System Biological Research on Food Quality for Personalised Nutrition and Health Using Foodomics Techniques: A Review

Abstract

Food quality is closely related to human health as people obtain energy from food. Traditional food science focuses on the provision of enough food for health guarantee. With economic development, people have a rising demand on quality and safety of the food they eat. Today, people are not only interested in eating sufficient and appropriate food, but expect to prevent diseases or treat existing diseases with diets. The development of the systems biology, especially various omics tools, is beneficial to the study of the impact of food compositions and ingredients on human health, advancing traditional food research into a new age: foodomics. Foodomics aims at studying the relationship between food quality and safety and food compositions and nutrition using omics tools such as genomics, transcriptomics, proteomics, and metabolomics, in addition to analytical techniques including chemometrics and bioinformatics. This review discusses recent advances in foodomics research.

Full text

Journal of Food and Nutrition Research, 2014, Vol. 2, No. 9, 608-616
Available online at http://pubs.sciepub.com/jfnr/2/9/13
© Science and Education Publishing
DOI:10.12691/jfnr-2-9-13
System Biological Research on Food Quality for
Personalised Nutrition and Health Using Foodomics
Techniques: A Review
Chuangmu Zheng1,2, Ailiang Chen1,2,*
1Institute of Quality Standard & Testing Technology for Agro-Products, Key Laboratory of Agro-product Quality and Safety, Chinese
Academy of Agricultural Sciences, Beijing, China
2Key Laboratory of Agro-product Quality and Safety, Ministry of Agriculture, Beijing, China
*Corresponding author: ailiang.chen@gmail.com
Received July 02, 2014; Revised September 01, 2014; Accepted September 08, 2014
Abstract Food quality is closely related to human health as people obtain energy from food. Traditional food
science focuses on the provision of enough food for health guarantee. With economic development, people have a
rising demand on quality and safety of the food they eat. Today, people are not only interested in eating sufficient
and appropriate food, but expect to prevent diseases or treat existing diseases with diets. The development of the
systems biology, especially various omics tools, is beneficial to the study of the impact of food compositions and
ingredients on human health, advancing traditional food research into a new age: foodomics. Foodomics aims at
studying the relationship between food quality and safety and food compositions and nutrition using omics tools
such as genomics, transcriptomics, proteomics, and metabolomics, in addition to analytical techniques including
chemometrics and bioinformatics. This review discusses recent advances in foodomics research.
Keywords: foodomics, food quality, food safety, nutrition, health
Cite This Article: Chuangmu Zheng, and Ailiang Chen, “System Biological Research on Food Quality for
Personalised Nutrition and Health Using Foodomics Techniques: A Review.” Journal of Food and Nutrition
Research, vol. 2, no. 9 (2014): 608-616. doi: 10.12691/jfnr-2-9-13.
1. Introduction
Food safety once has been, and remains undoubtedly a
focus of attention of consumers. Nevertheless, with
improvement of living standards, people nowadays have
sufficient food to feed themselves and have higher
requirements on food nutrition. People expect to know
exact contents of their diets, and identify various foods
that improve health and prevent possible diseases. Thus, a
high requirement is imposed on food research
improvement. Food constitutes a highly complex system,
and traditional assessment instruments based upon
analysis of constituents and components are ineluctably
restricted by the factors such as the extraction methods.
Moreover, from the perspective of food nutrition,
emphasis on specific ingredients often leads to neglect of
other ingredients or components that promote or impact
health. Needless to say, study only on the effects of
specific functional ingredients of food on specific
metabolic pathways will also lead to neglect of the impact
of food on the entire human body (Capozzi and Bordoni
2013). Foodomics has emerged as a new science with the
increase of people's concern about food safety and food
nutrients and the development of analysis techniques of
high-throughput omics (genomics, transcriptomics, and
metabolomics) in the postgenomic era (Capozzi and
Bordoni 2013). Additionally, the completion of genome
sequencing of animals and plants that feed people has
provided foundation for the application of various omics
techniques.
The concept of foodomics first appeared in 2007 (N and
I 2007, FoodOmics 2009). In 2009, professor Alejandro
Cifuentes from the Institute of Food Science Research
(CIAL) of the National Research Council of Spain first
defined foodomics as a new discipline that studies the
food and nutrition domains by using omics technologies,
as reported in Journal of chromatography A (Cifuentes
2009). The goal of foodomics research is to improve
consumers' well-being and health (Capozzi and Bordoni
2013, Herrero et al,. 2010, Herrero et al,. 2012, Cifuentes
2013). Therefore, the research objects of foodomics cover
two domains: food science and nutrition science. By using
a variety of omics techniques (e.g., nutrigenomics,
microbial genomics, toxicogenomics, nutritranscriptomics,
nutriproteomics, nutrimetabolomics, and systems biology),
foodomics combines agricultural products, food
compositions, and dietary structure with individual
physical trait differences for health maintenance and
disease prevention (Capozzi and Bordoni 2013).
Subsequently, researches have been carried out on food
quality, traceability, food safety and assessment, food
ingredients and nutrition mechanism, ripening and food
processing of post-harvest agricultural products, and

609 Journal of Food and Nutrition Research
health-enhancement food products in relation with disease
prevention.
The concept of foodomics is a natural result of food
science development when the systems biology techniques
are applied to the research of food nutrition and health.
Since the completion of human genome project (HGP),
scientists have conducted researches on the physiological
and biochemical mechanisms in vital processes from the
aspects of genes (including epigenome, single-nucleotide
polymorphism (SNP), etc.), RNAs (including mRNAs,
miRNAs, and LiRNAs), proteins, small molecule
metabolites, and other aspects of the systems biology.
Human health conditions are susceptible to genetic,
environmental, and other factors, among which nutrients
from people's diets are closely related to health. Food-
related nutritional and health issues have become a major
research direction in food science, and systems biology
approaches become basic research tools. Moreover, food
science is a comprehensive discipline that encompasses
various subjects in different fields such as physics,
biology, chemistry, and medical science. As a matter of
fact, foodomics is the application of systems biology
approaches in food science.
Soon after the concept of foodomics is proposed,
numerous scientists who are specialized in fields related to
foodomics quickly responded. Since 2009, International
Conference on Foodomics has been held every two years
in Italy, and the third conference was held
(http://foodomics.eu/) in 2013. In 2012, the
Electrophoresis magazine published a special issue on
"Food analysis in the postgenomic era: Foodomics
(Cifuentes 2012)," which elaborated the scope of
researches and analysis approaches of foodomics. In
November 2013, Prague of Czech Republic hosted the
sixth international symposium on recent advances in food
analysis, in which foodomics was listed as one of the
thematic forums. In May 2013, the 10th International
Conference of Food Science and Technology (ICFST) was
held in Jiangnan University located in Wuxi of Jiangsu
province in China, and foodomics was one of the 12
theme subjects under discussion.
