By Eric Sorensen, WSU science writer 
PULLMAN, Wash. – The largest study of its kind has found that organic foods and crops have a suite of advantages over their conventional counterparts, including more antioxidants and fewer, less frequent pesticide residues.
The study looked at an unprecedented 343 peer-reviewed publications comparing the nutritional quality and safety of organic and conventional plant-based foods, including fruits, vegetables and grains. The study team applied sophisticated meta-analysis techniques to quantify differences between organic and non-organic foods.
Most of the publications covered in the study looked at crops grown in the same area on similar soils. This approach reduces other possible sources of variation in nutritional and safety parameters.
The research team found the quality and reliability of comparison studies has greatly improved in recent years, leading to the discovery of significant nutritional and food safety differences not detected in earlier studies. For example, the new study incorporates the results of a research project led by WSU’s John Reganold that compared the nutritional and sensory quality of organic and conventional strawberries grown in California.
Responding to the new paper’s results, Reganold said, “This is an impressive study, and its major nutritional findings are similar to those reported in our 2010 strawberry paper.”
In general, the team found that organic crops have several nutritional benefits that stem from the way the crops are produced. A plant on a conventionally managed field will typically have access to high levels of synthetic nitrogen and will marshal the extra resources into producing sugars and starches. As a result, the harvested portion of the plant will often contain lower concentrations of other nutrients, including health-promoting antioxidants.
Without the synthetic chemical pesticides applied on conventional crops, organic plants tend to produce more phenols and polyphenols to defend against pest attacks and related injuries. In people, phenols and polyphenols can help prevent diseases triggered or promoted by oxidative damage, like coronary heart disease, stroke and certain cancers.
Overall, organic crops had 18 to 69 percent higher concentrations of antioxidant compounds. The team concludes that consumers who switch to organic fruit, vegetables and cereals would get 20 to 40 percent more antioxidants. That’s the equivalent of about two extra portions of fruit and vegetables a day, with no increase in caloric intake.
“This study is telling a powerful story of how organic plant-based foods are nutritionally superior and deliver bona fide health benefits,” said Benbrook.
In a surprising finding, the team concluded that conventional crops had roughly twice as much cadmium, a toxic heavy metal contaminant, as organic crops. The leading explanation is that certain fertilizers approved for use only on conventional farms somehow make cadmium more available to plant roots. A doubling of cadmium from food could push some individuals over safe daily intake levels.
“We benefited from a much larger and higher quality set of studies than our colleagues who carried out earlier reviews,” said Carlo Leifert, a Newcastle University professor and the project leader.
The Newcastle study cost about $429,000 and was funded by the European Framework Programme 6, which is a research program of the European Union, and the Sheepdrove Trust, a private charity that supports research on sustainability, diversity and organic farming.
Contact: Chuck Benbrook, research professor, Washington State University, 541-828-7918, cbenbrook@wsu.edu
Demand for organic foods is partially driven by consumers' perceptions that they are more nutritious. However, scientific opinion is divided on whether there are significant nutritional differences between organic and non-organic foods, and two recent reviews have concluded that there are no
differences. In the present study, we carried out meta-analyses based on 343 peer-reviewed publications that indicate statistically significant and meaningful differences in composition between organic and non-organic crops/crop-based foods. Most importantly, the concentrations of a range of antioxidants such as polyphenolics were found to be substantially higher in organic crops/crop-based foods, with those of phenolic acids, flavanones, stilbenes, flavones, flavonols and anthocyanins being an estimated 19 (95 % CI 5, 33) %, 69 (95 % CI 13, 125) %, 28 (95 % CI 12, 44) %, 26 (95 % CI 3, 48) %, 50 (95 % CI 28, 72) % and 51 (95 % CI 17, 86) % higher, respectively. Many of these compounds have previously been linked to a reduced risk of chronic diseases, including CVD and neurodegenerative diseases and certain cancers, in dietary intervention and epidemiological studies. Additionally, the frequency of occurrence of pesticide residues was found to be four times higher in conventional crops, which also contained significantly higher concentrations of the toxic metal Cd. Significant differences were also detected for some other (e.g. minerals and vitamins) compounds. There is evidence that higher antioxidant concentrations and lower Cd concentrations are linked to specific agronomic practices (e.g. non-use of mineral N and P fertilisers, respectively) prescribed in organic farming systems. In conclusion, organic crops, on average, have higher concentrations of antioxidants, lower concentrations of Cd and a lower incidence of pesticide residues than the non-organic comparators across regions and production seasons.
PULLMAN, Wash. – The largest study of its kind has found that organic foods and crops have a suite of advantages over their conventional counterparts, including more antioxidants and fewer, less frequent pesticide residues.
The study looked at an unprecedented 343 peer-reviewed publications comparing the nutritional quality and safety of organic and conventional plant-based foods, including fruits, vegetables and grains. The study team applied sophisticated meta-analysis techniques to quantify differences between organic and non-organic foods.
Quality of studies improves
“Science marches on,” said Charles Benbrook, a Washington State University researcher and the lone American co-author of the paper published in the British Journal of Nutrition. “Our team learned valuable lessons from earlier reviews on this topic, and we benefited from the team’s remarkable breadth of scientific skills and experience.”Most of the publications covered in the study looked at crops grown in the same area on similar soils. This approach reduces other possible sources of variation in nutritional and safety parameters.
The research team found the quality and reliability of comparison studies has greatly improved in recent years, leading to the discovery of significant nutritional and food safety differences not detected in earlier studies. For example, the new study incorporates the results of a research project led by WSU’s John Reganold that compared the nutritional and sensory quality of organic and conventional strawberries grown in California.
Responding to the new paper’s results, Reganold said, “This is an impressive study, and its major nutritional findings are similar to those reported in our 2010 strawberry paper.”
Organic plants produce more antioxidants
The British Journal of Nutrition study was led by scientists at Newcastle University in the United Kingdom, with Benbrook helping design the study, write the paper and review the scientific literature, particularly on studies in North and South America.In general, the team found that organic crops have several nutritional benefits that stem from the way the crops are produced. A plant on a conventionally managed field will typically have access to high levels of synthetic nitrogen and will marshal the extra resources into producing sugars and starches. As a result, the harvested portion of the plant will often contain lower concentrations of other nutrients, including health-promoting antioxidants.
Without the synthetic chemical pesticides applied on conventional crops, organic plants tend to produce more phenols and polyphenols to defend against pest attacks and related injuries. In people, phenols and polyphenols can help prevent diseases triggered or promoted by oxidative damage, like coronary heart disease, stroke and certain cancers.
Overall, organic crops had 18 to 69 percent higher concentrations of antioxidant compounds. The team concludes that consumers who switch to organic fruit, vegetables and cereals would get 20 to 40 percent more antioxidants. That’s the equivalent of about two extra portions of fruit and vegetables a day, with no increase in caloric intake.
10 to 100 times fewer pesticide residues
The researchers also found pesticide residues were three to four times more likely in conventional foods than organic ones, as organic farmers are not allowed to apply toxic, synthetic pesticides. While crops harvested from organically managed fields sometimes contain pesticide residues, the levels are usually 10-fold to 100-fold lower in organic food, compared to the corresponding, conventionally grown food.“This study is telling a powerful story of how organic plant-based foods are nutritionally superior and deliver bona fide health benefits,” said Benbrook.
In a surprising finding, the team concluded that conventional crops had roughly twice as much cadmium, a toxic heavy metal contaminant, as organic crops. The leading explanation is that certain fertilizers approved for use only on conventional farms somehow make cadmium more available to plant roots. A doubling of cadmium from food could push some individuals over safe daily intake levels.
Team surveys more and better studies
More than half the studies in the Newcastle analysis were not available to the research team that carried out a 2009 study commissioned by the UK Food Standards Agency. Another review published by a Stanford University team in 2011 failed to identify any significant clinical health benefits from consumption of organic food, but incorporated fewer than half the number of comparisons for most health-promoting nutrients.“We benefited from a much larger and higher quality set of studies than our colleagues who carried out earlier reviews,” said Carlo Leifert, a Newcastle University professor and the project leader.
The Newcastle study cost about $429,000 and was funded by the European Framework Programme 6, which is a research program of the European Union, and the Sheepdrove Trust, a private charity that supports research on sustainability, diversity and organic farming.
Contact: Chuck Benbrook, research professor, Washington State University, 541-828-7918, cbenbrook@wsu.edu
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Abstract
Demand for organic foods is partially driven by consumers' perceptions that they are more nutritious. However, scientific opinion is divided on whether there are significant nutritional differences between organic and non-organic foods, and two recent reviews have concluded that there are no
differences. In the present study, we carried out meta-analyses based on 343 peer-reviewed publications that indicate statistically significant and meaningful differences in composition between organic and non-organic crops/crop-based foods. Most importantly, the concentrations of a range of antioxidants such as polyphenolics were found to be substantially higher in organic crops/crop-based foods, with those of phenolic acids, flavanones, stilbenes, flavones, flavonols and anthocyanins being an estimated 19 (95 % CI 5, 33) %, 69 (95 % CI 13, 125) %, 28 (95 % CI 12, 44) %, 26 (95 % CI 3, 48) %, 50 (95 % CI 28, 72) % and 51 (95 % CI 17, 86) % higher, respectively. Many of these compounds have previously been linked to a reduced risk of chronic diseases, including CVD and neurodegenerative diseases and certain cancers, in dietary intervention and epidemiological studies. Additionally, the frequency of occurrence of pesticide residues was found to be four times higher in conventional crops, which also contained significantly higher concentrations of the toxic metal Cd. Significant differences were also detected for some other (e.g. minerals and vitamins) compounds. There is evidence that higher antioxidant concentrations and lower Cd concentrations are linked to specific agronomic practices (e.g. non-use of mineral N and P fertilisers, respectively) prescribed in organic farming systems. In conclusion, organic crops, on average, have higher concentrations of antioxidants, lower concentrations of Cd and a lower incidence of pesticide residues than the non-organic comparators across regions and production seasons.
