European Journal of Soil Science, June 2012, 63, 315–324
doi: 10.1111/j.1365-2389.2012.01439.x
Chemical properties of humic matter as related
to induction of plant lateral roots
L . P . C a n e l l a sa , L . B . D o b b s sa , A . L . O l i v e i r ab , J . G . C h a g a sa , N . O . A g u i a ra ,
V . M . R u m j a n e k c , E . H . N o v o t n y d , F . L . O l i v a r e s a , R . S p a c c i n i e,f & A . P i c c o l o e,f
a Núcleo
de Desenvolvimento de Insumos Biológicos para a Agricultura (Nudiba), Universidade Estadual do Norte Fluminense Darcy
Ribeiro (UENF) - Av. Alberto Lamego 2000, Campos dos Goytacazes 28602-013, Brazil, b Laboratório de Química do Núcleo de
Criminalística da Superintendência da Polícia Federal no Estado do Rio de Janeiro, Av. Rodrigues Alves, 1, Rio de Janeiro 20081-250,
Rio de Janeiro, Brazil, c Departamento de Química, Universidade Federal Rural do Rio de Janeiro, BR 465 km 7, Seropédica 23890-000
RJ, Brazil, d Embrapa Solos - Rua Jardim Botânico, 1024, Rio de Janeiro 22460-000, Rio de Janeiro, Brazil, e Dipartimento di Scienza del
Suolo, della Pianta, dell’Ambiente e delle Produzioni Animali (DiSSPAPA), Università di Napoli Federico II, Via Università 100, 80055
Portici, Italy, and f Centro Interdipartimentale per la Risonanza Magnetica Nucleare (CERMANU), Università di Napoli Federico II, Via
Università 100, 80055 Portici, Italy
Summary
A series of humic matter samples isolated from a soil sequence, different oxisols, size-fractionated from a
vermicompost humic acid and subjected to chemical modifications, were characterized by CPMAS 13 C-NMR
spectroscopy. The relative signal areas in chemical shift regions of NMR spectra of the four sets of samples
were analysed by principal component analysis (PCA). Hierarchical cluster analysis (HCA) was applied to
build a classification model, which allowed the recognition of humic matter according to its origin. The
relationship between carbon species and biological activity of humic acids, as promoters of lateral root
emergence, was obtained by applying PLS multivariate analysis. This showed that lateral root emergence
was mostly related to NMR parameters such as the hydrophobicity index (HB/HI) and the 40–110 and
160–200 ppm chemical shift regions (hydrophilic carbon HI), while the content of hydrophobic (HB) carbon in
humic samples was negatively correlated with induction of lateral root hair. Our results represent a step further
in the structure-bioactivity relationship of natural humic substances and confirm their role as plant root growth
promoters.
Introduction
Humic substances (HS) regulate the global carbon and nitrogen
cycles and affect the growth of plants and microorganisms. Direct
effects of HS on plant metabolism have been widely reported (for a
recent review see Nardi et al., 2009). Their use as a plant growth
promoter is being progressively adopted by farmers despite the
fact that the mechanisms through which HS influence plant physiology and growth are not completely understood. Furthermore,
manufacturing technologies for controlling HS activity have not
yet been developed because of their molecular complexity (Nebbioso & Piccolo, 2011). Establishing a relationship between structural composition and biological activity of HS is important for
the development of biological resources to be applied to modern
sustainable agriculture. However, this is no simple task because of
Correspondence: L. P. Canellas. E-mail: [email protected]
Received 22 August 2011; revised version accepted 10 February 2012
© 2012 The Authors
Journal compilation © 2012 British Society of Soil Science
the humic molecular complexity, as well as the plethora of plant
biochemical processes modified by HS applications.
Cross-polarization magic angle spinning (CPMAS) 13 C-NMR
spectroscopy has been increasingly applied in HS studies. The
major advantage of CPMAS 13 C-NMR spectroscopy lies in the
rapid and non-destructive acquisition of quantitative structural
information on carbon forms present in environmental samples without the need for extensive pretreatment (Smernik &
Oades, 1999). Piccolo (2002) showed that HS are not crosslinked domains of unknown macro-polymers but are complex
supramolecular structures of different plant, animal and microbial biochemical products at various stages of decomposition and
held together by weak forces. Major molecular components of
HS are aliphatic acids, ethers, esters, alcohols, aromatic ligninderived fragments, polysaccharides and polypeptides, which may
be also easily observed by 13 C-CPMAS and other NMR spectroscopic techniques (Nebbioso & Piccolo, 2011). Furthermore,
Šmejkalová et al. (2008) showed by NMR spectroscopy that
315
316 L. P. Canellas et al.
principal component analysis (PCA) was able to identify the main
similarities and dissimilarities among molecular structural characteristics of a number of different humic materials.
