Vol.2, No.4, 424-431 (2011)
opyright © 2011 SciRes. Openly accessible at http://www.scirp.org/journal/AS/
Agricultural Scienc es
Influence of agronomic variables on quality of tomato
Marcos Hernández Suárez1, Eladia Peña Méndez2, Beatriz Rodríguez Galdón3,
Elena Rodríguez Rodríguez2, Carlos Díaz Romero2*
1Agriculture Technology National Centre “Extremadura” CTAEX, Villafranco del Guadiana, Badajoz, Spain;
2Analytical Chemistry, Nutrition and Food Science Department, La Laguna University, La Laguna, Spain;
*Corresponding Aut hor: cdiaz@ull.es
3Biochemistry and Molecular Biology Department, Extremadura University, Badajoz, Spain.
Received 4 August 2011; revised 18 September 2011; accepted 11 October 2011.
In order to study interactions between agro-
nomic variables and chemical composition that
determine the quality of tomato fr uit s, a group of
statistical techniques were applied: discriminant
analysis (DA), cluster analysis (CA) and prince-
pal component analysis (PCA) combined with
ANOVA. The results of DA when characterizing
the agronomic parameters were successful, es-
pecially when the collection date was used as a
factor for classification. CA showed the impor-
tance of the chemical variables related to the
metabolic relationships, w hile the principal com-
ponent analysis and ANOV A provide information
on the interaction between variables related to
the production and chemical composition of
tomatoes. The combined use of PCA and ANOVA
is a suitable tool for studying the complex in-
teractions between agronomy and chemical
composition. Collection date was the main ag-
ronomic parameter effected the chemical com-
position, while variety and production system
had a minor effect. The application of PCA-
ANOVA showed that the taste of tomato de-
pends on three factors: sugars (glucose and
fructose), acidity (citric, malic and ascobirc
acids), an d mine ral s (Na and Mg). F or the tom a-
toes with same maturity degree, the taste de-
pends on interaction of date collection and
system production.
Keywords: Tomato; Chemical Composition;
Agronomy; Multivariate Analysis
The tomato (Solanum lycopersicon) is not only one of
the world’s most important vegetables, but it is also the
most widely used as well as being a versatile vegetable
crop. They are consumed fresh and are also used to
manufacture a wide range of processed products. These
are some of the reasons why the scientific community
has recently become interested in the tomato [1]. It is an
excellent source of the following nutrients and second-
dary metabolites which are important for human health:
minerals, vitamins C and E, β-carotene, lycopene, fla-
vonoids, organic acids, phenolics and chloroph yll [2-4].
In the case of plant foods, fruit ripening is a geneti-
cally programmed process culminating in changes in
color, texture, flavor, and chemical compositions [5]. As
a result, the chemical composition of the tomato fruit
depends on factors such as cultivar, maturity and the
environmental conditions in which they are grown [6-8].
Foodstuffs are a physico-chemical complex matrix of
several interacting factors. A complete understanding of
the complex interactions between environment, metabo-
lism, and chemical composition of crops would require
the input of information fro m a multidiscip lin ary team of
scientists and the use of tools to in terpret those relations,
by example multivariate analysis [9].
In previous reports [10-13], the chemical composition
of the tomato has been widely described according to
several agronomic variables such as variety, date of col-
lection, cultivation area and production system. The aim
of this work is to characterize and unravel the relation-
ship between agronomy and chemical composition of
tomatoes by using the combination of several chemom-
etric tools.
2.1. Samples
One hundred and sixty seven samples, belonging to
five cultivars of tomatoes (Dorothy, Boludo, Thomas,
Dominique, Dunkan), were provided by ACETO (Aso-
M. H. Suárez et al. / Agricultural Sciences 2 (2011) 424- 431
Copyright © 2011 SciRes. Openly accessible at http://www.scirp.org/journal/AS/
ciación Provincial de Cosecheros Exportadores de To-
mates de Tenerife) and other companies from different
farms located in the southern and western regions of the
island of Tenerife (Spain). Four samples (1 kg of weight)
of each of the five cultivars were collected during dif-
ferent periods. Agronomic parameters such as variety,
production system, date of collection and cultivation
area were considered (Tab le 1). Additional information
relating to the tomato samples can be found in previous
research [10-13].
2.2. Analytical Methods
Three tomatoes selected from each sample were
hand-rinsed with ultrapure water, shaken to remove any
excess water and gently blotted with a paper towel. The
tomatoes were then mixed and homogenised to a homo-
geneous puree using a model T-25 Basic Turmix (Ika-
Werke, Staufen, Germany). The puree was stored in a
polyethylene tube at –80˚C. Several sub-samples were
taken in duplicate from this puree to measure the differ-
ent parameters.