Increased public concerns about the negative environmental
and health impacts of agrochemicals (pesticides, growth regulators and
mineral fertilisers) used in crop production have been major drivers for
the increase in consumer demand for organic foods over the last 20
years(
1
–
3
).
Organic crop production standards prohibit the use of
synthetic chemical crop protection products and certain mineral
fertilisers (all N, KCl and superphosphate) to reduce environmental
impacts (nitrate (
) leaching and P run-off and pesticide contamination of
groundwater) and the risk of pesticide residues being present in crop
plants(
4
). Instead, they prescribe regular inputs of
organic fertilisers (e.g. manure and composts), use of legume crops in
rotation (to increase soil N levels), and application of preventative
and non-chemical crop protection methods (e.g. the use of crop rotation,
more resistant/tolerant varieties, mechanical and flame weeding, and
biological disease and pest control products). However, organic
standards permit the use of certain plant or microbial extract and/or
mineral (e.g. Cu- and S-based) crop protection products(
5
,
6
).
) leaching and P run-off and pesticide contamination of
groundwater) and the risk of pesticide residues being present in crop
plants(
4
). Instead, they prescribe regular inputs of
organic fertilisers (e.g. manure and composts), use of legume crops in
rotation (to increase soil N levels), and application of preventative
and non-chemical crop protection methods (e.g. the use of crop rotation,
more resistant/tolerant varieties, mechanical and flame weeding, and
biological disease and pest control products). However, organic
standards permit the use of certain plant or microbial extract and/or
mineral (e.g. Cu- and S-based) crop protection products(
5
,
6
).
As a result, organic and conventional crop production may
differ significantly in crop rotation designs and fertilisation and crop
protection protocols as well as in the type of crop varieties used(
6
–
10
). Apart from minimising the risk of agrochemical
residues being present in crops, the agronomic protocols used in
organic farming systems may also affect mineral uptake patterns and
metabolic processes in crop plants. Recent studies have shown that the
switch from mineral to organic fertilisers results in significant
differences in gene and protein expression patterns and, as a result, in
secondary metabolite profiles; for example, approximately 10 % of
proteins have been found to be either up- or down-regulated in response
to contrasting fertiliser inputs in potato and wheat(
10
–
15
). Also, a switch from pesticide-based
conventional to organic crop protection protocols has been shown to have
a significant, but more limited effect than fertilisation regimens, and
there were some statistically significant interactions between
fertilisation and crop protection protocols with respect to gene and
protein expression pattern(
10
–
15
).
Over the last 20 years, a large number of scientific
studies have compared the concentrations of nutritionally relevant
minerals (e.g. Fe, Zn, Cu and Se), toxic metals (e.g. Cd and Pb),
pesticide residues, macronutrients (e.g. proteins, fats and
carbohydrates) and secondary metabolites (e.g. antioxidants,
(poly)phenolics and vitamins) in crops from organic and conventional
production systems (see the online supplementary material for a list of
publications).
There is particular interest in antioxidant
activity/concentrations, as there is strong scientific evidence for
health benefits associated with increased consumption of crops rich in
(poly)phenolics and other plant secondary metabolites with antioxidant
activity (e.g. carotenoids and vitamins C and E)(
16
–
18
). Most importantly, a substantial number of
human dietary intervention studies have reported an increased dietary
intake of antioxidant/(poly)phenolic-rich foods to protect against
chronic diseases, including CVD, certain cancers (e.g. prostate cancer)
and neurodegenerative diseases; a detailed description of the evidence
has been given in recent reviews by Del Rio et al.
(
16
) and Wahlqvist(
17
). Also, these plant secondary metabolites are
increasingly being recognised to contribute significantly to the health
benefits associated with increased fruit, vegetable and whole grain
consumption(
16
–
18
).
Several systematic literature reviews have recently
analysed the available published information, using both qualitative and
quantitative methods, with the aim of identifying the potential effects
of organic and conventional production protocols on the nutritional
quality of crops(
19
–
21
). However, these systematic reviews (1) used
different methodologies (e.g. weighted and unweighted meta-analyses) and
inclusion criteria, (2) did not cover most of the large amount of
information published in the last 4–5 years, (3) provided no structured
assessment of the strength of the evidence presented, and (4) came to
contrasting conclusions. As a result, there is still considerable
controversy as to whether the use of organic production standards
results in significant and consistent changes in the concentrations of
potentially health-promoting (e.g. antioxidants, (poly)phenolics,
vitamins and certain minerals) and potentially harmful (e.g. Cd and Pb)
compounds in crops and crop-based foods(
7
,
19
–
22
). However, there is increasing evidence and more
widespread acceptance that the consumption of organic foods is likely
to reduce exposure to pesticide residues(
21
,
23
,
24
).
There are major research synthesis challenges to assessing
differences in crop composition resulting from farming practices. Most
importantly, the studies available for meta-analyses (1) have used
different experimental designs (e.g. replicated field experiments, farm
surveys and retail surveys) and (2) have been carried out in
countries/regions with contrasting agronomic and pedo-climatic
background conditions (see the online supplementary material for a list
of publications). This heterogeneity is likely to increase the amount of
published data required to detect and understand variation in
composition parameters resulting from the use of contrasting crop
production methods. An additional problem is that many studies do not
report measures of variation, which reduces the within-study power of
unweighted analyses and the between-study power of weighted analyses.
Weighted meta-analyses are widely regarded as the most appropriate
statistical approach for comparing data sets from studies with variable
experimental designs(
25
,
26
). However, some studies have used unweighted analytical methods(
19
) to avoid the loss of information associated with conducting weighted meta-analyses on a subset of the available information.
Therefore, the main objectives of the present study were to
(1) carry out a systematic literature review of studies focused on
quantifying composition differences between organic and conventional
crops, (2) conduct weighted and unweighted meta-analyses of the
published data, (3) carry out sensitivity analyses focused on
identifying to what extent meta-analysis results are affected by the
inclusion criteria (e.g. using mean or individual data reported for
different crop varieties or experimental years) and meta-analysis method
(e.g. weighted v. unweighted), and (4) discuss
meta-analysis results in the context of the current knowledge about the
nutritional impacts of compounds for which significant composition
differences were detected.
The present study specifically focused on plant secondary
metabolites (especially antioxidants/(poly)phenolics and vitamins),
potentially harmful synthetic chemical pesticides, toxic metals
(including Cd, As and Pb),
, nitrite (
), macronutrients (including proteins, amino acids, carbohydrates
and reducing sugars) and minerals (including all plant macro- and
micronutrients). Metabolites produced by micro-organisms on plants (e.g.
mycotoxins) were not the subject of the present systematic literature
review and meta-analyses.
, nitrite (
), macronutrients (including proteins, amino acids, carbohydrates
and reducing sugars) and minerals (including all plant macro- and
micronutrients). Metabolites produced by micro-organisms on plants (e.g.
mycotoxins) were not the subject of the present systematic literature
review and meta-analyses.Materials and methods
Literature search: inclusion criteria and search strategy
The literature search strategy and meta-analysis protocols used were based on those previously published by Brandt et al.
(
27
), and flow diagrams of the protocols used are shown in Figs. 1 and 2.
Relevant publications were identified through an initial search of the
literature with Web of Knowledge using the following search terms: (1)
organic* or ecologic* or biodynamic*; (2) conventional* or integrated;
(3) names of ninety-eight relevant crops and foods (see online
supplementary Table S1 for a full list). Publications in all languages,
published in peer-reviewed journals, and reporting data on both
desirable and undesirable composition parameters were considered
relevant for inclusion in the meta-analyses. The search was restricted
to the period between January 1992 (the year when legally binding
organic farming regulations were first introduced in the European Union)
and December 2011 (the year when the project ended) and provided 17 333
references. An additional 208 publications (published between 1977 and
2011) were found by (1) studying lists of references or (2) directly
contacting the authors of the published papers and reviews identified in
the initial literature search. The abstracts of all publications were
then examined to determine whether they contained original data obtained
by comparing composition parameters in organic and conventional plant
foods. This led to the identification of 448 suitable publications. Of
these, 105 papers were subsequently rejected, because reading of the
full papers indicated that they did not report suitable data sets or
contained the same data as other studies.
Fig. 1 Summary of the search and
selection protocols used to identify papers included in the
meta-analyses. * Review carried out by one reviewer; † Data extraction
carried out by two reviewers. CF, comparison of matched farms; BS,
basket studies; EX, controlled field experiments.
Fig. 2 Meta-analysis strategy
used for the identification of data sets in the literature review.
* References are summarised in Table S2 (available online). RD, risk
difference.