Many studies have confirmed the hypothesis of a direct effect
of HS on plant physiology (Asli & Neumann, 2010; Mora et al.,
2010), and in particular on the development of lateral roots
(Canellas et al., 2002; Schmidt et al., 2007; Zandonadi et al.,
2007; Canellas et al., 2008a). Lateral roots branch from primary
roots and greatly increase roots’ total surface area. According to
Nibau et al. (2008), the responsibility of each stage of lateral root
development is attributed to the auxin hormone. Like auxins, HS
induce plasma membrane (PM) H+ -ATPase activities (Canellas
et al., 2002). These enzymes cleave ATP molecules and generate
an electrochemical gradient that provides energy to secondary
cell transporters. The main function of the PM H+ -ATPase is
to generate a proton electrochemical gradient, thereby providing
the driving force for the uptake and efflux of ions and metabolites
across the PM (Sze, 1985). In fact, it has been shown that HSinduced H+ pump activity (Canellas et al., 2002) might play a key
role in cell expansion in a similar way to that described for the acid
growth mechanism (Rayle & Cleland, 1992). The modification of
root system architecture by HS may stimulate uptake of water and
nutrients by plants, thereby facilitating adaptation and survival
in poorly fertile or arid soils. In this respect, Baigorri et al.
(2010) reported that multivariate analysis was very efficient in
discriminating among different groups of HS that were thought to
favour lateral root growth.
A deeper knowledge of the structural features that characterize
HS is required to understand a number of processes occurring in
plant-humic matter interactions better. In previous work, Canellas
et al. (2008) found that humic acids isolated from a tropical soil
sequence induce lateral root emergence and H+ -ATPase activity
and these biological activities were correlated with the degree of
humification, evaluated by electron paramagnetic resonance and
fluorescence index. These authors showed that all humic acids
isolated from different Oxisols were able to induce root growth
and the enhancement was significantly correlated with humic acid
hydrophobicity. Although a linear relationship between humic
acids, hydrophobicity and their bioactivity was found (Canellas
et al., 2010), this does not depend on the hydrophobic C species
present (Canellas et al., 2011). While these results point to a
possible route that will lead to a structure/activity relationship
between humic matter and induction of lateral root emergence,
the conclusions cannot be generalized without suitable statistical
validation.
Here we used a set of different humic materials (n = 29)
and applied multivariate analysis (PCA and PLS) to simplify
interpretation of CPMAS 13 C-NMR spectra. Our aim was to
determine whether CPMAS 13 C NMR spectra of HS may be used
to distinguish the origin of HS samples and correlate lateral root
emergence with humic chemical composition.
Materials and methods
Soils
Soil samples were obtained from two sets of distinct experiments.
One set of samples (SS) was collected from the surface horizon
of a soil sequence located in the northern region of Rio de
Janeiro State, Brazil. The complete description of these samples
can be found in Canellas et al. (2008a) but location and some
selected properties are shown in Table 1. The second set (Ox) was
Table 1 Origin and location of humic material and some selected properties of soils used for humic acid extraction
Soil Origin (Brazil)
Code
Petrópolis, RJ
Italva, RJ
Italva, RJ
Itaperuna, RJ
Itaperuna RJ
Campos dos Goytacazes, RJ
SS1
SS2
SS3
SS4
SS5
SS6
Nova Lima, MG
Nova Friburgo, RJ
Mendes, RJ
Brasília, DF
Santo Ângelo, RS
Vacaria, RS
Campos dos Goytacazes
Size fraction humic acids from
vermicompost
Chemical derivatives of HSs from
vermicompost
Ox1
Ox2
Ox3
Ox4
Ox5
Ox6
Ox7
SF
D
Classification
Soil Sequence (SS)
Lithic Udorthent
Vertici Argiustoll
Typic Calciustoll
Ultic Paleustalf
Typic Kanhaplustult
Haplustox
Oxisols (OX)
Rhodic humic Hapludox
Sombrihumox
Hapludox
Rhodic Hapludox
Haploperox
Rhodustalf
Xanthic hapludox
—
pH
OC
/ kg−1
Total N
/ kg−1
Clay
/ kg−1
HA
/ kg−1
5.4
6.6
8.8
5.8
6.2
5.1
44
16
26
12
14
10
2.5
1.8
4.4
1.5
1.4
0.9
132
470
420
270
240
250
25.0
2.4
3.4
1.4
2.0
1.1
5.8
5.2
5.3
5.1
6.1
6.8
5.4
—
12.8
29.5
12.5
25.4
43.0
10.7
8.6
—
1.8
3.3
1.6
1.2
3.9
2.0
1.0
—
280
490
490
750
720
620
380
—
0.02
0.08
0.06
0.07
0.05
0.06
0.09
—
Canellas et al. (2010)
—
—
—
—
—
Dobbss et al. (2010)
References
Canellas et al. (2008a)
Canellas et al. (2009)
© 2012 The Authors
Journal compilation © 2012 British Society of Soil Science, European Journal of Soil Science, 63, 315–324
Structure-bioactivity relationship of humic substances
collected from different Brazilian Oxisols (Canellas et al., 2009).
