Directory UMM :Data Elmu:jurnal:B:Biochemical Systematics and Ecology:Vol29.Issue3.Mar2001:

Biochemical Systematics and Ecology 29 (2001) 223–240

Phenolic and phenolic-related factors as
determinants of suitability of mountain birch
leaves to an herbivorous insect
Vladimir Ossipova,b,*, Erkki Haukiojaa, Svetlana Ossipovaa,b,
Sinikka Hanhima¨kia, Kalevi Pihlajab
b

a
Section of Ecology, Department of Biology, University of Turku, FIN – 20014 Turku, Finland
Laboratory of Physical Chemistry, Department of Chemistry, University of Turku, FIN - 20014,
Turku, Finland

Received 19 July 1999; accepted 17 May 2000

Abstract
We investigated the role of phenolic and phenolic-related traits of the leaves of mountain
birch (Betula pubescens ssp. czerepanovii) as determinants of their suitability for the growth of
larvae of the geometrid Epirrita autumnata. As parameters of leaf suitability, we determined
the contents of total phenolics, gallotannins, soluble and cell-wall-bound proanthocyanidins

(PAS and PAB, respectively), lignin, protein precipitation capacity of tannins (PPC), and leaf
toughness. In addition, we examined concentrations of soluble carbohydrates and proteinbound amino acids as background variables describing the nutritive value of leaves. The
correlation of the leaf traits of our 40 study trees with the tree-specific relative growth rate
(RGR) of E. autumnata showed that the only significant correlation with RGR was that of
PAS } the largest fraction of total phenolics } and even that explained only 15% of the
variation in E. autumnata growth. The nonlinear estimation of the relationship between RGR
and PAS by piecewise linear regression divided the 40 study trees into two groups: (i) 19 trees
with good leaves for E. autumnata (RGR ranging from 0.301 to 0.390), and (ii) 21 trees with
poor leaves (RGR ranging from 0.196 to 0.296). The suitability of leaves within these two
groups of trees was determined by different phenolic traits. Within the good group, the
suitability of leaves for larvae was determined by the PPC of extracts, which strongly
correlated with gallotannins, and by the total content of gallotannins. In contrast, the leaves of
poor trees had significantly higher contents of both PAS and PAB, but leaf toughness
correlated only negatively with the RGR of E. autumnata larvae. We also discuss the causes of

*Correspondence address: Department of Chemistry, University of Turku, FIN - 20014, Turku,
Finland. Tel.: +358-2-333-6728; fax: +358-2-333-6700.
E-mail address: ossipov@utu.fi (V. Ossipov).
0305-1978/01/$ - see front matter # 2001 Elsevier Science Ltd. All rights reserved.
PII: S 0 3 0 5 - 1 9 7 8 ( 0 0 ) 0 0 0 6 9 - 7

224

V. Ossipov et al. / Biochemical Systematics and Ecology 29 (2001) 223–240

variation in the phenolic and phenolic-related factors that determine the suitability of leaves
for E. autumnata larvae in different groups of trees. # 2001 Elsevier Science Ltd. All rights
reserved.
Keywords: Betula pubescens ssp. czerepanovii; Birch; Epirrita autumnata; Gallotannins; Lignin; Phenolics;
Plant–insect relationships; Proanthocyanidins

1. Introduction
In higher plants the shikimate pathway produces various phenolic compounds,
such as hydroxybenzoic and hydroxycinnamic acids, flavonoids, coumarins, lignins
and hydrolysable and condensed tannins (proanthocyanidins). In woody plants,
these metabolites represent the major route of carbon channelling and account for
approximately 30–40% of the plant dry mass. Phenolics have wide ranging
functions, including structural support, pigmentation, signalling and defence against
environmental and biotic stresses (Dixon and Paiva, 1995; Douglas, 1996). They
have traditionally been considered to play an important role in plant–herbivore