Data sets were deemed suitable if the mean concentrations of at least one mineral, macronutrient, secondary metabolite or
/
or the frequency of occurrence of pesticide residues in organic
and conventional crops or crop-based foods were reported. Only four
non-peer-reviewed papers with suitable data sets were identified but
subsequently rejected, as the small number minimised any potential bias(
28
) from using peer review as a ‘quality’ selection criterion.
/
or the frequency of occurrence of pesticide residues in organic
and conventional crops or crop-based foods were reported. Only four
non-peer-reviewed papers with suitable data sets were identified but
subsequently rejected, as the small number minimised any potential bias(
28
) from using peer review as a ‘quality’ selection criterion.
As a result, 343 peer-reviewed publications reporting crop
composition data were selected for data extraction, of which 156
references fulfilled the criteria for inclusion in the standard weighted
meta-analysis and 343 fulfilled the criteria for inclusion in the
standard unweighted meta-analysis. This represents a significantly
greater evidence base than the three previous systematic
reviews/meta-analyses of comparative crop composition data(
19
–
21
). All publications included in these previous
reviews (including studies published before 1992) were also used in the
standard weighted meta-analysis carried out in the present study, except
for a small number of papers that were found to report the same data as
other publications that had already been included.
Data were extracted from three types of comparative
studies: (1) comparisons of matched farms (CF), farm surveys in which
samples were collected from organic and conventional farms in the same
country or region; (2) basket studies (BS), retail product surveys in
which organic and conventional products were collected in retail
outlets; (3) controlled field experiments (EX) in which samples were
collected from experimental plots managed according to organic or
conventional farming standards/protocols. Data from all the three types
of studies were deemed relevant for the meta-analyses if the authors
stated that (1) organic farms included in farm surveys were using
organic farming methods, (2) organic products collected in retail
surveys were labelled as organic, and (3) organic plots used in EX were
managed according to organic farming standards.
Several studies compared more than one organic or
conventional system or treatment. For example, additional conventional
systems/treatments were described as ‘integrated,’ ‘low input,’ ‘low
fertility’ or ‘extensive’, and an additional organic system/treatment
included in some studies was described as ‘biodynamic’. Also, in some
publications, organic or conventional systems with contrasting rotation
designs (e.g. with or without cover crops) or fertilisation regimens
(different types and levels of N inputs) were compared. In such cases,
only the organic and conventional (non-organic) system identified by the
authors as closest to the typical, contemporary organic/conventional
farming system was used in the meta-analyses, as recommended by Brandt et al.
(
20
). Full references of the publications and a
summary of descriptions of the studies included in the meta-analyses are
given in Tables S2 and S4 (available online).
The database generated and used for the meta-analyses will be made freely available on the Newcastle University website (http://research.ncl.ac.uk/nefg/QOF) for use and scrutiny by others.
Data and information extraction and validation
Information and data were extracted from all the selected
publications (see above) and compiled in a Microsoft Access database. A
list of the information extracted from the publications and recorded in
the database is given in Table S4 (available online).
Data reported as numerical values in the text or tables
were copied directly into the database. Only data published in graphical
form were enlarged, printed, measured (using a ruler) and then entered
into the database as described previously(
20
).
Where data for multiple time points were reported, two
approaches were used, depending on whether the analysed crop tissue was
likely to be used as food/feed. For crops that are continuously
harvested (e.g. tomato and cucumber), analytical data for mature/ripe
products (e.g. fruits) collected at multiple time points during the
season were averaged before being used in the standard meta-analyses; if
analytical data for immature/unripe products were reported, they were
not included in the mean. For crops (e.g. grape and cereals) in which
products (e.g. fruits and grain) are harvested/analysed at different
maturity stages, only analytical results for the mature product (that
would have been used as food/feed) were used. In both the standard
weighted and standard unweighted analyses, composition data reported for
different cultivars/varieties and/or years/growing seasons in the same
publication were averaged before being used in the meta-analyses.
Publications were assessed for eligibility and data were
independently extracted from them by two reviewers. Data extracted by
the two reviewers were then compared. Discrepancies were detected for
approximately 2 % of the data extracted, and in these cases, data
extraction was repeated to correct mistakes. A list of the publications
included in the meta-analyses is given in Table S2 (available online).
Study characteristics, summaries of the methods used for
sensitivity analyses and ancillary information are given in Tables
S2–S10 (available online). These include information on (1) the number
of papers from different countries and publication years used in the
meta-analyses (see online supplementary Figs. S1 and S2); (2) study
type, location and crop/products assessed in different studies (see
online supplementary Table S3); (3) the type of material/data extracted
from the papers (see online supplementary Table S4); (4) data-handling
methods/inclusion criteria and meta-analysis methods used in the
sensitivity analyses (see online supplementary Table S5); (5)
composition parameters included in the meta-analyses (see online
supplementary Table S6); and (6) composition parameters for which
meta-analyses were not possible (n< 3; see online supplementary Table S7).
Table S8 (available online) summarises basic statistics on
the number of studies, individual comparisons, organic and conventional
sample sizes, and comparisons showing statistically or numerically
higher concentrations in organic or conventional crops for the
composition parameters included in Figs. 3 and 4.
Tables S9 and S10 (available online) summarise the numerical values for
the mean percentage differences (MPD) and 95 % CI calculated using the
data included in the standard unweighted and weighted meta-analyses of
composition parameters shown in Figs. 3 and 4, respectively (where MPD are shown as symbols).
Fig. 3 Results of the standard
unweighted and weighted meta-analyses for antioxidant activity, plant
secondary metabolites with antioxidant activity, macronutrients,
nitrogen compounds and cadmium (data reported for all crops and
crop-based foods included in the same analysis). MPD, mean percentage
difference; CONV, conventional food samples; ORG, organic food samples; n,
number of data points included in the meta-analyses; FRAP, ferric
reducing antioxidant potential; ORAC, oxygen radical absorbance
capacity; TEAC, Trolox equivalent antioxidant capacity; SMD,
standardised mean difference. Values are standardised mean differences,
with 95 % confidence intervals represented by horizontal bars. * P
value < 0·05 indicates a significant difference between ORG and
CONV. † Numerical values for MPD and standard errors are given in Table
S9 (available online). ‡ Ln ratio = Ln(ORG/CONV × 100 %).
§ Heterogeneity and the I
2 statistic. ∥ Data reported for different
compounds within the same chemical group were included in the same
meta-analyses. ¶ Outlying data points (where the MPD between ORG and
CONV was more than fifty times greater than the mean value including the
outliers) were removed. ○, MPD calculated using data included in the
standard unweighted meta-analysis; 
, MPD calculated using data included in the standard weighted meta-analysis; ◆, SMD.
, MPD calculated using data included in the standard weighted meta-analysis; ◆, SMD.
Fig. 4 Results of the standard
unweighted and weighted meta-analyses for different crop types/products
for antioxidant activity, plant secondary metabolites with antioxidant
activity, macronutrients, nitrogen and cadmium. MPD, mean percentage
difference; CONV, conventional food samples; ORG, organic food samples; n,
number of data points included in the meta-analyses; SMD, standardised
mean difference. Values are standardised mean differences, with 95 %
confidence intervals represented by horizontal bars. * P
value < 0·05 indicates a significant difference between ORG and
CONV. † Numerical values for MPD and standard errors are given in Table
S10 (available online). ‡ For parameters for which n≤ 3
for specific crops/products, results obtained in the weighted
meta-analyses are not shown. § Ln ratio = Ln(ORG/CONV × 100 %). ∥ Data
reported for different compounds within the same chemical group were
included in the same meta-analyses. ¶ Outlying data points (where the
MPD between ORG and CONV was more than fifty times greater than the mean
value including the outliers) were removed. ○, MPD calculated using
data included in the standard unweighted meta-analysis; , MPD calculated using data included in the standard weighted meta-analysis; ◆, SMD.
, MPD calculated using data included in the standard weighted meta-analysis; ◆, SMD.Meta-analyses
A total of eight different meta-analyses were undertaken.
The protocols used for the standard weighted and unweighted
meta-analyses were based on the methodologies described by Palupi et al.
(
29
) and Brandt et al.
(
20
), respectively. In Fig. 3,
the results obtained using standard random-effects meta-analysis
weighted by inverse variance and a common random-effects variance
component and unweighted meta-analysis of difference in means are shown.
In addition, six sensitivity analyses were undertaken. Sensitivity
analyses included (1) using data reported for each cultivar or variety
of crops separately and/or (2) treating data reported for different
years in the same publication as separate events in the weighted or
unweighted meta-analyses (see online supplementary Table S5). The
results of the sensitivity analyses are available on the Newcastle
University website (http://research.ncl.ac.uk/nefg/QOF).
Effect sizes for all the weighted meta-analyses were based
on standardised mean differences (SMD) as recommended for studies in
which data obtained by measuring the same parameters on different scales
are included in meta-analyses(
25
,
26
).
Both weighted and unweighted meta-analyses were carried out using the R statistical programming environment(
30
). Weighted meta-analyses, with the SMD as the
basic response variable, were conducted using standard methods and the
open-source ‘metafor’ statistical package(
31
–
34
). A detailed description of the methods and
calculations used is given in the ‘Additional Methods Description’
section in the online supplementary material.
A positive SMD value indicates that the mean concentrations
of the observed compound are greater in the organic food samples, while
a negative SMD indicates that the mean concentrations are higher in the
conventional food samples. The statistical significance of a reported
effect size (i.e. SMDtot) and CI were estimated based on standard methods(
35
) using ‘metafor’(
31
). The influence of potential moderators, such as
crop/food type (fruits, vegetables, cereals, oil seeds and pulses,
herbs and spices, and crop-based compound foods), was additionally
tested using mixed-effect models(
36
) and subgroup analyses.