Soil properties are presented in Table 1 and were determined
after air drying and sieving at 2 mm. Organic carbon content
(Corg, g kg−1 ) was determined by a modified Walkey-Black
procedure (Yeomans & Bremner, 1988). Total nitrogen (N) was
determined by the Kjeldahl method (Bremner & Mulvaney, 1982),
and other soil chemical properties were determined according to
the Embrapa Soil Handbook (1997).
Vermicompost
A vermicompost was obtained from a mixture of plant residues
from Panicum maximum Jacq. and cattle manure 5:1 (v:v). The
organic residues were mixed and earthworms (Eisenia foetida,
Savigny, 1826) were added at a ratio of 5 kg earthworms per m3
of organic residue. A bed of worms and organic residues was first
prepared in a container and additional layers of organic residues
were periodically placed on the bed until it was 50 cm high. At
the end of the transformation process (3 months after addition
of the last organic residues), worms were moved into fresh
organic residue (plant + cattle manure) and placed in a corner of
the container. The organic matter characteristics of the resulting
vermicompost were: pH 7.8, 46.5 g kg−1 total organic carbon and
17.3 g kg−1 HA carbon. HA were isolated from vermicompost and
purified as reported elsewhere (Canellas et al., 2002).
Extraction and purification of HA
Humic acids were extracted and purified as described by Canellas
et al. (2002). Briefly, 50 g of soil or vermicompost were mixed
with 500 ml of 0.5 m NaOH, under a N2 atmosphere. After
shaking for 12 hours, the suspension was centrifuged at 5000 g,
and the supernatant was acidified to pH 1.5 with 6 m HCl to obtain
an HA precipitate. The HA was again solubilized with 1 m NaOH
and precipitated with 6 m HCl. This purification procedure was
repeated three times. The HA residue was then added to 100 ml
of a dilute HF-HCl solution (5 ml 36% HCl + 5 ml 48% HF l−1 )
and shaken overnight. After centrifuging (5000 g) for 15 minutes,
the HA residue was repeatedly washed with deionized water,
dialyzed against deionized water using a 1 kDa-cut-off membrane
(Thomas Scientific, Inc., Swedesboro, NJ, USA) until-chloride
free and finally freeze-dried.
Fractionation of a vermicompost HA by preparative high
performance size exclusion chromatography (HPSEC)
The HPSEC mobile phase consisted of a 10 mm CH3 CO2 Na,
5 mm KCl and 1 mm CH3 CO2 H milli-Q water solution adjusted
to pH 7.0 with 100 mm KOH. The same solution was used to
dissolve the humic acids to a concentration of 600 mg l−1 . The
humic solution was filtered through glass microfibre filters (Whatman GF/C) and loaded into a rheodyne rotatory injector, equipped
with a 5-ml sample loop. The HPSEC system consisted of a Gilson
auto-sampler model 231, a Gilson 305 pump, a preparative Biosep
317
SEC-S-2000 (600 × 21.2 mm id) column, preceded by a Biosep
SEC-S-2000 guard column (78.0 × 21.2 mm id), both from Phenomenex (Torrance, CA, USA), a Gilson 116 UV detector set at
280 nm, and a Gilson FC205 fraction collector, to collect automatically humic fractions continuously. The elution flow-rate was
set at 1.5 ml min−1 and all chromatographic runs were automatically recorded by Unipoint Gilson Software (Gilson Scientific Ltd,
Luton, UK). The six isolated size-fractions (SF) were first freezedried to reduce their volume, resuspended in 5 ml of deionized
water, dialyzed (Spectra/Por 6 dialysis tube, 1 kD MW cut-off)
against deionized water, and again freeze-dried. Of the 642 injections of HA solution (1926 mg), the masses measured for the
six isolated size-fractions (SF1–SF6) were 492.6, 168.6, 369.1,
567.9, 61.0 and 136.6 mg, respectively, for a total recovery of
93% (1798 mg) of initial HA mass.
Chemical modifications of HA from vermicompost
(derivatization)
The complete description of chemical reactions used to modify HA
can be found in Dobbss et al. (2010). Briefly, we conducted the
following reactions: (i) acidic oxidation with KMnO4 (D1) using
20 ml 10 mm KMnO4 and 0.25 M H2 SO4 solution; (ii) basic
oxidation with KMnO4 (D2) carried out in 20 ml 10 mm KMnO4
and 0.5 m KOH solution; (iii) reduction with sodium borohydride
(D3); (iv) alkaline methanolic hydrolysis (D4) with 20 ml 1 m
KOH-CH3 OH solution under reflux at 75◦ C for 1 hour; (v) acid
hydrolysis with H2 SO4 (D5) with 25 ml 2 m H2 SO4 solution
under reflux at 60◦ C for 2 hour; (vi) acid hydrolysis by 2 m HCl in
Dioxane (D6); (vii) extraction of free lipids (D7) where unbound
alkyl components were extracted by dichloromethane/methanol
(2:1, v:v); and (viii) methylation (D8) obtained by reaction with
methyl iodide through phase-transfer catalysis. All HS derivatives
(the residual matter of the different reactions) were submitted to
dialysis against distilled water (1 kDa MW cut-off) followed by
freeze-drying.