interactions (Feeny, 1976; Rhoades and Cates, 1976; Herms and Mattson, 1992;
Bryant et al., 1993; Haukioja et al., 1998).
The phenolics of mountain birch leaves (Betula pubescens ssp. czerepanovii) have
been assumed to contribute to the plant’s resistance against herbivorous insects, for
three reasons: (i) the leaves generally have very high levels of phenolics, often
exceeding 10% of the dry mass; (ii) foliar tannins are effective in protein
precipitation and are therefore presumably well suited for defensive functions; and
(iii) after leaf damage, concentrations of leaf phenolics increase considerably and
remain high during the year following defoliation (Tuomi et al., 1984; Haukioja
et al., 1985a; Neuvonen et al., 1987; Nurmi et al., 1996; Ossipov et al., 1997;
Kaitaniemi et al., 1998). However, in attempts to associate insect performance with
leaf chemistry, we have found only weak correlations, and different experiments have
yielded partly contradictory results (Haukioja et al., 1985b; Tuomi et al., 1988;
Neuvonen and Haukioja, 1991; Suomela et al., 1995; Ruohoma¨ki et al., 1996;
Kaitaniemi et al., 1998). We think that this discrepancy can be explained by
high among-tree variation in the composition and content of some phenolics; in
addition, the suitability of leaves for insects in different trees and at different
developmental phases of leaves may be determined by different compounds (Kause
et al., 1999).
Earlier studies of the chemical basis of mountain birch–insect relationships utilized

crude estimates of phenolics and their correlations with insect performance
(Haukioja et al., 1985a,b; Tuomi et al., 1984, 1988). Recently, we have identified
the main low molecular mass phenolics in mountain birch leaves, and have
elucidated the main characteristics of gallotannins, condensed tannins (soluble and
cell-wall-bound proanthocyanidins), and lignins (Ossipov et al., 1995, 1996, 1997;
Nurmi et al., 1996; Ossipova et al., in press). Since these phenolic oligo- and
polymers contribute to protein precipitation capacity and to leaf toughness, we are

V. Ossipov et al. / Biochemical Systematics and Ecology 29 (2001) 223–240

225

now in a position to study the role of phenolics and phenolic-related leaf traits in
more detail.
We realize that the content of phenolics, or of any plant secondary metabolites, do
not alone determine leaf quality for herbivores; after all, herbivores require nutritive
compounds from their diet. Accordingly, we measured the contents of protein-bound
amino acids and soluble carbohydrates in the birch leaves to provide background
information to suitability (Tenow, 1972; Haukioja et al., 1988).
Earlier work has demonstrated that the performance of Epirrita autumnata larvae

on trees with high and low concentrations of gallotannins depends on different
phenolics, gallotannins and proanthocyanidins (Kause et al., 1999). It was also
found that difference between trees with low and high concentration of gallotannins
could be explained at least in part by phenological differences among the trees. To
further elucidate the multiplicity of chemical factors determining birch leaf
suitability for E. autumnata larvae, we replicated the experiment in a different year.
We used a larger number of trees, with higher among-tree variation in leaf
suitability, and determined a more extensive array of phenolic and phenolic-related
leaf traits, including leaf toughness and lignin content. In the present work, we found
that the suitability of birch leaves for E. autumnata larvae is the result of the
combined action of at least three phenolic factors } gallotannin and proanthocyanidin concentrations and leaf toughness } and that the relative intensity of these
factors varies among trees.

2. Materials and methods
2.1. Study site and organisms
Our study area is located near the Kevo Subarctic Research Station of Turku
University, in northern Finland (698 450 N, 278 010 E), at an altitude of 150 m above
sea level. The area is covered by a forest consisting almost purely of mountain birch
(Betula pubescens ssp. czerepanovii (=tortuosa) (Orlova) Ha¨met-Ahti). Forty mature
mountain birch trees were randomly chosen from a single homogeneous forest plot.

