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Historical changes in the mineral content of fruits and vegetables

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Abstract

Implies that a balance of the different essential nutrients is necessary for maintaining health. The eight minerals that are usually analysed are Na, K, Ca, Mg, P, Fe, Cu, Zn. A comparison of the mineral content of 20 fruits and 20 vegetables grown in the 1930s and the 1980s (published in the UK Government’s Composition of Foods tables) shows several marked reductions in mineral content. Shows that there are statistically significant reductions in the levels of Ca, Mg, Cu and Na in vegetables and Mg, Fe, Cu and K in fruit. The only mineral that showed no significant differences over the 50 year period was P. The water content increased significantly and dry matter decreased significantly in fruit. Indicates that a nutritional problem associated with the quality of food has developed over those 50 years. The changes could have been caused by anomalies of measurement or sampling, changes in the food system, changes in the varieties grown or changes in agricultural practice. In conclusion recommends that the causes of the differences in mineral content and their effect on human health be investigated.
[ 207]
British Food Journal
99/6 [1997] 207–211
© MCB University Press
[ISSN 0007-070X]
Historical changes in the mineral content of fruits
and vegetables
Anne-Marie Mayer
Independent Researcher, Devon, UK
Implies that a balance of the
different essential nutrients is
necessary for maintaining
health. The eight minerals
that are usually analysed are
Na, K, Ca, Mg, P, Fe, Cu, Zn.
A comparison of the mineral
content of 20 fruits and 20
vegetables grown in the
1930s and the 1980s (pub-
lished in the UK Government’s
Composition of Foods
tables)
shows several marked reduc-
tions in mineral content.
Shows that there are statisti-
cally significant reductions in
the levels of Ca, Mg, Cu and
Na in vegetables and Mg, Fe,
Cu and K in fruit. The only
mineral that showed no sig-
nificant differences over the
50 year period was P. The
water content increased
significantly and dry matter
decreased significantly in
fruit. Indicates that a nutri-
tional problem associated
with the quality of food has
developed over those 50
years. The changes could
have been caused by anom-
alies of measurement or
sampling, changes in the food
system, changes in the vari-
eties grown or changes in
agricultural practice. In
conclusion recommends that
the causes of the differences
in mineral content and their
effect on human health be
investigated.
The purpose of this paper is to address the
question: has the nutritional quality (particu-
larly essential mineral content) of fruits and
vegetables changed this century during the
period of changes in the food system and
modernization in agriculture? The UK Gov-
ernment’s Composition of Foods data provides
a source of data at two time points separated
by approximately 50 years; by comparing this
data I attempt to answer this question.
The composition of foods tables
The first edition of the UK Chemical Composi-
tion of Foods[1] arose from a need to provide
investigators with information for a wide
range of foods consumed in the UK. The data
on fruit and vegetables were compiled from
previous studies of the composition of
foods[2]. Unfortunately, these reports were
destroyed in a fire during the Second World
War and have been out of print ever since.
This means that exact dates or details of the
analyses are not known.
Since the first edition there have been four
subsequent updates of the full Composition of
Foods tables. It wasn’t until the fifth edition,
however, that the tables included substantial
revisions of the original data on fruits and
vegetables that were listed in the first edition.
The fifth edition of The Composition of
Foods[3] addressed a need for updates of the
old data. The introductory section states “The
nutritional value of many of the more tradi-
tional foods has changed. This can happen
when there are new varieties or new sources
of supply for raw materials; with new
farming practices which can affect the nutri-
tional value of both plant and animal
products…”
The updated compositions of fruits and
vegetables are based on analytical studies
commissioned by the Ministry of Agricul-
ture, Fisheries and Food (MAFF). The sam-
ples were designed to reflect the usual pattern
of consumption in the UK at the time of analy-
sis. The tables are not designed to provide
comparative historical data – the fruit and
vegetables would not necessarily have been
grown in similar conditions, soils, or times of
year or be of the same varieties. The data
were also provided by mixed sources (see
below). More controlled data would have been
better, but this data nevertheless provides a
good starting point for the comparison.
The updated vegetable analyses were car-
ried out by the Institute for Food Research
between 1984 and 1987 and have been used for
all the vegetable mineral data. The updated
fruit analyses were based largely on data
from the Laboratory of the Government
Chemist (LGC). Most of the twenty fruits
listed, however, include data from other
sources for one or more of the minerals. For
instance, the entry for cooking apples makes
use of data from the LGC for P, Fe, Cu and Zn.
The values for Na, K, Ca, Mg are an average of
LGC data and the old Chemical Composition of
foods data from 1936. Table I lists sources of
data for all the twenty vegetables and fruits
that were selected for the comparison.
In this paper I have examined only raw
fruits and vegetables. This has been done to
exclude differences caused by changes in
methods of processing. The updated analyses
provide an opportunity to compare the
changes in purchased raw food over approxi-
mately a 50-year period.