NMR spectroscopy
Cross-polarization magic angle spinning (CPMAS)-13 C-NMR
spectra were acquired with a Bruker AVANCE 300 (Bruker
Daltonics Inc., Billerica, MA, USA), equipped with a 4-mm widebore magic angle spinning probe, operating at a 13 C resonating
frequency of 75.475 MHz, and a rotor spin rate of 5000 ± 1 Hz.
Samples were packed in 4-mm zirconia rotors with Kel-F caps;
1510 data points were collected over an acquisition time of 20 ms,
a recycle delay (RD) of 3.0 s, and 2000 scans. A variable contacttime pulse sequence was applied with a 1 H ramp to account for
heterogeneity of the Hartmann-Hahn condition at fast rotor spin
rates (Šmejkalová et al., 2008). An average spin lock frequency of
60 MHz was applied during the ramped cross-polarization time.
Contact time was varied from 0.010 to 7 ms. Spectra processing
was carried out with Topspin software (Bruker Daltonics Inc.).
All free induction decays were transformed by applying first a
© 2012 The Authors
Journal compilation © 2012 British Society of Soil Science, European Journal of Soil Science, 63, 315–324
318 L. P. Canellas et al.
16k zero filling and then an exponential filter function with a line
broadening of 100 Hz.
Spectra were integrated at the chemical shift intervals of 200 to
160 ppm (carbonyls of ketones, quinones, aldehydes and carboxy
groups), 185 to 160 ppm (carbonyls of aldehydes and carboxy
groups), 160 to 110 ppm (aromatic and olefinic carbons), 110 to
90 ppm (anomeric carbons), 90–65 ppm (C-O systems, such as
alcohols and ethers), 65 to 44 ppm (C-N groups and complex
aliphatic carbons), and 44 to 0 ppm (alkyl carbons). The areas
pertaining to alkyl (44 to 0 ppm) and aromatic/olefinic (160
to 110 ppm) carbons were summed to represent hydrophobic
carbons (degree of hydrophobicity, HB). Similarly, the areas
in the intervals related to polar carbons (200 to 160, 110 to
90 and 90 to 5 ppm) were summed to represent the degree of
carbon hydrophilicity (HI). The aromaticity degree was calculated
by dividing the areas of aromatic and olefinic carbons (160 to
110 ppm) by the area of the spectrum from 0 to 160 ppm and
multiplying by 100.
Effects on plant roots: emergence of lateral roots
Maize seeds (Zea mays L. var.UENF 506) provided by UENF
Plant Science Department were surface-sterilized by soaking in
0.5% NaClO for 30 minutes, followed by rinsing and then soaking
in water for 6 hours. The seeds were then sown on wet filter
paper and germinated in the dark at 28◦ C. Four-day-old maize
seedlings with roots approximately 0.5 cm long were transferred
into a solution containing 2 mm CaCl2 and either 0, 12.5, 25.0,
50.0, 100.0, 150.0, 200.0, 275.0 or 400.0 mg of HS or HA l−1
(pH 5, 8) with 10 replicates. Maize seedlings were placed in a
plant growth cabinet with a photoperiod of 10 hours of light and
14 hours of darkness, a light intensity of 120 μm m2 s−1 , and
temperatures of 25◦ C (night) and 28◦ C (day). Roots were collected
on the seventh day and scanned at 300 dpi for evaluation of the
number of lateral roots for root analysis by Delta-t scan software
(Delta T Devices Ltd, Cambridge, UK). Additional samples of
root seedlings were collected for further experiments.
H + -ATPase activity
Plasma membrane (PM) vesicles were isolated from maize roots
grown with the optimum HS or HA concentration, using a
differential centrifugation method (Canellas et al., 2002). The
vesicles were either used immediately or frozen under liquid
N2 and stored at −70◦ C until use. Protein concentrations
were determined according to Lowry et al.’s (1951) method.
ATPase activity in PM vesicles was determined by measuring
colorimetrically the release of inorganic phosphorus. Between 80
and 95% of ATPase activity of the PM vesicles measured at
pH 6.5 was inhibited by vanadate (0.1 mm), an effective inhibitor
of the P-type H+ -ATPases. In all experiments, ATPase activity was
measured at 30◦ C, with or without vanadate, and the difference
between these two activities was attributed to plasma membrane
H+ -ATPase.
Multivariate statistical analysis
The CPMAS dataset consisted of a matrix (29 × 8) with each
row representing one of the humic substances: 13 HAs from
soils (SS and OX), seven HPSEC humic acid fractions (SF)
and nine chemical derivatives (D). The eight variables were the
spectral areas and their compositions (indices A, HB, HI and
HB/HI), calculated as reported above, are shown in Table 2.
