Low Carbon Economy, 2011, 2, 144-151
doi:10.4236/lce.2011.23018 Published Online September 2011 (http://www.SciRP.org/journal/lce)
Towards Green Remediation: Metal
Phytoextraction and Growth Analysis of Sorghum
bicolor under Different Agronomic Management
Guido Fellet, Luca Marchiol
Dipartimento di Scienze Agrarie e Ambientali, Università degli Studi di Udine, Udine, Italy.
Received February 25th, 2011; revised March 15th, 2011; accepted March 25th, 2011.
ABSTRACT
The role agronomy plays in the management of phytotechnologies is a significant example of the answers that the
agrosciences can offer to the issues of society in the field of Green Remed iation. This paper reports a study designed to
test how the principles of classical plant growth analysis can be used in the field of phytoremediation. In the framework
of a phytoremediation field trial set up in Torviscosa (Udine, Italy), Sorghum bicolor was grown receiving mineral fer-
tilization, organic amendment, or neither as control. Crop growth was examined following classical functional growth
analysis. Leaf area index (LAI), relative growth-rate (RGR) and shoot to weight ratio (SWR) showed how plants be-
haved in response to the treatments. Sorghum bicolor showed a poor potential for phytoremediation under our experi-
mental conditions. However, some parameters of classical crop growth analysis resulted potentially useful also in the
field of phytoremediation.
Keywords: Green Remedi at i o n, Heavy Metals, Phytoextraction, Field Experiment
1. Introduction
The heavy metals soil contamination is of great concern
due to its potential impact on human and animal health.
The traditional soil clean-up treatments take place by
means of technologies based on a physicochemical ap-
proach (e.g. solidifications and stabilizations, soil wash-
ing, electrokinetics, redox reactions). Such technologies
are costly, have substantial side effects and are power
consuming [1].
The Green Remediation (GR) is the practice of con-
sidering all environmental effects of a clean-up process
during each phase, and incorporating strategies to maxi-
mize the net environmental benefit of the clean-up. The
GR reduces the demand placed on the environment dur-
ing clean up actions, otherwise known as the “footprint”
of remediation, and avoids the potential for collateral
environmental damage [2].
The term “phytotechnologies” includes a variety of in
situ gentle techniques of environmental remediation.
Phytotechnologies can be applied to inorganic contami-
nants, such as heavy metals, metalloids, radioactive ma-
terials, and salts [3] and potentially offer efficient and
environmentally friendly solutions for the clean-up of
contaminated soils contributing to a sustainable land use
management [4].
Phytoextraction is one of the different options offered
by the phytotechnologies that typically is used to address
metals, metalloids and radionuclides [3]. Phytoextraction
involves the use of plants to remove contaminants from
the soil. The aerial biomass, which accumulated heavy
metals can be removed and disposed or burnt to recover
the metals. Biomass may require periodic harvesting and
proper disposal to avoid metal release when the plants
die or drop their leaves [3].
The amount of pollutants removed by the plants from
the contaminated soil is calculated by multiplying the
harvestable crop biomass and the concentration of the
pollutants within the biomass. The phytoextraction effi-
ciency for a given species is determined by 1) The plant
biomass production and 2) The metal bioaccumulation
factor (shoots to soil metal concentration ratio) [5].
Therefore, phytoextraction is essentially an agronomic
approach and its success depends ultimately on the ag-
ronomic practices (including the proper plant/crop choice)
that should be optimized in order to enhance the effi-
ciency of the soil clean-up process to the site specific

Towards Green Remediation: Metal Phytoextraction and Growth Analysis of Sorghum bicolor under Different 145
Agronomic Management
conditions.
The fundamental role of agronomy in the management
of phytoremediation systems is a significant example
about the role that agrosciences can offer to answer to the
issues of society in the perspective of GR [6].
Despite the intensive research in the last decade, an-
other widening gap between science and practicality lays
on the fact that very few field trials have been realized.