We carried out tests of homogeneity (Q statistics and I
2 statistics) on all the summary effect sizes. Homogeneity was indicated if I
2 was less than 25 % and the P value for the Q
statistics was greater than 0·010. Funnel plots, Egger tests of funnel
plot asymmetry and fail-safe number tests were used to assess
publication bias(
37
) (see online supplementary Table S13 for further information).
For the unweighted meta-analysis, the ratio of organic means:conventional means (
) expressed as a percentage was ln-transformed, and the values
were used to determine whether the arithmetic average of the
ln-transformed ratios was significantly greater than ln(100), using
resampling(
38
). The reported P values were derived from Fisher's one-sample randomisation test(
39
), and a P< 0·05 was
considered statistically significant. For all composition parameters for
which a statistically significant difference between organic and
conventional food samples was detected in the standard weighted analysis
(analysis 1), forest plots were constructed to show SMD and
corresponding 95 % CI for individual studies and types of foods (see Fig. 4 and online supplementary Figs. S5–S41). In addition, the results of the standard unweighted analyses are shown in Figs. 3 and 4.
) expressed as a percentage was ln-transformed, and the values
were used to determine whether the arithmetic average of the
ln-transformed ratios was significantly greater than ln(100), using
resampling(
38
). The reported P values were derived from Fisher's one-sample randomisation test(
39
), and a P< 0·05 was
considered statistically significant. For all composition parameters for
which a statistically significant difference between organic and
conventional food samples was detected in the standard weighted analysis
(analysis 1), forest plots were constructed to show SMD and
corresponding 95 % CI for individual studies and types of foods (see Fig. 4 and online supplementary Figs. S5–S41). In addition, the results of the standard unweighted analyses are shown in Figs. 3 and 4.
Table S12 (available online) summarises the results of the
standard weighted and unweighted meta-analyses for all the composition
parameters for which no analyses detected significant differences
between organic and conventional products.
MPD were calculated for all parameters for which
significant effects were detected by the standard unweighted and/or
weighted meta-analysis protocols. This was done to facilitate value
judgements regarding the biological importance of the relative effect
magnitudes. A detailed description of the calculations is given in the
‘Additional Methods Description’ section in the online supplementary
material.
We also calculated MPD using only data pairs included in
the weighted meta-analyses to estimate the impact of excluding data for
which no measures of variance were reported on the magnitude of
difference. As the MPD can be expressed as ‘% higher’ in conventional or
organic crops, they provide estimates for the magnitude of composition
differences that are easier to correlate with existing information on
the potential health impacts of changing dietary intake levels for
individual or groups of compounds than the SMD values. The 95 % CI for
MPD were estimated using a standard method(
35
).
For some composition parameters, individual effect sizes
were more than fifty times greater than the pooled effect. This applied
to one effect size each for phenolic acids, flavanones, flavones,
flavonols, carbohydrates, DM and
; four effect sizes for carotenoids and xanthophylls; eight
effect sizes for amino acids; and forty-one effect sizes for volatile
compounds. Such large differences can be considered biologically
implausible, and these ‘outlier’ data pairs were therefore omitted from
the final standard meta-analyses as shown in Figs. 3 and 4 and Tables S10 and S11 (available online).
; four effect sizes for carotenoids and xanthophylls; eight
effect sizes for amino acids; and forty-one effect sizes for volatile
compounds. Such large differences can be considered biologically
implausible, and these ‘outlier’ data pairs were therefore omitted from
the final standard meta-analyses as shown in Figs. 3 and 4 and Tables S10 and S11 (available online).
Data reported for the frequency of occurrence of detectable
pesticide residues (percentage of samples with detectable pesticide
residues) in organic and conventional crops were compared using a
weighted meta-analysis protocol based on the ln-transformed OR(
40
). The formula used to calculate OR is given in
the ‘Additional Methods Description’ section in the online supplementary
material.
An overall assessment of the strength of evidence was made
using an adaptation of the GRADE (Grading of Recommendations,
Assessment, Development and Evaluation) system(
41
).
Results
Analyses were based on data from publications reporting
results from EX (154 papers), CF (116 papers), and BS (fifty-five
papers) or results from more than one type of study (EX, CF and/or BS;
eighteen papers) (see online supplementary Table S3).
Approximately 70 % of all the studies included in the
meta-analyses were carried out in Europe, mainly in Italy, Spain,
Poland, Sweden, the Czech Republic, Switzerland, Turkey, Denmark,
Finland and Germany, with most of the remaining studies being carried
out in the USA, Brazil, Canada and Japan (see online supplementary Table
S3 and Fig. S2). Among the papers included in the meta-analyses, 174
reported comparison data for vegetables and a smaller number reported
data for fruits and cereals (112 and sixty-one, respectively), while
only thirty-seven reported data for other crops/crop-based food products
(e.g. oil seeds and pulses, herbs and spices, and compound foods) (see
online supplementary Table S3). Publications reported data for 907
different composition parameters, of which 182 were included in the
meta-analyses (see online supplementary Tables S6 and S7).
Antioxidant activity
A large number of comparisons were available for
antioxidant activity in organic and conventional crops (160 for the
unweighted meta-analysis and sixty-six for the weighted meta-analysis),
but the authors used a wide range of different methodologies. Both
weighted and unweighted meta-analyses detected a significantly higher
antioxidant activity in organic crops (Fig. 3) and the MPD was 17 (95 % CI 3, 32) % (Fig. 3).
When data reported for fruits and vegetables were analysed
separately, a significant difference was detected for fruits, while only
a trend towards a significant difference (P= 0·06) was observed for vegetables (Fig. 4), although there was no evidence of an interaction.
When data available for specific antioxidant activity
assays were analysed, similar results were obtained for the Trolox
equivalent antioxidant capacity assay with both the standard weighted
and unweighted meta-analyses and for the ferric reducing antioxidant
power and oxygen radical absorbance capacity assays with only the
standard unweighted meta-analysis (Fig. 3).
Antioxidants/(poly)phenolics
The concentrations of secondary metabolites with
antioxidant activity, including a wide range of nutritionally desirable
(poly)phenolics, were also studied in a relatively large number of
studies (see online supplementary Table S8).
For (poly)phenolics, the standard weighted meta-analysis
detected significantly and substantially higher concentrations of total
flavonoids, total phenolic acids, phenolic acids (where data reported
for all individual phenolic acid compounds were included in the same
analysis), flavanones, stilbenes, flavones, flavonols, kaempferol, total
anthocyanins and anthocyanins in organic crops and/or processed foods
made from organic crops. The unweighted meta-analysis yielded similar
results, except for (1) total flavonoids, for which no significant
difference was detected, and (2) flavanones and flavones, for which only
trends towards higher concentrations in organic crops were detected (Fig. 3). The unweighted meta-analysis also detected significantly higher concentrations of chlorogenic acid (5-O-caffeoylquinic acid) in organic crops (Fig. 3). The MPD for most of the compounds were between 18 and 69 % for most of the above-mentioned antioxidant compounds (Fig. 3).
Inclusion of data for which no measures of variance were reported in
the calculation of MPD yielded similar values for phenolic compounds,
phenolic acids, chlorogenic acid, flavones, quercetin, kaempferol and
anthocyanins; higher values for phenolic acids (total), stilbenes and
quercetin-3-rutinoside; and lower values for flavonoids, flavanones and
flavonols (see Fig. 4 and online supplementary Table S9).
When data reported for phenolic compounds, phenolic acids
and flavanones in fruits, vegetables, cereals and/or processed
crop-based foods were analysed separately, significant differences were
detected only for the concentrations of phenolic compounds and phenolic
acids in fruits and a trend towards a significant difference (P= 0·09) was detected for the concentrations of flavanones in fruits (Fig. 4),
although there was no evidence of an interaction. In contrast, when
differences in the concentrations of flavones and flavonols were
analysed separately for fruits, vegetables and cereals, significant
differences were detected for vegetables and cereals, but not for
fruits, with evidence of interactions (Fig. 4).
For all other antioxidant/(poly)phenolic compounds, separate analyses
for different crop types were not possible due to the unavailability of
sufficient data.
Smaller, but statistically significant and biologically
meaningful composition differences were also detected for a small number
of carotenoids and vitamins. Both unweighted and weighted meta-analyses
detected significantly higher concentrations of xanthophylls and l-ascorbic
acid and significantly lower concentrations of vitamin E in organic
crops. Higher concentrations of total carotenoids, carotenoids (where
data reported for all individual phenolic acid compounds were included
in the same analysis) and lutein were also detected by the unweighted
meta-analysis (Fig. 3).
The MPD were 17 (95 % CI 0, 34) % for total carotenoids, 15 (95 % CI
− 3, 32) % for carotenoids (where data reported for all individual
carotenoid compounds were included in the same analysis), 12 (95 % CI
− 4, 28) % for xanthophylls, 5 (95 % CI − 3, 13) % for lutein, 6 (95 %
CI − 3, 15) % for vitamin C and − 15 (95 % CI − 49, 19) % for vitamin E.
Inclusion of data for which no measures of variance were reported in
the calculation of MPD resulted in slightly higher values (see Fig. 4 and online supplementary Table S9).