Moisture content was determined by drying the sam-
ples to a constant weight at 105˚C according to AOAC
[14]. Ash content was measured by calcinations at 550˚C
to a constant weight, according to AOAC [14]. Nitrogen
content was determined according to the Kjeldahl
method and nitrogen value was multiplied by 6.25 as
conversion factor [14]. Total fibre was determined ac-
cording to the method proposed by Prosky et al. [15].
Ascorbic acid was determined by the 2,6-dichlorophe-
nol-indophenol titration procedure [14]. The acidity was
determined by means of titration with NaOH 0.1 mol/L
until pH 8.1, expressing the results in grams of anhy-
drous citric acid per 100 g. The pH was determined by
potenciometric measurement at T = 20˚C with a pH-
meter [14]. The content of total phenolics was deter-
mined according to the Folin-Ciocalteu method [16].
Lycopene concentration was determined spectropho-
tometrically [17].
The mineral content was determined by atomic ab-
sorption spectrophotometry previous to nitric digestion
[11], except for phosphorous which was measured by a
colorimetric method, using the Vanadate-Molybdate re-
agent [18]. The analytical HPLC methods were used to
measure the contents of sugars were proposed by Li et al.
[19] and modified by Hernández et al. [12]. The analyti-
cal method used to measure the content of organic acids
was proposed by Hernández et al. [13]. Hydroxycin-
namic acids were determined according the methos pro-
posed by Martínez-Valverde et al. [20] and modified by
Hernández et al. [10].
2.3. Statistical Analysis
All the statistics were performed by means of the
SPSS version 17.0 software for Windows (SPSS Inc.
Chicago, IL). Each quantitative variable was standard-
ized according to a typical z-standarization.
A linear discriminant analysis (LDA) was applied on
chemical composition to classify the tomato samples
according to the agronomical parameters such as variety,
production system, date of collection and the cultivation
area. The variables used for the classification of tomato
samples Stepwise LDA was applied using Wilk’s lambda
and F-statistic as the selection criterion for the quantita-
tive variables, thereby enhancing the discrimination be-
tween established groups.
Cluster analysis (CA) is one of the most useful chemo-
metric tools for studying the classification tendency of
the samples. Moreover, CA was applied to find out the
underlying relationships between the chemical parame-
ters used in this study. Among several clustering algo-
rithms, Ward’s method was selected as the linkage method
using Euclidean distance as the measure of similarity.
Table 1. Distribution of the tomato samples analyzed according to cultivar, cultivation method, sampling period, and region of pro-
Production system Date of collection Cultivation area*
Variety Total
Intensive Organic HydroponicOct 04-Nov 04Dec 04-Jan 05Feb 05-Mar 05Apr 05-Jun 05 WestSouth
Dorothy 50 25 14 11 14 16 12 8 16 9
Boludo 46 28 14 4 12 12 11 11 15 13
Dominique 19 10 9 0 4 8 5 2 0 0
Thomas 25 16 9 0 8 8 4 5 0 0
Dunkan 27 4 12 11 2 10 9 6 0 0
Overall 167 83 58 26 40 54 41 32 31 22
*Only in intensive cultivation.
M. H. Suárez et al. / Agricultural Sciences 2 (2011) 424- 431
Copyright © 2011 SciRes. Openly accessible at http://www.scirp.org/journal/AS/
Principal component analysis (PCA) was applied to
explore the complex relationships/connections between
the parameters regarding the agronomical uses and the
chemical composition. One way ANOVA was performed
to investigate which agronomical parameters influence
each principal component (PC) and clarify the results
Some scientists suggest that multivariate analysis
should be performed with those independent variables
without a clear relationship between them [21]. In a pre-
vious papers [10-13], we reported that pH, acidity and
ash depend on other analyzed variables, organic acids
and minerals respectively. Besides, in this moisture
showed an inverse relationship with the rest of the vari-
able studied due to the fact that an increase in water
content reduces the concentration of other parameters
[10-13]; these facts are consistent with data from other
authors [22]. Therefore, the variables moisture, ash, pH,
and acidity were not consid ered in this paper.