So far, unrealistic field scale extrapolations from ex-
perimental data from lab and greenhouse trials have
raised doubts about the feasibility of metal phytoextrac-
tion [7].
An up-to-date inventory of the field trials performed in
Europe in the years 2000-2008 is reported by Mench et
al. [8]. Regarding Italy, the field experiment of Torvis-
cosa is cited and—so far—it is the only phytoremedia-
tion experiment performed at field scale within an indus-
trial site [9]. As this trial was managed by our group, the
present study reports a study that shows 1) How the prin-
ciples of plant growth analysis [10] can be used in the
field of phytoremediation, and 2) Reports the uptake and
removal of elements recorded growing Sorghum bicolor
in a multi-metal contaminated soil.
2. Materials and Methods
The experiment at Torviscosa, NE Italy (45˚49′N, 13˚16′
E, 14 m above sea level, mean annual temperature
13.5˚C, average annual rainfall 1200 mm) was organized
in a randomized block design with two factors, species
and treatment, and three replications [9]. The substrate of
the experimental site is polluted by several heavy metals
and As; currently, this site and the surroundings are in-
cluded in the national priority list of polluted sites. In this
paper, the term soil will be referred to the heavy metals
rich substrate from Torviscosa even though the substrate
is not properly a soil.
The plant growth analysis and the results reported in
this paper are referred to Sorghum bicolor. The experi-
ment of Torviscosa basically dealt with different fertili-
zation strategies. The plants were subjected to three dif-
ferent agronomic treatments: control (CT, the local metal
enriched substrate), mineral fertilization (MF) and or-
ganic amendment (OA). More detailed information is
provided by Marchiol et al. [9].
Growth stages during the crop cycle were recorded
following Vanderlip [11]. Plant sampling started 40 days
after sowing. Plants were taken for analysis at 42 days,
56 days, 70 days, 84 days, 98 days and 112 days after
sowing. Six plants were collected from an area of 0.4 m2
from each plot. The plants were harvested with a shovel.
All plant fractions (roots, leaves, shoots and heads) were
washed carefully with demineralised water.
2.1. Chemical Analysis
Soil samples, collected to determine the main soil pa-
rameters and the metal concentrations, were dried at
room temperature for two days, sieved to <2 mm and
their particle size measured by the Bouyoucos hydrome-
ter method [12]. The pH of each sample was measured in
a soil/water slurry at a 1/2.5 ratio.
The plant specimens were divided into the following
fractions: root apparatus and aboveground biomass (fur-
ther on divided into roots and shoots for the plant growth
analysis indexes). Plant fractions were rinsed with abun-
dant tap water to remove dust or adhering particles and
carefully washed with deionized water.
The soil and plant samples were oven-dried at 105˚C
for 24 h and acid-digested in a microwave oven (CEM,
MARSXpress) according to the USEPA 3051 and 3052
method, respectively [13,14]. After mineralization, both
the soil and plant extracts were filtered (0.45 m PTFE),
diluted and analysed. Total Cd, Cr, Cu, Fe, Pb and Zn
contents in the extracts were determined by means of an
ICP-OES (Varian Inc., Vista MPX). The measurement of
As was done separately with a continuous-flow vapour
generation system that provided improved detection lim-
its for this element (VGA-77, Varian Inc.).
2.2. Statistical Analysis
Pearson’s correlation coefficient analysis was undertaken
to assess the relationship between the crop biomass yield
and its concentrations of As, Cd, Co, Cu, Pb, and Zn, and
between elements. The calculated coefficients were
tested for significance with Student-Newmann-Keuls’
test. Experimental data were subjected to a two-way
ANOVA (p < 0.05) to examine the effects of the agro-
nomic strategies. Differences between means were de-
termined using Student-Newmann-Keuls range test (p <
0.05).
The accuracy of the analytical procedure was checked
with standard solutions every 15 samples. Scandium was
used as internal standard. For the statistical analysis, in
samples where an element was not detected, its concen-
tration was assumed to be one-half of the respective lim-
its of detection [15]. Detection limits were: 3 μg·L –1 for
As, 1.5 μg·L–1 for Pb, 0.9 μg·L–1 for Cu, 0.4 μg·L –1 for
Co and 0.2 μg·L–1 for Cd and Zn.
