary fiber. The formers refer to carbohydrates digested and absorbed in the human small intestine; monosaccharides, disaccharides, maltooligosaccharides, and starch are the main glycemic carbohydrates. The term dietary fiber is referred to as nondigestible carbohydrates passing to the large intestine. In the abovementioned opinion, the definitions of sugars and added sugars are also reported. The term sugars refers to monosaccharides and disaccharides, while added sugars comprise sucrose, fructose, glucose, starch hydrolysates such as glucose syrup and high-fructose syrup, and other sugar preparations used as such or added during food manufacturing (EFSA, 2010). The sum of naturally occurring sugars and added sugars is referred to as total sugars.

According to the World Health Organization (WHO), sugars can be categorized as: (1) intrinsic sugars, that is, sugars naturally present in fruit, vegetables, and milk; and (2) free sugars, that is, mono- and disaccharides added by the manufacturer during food manufacturing or cooking, and sugars naturally present in syrups, honey, and fruit/vegetable juices that are in excess compared with the same volume of 100% fruit and vegetable juice of the same type (WHO, 2015XXX).

1.2.1.1 Dietary fiber

So far, no single definition of DF has been agreed upon food scientists and international organizations. Many scientific communities and regulatory bodies have attempted to provide a clear definition of DF for scientific and legal purposes.

Regulation (EU) No. 1169/2011 defines as dietary fiber carbohydrate polymers with three or more monomeric units, which are neither digested nor absorbed in the human small intestine and belong to the following:

i. edible carbohydrate polymers naturally occurring in the food as consumed;

ii. edible carbohydrate polymers that have been obtained from food raw material by physical, enzymatic, or chemical means and which have a beneficial physiological effect demonstrated by generally accepted scientific evidence; and

iii. edible synthetic carbohydrate polymers that have a beneficial physiological effect demonstrated by generally accepted scientific evidence (EU, 2011).

In 2010 in the advice on DRVs for carbohydrates and DF, EFSA defined DF as nondigestible carbohydrates and lignin, including: (1) nonstarch (polysaccharides), that is, cellulose, hemicelluloses, pectins, and hydrocolloids (i.e., gums, mucilages, and β-glucans); (2) resistant oligosaccharides, such as FOS, galactooligosaccharides, and other resistant oligosaccharides, (3) resistant starch (consisting of physically enclosed starch, some types of raw starch granules, retrograded amylose, and chemically and/or physically modified starches); and (4) lignin, associated with the DF polysaccharides (EFSA, 2010).

According to Food and Drug Administration (FDA) definition, the term DF refers to nondigestible soluble and insoluble carbohydrates, with three or more monomeric units, and lignin that are intrinsic and intact in plants; isolated or synthetic nondigestible carbohydrates, with three or more monomeric units, determined by FDA to have physiological effects that are beneficial to human health (FDA, 2016XXX). While the EU and FDA definitions include carbohydrate polymers of three or more monomeric units in DF, the Codex Alimentarius specifies that the number of monomers constituting the carbohydrate polymers is 10 or more.

According to American Association for Clinical Chemistry (AACC) International, DF is the edible part of plants or analogous carbohydrates that are resistant to digestion and absorption in the small intestine with complete or partial fermentation in the large intestine. Polysaccharides, oligosaccharides, lignin, and associated plant substances are included in DF (AACCI, 2001XXX). Beneficial physiological effects, such as laxation and/or blood cholesterol attenuation and/or blood glucose attenuation, are promoted by DF. This definition covers the origin, chemistry, and physiology aspects of DF.

DF might be also referred to as nonstarch polysaccharides fiber or as Association of Official Agricultural Chemists (AOAC) fiber. Nonstarch polysaccharide fiber includes polysaccharides of the plant cell wall components typical of plant foods. AOAC fiber comprises nondigestible carbohydrates, such as lignin and resistant starch. In addition, the AOAC fiber includes nonstarch polysaccharide fiber and nondigestible carbohydrates that can be added as ingredients to foods.