When data reported for total carotenoids and xanthophylls
in fruits, vegetables, cereals and processed crop-based compound foods
were analysed separately, significantly higher concentrations in organic
samples were detected only for fruits (Fig. 4), with evidence of interactions being detected for carotenoids, but not for xanthophylls.
The meta-analyses did not detect significant differences
for a range of other secondary metabolites with antioxidant activity.
These included some individual carotenoids (α-carotene, lycopene,
β-cryptoxanthin and zeaxanthin), vitamins (α-tocopherol, γ-tocopherol,
vitamin B and vitamin B1), some specific phenolic acids (total hydroxycinnamic acids, caffeic acid, p-coumaric acid, ferulic acid, sinapic acid, 5-O-caffeoylquinic
acid, ellagic acid, gallic acid and salicylic acid), some specific
flavones and flavonols (apigenin, luteolin, myricetin 3-O-glucoside, quercetin 3-O-galactoside, quercetin-3-O-glucoside and quercetin-3-O-malonyl glucoside) and some specific flavanones (naringenin and naringenin (R-enantiomer)).
Macronutrients, fibre and DM content
Both unweighted and weighted meta-analyses detected
significantly higher concentrations of total carbohydrates and
significantly lower concentrations of proteins, amino acids and fibre in
organic crops/crop-based compound foods (Fig. 3). The unweighted meta-analysis also detected significantly higher concentrations of reducing sugars and DM in organic crops (Fig. 4).
The MPD were 25 (95 % CI 5, 45) % for total carbohydrates, 11 (95 % CI
2, 20) % for carbohydrates (where data reported for all individual
phenolic acid compounds were included in the same analysis), 7 (95 % CI
4, 11) % for reducing sugars, − 15 (95 % CI − 27, − 3) % for proteins,
− 11 (95 % CI − 14, − 8) % for amino acids, 2 (95 % CI − 1, 6) % for DM
and − 8 (95 % CI − 14, − 2) % for fibre. Inclusion of data for which no
measures of variance were reported in the calculation of MPD resulted in
similar values for carbohydrates, proteins, DM and fibre; higher values
for reducing sugars; and lower values for carbohydrates (total) and
amino acids (see Fig. 4 and online supplementary Table S9).
When data reported for proteins and amino acids in
vegetables, cereals and/or processed crop-based foods were analysed
separately, significant differences were detected for cereals and
processed crop-based foods, but not for vegetables (Fig. 4),
although there was no evidence of an interaction. Also, when data
reported for carbohydrates in vegetables, fruits and cereals were
analysed separately, no significant effects could be detected in their
concentrations (Fig. 4).
Toxic metals, nitrogen, nitrate, nitrite and pesticides
Both weighted and unweighted meta-analyses detected
significantly lower concentrations of the toxic metal Cd and total N in
organic crops, while lower concentrations of
and
in organic crops were detected only by the unweighted meta-analysis (Fig. 3). The MPD were − 48 (95 % CI − 112, 16) % for Cd, − 10 (95 % CI − 15, − 4) % for N, − 30 (95 % CI − 144, 84) % for
and − 87 (95 % CI − 225, 52) % for
(Fig. 3).
and
in organic crops were detected only by the unweighted meta-analysis (Fig. 3). The MPD were − 48 (95 % CI − 112, 16) % for Cd, − 10 (95 % CI − 15, − 4) % for N, − 30 (95 % CI − 144, 84) % for
and − 87 (95 % CI − 225, 52) % for
(Fig. 3).
Inclusion of data for which no measures of variance were reported in the calculation of MPD resulted in similar values for N,
,
and Cd (see Fig. 4 and online supplementary Table S9).
,
and Cd (see Fig. 4 and online supplementary Table S9).
When data reported for N and Cd concentrations in fruits,
vegetables and cereals were analysed separately, significant differences
were detected for cereals, but not for vegetables and/or fruits (Fig. 4), although there was no evidence of an interaction.
For the toxic metals As and Pb, no significant differences
could be detected in their concentrations between organic and
conventional crops in the meta-analyses (see online supplementary Table
S12).
The standard meta-analyses showed that the frequency of
occurrence of detectable pesticide residues was four times higher in
conventional crops (46 (95 % CI 38, 55) %) than in organic crops (11
(95 % CI 7, 14) %) (Fig. 5).
Significantly higher frequencies of occurrence of pesticide residues in
conventional crops were also detected when data reported for fruits,
vegetables and processed crop-based foods were analysed separately (Fig. 5).
Conventional fruits had a higher frequency (75 (95 % CI 65, 85) %) of
occurrence of pesticide residues than vegetables (32 (95 % CI 22, 43) %)
and crop-based compound foods (45 (95 % CI 25, 65) %), while
contamination rates were very similar in the different organic crop
types. This resulted in significant differences in the OR for different
crop types (Fig. 5).
Fig. 5 Results of the standard
weighted meta-analysis comparing ln OR for the frequency of occurrence
of pesticide residues (percentage of positive samples) in organic and
conventional crops. A mixed-effect model with crop/product group as a
moderator was used. OR, ln OR for each product group (◆); ORG, organic
food samples; CONV, conventional food samples; n,
number of data points included in the meta-analyses. Values are odds
ratios, with 95 % confidence intervals represented by horizontal bars.
* P value < 0·05 indicates a significant difference between ORG and CONV. † Crops/product groups for which n≤ 3 were removed from the plots. ‡ Compound foods.
Other minerals
For most of the minerals (including many plant marco- and
micronutrients), the meta-analyses could not detect significant
composition differences between organic and conventional crops (see
online supplementary Table S12). However, for a small number of
minerals, differences in composition were identified by both weighted
and unweighted meta-analyses, which detected significantly lower
concentrations of Cr and Sr ( − 59 (95 % CI − 147, 30) % and − 26 (95 %
CI − 45, − 6) %, respectively), but significantly higher concentrations
of Mo and Rb (65 (95 % CI 26, 105) % and 82 (95 % CI 6, 157) %,
respectively) in organic crops. Also, lower concentrations of Mn ( − 8
(95 % CI − 13, − 3) %) and higher concentrations of Ga and Mg in organic
crops (57 (95 % CI − 122, 8) % and 4 (95 % CI − 5, 13) %, respectively)
were detected only by the weighted meta-analysis, while slightly higher
concentrations of Zn (5 (95 % CI − 6, 15) %) in organic crops were only
detected by the unweighted meta-analysis (see online supplementary
Table S11). As differences for Zn and Mg were relatively small and as
there is limited information about potential health impacts associated
with changing intake levels of either mineral (Cr, Ga, Mo, Sr and Mo),
more detailed results are provided only in the online supplementary
material.
Effects of crop type/species/variety, study type and other sources of variation
Heterogeneity was extremely high (I
2>75 %) for most of the composition parameters, with I
2 ranging from 76 % for ascorbic acid to 100 % for carotenoids and DM (Fig. 3). The only exceptions were vitamin E, reducing sugars, fibre and
, for which the small number of studies and/or high within-study
variability limited the ability to distinguish heterogeneity between the
effects.
, for which the small number of studies and/or high within-study
variability limited the ability to distinguish heterogeneity between the
effects.
Strong or moderate funnel plot asymmetry consistent with a
publication bias was detected for approximately half of the parameters.
However, it is not possible to definitively attribute discrepancies
between large precise studies and small imprecise studies to publication
bias, which remains strongly suspected rather than detected where
asymmetry is severe (see Table 1 and online supplementary Table S13).
Table 1 GRADE (Grading of
Recommendations, Assessments, Development and Evaluation) assessment of
the strength of evidence for standard weighted meta-analysis for
parameters included in Fig. 3 (Standardised mean difference values (SMD) and 95 % confidence intervals)
FRAP, ferric reducing antioxidant potential; ORAC, oxygen
radical absorbance capacity; TEAC, Trolox equivalent antioxidant
capacity.
*Study quality was considered
low because of high risks of bias and potential for confounding.
However, we considered large effects to mitigate this sensu GRADE; large effects were defined as >20 %, moderate effects as 10–20 % and small as < 10 %.
†Inconsistency was based on the measure of heterogeneity and the consistency of effect direction sensu GRADE.
‡Precision was based on the
width of the pooled effect CI and the extent of overlap in the
substantive interpretation of effect magnitude sensu GRADE.
§Publication bias was assessed
using visual inspection of funnel plots, Egger tests, two fail-safe
number tests, and trim and fill (see online supplementary Table S13).
Overall publication bias was considered high when indicated by two or
more methods, moderate when indicated by one method, and low when
indicated by none of the methods. The overall quality of evidence was
then assessed across domains as in standard GRADE appraisal.
∥Outlying data pairs (where the
mean percentage difference between the organic and conventional food
samples was over fifty times higher than the mean value including
outliers) were removed.
When meta-analysis results obtained from different study
types (BS, CF and EX) were compared, similar results were obtained for
most of the composition parameters included in Fig. 3
(see online supplementary Figs. S3 and S4). However, there was
considerable variation between results obtained for different crop
types, crop species, and/or studies carried out in countries with
contrasting pedo-climatic and agronomic background conditions (see Fig. 4 and online supplementary Figs. S5–S41).