2.3. Anti Microbial Functions
The classical approach to the plant growth analysis is
based on data collected at the different sampling dates
used to define the adaptation of plants to different agro-
nomic management strategies. Leaf area index (LAI),
relative growth rate (RGR) and shoot growth rate (SWR)

Towards Green Remediation: Metal Phytoextraction and Growth Analysis of Sorghum bicolor under Different
146
Agronomic Management
were chosen as indicators.
The basic parameters for the plant growth analysis
consisted of the green leaf area (A), dry biomass of roots
(R), stalks (S), leaves (L) and heads (H), and the total
plant biomass (W = R + S + L + H). The plant total leaf
area (LA) was estimated by measuring the green leaf area
of all leaves with a leaf area meter (LI-3100, LI-COR,
Lincoln, NE). R, S, L and H were measured after drying
the samples for 24 h at 105˚C in a forced-air oven.
The following standard growth analysis parameters
were calculated as follows [10]:
Leaf area index (LAI)
A
LP [dimensionless] (1)
Relative growth rate (RGR)

1ddWWT

[(g·g–1)d–1] (2)
Shoot weight ratio (SWR)
W
SW [dimensionless] (3)
where LA is the leaf area, P is the ground area covered by
the crop, W is the total plant dry mass, SW is the shoot dry
mass and T is time.
The means of the parameters were transformed to
natural logarithms to obtain the homogeneity of errors;
thereafter, they were subjected to the smooth curve-fit-
ting to describe the relationships of the indices versus
time. LAI data were interpolated with a logistic function,
while RGR and SWR data were fit with a first-order and
a second-order polynomial curve, respectively.
3. Results
3.1. Soil and Plant Biomass Pollutants Content
The basic soil parameters and the concentration of heavy
metals and As are given in Table 1.
The concentrations of As, Cd, Co, Cu, Pb and Zn in
the soil of the experimental site are above the recom-
mended permissible values according to Italian legisla-
tion (Decree 152/06). The high Fe content of the pyrite
cinders explains the concentration (about 9%) of this
micronutrient in the soil (Table 1). The average total Fe
content of temperate soils usually varies in the range 1%
- 5% [16].
Table 2 shows the output of Pearson correlation coef-
ficients (r) analysis between the aboveground biomass
yield of Sorghum bicolor and the concentration of a
given element in the biomass, and the correlation be-
tween elements recorded for each treatment.
Positive and significant relationships between shoot
biomass yield and the concentrations of As (MF p < 0.05;
OA p = 0.01), Co (MF p < 0.001; OA p = 0.01), Cu (MF
p < 0.05; OA p = 0.01) and Pb (MF p < 0.001; OA p =
Table 1. Characterization of the soil (0 - 25 cm) collected at
the field trial of Torviscosa. For reference the concentration
thresholds for As and heavy metals fixed by Italian and EU
legislation respectively, are provided.
Parameter Value Italy§ EU¶
Sand (%) 69.4
Silt (%) 25.4
Clay (%) 5.17
pH (H2O) 7.75
OC (g·kg–1) 9.10
CEC (cmol + kg–1) 5.5
E (mS·cm–1) 2.65
Fe (%) 9.02
As (ppm) 309† ± 20‡ 20 -
Cd (ppm) 4.29 ± 0.29 2 3
Co (ppm) 50.9 ± 2.31 20 -
Cu (ppm) 1527 ± 148 120 140
Pb (ppm) 233 ± 18 100 300
Zn (ppm) 980 ± 52 150 300
† n =20; ‡ Standard error; § Decree 152/06; ¶ 86/278/EU Directive.