The CPMAS dataset was auto-scaled and analysed by principal
component analysis (PCA), hierarchical cluster analysis (HCA)
and partial least squares regression (PLS) using the statistical
software package The Unscrambler ×10.1 (Camo Inc., Oslo,
Norway). PCA was performed to establish if the HS described by
spectral areas could be separated according to geographical origin
of bulk soils, as well as HPSEC fractionation and modification
by chemical reactions. HCA, like PCA, is an unsupervised
classification method and was conducted to verify the similarity
of the extract grouping observed in PCA. Ward’s (Brereton, 2003)
method using squared Euclidean distance was used as a similarity
measure. PLS (partial least squares) regression was performed to
establish which carbon species were associated with lateral root
emergence. The optimum number of factors was calculated by full
cross-validation.
Results
The different HS (Table 1) were analysed by solid state NMR
without further pretreatments and the relative spectral areas,
degree of aromaticity (A), hydrophobic (HB) and hydrophilic (HI)
carbon contents and HB:HI ratio (hydrophobicity index) were used
as variables to describe these HS in the multivariate analysis. The
first two principal components retrieved 87% of the original data
variance (Figure 1a). Although PCA is an unsupervised method
(Brereton, 2003) and therefore does not strictly account for the
origin of HS samples, the resulting score plots achieved a sample
separation that is in accordance with the origin of the HS studied
(Figure 1a).
Humic substances from soil and vermicompost samples were
separated on PC1 according to their polar and C-alkyl nature.
Samples with larger hydrophilic-C (HI), O-alkyl/methoxyl/N-alkyl
(40–110 ppm) and alkyl (0–40 ppm) content were positioned
in the PC1 positive side (Figure 1a,b). Samples with greater
aromatic-C (110–160 ppm) and hydrophobic-C (HB) content, as
well as a large degree of aromaticity (A) and HB:HI index,
resulted in a negative side to PC1 (Figure 1a,b). Therefore, the
contents of polar and alkyl groups were larger in size-separated
humic fractions (SF) than in humic derivatives from vermicompost
(D), which had similar values to the soil sequence (SS) samples.
The oxisol (OX) samples were more hydrophobic and with a
greater degree of aromaticity than all other samples. However,
the SF0 and D5 samples seemed to be similar to OX samples and
well within this sample group. The SS and D samples appearing
in the middle of PC1 were further differentiated along PC2,
which had a separation based on the 160–200 ppm chemical shift
© 2012 The Authors
Journal compilation © 2012 British Society of Soil Science, European Journal of Soil Science, 63, 315–324
Structure-bioactivity relationship of humic substances
Table 2 CPMAS
13
C NMR signal integrations and effects of humic acids on number of lateral roots (NLR) and plasma membrane H+ -ATPase activity
Chemical shift / ppm
SS1
SS2
SS3
SS4
SS5
SS6
Ox1
OX2
OX3
OX4
OX5
OX6
OX7
SF0
SF1
SF2
SF3
SF4
SF5
SF6
D0
D1
D2
D3
D4
D5
D6
D7
D8
Average
Max
Min
SD
319
Index from NMR data
Activity
160–200
110–160
40–110
0–40
A
HB
HI
HB / HI
NRLt
HATPase
20.00
20.00
14.00
15.00
22.00
16.00
12.20
12.80
12.40
10.90
11.20
11.40
10.90
11.20
7.50
9.00
6.90
3.50
6.80
5.20
10.00
9.80
10.20
9.90
10.60
8.50
9.30
10.80
9.90
11.3
22.0
3.5
4.2
19.00
20.00
22.00
27.00
23.00
25.00
27.60
33.60
36.70
33.00
25.50
30.30
32.60
30.60
18.40
21.10
13.00
9.00
5.20
6.80
23.90
26.20
25.10
24.20
25.80
30.70
27.30
25.60
23.90
23.9
36.7
5.2
7.7
30.00
38.00
33.00
36.00
30.00
35.00
38.40
33.70
32.90
34.80
36.90
36.50
35.60
32.00
47.20
44.70
52.20
56.20
51.80
52.30
42.90
38.70
39.90
43.90
42.40
35.10
42.70
43.30
41.20
39.9
56.2
30.0
7.0
31.00
22.00
30.00
21.00
26.00
23.00
21.90
19.90
18.00
21.30
26.40
21.90
20.80
26.30
26.90
25.10
28.00
31.30
36.20
35.80
23.20
25.40
24.70
22.00
21.20
25.70
20.80
20.30
25.00
24.9
36.2
18.0
4.6
23.80
25.00
25.90
32.10
29.10
30.10
31.40
38.50
41.90
37.00
28.70
34.20
36.60
34.40
19.90
23.20
13.90
9.30
5.60
7.20
26.60
29.00
28.00
26.90
28.90
33.60
30.10
28.70
26.50
27.1
41.9
5.6
8.9
50.00
42.00
52.00
48.00
49.00
48.00
49.50
53.50
54.70
54.30
51.90
52.20
53.40
56.90
45.30
46.20
41.00
40.30
41.40
42.60
47.10
51.60
49.80
46.20
47.00
56.40
48.10
45.90
48.90
48.7
56.9
40.3
4.6
50.00
58.00
47.00
51.00
52.00
51.00
50.60
46.50
45.30
45.70
48.10
47.90
46.50
43.20
54.70
53.70
59.10
59.70
58.60
57.50
52.90
48.50
50.10
53.80
53.00
43.60
52.00
54.10
51.10
51.2
59.7
43.2
4.6
1.00
0.72
1.13
0.92
0.96
0.92
0.98
1.15
1.21
1.19
1.08
1.09