A conventional but rather outdated approach for DF classification is based on its solubility in water. Soluble fiber comprises noncellulosic polysaccharides, oligosaccharides, pectins, β-glucans, and gums. Insoluble fiber comprises cellulose, hemicellulose, and lignin (Li & Komarek, 2017XXX). In an attempt to relate the chemical properties of fibers with their physiological effects, soluble fiber was associated with lowering and moderating cholesterol and postprandial blood glucose, while insoluble fiber was associated with improved laxation and increased fecal bulk (Slavin, 2013). However, this relationship is inconsistent: inulin and oligofructose are soluble fibers with demonstrated ability to increase fecal weight and do not appear to lower blood cholesterol (Slavin, 2013).

1.2.2 Labeling of carbohydrates in the EU

1.2.2.1 Labeling of sugars in the EU

According to Regulation (EU) No. 1169/2011 of the European Parliament and of the Council on the provision of food information to consumers, the nutrition declaration must include the content of carbohydrates and sugars (EU, 2011). Nutritional claims on sugars are admitted by Regulation (EC) No. 1924/2006 (EC, 2006). The claim Sugar-free indicates that the product contains no more than 0.5 g of sugar per 100 g or 100 mL. The no added sugars claim designates products not containing any added mono- or disaccharides, nor other components used as sweetener. The claim naturally occurring sugars appears in products containing only naturally present sugars. When the product contains no more than 5 g of sugar per 100 g for solids or 2.5 g of sugar per 100 mL for liquid, the claim low sugars can be applied (EC, 2006).

1.2.2.2 Labeling of dietary fiber in the EU

In Regulation (EU) No. 1169/2006, the declaration of DF content on the nutrition label is voluntary (EU, 2011). Regulation (EU) No. 1924/2006 laid down two nutrition claims related to DF: (1) source of fiber; and (2) high in fiber. The former is applied when the product contains at least 3 g of fiber per 100 g or at least 1.5 g of fiber per 100 kcal. The latter is used when the product contains at least 6 g of fiber per 100 g or at least 3 g of fiber per 100 kcal (EC, 2006).

1.2.3 The importance of carbohydrate analysis

Carbohydrates contribute to the sweetness, appearance, and textural characteristics of many foods. As far as their effects on human body are concerned, they are an important source of energy, can affect a number of physiological functions, such as blood glucose and cholesterol control, and may influence intestinal functionality.

Hence, determining the concentration of carbohydrates and characterizing them are important for assessment of food quality, economic value of food products, compliance with nutritional labeling, adulteration, and efficiency of food processing.

1.2.4 Traditional and emerging methods for sample preparation in carbohydrate analysis

Sample preparation depends on both the specific carbohydrate being determined and the food product being analyzed. Whichever carbohydrate is going to be determined and whichever matrix is going to be analyzed, the sample preparation in the analysis of carbohydrates is a critical step, as other nutrients, e.g., lipids and/or proteins, may interfere with their determination and quantification. Hence, the first step in carbohydrate analysis is drying to constant weight. Then, carbohydrates are separated from other food components. It is important to remove quantitatively lipids and lipid-soluble substances using a Soxhlet extractor or by extraction with petroleum ether or hexane, in order to enable a complete extraction of water-soluble carbohydrates (Nielsen, 2017). Fractionation might be required after extraction if the extracted sample is too complex to be analyzed.

Several methods can be used for carbohydrate extraction and fractionation: liquid chromatography (LC) and gas chromatography (GC) are the most commonly used (Sanz & Martínez-Castro, 2007XXX). These techniques are, however, time-consuming and labor-intensive, and require high volume of solvent. Currently, the new challenge in carbohydrate analysis is the use of green techniques and possibly of green solvents. An ideal green solvent should

1. be easily biodegradable in the environment;

2. have low toxicity to humans and other organisms;

3. be naturally occurring and/or produced from renewable sources; and

4. not require traditional evaporation steps (Montañés & Tallon, 2018).

In the following paragraphs, traditional and emerging methods for sample preparation in carbohydrate analysis are presented and compared.