0.01) were found (Table 2). The concentrations of some
elements recorded in the crop biomass were correlated
with those of others. In particular, there was a strong
positive relationship between As and Co (MF p < 0.001;
OA p < 0.001), between As and Cu (CT p < 0.001; MF p
< 0.001; OA p < 0.001) and between As and Pb (MF p <
0.001; OA p < 0.001). The concentration of Co had sig-
nificant positive correlations with the Cu in CT and OA
plants (both at p < 0.001), and of Pb in CT, MF and OA
plants at p < 0.001. Finally, Cu correlated only with Pb
(CT p < 0.001; MF p < 0.01; OA p < 0.001) (Table 2)
whereas Cd did only with Cu in OA plants (p < 0.05) and
Zn in respectively CT (p < 0.001) and OA (p < 0.05)
plants (Table 3).
3.2. Plant Growth Analysis
The accumulation of the dry matter in the plant fractions
during the growth cycle is reported in Figure 1. The dif-
ferent treatments had significant effects on the accumula-
tion of dry matter in the root system (Figure 1a). Since
the early stages, the MF plants responded to the readily
available nutrients supplied with fertilizers and reached
the highest level of dry matter in the roots (4.80 g·plant–1)
which is more than twice that of the OA plants (2.08
g·plant–1). The more developed root systems, the greater
availability of water and mineral nutrients.
In MF plants, compared to OA plants, a significantly
higher accumulation of dry matter in the stalks was ob-
erved (11.2 and 6.16 g·plant–1, respectively) (Figure 1(b)). s

Towards Green Remediation: Metal Phytoextraction and Growth Analysis of Sorghum bicolor under Different
Agronomic Management
147
Table 2. Pearson’s correlation coefficient (r) between biomass yield and concentration of elements in the shoots, significant
correlations are noted by * p < 0.05; ** p < 0.01; *** p < 0.001.
N = 21 Treatment Shoot biomassAsShoots CdShoots CoShoots CuShoots PbShoots
CT –0.354
AsShoots MF 0.543*
OA 0.681**
CT –0.296 0.372
CdShoots MF –0.188 –0.197
OA –0.012 0.162
CT –0.149 0.459 0.278
CoShoots MF 0.757*** 0.812***–0.208
OA 0.827** 0.842***0.298
CT –0.467 0.712***0.138 0.753***
CuShoots MF 0.549* 0.487***0.328 0.416
OA 0.574** 0.829***0.494* 0.831***
CT –0.062 0.391 0.247 0.825***0.679**
PbShoots MF 0.790*** 0.853***–0.145 0.951***0.536*
OA 0.668** 0.835***0.425 0.898***0.961***
CT –0.058 0.461 0.927***0.296 0.132 0.221
ZnShoots MF 0.025 –0.139 0.769***–0.24200.234 –0.164
OA –0.251 –0.158 0.551* –0.044 0.115 –0.013
Table 3. Biomass yield and amount of elements removed by CT, MF and OA plants of S. bicolor. Data within a column not
followed by the same letter indicates significant differences dete r mined by the Student Newman Keuls test.
Element removal
Biomass yield As Cd Co Cu Pb Zn
Treatment
t·ha–1 g·ha–1 g·ha–1 g·ha–1 g·ha–1 g·ha–1 g·ha–1
CT 1.54 c 7.47 a 0.39 b 0.87 b 40.1 a 4.40 a 147 c
MF 22.1 a 110 a 5.83 a 16.5 a 644 a 78.1 a 1,223 b
OA 16.9 b 97.1 a 4.43 a 11.5 ab 681 a 86.0 a 1,944 a
ANOVA† 0.0000*** 0.0540ns 0.0094** 0.0438* 0.0628ns 0.1192ns 0.0001***
† p values
As expected, CT plants suffered from the poor quality of
the native substrate, storing less than 80% of dry matter
in roots, and less than 17% in stalks, compared to MF
plants.
The biomass accumulation in the leaves was signifi-
cantly higher in MF plants than in OA plants (Figure
1(c)). However, this difference was less evident than that
reported for roots and stalks.