Methods
I analysed twenty vegetables and fruits using
two versions of the Composition of Foods
tables[3,4]. I used the 1960 version for the old
data because it was easily available and
includes the same analyses as the first and
second editions. It also reports the results to
one more significant digit than the fourth
edition. The fruits and vegetables selected
had to meet the following criteria:
The old data had been updated for the fifth
edition of the food tables. Some fruits have
also been included when old and new data
were averaged as outlined in Table I.
The descriptions of the analysed portion of
the food were identical. For example, both
samples were peeled.
Only raw samples were included.
The food was not dried or rehydrated and
dry pulses were not included.
The food was not a condiment (e.g. horse-
radish root).
[ 208]
Anne-Marie Mayer
Historical changes in the
mineral content of fruits and
vegetables
British Food Journal
99/6 [1997] 207–211
A total of 20 fruits and 20 vegetables satisfied
these criteria and these are listed with their
mineral contents at both time points in Table
III.
I calculated the logarithm of the ratios
(new:old) for each mineral for each fruit and
vegetable and from these computed the geo-
metric means. Students t-test was used to test
whether each mean ratio was significantly
different from 1. The logs of the ratios were
used for this test.
Findings
The average ratios and results of the t-test
are listed in Table II. A ratio of 0.81 for
Table I
Sources of data for
The Composition of Foods
tables
Fruits Sources and dates of data
Apricots LGC 85-86 except Na: average of literature
Bananas LGC 85-86 except K, Zn: average of literature
Blackberries LGC 85-86
Cherries LGC 85-86
Cooking apples LGC 85-86 except Na, K, Ca, Mg: average of LGC, MW4
Eating apples LGC 85-86 except Na, K, Cu: average of literature
Grapefruit LGC 85-86 except Na, K, Ca: average MW4, USDA 86, literature
Grapes LGC 85-86 except Na, K, Zn: average of literature
Lemons MW4, USDA, literature.
Melon cantaloupe LGC 85-86
Nectarines LGC 85-86 except K, Mg: literature
Oranges LGC 85-86 except K: literature
Passion fruit Literature sources
Peaches LGC 85-86 except K: literature
Pears LGC 90
Pineapple LGC 85-86, MW4, literature
Plums Recalculated from stewed plums
Raspberries LGC 85-86
Rhubarb Average of USDA 81, MW4
Strawberries LGC 85-86
Notes:
LGC Laboratory of the Government Chemist
MW4
McCance and Widdowson’s Composition of Foods
4th edition (1936 data)[6]
USDA United States Department of Agriculture data
First to third editions: The data used in the first four editions of the
Chemical Composition of Foods
were compiled
from the 1936 data[2]
Fourth edition: The data were compiled from the 1936 data with a few additions from the literature. For example Zn
values were added from literature sources
Fifth edition: The data for vegetables in the fifth edition were all taken from the Institute of Food Research between
1984 and 1987. The data for fruits were obtained from mixed sources
Table II
Average
a
ratio of mineral content (new:old) of 20 vegetables and 20 fruits
b
Ca Mg Fe Cu Na K P Dry matter H
2
O
Vegetables ratio 0.81 0.65 0.78 0.19 0.57 0.86 0.94 0.97 1.00
p
value
c
0.014* 0.000* 0.088 0.000** 0.013* 0.090 0.487 0.53 0.872
Fruits ratio 1.00 0.89 0.68 0.64 0.90 0.80 0.99 0.91 1.02
p
value 0.957 0.016* 0.002** 0.006** 0.561 0.000** 0.903 0.023* 0.006**
Notes:
a
Geometric mean, the antilogarithm of the mean of the logarithm of the ratio of 1980s to 1930s values
b
See text for data sources and Table III for vegetables and fruits included. Analyses of Mn, Se and I were
only added in the 1991 edition. Zn was only added in the 1978 edition. S was omitted from the 1991
tables although it was analysed in previous editions. C1 was not revised in many cases for the 1991
edition. For these reasons comparisons were only possible for the above 7 minerals, water and dry matter.
c
Probability that average of logarithm of new:old is statistically different from 0 by
t
-test. (This is
equivalent to the ratios being different from 1)
* = significant at the 5 per cent level
** = significant at the 2 per cent level
[ 209]
Anne-Marie Mayer
Historical changes in the
mineral content of fruits and
vegetables
British Food Journal
99/6 [1997] 207–211
calcium, for example, means that over an
approximate 50-year period the average con-
tent of calcium in vegetables has declined to
81 per cent of the original level.