3.1. Characterization of Agronomic
Variables by LDA
When the tomato variety is used as the criterion for
classification, a very low classification, 32.3% (27.5%
after cross-validation) was obtained and the selected
variables in this stepwise-LDA were Fe, glucose and
ferulic acid. This percentage of classification suggests
that the chemical parameters analyzed were not good
enough to characterize the varieties. Alth ough the results
appear to contradict other studies that report a change in
chemical composition with the tomato variety [7,8,20],
in our case the variety has a limited influence on the
chemical composition. This could be attributed to dif-
ferences in the ripening stage of tomatoes belonging to
different varieties, although, in this work, tomato sam-
ples did not show significant difference between each
other regarding the maturity index [12].
Tomatoes undergo a wide range of biosynthetic as well
as degradative reactions that markedly affect the final
chemical composition of the fruit during ripening [23].
These changes are highly coordinated and modified by
genetic and environmental factors. This aspect is impor-
tant because the consumer chooses the tomatoes for their
appearance (color, size, shape, freedom from physio-
logical disorders, and decay), firmness, texture, dry mat-
ter, and organoleptic (flavor) and health properties [24].
In the case of the date of collection as th e criterion for
classification, a high percentage of classification (91.6%,
89.8% after cross-validation) was observed when select-
ing the following variables: glucose, lycopene, and py-
ruvic, malic, citric, fumaric, and p-c ou maric acids, Na, K,
Mg, P, and Ca. Figure 1 presents the classification of the
tomato samples on the two firsts discriminant functions.
This percentage of classification suggests that the physi-
co-chemical matrix of data selected can be used to char-
acterize the tomatoes according to the date of collection
satisfactorily (Figure 1). An analysis of the results
shows the relationship of the variables selected in the
stepwise-LDA with temperature. The synthesis of glu-
cose (photosynthesis) and organic acids (pyruvic, malic,
citric and fumaric) of the Krebs cycle are regulated by
the temperature [25], and lycopene synthesis is com-
pletely inhibited at 32˚C and temperatures higher than
30˚C - 35˚C notably reduced the lycopene content [26].
Adverse environmental conditions can generate reactive
oxygen species (ROS) in cherry tomato fruits, which
attack all types of biomolecules, causing several altera-
tions in the fruit [26-28]. This could explain why lyco-
pene and p-coumaric acids, both antioxidants, were se-
lected to characterize the date of collection.
As regards the minerals, the deficiency of Ca in the
tissues can cause physiological disorders. Besides which,
salinization also limits the absorption of Ca. Both proc-
esses involve a regulation of ion concentrations (Ca, Na
and K), especially in the summer [29,30].
When the production system was the criterion of clas-
sification, a low percentage of classification, 69.3%
(63.9% after cross-validation) was obtained after select-
ing the following variables: glucose, lycopene, P, Na,
Mg, Mn, and total fibre. Therefore, no clear relationship
Figure 1. Scores plot of tomato samples according to the date
of collection on the space of two first discriminant functions.
M. H. Suárez et al. / Agricultural Sciences 2 (2011) 424- 431
Copyright © 2011 SciRes. Openly accessible at http://www.scirp.org/journal/AS/
between the quantitative variables with the production
system was found. Few studies have shown that there are
no differences in the physico-chemical and sensory qual-
ity of conventional tomatoes grown in soil or in rock-
wool slabs (a kind of hydroponic culture) [31]. However,
it has been shown that organic foods seem to have higher
levels of vitamin C, certain essential minerals (Ca, Mg,
Fe) and phytochemicals such as lycopene in tomatoes,
polyphenols in potatoes or flavonols in apples [31-33 ].
Organic tomatoes contained more salicylic acid but
less vitamin C and lycopene when compared to crops
grown using conventional and organic methods [31,34,
35]. Organic fruits had a slightly higher protein content
than conventionally cultivated fruits, perhaps because
the plants were grown und er stressful conditions [36,3 7].
Cultivation area was considered as the fourth factor
for classification. Only intensively cultivated Dorothy
and Boludo varieties were considered in this case. The
following variables: pyruvic acid, ascorbic acid, total
fibre, Na, Ca, Mg, and Mn were selected and gave a high
percentage of classification, 92.3% (90.8% after cross-
validation). The good results suggest that when the pro-
duction system is homogeneous, the differences between
tomatoes varieties grown in different areas could mainly
be due to the mineral composition of soils as well as to
climatic factors. Low levels of Ca in soil may influence
the content of total fibre in tomatoes [38]. The presence
of ascorbic acid in the selected variables could be ex-
plained by two reasons: firstly because Na increases
ascorbic acid in the tomato fruit [36], and secondly be-
cause light exposure is favourable to vitamin C accumu-
lation [26,39]. Metabolic relationships could explain the
presence of Mg, Mn and pyruvic acid. Mg active en-
zymes such as phosphoenol pyruvate carboxylase and
Mn are involved in photosynthesis [25].
