Advances in agronomy volume 102

ADVANCES IN AGRONOMY
Advisory Board

PAUL M. BERTSCH

RONALD L. PHILLIPS

University of Kentucky

University of Minnesota

KATE M. SCOW

LARRY P. WILDING

University of California,
Davis

Texas A&M University

Emeritus Advisory Board Members

JOHN S. BOYER

KENNETH J. FREY

University of Delaware

Iowa State University

EUGENE J. KAMPRATH

MARTIN ALEXANDER

North Carolina State
University

Cornell University

Prepared in cooperation with the
American Society of Agronomy, Crop Science Society of America, and Soil
Science Society of America Book and Multimedia Publishing Committee
DAVID D. BALTENSPERGER, CHAIR
LISA K. AL-AMOODI

CRAIG A. ROBERTS

WARREN A. DICK

MARY C. SAVIN

HARI B. KRISHNAN

APRIL L. ULERY

SALLY D. LOGSDON


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CONTRIBUTORS

Numbers in Parentheses indicate the pages on which the authors’ contributions begin

Muhammad Arshad (159)
Institute of Soil and Environmental Sciences, University of Agriculture, Faisalabad,
Pakistan
Marco van den Berg (135)
International Rice Research Institute (IRRI), Metro Manila, Philippines
Richard M. Bruskiewich (135)
International Rice Research Institute (IRRI), Metro Manila, Philippines
H. Cantarella (267)
Instituto Agronoˆmico, Campinas, SP, Brazil
S. H. Chien$ (267)
Formerly with International Fertilizer Development Center (IFDC), Muscle
Shoals, Alabama, USA
Jørgen Eriksen (55)
Department of Agroecology and Environment, Faculty of Agricultural Sciences,
Aarhus University, Tjele, Denmark
Ya-Jun Gao (223)
College of Resources and Environmental Sciences, Northwest Science and
Technology University of Agriculture and Forestry, Yangling, Shaanxi, People’s
Republic of China
Yong Gu (201)
USDA-ARS, Western Regional Research Center, Albany, California, USA
S. Heuer (91)
International Rice Research Institute (IRRI), Metro Manila, Philippines
Khwaja Hossain (201)
Division of Science and Mathematics, Mayville State University, Mayville, North
Dakota, USA
G. Howell (91)
International Rice Research Institute (IRRI), Metro Manila, Philippines

$

Present address: 1905 Beechwood Circle, Florence, Alabama, USA

ix


x

Contributors

Sarfraz Hussain (159)
Institute of Soil and Environmental Sciences, University of Agriculture, Faisalabad,
Pakistan
A. Ismail (91)
International Rice Research Institute (IRRI), Metro Manila, Philippines
S. V. K. Jagadish (91)
International Rice Research Institute (IRRI), Metro Manila, Philippines
Venu Kalavacharla (201)
Department of Agriculture and Natural Resources, Delaware State University,
Dover, Delaware, USA
Azeem Khalid (159)
Department of Environmental Sciences, PMAS Arid Agriculture University,
Rawalpindi, Pakistan
Shahryar F. Kianian (201)
Department of Plant Sciences, North Dakota State University, Fargo, North
Dakota, USA
Shi-Qing Li (223)
College of Resources and Environmental Sciences, Northwest Science and
Technology University of Agriculture and Forestry, Yangling, Shaanxi, People’s

Republic of China
Sheng-Xiu Li (223)
College of Resources and Environmental Sciences, Northwest Science and
Technology University of Agriculture and Forestry, Yangling, Shaanxi, People’s
Republic of China
Shivcharan S. Maan (201)
Department of Plant Sciences, North Dakota State University, Fargo, North
Dakota, USA
Noel P. Magor (135)
International Rice Research Institute (IRRI), Metro Manila, Philippines
S. S. Malhi (223)
Agriculture and Agri-Food Canada, Research Farm, Melfort, Saskatchewan, Canada
C. Graham McLaren (135)
International Rice Research Institute (IRRI), Metro Manila, Philippines
Thomas Metz (135)
International Rice Research Institute (IRRI), Metro Manila, Philippines
H. Pathak (91)
International Rice Research Institute (IRRI), New Delhi, India


Contributors

xi

L. I. Prochnow (267)
International Plant Nutrition Institute (IPNI), Piracicaba, SP, Brazil
E. Redona (91)
International Rice Research Institute (IRRI), Metro Manila, Philippines
Oscar Riera-Lizarazu (201)
Department of Crop and Soil Science, Oregon State University, Corvallis,

Oregon, USA
Muhammad Saleem (159)
Department of Environmental Microbiology, UFZ Helmholtz Centre for
Environmental Research, Leipzig, Germany
R. Serraj (91)
International Rice Research Institute (IRRI), Metro Manila, Philippines
David Shires (135)
International Rice Research Institute (IRRI), Metro Manila, Philippines
Tariq Siddique (159)
Department of Renewable Resources, University of Alberta, Edmonton, AB,
Canada
R. K. Singh (91)
International Rice Research Institute (IRRI), Metro Manila, Philippines
K. Sumfleth (91)
International Rice Research Institute (IRRI), Metro Manila, Philippines
Matthew D. Thompson (1)
Cancer Prevention Laboratory, Department of Horticulture and Landscape
Architecture, Colorado State University, Fort Collins, Colorado, USA
Henry J. Thompson (1)
Cancer Prevention Laboratory, Department of Horticulture and Landscape
Architecture, Colorado State University, Fort Collins, Colorado, USA
Xiao-Hong Tian (223)
College of Resources and Environmental Sciences, Northwest Science and
Technology University of Agriculture and Forestry, Yangling, Shaanxi, People’s
Republic of China
Zhao-Hui Wang (223)
College of Resources and Environmental Sciences, Northwest Science and
Technology University of Agriculture and Forestry, Yangling, Shaanxi, People’s
Republic of China
R. Wassmann (91)