Finally, we recorded the dynamics of the transfer of
dry matter from the vegetative parts of the plants towards
the reproductive structures. No difference was observed
between MF and OA plants (Figure 1(d)), while CT
plants did not succeed in reaching the flowering stage.
Figure 2 reports the growth analysis parameters. The
LAI values changed during plant growth from 0.09 to
0.69 in CT plants, from 0.64 to 6.11 in MF plants and
from 1.09 to 3.15 in OA plants. Plotting LAI values ver-
sus time yielded distinct curves, with lower canopy
build-up for CT plants (Figure 2(a)). The growth of S.
bicolor was affected strongly by the CT conditions; in
fact, such plants did not grow beyond the vegetative
stage, showing remarkable growth retardation. From
growth stage GS2 (fourth leaf), the LAI curve of MF and
OA plants diverged, increasing the differences starting
from the top of the curve. OA plants grew faster than MF
plants, reaching growth stage GS5 (bloom) 14 days be-
fore the MF plants did (Figure 2(a)).
The biomass yield of a plant depends on the size of the
leaf canopy, the biochemical activity of the leaves, and
the canopy persistence. Therefore, the longer vegetative
phase of the MF plants contributed to their greater bio-
mass production by delaying the senescence of the can-
opy (Figure 2( a) ).
The RGR functions—which express the increase in
plant weight per unit of weight and time—decreased
linearly over the sampling period for all three treatment
groups (Figure 2(b)). However, while the interpolating
functions have a similar slope in MF and OA plants (m =
–0.047 and –0.044, respectively), the gradient of the
RGR function of CT plants is lower (m = –0.002), indi-
cating a very slow growth rate. Note that RGR, calcu-
lated by Equation (2), indicates the instantaneous values

Towards Green Remediation: Metal Phytoextraction and Growth Analysis of Sorghum bicolor under Different
148
Agronomic Management
Figure 1. (a) Root, (b) stalks, (c) leaves and (d) heads bio-
mass dry matter of CT, MF and OA plants of Sorghum bi-
color. Mean vertical bars represent standard error.
of the parameter during the growth cycle of sorghum;
which is why the data are omitted from Figure 2(b).
Figure 2(c) shows the curves for SWR, which is a
measure of the shoots biomass as a proportion of the total
plant biomass. This is a fundamental parameter in a phy-
toremediation project, as the agronomic management
should provide the maximum biomass yield in order to
remove the greatest amount of metals from the soil.
Figure 2. (a) Leaf area index (LAI), (b) Relative growth rate
(RGR) and (c) Shoot weight ratio (SWR) as function of time
for CT, MF OA plants of S. bicolor. Following Vanderlip
[11] growth stages GS 2 (4th Leaf), GS 5 (Boot) and GS 9
(Physiological maturity) are indicated with “*” and hori-
zontal bars. Data were fitted using logistic (A) and polyno-
mial functions (B,C).
Functions:
(A)
CT: a = 0.59; b = 227.1; c = 18.6; r2 = 0.91
MF: a = 5.76; b = 214.8; c = 19.3; r2 = 0.81
OA: a = 3.71; b = 201.8; c = 16.4; r2 = 0.88
[( )]
[( )]2
4
[1 ]
xb
c
xb
c
e
ya e






(B)
CT: y = 0.52 – 0.0018x; m = –0.00
MF: y = 11.34 – 0.044x; m = –0.047
OA: y = 9.96 – 0.041x; m = –0.044
(C)
CT: y = –3.66 + 0.040x – 9.11x2; r2 = 0.88
MF: y = –3.86 + 0.043x – 9.83x2; r2 = 0.89
OA: y = –4.52 + 0.051x – 1.18x2; r2 = 0.93

Towards Green Remediation: Metal Phytoextraction and Growth Analysis of Sorghum bicolor under Different 149
Agronomic Management
SWRmax indicates the time of highest biomass yield dur-
ing the crop cycle, providing information to guide the
harvest scheduling. Due to growth retardation, the CT
plants reached SWRmax (0.80) at GS5, whereas the MF
and OA plants reached GS5 phase in the ascending
branch of the SWR curve, and SWRmax was 0.86 and
0.91, respectively (Figure 2(c)).