The research methods and instruments of foodomics
include food chemistry, analytical chemistry, biochemistry,
molecular biology, food technology, and clinical science.
With the purpose of enhancing the overall understanding
of foodomics from different fields, this review gives a
brief introduction to the scope of this research and
analytical methods apart from the concept of foodomics.
2. Main Applications of Foodomics
Researches
Two aspects in foodomics research are the food quality
and safety and the relationship between food nutrition and
health.
2.1. Food Quality and Safety Research
With economic development and trade globalization,
food quality and safety issues start to draw global
attention. Many nations are taking effort to boost research
on food quality and safety not only in order to provide
sufficient nourishing foods for consumers but also to
protect consumers from food fraud and drug and pesticide
residue contamination. Foodomics facilitates systematic
research on food quality and safety by including the
compositions and quality of food, food discrimination and
traceability, assessment of genetically modified foods,
detection of food allergens, biotoxins, and other hazardous
factors, impact of post-harvest storage and processing on
active constituents of food into its research scope
(Picariello et al,. 2012).
Food contamination detection and traceability/
authentication. Foodomics greatly improves
comprehensive analysis and research on food
contaminants and allergens by identifying biomarkers for
unsafe food so that unsafe food can be detected at an early
stage to protect consumers. It can also facilitate
establishment of more reliable approaches to food origin
traceability and authentication. Nowadays, food
components are various, and potential hazardous matters
in food might differ tremendously. Traditional targeted
analysis cannot detect contaminants and hazardous matters
in food other than the target analyte. The metabolomics
technique based on mass spectrometry provides a
possibility of non-targeted analysis of hazardous matters.
Mass spectrometry (MS) is so powerful that it can even
detect unknown compounds and conduct structural
analysis. What's more, it is easy to couple with highly
efficient separation techniques such as gas
chromatography (GC), high performance liquid
chromatography (HPLC), and capillary electrophoresis
(CE). Therefore, MS is a powerful instrument for analysis
and identification of the total components in food,
facilitating analysis of food quality and safety and origin
traceability (Castro‐Puyana et al,. 2013). For example,
Tengstrand et al. utilized the electron impact time-of-flight
mass spectrometry combined with ultra-high-pressure
liquid chromatography (UHPLC-EI-TOF-MS) technique
to identify the metabolic fingerprint of juice with various
contaminants (Tengstrand et al,. 2013). By screening and
selecting the peaks of abnormal compounds, they explored
a new method of identifying unknown contaminants in
juice. In the aspect of product authentication, many types
of food have similar appearance but different nutritional
values, which requires a developed food product
authentication method. By utilizing high performance
liquid chromatography/mass spectrometry (HPLC/MS),
protein mass spectrometry and peptide fingerprinting of
various foods can be analyzed, and specific peptide
biomarkers can be screened based on rapid identification
by HPLC coupled with multiple reaction monitoring mass
spectrometry (Ortea et al,. 2012). Food allergens cause
allergic reactions with people of specific groups. Specific
food ingredients are fatal supposed that allergic reactions
are severe. MS-based proteomics can effectively detect
food allergens that are usually neglected by traditional
nucleic acid detection or enzyme-linked immunosorbent
assay (ELISA) based on antigen-antibody reactions. If the
sample extraction process is optimized, traditional two-
dimensional electrophoresis and protein microarray
techniques will also be able to detect allergens as precisely
as at the parts per billion (ppb) level (Picariello et al,.
2013). Because stable isotope mineral and mineral
elements vary from one another in different regions, their
fingerprint spectra can be built by employing stable
isotope mass spectrometry and inductively coupled plasma

Journal of Food and Nutrition Research 610
mass spectroscopy (ICP-MS). This can then be used in
food origin traceability and identification of animals and
plants from different origins (Zhao et al,. 2014).
Monitoring and appraisal of production and
processing of foods. An increasing number of different
organic food products are present in the market, providing
consumers with a variety of choices. Organic foods are
produced in different ways from traditional foods, in terms
of pesticide and veterinary drug residues and nutritional
components. Therefore, traditional food analysis methods
such as targeted detection are no longer capable of
authenticating organic food products to ensure food
quality. By utilizing proteomics and metabolomics,
researchers can comprehensively compare organic and
traditional food products on the molecular level and
quickly identify organic food products in clusters
(D'Alessandro and Zolla 2012). People rely on animal-
derived foods such as meat, milk, and eggs as their main
sources of dietary proteins. Animal-derived foods are
susceptible to quality damage and putrefaction during
food processing, storage, and transportation. Therefore,
quality and safety monitoring of these foods is of
remarkable significance. Proteomics and metabolomics
instruments can be used to analyze the protein components
and composition changes during processing, storage, and
transportation of these products, in addition to identifying
proteins and small molecular markers related to food
quality. In this way, potential adulteration, food
putrefaction, and other food safety problems can be
identified (Cozzolino et al,. 2002, Gaso-Sokac et al,. 2010,
Gaso-Sokac et al,. 2011, Leitner et al,. 2006). Similarly,
the foodomics technologies including proteomics and
metabolomics can be utilized in authenticating and
analyzing chilled fresh meat and refrigerated meat. Protein
compositions and metabolite changes of post-slaughter
animal meat can also be studied to enhance meat product
quality and prolong shelf-life (D’Alessandro and Zolla
2013). Traditional fermented food products are prone to
safety risks due to their special manufacturing procedures.
Fast identification of specific small molecular matters
produced in the enzyme fermentation procedures of these
foods can be achieved using metabolomics techniques.
Then, these markers can be used for quality control of
these fermented foods with metabolic fingerprints built up
(Hannon et al,. 2007). In the 2013 Recent Advances in
Food Analysis (RAFA) conference, Clementine Le
Boucher from the French Academy of Agricultural
Sciences reported "Toward new comprehension of cheese
ripening." Using GC/MS and fingerprint analysis
techniques, the authors compared various cheeses
prepared with different fermentation time and found 45
different metabolites (12 amino acids, 25 volatile
constituents, 4 vitamins, and 1 carnitine) along with
unknown constituents by omics studies. The study
provides indicators for assessing various types of cheeses
with different ripening levels or different flavors.
Moreover, metabolomics can be applied to the research of
physiological changes in post-harvest fruits and vegetables,
providing theoretical foundation for the research of
preservation and control technologies of fruits and
vegetables (Ibanez et al,. 2012).