1.2.4.1 Carbohydrate extraction and fractionation

Liquid–liquid extraction and green solvents

Liquid–liquid extraction is a technique commonly used in carbohydrate analysis. It is based on the partition of analytes between two immiscible liquids. It requires the use of great amounts of organic solvents. Many of them are toxic, flammable, corrosive, and harmful to analysts, and also contribute to environmental pollution. Their recovery and reuse require energy-intensive distillation, as well.

Green solvents, such as ionic liquids (ILs), supercritical fluids, and deep eutectic solvents, have been used in carbohydrate synthesis and in recovery thereof from biomasses and food waste (Farrán et al., 2015XXX). The use of ILs in carbohydrate chemistry has been reported by Prasad et al. (Prasad, Kale, Kumar, & Tiwari, 2010XXX). Xu et al. investigated the use of ILs for the extraction of aminoglycosides from milk samples (Xu et al., 2013XXX). As far as the application of green solvents in food analysis is regarded, few studies are reported. The IL 1-n-butyl-3-methylimidazolium chloride has been used to analyze variations in the carbohydrate composition of banana pulps in order to evaluate their ripening stage by high-resolution ¹³C-nuclear magnetic resonance (NMR) spectroscopy (Fort, Swatloski, Moyna, Rogers, & Moyna, 2006XXX).

Solid-phase extraction

Solid-phase extraction (SPE) is a separation technique based on the partition of the targeted analyte between a solid phase and a liquid phase. The former is commonly a sorbent held in a column, while the latter is the sample matrix or a solution of analytes (Ötles & Kartal, 2016XXX). Appropriate SPE extraction sorbents must be selected depending on the understanding of interactions between sorbent and analyte of interest. Reverse-phase cartridges, such as octyl (C8) and octadecyl (C18) silica phases, are commonly used for carbohydrate purification: they have higher affinity for hydrophobic compounds and lower affinity for hydrophilic solutes, namely, oligosaccharides. C18 cartridges have been also applied for the fractionation of (1–4)-α-glucans (Ötles, 2011). Ion-exchange SPE has been used for desalting oligosaccharide mixtures (Soria, Brok, Sanz, & Martínez-Castro, 2012XXX). Robinson et al. purified milk oligosaccharides by graphitized carbon-SPE (Robinson, Colet, Tian, Poulsen, & Barile, 2018XXX).

Supercritical fluid extraction

Supercritical fluid extraction (SFE) is based on the use of fluids at pressure and temperature above their critical points, that is, at conditions where there is no distinction between the gas and liquid phases. A supercritical fluid has gas-like properties, such as diffusion, viscosity, and surface tension, and liquid-like properties, namely, density and solvation power. Thanks to that, SFE enables shorter time and higher extraction yields than conventional methods.

CO2 is the solvent of choice for SFE, since its critical temperature is close to room temperature (≈31°C) and its critical pressure allows operating at moderate pressures (Zhu et al., 2016). CO2 has additional advantages: it is odorless, tasteless, inert, and inexpensive. SFE by using CO2 as fluid has been widely used in the recovery of carbohydrates from food waste, despite the low polarity of this fluid (Herrero, Mendiola, Cifuentes, & Ibáñez, 2010XXX). In order to increase carbohydrate solubility, ethanol/water is used as cosolvent to obtain selective fractionations. This technique has been used to fractionate carbohydrate mixtures produced by enzymatic transglycosylation (Montañés et al., 2008XXX; Montañés, Fornari, Olano, & Ibáñez, 2012XXX), to extract carbohydrates from barley hull (Sarkar, 2013XXX), and to extract inulin from food plant material (Zhu et al., 2016).

Pressurized liquid extraction

Pressurized liquid extraction (PLE) is a sample preparation technique based on the extraction of analytes from semisolid or solid matrices by using solvents under elevated temperature (50°C–200°C) and pressure (500–3000 psi) conditions for short time periods (5–10 min) (de la Guardia & Armenta, 2011). High temperatures and pressures increase, in fact, the extraction efficiency. In detail, high temperatures promote solubility of targeted analyte in the solvent, encourage the diffusion of the analyte to the matrix surface, and increase the diffusion rate of the analyte in the solvent. Hence, the solvation power of solvents is enhanced and the extraction rates increased. High pressures allow the solvent to remain under its boiling point and promote its penetration in the food matrix (de la Guardia & Armenta, 2011; Picó, 2017).