Research Center Karlsruhe (IMK-IFU), Karlsruhe, Germany, and International
Rice Research Institute (IRRI), Metro Manila, Philippines


PREFACE

Volume 102 contains eight reviews addressing contemporary topics in the
crop and soil sciences. Chapter 1 is a timely review on biomedical agriculture whose goal is to ‘‘identify specific genotypes of a food crop which,
alone and when combined with other food crops, form a dietary pattern that
reduces chronic disease risks.’’ Chapter 2 deals with sulfur cycling in
temperate agricultural systems. Chapter 3 covers an important topic –
climate change impacts on Asian rice production. Chapter 4 deals with
informatics in agricultural research. Chapter 5 discusses the impact of
pesticides on soil microbial diversity, enzymes, and biochemical reactions.
Chapter 6 is a comprehensive review on radiation hybrid mapping in crop
plants. Chapter 7 is concerned with nutrient and water management effects
on crop production and nutrient and water use efficiency in dryland areas of
China. Chapter 8 is a timely review on developments in fertilizer production and use to enhance nutrient efficiency and minimize environmental
impacts.
I appreciate the excellent contributions of the authors.
DONALD L. SPARKS
Newark, Delaware, USA

xiii


C H A P T E R

O N E

Biomedical Agriculture: A Systematic
Approach to Food Crop Improvement
for Chronic Disease Prevention
Matthew D. Thompson and Henry J. Thompson
Contents
1. Biomedical Agriculture: A Twenty-First-Century Response to an
Emerging Global Problem
2. The Biomedical Landscape
2.1. Terminology
2.2. Chronic disease prevention
3. Agricultural Landscape
3.1. Genotypic diversity in crops
3.2. Chemical basis for CDP
3.3. Assembling a test collection of a crop’s genotypes
3.4. Extending chemical profiling to food crop combinations
3.5. Other considerations
4. Evaluating Crops
4.1. Animal-based approaches
4.2. Nonanimal approaches
4.3. Evaluation of crop genotypes and food combinations in human
participants
5. Biomedical Agriculture in Practice: A Developing Program in Crop
Improvement
5.1. Crops for HealthTM
5.2. The plant food–cancer risk conundrum
5.3. Biomedical agriculture: A transdisciplinary effort
5.4. The vanguard project: Determining the health benefits
of dry beans
6. Building the Infrastructure to Sustain the Effort
6.1. Transdisciplinary conceptualization

6.2. Land grant tradition

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Cancer Prevention Laboratory, Department of Horticulture and Landscape Architecture, Colorado State
University, Fort Collins, Colorado, USA
Advances in Agronomy, Volume 102
ISSN 0065-2113, DOI: 10.1016/S0065-2113(09)01001-3

#

2009 Elsevier Inc.
All rights reserved.

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Matthew D. Thompson and Henry J. Thompson

7. Summary and Future Prospects
Acknowledgments
References

41
44
44

Abstract
Biomedical agriculture (BMA) is a transdisciplinary approach and emerging field
that engages agronomists and biomedical scientists in a program of discovery,
dissemination, and training. The ultimate goal of BMA is to identify specific
genotypes of a food crop which, alone and when combined with other food
crops, form a dietary pattern that reduces chronic disease risk, that is, risk for
cancer, cardiovascular disease, type II diabetes, and obesity. To achieve this
goal, a systematic approach is required that investigates staple and specialty
crop genotypes for bioactivity that translates into improved chronic disease
biomarkers, alterations of which are associated with reduced disease risk. The

primary mechanisms targeted for food-mediated disease risk reduction are
altered glucose metabolism, chronic inflammation, excessive cellular oxidation,
and/or chronic endotoxemia. The crop improvement process via BMA is tiered,
establishing efficacy for chronic disease prevention in molecular, cellular, and
animal investigations of crop genotypes and food combinations before evaluation in cohorts of human participants. Ultimately, specific dietary plans will be
tailored for individuals at risk for one or more chronic diseases. Informatics and
omics technologies enable transdisciplinary collaborations, giving the agricultural and biomedical sciences a common research setting that sustains and
translates progress into the community.

1. Biomedical Agriculture: A TwentyFirst-Century Response to an Emerging
Global Problem
The human experience has been continually redefined through agriculture. The domestication of modern crops enabled the development of
civilizations, and since then, we have continued to reap the benefits of more
modern agricultural revolutions: as examples, Mendelian and molecular
genetics applied to selection and breeding (Dwivedi et al., 2007; Pickersgill,
2007), mechanization and precision agriculture (Glancey et al., 2005), and
genomics (Burke et al., 2007; Varshney et al., 2006). As technology has
advanced, those in agriculture have always leveraged the new tools made
available through scientific enterprise to meet the changing demands of
society. Looking ahead, the agricultural sciences are once again poised to
improve the human experience, in part because of the omics revolution
(Brown and van der Ouderaa, 2007; Kaput, 2004, 2007; Kaput et al., 2005;
Watkins and German, 2002a,b; Watkins et al., 2001). In this chapter,


Biomedical Agriculture

3

approaches are discussed that deal with problems at the interface of agriculture and human health, with emphasis on chronic disease prevention (CDP).