Non-weighted MPD were calculated to aid in the biological
interpretation of effect size magnitude where either the weighted or
unweighted meta-analysis had identified statistically significant
results. For many parameters, MPD based on all the available data
produced values very similar to those calculated using only data for
which measures of variance were reported ( = those used for the weighted
meta-analysis; Fig. 3). However, for other parameters (flavonoids, total phenolic acids, flavanones, rutin, l-ascorbic acid, reducing sugars and Cd), inclusion criteria had a large effect on the MPD.
Also, when the calculated MPD were superimposed onto SMD
(with 95 % CI) results at an appropriate scale ( − 100 to +100 for MPD
and − 5 to +5 for SMD), a reasonable match was observed, with MPD for
most of the compounds being present within the 95 % CI for SMD (Fig. 3).
However, for some parameters (Trolox equivalent antioxidant capacity,
total phenolic acids, stilbenes, rutin, total carotenoids, l-ascorbic acid, vitamin E, reducing sugars, proteins,
,
and Cd), MPD were outside the 95 % CI of SMD, and therefore these should be seen as less reliable.
,
and Cd), MPD were outside the 95 % CI of SMD, and therefore these should be seen as less reliable.
For the composition parameters included in Fig. 3,
sensitivity analyses, which were based on different inclusion criteria
and data-handling methods, yielded results broadly similar to those
yielded by the standard weighted and unweighted meta-analyses.
The overall assessment of the strength of evidence using an adapted GRADE(
41
) approach highlighted uncertainties in the
evidence base, but the overall strength of evidence was moderate or high
for the majority of parameters for which significant differences were
detected (see Table 1 and online supplementary Table S13).
Discussion
The results of meta-analyses of the extensive data set of
343 peer-reviewed publications indicated that organic crops and
processed crop-based foods have a higher antioxidant activity and
contain higher concentrations of a wide range of nutritionally desirable
antioxidants/(poly)phenolics, but lower concentrations of the
potentially harmful, toxic metal Cd. For plant secondary metabolites,
this confirms the results of the meta-analyses carried out by Brandt et al.
(
20
), which indicated that there are significant
composition differences between organic and conventional crops for a
range of nutritionally relevant compounds. However, it contradicts the
results of the systematic reviews/meta-analyses by Dangour et al.
(
19
) and Smith-Spangler et al.
(
21
), which indicated that there are no significant
composition differences between organic and conventional crops. The main
reason for the inability of previous studies to detect composition
differences was probably the highly limited number of studies/data sets
available or included in analyses by these authors, which would have
decreased the statistical power of the meta-analyses.
In addition, most of the previous studies did not use
weighted meta-analyses based on SMD. This approach is recommended when
combining data from studies that measure the same parameter (e.g. the
major phenolic compounds found in different crops), but use different
scales(
25
,
26
,
29
). In the study carried out by Dangour et al.
(
19
), published data from (1) surveys in which the
organic samples were produced to ‘biodynamic-organic’ standards and (2)
field experiments investigating associations between organic and
conventional production protocols and crop composition were not included
in the meta-analyses. This would have further reduced the number of
data sets and sensitivity of meta-analyses and contributed to the lack
of significant composition differences being detected. In the
meta-analyses carried out in the present study, ‘biodynamic-organic’
data sets were treated as organic, as biodynamic standards comply with
the legal European Union organic farming standards. Data from
comparative field experiments were also included, as controlled
experimental studies are less affected by confounding factors (e.g.
contrasting soil and climatic and agronomic background conditions
between farms that supplied organic and conventional samples) than farm
and retail surveys. The reason for excluding field experiments carried
out in the study of Dangour et al.
(
19
) is that in the field experiments the organic
plots were not certified according to organic farming standards. In the
meta-analyses carried out in the present study, field experiments
investigating associations between organic and conventional agronomic
practices/protocols and crop composition were included, as the crop
management practices rather than the certification process were assumed
to affect crop performance and composition.
The finding of a four times higher frequency of occurrence
of pesticide residues in conventional crops confirms the results of the
study of Smith-Spangler et al.
(
21
), in which a very similar set of studies (nine of the ten publications used in the present study) were used for analysis.
The potential (1) nutritional benefits of higher
concentrations of antioxidant/(poly)phenolics in organic crops, (2)
risks associated with potentially harmful pesticide residues, Cd,
and
, and (3) agronomic factors responsible for composition differences are discussed in more detail below.
and
, and (3) agronomic factors responsible for composition differences are discussed in more detail below.Antioxidants/(poly)phenolics
Among the composition differences detected by the
meta-analyses carried out in the present study, the higher antioxidant
activity and higher concentrations of a wide range of
antioxidants/(poly)phenolics found in organic crops/crop-based foods may
indicate the greatest potential nutritional benefits. Based on the
differences reported, results indicate that a switch from conventional
to organic crop consumption would result in a 20–40 % (and for some
compounds more than 60 %) increase in crop-based
antioxidant/(poly)phenolic intake levels without a simultaneous increase
in energy, which would be in line with the dietary recommendations(
16
,
17
). This estimated magnitude of difference would
be equivalent to the amount of antioxidants/(poly)phenolics present in
one to two of the five portions of fruits and vegetables recommended to
be consumed daily and would therefore be significant/meaningful in terms
of human nutrition, if information linking these plant secondary
metabolites to the health benefits associated with increased fruit,
vegetable and whole grain consumption is confirmed(
16
–
18
).
However, it is important to point out that there is still a
lack of knowledge about the potential human health impacts of
increasing antioxidant/(poly)phenolic intake levels and switching to
organic food consumption. For example, there are still gaps in the
understanding of the (1) uptake, bioavailability and metabolism of
(poly)phenolics after ingestion and (2) exact compounds/molecules and
modes of action responsible for health benefits(
16
). Also, it is important to consider that most of
the human dietary intervention studies on associations between
antioxidant/(poly)phenolic intake and health indicators were based on
the comparison of standard diets with diets in which the amount of
specific (poly)phenolic-rich foods (e.g. cocoa, red wine, tea/coffee,
berries, citrus and nuts) was high(
16
,
17
).
There are, to our knowledge, only two human dietary
intervention studies in which contrasting antioxidant/(poly)phenolic
intake levels were generated by providing diets based on conventional
and organic crops; both studies focused on assessing antioxidant status
in humans and were inconclusive with respect to the identification of
potential health impacts of organic food consumption(
21
,
42
,
43
). However, there are several animal dietary
intervention studies that have identified significant associations
between organic feed consumption and animal growth and physiological
(including immune and endocrine) parameters and/or biomarkers of health
when compared with conventional feed consumption(
44
,
45
). Among these studies, one recent factorial
animal study has gone one step further and assessed associations between
contrasting crop fertilisation and crop protection protocols used in
conventional and organic farming systems and (1) the composition
(including (poly)phenolic content) of crops/compound feeds made from
crops and (2) the growth, physiological, immunological and hormonal
parameters of rats that consumed these feeds(
46
). With respect to composition differences, the
study yielded results similar to those of the meta-analyses carried out
in the present study. For example, rat feeds produced from organic crops
had lower concentrations of proteins and Cd, but higher concentrations
of polyphenols and the carotenoid lutein. The study also demonstrated
that composition differences were mainly linked to contrasting
fertilisation regimens (green and animal manures v.
mineral fertiliser inputs). The consumption of feeds made from organic
crops by the rats resulted in higher levels of body protein, body ash,
leucocyte count, plasma glucose, leptin, insulin-like growth factor 1,
corticosterone, and IgM, and spontaneous lymphocyte proliferation, but
lower levels of plasma IgG, testosterone and mitogen-stimulated
proliferation of lymphocytes(
46
). Redundancy analysis identified total
polyphenol concentrations in feeds as the strongest driver for the
physiological/endocrinological parameters assessed in rats. This
suggests that a switch from conventional to organic crop consumption may
have impacts similar to those of an increase in the intake of foods
with high antioxidant/(poly)phenolic contents. This hypothesis would
merit further exploration in animal and human dietary intervention
studies.
Many of the antioxidants, including (poly)phenolics, found
in higher concentrations in organic crops are known to be produced by
plants in response to abiotic (e.g. wounding and heat, water and
nutrient stress) and biotic (pest attacks and disease) stress and form
part of the plants' constitutive and inducible resistance mechanisms to
pests and diseases(
47
–
49
). Therefore, higher concentrations of
(poly)phenolics in organic crops may be due to higher incidence/severity
of pest and disease damage, causing enhanced (poly)phenolic production
as part of the inducible plant resistance response. The differences in
antioxidant concentrations between organic and conventional crops may
therefore have been due to contrasting pest and disease damage and/or
fertilisation intensity. However, there are, to our knowledge, no sound
published data/evidence for a causal link between higher pest/disease
incidence/severity and antioxidant/(poly)phenolic concentrations in
organic crops. In contrast, there is increasing evidence that
differences in fertilisation regimens between organic and conventional
production systems (and, in particular, the non-use of high mineral N
fertiliser inputs) are significant drivers for higher (poly)phenolic
concentrations in organic crops(
20
,
49
–
52
). For example, Sander & Heitefuss(
50
) reported that increasing mineral N
fertilisation resulted in reduced concentrations of phenolic resistance
compounds in wheat leaves and increased severity of foliar disease
(powdery mildew). Similarly, a review by Rühmann et al.