Agricultural products improvement and genetically
modified foods. Applying systems biology approaches in
the research of food sources (i.e. animals, plants, and
crops) to enhance the planting and breeding technologies
so as to increase productivity and promote quality is
indubitably significant for food safety improvement. For
instance, flatfish is extensively cultivated for its
appreciable nutritional and commercial values. During the
metamorphosis period when flounder larvae turn into
benthic, flatfish often dies from fatal diseases such as
pathological changes of fishbone and pigmentation
deposition. Therefore, the transcriptomics study of flatfish
is necessary in order to comprehensively understand the
physiological and biochemical processes of reproduction,
growth and development, nutrition supply, and
immunology, etc. Study on the nutritional needs of
flounder larvae in the process of metamorphosis and the
nutrients' impacts on its development and growth is
notably important. Better cultivation techniques and
feeding formulas can be derived to enhance the flatfish
quality and its nutritional value (Cerda and Manchado
2013, Murray et al,. 2010). MiRNAs regulate gene
expression of organisms in vivo. Fu et al. conducted study
on the changes of miRNA expression of flounder larvae
during metamorphosis by the RNA sequencing technology
and discovered miRNAs specific to pigmentation
deposition and deformation. This is massively significant
on the exploration of the regulatory network of gene
expression during the process of metamorphosis (Fu et al,.
2011). Genetically modified foods have always been
under dispute from the beginning. Backlash from
consumers and potential hazardous effects lead to various
restriction policies on the research, production, and sale of
genetically modified foods in all countries. Therefore,
comprehensive evaluation of transgenic products becomes
urgent and increasingly important. However, no single
traditional research method is able to implement
comprehensive assessment on the impacts of genetically
modified food on human health and environment. Instead,
foodomics analysis techniques are able to
comprehensively analyze the compositions of genetically
modified food on the levels of transcriptomics, proteomics,
and metabolomics. In the meantime, this study combines
bioinformatics and chemometrics methods to contribute to
the research on potential biological effects of genetically
modified products (Valdés et al,. 2013). An increasing
number of metabolomics and proteomics techniques based
on mass spectrometry are utilized in the analysis of
genetically modified foods (Agrawal et al,. 2013, Garcia-
Canas et al,. 2011, Valdés and García‐Cañas 2013).
Cifuentes et al. (Simo et al,. 2010) applied the CE-TOF-
MS technique to the analysis of more than 150 proteolytic
peptides for both transgenic soybeans and traditional
soybeans, but no significant difference was found. This
study sheds light on new assessment methods for the
safety of genetically modified food on the proteomics
level.
2.2. Research on the Relationship between
Food Nutrition and Human Health
Human physical health is determined by both genes and
the environment, and food intake is the most crucial
external factor for human health. After being consumed,
food alters human body gene expressions as well as the
protein and metabolite composition levels, and different
food ingredients would lead to different alterations. Due to

611 Journal of Food and Nutrition Research
genetic differences of each individual, human reacts with
food ingredients differently. In this situation, the
application of foodomics techniques is very important to
the analysis of the impacts of food compositions on
genomes, transcriptomes, proteomes, and metabolomes.
This is because researches on food and nutritional
mechanisms at the molecular level to define the
correlation of the genes and diets with health will
elucidate the optimization of the design on dietary
compositions and regulation of human physiological state
as well as the development of health-enhancing functional
food and disease prevention (Corella et al,. 2011). As a
result, nutritional values of food to human health will
become a research focus of food science following food
quality and safety.
Food compositions and their impacts on
physiological health. Food influences human health as a
major source of human nutrition, and therefore researches
on various food compositions and their influence on
physiological health have significant effects on the
prevention of diseases by means of optimized daily diet,
especially identification of risky and hazardous factors in
food and functional components favorable to disease
prevention and treatment. These researches mainly focus
on the functional mechanism of active components in food
on human health at the levels of proteomes, genomes, and
metabolomes (Corella et al,. 2011, Wittwer et al,. 2011).
For example, during the course of aging, accumulation of
in vivo oxidative stresses will cause diseases such as
diabetes, atherosclerosis, neurodegenerative diseases, and
other inflammation diseases because in vivo oxidative
stresses trigger post-translational modifications in proteins,
mostly carbonyl modifications. Research results in recent
years demonstrated that antioxidative components in daily
diet could distinctly reduce protein oxidation in human
bodies, thus ameliorating the state of oxidative stress.
Antioxidants differ in their abilities to ameliorate
oxidation of different proteins at different binding sites,
and therefore quantitative assessment of the amelioration
effects of various antioxidants on different protein
oxidation at the protein level will help improve the diet
pattern for disease prevention and deferment of
senescence (Madian et al,. 2013). Valdes et al. applied
transcriptomics and metabolomics strategies to the study
of the anti-proliferative effects of dietary polyphenols
extracted from rosemary on two human leukemia lines,
with one being drug-sensitive (K562) and the other being
drug-resistant (K562/R) (Valdes et al,. 2012). Microarray
techniques were used for transcriptomics analysis and
MS-based non-targeted analytical approaches (CE-TOF
MS and UPLC-TOF MS) were used for metabolomics
analysis. With the combined studies of transcriptomics
and metabolomics, it was found that rosemary extracts had
different functional mechanisms on the two phenotypes of
leukemia lines. In addition, ingenuity pathway analysis
(IPA) was used as a bioinformatic tool to study the gene
changes to find out the genes that lead to different
metabolic pathways of two human leukemia lines,
providing the inhibitory mechanism of leukemia cell
proliferation from rosemary extracts. Then, Valdes et al.
first researched the bioactivity of rosemary extracts
against colon cancer cells at the molecular level via the
foodomics methodology based on the combined analytical
platforms of transcriptomics, proteomics, and
metabolomics studies (Ibanez et al,. 2012). This allows
determination of changed genes, proteins, and metabolites
that are correlated with antioxidation, pro-apoptosis, and
cell proliferation inhibition, which provides new insights
on the establishment of the biological mechanisms of
rosemary extracts with biological data. Red microalgae
contain a variety of functional constituents such as
sulfated polysaccharides, polyunsaturated fatty acids,
zeaxanthin, vitamins, minerals, and proteins. After red
microalgae products were fed to mice, it was found that
the products significantly improved the total serum
cholesterol, serum triglycerides, hepatic cholesterol levels,
and HDL/LDL ratios, and increased excretion of neutral
sterols and bile acids. These findings support the possible
usage of red microalgae as novel nutraceuticals (Dvir et
al,. 2009). In the meantime, based on the relationships
between food components and diseases, the proteomics
technology can be used to characterize and screen food
allergens so as to prevent health hazards (Picariello et al,.
2013).
Research on individual nutrigenetics. Many diseases
and unhealthy status, such as obesity, diabetes, mellitus
and cardiovascular diseases, and cancers, are closely
related to human diet. Moreover, these diseases and
human's susceptibility to these diseases are correlated with
a variety of gene mutations. With the completion of the
human genome project and subsequent sequencing, the
relationship between genetic heterogeneity and human
health is gaining attention. Responses to such individual
genotype differences by adjusting people's diet to
safeguard human health will be a research focus of future
food science (Williams et al,. 2008). For example, the
polymorphism of apolipoprotein A-II (APOA2) promoter
subregion (-265T > C) is associated with lipid metabolism
and obesity. Individuals with the CC gene type are likely
to be more obese than those with the TT or TC gene type.