There were significant reductions in the
levels of Ca, Mg, Cu and Na, in vegetables
and Mg, Fe, Cu and K in fruits. The greatest
change was the reduction of copper levels in
vegetables to less than one-fifth of the old
level. The only mineral that showed no
significant differences over the 50-year
period was P. Water increased significantly
Table III
Mineral content of vegetables and fruit (mg/100mg)
Dry Dry
Ca Ca Mg Mg Fe Fe Cu Cu Na Na K K P P Matter Matter H
2
O% H
2
O%
old new old new old new old new old new old new old new old new old new
Vegetables
Beetroot 24.9 20.0 15.0 11.0 0.37 1.0 0.07 0.02 84.0 66.0 303.0 380.0 32.1 51 12.9 12.9 87.1 87.1
Brussels 28.7 26.0 19.6 8.0 0.66 0.7 0.05 0.02 9.6 6.0 515.0 450.0 78.4 77.0 15.7 15.7 84.3 84.3
Sprouts
Cabbage – winter 72.3 68.0 16.8 6.0 1.23 0.6 N 0.02 28.4 3.0 240.0 270.0 64.1 46.0 9.4 10.3 90.6 89.7
Carrots – old 48.0 25.0 12.0 3.0 0.56 0.3 0.08 0.02 95.0 25.0 224.0 170.0 21.0 15.0 10.2 10.2 89.8 89.8
Celery 52.2 41.0 9.60 5.0 0.61 0.4 0.11 0.01 137.0 60.0 278.0 320.0 31.7 21.0 6.5 4.9 93.5 95.1
Lettuce 25.9 28.0 9.7 6.0 0.73 0.70 0.15 0.01 3.1 3.0 208 220 30.2 28.0 4.8 4.9 95.2 95.1
Mushroom 2.9 6.0 13.2 9.0 1.03 0.6 0.64 0.72 9.1 5.0 467.0 320.0 136.0 80.0 8.5 7.4 91.5 92.6
Mustard and cress 65.9 50.0 27.3 22.0 4.54 1.0 0.12 0.01 19.0 19.0 337.0 110.0 65.5 33.0 7.5 4.7 92.5 95.3
Onions 31.2 25.0 7.6 4.0 0.30 0.30 0.08 0.05 10.2 3.0 137.0 160.0 30.0 30.0 7.2 11.0 92.8 89.0
Parsley 325.0 200.0 52.2 23.0 8.00 7.7 0.52 0.03 33.0 33.0 1,080.0760.0 128.0 64.0 21.3 16.9 78.7 83.1
Parsnips 54.8 41.0 22.4 23.0 0.57 0.6 0.10 0.05 16.5 10.0 342.0 450.0 69.0 74.0 17.5 20.7 82.5 79.3
Peas 15.1 21.0 30.2 34.0 1.88 2.8 0.23 0.05 0.5 1.0 342.0 330.0 104.0 130.0 21.5 25.4 78.5 74.6
Potatoes – old 7.7 5.0 24.2 17.0 0.75 0.4 0.15 0.08 6.5 7.0 568.0 360.0 40.3 37.0 24.2 21.0 75.8 79.0
Pumpkin 39.0 29.0 8.2 10.0 0.39 0.4 0.08 0.02 1.3 0.0 309.0 130.0 19.4 19.0 5.3 5.0 94.7 95.0
Runner beans 33.3 33.0 23.0 19.0 0.74 1.2 0.09 0.02 6.5 0.0 276.0 220.0 25.9 34.0 8.4 8.8 91.6 91.2
Radishes 43.7 19.0 11.4 5.0 1.88 0.6 0.13 0.01 59.0 11.0 240.0 240.0 27.1 20.0 6.7 4.6 93.3 95.4
Swedes 56.4 53.0 10.8 9.0 0.35 0.1 0.05 0.01 52.2 15.0 136.0 170.0 19.0 40.0 8.6 8.8 91.4 91.2
Tomatoes 13.3 7.0 11.0 7.0 0.43 0.5 0.10 0.01 2.8 9.0 288.0 250.0 21.3 24.0 6.6 6.9 93.4 93.1
Turnips 58.8 48.0 7.4 8.0 0.37 0.2 0.07 0.01 58.0 15.0 238.0 280.0 27.5 41.0 6.7 8.8 93.3 91.2
Watercress 222.0 170.0 17.0 15.0 1.62 2.2 0.14 0.01 60.0 49.0 314.0 230.0 52.0 52.0 8.9 7.5 91.1 92.5
Fruits
Apricots 17.2 15.0 12.3 11.0 0.37 0.5 0.12 0.06 N 2.0 320.0 270.0 21.3 20.0 13.4 12.8 86.6 87.2
Bananas 6.8 6.0 41.9 34.0 0.41 0.3 0.16 0.10 1.2 1.0 348.0 400.0 28.1 28.0 29.3 24.9 70.7 75.1
Blackberries 63.3 41.0 29.5 23.0 0.85 0.7 0.12 0.11 3.7 2.0 208.0 160.0 23.8 31.0 18.0 15.0 82.0 85.0
Cherries 15.9 13.0 9.6 10.0 0.38 0.2 0.07 0.07 2.8 1.0 275 210 16.8 21.0 18.5 17.2 81.5 82.8
Cooking apples 3.6 4.0 2.9 3.0 0.29 0.1 0.09 0.02 21.0 2.0 123.0 88.0 16.2 7.0 14.4 12.3 85.6 87.7