(
51
) describes the negative correlations between N
fertilisation/supply-driven shoot growth and concentrations of
phenylpropanoids and apple scab resistance in young leaves in apple
trees(
51
). In tomato, deficiency of both N and P was found to be linked to flavonol accumulation in plant tissues(
52
). More recently, Almuayrifi(
49
) has demonstrated that the non-use of synthetic
pesticides and fungicides has no effect on phenolic acid and flavonoid
concentrations and profiles in wheat, but that the use of standard,
conventional mineral (NPK) fertiliser regimens is associated with
significantly lower phenolic acid and flavonoid concentrations in wheat
leaves compared with organic wheat crops fertilised with green and
animal manures only. The variability in relative differences in
antioxidant/(poly)phenolic concentrations found between studies and
crops may therefore at least partially be explained by variability in
the fertilisation protocols in both the organic and non-organic systems
compared. The finding in the present study that organic crops have
significantly lower N,
and
concentrations would support the theory that differences in
antioxidant/(poly)phenolic concentrations between organic and
conventional crops are driven by contrasting N supply patterns. This
view is supported by previous studies that have suggested that under
high N availability, plants allocate carbohydrates from photosynthesis
to primary metabolism and rapid growth while producing less amounts of
secondary metabolites involved in defence(
51
).
and
concentrations would support the theory that differences in
antioxidant/(poly)phenolic concentrations between organic and
conventional crops are driven by contrasting N supply patterns. This
view is supported by previous studies that have suggested that under
high N availability, plants allocate carbohydrates from photosynthesis
to primary metabolism and rapid growth while producing less amounts of
secondary metabolites involved in defence(
51
).
However, additional research is required to gain a more
detailed understanding of the relative contribution of fertilisation and
crop protection regimens and disease and pest prevalence/severity to
the expression of constitutive and inducible resistance mechanisms in
different organically managed crop plants(
50
).
Cadmium and pesticide residues
Cd is a highly toxic metal and one of the only three toxic
metal contaminants (the other two being Pb and Hg) for which the
European Commission has set maximum residue levels (MRL) in foods(
53
). Cd accumulates in the human body (especially
in the liver and kidneys) and therefore dietary Cd intake levels should
be kept as low as possible(
53
). The on average 48 % lower Cd concentrations
found in organic crops/crop-based foods in the meta-analyses carried out
in the present study are therefore desirable, although the exact health
benefits associated with reducing Cd intake levels via a switch to
organic food consumption are difficult to estimate. Similar to the
results of the present study, a recent literature review by
Smith-Spangler et al.
(
21
) has also reported that of the seventy-seven
comparative data sets (extracted from fifteen publications), twenty-one
indicated significantly lower and only one significantly higher Cd
concentrations in organic foods. Differences in Cd contamination levels
between organic and conventional winter wheat have recently been shown
to be mainly linked to differences in fertilisation regimens (especially
the high mineral P inputs used in conventional farming systems),
although contrasting rotation designs also contributed to differences in
Cd concentrations between organic and conventional wheat(
7
). A range of other soil (e.g. pH) and agronomic (e.g. liming) factors are known to affect Cd concentrations in crops(
54
), and these may explain the variability in results between individual comparative studies, crop species and crop types (see Fig. 4 and online supplementary Figs. S4 and S22).
The present study demonstrated that the prohibition of
synthetic chemical pesticide use under organic farming standards results
in a more than 4-fold reduction in the number of crop samples with
detectable pesticide residues. This supports previous studies that have
concluded that organic food consumption can reduce exposure to pesticide
residues(
21
–
23
). The considerably higher frequency of
occurrence of detectable residues in conventional fruits (75 %) than in
vegetables (32 %) may indicate higher levels of crop protection inputs
being used in fruit crops, but could also have been due to the use of
more persistent chemicals, different sprayer technologies used and/or
pesticide applications being made closer to harvest. The finding of
detectable pesticide residues in a proportion (about 11 %) of organic
crop samples may have been due to cross-contamination from neighbouring
conventional fields, the continued presence of very persistent
pesticides (e.g. organochlorine compounds) in fields or perennial crop
tissues from past conventional management, and/or accidental or
fraudulent use of prohibited pesticides in organic farms.
Pesticide residues that are below the MRL set by the European Commission(
55
,
56
) are considered by regulators not to pose risk
to consumers or the environment, as they are significantly lower than
concentrations for which negative health or environmental impacts can be
detected in the regulatory pesticide safety testing carried out as part
of the pesticide approval process(
55
). However, a significant number of crop samples
included in the regulatory European Food Safety Authority pesticide
residue monitoring in Europe are still found to contain pesticide
residues above the MRL(
57
). For example, in recent European Food Safety
Authority surveys, pesticide residues above the MRL have been found in
6·2 % of spinach, 3·8 % of oat, 3·4 % of peach, 3·0 % of orange, 2·9 %
of strawberry and lettuce, 2·8 % of table grape and 2·7 % of apple
samples analysed(
57
). There is still scientific controversy about
the safety of some currently permitted pesticides (e.g. organophosphorus
compounds) even at levels below the MRL and complex mixtures of
pesticides, as additive/synergistic effects of pesticide mixtures have
been documented and safety testing of pesticide mixtures is currently
not required as part of the regulatory pesticide approval process(
58
–
60
). Similar to Cd, the lower risk of exposure to
pesticide residues can be considered desirable, but potential health
benefits associated with reducing pesticide exposure via a switch to
organic food consumption are impossible to estimate.
It should be pointed out that (1) there are only eleven
studies in which the frequencies of occurrence of pesticide residues
were compared, (2) eight of these studies focused on only one crop
species, (3) no comparative studies for cereals, oilseeds and pulses
were identified in the literature review, and (4) the data available did
not allow scientifically robust comparisons of the concentrations of
pesticides. Therefore, it is important to carry out further studies to
improve our understanding of differences in the frequency of occurrence
and concentrations of pesticide residues between organic and
conventional crops.
Proteins, amino acids, nitrogen and nitrate/nitrite
The concentrations of proteins, amino acids and N (which
are known to be positively correlated in plants) were found to be lower
in organic crops, and this is consistent with the results of previous
studies that have linked lower protein concentrations to lower N inputs
and N availability in organic crop production systems(
61
,
62
). The nutritional significance/relevance of
slightly lower protein and amino acid concentrations in organic crops to
human health is likely to be low, as European and North American diets
typically provide sufficient or even excessive amounts of proteins and
essential amino acids. Also, while some studies concluded that protein
content in most European and North American diets is too high and that
this contributes to the increasing incidence of diabetes and obesity(
63
), other studies reported that increasing protein intake levels may be a strategy to prevent obesity(
64
). Therefore, the lower protein and amino acid
concentrations found in organic foods are unlikely to have a significant
nutritional or health impact.
The higher
and
concentrations in conventional crops are also thought to be linked to high mineral N inputs, as both
and
are known to accumulate in plants under high-mineral N input regimens(
65
). The higher
concentrations in conventional crops/crop-based foods are
nutritionally undesirable, as they have been described to be risk
factors for stomach cancer and methaemoglobinaemia in humans(
65
). However, while increasing dietary
intake levels is widely considered to be potentially harmful for
human health, there is still controversy about the potential health
impacts of crop-based dietary
intake(
65
–
67
).
and
concentrations in conventional crops are also thought to be linked to high mineral N inputs, as both
and
are known to accumulate in plants under high-mineral N input regimens(
65
). The higher
concentrations in conventional crops/crop-based foods are
nutritionally undesirable, as they have been described to be risk
factors for stomach cancer and methaemoglobinaemia in humans(
65
). However, while increasing dietary
intake levels is widely considered to be potentially harmful for
human health, there is still controversy about the potential health
impacts of crop-based dietary
intake(
65
–
67
).Effects of crop type/species/variety, study type and other sources of variation
One of the main challenges to interpreting comparisons of
organic and inorganic food production systems is the high heterogeneity
arising from combinations of (1) crops, crop types and/or crop-based
foods, (2) countries, and/or (3) pedo-climatic and agronomic background
conditions. As has been mentioned in previous reviews(
19
–
21
), pooling diverse information was necessary,
because for most of the composition parameters, the number of published
studies available was not sufficient to carry out separate meta-analyses
for specific countries/regions and crop types and species.
Consequently, heterogeneity was extremely high (I
2>75 %) for most of the composition parameters for which significant differences were detected.
For many composition parameters, the method of synthesis
did not have large effects on results, in terms of both statistical
significance and the magnitude of relative difference between organic
and conventional crops. This indicates that there is now a sufficiently
large body of published information to identify differences that are
relatively consistent across study types, crops, and pedo-climatic and
agronomic environments. Therefore, for these parameters, future studies
should focus on increasing our understanding of the underlying
agronomic, pedo-climatic and crop genetic factors responsible for
composition differences between organic and conventional crops.
For other composition parameters (e.g. ferric reducing
antioxidant power, oxygen radical absorbance capacity, Trolox equivalent
antioxidant capacity, and levels of flavonoids, stilbenes, total
carotenoids, l-ascorbic acid, proteins,
and Cd), differences in methods had a large impact in terms of
both significant effects being detected and/or estimates of the
magnitude of difference based on MPD and SMD. For these compounds,
additional high-quality studies (that report measures of variance) are
required to increase the power of weighted meta-analyses.
and Cd), differences in methods had a large impact in terms of
both significant effects being detected and/or estimates of the
magnitude of difference based on MPD and SMD. For these compounds,
additional high-quality studies (that report measures of variance) are
required to increase the power of weighted meta-analyses.