The total fat and protein intake is statistically higher in CC
gene type individuals than in TT or TC gene type
individuals. Therefore, regulating dietary intake of these
people will help reduce obesity (Corella et al,. 2007).
Valdes et al. utilized transcriptomics techniques to study
the effects of rosemary extracts on the transcriptional gene
changes of human colon cancer cells SW480 and HT29
and found only 18% of the differentially expressed genes
were common in both cell lines, indicating that the two
lines of human colon cancer cells (SW480 and HT29)
caused by different gene mutation had different reactions
with the same active component (Valdes et al,. 2013).
Based on this, the authors utilized two bioinformatics
tools (i.e. Ingenuity Pathway Analysis and Gene Set
Enrichment Analysis) to carry out functional analysis on
the mutated genes to deduce the possible signaling
pathway of inhibition of cell cycles and apoptosis caused
by rosemary polyphenols.
3. Development on Foodomics
Technologies
It is not difficult to conclude from the previously
mentioned concept of foodomics that the analysis
techniques of foodomics are common omics techniques
used in the systems biology, such as genomics,
transcriptomics, proteomics, and metabolomics. Each

Journal of Food and Nutrition Research 612
technique produces huge amount of data, and as a result,
bioinformatics and chemometrics developed along with
the omics are becoming indispensable tools of foodomics
research.
3.1. Genomics Techniques
Food nutrition and human genes are highly correlated
as human bodies are exposed to food every day. In this
case, human health is a result of interaction between genes
and exposure to environments including food. Therefore,
the association of food nutrition with health is difficult to
investigate without genomics researches. Researches on
the relationships among genes, diet, and health are based
on the researches of the functional mechanism of food
nutrition at the molecular level. Genomics studies in
foodomics can be conducted in two aspects (Capozzi and
Bordoni 2013). On one hand, genomics studies have
shown that human diseases and human's susceptibility to
certain diseases are related to various gene mutations.
Human's susceptibility to certain diseases can be adjusted
by proper diet regulations. Therefore, investigating
different responses of structural or functional genomes to
food and analyzing the relationships between nutrient
components and health and diseases could greatly
accelerate individual nutrigenomic study and appropriate
alterations of the diet plan for certain people (Wittwer et
al,. 2011). On the other hand, applications of genomics
techniques to the promotion of agricultural product quality,
especially nutritional components of bulk agricultural
products, may provide a solution to malnutrition and some
other diseases (Pérez-Massot et al,. 2013). Genomics
technologies can be categorized into microarray and
genome sequencing techniques. The former mainly
determines and assesses the differences of genomes in
each individual using various gene chips (e.g., sequencing
chips, single nucleotide polymorphism chip, methylation
chip, copy-number chip, and molecular cytogenetic chip)
designed with known genomic information; the latter is
the main next-generation sequencing technology (e.g., De
nove genome sequencing, resequencing, and RNA
sequencing) that is still being studied today (Cerda and
Manchado 2013).
3.2. Transcriptomics Techniques
The transcriptomics technology covers the whole set of
gene expressions in a sample, usually the full expression
of mRNAs. The adjustment functionality of non-coding
RNAs in gene expression is drawing growing attention
today, and miRNAs, LncRNAs, and other RNAs are also
the major targets of the transcriptomic research. The
research on the mRNA expression levels reflects the
impact of food on gene expression regulation, because
gene expression regulation has a significant relationship
with human health status. Therefore, the transcriptomics
technology can be applied in the research on the role of
active food components in the maintenance of
physiological equilibrium and disease prevention (Bordoni
et al,. 2007). Similar to the genomics technology, the
transcriptomics technology also includes two types of
techniques: microarray and sequencing. Currently, many
companies such as Agilent, Illumina, and Affymetrix have
developed mRNA and miRNA gene expression chips of
various species including humans'. Companies in China
such as CapitalBio (Beijing) have also developed a variety
of mRNA expression profiling chips and have integrated
the LiRNA detection probe into the chips, which can be
utilized in expression profile measurement of mRNAs and
LncRNAs of various species. With the development of the
sequencing technology and reduction of its price,
sequencing assessment of all the mRNA, miRNA, and
LncRNA expressions in human bodies (in vivo) with the
transcriptomics technology becomes possible for those
species without expression profiling chips.
3.3. Proteomics Techniques
Proteomic technologies are applied to the analysis of
the total protein compositional data in a sample. Protein
compositions in food are closely related to food quality
issues such as food safety, origin, category, and
processing. Even food with extreme genetic homogeneity
may have different functions and components. Neither
genomics nor transcriptomics can truly reflect protein
compositions and variations in food because of the post-
translational modification process of proteins. Therefore,
food analysis at the proteomic level has significant
importance in enhancing food quality and safety
(D'Alessandro and Zolla 2012, Agrawal et al,. 2013,
Boschetti and Righetti 2012). Meanwhile, analysis on
proteomic changes of human cells or tissues after food is
taken into human bodies will help study the mechanism of
food nutrition and its relationship with health. It will also
address such challenges as to determine active substances
in food for prevention of cancers and other diseases
(Shukla and George 2011). A variety of proteins exist in
biological samples with a magnitude of concentration
differentiation, and many trace proteins provide important
functions for the samples with the concentration levels
below the detection sensitivity. Therefore, various protein
isolation and identification technologies are needed and
the isolation and separation of a large quantity of protein
samples is the basis of proteomics research. The
traditional two-dimensional polyacrylamide gel
electrophoresis (2-DE) method is extremely time-
consuming and tedious, and it has a lot of constraints in
isolation of tremendously-high molecular weight proteins,
particularly-low molecular weight proteins, extremely
alkaline proteins, and hydrophobic protein. In order to
reduce the complexity of samples, protein isolation is
applied in proteomics research using multi-dimensional
liquid chromatography, which gradually becomes a major
technology. Mass spectrometry including various TOF-
MS techniques is currently a major method for protein
identification after protein isolation. Generally, two
proteomics analysis strategies are used before mass
spectrometry. One is the "Bottom-up" strategy, by which
the "Shotgun" approach first performs protein
enzymolysis and then uses chromatography to isolate and
purify the resulting peptides for subsequent mass
spectrometry. The other is the "Top-down" strategy,
where the protein samples first go through
chromatography and then enzymolysis to generate
peptides, and finally mass spectrometry is carried out on
the peptides. The former method is easily automated and
suitable for a large quantity of protein identification; the
latter is suitable for analysis of a post-translational
modification site. The protein chip technology developed

613 Journal of Food and Nutrition Research
based on microarray has also been applied in proteomics
analysis. The recently developed lab-on-a-chip system (or
Micro Total Analysis System) assembles all the protein
extraction, separation, and identification processes on one
microfluidic chip. In this way, the efficiency of the
proteomics analysis is greatly increased by reduced
sample consumption, analysis time, and cost (Nazzaro et
al,. 2012).