3.2. Characterization of Chemical
Composition by CA
Figure 2 presents the dendrogram obtained using
Ward’s linkage method (Euclidean distance). Five main
groups were considered: A, B, C, D and E, where there
are several subgroups withi n each group.
Group A included two subgroups, sugars (fructose and
glucose) and certain organic acids (malic, citric,and fu-
maric acids). These variables are associated with or-
ganoleptic properties which are mainly attrib uted to their
aroma compounds, sugars, and organic acid contents
[31]. Glucose and fructose account for about 95% of the
total sugars in the tomato whereas sucrose is detected in
trace amounts [40,41].
The rest of groups are linked to the nu tritional quality.
Worthington [31] defined nutritional quality o f a fruit for
the content in minerals, vitamins, and bioactive com-
pounds such as carotenoid and flavonoid contents.
Group B included chemical parameters essential for
good plant development. A first subgroup: oxalic and
pyruvic acids; and a second subgroup with protein and
Fe. Pyruvic and oxalic acids are precursors of the Krebs
cycle and Fe is the main micronutrient, often linked to
proteins or enzymes [25].
Figure 2. Dendrogram obtained by cluster analysis of variables using Ward’s method of linkage.
M. H. Suárez et al. / Agricultural Sciences 2 (2011) 424- 431
Copyright © 2011 SciRes. Openly accessible at http://www.scirp.org/journal/AS/
The several subgroups of parameters included within
group C have clear relationships between them. The
availability of Mg depends on K concentration and both
minerals are involved in the synthesis of carotenoid
compounds [42]. Salt enrichment (Na) in the nutrient
solution of plants is known to increase the ascorbic acid
content, which adds acidic taste to the fruit [43]. As re-
gards phenolic compounds, although genetic control is
the main factor in determining their accumulation in
vegetable foods, external factors may also have a sig-
nificant effect on this. In many plant species the flavonol
content may be enhanced in response to elevated light
levels, in particular to increased UV-B radiation and the
level of P. Tomato plants grown under high light accu-
mulate a higher soluble phenol content (rutin and chloro-
genic acid) than low-light plants [44-47].
Chemical parameters related with structural function
appear in group D. Ca plays an essential role in this
process by preserving the structural and functional in-
tegrity of plant membranes, stabilizing cell wall struc-
tures and regulating ion transport [48,49].
Group E consisted of the main antioxidants, such as
hydroxycinnamic acids and lycopene, and of Cu. The
data available on the effect of mineral nutrients on the
antioxidant compounds of tomato are either scarce or not
very reliable or appl icabl e [26 ] .
3.3. Characterization of Agronomic
Variables and Chemical
Composition by PCA
After performing PCA analysis, 71.3% of the variance
could be explained by eight main components having
eigenvalues higher than 1. Table 2 shows the first six
PCs for the characterization of tomatoes. The chemical
variables had low loads on PC7 and PC8, and therefore,
they are not shown. The last column of Tab l e 2 shows
the result of one way ANOVA on each PC. Figure 3
shows the loading p lot of the considered variables in the
PCA projected on the plane of PC1 vs PC2.
Table 2. Results of PCA without rotation. Total variance explained: 71.3%.
PC % variance Main quantitative variables included Agronomic parameters that influences in the PC§
PC1 16.4 Glucose, fructose, malic acid, citric acid, ascorbic acid, Na, Mg* Date of collection, production system, cultivation area†
PC2 13.3 Lycopene, oxalic acid, protein, Zn, Fe, Cu Date of collection, cultivation area†
PC3 11.1 p-Coumaric acid, caffeic acid, ferulic acid, Ca, Mn, P Date of collection, production system, cultivation area†
PC4 9.1 Total fibre, pyruvic acid, chlorogenic acid Production system
PC5 7.1 K, Mg* Date of collection, production system
PC6 5.8 Phenolic compounds, fumaric acid Variety
*The PCA included the Mg in two PCs, 1 and 5, with similar load; §ANOVA on each PC (P < 0.05); Only for the intensive Dorothy and Boludo varieties.
Figure 3. Loading plot of Principal Components Analysis (PCA) projected on
the space of PC1 vs PC2.