The growth type of mountain birch is indeterminate, with two kinds of shoots,
short shoots and long shoots (Ruohoma¨ki et al., 1997). Short shoot leaves (usually
three leaves per shoot) burst simultaneously in spring, and are therefore evenly aged
within a tree. This is in contrast to long shoot leaves, which are produced
continuously at growing branch tips until late summer, and which therefore vary in
age even within a shoot. To control for leaf age within an individual tree, we used
only short shoot leaves in our analysis. To evaluate among-tree variation in the time
of leaf burst and consequently in leaf age, the length of the leaves was recorded on 7
June at the time of bud break.
The autumnal moth, Epirrita autumnata (Bkh.), is a univoltine polyphagous
geometrid; in Lapland its larvae are usually found on mountain birch, the most
common tree species of the area (Haukioja et al., 1988). Adult moths fly in autumn,
when the females lay eggs which overwinter and hatch the following spring at the

226

V. Ossipov et al. / Biochemical Systematics and Ecology 29 (2001) 223–240

time of birch budbreak (Tammaru et al., 1995). The larvae feed on short shoots for
most of their larval period since there simply are no long shoots available.

E. autumnata population densities fluctuate cyclically at about 10-yr intervals; they
may reach outbreak levels and defoliate vast areas of birch forests (Tenow, 1972;
Haukioja et al., 1988).
2.2. Plant sample preparation
A total of 15–25 leaves from short shoots only, i.e. even-aged leaves, were sampled
throughout the canopy of the experimental trees on 28 June, between 9 and 10:30
a.m. Unlike the previous experiment (Kause et al., 1999), the leaves of our
experimental trees had completed active growth at the time of sampling. The samples
were immediately placed in an insulated box filled with ice and transported to the
nearby laboratory. The plant material was vacuum dried. The leaf samples of
individual trees were then homogenized into a powder and stored in plastic vials at
ÿ 208C.
About 200 mg of the powder was suspended in 10 ml of 70% aqueous acetone,
allowed to stand for 1 h at room temperature with continuous stirring and
centrifuged for 10 min at 2500g. The pellet was re-extracted twice. The acetone
extract was reduced to the aqueous phase by evaporation at room temperature, and
the resulting aqueous phase was frozen and lyophilized. The lyophilized residue was
redissolved in 9 ml of water and centrifuged for 20 min at 3000g. This purified extract
was used for the determination of soluble phenolics, carbohydrates and protein
precipitation capacity of tannins. The acetone-insoluble residue was collected,

lyophilized and weighed, and was used for the determination of cell-wall-bound
proanthocyanidins, lignin and protein-bound amino acids.
2.3. Biochemical determinations
2.3.1. Total content of soluble phenolics
A modification of the Folin-Ciocalteau method (Torres et al., 1987) was used to
determine the total content of phenolic compounds. An 0.1 ml sample of the purified
extract was placed in a 15 ml tube and mixed with 5.9 ml water. 1.0 ml of this diluted
extract was mixed with 1.0 ml 1 N Folin-Ciocalteau’s phenol reagent (Fluka,
BioChemika, Buchs) in a 10-ml centrifuge tube and allowed to stand for 2–5 min.
Then 2 ml of 20% Na2CO3 was added. After 10 min incubation at room temperature,
the mixture was centrifuged for 8 min at 1500g and the absorbance was measured at
730 nm on a Perkin-Elmer Spectrophotometer 550. The standard curve was created
with known concentrations of gallic acid.
2.3.2. Soluble proanthocyanidins (PAS)
PAS were analyzed by a modification of the method of Terrill et al. (1992) for the
optimization of proanthocyanidins from birch leaves (Ossipova et al., in press).
0.1 ml of purified extract and 0.6 ml of water were added to 6 ml of a freshly prepared