3.4. Metabolomics Techniques
Metabolomics studies all endogenous or exogenous
small molecule metabolites with a molecular weight less
than 1000 D in a biological system and explores their
metabolic pathways. The metabolome represents the final
phenotype of a genome and is the terminal of various
reaction processes in the biological systems. Studies of
metabolic phenotypes and metabolic mechanisms help us
to differentiate different metabolite pathways of food
components in human bodies and to view their metabolic
composition changes. We can also use metabolomics to
analyze different impacts on physiological functions of
various metabolites. After analyzing the physiological
health state, we could find metabolic markers related to
health status and food nutrition so as to evaluate the
nutritional functionality of food (Villaño et al,. 2013).
Besides the study of food-induced metabolic changes in
human bodies, metabolomic studies also include the study
on the compositions of large-scale small molecule
metabolites in food, analysis and assessment of active
functional components or hazardous ingredients of food,
which could help discriminate food quality and identify
food sources by fingerprint chromatography of food
metabolites. Huge quantities of small-molecular
substances exist in food and human bodies, which possess
different physicochemical attributes and have different
concentrations, bringing challenges to metabolomic
analysis techniques. Currently, metabolomics techniques
are mainly classified into mass spectrometry (MS) and
nuclear magnetic resonance (NMR) techniques (Hu and
Xu 2013). These two techniques are separately used in
combination with sample separation techniques such as
liquid chromatography (LC), gas chromatography (GC),
and capillary electrophoresis (CE) (Scherer et al,. 2013).
According to the study purpose, these researches can be
divided into metabolic target analysis for one or several
kinds of specific biomarkers, metabolomic profiling for a
group of metabolites with the same metabolic pathway or
other characteristics, and metabolic fingerprinting for
different metabolic phenotypes in response to different
cellular environments. Inoue et al. applied UPLC-FL-ESI-
TOF/MS in combination with fluorescence derivatization
to establish a platform for identifying active compounds
with unknown functionalities in food (Inoue et al,. 2013).
CE is a foodomics technique commonly applied in the
analysis of food components, which is often used with MS
for the analysis of amino acids, bio-amines, proteins,
peptides, nucleic acids, carbohydrates, phenols, pigments,
toxins, pesticides, vitamins, additives, and organic and
non-organic ions in food as well as food processing
procedures. CE is utilized in the surveillance of food
quality, safety, nutritional values, and processing and
transportation procedures (Ibáñez et al,. 2013). Review
articles are published each year on "electrophoresis" to
introduce this method and its application (Herrero et al,.
2010, García‐Cañas et al,. 2014, Castro-Puyana et al,.
2012). Çelebier et al. described the detailed procedure of
CE on the research of the changes of metabolites under the
effect of rosemary extracts on colonic cancer cells HT29
using the CE-MS technique (Celebier et al,. 2012). A
research conducted by Vazquez-Fresno et al.
demonstrated that hydrogen nuclear magnetic resonance
spectroscopy could be utilized in obtaining grape wine
metabolite profiles in human urine and in detecting
endogenous physiological markers after grape wine
drinking (Vazquez-Fresno et al,. 2012).
3.5. Other Omics Techniques
The significance of foodomics lies in that it provides
omics-based research ideas. To enhance the pertinence of
studies, facilitate data analysis, and clarify the
mechanisms, different researches on various levels of
omics can be carried out for different foods and research
objects. To study the mechanism of food components
influencing human health, more special omics, such as
epigenome, non-coding RNAomics, and post-translated
modification proteome and enzymome, recently emerged
and were applied as foodomics techniques (Gaso-Sokac et
al,. 2010). For example, the epigenome technology mainly
focuses on non-sequence changes of DNAs (which
majorly includes DNA-methylation, histone modification,
and non-coding RNAs including small RNAs). In
mammals, many food components such as folic acid,
vitamin B6, vitamin B12, betaine, methionine, and choline
are found in relation with DNA-methylation. By analyzing
epigenome alterations induced by food components,
researches on food nutrients and their relationships with
disease prevention can be carried out (Cifuentes 2013).
Epigenomics analysis techniques majorly comprise
chromatin immuno-precipitation DNA sequencing. In
quality control and safety analysis of food, more precise
subdivisions of omics, such as peptidome, lipidome
(Wang and Zhang 2011), glycome, polyphenols
(Delcambre and Saucier 2013, Picariello et al,. 2012), and
enzymome (Josic and Giacometti 2013), appear to aim at
different components and ingredients in food. After the
special components that represent the specific
physiological state of food are analyzed, the storage and
processing (freezing and thawing) of food can be properly
monitored.
3.6. Chemometrics and Bioinformatics
A variety of foods and their composition complexity
impose high requirements on food analysis or
experimental design. In addition, the application of
modern foodomics techniques definitely generates a large
amount of complex experimental data. Therefore, one of
the challenges in foodomics is to appropriately design
experiments, analyze measurement data, and obtain useful
information from the data (Erazo et al,. 2013).
Chemometrics and bioinformatics are two important tools
for data analysis in foodomics. Developed on the basis of
chemistry, chemometrics incorporates the theories and
methods of mathematics, statistics, computer science, and
other related studies into chemical analysis, optimizes
experimental design, and acquires complicated
relationships between chemical compounds, structures,

Journal of Food and Nutrition Research 614
and performance to the greatest extent using measurement
data based on analytical chemistry (Skov and Engelsen
2013). Currently, the common chemometric methods used
in food analysis include principal component analysis
(PCA), discriminant analysis (DA), clustering analysis
(CA), partial least square regression (PLS), multiple linear
regression (MLR), artificial neural network (ANN), soft
independent modeling of class analogy (SIMCA), and
wavelet transform. When combined with techniques such
as infrared spectroscopy (IR) and GC-MS, these
chemometric techniques can be applied to food nutrient
analysis and nutrient monitoring during food production
and processing (Ammor et al,. 2009, Xie et al,. 2009,
Jalali-Heravi et al,. 2006). For example, Mohammed et al.
proposed a method for rapid monitoring of the spoilage of
minced beef using Fourier transform infrared spectroscopy
in tandem with chemometrics (Ammor et al,. 2009). Food
nutrient analysis techniques combining chemometrics with
GC-MS can also be utilized to detect adulterants in edible
oils and foods (Zhu et al,. 2010, Vlachos et al,. 2006).
Unlike chemometrics, bioinformatics is used to explore
the correlations between food nutrition and health. By
processing mass data of genes, proteins, and metabolites
measured by foodomics, bioinformatics is used to
discover the relationships between specific data and
human physical health. Currently, most of the researches
on the mechanism of food compositions in human bodies
using the techniques of transcriptomics, proteomics, and
metabolomics have large amount of descriptive data
(Wittwer et al,. 2011). Since little has been known about
the functions of most genes, proteins, and metabolites, in
order to explain and elaborate these data, bioinformatics
provides a tool for possible molecular signal transfer in a
wide range from food compositions to impacts on health.