This technique combines the benefits of high throughput, automation, and low solvent consumption (de la Guardia & Armenta, 2011). Thanks to the small volume of organic solvent generated and the reduction of analysis time and cost, it is considered a green technique. Despite that, the presence of rather high percentages of water in the sample to be analyzed decreases the analyte extraction efficiency when using hydrophobic organic solvents, since water hampers the contact between the solvent and the analyte (de la Guardia & Armenta, 2011).

PLE can be performed in both static and dynamic modes. It is also referred to as accelerated solvent extraction (ASE), pressurized solvent extraction, high-pressure solvent extraction, high-pressure high temperature solvent extraction, pressurized hot solvent extraction, and subcritical solvent extraction (Duarte, Justino, Gomes, Rocha-Santos, & Duarte, 2014XXX). When water is used as solvent, in the condensed phase between 100°C and the critical point, the technique is referred to as subcritical water extraction, hot water extraction, pressurized hot water extraction, or high temperature water extraction (de la Guardia & Armenta, 2011; Picó, 2017).

PLE has been applied in the determination of carbohydrate content in the edible mushrooms Cordyceps (Guan, Yang, & Li, 2010XXX). Alongside microwave extraction, PLE has been also used to isolate low-molecular-weight (LMW) carbohydrates, such as inositol, and inulin from artichoke internal bracts (Ruiz-Aceituno, García-Sarrió, Alonso-Rodriguez, Ramos, & Sanz, 2016XXX). It was also applied to the extraction of bioactive carbohydrates from mulberry (Morus alba) leaves (Rodríguez-Sánchez, Ruiz-Aceituno, Sanz, & Soria, 2013XXX).

Field flow fractionation

Field flow fractionation (FFF) is a separation technique based on the interaction of the analyte with an externally generated field (possibly electric, thermal, magnetic, or gravitational), applied perpendicularly to the direction of the mobile phase flow. Basically, a laminar flow of mobile phase sweeps sample analytes within a capillary. The applied field drives the analytes into different laminar flows, depending on their size, density, and surface properties (Roda et al., 2009XXX). In carbohydrate analysis, FFF enables to fractionate polysaccharides, such as cellulose, starch, and pullulan (Ötles, 2011). In food analysis, FFF has been applied to determine the molecular size distribution of starches and modified celluloses, and to study protein aggregation during food processing. Qureshi and Kok reported on the application of FFF to the characterization of polysaccharides used as thickeners and dispersing agents (Qureshi & Kok, 2011XXX).

Chromatography-based methods

Chromatography-based methods are commonly applied to carbohydrate fractionation. They require the use of open columns with stationary phases, based on anion exchange, adsorption, or gel-filtration/permeation mechanisms. Few recent applications of chromatography-based methods in carbohydrate analysis are reported. Mariño et al. applied weak anionic-exchange chromatography in milk carbohydrate analysis (Mariño et al., 2011XXX), while Jantscher-Krenn et al. used gel-filtration chromatography in the analysis of oligosaccharides and separation thereof from lactose and salts in human milk (Jantscher-Krenn, Lauwaet, et al., 2012XXX; Jantscher-Krenn, Zherebtsov, et al., 2012XXX). The use of gel-filtration matrices has some shortcomings: many of them, such as Sephadex and Sepharose, are themselves carbohydrates; hence, they shed carbohydrate polymers into the mobile phase. Moreover, nonspecific interactions with matrix materials can occur because of the amphipathic properties of sugars.

Membranes

Ultrafiltration and nanofiltration have been applied to carbohydrate sample preparation. These techniques are based on the use of membranes selected upon the value of the molecular mass of the smallest compound retained to an extent larger than 90% (molecular weight cutoff). Recently, Mehra et al. prepared powders enriched in bovine milk oligosaccharides by membrane filtration technology (Mehra et al., 2014XXX).