In the past decade, numerous approaches have been suggested to investigate food-based health improvement. Clearly, the magnitude of foodrelated problems is enormous. Malnourishment and essential nutrient deficiency continue to affect more than half of the world’s population (Mayer
et al., 2008), and concomitantly, a surge in chronic disease is being driven by
the obesity epidemic (Must et al., 1999; Rippe et al., 1998; World Health
Organization, 2003). While some agronomists work within their respective
specialties to combat plant pests and environmental constraints on yield with
omics approaches (Keon et al., 2003; Weller et al., 2001), others are applying
similar methods to find solutions to food and nutrition problems, such as in
biofortification (Nestel et al., 2006; Welch, 2005; Welch and Graham,
2005). Through highly integrative research, some have suggested agronomists should work closely with nutritionists and those in the biomedical
community. In 1997, Combs, Duxbury, and Welch wrote:
The paradigms of agricultural institutions, public health departments, and
human nutritionists must be changed from current linear approaches to
integrated and interactive approaches. If effective, food-based solutions to
micronutrient deficiencies and other human health issues are to be forthcoming. [The program] is forging explicit linkages across a wide array of
disciplines and is supporting interdisciplinary research, teaching and extension activities concerned with the development and use of food systems
technologies for improved human nutrition and health. By better linking
agricultural production to nutritional goals and human needs, food systems
that make sustainable improvements in human nutrition and health can be
formed. (Combs et al., 1997)

In the 11 years since this visionary thinking was introduced, progress has
been made in biofortification programs (Gilani and Nasim, 2007; Pfeiffer
and McClafferty, 2007) and the development of the field of nutrigenomics,
where diet–gene–disease interactions are studied (DellaPenna, 1999; Kaput,
2007; vanOmmen, 2004). In these settings, relationships between agriculture and the biomedical sciences have continued to be encouraged (Hawkes
and Ruel, 2006; Kochian and Garvin, 1999; Metzlaff, 2005; Watkins et al.,
2001; Welch and Graham, 2005). Yet beyond efforts to improve micronutrient content of crops, little work has been done to establish a framework
for food-based approaches to prevent chronic diseases such as cancer,
cardiovascular disease, type II diabetes, and obesity. These complex diseases
are not based on a definable nutrient deficiency; therefore, greater difficulties arise in developing strategies for crop improvement to combat their

occurrence and consequences.
Epidemiological evidence from prospective studies conducted in the
United States and Europe are consistent with the idea that dietary patterns
emphasizing plant foods are associated with lower prevalence of chronic


4

Matthew D. Thompson and Henry J. Thompson

diseases (Bamia et al., 2007; Hung et al., 2004; WCRF/AICR, 2007; World
Health Organization, 2003, 2007; Yusuf et al., 2001). However, efforts to
identify the specific foods and/or food components that account for the
reduction in disease risk have been mixed (Hung et al., 2004; McCullough
and Willett, 2006; McCullough et al., 2000; Riboli and Norat, 2003). This
situation underscores the current lack of knowledge about how foods affect
long-term human health. As a consequence, there is a lack of recognition
that food crop genotypes, that is, any genetic variation, whether evolved,
selected, or bred, in any particular food crop, can differ when evaluated for
health benefit. The absence of information about crop genotypes on questionnaires used to collect dietary information in human population studies
clearly illustrates this insufficiency ( Johansson et al., 2002; Willett and Hu,
2007; Willett et al., 1987). Similarly, there is currently no scientific rationale
for how to combine plant foods for maximal ability to reduce chronic
disease risk, although the need for a different approach has been voiced
(Chiuve and Willett, 2007; Thompson et al., 2006). Rather, the predominant focus of established dietary guidelines is on the provision of adequate
levels of essential nutrients (Aggett et al., 1997; Harris, 2000). Despite the
limitations in our knowledge, chronic disease risk and its associated comorbidities and mortality are reduced by plant food-rich dietary patterns
(Craddick et al., 2003; Fung et al., 2008; Hung et al., 2004), and this is
consistent with the hypothesis that specific food crops and genotypes within
each food crop will be identified that uniquely impact human health.

The literature is rich in studies that approach plant improvement from
the single trait perspective (Grusak, 1999; Kinney, 2006). Regrettably
though, populations around the world are experiencing mortality from
chronic diseases that reflect broader issues than mono- or binutrient deficiency syndromes, a situation reflected in a recent meta-analysis that
reported that supplement-based nutrient interventions failed to prevent
chronic disease occurrence and in some cases actually increased mortality
(Bjelakovic et al., 2007). In seeking to define health-promoting traits of
crops, biomedical agriculture (BMA) looks at food as the primary vehicle by
which chemicals are delivered to the human body on a daily basis. The
premise of this approach is that there will be no single ‘‘magic bullet’’
chemical solution for CDP. This is a concept that is often met with
resistance, and so, it is a feature that distinguishes BMA from other
approaches to health promotion and disease prevention that are based on
single agent chemical strategies. Accordingly, for a food-based intervention,
there must be an identifiable pattern of biosynthesis in a crop that is
associated with CDP. Identifying the profile of chemical constituents of
crop and/or food combinations will provide the critical knowledge base
required to understand how crops can be ingested to maintain health,
reduce disease risk, and maximize effectiveness of treatment regimes for
established disease states. BMA aims to shape the health preventive nature of


Biomedical Agriculture

5

the diet by identifying food crop traits that agricultural practice can and
should improve.
BMA was conceptualized in response to a litany of issues that are
encountered by agronomists, biomedical scientists, and health care professionals interested in food-based approaches to disease prevention. Some of

those issues are summarized in Table 1. To clarify, BMA is not the science
of the Green Revolution and its biofortification extension that has as its goal
the eradication of starvation and malnutrition in the global community.
BMA also does not deal with therapeutic uses of foods that seek to complement the standards of medical care, nor does BMA deal with the use of food
as a substitute for pharmaceutical interventions in disease treatment,
although what is learned from BMA will certainly affect these fields. Rather,
BMA targets the plant food component of the human diet, since that
component is least understood relative to its potential to contribute to
health promotion and disease prevention. The primary focus of BMA is
on staple food crops of the world, specifically dry beans, corn, rice, wheat,
and potatoes. This approach capitalizes on the regular daily intake of a
consistent and large amount of food staples by all family members, and in
so doing, addresses a major public health concern about whether the foods
developed are likely to be consumed. Because staple foods predominate in
the diets of the poor, this strategy implicitly targets lower-income households. When this approach is combined with the use of adapted crop
genotypes with both agronomic and cultural food characteristics essential
to profitable and consistent production, and the culinary customs of the
target population, successful dissemination and consumption of foods with
CDP activity can occur.
The overall goal of BMA is to identify specific genotypes of a food crop
that alone and when combined with other food crops, form a dietary pattern
(food combination) that reduces chronic disease risk, that is, risk for cancer,
cardiovascular disease, type II diabetes, and obesity. To achieve this goal, a
systematic approach is required that investigates both staple and specialty
crops (i.e., a wide array of vegetables and fruits) for genotypes with bioactivity against a set of chronic disease biomarkers, the alterations of which are
associated with reduced disease burden. The primary mechanisms common
to these chronic diseases and targeted for food-mediated disease risk reduction are altered glucose metabolism, chronic inflammation, excessive cellular oxidation, and chronic endotoxemia (Fig. 1). The crop improvement
process is tiered, involving molecular, cellular, and animal investigations of
crop genotypes and food combinations, as well as clinical studies.
Ultimately, specific dietary plans will be tailored for individuals at risk for