M. H. Suárez et al. / Agricultural Sciences 2 (2011) 424- 431
Copyright © 2011 SciRes. Openly accessible at http://www.scirp.org/journal/AS/
PC1 explains 16.4% of the variance and is formed by
the chemical variables that define the organoleptic prop-
erties of the tomato (Table 2): sugars (glucose and fruc-
tose), the main organic acids (malic, citric and ascorbic
acids) and the minerals Na and Mg together (Mg is also
included in PC5). Date of collection, production system
and the cultivation area are the agronomic variables
which influence this PC. As has already been mentioned,
the organic acids are related with organoleptic properties
and they contribute to increasing ascorbic acid as well as
adding acidic taste to the fruit [36].
PC2 explains 13.3% of the variance and groups the
following variables together: lycopene, oxalic acid, pro-
tein, Zn, Fe and Cu. This PC contains variables directly
influenced by date of collection and the cultivation area
and suggests a metabolic relationship that depends on
the environmental conditions. The synthesis of lycopene
is influenced by temperature [26]. Therefore, the synthe-
sis of this carotenoid starts at temperatures above 16˚C,
is optimal at 22˚C - 25˚C and decreases from 30˚C [26].
Furthermore, the accumulation of lycopene blocks radia-
tion with values greater than 650 W/m2 thereby affecting
the homogeneous red color of the fruit [23]. With respect
to the proteins, plants grown under stressful conditions
may provide a storage form of nitrogen that is re-utilized
when the stress is over, the protein may also be synthe-
sized in response to salt stress, such as happens in crop
fertilization [48,49]. The presence of Zn, Fe and Cu in
this PC may be due to a metal-protein association, such
as the synthesis of isoenzymes of superoxide dismutase
linked to Zn and Cu which is a vegetable defense me-
chanism [25].
Hydroxycinnamic acids (p-coumaric, caffeic and fer-
ulic acids) and the minerals Ca and P and the trace ele-
ment, Mn, are associated to PC3. This PC could be asso-
ciated to antioxidant activity and to some minerals. Plants
synthesize antioxidant compounds such as the hydroxyl-
cinnamic acid (p-coumaric, caffeic and ferulic acids)
which frequently occur in foods as simple esters with
quinic acid or glucose, as well as flavonoids and phenol-
lic compounds to prevent oxidation reactions [50]. Fla-
vonoids and pheno lic acids are componen ts der ived fr om
the route of the pentose phosphate, which is involved in
maintaining and providing antioxidant defense functions
and they may accumulate because of a deficiency of N, P
and Fe [51]. The presence of P in this PC could be ex-
plained by the fact that an appropriate level of P is cru-
cial not only for normal growth and development of the
plant, but also for the synthesis of various secondary
metabolites [47]. Mn participates in the electron trans-
port of photosynthesis and Ca is a structural element of
the membrane through which the exchange of electrons
takes place [25].
PC4 groups the following variables together: total fi-
bre, pyruvic acid and chlorogenic acid. The percentage
of variance explained was 9.1% and the production sys-
tem was the agronomic variable associated to this PC.
PC5 explains 7.1% of variance, the variables associated
were K and Mg; which depend on date of collection and
production system. PC6 is the only PC that depends on
variety. It groups phenolic compounds and fumaric acid
together and it explains only 5.8% of the variance.
Each of the remaining PCs should be formed by at
least 4 variables in order to interpret their meaning cor-
rectly [21]. An intuitive interpretation could be taken
from reviews in the literature. Thus, PC5 is formed by K
and Mg which are related with the synthesis of carote-
noids and pigments. The application of K fertilizers,
especially lycopene, can increase the carotenoid conten ts
in tomatoes and Mg is a component of chlorophyll [26,
52]. Note that PC6 is the only principal component
where variety is the variable with the greatest load.
Some authors have used the metabolic compounds asso-
ciated to the second metabolites, as a quick classification
of samples according to their origin or biological prove-
nance [53].
Multivariate statistical analysis is a suitable tool for
the evaluation of extensive data tables but in some cases
it is essential the combination of several techniques to
obtain good results. The application of PCA-ANOVA
was an effective tool to analyze the chemical composi-
tion of tomato and to know the agronomic variables that
influence the composition. For the same maturity, the
organoleptic quality of tomato expressed as the sugar
content, organic acids and mineral content (Na) only
depends on interaction of production system and date of
[1] Giovanelli, G. and Paradiso, A. (2002) Stability of dried
and intermediate moisture tomato pulp during storage.
Journal of Agricultural and Food Chemistry, 50, 7277-
7281. doi:10.1021/jf025595r
[2] Madhavi, D.L. and Salunkhe, D.K. (1998) Production,
composition, storage, and processing. New York.