1.15
1.32
0.83
0.86
0.69
0.67
0.71
0.74
0.89
1.06
0.99
0.86
0.89
1.29
0.93
0.85
0.96
1.0
1.4
0.7
0.2
11.79
9.85
4.12
3.74
4.12
10.39
26.46
30.08
28.28
33.47
31.46
31.78
27.75
9.70
9.17
12.85
10.68
11.53
10.00
11.18
12.21
13.78
6.08
10.34
12.49
14.49
11.36
10.72
12.92
14.9
33.5
3.7
9.1
22.56
20.30
18.08
13.64
7.94
14.59
9.49
8.66
10.72
14.83
15.78
10.00
20.00
13.42
7.07
15.46
6.56
17.20
9.22
13.11
6.16
13.08
14.21
9.85
0.00
11.00
2.45
8.19
13.42
12.0
22.6
1.0
5.1
Biological data were normalized with respect to plant control response (0%) and transformed by square root. A = ((160 to 110)/(0–160) × 100);
HB = ((160 to 110) + (44 to 0)); and HI = ((185 to 160) + (90 to 65) + (65 to 44)).
region comprising carbonyls of ketones, quinones, aldehydes and
carboxyl carbons. The SS samples with a large content of these
functional groups were positioned in the upper PC2 component of
the score plot.
The first two PCAs define a plane in which all samples are
projected to account for the maximum possible variance. Data
grouping and other relationships that are hardly visible in higher
dimensional variable space usually become apparent by PCA.
However, samples that are closely related on this plane may be
quite dissimilar. HCA was performed to confirm the apparent
grouping by PCA (Figure 2). HCA grouped samples according to
their similarity, by applying the criteria of Euclidean distance for
the eighth variable space. The dendrogram in Figure 2 shows two
distinct groups at the highest level, with samples SF3, SF4, SF5
and SF6 being very different from the rest of samples. By cutting
the dendrogram at level 7, it may be observed that the OX group
was separated from other samples. Samples SF1 and SF2 were
classified within group D, as their chemical carbon distribution
was closely related. Samples F0 and D5 appeared to be similar
to each other and formed an isolated group in the dendrogram at
level 2.
Relationship between humic structural features and root
growth induction
The PLS analysis models the relationship between a set of
predictor variables X (n samples, m variables) and a set of
response variables Y (n samples, p responses). Because there was
only one response in this study (number of lateral roots), Y is a
© 2012 The Authors
Journal compilation © 2012 British Society of Soil Science, European Journal of Soil Science, 63, 315–324
320 L. P. Canellas et al.
(a)
(b)
Figure 1 (a) PCA scores, indicating good separation of humic substances
in different groups according to their origin. (b) PCA loading plot. Position
of the variables along the PCs indicates their importance for that PC.
column vector with 29 rows. The data obtained from CPMAS
spectra of humic samples were submitted to PLS to establish a
correlation between the chemical shift regions, the HB, HI, A
and HB/HI indexes and the promotion of lateral root emergence.
The results from the PLS analysis are shown in Figure 3(a,b). A
full cross-validation selected four optimum factors, which retained
88% of the explained Y variance and 99.9% of the X variance,
and ensured a 93% correlation with R 2 = 0.88 (Figure 3).
The most important variable to predict lateral root emergence
was the HB:HI index (Table 3). The HI hydrophilicity index had
a large positive correlation coefficient (Table 3). Conversely, the
HB hydrophobicity index was negatively correlated with lateral
root emergence, while the A degree of aromaticity appeared to be
irrelevant in predicting lateral root emergence. The 40–110 ppm
region had a relatively larger positive regression coefficient than
the 160–200 ppm region, thus suggesting that extracts with
greater HB/HI and 40–110 ppm contribution should increase
lateral root emergence.
Discussion
Sustainability of agricultural systems has become an important
issue all over the world and fertilizer factories are now redirecting
their production to biostimulants based on humic substances and
other organic compounds (Ertani et al., 2011). Great importance
is placed on the correlation between humic matter composition
and its ability to stimulate lateral root emergence from maize
primary roots We used PCA and HCA to classify different humic
matter according to its origin and partial least squares regression
(PLS) to generate a model to describe the induction of lateral root
emergence by these substances in order to guide the production
of more effective biostimulants. Stimulating a large root system
by humic matter is regarded as an advantage for exploiting a
greater soil volume: effects on lateral root initiation are therefore
important.