one or more chronic diseases.
We have been gratified over the last 3 years with the extent to which
agronomists, and particularly plant breeders around the country, have
responded to the content outlined herein, and this chapter is structured to


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Matthew D. Thompson and Henry J. Thompson

Table 1

Issues encountered in biomedical agriculture

Category

Examples

Plant/
agronomy

Defining diversity for a crop
Ability to determine how commercial crop genotypes
relate to the crop’s domestication and extant diversity
Identifying germplasm resources for a crop
Obtaining crop genotype collection with adequate genetic
or chemical diversity
Gene versus environment interactions: relative importance
Plant physiology as a surrogate for bioactivity
Balancing agronomic traits (yield, disease resistance)

Appropriate time to develop a RIL population
Material accessibility, availability
Source of material, crediting donors
Material storage (space, temperature, amount)
Material traceability
Hundreds to thousands of crop genotypes
Crop genotype grouping and selection
Assay selection, translation of effects (e.g., in vitro
antioxidant to in vivo antioxidant)
Cost of the assay versus throughput
Tiered approach: what are the logical steps; what should be
measured
Animal physiology versus cells in culture
Complexity of food versus a single chemical
Drawing conclusions before working with biologically
diverse collections of crop genotypes
Gut microflora assessment and metabolism
Method of preparation of crop as a food
Amount of crop incorporated into diet
Nature of the control group; a reference diet; a reference
genotype
Quality control
Expense
Working with doctors and patients
Practicality and feasibility
Profitability/cost
Identifying exactly what accounts for protection
Public concern over GMO
Moving food to the market
Motivation to collaborate, dealing with negative findings

Funding sources, nontraditional
Publication: work is out of scope, not mechanistic

Screening

Preclinical/
animal

Clinical

Grower/
consumer

Funding/
collaboration


Biomedical Agriculture

7

Figure 1 Chronic disease and pathogenesis. Major chronic diseases account for 60% of
all deaths worldwide. In BMA, the focus is on cancer, cardiovascular disease, type II
diabetes, and obesity. Common to the pathogenesis of these diseases are altered glucose
metabolism, chronic inflammation, increased cellular oxidation, and chronic
endotoxemia.

provide a vision for the integral role that those in agriculture need to play for
efforts in CDP to be successful. The chapter addresses the following topics.
A summary of commonly encountered terminology in the field of food,

nutrition, and health is found in Section 2.1. The rationale for selection of
biomarkers that will serve as targets for crop screening and improvement is
discussed in the remainder of Section 2. A series of recommendations for
selecting genotypes of a crop for evaluation is presented in Section 3 and the
integration of this selection process with preclinical testing in animal models for
human disease is discussed in Section 4. Extension of the evaluation process to
the clinic is outlined in Section 4.3. Examples from our own work in BMA that
illustrate the implementation of the principles presented in various sections are
provided in Section 5. An approach for sustaining the BMA initiative is the
topic of Section 6, and Section 7 is a summary with future directions.


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Matthew D. Thompson and Henry J. Thompson

2. The Biomedical Landscape
2.1. Terminology
For those who work in fields related to food, nutrition, and health, and for
all consumers who make a concerted effort to benefit from foods at the
market to promote their health and prevent chronic disease, the area is well
known to be rife with claims, counter claims, half-truths, and everchanging recommendations and guidelines. To layout a framework for
investigating crop improvement for CDP, terminology commonly encountered in the area is briefly reviewed.
2.1.1. Food and health terms
Communication in this field can sometimes be unclear because the terms
are numerous, have both similar and sometimes vague definitions, and are
therefore often used interchangeably. Some of these terms will not appear
anywhere else in the chapter but are included to demonstrate that language
in nutrition and health has a powerful role in influencing the science and
public opinion:

(a) Essential nutrients are those substances that cannot be made in the human
body but that are required for normal cellular function. The absence of
essential dietary nutrients results in defined disease syndromes.
(b) Nonessential nutrients are not required for life, but they may promote
health. As discussed by Burlingame, the definition of a nutrient is up for
debate (Burlingame, 2001). Many chemical constituents of plant foods
are termed nonessential nutrients since they may positively impact
health; such chemicals are sometimes also referred to as phytonutrients.
(c) Phytochemical is a term that connotes health benefit based on colloquial
usage; however, in this chapter it will simply refer to plant chemicals.
Often the term phytochemical is associated with an antioxidant function,
but this practice is misleading.
(d) Dietary supplement is a term that infers a need to add a component to the
diet that is lacking. At one time, supplements were primarily comprised
of only essential nutrients such as vitamins and minerals. Currently, a
wide array of essential and nonessential nutrients can be purchased as
dietary supplements. The U.S. Food and Drug Administration regulates dietary supplements as foods, not drugs, and therefore, there is
limited regulation of the dietary supplement industry (Sadovsky et al.,
2008). Of note, assumptions and claims regarding the positive health
impact of antioxidant supplements are being challenged. Studies have
shown supplements can be associated with increased risk of mortality
(Bjelakovic et al., 2007).