3.3. Removal of elements by crop removal
The maximum removal of pollutants is achieved by har-
vesting the plant biomass when the maximum biomass is
reached. The values of biomass yield of sorghum ob-
tained in response to the agronomic treatments are
showed in Table 3. We recorded an amount of above-
ground biomass equivalent to 1.54, 22.1 and 16.9 t of dry
matter per hectare for CT, MF and OA plants, respec-
tively.
The amounts of elements removed from the soil were
calculated by multiplying the average concentrations of
elements in the shoots, reported in Marchiol et al. [9],
and the biomass yield (Table 3). Being derived from the
plant biomass, this parameter mainly reflects the effects
of the different fertilizations observed for the biomass
yield. In fact, the input of mineral fertilizers and the or-
ganic amendment, having improved the nutritional status
of the plants, allowed the removal of greater amounts of
elements than in the control treatment. This difference
was statistically significant in the case of Cd, Co and Zn
(Table 3). The ANOVA did not indicate a significant
effect of the different crop management in the case of As
and Cu. Data for MF and OA plants have a certain vari-
ability that has hidden the effects of the treatments. De-
spite this disturbance, the p values obtained from the
ANOVA for As (p = 0.054) and Cu (p = 0.062) are very
close to the standard significance level (0.05) (Table 3).
The biomass of OA plants removed significantly more
Zn than the MF plants, 1944 g·ha–1 vs. 1223 g·ha–1.
These values are about 10-fold the uptake of Zn recorded
for CT plants.
4. Discussion
A great deal of progress has been achieved at experi-
mental level for several approaches offered by phy-
totechnologies. Several comprehensive reviews by M-
cGrath & Zhao [5], Pilon-Smits [17], Vangronsveld et al.
[18], Wu et al. [1] and Krämer [19], summarized many
important aspects of this novel plant-based technology
and the achievements of the scientific community. Sig-
nificant and decisive advances are still expected from
research. At this moment we are still far from being able
to apply on a large scale the phytotechnologies.
The process of phytoextraction is based substantially
on plant-soil interactions where the mass transfer of an
inorganic pollutant from the bulk soil to the plant bio-
mass is promoted. This implies that the management of
the two elements of the system (plant and soil) should
have effects on the efficiency of the process. As phy-
toremediation is essentially an agronomic approach, its
success depends ultimately on standard agronomic prac-
tices such as plant species selection, specific soil man-
agement practices, fertilization, irrigation and weed and
pest control [20,8]. Moreover, it is a long-term remedia-
tion effort and many cropping cycles to decontaminate
metal pollutants to acceptable levels are required. Ap-
propriate and effective schemes of crop rotation should
be available.
Here, we present the data collected during the first
year of the field study which ran at Torviscosa. We ob-
served the phytoremediation potential of S. bicolor in
polycontaminated soil. The plants grew in polluted soil
containing six elements above the threshold allowed by
the Italian law.
The dearth of descriptions of field experiments on
phytoremediation makes it difficult to discuss our data.
Moreover, the performances of a plant species in differ-
ent field experiments will be different, for specific condi-
tions of soil and pollution can significantly affect the
metal bioavailability [21].
However, we tried to compare our data with the few
results in the literature on phytoremediation experiments
in which crops have been studied in field trials. We did
not attempt a direct comparison of experimental data
obtained from different trials but rather a) An evaluation
of the capability of our experimental design compared to
others and b) The potential of the phytoremediation tech-
nique at the experimental site of Torviscosa.
Keller et al. [22] studied Brassica juncea, Zea mays,
Nicotiana tabacum, stands of Salix sp. and Thlaspi
caerulescens cultivated over two years in a site polluted
by smelter emissions. In other experiments, the accumu-
lation of As and trace metals in Helianthus annuus [22]
and in Hordeum distichum, x Triticosecale, Brassica
napus and Brassica carinata [23] were studied.