Overall assessment of the strength of evidence for
antioxidant/(poly)phenolic parameters indicated high or moderate
reliability for thirteen of the nineteen parameters and moderate
reliability for Cd. This supports the conclusion that future research
would likely be confirmatory.
In contrast to previous literature reviews(
19
–
21
), the larger number of studies now available
allowed separate meta-analyses to be carried out for different crop
types (e.g. fruits, vegetables and cereals), but only for a limited
number of composition parameters. This demonstrates that there is
variation between crop types with respect to (1) whether the production
system has a significant effect and/or (2) the magnitude of difference
between organic and conventional crops, although sample sizes remain
insufficient to detect interactions between crop types in many cases.
The present study also identified variation between studies
(1) carried out in countries with different pedo-climatic conditions
and agronomic protocols (e.g. rotation designs, irrigated or
non-irrigated crop production, and level and type of animal manures
used) and/or (2) focused on different crop species. This is not
surprising as both genetic and environmental/agronomic factors are known
to affect the concentrations of N,
,
, proteins, sugars, antioxidants/(poly)phenolics, Cd and pesticides in crops(
7
,
9
–
12
,
20
,
47
–
52
,
62
). However, due to the lack of detailed
information on agronomic and pedo-climatic background conditions in most
of the available literature, it is currently not possible to quantify
the relative contribution of genetic and environmental/agronomic sources
of variation.
,
, proteins, sugars, antioxidants/(poly)phenolics, Cd and pesticides in crops(
7
,
9
–
12
,
20
,
47
–
52
,
62
). However, due to the lack of detailed
information on agronomic and pedo-climatic background conditions in most
of the available literature, it is currently not possible to quantify
the relative contribution of genetic and environmental/agronomic sources
of variation.
The unweighted MPD were calculated to provide an estimate
of the magnitude of difference that is meaningful when considering
nutritional/health impacts of changes in crop composition. However, care
should be taken when interpreting MPD values, as they do not take
variability in the precision of individual studies into account(
25
) and provide less precise estimates of effect than weighted estimates.
However, there is now evidence from a large number of
quality studies that consistently show that organic production systems
result in crops/crop-based compound foods with higher concentrations of
antioxidants/(poly)phenolics and lower concentrations of Cd and
pesticide residues compared with conventional production systems. There
is little uncertainty surrounding this overall result, but further
research is required to quantify more accurately the relative impacts of
(1) crop types, species, and varieties/cultivars/hybrids and (2)
agronomic and pedo-climatic background conditions on the relative
difference between organic and conventional crop composition.
The need for use of standardised protocols for comparative food composition studies
The present study identified deficiencies in a large
proportion of the published studies. These included a lack of
standardised measurements and a lack of reporting (and, in particular,
the non-reporting of measures of variability and/or replication) for
many composition parameters, and there was evidence of duplicate or
selective reporting of data collected in experiments, which may lead to
publication bias. Particularly, there is a lack of studies comparing
pesticide residue levels in organic and conventional crops, and there
has been very little effort taken to re-analyse and then publish
available comparative data from food surveillance surveys (e.g. the
regular pesticide residue and food composition surveys carried out by
the European Food Safety Authority and national agencies in Europe and
elsewhere). Also, in many studies, there was a lack of detailed
information on (1) the geographical origin of samples in retail surveys
and (2) agronomic (e.g. rotation, fertilisation, tillage and irrigation
regimens), pedo-climatic and crop genetic backgrounds (in farm surveys
and field experiments), which would allow potential sources of variation
to be investigated.
Not all studies included in the meta-analyses used
certified reference materials as a quality assurance measure for the
accuracy of estimates of concentrations of compounds in crops. This is
unlikely to have affected the estimates of relative differences between
organic and conventional crops, as the same extraction and analytical
methods were used for organic and conventional samples in all the
studies included in the meta-analyses in the present study. However,
data from studies that did not use reference materials are less reliable
when used to estimate the concentrations of nutritionally relevant
compounds in crops and total dietary intake levels of such compounds in
crop-based foods.
Therefore, it is important to develop guidelines for
studies comparing the impacts of agronomic practices on crop/food
composition to minimise heterogeneity and/or allow agronomic,
environmental and crop genetic drivers to be used as covariates in
analyses.
The need for dietary intervention/cohort studies to identify health impacts
A recent review by Smith-Spangler et al.
(
21
) has analysed the results of fourteen studies in
which the effects of organic and conventional food (both crop and
livestock product) consumption on clinical outcomes (e.g. allergic
symptoms and Campylobacter infections) and
health markers (e.g. serum lipid and vitamin concentrations) were
studied. However, they concluded that the currently available data do
not allow clear trends with respect to health markers and outcomes to be
identified. Therefore, there is an urgent need for well-controlled
human intervention and/or cohort studies to identify/quantify potential
human health impacts of organic v. conventional food consumption.
Diet composition may have an effect on the relative impact
of switching from conventional to organic food consumption, and this
should be considered in the design of such studies. For example, the
relative impact of switching from conventional to organic food
consumption could be expected to be smaller for diets with high amounts
of (poly)phenolic-rich foods.
Supplementary material
To view supplementary material for this article, please visit http://dx.doi.org/10.1017/S0007114514001366
Acknowledgements
The authors thank Lord Peter Melchett (Policy Director of
the Soil Association, Bristol, UK, and an organic farmer), Professor Dr
Juha Helenius (Professor of Agroecology, University of Helsinki,
Finland) and Teresa Jordon (Nafferton Ecological Farming Group office
manager, Newcastle University) for critically reviewing/editing the
manuscript. Lord Peter Melchett, the Policy Director of the Soil
Association, was invited to critically review the manuscript to (1)
ensure that the authors had covered all the information/publications
available to the main UK Organic Farming sector body and (2) obtain
feedback on the main results and conclusions reported in the article.
Lord Melchett did not suggest any major revisions to the manuscript.
The authors are grateful to the European Community for
funding through financial participation under the Sixth Framework
Programme for Research, Technological Development and Demonstration
Activities for the Integrated Project QUALITYLOWINPUTFOOD,
FP6-FOOD-CT-2003-506358. They are also grateful to the Sheepdrove Trust
for the ‘Meta-analyses of data on composition of organic and
conventional foods’ for providing financial and technical support. The
Sheepdrove Trust supports independent R&D underpinning the
development of organic and sustainable farming and food systems.
Financial support was provided by the Trust without conditions, and the
Trust had no influence on the design and management of the research
project and the preparation of publications from the project.
The authors' contributions are as follows: M. B. (an animal
and food scientist) designed the database, carried out many of the
meta-analyses and contributed to the writing of the manuscript; D. S.-T.
(a nutritionist) carried out a major part of the literature search and
extraction and contributed to the writing of the manuscript; N. V. (a
crop scientist) contributed to the literature search (especially for
perennial and Mediterranean crops) and the preparation of the
manuscript; C. S. (a human nutritionist) contributed to the design of
the study, the discussion of potential health impacts of composition
differences and the critical review of the manuscript; R. S. (an
environmental modeller and data analyser) helped to design the
literature search and database storage and helped to design and provided
guidance for the meta-analyses used; G. B. S. (a research synthesis
methodologist specialising in meta-analytical approaches) contributed to
and provided advice on the additional analyses carried out in response
to referees' recommendations; C. B. (an agronomist specialising on
organic production systems) helped with the literature review
(especially with respect to studies carried out in North and South
America) and the preparation/review of the manuscript; B. B. (an
agricultural microbiologist) contributed to the literature search, the
critical review of the manuscript and the discussion related to the
mechanisms for higher antioxidant concentrations in organic crops; E. M.
(a plant pathologist) helped with the literature search and the
critical review of the manuscript, in particular, with respect to
interactions between antioxidant concentrations and crop resistance; C.
G. (a plant pathologist/crop agronomist) helped with the literature
search (especially with respect to Mediterranean crops) and the critical
review of the manuscript; J. G.-O. (a human nutritionist) contributed
to the literature review and the discussion of potential health impacts
of composition differences identified in the meta-analyses; E. R. (a
human nutritionist) helped with the literature review and the critical
revision of the manuscript, especially with respect to human
intervention studies focused on the health impacts of organic food
consumption; K. S.-S. (an animal nutritionist/physiologists) contributed
to the literature review and the critical revision of the manuscript,
especially with respect to animal dietary intervention studies focused
on the physiological and health impacts of organic feed consumption; R.
T. (a human nutritionist) helped with the literature review and the
critical revision of the manuscript, especially with respect to studies
carried out in Scandinavian countries; D. J. (an agronomist specialising
on organic production systems) contributed to the literature review
(especially with respect to studies carried out in Eastern and Central
European countries) and the preparation/review of the manuscript; U. N.
(head of Europe's largest organic farming institutes) helped with the
literature review (especially with respect to studies linking mineral
nutrient supply and antioxidant concentrations in crops) and the
critical review of the manuscript; P. N. (a plant pathologist/crop
agronomist) contributed to the interpretation of data and the critical
review of the manuscript; C. L. (an agronomist specialising on
agricultural production system design and the study of interactions
between agronomic practices, and food quality and safety) had primary
responsibility for the design of the study, the management of the
research project and the preparation of the manuscript.
Conflict of interest: the senior author of the paper, C.
L., owns farm land in Germany that is managed according to conventional
farming standards and a smallholding in Greece that is managed according
to organic farming standards.
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