Biomedical Agriculture

9

(e) Functional food is a term lacking a standard definition but generally
implies a food or food product containing components that promote

health. The term was established in Japan in the 1980s and has since
become embraced by the health sciences community (Hasler, 2002).
The term is primarily intended to (1) raise awareness of food’s role in
promoting health and (2) define markets for products to be sold (Hasler,
2000). However, the use of the word ‘‘functional’’ implies any food
with health benefit is a functional food. This creates problems in
differentiating functional and nonfunctional foods given that most
foods have some health-related nutrient content (Scrinis, 2008). Functional food and the related term nutraceutical both imply some level of
enhanced, beneficial biological activity.
(f ) Nutraceutical was coined by DeFelice in 1989 (Kalra, 2003). While it
connotes the properties of a food having health benefit to prevent or
treat disease, it has no strict regulatory definition, as opposed to the term
pharmaceutical (Mollet and Rowland, 2002).
(g) Medicinal food is yet another term denoting biological activity associated
with health benefit; however, like the nutraceutical and functional food
areas, it is not well regulated. Of note, overt medicalization of the food
supply is not desirable, as this would imply foods have drug-like effects
(Lawrence and Rayner, 1998).
(h) Bioactive food components (BAFC) do not imply health benefit or
embrace a medical platform. The term simply denotes that a food
possesses a component, that when consumed, influences a particular
biological system. As such, any given food has numerous BAFC
(Kris-Etherton et al., 2004).
2.1.2. Examples of the need to clarify terminology
In general, terms associated with health benefits of foods were developed to
avoid the strict regulatory oversight which pharmaceuticals receive; however, efforts are underway to standardize health claims (Hasler, 2008).
Nonetheless, examples of confusion regarding terminology abound, but
three that are commonly encountered illustrate the importance of understanding terminology. Dietary fiber is plant matter that is resistant to digestion
in the intestinal tract and that is known to improve gut function and reduce
the risk for certain types of cancer (Qu et al., 2005). Dietary fiber has also

been shown to beneficially reduce blood lipid profiles associated with
atherosclerosis (Berg et al., 2008). Fiber is a good example of a food
component that fits the majority of definitions outlined above (Prosky,
2000). The use of multiple, vaguely defined terms can lead to the perception
that a fiber-containing product has effects that cannot be achieved through a
balanced diet (Mayo Clinic, 2007). Vitamin C (ascorbic acid) is a well-known
essential nutrient and enzyme cofactor. Additionally, vitamin C plays an
important role as an exogenous antioxidant. However, in some cases,


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Matthew D. Thompson and Henry J. Thompson

consumers use vitamin C for medicinal purposes. This can distort the
understanding of scientists and consumers alike about the role of vitamin C
in health promotion and disease prevention, and of what vitamin C is
capable of doing when ingested in the diet as an essential nutrient (Naidu,
2003). Antioxidants have many established health benefits resulting from
their ability to act as reducing agents in biological systems. The damage
accumulated by free radical species has been associated with ageing and
many chronic diseases such as cancer and heart disease (Ames et al., 1993).
However, the mechanisms of bioactivity of many phytochemicals with
antioxidant activity is likely to be via their function as cell signaling agents
(Williams et al., 2004), not their activity as reducing agents. Yet this aspect
of chemical functionality, that is, the ability to regulate critical cell signaling
pathways, is frequently overlooked, in part because of misused or inadequate terminology. Unfortunately, terminology in the marketplace more
often has been used as a means to avoid regulatory issues and to market
products. As is evident from this review of terminology and brief commentary, crop improvement for CDP will benefit most from clearly stated
objectives and known target endpoints where these aspects of the work

are defined using carefully chosen terminology.

2.2. Chronic disease prevention
2.2.1. Background
Human diseases can be broadly categorized into infectious diseases and
noninfectious diseases. In general, chronic diseases are noninfectious diseases. As defined by the U.S. Center for National Health Statistics, a chronic
disease is one lasting for a duration in excess of 3 months (Centers for
Disease Control, 2008). According to the World Health Organization
(WHO), chronic diseases progress slowly and are of long duration. Chronic
diseases, such as cardiovascular disease, cancer, and diabetes, are the leading
causes of mortality both in the United States and around the world (Centers
for Disease Control, 2007; World Health Organization Global Report,
2008). As reported by the U.S. Centers for Disease Control, data collected
in 2007 indicated that chronic diseases, specifically diseases of the heart,
malignant neoplasms, cerebrovascular diseases, and diabetes mellitus
accounted for over 60% of all deaths in the US (Centers for Disease
Control, 2007). These same diseases, as well as chronic respiratory disease,
were also reported by WHO to account for 60% of all deaths worldwide
(World Health Organization Global Report, 2008). Globally, as summarized in Table 2, 80% of chronic disease deaths occur in low and middle
income countries, almost half of chronic disease deaths occur in people
under the age of 70, and without intervention, 17 million people will die
prematurely this year from a chronic disease (World Health Organization,
2008). The economic burden associated with prevalent chronic diseases,