1.2.4.2 Acid hydrolysis and derivatization for traditional analysis of monosaccharides and oligosaccharides

As aforesaid, high-performance liquid chromatography (HPLC) and GC are commonly used in the determination of monosaccharides. The use of these techniques allows a qualitative and quantitative characterization of samples. Compared with enzymatic methods, they enable the simultaneous separation and determination of carbohydrates in a single analysis. However, when determining the composition of polysaccharides by HPLC, a depolymerization step is required. It consists of treating samples with a strong acid and heat. In these conditions, the glycosidic bond between the monosaccharide residues is cleaved. Sulfuric acid and trifluoracetic acid are commonly used. The latter is preferred, since it can be easily removed prior to HPLC analysis. If GC is used for monosaccharide analysis, derivatization is necessary in order to make carbohydrates volatile. Neutral sugars are analyzed by GC as alditol acetates obtained by reduction and acetylation, while acidic sugars are determined by GC as trimethylsilyl or trifluoroacetyl ethers.

1.2.5 Emerging technologies for carbohydrate analysis

Several analytical techniques have been applied to carbohydrate analysis: spectroscopic methods such as UV-Vis, fluorescence, infrared (IR), Raman, atomic absorption, atomic emission, NMR, and mass spectrometry (MS). Separation methods, such as LC and GC, have been used. Novel approaches such as biosensors, hyperspectral imaging (HSI), and hyphenated techniques will be discussed in this section.

1.2.5.1 Biosensors

Biosensors are analytical devices consisting of a bioreceptor element, recognizing the targeted analyte and a transducer converting the biological response into a measurable electrical signal (Monosik, Stredansky, Tkac, & Sturdik, 2012). Enzymes, antibodies, DNA, and microorganisms can be used as bioreceptor elements. A broad classification categorizes biosensors into enzymatic and nonenzymatic (Hu, Sun, Pu, & Pan, 2016XXX). Enzymatic biosensors have been used in the determination of sugars. Glucose oxidase (GOD) and d-fructose dehydrogenase are the most commonly used enzymes in glucose and fructose enzymatic biosensors. Invertase and mutarotase are used in sucrose enzymatic biosensors. Sucrose is hydrolyzed into fructose and glucose by an invertase, then α-d-glucose is converted into β-d-glucose by mutarotase, and finally, GOD is used (Monosik et al., 2012).

Recently, the content of glucose in fruit homogenates has been detected by using an enzymatic biosensor based on GOD (Ang, Por, & Yam, 2015XXX). Enzymatic biosensors have also been applied to the determination of glucose in raw fruits by using a continuous flow system (Vargas, Ruiz, Campuzano, Reviejo, & Pingarrón, 2016XXX). This method still has some drawbacks such as the need of pretreatments like homogenization, filtering, and dilution in order to obtain solutions as pure as possible. Nonenzymatic biosensors are based on synthetic biomimetic enzymes. A biosensor of a new polyvinyl acetate electrode reinforced by MnO2/CuO loaded on graphene oxide nanoparticles was developed for glucose determination (Farid, Goudini, Piri, Zamani, & Saadati, 2016XXX).

1.2.5.2 Supercritical fluid chromatography and supercritical fluid chromatography-mass spectroscopy

Supercritical fluid chromatography (SFC) is a separation technique based on the use of supercritical fluid, mostly CO2, in combination with one or more polar organic solvents, especially alcohols, used as mobile phase. SFC instrumentation is obtained adapting LC or GC systems. In SFC equipment similar to HPLC instruments, the mobile phase is a binary or ternary solution, with CO2 being the main component. The separation is commonly obtained as gradient elution. The most common detector used is the ultraviolet (UV). Compared with HPLC, SFC requires shorter time and more rapid equilibration; hence, it enables to analyze more samples in a day. In addition, lower amounts of solvents are consumed, and CO2 can be easily removed and lower energy is required in fractionation and evaporation. SFC thus meets the law requirements for environmental protection and has a reputation as green technique. Few shortcomings are reported: SFC pump system must have a chilled pump in order to have liquid CO2, and the system for UV detection must be under pressure (Taylor, 2010XXX). Compared with GC, SFC requires no derivatization and enables to analyze thermally labile compounds and solutes of higher molecular weight (Montañés & Tallon, 2018). The use of mobile phases modified with a certain proportion of water allowed using SFC in more polar compounds such as carbohydrates and amino acids (Fornari & Stateva, 2015XXX). The separation and/or analysis of carbohydrates by SFC have been reported in few studies. Lefler and Chen separated a mixture of fructose, glucose, sucrose, and neohesperidine dihydrochalcone by SFC (Lefler & Chen, 2008XXX). Preparative scale SFC was also used to separate derivatized anomeric monosaccharides (Montañés, Rose, Tallon, & Shirazi, 2015XXX).