V. Ossipov et al. / Biochemical Systematics and Ecology 29 (2001) 223–240

227

mixture of 1-butanol/concentrated HCl (95:5, v/v) in a 10-ml screw-top glass
centrifuge tube. The optimal concentration of water in the reaction mixture
was 10–11% (v/v). After mixing, the tubes were placed in a constant-level water bath
for 50 min at 958C. The tubes were then cooled to room temperature and absorbance
at 555 nm was measured. The standard curve was prepared with known
concentrations of proanthocyanidins, which were isolated from mature birch
leaves and purified by preparative chromatography on Sephadex LH-20 (Ossipova
et al., in press).
2.3.3. Cell-wall-bound proanthocyanidins (PAB)
PAB were analyzed in the acetone-insoluble residue by the same method as PAS
(Ossipova et al., in press). About 7 mg of the dry residue was suspended in a reaction
mixture containing 6 ml of 1-butanol/concentrated HCl (95:5, v/v) and 0.7 ml of
water. The sample was heated for 50 min at 958 C, cooled and centrifuged for 10 min
at 2500g. The absorbance of the solution at 555 nm was then measured.
2.3.4. Total content of gallotannins
Quantitative analysis of gallic acid in the hydrolysate of extracts was used for the
determination of total gallotannins (a modification of the method by Inoue and
Hagerman, 1988). One ml of extract was placed in a 2-ml Teflon-lined screw-cap

glass tube, freeze-dried and dissolved in 1 ml 1 M H2SO4. The tube was capped and
hydrolysis was run for 4 h at 1008C. A 0.1 ml aliquot of the hydrolysate was then
diluted to 1 ml with distilled water. 0.2 ml of this sample was mixed with 0.3 ml of
0.667 % methanolic rhodanine solution. After exactly 5 min, 0.2 ml of 0.5 M KOH
solution was added. After 2.5 min, the mixture was diluted to 5 ml with distilled
water. Five to 10 min later the absorbance at 520 nm was read. The rhodanine assay
was standardized with gallic acid.
2.3.5. Lignin
Lignin was assayed by derivatization with thioglycolic acid (modified from the
method of Lange et al., 1995). Approximately 15 mg of the acetone-insoluble residue
was placed in a 1.5-ml Eppendorf screw-cap vial and treated consecutively with
1.5 ml of the following solvents and solutions, with mixing for 15 min followed by
centrifugation for 5 min at 7000g (Eppendorf centrifuge 5417C): (a) 1 M NaCl, (b)
1% (w/v) sodium dodecyl sulphate (SDS), (c) H2O (twice), (d) ethanol, (e) CHCl3 /
CH3OH (1:1, v/v), and (f) acetone (twice). The remaining insoluble material was
vacuum-dried overnight and treated with 1 ml of 2 M HCl and 0.2 ml of thioglycolic
acid for 4 h at 958C. After cooling to room temperature, the mixture was centrifuged
for 10 min at 7000g. The supernatant was removed with a Pasteur pipette, and the
remaining pellet was washed three times with H2O. The pellet of purified cell walls
was suspended in 1 ml of 0.5 M NaOH and shaken vigorously overnight to extract

the lignin thioglycolic acid derivatives (LTGA). Following centrifugation as above,
the supernatant was decanted into a 2-ml Eppendorf vial, and the pellet was washed
with 0.5 ml of 0.5 M NaOH. The combined alkali extract was acidified with 0.3 ml of