Biomedical Agriculture

11

Table 2 Chronic disease statistics from the World Health Organization

Chronic disease is responsible for 60% of all deaths worldwide
80% of chronic disease deaths occur in low and middle income countries
Almost half of chronic disease deaths occur in people under the age of 70
Around the world, chronic disease affects women and men almost equally
The major risk factors for chronic disease are an unhealthy diet, physical
inactivity, and tobacco use
Without action, 17 million people will die prematurely this year from a
chronic disease
One billion adults are overweight—without action, this figure will surpass
1.5 billion by 2015
22 million children under 5 years old are overweight
Tobacco use causes at least five million deaths each year
If the major risk factors for chronic disease were eliminated, at least 80%
of heart disease, stroke, and type II diabetes would be prevented; 40% of
cancer would be prevented
Source: World Health Organization, />
that is, obesity, diabetes, cardiovascular diseases, and cancer, is enormous,
approaching a trillion dollars per annum in the US and growing at a rapid
rate (Eyre et al., 2004; World Health Organization, 2007; World Health
Organization Global Report, 2008). If the major risk factors, of which diet
plays a central role, were eliminated, at least 80% of heart disease, stroke, and
type II diabetes, and greater than 40% of cancers would be prevented
(World Health Organization Global Report, 2008). The prevalence of
these diseases is being driven by the global obesity epidemic, with obesity
acting as a gateway disease, that itself is associated with decreased longevity
(Centers for Disease Control, 2008; World Health Organization, 2007). In
general, chronic diseases cannot be prevented by vaccines and are not
completely reversed by medication (World Health Organization, 2003).
Health damaging behaviors, such as poor eating habits, physical inactivity,

and tobacco use, are major contributors to these highly prevalent chronic
diseases. As a result, chronic diseases are largely preventable since causality is
linked to environmental exposures that can be controlled by the individual
(Eyre et al., 2004; World Health Organization Global Report, 2008).
Excess body weight for height is the single most prevalent chronic
disease in the world. Not only is life expectancy reduced by obesity, but
also the risk for chronic diseases and their associated morbidities and mortality is increased (Eyre et al., 2004; Kahn et al., 2005). It is quantified by
determining an individual’s body mass index (BMI), that is, weight (in kg)
divided by height (in m2). A BMI between 18.5 and 24.9 is considered


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Matthew D. Thompson and Henry J. Thompson

within normal limits; a BMI between 25.0 and 29.9 is categorized as
overweight; a BMI between 30.0 and 34.9 is considered obese; and a
BMI greater than or equal to 35.0 is considered morbidly obese (IARC,
2002). Based on this system, obesity is easily determined and can be
monitored over time via the measurement of BMI. For simplicity, we
will refer to excess body weight for height as obesity for the remainder of
this chapter. In BMA, obesity is viewed as the most important chronic
disease to prevent because it impacts the development of the others so
profoundly. If food crop genotypes and food combinations can be identified
that assist individuals in preventing excess weight gain, then a significant
amount of the world’s chronic disease burden would be relieved. A list of
candidate crop-related weight prevention strategies is provided in Table 3.
Crops clearly have the potential to reduce obesity and its consequences,
including the risk for cardiovascular diseases, cancer, and type II diabetes,
through weight regulation alone. However, other mechanisms are normally

involved in the progression of chronic diseases.
2.2.2. The basis of biomarker-assisted screening for CDP:
Mechanisms and markers
One of the goals for the biomedical research community, in support of
BMA, is to provide agronomists with a set of tools that can be used to screen
crop genotypes and food combinations for CDP activity. To achieve this
goal, chronic disease risk must be reduced to a simplified, representative set
of biological features in animal and human pathophysiology that can be
assessed using chemical analyses and that are causally associated with disease
occurrence. The tools that result from this effort are referred to as biomarkers. The characteristics of useful biomarkers include (1) causal linkage to
the initiation or progression of the disease process, (2) concentrations
Table 3 Potential modes of action for food crops to reduce body weight and
risk of obesity
Mode of action

References

Reducing levels of digestible energy
High fiber content that adds bulk to the
diet and accelerates and sustains onset of
satiety
Reestablishing normal function of cellular
energy sensors
Altering gut microflora to promote
negative energy balance
Increasing nutrient density, maximizing
the nutrient to energy ratio

Englyst and Englyst (2005)
Burton-Freeman (2000)

Marshall (2006)
Turnbaugh et al. (2006)
Drewnowski (2005)


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13

change in response to changes in disease risk, (3) concentrations respond to
changes in the foods consumed, (4) easily assessed using validated chemical
assays, and (5) similarly affected in preclinical models for human diseases and
in the human disease itself. Identifying a panel of biomarkers that have
shared associations with the risk for cardiovascular disease, cancer, type II
diabetes, and obesity is based on the common mechanisms that underlie the
pathogenesis of these diseases (Biddinger and Kahn, 2006; Eyre et al., 2004;
Holmes et al., 2008; Marshall, 2006).
2.2.3. Common mechanisms and biomarkers
The goal of BMA is to reduce the risk of four seemingly unrelated chronic
diseases. The relationships between these diseases have become better
understood as data resulting from omics investigations has provided evidence of a common pathogenic basis for their occurrence (Fig. 2) (Holmes
and Nicholson, 2007; Holmes et al., 2008; Li et al., 2008; Marshall, 2006;
Martin et al., 2007). Specifically, cardiovascular disease, cancer, type II
diabetes, and obesity are metabolic disorders with shared impairments in
both cellular processes and metabolism, although each disease also retains
unique characteristics. At the cellular level, the pathologies associated with
each disease display alterations in cell proliferation, blood vessel formation,
and cell death, that is, necrosis, apoptosis, and autophagy. Also common to
these diseases are alterations in glucose metabolism, chronic inflammation,

and cellular oxidation that is attributed to a common network of cell
signaling events that are misregulated in each of these disease states
(Marshall, 2006). In addition, emerging evidence indicates the modulation
of gut microflora predisposes an individual to each of the disease processes
(Li et al., 2008; Martin et al., 2007). Microflora appear to be able to exert
effects through either biosynthesis of new compounds or chemical transformations of ingested ones, and as a consequence, influence exposure of
the host to gut microflora-associated endotoxins (Li et al., 2008; Martin
et al., 2007; Nicholson et al., 2008). Identification of a common set of
biomarkers for the shared pathogenic elements among these diseases is a
critical step in outlining a systematic approach to crop improvement.
A biomarker is objectively measured and evaluated as an indicator of
normal biological or pathogenic processes, or pharmacologic responses to a
therapeutic intervention (Packard and Libby, 2008). The substance is usually measured in blood or urine. The biomarkers relevant to BMA are
biological indicators of disease risk or disease presence (Table 4). The
information detailed in the following paragraphs provides a brief overview
of each biomarker class. Biomarker-assisted screening in animals on different diets can be used to guide both crop genotype selection and the
identification of beneficial food combinations. Additionally, the same biomarkers can be monitored clinically to determine efficacy of plant foodbased interventions in human subjects. Therefore, biomarker-assisted food