Eating apples 3.6 3.0 4.7 3.0 0.29 0.1 0.11 0.02 2.4 3.0 118.0 100.0 7.7 8.0 15.7 14.6 84.3 85.4
Grapes 11.7 13.0 5.3 7.0 0.34 0.3 0.09 0.12 1.7 2.0 283.0 210.0 19.0 18.0 20.0 18.2 80.0 81.8
Grapefruit 17.1 23.0 10.4 9.0 0.26 0.1 0.06 0.02 1.4 3.0 234.0 200.0 15.6 20.0 9.3 11.0 90.7 89.0
Lemons 107.0 85.0 11.6 12.0 0.35 0.5 0.26 0.26 6.0 5.0 163.0 150.0 20.7 18.0 14.8 13.7 85.2 86.3
Melon cantaloupe 19.1 20.0 20.1 11.0 0.81 0.3 0.04 0.00 13.5 8.0 319.0 210.0 30.4 13.0 6.4 7.9 93.6 92.1
Nectarines 3.9 7.0 12.6 10.0 0.46 0.4 0.06 0.06 9.1 1.0 268.0 170.0 23.9 22.0 19.8 11.1 80.2 88.9
Oranges 41.3 47.0 12.9 10.0 0.33 0.1 0.07 0.05 2.9 5.0 197 150 23.7 21.0 13.9 13.9 86.1 86.1
Passion fruit 15.6 11.0 38.6 29.0 1.12 1.3 0.12 N 28.4 19.0 348.0 200.0 54.2 64.0 26.7 25.1 73.3 74.9
Peaches 4.8 7.0 7.9 9.0 0.38 0.4 0.05 0.06 2.7 1.0 259.0 160.0 18.5 22.0 13.8 11.1 86.2 88.9
Pears 7.5 11.0 7.2 7.0 0.21 0.2 0.15 0.06 2.3 3.0 128.0 150.0 9.7 13.0 16.8 16.2 83.2 83.8
Pineapple 12.2 18.0 16.9 16.0 0.42 0.2 0.08 0.11 1.6 2.0 247.0 160.0 7.8 10.0 15.7 13.5 84.3 86.5
Plums 12.4 13.0 7.6 8.0 0.33 0.4 0.10 0.10 1.9 2.0 192.0 240.0 15.4 23.0 15.4 16.1 84.6 83.9
Raspberries 40.7 25.0 21.6 19.0 1.21 0.7 0.21 0.10 2.5 3.0 224.0 170.0 28.7 31.0 16.8 13.0 83.2 87.0
Rhubarb 103.0 93.0 13.6 13.0 0.40 0.3 0.13 0.07 2.2 3.0 425.0 290.0 21.0 17.0 5.8 5.8 94.2 94.2
Strawberries 22.0 16.0 11.7 10.0 0.71 0.4 0.13 0.07 1.5 6.0 161.0 160.0 23.0 24.0 11.1 10.5 88.9 89.5
Notes: Old:
Composition of Foods
3rd edition (1930s data)[4]
New:
Composition of Foods
5th edition (1980s data)[3]
N: No data available
Ca, Mg, Fe, Na, K and P were reported to one fewer significant digits in the 1991 tables.
[ 210]
Anne-Marie Mayer
Historical changes in the
mineral content of fruits and
vegetables
British Food Journal
99/6 [1997] 207–211
and dry matter decreased significantly in
fruits.
What role do the minerals play in human
nutrition?
Minerals all have several roles in human
biochemistry and physiology and all the
minerals mentioned above are essential in
the diet of humans. Many are co-factors for
different enzymes and we are dependent on
them for energy efficiency, fertility, mental
stability and immunity. Although fruits and
vegetables generally supply a small propor-
tion of total mineral dietary requirements,
the reductions could be important to some
groups so the causes of the reductions need
investigating. It is not clear what is causing
the reductions. There are several possibilities
and these are outlined below.
Are the reductions anomalies of
measurement or sampling?
The earlier analyses of some minerals may
have been inaccurate compared to modern
analytical methods. Elsie Widdowson, how-
ever, notes in the introduction to The Compo-
sition of Foods[3] that “those methods were no
less accurate than the modern automated
ones, but they took a much longer time”. If
this is true, we should be able to rely on the
consistency of the analytical methods. How-
ever, there has been much debate over this
question and no clear conclusion has been
reached.