A variety of bioinformatic tools have been developed and
used for functional annotation and clustering of genes and
proteins generated via omics techniques. Using statistics,
the potential biomarkers of food nutrition and health can
be discriminated; with the knowledge of signaling
pathways, potent nutritional molecular mechanisms can be
evaluated. For instance, Valdes et al. used two
bioinformatics tools Ingenuity Pathway Analysis and
Gene Set Enrichment Analysis to analyze the data of
transcriptomics, proteomics, and metabolomics after
rosemary extracts were applied to cancer cells and
analyzed the mechanisms of rosemary by giving possible
signaling pathways (Ibanez et al,. 2012, Valdes et al,.
2012, Valdes et al,. 2013). In the RAFA conference in
2013, Lieven van Meulebroek et al. from Ghent
University in Belgium reported the research results on the
regulation of plant hormones generated by the carrotene
metabolism in tomatoes based on foodomics. The results
were obtained by using UPLC-Orbitrap and related
bioinformatics tools Sievetm (fingerprinting analysis) and
Simcatm (data processing). The development of
bioinformatics facilitates data analysis and explanation,
and in return the bioinformatics is developed based on
data analysis. In this regard, after data analysis is complete
and some explanations are given using bioinformatics, the
results need to be verified with traditional chemical or
biological experiments.
4. Conclusions
The systems biology and its development in the fields
of life science, medical science, and pharmacology
provide boundless opportunities and challenges for food
nutrition and health studies. These subjects are associated
with food science and gradually become key directions for
future research on food science. Cardiovascular diseases,
diabetes, and cancers, which are developed by the joint
action of the living environment and genes, are becoming
major threats to human health in a modern society. Food,
as the external environmental stimulus that is correlated
with people in their lifetime, is closely related to the
occurrence and development of these diseases. Therefore,
based on the traditional concepts of sufficient feeding and
good feeding conditions, food science has been further
developed into a new era when people have higher
requirements on food science, including food nutrition and
health research at the systems biology level and based on
personalized diet for maintenance of good health. In this
manner, pains brought by body diseases can be mitigated,
a large sum of medical costs can be saved, and the
happiness status brought by foodomics can be achieved. In
addition, researches on foodomics require cooperation of
people working in different fields such as food science,
analytical chemistry, clinical science, pharmacology, and
life science. Subsequently, foodomics will greatly
accelerate our researches on food safety, traceability,
quality, new foods, transgenic foods, functional foods, and
nutraceuticals.
References
[1] Agrawal, G. K., Sarkar, A., Righetti, P. G., Pedreschi, R.,
Carpentier, S., Wang, T., Barkla, B. J., Kohli, A., Ndimba, B. K.,
Bykova, N. V., Rampitsch, C., Zolla, L., Rafudeen, M. S., Cramer,
R., Bindschedler, L. V., Tsakirpaloglou, N., Ndimba, R. J., Farrant,
J. M., Renaut, J., Job, D., Kikuchi, S. & Rakwal, R. (2013). A
decade of plant proteomics and mass spectrometry: translation of
technical advancements to food security and safety issues. Mass
Spectrom Rev, 32, 335-65.
[2] Ammor, M. S., Argyri, A. & Nychas, G. J. E. (2009). Rapid
monitoring of the spoilage of minced beef stored under
conventionally and active packaging conditions using Fourier
transform infrared spectroscopy in tandem with chemometrics.
Meat Science, 81, 507-514.
[3] Bordoni, A., Astolfi, A., Morandi, L., Pession, A., Danesi, F., Di
Nunzio, M., Franzoni, M. & Biagi, P. (2007). N-3 PUFAs
modulate global gene expression profile in cultured rat
cardiomyocytes. Implications in cardiac hypertrophy and heart
failure. FEBS Lett, 581, 923-9.
[4] Boschetti, E. & Righetti, P. G. (2012). Breakfast at Tiffany's?
Only with a low-abundance proteomic signature! Electrophoresis,
33, 2228-39.
[5] Capozzi, F. & Bordoni, A. (2013). Foodomics: a new
comprehensive approach to food and nutrition. Genes Nutr, 8, 1-4.
[6] Castro-Puyana, M., Garcia-Canas, V., Simo, C. & Cifuentes, A.
(2012). Recent advances in the application of capillary
electromigration methods for food analysis and Foodomics.
Electrophoresis, 33, 147-67.
[7] Castro‐Puyana, M., Mendiola, J. A., Ibáñez, E. & Herrero, M.
(2013). MS-based Metabolomics Approaches for Food Safety,
Quality, and Traceability. In: Foodomics: Advanced Mass
Spectrometry in Modern Food Science and Nutrition (edited by
CIFUENTES, A.). Pp. 453-470. New Jersey: John Wiley & Sons.
[8] Celebier, M., Ibanez, C., Simo, C. & Cifuentes, A. (2012). A
Foodomics approach: CE-MS for comparative metabolomics of
colon cancer cells treated with dietary polyphenols. Methods Mol
Biol, 869, 185-95.
[9] Cerda, J. & Manchado, M. (2013). Advances in genomics for
flatfish aquaculture. Genes Nutr, 8, 5-17.

615 Journal of Food and Nutrition Research
[10] Cifuentes, A. (2009). Food analysis and foodomics. J Chromatogr
A, 1216, 7109.
[11] Cifuentes, A. (2012). Food Analysis in the Postgenomic Era:
Foodomics. Electrophoresis, 33, 2199-2199.
[12] Cifuentes, A. (2013). Foodomics: Principles and Applications. In:
Foodomics: Advanced Mass Spectrometry in Modern Food
Science and Nutrition (edited by CIFUENTES, A.). Pp. 1-13. New
Jersey: John Wiley & Sons.
[13] Corella, D., Arnett, D. K., Tsai, M. Y., Kabagambe, E. K.,
Peacock, J. M., Hixson, J. E., Straka, R. J., Province, M., Lai, C.
Q., Parnell, L. D., Borecki, I. & Ordovas, J. M. (2007). The -
256T>C polymorphism in the apolipoprotein A-II gene promoter
is associated with body mass index and food intake in the genetics
of lipid lowering drugs and diet network study. Clin Chem, 53,
1144-52.
[14] Corella, D., Arnett, D. K., Tucker, K. L., Kabagambe, E. K., Tsai,
M., Parnell, L. D., Lai, C. Q., Lee, Y. C., Warodomwichit, D.,
Hopkins, P. N. & Ordovas, J. M. (2011). A high intake of
saturated fatty acids strengthens the association between the fat
mass and obesity-associated gene and BMI. J Nutr, 141, 2219-25.
[15] Cozzolino, R., Passalacqua, S., Salemi, S. & Garozzo, D. (2002).
Identification of adulteration in water buffalo mozzarella and in
ewe cheese by using whey proteins as biomarkers and matrix-
assisted laser desorption/ionization mass spectrometry. Journal of
Mass Spectrometry, 37, 985-991.