Coupling of SFC to MS has been applied in the determination of carbohydrates and also of oils and lipids (Kaklamanos, Aprea, & Theodoridis, 2012XXX).

1.2.5.3 Liquid chromatography: high performance anion-exchange chromatography with pulsed amperometric detection

LC methods have been extensively used in the determination of carbohydrates in foods (Costa & Conte-Junior, 2015XXX; Weiß & Alt, 2017XXX). Silica-based amino-bonded, polymer-based and cation-exchange columns with refractive index or low wavelength UV detection have been used. However, these methods preclude the use of gradients and require sample acid hydrolysis and stringent clean up prior to injection. Moreover, they have a low sensitivity.

High-performance anion-exchange chromatography with pulsed amperometric detection (HPAE-PAD) allows overcoming some drawbacks of traditional LC methods used in carbohydrate analysis: it enables to quantify carbohydrates in their nonderivatized forms, at low picomole levels, with minimal sample preparation and clean up. It is extremely carbohydrate selective and specific: only carbohydrates containing functional groups that are oxidable at the targeted detection voltage are detected. Moreover, neutral or cationic sample components, other than carbohydrates, elute in or close to the void volume of the column; hence, there are no interferences with carbohydrates of interest. Since derivatization is unnecessary, sample preparation requires only the removal of interfering components such as lipids and proteins.

In HPAE-PAD systems for carbohydrate analysis, columns are coated with exchange resins, and sodium hydroxide is used as eluant to separate mono- and disaccharides. Sodium hydroxide is inexpensive and relatively safe. In oligosaccharide analysis, sodium acetate is used alongside sodium hydroxide. The former increases ionic strength and ensures proper pushing off of oligosaccharides from the column. The separation is based on the ability of carbohydrates to ionize in a strong alkaline environment. Moreover, the use of PAD enables to achieve low detection limits and to use gradient elution. HPAE-PAD also allows the separation of neutral and acidic monosaccharides in one analytical run. Recently, HPAE-PAD has been applied to the determination of carbohydrates in microalgae and has been found effective in resolving 13 monosaccharides (Templeton, Quinn, Van Wychen, Hyman, & Laurens, 2012XXX).

1.2.5.4 Hyperspectral imaging

HSI is a noninvasive and reagent-free spectral imaging technique, providing the spatial distribution of different components in samples with very high spectral resolution (Wu & Sun, 2013XXX). One of the peculiar properties of HSI is its ability to display the metabolite changes; hence, it can be applied in monitoring compositional changes in foods. The use of HSI systems as a scientific tool for quality assessment of fruit and vegetables has been reviewed by Lorente et al. (2012)XXX. More recently, Nogales-Bueno et al. described the application of near-infrared (NIR) HSI to assess the sugar content of red and white grapes (Nogales-Bueno, Hernández-Hierro, Rodríguez-Pulido, & Heredia, 2014XXX). Hu et al. developed a model based on HSI to assess blueberry postharvest quality (Hu, Dong, & Liu, 2016XXX).

1.2.6 Dietary fiber analysis

The analysis of DF is intimately related to its definition. So far, agreement on DF definition has not been achieved by scientific bodies and regulatory committees, and different components have been included in or excluded from DF. Hence, several official methods have been developed by the AOAC, today AOAC International, and by the AACC, each complying with a proper DF definition and periodically revised. They can be broadly categorized into: (1) enzymatic-gravimetric methods; and (2) enzymatic-chemical methods including the use of colorimetry, GC, and HPLC for quantification (Table 1.2). Enzymatic-gravimetric methods are commonly used for routine analyses, since they are simple, fast, and robust. Total, soluble and insoluble DFs can be determined. These methods involve sample treatment with a succession of enzymes to remove digestible material. Then, an ethanol precipitation enables to isolate nonstarch polysaccharides. Finally, ash and protein are determined and their content is subtracted from the dry residue weight to obtain total DF. The main shortcoming of enzymatic-gravimetric methods is the lack of information about the different DF components. In contrast, enzymatic-chemical assays, based on GC and HPLC, enable to determine all sorts of DF.