228

V. Ossipov et al. / Biochemical Systematics and Ecology 29 (2001) 223–240

concentrated HCl and the LTGA was allowed to precipitate for 4 h at 48C. The
mixture was centrifuged as above, the supernatant was removed with a Pasteur
pipette, and the pellet was vacuum-dried. The pellet was dissolved in 1 ml of 0.5 M
NaOH and diluted to 15 ml with 0.5 M NaOH. Absorption at 280 nm was measured,
using an absorption value of 0.316/mg lignin (Lange et al., 1995) for the calculation
of lignin content in cell wall preparations.
2.3.6. Protein precipitation capacity (PPC) of tannins
For determination of the PPC of tannins in birch leaf extracts, a radial diffusion
method with agarose gel was used (Hagerman, 1987). In this assay, tannins diffuse
through a protein-containing gel. A visible disk-shaped precipitate develops as the
tannin interacts with the protein. The area of the disk is linearly related to the
amount of tannins placed in the well. A 1 ml aliquot of the extract from birch leaves
was freeze-dried and diluted in 0.2 ml of water. Two successive aliquots of 0.01 ml
each were applied to the diffusion gel. After 96 h of incubation at 308C, the diameters
of the rings were measured. The data were presented as the area of tannin–protein
precipitate in cm2 g ÿ 1 of dry mass of birch leaves.
2.3.7. Leaf toughness
The toughness of 10 leaves per tree was measured with a penetrometer
(Department of Chemistry, University of Turku, Finland), similar to that described
by Feeny (1970), on leaf blades outside major veins. The results are expressed in g
mm ÿ 2 necessary to puncture the blade.
2.3.8. Protein-bound amino acids
Approximately 20 mg of the acetone insoluble residue was hydrolyzed with 5 ml
6 N HCl for 24 h at 1058C. An 0.05 ml aliquot of the hydrolysate was placed in a
Microcentrifuge tube, dried for 2 h at 1058C and dissolved in 0.2 ml of 0.1 M borate
buffer, pH 11.4. Protein-bound amino acids were derivatized with 9-fluorenylmethyl
chlorformat (FMOC-Cl) and analyzed by HPLC (Bank et al., 1996). For
derivatization, 0.2 ml of FMOC reagent in acetone (1.5 mg ml ÿ 1) was added to
0.2 ml of amino acid solution, mixed immediately and then allowed to stand for
40 min at room temperature. An 0.05 ml aliquot of amino acid derivatives was added
to the vials with 0.95 ml of 25% (v/v) acetonitrile in 0.05 M boric acid. An 0.02 ml
aliquot of the diluted sample was injected into an HPLC system.
The HPLC system (La Chrom system, Merck-Hitachi) consists of a pump L-7000,
a fluorescent detector L-7480, a programmable autosample L-7250, and an interface
D-7000. Peak Master (Harley System) software, run under Microsoft Windows 3.11,
was used for data acquisition and processing. The sample was injected into a RPHPLC column (150  3.9 mm i.d., Pico-Tag 1 , Waters).
The derivatized amino acids were separated using a slightly modified ternary
gradient system as described by Bank et al. (1996). Solvent A was 40 mM citric
acid containing 5 mM tetramethylammonium chloride and 0.01% (w/v) sodium
azide, adjusted to pH 2.85 with 20 mM sodium acetate containing 5 mM