The methods of sampling fruit and vegeta-
bles were designed to reflect the usual choice
of foods at the time of the research. There
could be differences in the methods of sam-
pling. It is not possible to compare the details
of the methods used because the original data
are no longer available. Also, the use of mixed
sources of data for the 1991 edition of The
Composition of Foods[3] is an unknown factor
and possible source of bias. It is not known
whether the first edition of the Chemical
Composition of Foods[1] used similar methods
of data compilation.
Food system changes
In the past sixty years the food supply system
has changed considerably. For instance we
now eat more “out of season” and imported
foods grown on a wide variety of soils from
many different countries. Some of the fruits
and vegetables have always been imported
but many of those previously grown in the
UK are also now imported. Storage and ripen-
ing systems have changed. Greenhouse crops
are “brought on” more quickly now and often
grown in soil-less mixes. Could these prac-
tices have changed the composition of fruits
and vegetables?
The varieties of plants cultivated now has
also changed. Nowadays we practise sophisti-
cated plant breeding and have bred selec-
tively for qualities that will suit the demands
of, for example, high yield, post-harvest
handling qualities and cosmetic appeal. Also
we select varieties that will respond well to
the methods of agriculture currently
employed. Specific breeding to enhance nutri-
tional quality is rare.
Agricultural practices
During the early 1930s agricultural chemicals
were hardly used. Manure and compost were
the main fertilizers used. After the war prac-
tices changed and farmers became more
reliant on the use of fertilizers and other
agrochemicals as well as heavy farm machin-
ery.
Agriculture which relies on NPK fertilizers
and pesticides, that adds little organic matter
to the soil and that alternates between soil
compaction and ploughing, could produce
food depleted in minerals. These practices
affect the structure, chemistry and ecology of
the soil in ways that could affect the availabil-
ity of minerals to plants and hence the min-
eral content of crops. For instance, mycor-
rhizal fungi have a symbiotic relationship
with plant roots in which sugars and miner-
als are exchanged. The fungi are reduced by
high levels of available phosphate and nitro-
gen, low pH, waterlogging or excessive
dryness[5].
Another factor could be the differing levels
of contamination of crops with residues of
pesticides containing high concentrations of
minerals – for example Bordeaux mixture
contains high levels of copper and was widely
used as a pesticide.
In principle, modern agriculture could be
reducing the mineral content of fruit and
vegetables. We need to find out if this, or any
of the other explanations described above, are
significant factors in practice. Considering
the magnitude of the reductions this matter
deserves urgent attention.
The following questions arise from the
findings:
Are the data reliable?
Is the apparent decline caused by dimin-
ished levels of minerals in the soil, poor
availability, the choice of cultivars or other
changes in the food system?
To what extent is the decline in minerals of
importance to human nutrition?
Are other countries experiencing similar
changes?
Are there similar reductions in other
crops – such as cereals?
[ 211]
Anne-Marie Mayer
Historical changes in the
mineral content of fruits and
vegetables
British Food Journal
99/6 [1997] 207–211
Are other minerals of equal importance to
human nutrition, such as Se and Cr, also
reduced?
Are other nutrients – for example, vita-
mins – also reduced?
Are some cultivars producing crops that
are lower in minerals than others?
Does soil contamination – past or present –
affect the mineral content of crops?
To answer these questions existing literature
needs to be reviewed and further research
carried out along the suggested lines;
an analysis of the effect of the latest Com-
position of Foods data on usual diets;
compilation of a database of historical data
from different countries, different time
scales and different crops;
detailed and controlled studies of soils and
the effects of methods of agriculture on
plant nutrition and crop mineral content;
studies of the mineral content of fruit and
vegetables grown using different cultivars
in common use now and 60 years ago;
regular monitoring of food composition
with details on cultivars, methods of grow-
ing and soils.
References
1 McCance, R.A. and Widdowson, E.M., The
Chemical Composition of Foods, Medical
Research Council Special Report Series No.
235, HMSO, London, 1940.
2 McCance, R.A., Widdowson, E.M. and
Shackleton, L.R.B., The Nutritive Value of
Fruits, Vegetables and Nuts, Medical Research
Council Special Report Series No. 213, HMSO,
London, 1936.
3 Holland, B., Welch, A.A., Unwin, I.D., Buss,
D.H., Paul, A.A. and Southgate, D.A.T.,
McCance and Widdowson’s Composition of
Foods fifth edition, Royal Society of Chemistry
and the Ministry of Agriculture, Fisheries and
Food, HMSO, London, 1991.
4 McCance, R.A. and Widdowson, E.M., The
Composition of Foods third edition, Medical
Research Council Special Report series No.
213, HMSO, London, 1960.
5 Killham, K., Soil Ecology, Cambridge Univer-
sity Press, Cambridge, 1994.
6 Paul, A.A. and Southgate, D.A.T., McCance and
Widdowson’s Composition of Foods fourth
edition, Ministry of Agriculture, Fisheries and
Food and Medical Research Council, HMSO,
London, 1978.