[16] D'Alessandro, A. & Zolla, L. (2012). We are what we eat: food
safety and proteomics. J Proteome Res, 11, 26-36.
[17] D’Alessandro, A. & Zolla, L. (2013). Foodomics to investigate
meat tenderness. TrAC Trends in Analytical Chemistry, 52, 47-53.
[18] Delcambre, A. & Saucier, C. (2013). High-Throughput OEnomics:
Shotgun Polyphenomics of Wines. Anal Chem, 85, 9736-9741.
[19] Dvir, I., Stark, A. H., Chayoth, R., Madar, Z. & Arad, S. M.
(2009). Hypocholesterolemic effects of nutraceuticals produced
from the red microalga Porphyridium sp in rats. Nutrients, 1, 156-
67.
[20] Erazo, M. A., García, A., Rupérez, F. J. & Barbas, C. (2013).
Metabolomics of Diet-related Diseases. In: Foodomics: Advanced
Mass Spectrometry in Modern Food Science and Nutrition (edited
by CIFUENTES, A.). Pp. 429-451. New Jersey: John Wiley &
Sons.
[21] FoodOmics, I. C. o. (2009). International Conference on
FoodOmics, 28th and 29th May, 2009, Cesena, Italy: abstract
book. Marche Polytechnic University.
[22] Fu, Y. S., Shi, Z. Y., Wu, M. L., Zhang, J. L., Jia, L. & Chen, X.
W. (2011). Identification and Differential Expression of
MicroRNAs during Metamorphosis of the Japanese Flounder
(Paralichthys olivaceus). Plos One, 6.
[23] García-Cañas, V., Simó, C., Castro‐Puyana, M. & Cifuentes, A.
(2014). Recent advances in the application of capillary
electromigration methods for food analysis and Foodomics.
Electrophoresis, 35, 147-169.
[24] Garcia-Canas, V., Simo, C., Leon, C., Ibanez, E. & Cifuentes, A.
(2011). MS-based analytical methodologies to characterize
genetically modified crops. Mass Spectrom Rev, 30, 396-416.
[25] Gaso-Sokac, D., Kovac, S. & Josic, D. (2010). Application of
Proteomics in Food Technology and Food Biotechnology: Process
Development, Quality Control and Product Safety. Food
Technology and Biotechnology, 48, 284-295.
[26] Gaso-Sokac, D., Kovac, S. & Josic, D. (2011). Use of Proteomic
Methodology in Optimization of Processing and Quality Control
of Food of Animal Origin. Food Technology and Biotechnology,
49, 397-412.
[27] Hannon, J. A., Kilcawley, K. N., Wilkinson, M. G., Delahunty, C.
M. & Beresford, T. P. (2007). Flavour precursor development in
Cheddar cheese due to lactococcal starters and the presence and
lysis of Lactobacillus helveticus. International Dairy Journal, 17,
316-327.
[28] Herrero, M., Garcia-Canas, V., Simo, C. & Cifuentes, A. (2010).
Recent advances in the application of capillary electromigration
methods for food analysis and Foodomics. Electrophoresis, 31,
205-28.
[29] Herrero, M., Simo, C., Garcia-Canas, V., Ibanez, E. & Cifuentes,
A. (2012). Foodomics: MS-based strategies in modern food
science and nutrition. Mass Spectrom Rev, 31, 49-69.
[30] Hu, C. & Xu, G. (2013). Mass-spectrometry-based metabolomics
analysis for foodomics. TrAC Trends in Analytical Chemistry, 52,
36-46.
[31] Ibáñez, C., Simó, C., García-Cañas, V., Cifuentes, A. & Castro-
Puyana, M. (2013). Metabolomics, peptidomics and proteomics
applications of capillary electrophoresis-mass spectrometry in
Foodomics: A review. Analytica Chimica Acta, 802, 1-13.
[32] Ibanez, C., Valdes, A., Garcia-Canas, V., Simo, C., Celebier, M.,
Rocamora-Reverte, L., Gomez-Martinez, A., Herrero, M., Castro-
Puyana, M., Segura-Carretero, A., Ibanez, E., Ferragut, J. A. &
Cifuentes, A. (2012). Global Foodomics strategy to investigate the
health benefits of dietary constituents. J Chromatogr A, 1248,
139-53.
[33] Inoue, K., Nishimura, M., Tsutsui, H., Min, J. Z., Todoroki, K.,
Kauffmann, J. M. & Toyo'oka, T. (2013). Foodomics platform for
the assay of thiols in wines with fluorescence derivatization and
ultra performance liquid chromatography mass spectrometry using
multivariate statistical analysis. J Agric Food Chem, 61, 1228-34.
[34] Jalali-Heravi, M., Zekavat, B. & Sereshti, H. (2006).
Characterization of essential oil components of Iranian geranium
oil using gas chromatography-mass spectrometry combined with
chemometric resolution techniques. Journal of Chromatography A,
1114, 154-163.
[35] Josic, D. & Giacometti, J. (2013). Foodomics-Use of Integrated
Omics in Nutrition. Food Technology and Biotechnology. J Data
Mining Genomics Proteomics, 4, e106.
[36] Leitner, A., Castro-Rubio, F., Marina, M. L. & Lindner, W. (2006).
Identification of marker proteins for the adulteration of meat
products with soybean proteins by multidimensional liquid
chromatography - Tandem mass spectrometry. J Proteome Res, 5,
2424-2430.
[37] Madian, A. G., Janle, E. M. & Regnier, F. E. (2013). Examination
of the Efficacy of Antioxidant Food Supplements Using Advanced
Proteomics Methods. In: Foodomics: Advanced Mass
Spectrometry in Modern Food Science and Nutrition (edited by
CIFUENTES, A.). Pp. 101-123. New Jersey: John Wiley & Sons.
[38] Murray, H. M., Lall, S. P., Rajaselvam, R., Boutilier, L. A.,
Blanchard, B., Flight, R. M., Colombo, S., Mohindra, V. &
Douglas, S. E. (2010). A nutrigenomic analysis of intestinal
response to partial soybean meal replacement in diets for juvenile
Atlantic halibut, Hippoglossus hipploglossus, L. Aquaculture, 298,
282-293.
[39] N, S. & I, W. (2007). Horizon Seminar, Foodomics? Why we eat,
what we eat, and what's next on the menu took place on Tuesday,
19 June, 2007. http://www.ceb.cam.ac.uk/pages/foodomics.html.
[40] Nazzaro, F., Orlando, P., Fratianni, F., Di Luccia, A. & Coppola,
R. (2012). Protein analysis-on-chip systems in foodomics.
Nutrients, 4, 1475-89.
[41] Ortea, I., Pascoal, A., Canas, B., Gallardo, J. M., Barros-
Velazquez, J. & Calo-Mata, P. (2012). Food authentication of
commercially-relevant shrimp and prawn species: from classical
methods to Foodomics. Electrophoresis, 33, 2201-11.