Madejón et al. [24] observed an As extraction of about
3 g·ha–1 by growing H. annuus in a soil polluted by a
mine spill. In our case, sorghum removed about 220
g·ha–1 of As. The removal of Cd calculated by Keller et
al. [22] was 6.95 g·ha–1, 41.7 g·ha–1 and 9 g·ha–1 for B.
juncea, N. tabacum and Z. mays, respectively, while the
amount of Cd removed from the soil at Torviscosa was
5.62 g·ha–1. Lower performances were recorded by Sori-
ano and Fereres [23] in H. distichum (1.41 g·ha–1), x Tri-
ticosecale (1.95 g·ha–1), B. napus (2.08 g·ha–1) and B.
carinata (2.18 g·ha–1).

Towards Green Remediation: Metal Phytoextraction and Growth Analysis of Sorghum bicolor under Different
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Agronomic Management
We have found no data in the literature with which to
compare our data for Co removal by crops. We recorded
a removal of Cu within the range 644 - 820 g·ha–1, while
the values reported by Soriano and Fereres [23] were
lower also in this case; H. distichum 57.2 g·ha–1, x Triti-
cosecale 51.2 g·ha–1, B. napus 36.2 g·ha–1 and B. carinata
37.1 g·ha–1. The uptake of Cu calculated by Keller et al.
[22] was 146, 474 and 163 g·ha–1 for B. juncea, N. ta-
bacum and Z. mays, respectively.
The removal of Zn computed from the data collected
by Keller et al. [22] was 894 g·ha–1 for B. juncea, 1,834
g·ha–1 for N. tabacum and 1998 g·ha–1 for Zea mays. Data
for Zn removal provided by Soriano and Fereres [23]
were the following: 1070 g·ha–1 for H. distichum, 923
g·ha–1 for x Triticosecale, 902 g·ha–1 for B. napus and
797 g·ha–1 for B. carinata. Our sorghum plants showed
the same potential. However, in absolute terms, we ex-
tracted quite a small amount of elements [9].
More recently, Zhuang et al. [25] provided further in-
formation regarding the potential for phytoremediation of
sorghum in multi-contaminated soils working with dif-
ferent cultivars of sorghum.
In our experiment, due to the metal-binding capacity
of the organic matter, we had expected to observe a
lower concentration of metals in the plants grown in the
manure amended plots. This occurred for some elements
but not for others. The same managing strategy in a
polycontaminated soil seemed not to have the expected
effects on metal uptake. On the other hand, most metal-
contaminated soils contain more than one metal [7]. This
aspect poses further technical problems for the agro-
nomical management of phytoremediation projects.
5. Conclusions
In the perspective of the extensive application of phy-
toremediation it is of great importance to understand how
the efficiency of the process can be improved through the
crop management practices.
In a phytoremediation field trial we tested the effects
induced by two different agricultural practices on the
process of metal phytoextraction. Some parameters of
classical crop growth analysis were used to study the
adaptation and the response of plants to the experimental
conditions in terms of biomass production and growth
rate. This approach can be used profitably in phytoreme-
diation projects to predict the harvest scheduling of the
crops.
Under our experimental conditions Sorghum bicolor
showed a poor potential for phytoremediation. However,
in terms of element removal, it was recorded a positive
feedback induced by the agronomic treatments. Since in
the experimental design did not consider any practice
specifically designed to enhance the bioavailability of the
trace metals (e.g. chelating agents), we can assume that
sorghum could be potentially more effective than what
we observed.
Currently, phytoremediation is not yet a market-
available green technology. Further investments of intel-
lectual and financial resources will promote a real appli-
cative potential to phytoremediation. More effort should
be devoted to develop medium/long term field trials with
the twofold objective to test and optimize agricultural
practices to make phytoremediation faster and more ef-
fective.
6. Acknowledgements
This research was part of the project “Phytoextraction of
heavy metals in sites polluted by industrial activities:
efficiency of soil-plant system”, supported by the Italian
Ministry of University and Research (N. 2003072589).
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