... There is concern that the mineral content of plant-based foods has declined in the past few decades. A 1997 study comparing nutrient data of vegetables and fruits in two UK food composition tables analysed in 1930s and 1980s found a significant decline in the levels of magnesium, calcium, copper, sodium, potassium and iron in those foods over time [12]. Since then, studies comparing historical US food composition data have also noted a marked temporal decrease in mineral content of plant-based foods [13,14]. ...
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... Mayer [26] 1997 United Kingdom ...
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Evidence-based knowledge of the relationship between foods and nutrients is needed to inform dietary-based guidelines and policy. Proper and tailored statistical methods to analyse food composition databases (FCDBs) could assist in this regard. This review aims to collate the existing literature that used any statistical method to analyse FCDBs, to identify key trends and research gaps. The search strategy yielded 4238 references from electronic databases of which 24 fulfilled our inclusion criteria. Information on the objectives, statistical methods, and results was extracted. Statistical methods were mostly applied to group similar food items (37.5%). Other aims and objectives included determining associations between the nutrient content and known food characteristics (25.0%), determining nutrient co-occurrence (20.8%), evaluating nutrient changes over time (16.7%), and addressing the accuracy and completeness of databases (16.7%). Standard statistical tests (33.3%) were the most utilised followed by clustering (29.1%), other methods (16.7%), regression methods (12.5%), and dimension reduction techniques (8.3%). Nutrient data has unique characteristics such as correlated components, natural groupings, and a compositional nature. Statistical methods used for analysis need to account for this data structure. Our summary of the literature provides a reference for researchers looking to expand into this area.
... Given the findings of the studies discussed above, it is reasonable to hypothesize that in addition to the known effects of crop breeding (Morris and Sands, 2006), microbial community disruption due to degraded soil health contributed to the historical declines of mineral micronutrients and phytochemicals in crops (Mayer, 1997;Davis et al., 2004;White and Broadley, 2005;Ekholm et al., 2007;Davis, 2009). Indeed, evidence for such a connection emerged in the early days of nowconventional practices. ...
... Although early studies pointed to contrasting effects of soil organic matter and chemical fertilizers on soil life in influencing the composition of crops, understanding why lay beyond the scope of conventional thinking. In subsequent decades, studies demonstrated mechanisms underlying connections that help explain, and potentially point to ways to reverse, reported historical declines in micronutrient density (Mayer, 1997;Davis et al., 2004;Ekholm et al., 2007;Davis, 2009). While there appears to be little evidence of significant differences in macronutrient composition, other than some conventional crops containing higher protein levels, there is substantial evidence that farming systems impact micronutrient levels. ...
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Controversy has long surrounded the question of nutritional differences between crops grown organically or using now-conventional methods, with studies dating back to the 1940s showing that farming methods can affect the nutrient density of crops. More recent studies have shown how reliance on tillage and synthetic nitrogen fertilizers influence soil life, and thereby soil health, in ways that can reduce mineral micronutrient uptake by and phytochemical production in crops. While organic farming tends to enhance soil health and conventional practices degrade it, relying on tillage for weed control on both organic and conventional farms degrades soil organic matter and can disrupt soil life in ways that reduce crop mineral uptake and phytochemical production. Conversely, microbial inoculants and compost and mulch that build soil organic matter can increase crop micronutrient and phytochemical content on both conventional and organic farms. Hence, agronomic effects on nutritional profiles do not fall out simply along the conventional vs. organic distinction, making the effects of farming practices on soil health a better lens for assessing their influence on nutrient density. A review of previous studies and meta-studies finds little evidence for significant differences in crop macronutrient levels between organic and conventional farming practices, as well as substantial evidence for the influence of different cultivars and farming practices on micronutrient concentrations. More consistent differences between organic and conventional crops include that conventional crops contain greater pesticide levels, whereas organically grown crops contain higher levels of phytochemicals shown to exhibit health-protective antioxidant and anti-inflammatory properties. Thus, part of the long-running controversy over nutritional differences between organic and conventional crops appears to arise from different definitions of what constitutes a nutrient—the conventional definition of dietary constituents necessary for growth and survival, or a broader one that also encompasses compounds beneficial for maintenance of health and prevention of chronic disease. For assessing the effects of farming practices on nutrient density soil health adds a much needed dimension—the provisioning of micronutrients and phytochemicals that support human health.
... When compared to ordinary fruit and vegetables, EFs are a good source of minerals. This is evidenced by the higher K content than vegetables and fruit, which have an average K content of 1500-2100 mg/kg FM (Table 4) [78][79][80]. Several researchers observed a similar trend in which potassium content was highest in flowers [14,[81][82][83]. ...
... The content of other elements in flowers is comparable to vegetables [80], but some selected leafy vegetables had a higher content of sodium than potassium [58]. Compared to fruit, a two-fold increase in Ca and Mg contents and a fourfold rise in Na content can be observed [78,85,86]. In addition, the content of mineral elements in flowers can be compared with published minerals data about wild-growing and cultivated mushrooms. ...