The major evidence for the positive effects of humus biofertilization points to HS-mediated changes in root growth and
morphology. Many humic materials are believed to contain phytohormones that can stimulate plant growth and change the assimilation partitioning patterns, thus affecting root growth processes
and resulting in longer and more branched roots, and/or roots with
greater surface area.
All humic materials used in this study showed a significant
induction of ATP hydrolysis compared with control plants
(Table 2). The present challenge is to relate a highly specific
auxin-like effect on lateral root emergence to a very complex and
heterogeneous medium such as humic matter. However, previous
work reported a strong relationship between soil properties and the
physiological effect of HS, especially soil acidity and indoleacetic
acid-like activity, revealing that differences between ecosystems
induce differences in HS biological activity (Pizzeghello et al.,
2001, 2002).
PCA was efficient in separating the different HS according
to their origin based on CPMAS 13 C NMR spectral data and
HCA confirmed the results from PCA. Šmejkalová et al. (2008)
previously used CPMAS 13 C NMR results to show that PCA
was able to extract the main similarities and dissimilarities
among the structural features of a number of different humic
materials. This multivariate statistical method was a powerful tool
for differentiating the chemical characteristics of size-fractions
separated from a natural humic acid.
PLS analysis was also performed to search for a correlation
between CPMAS 13 C NMR signal areas and the number of lateral
roots emerged from a primary axis. For four PLS factors, 88% of
the the variance was explained and provided a good correlation
to be able to use for prediction of the number of lateral roots.
The HB/HI, HI, 40–110 and 160–200 ppm chemical shift intervals contributed positively to the correlation, and the total content
of hydrophobic species (HB) made a negative correlation. The
theoretical and practical consequences of such correlation results
may be extrapolated from the present knowledge of humus chemical behaviour. Piccolo (2002) indicated that hydrophobic humic
components derived from plant degradation and microbial activity
are able to incorporate more polar molecules randomly and hence
increase protection against degradation. Spaccini et al. (2000) further showed that organic compounds released in soils during
mineralization of fresh maize residues were stabilized against
microbial degradation by surrounding hydrophobic components.
Furthermore, Spaccini et al. (2002) used isotopic labelling techniques to reveal that organic labile compounds are incorporated
© 2012 The Authors
Journal compilation © 2012 British Society of Soil Science, European Journal of Soil Science, 63, 315–324
Structure-bioactivity relationship of humic substances
321
Figure 2 Dendrogram showing the results from hierarchical cluster analysis (HCA) representing the relationships between the 29 humic samples.
into the hydrophobic domains of organic matter and this mechanism of hydrophobic protection prevents rapid microbial degradation, thereby enhancing persistence of organic matter in soil.
Humic substances adopt the behaviour of heterogeneous
micelles in aqueous solution (Piccolo, 2002), whose supramolecular structures contain the hydrophobic microenvironment that can
favour molecular interactions with exchanging surfactant, water or
organic molecules in solution (Nowick et al., 1994). The process
of molecular trapping into humic hydrophobic domains suggests
that the more hydrophobic the HS, the greater is the potential
hydrophobic incorporation of relatively hydrophilic bioactive
molecules. In turn, the more complex the 40–110 ppm signal
area, where the trapped bioactive molecules are mainly visible,
the greater their structural differences and, consequently, the more
diverse their bioactivity. Nardi et al. (2007) evaluated the effect of
size-separated humic fractions on the activity of enzymes involved
in the glycolytic and respiratory processes of maize seedlings.
They found that the smaller and more hydrophylic the fraction, the richer in carbohydrates and more active metabolically
it was. Nardi et al. (2007) concluded that the biological activity
of the HS appears to result from a specific arrangement of humic
molecules in solution, where the distribution of hydrophilic components within a hydrophobic environment maintains a sufficient
degree of conformational flexibility to allow the interaction of
active humic molecules with root cells. In previous work, Canellas et al. (2008, 2009, 2010) and Dobbss et al. (2010) found a
significant correlation between hydrophobicity of humic acids and
their effects on H+ -ATPase activity.
Linear regression (LR) and multiple linear regression (MLR)
correlate independent X-variables with one Y-property. Therefore
the X-variables must be uncorrelated, otherwise misinterpretations
may occur (Esbensen, 2001). The variables used to describe
the soil (NMR data) are highly correlated, therefore the use of
alternative approaches such as PLS to model the relationship
between carbon species and biological activity of humic acids is
advantageous. Multivariate analysis may disclose results hidden in
relationships between the variables and the models are thus easier
to interpret. The multivariate approach allows the integration of
data from different, very distinct samples in order to explain
the factors responsible for data variation. The involvement of
humic acids in root growth stimulation is of practical interest
because, if identified, the relevant chemical properties responsible
for HS induction of root growth may be manipulated during the
humification process of different organic residues, thus enhancing
their biological effects on plants.