[3] Lavelli, V., Peri, C. and Rizzolo, A. (2000) Antioxidant
activity of tomato products as studied by model reactions
using xanthine oxidase, myeloperoxidase, and copper-
induced lipid peroxidation. Journal of Agricultural and
Food Chemistry, 48, 1442-1448. doi:10.1021/jf990782j
[4] Leonardi, C., Ambrosino, P., Esposito, F. and Fogliano, V.
(2000) Antioxidative activity and carotenoid and to-
matine contents in different typologies of fresh con-
sumption tomatoes. Journal of Agricultural and Food
Chemistry, 48, 4723-4727. doi:10.1021/jf000225t
M. H. Suárez et al. / Agricultural Sciences 2 (2011) 424- 431
Copyright © 2011 SciRes. Openly accessible at http://www.scirp.org/journal/AS/
[5] Giovanelli, G., Lavelli, V., Peri, C. and Nobili, S. (1999)
Variation in antioxidant components of tomato during
vine and post-harvest ripening. Journal of the Science of
Food and Agriculture, 79, 1583-1588.
[6] Van Boekl, M. and Jongen, W.M. (1997) Product quality
and food processing: How to quantify the healthiness of a
product. Cancer Letters, 114, 65-69.
[7] Abushita, A.A, Daood, H.G. and Biacs, P.A. (2000)
Change in carotenoids and antioxidants vitamins in to-
mato as a functional of varietal and technological factors.
Journal of Agricultural and Food Chemistry, 48, 2075-
2081. doi:10.1021/jf990715p
[8] Thompson, K.A., Marshall, M.R., Sims, C.A., Wei, C.I.,
Sargent, S.A. and Scott, J.W. (2000) Cultivar, maturity
and heat treatment on lycopene content in tomatoes.
Journal of Food Science, 65, 791-795.
doi:10.1111/j. 13 65-2621.2000.tb13588.x
[9] Grattan, S.R. and Grieve, C.M. (1999) Salinity—Min-
eral nutrient relations in horticultural crops. Scientia
Horticulturae, 78, 127-157.
[10] Hernández, M., Rodríguez, E. and Díaz, C. (2007a) Free
hydr oxycin namic a cids, lycope ne and color paramet ers i n
tomato cultivars. Journal of Agricultural and Food Che-
mistry, 55, 8604-8615. doi:10.1021/jf071069u
[11] Hernández, M., Rodríguez, E.M. and Díaz, C. (2007b)
Mineral and trace element concentrations in cultivars of
tomatoes. Food Chemistry, 104, 489-499.
[12] Hernández, M., Rodríguez, E.M. and Díaz, C. (2008b).
Chemical c omposi tion of tomat o (Lycopersi con es c ulen tum )
from Tenerife, the Canary Islands. Food Chemistry, 106,
1046-1056. doi:10.1016/j.foodchem.2007.07.025
[13] Hernández, M., Rodríguez, E. and Díaz, C. (2008a)
Analysis of organic acid content in cultivars of tomato
harvested in Tenerife. European Food Research and
Technology, 226, 423-435.
[14] AOAC (1999) Food composition; additives; natural con-
taminants. Official Methods of Analysis of AOAC, 2,
AOAC, Arlington.
[15] Prosky, L., Asp, N., Furda, I., De Vries, J., Schweizer, T.
and Harland, B. (1985) Determination of total dietary fi-
ber in foods and food products: Collaborative study.
Journal of Association of Official Analytical Chemists,
68, 677-679.
[16] Kujala, T.S., Loponen, J.M., Klika, K.D. and Pihlaja, K.
(2000) Phenolic and betacyanins in red beetroot (Beta
vulgaris) root: Distribution and effect of cold storage on
the content of total phenolic and three individual com-
pounds. Journal of Agricultural and Food Chemistry, 48,
5338-5342. doi:10.1021/jf000523q
[17] Fish, W., Perkins-Veazie, P. and Collins, J. (2002) A
quantitative assay for lycopene that utilizes reduced
volumes of organic solvents. Journal of Food Composi-
tion and Analysis, 15, 309-317.
[18] BOE (1995) Boletín Oficial del Estado. R.D. 2257/1994,
de 25 de noviembre, por el que se aprueban los métodos
oficiales de piensos o alimentos para animales y sus
materias primas. No. 52 de 2 de marzo de 1995, 7161-
[19] Li, B.W., Andrews, K.W. and Pehrsson, P. R. (2002) Indi-
vidual sugars, soluble, and insoluble dietary fiber con-
tents of 70 high consumption foods. Journal of Food
Composition and Analysis, 15, 715-723.