Table 1.2

AACC, American Association for Clinical Chemistry; AOAC, Association of Official Agricultural Chemists; FOS, fructooligosaccharides; IDF, insoluble dietary fiber; RS2, type-2 resistant starch; RS3, type-3 resistant starch; SDF, soluble dietary fiber; TDF, total dietary fiber; TGOS, trans-galactooligosaccharides.

Methods allowing the determination of compounds that behave physiologically as DF but are soluble in aqueous ethanol, such as fructans and polydextrose, have been selectively developed (AOAC Official method 997.08 and AOAC Official method 999.03 for fructans and AOAC Official method 2000.11). They are reported in Table 1.2 and enable a proper estimation of DF content. The most widely used method for DF analysis is the AOAC method 985.29. It requires sample treatment with 80% ethanol. As a consequence, digestible carbohydrates are solubilized in aqueous ethanol, while indigestible carbohydrates form a residue. Fructans are partially soluble in ethanol 80%; hence, they might be excluded from DF determination despite they can increase fecal bulk (Cui, 2005XXX). Due to the partial solubility of fructans in ethanol, inulinase is used in order to completely exclude fructans and prevent them from being counted twice and overestimate DF content.

Whichever official method is used, DF analysis is labor-intensive, is time-consuming, and requires skilled technicians, besides a large amount of laboratory space and glassware.

Efforts for automation of this analysis have been done. Bolen et al. reported on the effectiveness of ANKOMTDF Dietary Fiber Analyzer to automate the AOAC Method 991.43 fiber analysis (Bolen, Patel, Mui, Kasturi, & Challa, 2018XXX) and on the validation thereof. The AOAC Official Method 991.43 enables to determine total dietary fiber, insoluble dietary fiber, and soluble dietary fiber in food products. Despite being one of the most commonly used methods among the scientific community, it requires several steps, such as sample homogenization, desugaring, defatting, enzymatic digestion of starch and protein, and protein and ash measurements, and an analysis may take from 3 to 7 days to complete. Barrington Analytical Laboratory has partnered with ANKOM Technology (Macedon, NY, United States) for the automation of this complex analytical procedure and developed the ANKOMTDF analyzer. It enables to increase productivity and efficiency, to simplify sample handling, to lower glassware clean up, to simplify analyst training, and to increase laboratory safety.

1.3 Fat and fatty acids

1.3.1 Definition of dietary fat and sources thereof

Dietary fats are food components playing several important roles in human body. They supply energy (about 9 kcal/g), act as structural components of cell membranes, are precursors of some hormones, bile acids, and bioactive compounds, act as carriers for nutrients, such as fat-soluble vitamins, and take part in many vital processes. The influence of dietary fats on inflammatory gene expression has been also reported (Rocha et al., 2017XXX). Dietary fats mainly consist of TGs (or triacylglycerols), mono- and diglycerides, phospholipids, and cholesterol (Erdman, MacDonald, & Zeisel, 2012XXX). From a structural point of view, TGs are composed of three fatty acids (FAs) attached to a glycerol backbone. Based on the number of carbon atoms and number of double bonds they possess, TGs can be classified into: (1) saturated fatty acids (SFA); and (2) unsaturated FAs. The former can be further categorized into short, medium, long, and very long chain FAs, based on their chain length.