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Ornamental edible flowers can be used as novel nutraceutical sources with valuable biological properties. The purpose of this study was to establish nutritional, chemical, and sensory characteristics, antioxidant capacity (AC), and the relationship between their bioactive components and AC. The selected flowers Begonia × tuberhybrida, Tropaeolum majus, Calendula officinalis, Rosa, Hemerocallis, and Tagetes patula, can be easily collected due to their larger size. Their methanolic extracts were spectrophotometrically determined for polyphenols, flavonoids, and AC. Mineral elements were analyzed by atomic-absorption spectroscopy; crude protein was quantified by the Kjeldahl method. Eventually, 30 panelists evaluated sensory properties in 11 attributes. In addition, this study may serve to popularize selected blossoms. In flowers the contents of minerals were in this order: K > Ca > P > Mg > Na > Zn > Mn > Fe > Cu > Mo. AC ranged between 4.11 and 7.94 g of ascorbic acid equivalents/kg of fresh mass. The correlation coefficients between AC-total phenolics and AC-total flavonoids were r = 0.73* and r = 0.58*, respectively. It is also possible to observe a strong correlation between mineral elements and bioactive compounds. Hemerocallis was rated as the best and most tasteful; additionally, it exhibited the highest AC, total phenolic and flavonoid contents.
... The 6 nutrients -protein, calcium, iron, phosphorus, riboflavin and ascorbic acid were showed a significant decline in the 43 studied crops. Similarly, Mayer (1997) analysed nutrients in 20 fruits crop and vegetables between 1930 and 1980. The study suggested that significant reductions in the levels of calcium (Ca), magnesium (Mg), copper (Cu) and sodium (Na) in vegetables and magnesium (Mg), iron (Fe), copper (Cu) and potassium (K) in fruits. ...
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Change in climate directly effects on the agricultural ecosystem that results in changing agricultural climatic elements such as temperature, precipitation and sunlight. The impacts of climate change on global food system, nutrition and health will depend on a variety of environmental factors. Due to continuously increasing global temperature, the negative impact of climate change on agricultural crops includes reduction in crop quality and quantity. The increasing population demands more food which resulted intensive agricultural practices like the use of pesticides, livestock generation, extensive use of water resources. The high anthropogenic activities result, degradation of natural resources. Now, it is the need of the hour to strengthen our capacities to combat these constant environmental changes with integration of knowledge from, ancestors, communities and scientific innovations. Technological innovations to meet the local needs of food and nutrition with best practices for producing, preserving and preparing healthy foods
... US consumers now spend an average of only 8.6% of their disposable personal income on food-a number which has trended consistently downward since the 1960s (USDA ERS, 2021b). The focus on producing calories and consumer goods as cheaply as possible, however, has meant that the true costs of food production have been externalized-whether through the reduced nutritional content of food (Mayer, 1997;Davis et al., 2004), environmental degradation (Tscharntke et al., 2012;Allan et al., 2015;Clark and Tilman, 2017), unethical labor practices (Snipes et al., 2017;Klocker et al., 2020;Soper, 2020), or, as we review in this paper, the livelihoods of those who operate US farms. ...
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In nine of the last 10 years, the United States Department of Agriculture (USDA) has reported that the average funds generated on-farm for farm operators to meet living expenses and debt obligations have been negative. This paper pieces together disparate data to understand why farm operators in the most productive agricultural systems on the planet are systematically losing money. The data-driven narrative we present highlights some troubling trends in US farm operator livelihoods. Though US farms are more productive than ever before, rising input costs, volatile production values, and rising land rents have left farmers with unprecedented levels of farm debt, low on-farm incomes, and high reliance on federal programs. For many US farm operators, the indicators of a “good livelihood”—stability, security, equitable rewards for work—are largely absent. We conclude by proposing three axes of intervention that would help US agriculture better sustain all farmers' livelihoods, a crucial step toward improving overall agricultural sustainability: (1) increase the diversity of people, crops, and cropping systems, (2) improve equity in access to land, support, and capital, and (3) improve the quality, accessibility, and content of data to facilitate monitoring of multiple indicators of agricultural “success.”
... Reported declines in the nutrient density of crops (Mayer, 1997;Davis, Epp & Riordan, 2004;White & Broadley, 2005;Ekholm et al., 2007;Davis, 2009) are typically attributed to crop breeders having focused almost exclusively on increasing yields (Morris & Sands, 2006;Marles, 2017). However, studies demonstrating that fertilization regimes and soil life affect mineral uptake by crops (e.g., Lambert, Baker & Cole, 1979;Marschner & Dell, 1994;Miller, 2000;Jansa, Wiemken & Frossard, 2006;Ryan et al., 2008;White & Broadley, 2009;Zhang et al., 2012;Lehmann et al., 2014;Adak et al., 2016;Konecny et al., 2019) suggest that conventional farming practices of intensive tillage, nitrogen fertilization, and synthetic pesticide applications may have contributed to declining nutrient density through disrupting crop symbioses with soil life (Montgomery & Biklé, 2016, 2022. ...