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Matthew D. Thompson and Henry J. Thompson

Figure 2 Factors involved in chronic disease development. The pathogenesis of
cancer, cardiovascular disease (CVD), type II diabetes, and obesity have substantial
cellular and molecular interrelationships. As illustrated, consumption of a nutrientpoor, energy-dense diet leads to altered glucose metabolism and insulin resistance. In
addition, Gram-negative bacteria in the gut flourish and die, leaving cell wall components behind to enter the systemic circulation and result in a state of chronic inflammation. Glycation products are formed at increased rates due to elevated blood glucose and
may also lead to elevated levels of circulating inflammatory factors. Inflammatory
processes are one stimulus for increased production of free radical species in vivo.
Production of reactive species leads to oxidation of cellular components and can result

in DNA mutation and altered molecular function. In parallel, elevated levels of insulin
stimulate release of growth factors like IGF-1. Along with increases in available
glucose, this state of positive energy balance perturbs cellular energy sensing mechanisms. Dysfunction occurs as cells lose fine control of proliferation and death pathways.
Obesity results from a large number of known and unknown factors that elevate disease
risk. The cumulative and interdependent effects of many processes increase risk for the
development of chronic diseases. The aim of BMA is to develop crop genotypes that
have high chronic disease prevention (CDP) activity and high nutrient density. As
outlined, this may significantly reduce risk for disease.


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Biomedical Agriculture

Table 4 Biomarkers associated with chronic disease risk
Biomarker class

Chemical analyses

Glucose metabolism

Fasting glucose
Fasting insulin
Hemoglobin A1c
Insulin-like growth factor-1, total and free
C-reactive protein
Interleukin-6
Tumor necrosis factor-a
8-Hydroxy-2-deoxyguanosine
8-Isoprostane F2a

Oxygen radical absorbance capacity
Protein carbonyls
Lipopolysaccharide, total and free

Inflammation

Oxidation

Endotoxemia

crop improvement has emerged as an essential component underlying the
development of the BMA framework:
(a) Glucose metabolism. Glucose is essential for life both as a primary source
of energy and as a building block that directly or indirectly supports the
biosynthetic processes required for growth and maintenance of cell
function. Consequently the supply of glucose to cells within the body
in mammalian species is tightly regulated. The pathogenic events that
occur in cardiovascular disease, cancer, type II diabetes, and obesity
involve alterations in glucose metabolism, a primary manifestation of
which is insulin resistance (Misciagna et al., 2005; Zieman and Kass,
2004). Insulin resistance causes increased circulating levels of glucose,
insulin, and insulin-like growth factors (Ezzat et al., 2008; Frasca et al.,
2008; O’Connor et al., 2008). Elevated levels of circulating glucose also
cause glycation of proteins, one of which is hemoglobin A1c (Giugliano
et al., 2008; Misciagna et al., 2007). Collectively, elevated levels of
fasting glucose and insulin and nonfasting levels of IGF-1 and hemoglobin A1c are biomarkers for alterations in glucose metabolism associated with chronic disease risk (Pirola et al., 2003; Soldatos et al., 2005;
Stumvoll et al., 2005).
(b) Inflammation. Inflammation is the body’s basic response to infection and
injury, but when the signals that regulate this process are continuously
activated, a chronic inflammatory process results. Chronic inflammation stimulates processes which underlie chronic disease development,

such as the increased oxidation of cellular macromolecules as reviewed
elsewhere (Schwartsburd, 2003). Obesity and insulin resistance are also
associated with chronic inflammation (Schenk et al., 2008). While the


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Matthew D. Thompson and Henry J. Thompson

mechanisms are not completely elucidated, one hypothesis to explain the
association of insulin resistance with inflammation is that chronic hyperglycemia and insulin resistance lead to advanced glycation end products
that are able to bind to cell surface receptors that stimulate the production
of inflammatory cytokines (Lopez-Garcia et al., 2004). Three circulating
factors that are indicative of ongoing inflammation are interleukin-6,
C-reactive protein, and TNFa; they serve as biomarkers for chronic
disease risk (Casas et al., 2008; Coussens and Werb, 2002).
(c) Oxidative damage. Oxidative stress is caused by an imbalance between
the production of reactive oxygen species and a biological system’s
ability to readily detoxify the reactive intermediates or easily repair
the resulting damage. All forms of life maintain a reducing environment
within their cells which is largely preserved by enzymes and endogenous reducing agents. Reactive oxygen species can be beneficial, as they
are used by the immune system as a way to attack and kill pathogens, as
well as participate in cell signaling (Martindale and Holbrook, 2002).
However, disturbances in the normal redox state can cause toxic effects
through the production of peroxides and free radicals such as hydroxyl
(OHÁ) and superoxide (OÁ2 ) radicals, hydrogen peroxide (H2O2), and
singlet oxygen (1O2) (Breimer, 1990; Cerutti, 1985; Halliwell and
Gutteridge, 1999), particularly in response to inflammation (Coussens
and Werb, 2002; Schenk et al., 2008). In humans, oxidative stress is
involved in the pathogenesis of a number of disorders including cardiovascular disease, cancer, type II diabetes, and obesity (Collins, 1998;