[20] Martínez-Valverde, I., Periago, M., Provan, G. and Ches-
son, A. (2002) Phenolic compounds, lycopene and anti-
oxidant activity in commercial varieties of tomato (Ly-
copersicon esculentum). Journal of the Science of Food
and Agriculture, 82, 323-330.
[21] Díaz, V. (2002) Técnicas de análisis multivariante para
investigación social y comercial. Ejemplos Prácticos
Utilizando SPSS, Versión 11, Madrid.
[22] Nielsen, S. (2003) Food analysis. 3rd Edition, Kluwer
Academic, New York.
[23] Giuntini, D., Graziani, G., Lercari, B., Fogliano, V.,
Soldatini, G.F. and Ranieri, A. (2005) Changes in carote-
noid and ascorbic acid contents in fruits of different to-
mato genotypes related to the depletion of UV-B radia-
tion. Journal of Agricultural and Food Chemistry, 53,
3174-3181. doi:10.1021/jf0401726
[24] Grierson, D. and Kader, A.A. (1986) The tomato crop, a
scientific basis for improvement. Springer, London.
[25] Azcón-Bieto, J. and Talon, M. (2008) Fundamentos de
fisiología y bioquímica vegetal. Interamericana McGraw-
Hill, Madrid.
[26] Dumas, Y., Dadomo, M., Di Lucca, G. and Grolier, P.
(2003) Effects of environmental factors and agricultural
techniques on antioxidant content of tomatoes. Journal of
the Science of Food and Agriculture, 83, 369-382.
[27] Adams, S.R., Cockshull, K.E. and Cave, C.R.J. (2001)
Effect of temperature on the growth and development of
tomato fruits. Annals of Botany, 88, 869-877.
[28] Rosales, M.A., Cervilla, L.M., Ríos, J.J., Blasco, B.,
Sánchez-Rodríguez, E., Romero, L. and Ruiz, J.M. (2009)
Environmental conditions affect pectin solubilization in
cherry tomato fruits grown in two experimental Mediter-
ranean greenhouses. Environmental and experimental
botany, 67, 320-327.
[29] Cuartero, J. and Fernández-Muñoz, R. (1999) Tomato
and salinity. Scientia Horticulturae, 78, 83-125.
[30] Bertin, N., Guichard, S., Leonardi, C., Longuenesse, J.J.,
Langlois, D. and Navez, B. (2000) Seasonal evolution of
the quality of fresh glasshouse tomatoes under Mediter-
ranean conditions, as affected by air vapour pressure
deficit and plant fruit load. Annals of Botany, 85, 741-
750. doi:10.1006/anbo.2000.1123
[31] Worthington, V. (2001) Nutritional quality of organic
versus conventional fruits, vegetables, and grains. The
Journal of Alternative and Complementary Medicine, 7,
61-173. doi:10.1089/107555301750164244
[32] Magkos, F., Arvaniti, F. and Zampelas, A. (2003) Or-
ganic food or food for thought? A review of the evidence.
International Journal of Food Sciences and Nutrition, 54,
M. H. Suárez et al. / Agricultural Sciences 2 (2011) 424- 431
Copyright © 2011 SciRes. http://www.scirp.org/journal/AS/Openly accessible at
357-371. doi:10.1080/09637480120092071
[33] Thybo, A.K., Edelenbos, M., Christensen, L.P., Sørensen,
J.N. and Thorup-Kristensen, K. (2006) Effect of organic
growing systems on sensory quality and chemical com-
position of tomatoes. LWT—Food Science and Technol-
ogy, 39, 835-843.
[34] Jin, S., Chen, C.C. and Plant, A.L. (2000) Regulation by
ABA of osmotic-stress-induced changes in protein syn-
thesis in tomato roots. Plant, Cell and Environment, 23,
51-60. doi:10.1046/j.1365-3040.2000.00520.x
[35] Senaratna, T., Touchell, D., Bumm, E. and Sixon, K.
(2000) Acetyl salicylic (Aspirin) and salicylic acid in-
duce multiple stress tolerance in bean tomato plants. The
Journal of Plant Growth Regulation, 30, 157-161.
[36] Pastori, G.M. and Foyer, C.H. (2002) Common compo-
nents, networks, and pathways of cross-tolerance to
stress. The central role of “redox” and abscisic acid-me-
diated controls. Plant Physiology, 129, 7460-7468.
[37] Rossi, F., Godani, F., Bertuzzi, T., Trevisan, M., Ferrari, F.
and Gatti, S. (2008). Health promoting substances and
heavy metal content in tomatoes grown with different
farming techniques. European Journal of Clinical Nutri-
tion, 47, 266-272. doi:10.1007/s00394-008-0721-z
[38] Poovaiah, B.W., Glenn, G.M. and Reddy, A.S.N. (1988)
Calcium and fruit softening: Physiology and biochemis-
try. Horticultural Reviews, 10, 107-152.