[42] Pérez-Massot, E., Banakar, R., Gómez-Galera, S., Zorrilla-López,
U., Sanahuja, G., Arjó, G., Miralpeix, B., Vamvaka, E., Farré, G.,
Rivera, S., Dashevskaya, S., Berman, J., Sabalza, M., Yuan, D.,
Bai, C., Bassie, L., Twyman, R., Capell, T., Christou, P. & Zhu, C.
(2013). The contribution of transgenic plants to better health
through improved nutrition: opportunities and constraints. Genes
Nutr, 8, 29-41.
[43] Picariello, G., Mamone, G., Addeo, F. & Ferranti, P. (2012).
Novel Mass Spectrometry-Based Applications of
the'Omic'Sciences in Food Technology and Biotechnology. Food
Technology and Biotechnology, 50, 286-305.
[44] Picariello, G., Mamone, G., Addeo, F., Nitride, C. & Ferranti, P.
(2013). Proteomic-based Techniques for the Characterization of
Food Allergens. In: Foodomics: Advanced Mass Spectrometry in
Modern Food Science and Nutrition (edited by CIFUENTES, A.).
Pp. 69-99. New Jersey: John Wiley & Sons.
[45] Scherer, M., Ross, A., Moco, S., Collino, S., Martin, F. P., Godin,
J. P., Kastenmayer, P. & Rezzi, S. (2013). Shaping the Future of
Personalized Nutrition with Metabolomics. In: Foodomics:
Advanced Mass Spectrometry in Modern Food Science and
Nutrition (edited by CIFUENTES, A.). Pp. 271-301. New Jersey:
John Wiley & Sons.
[46] Shukla, Y. & George, J. (2011). Combinatorial strategies
employing nutraceuticals for cancer development. Ann N Y Acad
Sci, 1229, 162-75.
[47] Simo, C., Dominguez-Vega, E., Marina, M. L., Garcia, M. C.,
Dinelli, G. & Cifuentes, A. (2010). CE-TOF MS analysis of
complex protein hydrolyzates from genetically modified
soybeans--a tool for foodomics. Electrophoresis, 31, 1175-83.

Journal of Food and Nutrition Research 616
[48] Skov, T. & Engelsen, S. B. (2013). Chemometrics, Mass
Spectrometry, and Foodomics. In: Foodomics: Advanced Mass
Spectrometry in Modern Food Science and Nutrition (edited by
CIFUENTES, A.). Pp. 507-538. New Jersey: John Wiley & Sons.
[49] Tengstrand, E., Rosén, J., Hellenäs, K.-E. & Åberg, K. M. (2013).
A concept study on non-targeted screening for chemical
contaminants in food using liquid chromatography–mass
spectrometry in combination with a metabolomics approach.
Analytical and bioanalytical chemistry, 405, 1237-1243.
[50] Valdés, A. & García-Cañas, V. (2013). MS-Based Methodologies
for Transgenic Foods Development and Characterization. In:
Foodomics: Advanced Mass Spectrometry in Modern Food
Science and Nutrition (edited by CIFUENTES, A.). Pp. 191-220.
New Jersey: John Wiley & Sons.
[51] Valdés, A., Simó, C., Ibáñez, C. & García-Cañas, V. (2013).
Foodomics strategies for the analysis of transgenic foods. TrAC
Trends in Analytical Chemistry, 52, 2-15.
[52] Valdes, A., Garcia-Canas, V., Rocamora-Reverte, L., Gomez-
Martinez, A., Ferragut, J. A. & Cifuentes, A. (2013). Effect of
rosemary polyphenols on human colon cancer cells: transcriptomic
profiling and functional enrichment analysis. Genes Nutr, 8, 43-60.
[53] Valdes, A., Simo, C., Ibanez, C., Rocamora-Reverte, L., Ferragut,
J. A., Garcia-Canas, V. & Cifuentes, A. (2012). Effect of dietary
polyphenols on K562 leukemia cells: a Foodomics approach.
Electrophoresis, 33, 2314-27.
[54] Vazquez-Fresno, R., Llorach, R., Alcaro, F., Rodriguez, M. A.,
Vinaixa, M., Chiva-Blanch, G., Estruch, R., Correig, X. &
Andres-Lacueva, C. (2012). (1) H-NMR-based metabolomic
analysis of the effect of moderate wine consumption on subjects
with cardiovascular risk factors. Electrophoresis, 33, 2345-54.
[55] Villaño, D., Medina, S., Ignacio Gil, J., García-Viguera, C.,
Ferreres, F., Tomás-Barberán, F. A. & Gil-Izquierdo, A. (2013).
Ms-based Omics Evaluation of Phenolic Compounds as
Functional Ingredients. In: Foodomics: Advanced Mass
Spectrometry in Modern Food Science and Nutrition (edited by
CIFUENTES, A.). Pp. 415-427. New Jersey: John Wiley & Sons.
[56] Vlachos, N., Skopelitis, Y., Psaroudaki, M., Konstantinidou, V.,
Chatzilazarou, A. & Tegou, E. (2006). Applications of Fourier
transform-infrared spectroscopy to edible oils. Analytica Chimica
Acta, 573, 459-465.
[57] Wang, Y. Y. & Zhang, H. (2011). Tracking Phospholipid Profiling
of Muscle from Ctennopharyngodon idellus during Storage by
Shotgun Lipidomics. J Agric Food Chem, 59, 11635-11642.
[58] Williams, C. M., Ordovas, J. M., Lairon, D., Hesketh, J., Lietz, G.,
Gibney, M. & van Ommen, B. (2008). The challenges for
molecular nutrition research 1: linking genotype to healthy
nutrition. Genes Nutr, 3, 41-9.
[59] Wittwer, J., Rubio-Aliaga, I., Hoeft, B., Bendik, I., Weber, P. &
Daniel, H. (2011). Nutrigenomics in human intervention studies:
current status, lessons learned and future perspectives. Mol Nutr
Food Res, 55, 341-58.
[60] Xie, L. J., Ye, X. Q., Liu, D. H. & Ying, Y. B. (2009).
Quantification of glucose, fructose and sucrose in bayberry juice
by NIR and PLS. Food Chemistry, 114, 1135-1140.
[61] Zhao, Y., Zhang, B., Chen, G., Chen, A. L., Yang, S. M. & Ye, Z.
H. (2014). Recent developments in application of stable isotope
analysis on agro-product authenticity and traceability. Food
Chemistry, 145, 300-305.
[62] Zhu, X. R., Li, S. F., Shan, Y., Zhang, Z. Y., Li, G. Y., Su, D. L.
& Liu, F. (2010). Detection of adulterants such as sweeteners
materials in honey using near-infrared spectroscopy and
chemometrics. Journal of Food Engineering, 101, 92-97.