Depending on the number of double bonds, unsaturated FAs can be subgrouped as: (1) monounsaturated FAs (MUFAs), which display only one double bond; and (2) polyunsaturated FAs (PUFAs), which have two or more double bonds. Some PUFA, such as alpha-linolenic acid (ALA) and LA, are considered essential, since they cannot be synthesized by human body and they must be thus supplied by the diet. Some long-chain PUFAs, such as eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA), are considered conditionally essential, since they can be synthesized by the human body contingent on having essential precursor FAs. Unsaturated FAs can be otherwise grouped as cis-isomers or trans-isomers, based on the geometric configuration of their double bonds. Trans-isomers are referred to as trans-FAs (TFA) and can be further divided into: (1) ruminant TFA; and (2) industrially produced TFA (iTFA). The formers are produced from unsaturated FAs in ruminant animals, due to the activity of rumen bacteria, while the latters are formed during the incomplete hydrogenation of oils, especially plant oils, into solid or semisolid fats (hydrogenated oils).

The main sources of dietary fat are: (1) butter, margarine, and vegetable oils; (2) meat and poultry; (3) milk and dairy products; (4) egg yolk; (5) nuts; and (6) a variety of processed foods. Dietary fat intake mostly occurs in the form of TGs (IOM, 2005XXX).

1.3.2 Labeling of fats in the EU

In Europe, Regulation (EU) No. 1169/2011 on the provision of food information to consumers lays down that the nutritional label of prepacked foods mandatorily displays declaration for total and saturated fats (EU, 2011). The content must be reported as grams per 100 g of product. The presence of partially or fully hydrogenated oils must also be declared in the ingredient list, while the indication of the amounts of MUFA and PUFA is optional (EU, 2011). According to Regulation (EC) No. 1924/2006 (EC, 2006), the following fat-related nutrition claims can be reported on food packages:

a. Fat free: The product contains no more than 0.5 g of fat per 100 g or 100 mL.

b. Low fat: The product contains no more than 3 g of fat per 100 g for solids or 1.5 g of fat per 100 mL for liquids (1.8 g of fat per 100 mL for semiskimmed milk).

c. Saturated fat free: The sum of saturated fat and TFAs does not exceed 0.1 g of saturated fat per 100 g or 100 mL.

d. Low saturated fat: The sum of SFA and TFAs in the product does not exceed 1.5 g per 100 g for solids or 0.75 g/100 mL for liquids, and in either cases, the sum of SFA and trans-FAs must not provide more than 10% of energy.

e. Source of omega-3 fatty acids: The product contains at least 0.3 g ALA per 100 g and per 100 kcal, or at least 40 mg of the sum of EPA and DHA per 100 g and per 100 kcal.

f. High omega-3 fatty acids: The product contains at least 0.6 g ALA per 100 g and per 100 kcal, or at least 80 mg of the sum of EPA and DHA per 100 g and per 100 kcal.

g. High unsaturated fat: At least 70% of the FAs present in the product is from unsaturated fat under the condition that unsaturated fat provides more than 20% of energy of the product.

h. High monounsaturated fat: At least 45% of the FAs present in the product is from monounsaturated fat under the condition that monounsaturated fat provides more than 20% of energy of the product.

i. High polyunsaturated fat: At least 45% of the FAs present in the product is from polyunsaturated fat under the condition that polyunsaturated fat provides more than 20% of energy of the product.

The Report from the Commission to the European Parliament and the Council regarding trans fats in foods reports that no indication on the TFA content must be displayed (EC, 2015). However, Regulation (EU) No. 2019/649 of 24 April 2019, amending Annex III to Regulation (EU) No. 1925/2006 of the European Parliament and of the Council, harmonizes the limit for iTFA in food intended for the final consumer, across all the EU Member States. It lays down that the content of iTFA, in food intended for the final consumer, shall not exceed 2 g per 100 g of fat (EU, 2019XXX). In fact, a high intake of iTFA has been found to increase seriously the risk of heart disease more than any other nutrient on a per calorie basis (EC, 2015).

1.3.3 The importance of fat analysis

According to EFSA, the reference intake (RI) for fats should be lower than 35% (EFSA, 2017). The effect of fat intake and metabolites thereof on human health might be beneficial or detrimental depending not only on the total fat intake but also on the type of fat. Omega-3 FAs (i.e., ALA, EPA, and DHA) have beneficial effects, as they protect from the risk of Non Communicable Diseases (Abraham & Speth,