[39] Lee, S.K. and Kader, A.A. (2000) Preharvest and post-
harvest factors influencing vitamin C content of horti-
cultural crops. Postharvest Biology and Technology, 20,
207-220. doi:10.1016/S0925-5214(00)00133-2
[40] Haila, K., Kumpulainen, J., Hakkinen, U. and Tahvonen,
R. (1992) Sugar and organic acid contents of vegetables
consumed in Finland during 1988-1989. Journal of Food
Composition and Analysis, 5, 100-107.
[41] Young, T.E., Juvik, J.A. and Sullivan, J.G. (1993) Accu-
mulation of the components of total solids in ripening
fruits of tomato. Journal of the American Society for
Horticultural Science, 118, 286-292.
[42] Chapagain, B.P. and Wiesman, Z. (2004) Effect of potas-
sium magnesium chloride in the fertigation solution as
partial source of potassium on growth, yield and quality
of greenhouse tomato. Scientia Horticulturae, 99, 279-
288. doi:10.1016/S0304-4238(03)00109-2
[43] Zushi, K. and Matsuzoe, N. (1998) Effect of soil water
deficit vitamin C, sugar, organic acid, amino acid and
carotene contents of large-fruited tomatoes. Journal of
the Japanese Society for Horticultural Science, 67, 927-
933. doi:10.2503/jjshs.67.927
[44] Macheix, J.J., Fleuriet, A. and Billot, J. (1990). Fruit
phenolics. CRC Press, Boca Raton.
[45] Brandt, K., Giannini, A. and Lercari, B. (1995) Pho-
tomorphogenic responses to UV radiation III: A com-
parative study of UVB effects on anthocyanin and fla-
vonoid accumulation in wild type and aurea mutant of
tomato (Lycopersicon esculentum Mill.). Photochemistry
and Photobiology, 62, 1081-1087.
doi:10.1111/j. 17 51-1097.1995.tb02412.x
[46] Wilkens, R.T., Spoerke, J.M. and Stamp, N.E. (1996)
Differential responses of growth and two soluble pheno-
lics of tomato to resource availability. Ecology, 77, 247-
258. doi:10.2307/2265674
[47] Raghothama, K.G. (1999) Phosphate acquisition. Annual
Review of Plant Physiology and Plant Molecular Biology,
50, 665-693. doi:10.1146/annurev.arplant.50.1.665
[48] Asami, D.K., Hong, Y.J., Barrett, D.M. and Mitchell, A.E.
(2003) Comparison of the total phenolic and ascorbic
acid content of freeze-dried and air-dried marionberry,
strawberry, and corn using conventional, organic, and
sustainable agricultural practices. Journal of Agricultural
and Food Chemistry, 51, 1237-1241.
[49] Ashraf, M. and Harris, P. (2004). Potential biochemical
indicators of salinity tolerance in plants. Plant Science,
166, 3-16. doi:10.1016/j.plantsci.2003.10.024
[50] Matilla, P. and Kumpulainen, J. (2002). Determination of
free and total phenolic acid in plant-derived foods by
HPLC with diode-array detection. Journal of Agricul-
tural and Food Chemistry, 50, 3660-3667.
[51] Dixon, R.A. and Paiva, N.L. (1995). Stress-induced
phenylpropanoid metabolism. Plant Cell, 7, 1085-1097.
[52] Trudel, M.J. and Ozbun, J.L. (1971). Influence of potas-
sium on carotenoid content of tomato fruit. Journal of the
American Society for Horticultural Science, 96, 763-765.
[53] Fiehn, O. (2001). Combining genomics, metabolome ana l y -
sis, and biochemical modelling to understand metabolic
networks. Comparative and Functional Genomics, 2,
155-168. doi:10.1002/cfg.82
Cou: p-coumaric acid, Cu: copper, Lyc: lycopene, Zn:
zinc, Mn: manganese; Fer: ferulic acid, Caf: caffeic acid,
P: phosphorus, Pyr: pyruvic acid, Oxa: oxalic acid, Pro:
protein, Fe: iron, Fum: fumaric acid, Cit: citric acid, Fru:
fructose, Glu: glucose, Mal: malic acid, AA: ascorbic
acid, TF: total fibre, Phe: phenolic compounds, Mg:
magnesium, Na: sodium, Chlo, chlorogenic acid, K: po-
tassium, Ca: calcium