It is tempting to speculate that within the complex HS
structure, there are different types and concentrations of auxin-like
molecules, and the stimulatory effects of humic matter could be
triggered by their release from supramolecular structures, which,
in turn, may access receptors outside or inside the cell. Previous
studies have detected, in the plasmatic membrane, a receptor that
binds auxin, by which the H+ -ATPase could be activated in maize
© 2012 The Authors
Journal compilation © 2012 British Society of Soil Science, European Journal of Soil Science, 63, 315–324
322 L. P. Canellas et al.
(a)
(b)
Figure 3 (a) Functions to plot predicted values against measured values
for a fitted model produced using CP/MAS 13-C NMR data and induction
of lateral root emergence by different humic materials on maize seedlings.
The two lines consist of the calibration and validation regressions with
four PLS factors. Correlation is 93% and Pearson’s squared correlation
coefficient is 0.88. (b) The explained Y variance for PLS factors. The
upper line is the calibration variance and the lower curve is the validation
variance. The optimum number of factors is four, corresponding to 88%
of the Y calibration variance and 81% of the Y validation variance.
extracellular acidification in maize roots (Peters & Felle, 1999),
HS-induced H+ -ATPase activation might also be mechanistically
linked to root hair proliferation.
On the other hand, the 40–110 ppm spectral interval is not
exclusive to auxins and several other molecular biofragments show
signals in this region. Nebbioso & Piccolo (2011) found many
organic compounds linked to humic aggregates. It is probable
that HS may act as a buffer, either absorbing or releasing signalling molecules, depending on rhizosphere changes, such as the
acidification brought about by the activity of PM H+ -ATPase or
by exudation of organic acids, thereby behaving as a regulator of
hormonal balance with respect to lateral root emergence. Canellas
et al. (2011), by applying the same humeomic approach proposed
by Nebbioso & Piccolo (2011), found that when humic matter
was submitted to alkaline and acid hydrolysis it was progressively
stripped of molecular material and lost the ability to induce laterals. Interestingly, the humic matter residue resulting from the fractionation was selectively enriched with C-alkyl and C-aromatic,
which did not show NMR signals in the 4–100 ppm spectral
range. These findings support the conclusion that humic hydrophobic C domains protect and preserve bioactive molecular fragments,
which, when released in solution by changes of humic conformations in the rhizosphere, may interact with plant receptors.
It has been previously observed that plant exposure to a
humic solution induces exudation of short-chain organic acids
(Canellas et al., 2008b). Puglisi et al. (2008) also reported an
enhancement in organic acid exudation in maize seedlings after
soil treatment with HS. Organic acids are also recognized as
having an impact on soil humic substances in disaggregating their
unstable supramolecular structures into relatively smaller humic
associations (Piccolo, 2002). Bioactive molecules may be released
in the soil solution of the rhizosphere during the process of humus
disaggregation by organic acids, and then access cell membranes
to induce different physiological responses.
Table 3 Regression coefficients for four PLS factors
X variablea
Regression coefficient
160 to 0
110 to 60
40 to 10
0–0
A
HB
HI
HB:H1
0.1412
−0.1516
0.3958
−0.2705
−0.0978
−0.5238
0.7283
2.2364
a As described in Materials and methods.
Variable HB/HI is the most important to predict lateral root emergence for
present data.
protoplasts (Ruck et al., 1993). This hypothesis is consistent with
the acid growth mechanism, proposed for HS bioactivity, in which
activation of the PM, as well as of the tonoplast proton pumps,
occurs during lateral root growth (Zandonadi et al., 2007). Thus,
on the basis of the demonstration that cell growth depends on
Conclusion
Different sets of humic acids were used to evaluate their
inductive effects on lateral root emergence. The humic acids
were separated by principal component analysis and hierarchical
analysis according to their origin. In this work it was possible to
associate positively two main features arising from NMR spectra
of humic materials with the ability of humic materials to induce
lateral root emergence in maize seedlings. These features were the
40–110 ppm signal interval comprising O-alkyl and methoxyl/Nalkyl species, and the hydrophobic index (HB/HI) calculated from
NMR spectra. The multivariate PLS analysis showed that these
variables explained the major part (88%) of the variance in the
prediction of the number of lateral roots. Our results support the
view that the ability of humic materials to act in solution as plant
root growth promoters at small concentrations is related to polar
molecular biofragments preserved by the hydrophobic aggregates
into humic supramolecular associations. These results indicate
a route to reach a structure-activity relationship between humic
© 2012 The Authors
Journal compilation © 2012 British Society of Soil Science, European Journal of Soil Science, 63, 315–324
Structure-bioactivity relationship of humic substances
matter and plant biological activity showing that the positive role
exerted by humic acids on plant metabolism may be reflected
in lateral root emergence. In addition, this could be of practical
interest in finding sources of humic materials to contribute to
the growing demand for biofertilizers based on physiological
effects.
Acknowledgements
This work was partially supported by CNPq, FAPERJ, IFS and
National Institute of Science and Technology for Biological
N Fixation.
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