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Several independent comparisons indicate regenerative farming practices enhance the nutritional profiles of crops and livestock. Measurements from paired farms across the United States indicate differences in soil health and crop nutrient density between fields worked with conventional (synthetically-fertilized and herbicide-treated) or regenerative practices for 5 to 10 years. Specifically, regenerative farms that combined no-till, cover crops, and diverse rotations—a system known as Conservation Agriculture—produced crops with higher soil organic matter levels, soil health scores, and levels of certain vitamins, minerals, and phytochemicals. In addition, crops from two regenerative no-till vegetable farms, one in California and the other in Connecticut, had higher levels of phytochemicals than values reported previously from New York supermarkets. Moreover, a comparison of wheat from adjacent regenerative and conventional no-till fields in northern Oregon found a higher density of mineral micronutrients in the regenerative crop. Finally, a comparison of the unsaturated fatty acid profile of beef and pork raised on one of the regenerative farms to a regional health-promoting brand and conventional meat from local supermarkets, found higher levels of omega-3 fats and a more health-beneficial ratio of omega-6 to omega-3 fats. Despite small sample sizes, all three crop comparisons show differences in micronutrient and phytochemical concentrations that suggest soil health is an under appreciated influence on nutrient density, particularly for phytochemicals not conventionally considered nutrients but nonetheless relevant to chronic disease prevention. Likewise, regenerative grazing practices produced meat with a better fatty acid profile than conventional and regional health-promoting brands. Together these comparisons offer preliminary support for the conclusion that regenerative soil-building farming practices can enhance the nutritional profile of conventionally grown plant and animal foods.
... Thus, continuous updates of a FCDB are essential to reflect the changes not only in the types of food provided but also the composition thereof [39]. The evaluation of the effects can be based on changes in food composition [34] and some studies have applied statistical methods to different versions of FCDBs to determine changes over time in composition of fruits and vegetables [40][41][42]. Therefore, repeating our analysis on past versions and future updates of food composition data could assess whether the implementation of FBDGs and regulations have impacted the reformulation of products. ...
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Food composition databases (FCDBs) provide the nutritional content of foods and are essential for developing nutrition guidance and effective intervention programs to improve nutrition of a population. In public and nutritional health research studies, FCDBs are used in the estimation of nutrient intake profiles at the population levels. However, such studies investigating nutrient co-occurrence and profile patterns within the African context are very rare. This study aimed to identify nutrient co-occurrence patterns within the South African FCDB (SAFCDB). A principal component analysis (PCA) was applied to 28 nutrients and 971 foods in the South African FCDB to determine compositionally similar food items. A second principal component analysis was applied to the food items for validation. Eight nutrient patterns (NPs) explaining 73.4% of the nutrient variation among foods were identified: (1) high magnesium and manganese; (2) high copper and vitamin B12; (3) high animal protein, niacin, and vitamin B6; (4) high fatty acids and vitamin E; (5) high calcium, phosphorous and sodium; (6) low moisture and high available carbohydrate; (7) high cholesterol and vitamin D; and (8) low zinc and high vitamin C. Similar food patterns (FPs) were identified from a PCA on food items, yielding subgroups such as dark-green, leafy vegetables and, orange-coloured fruit and vegetables. One food pattern was associated with high sodium levels and contained bread, processed meat and seafood, canned vegetables, and sauces. The data-driven nutrient and food patterns found in this study were consistent with and support the South African food-based dietary guidelines and the national salt regulations.
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Micronutrient malnutrition is widespread and is linked with diets low in fruit and vegetables. However, during the twentieth century, declines in essential minerals in fruits and vegetables were reported in the UK and elsewhere. A new analysis of long-term trends of the mineral content of fruits and vegetables from three editions of the UK’s Composition of Foods Tables (1940, 1991 and 2019) was undertaken. All elements except P declined in concentrations between 1940 and 2019 – the greatest overall reductions during this 80-year period were Na (52%), Fe (50%), Cu (49%) and Mg (10%); water content increased (1%). There could be many reasons for these reductions, including changes in crop varieties and agronomic factors associated with the industrialisation of agriculture. Increases in carbon dioxide could also play a role. We call for a thorough investigation of these reductions and steps to be taken to address the causes that could contribute to global malnutrition.
McCance and Widdowson’s Composition of Foods fifth edition
  • B Holland
  • A.A Welch
  • I.D Unwin
  • D.H Buss
  • A.A Paul
  • D.A.T. Southgate
The Composition of Foods third edition
  • R.A McCance
  • E.M. Widdowson