Cooper et al., 2007; Schleicher and Friess, 2007; Vincent et al., 2007).
Biomarkers of oxidative damage include 8-oxodG, a marker of DNA
damage (Cadet et al., 2002; Cooke et al., 2006), 8-isoprostane F2a, a
marker of lipid peroxidation (Milne et al., 2007), and protein carbonyls,
a marker of protein oxidation (Hwang and Kim, 2007; Shacter, 2000).
(d) Gut microflora. The human intestinal tract houses an ‘‘extended
genome’’ (Kinross et al., 2008), the microbiome. A complex symbiosis
influences human host metabolism, physiology, and gene expression
(Nicholson et al., 2008). Advances in microbiological analysis and
systems biology are now beginning to implicate the gut microbiome
in the etiology of cardiovascular disease, cancer, type II diabetes, and
obesity, in part by a process referred to as chronic (or metabolic)
endotoxemia (Cani et al., 2007). Endotoxemia is due to the absorption
of lipopolysaccharide (LPS) from the gut (Cani et al., 2008). This
endotoxin is continuously produced in the gut from cell wall components of Gram-negative bacteria. Production and absorption of LPS can
be modulated via dietary effects on gut microflora composition and
inflammatory responses to LPS are influenced by obesity and insulin
resistance (Ley et al., 2006). The principal biomarkers for endotoxemia
are circulating levels of total and free LPS (Cani and Delzenne, 2007).


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17

In summary, for reasons not fully understood, chronic positive energy
balance and excess accumulation of body fat result in systemic changes in the
body such that the factors associated with physiological regulation of glucose metabolism become dysfunctional; this is referred to as altered glucose
metabolism. As a component of altered glucose metabolism and fat accumulation, the concentration of proinflammatory molecules in circulation
and in various organ sites begin to accumulate despite the lack of an external

inflammatory stimulus; this is referred to as chronic inflammation. Elevated
levels of reactive oxygen and nitrogen species can result, leading to the
oxidative damage of cellular macromolecules. A potential modulator of the
inflammatory condition is the presence or absence of populations of microflora in the gut that can lead to increased systemic exposure to microbial cell
wall components that promote inflammation and cellular oxidation in the
body, a condition referred to as chronic endotoxemia. These four conditions—altered glucose metabolism, chronic inflammation, increased cellular
oxidation, and chronic endotoxemia—are widely regarded as playing causal
roles in the initiation and progression of obesity, cardiovascular diseases,
cancer, and type II diabetes (Grundy et al., 2002).
2.2.4. Strategy for implementing biomarker-assisted crop
improvement for CDP
Biomarker-assisted crop improvement is envisioned as a dynamic process
that will evolve as the field of BMA matures. At the outset, three stages of
biomarker evaluation and use are envisioned. In the short term, one or more
biomarkers for each altered function associated with a disease condition
should be evaluated (Table 4). In the second phase, development of which is
ongoing, profiles of mammalian metabolites determined by highthroughput LC or GC mass spectrometry platforms will be used for determining chronic disease risk (Nicholson et al., 2008). These profiles will
(1) have greater sensitivity to detect changes in disease risk; (2) have the
advantage of requiring a small sample of blood, urine, or tissue for analysis;
and (3) be available at a cost affordable for use in crop screening in animals as
well as for monitoring human populations. A third phase of biomarkerassisted assessment is envisioned to include the use of genomics technologies
to categorize, more specifically, the nature of genetic predisposition of an
individual to chronic disease using functional polymorphisms (Ambrosone
et al., 1999; Kornman et al., 2004). The end goal is to determine crop
genotypes and food combinations that reduce chronic disease risk via
understanding how they affect pathogenic mechanisms involved in each
disease. Crop genetic and chemical diversity, as discussed in the next
section, are critical to understanding how to reduce disease risk by inhibiting cellular and molecular mechanisms underlying chronic disease
processes.

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3. Agricultural Landscape
3.1. Genotypic diversity in crops
Progress in food crop improvement is driven by screening genotypes for
desired agronomic traits (Lenihan et al., 2004; Lindsay et al., 2004; Wu et al.,
2005). Worldwide, the total number of genotypes for a given food crop is
quite large, probably in excess of 1000 genotypes per species (Food and
Agriculture Organization, 1998). For some crops, core collections have
been or are being assembled from which to draw germplasm for evaluation
for traits of agronomic interest (Fowler and Hodgkin, 2004); rice is a model
crop in this regard (Londo et al., 2006; McNally et al., 2006; Monna et al.,
2006). However, there have been no systematic efforts to tap global crop
diversity for CDP. One only has to review the accomplishments of natural
products discovery programs to recognize the potential of this approach
(Guilford and Pezzuto, 2008; Kinghorn et al., 2004; Park and Pezzuto, 2002).
Crops have undergone a long process of selection for agronomic traits
during domestication and genetic improvement for commercial use (Stuber
and Hancock, 2008). The scientific basis for proposing to screen diverse
food crop germplasm for CDP activity derives from the bottleneck theory
of domestication that estimates as much as 95% of the variation in germplasm for many traits was lost during that process (Ahn and Tanksley, 1993;
Frary et al., 2000; Gepts and Hancock, 2006; Gepts and Papa, 2003;
Lippman and Tanksley, 2001; Ross-Ibarra et al., 2007). Thus, one could
hypothesize that significant variation will be identified among genotypes
within a crop for CDP if sufficiently diverse germplasm resources are
evaluated. On the other hand, if only highly related commercial genotypes
are screened for CDP, it is likely that the genotypes tested will be found to

have limited variation for CDP. The prevailing practices for dietary assessment in the biomedical sciences assume that different genotypes within a
food crop will have similar effects on CDP (discussed in Section 1).
Therefore, little has been done to engage agronomists to challenge this
assumption and take advantage of plant biodiversity (Keil, 2008). In view of
this, a critical step in successful implementation of BMA is that a diverse
collection of crop genotypes be evaluated; failure to do so will limit the
potential of crop-based research for CDP.

3.2. Chemical basis for CDP
The basis for CDP by a food crop is hypothesized to be through the crop’s
normalization of glucose metabolism and cellular oxidation and its inhibition of chronic inflammation and endotoxemia (Section 2). While dysregulation of a common cell signaling network has been reported to underlie