V. Ossipov et al. / Biochemical Systematics and Ecology 29 (2001) 223–240

229

tetramethylammonium chloride and 0.01% (w/v) sodium azide. Solvent B was 80%
(v/v) of 20 mM sodium acetate solution containing 5 mM tetramethylammonium
chloride and 0.01% (w/v) sodium azide (adjusted to pH 4.5 with concentrated
phosphoric acid) plus 20% (v/v) methanol. Solvent C was acetonitrile. For elution
the next gradient was used: 0–15 min, 25–40 % C in A (linear gradient); 15–20 min,
40 % C in A (isocratic); 20.1–30 min, 36–38 % C in B (linear gradient); 30–45 min,
38–60 % C in B (linear gradient); 45–47 min, 40–80% C in B (linear gradient); 47–
55 min, 80% C in B (isocratic). The flow rate was maintained at 1 ml min ÿ 1
throughout the analysis with a column pressure of 70–113 bar. Fluorescence was
monitored at 254 and 630 nm (excitation and emission wavelengths, respectively).
Calibration curves were obtained using an amino acid standard solution AA-S-18
(Sigma).
2.3.9. Carbohydrates
The soluble carbohydrates of the birch leaves were analyzed by capillary gas–
liquid chromatography (GLC) in the form of TMS-derivatives (Kallio et al., 1985).
A 1.0 ml of purified extract and 0.1 ml of sorbitol solution (internal standard, 10 mg
ml ÿ 1) were placed in a 1.5 ml screw-cap vial and freeze-dried overnight. The dry
material was dissolved in 0.3 ml pyridine and 0.15 ml of a mixture of bis(trimethylsilyl)trifluoracetamid (Merck) and chlortrimethylsilan (Aldrich) (99/1, v/v). The
reaction mixture was kept at 608C for 1 h and left to stand overnight at room
temperature. The sample was then filled to 1.0 ml with pyridine and used for GLC
analysis. The TMS-derivatives of carbohydrates were analyzed with the PerkinElmer Autosystem GC with a flame ionization detector and Perkin-Elmer integrator
1020, using a 30 m HP-1 capillary column (crosslinked methyl sylicone gum, 0.25 mm
i.d., film thickness 0.25 m m, Hewlett-Packard, USA). The injector split ratio was
1:50 and the flow rate of the carrier gas, nitrogen, 40 ml min ÿ 1. The temperature of
the injector and detector was 2808C. The temperature of column was programmed as
follows: (1) 1508C, 1 min; (2) 150–2408C, 48C min ÿ 1; (3) 240–2908C, 208C min ÿ 1;
(4) 2908C, 14 min. The injected volume was 1 m l.
2.4. Growth of E. autumnata larvae
The leaf quality of each of the 40 trees was bioassayed by measuring the growth
rates of newly molted 5th instar E. autumnata larvae for 24 h. Prior to the feeding
trial, all larvae had been treated identically. The trees used for feeding the larvae
were from the same mountain birch population as the experimental trees. Five leaves
from each tree were sampled for bioassay between 5:30 and 6:30 a.m. on June 27, i.e.
one day before the sampling of leaves for the biochemical analyses. Five broods of
E. autumnata were used for the bioassay; a single E. autumnata larva from each
brood was allowed to feed on one of the five leaves from each tree. The larvae were
weighed at the start of the trial. The order of trees used to feed the larvae was
randomized. After 24 h the larvae were reweighed in the same order as at the
beginning of the trial. The times of all weighings were recorded to the nearest minute.
Illumination was continuous, corresponding to natural summer light at this latitude.

230

V. Ossipov et al. / Biochemical Systematics and Ecology 29 (2001) 223–240

The growth trial was conducted at 128C, which corresponds to the average summer
temperature in the area. As an index of leaf quality, we used the relative growth rate
of the larvae: RGR ¼ ðlnðme Þ ÿ lnðmb ÞÞ=time, where mb and me are the calculated
dry masses of a larva at the beginning and end of the growth trial, respectively. Dry
larval masses (DM) were calculated from fresh masses (FM) as DM=0.125*FM1.113
(Neuvonen and Haukioja, 1984).
2.5. Statistical analysis
All parameters of both birch leaves and herbivore growth were reduced to treespecific means, and these means were used in statistical analyses (Statistica, StatSoft,
1994). The correlations both among leaf parameters and between these parameters
and the RGR of E. autumnata were tested using multiple regression analysis. In a
preliminary analysis of the data, PAS was the only leaf trait that correlated
significantly with RGR, and even that explained only 15% of growth variation.
Multiple regression assumes a linear relationship between the dependent and the
independent variable. Accordingly, we studied the nature of the relationship between
the dependent variable RGR and the independent variable PAS and other phenolic
traits by nonlinear regression models. We used Piecewise Linear Regression with a
breakpoint (option from Nonlinear Regression, Statistica, StatSoft, 1993), which
estimates two separate linear regression equations; one for RGR values that are less
than or equal to the breakpoint and one for RGR values that are greater than the
breakpoint. As a result, our 40 study trees were divided into two groups, with good
and poor leaf quality for E. autumnata. The correlations between leaf traits and
RGR of E. autumnata were then tested within these groups separately. Differences in
the values of leaf traits between the two groups were analyzed by t-tests.

3. Results
3.1. Growth of larvae
Table 1 summarizes the traits measured for both larvae and leaves. The RGR of
E. autumnata on the leaves of the 40 trees ranged from 0.196 to 0.390: the best tree
supported larval growth twice as well as the worst one. The coefficient of variation of
E. autumnata growth rate on the leaves of our study birches was about three times as
great as in the previous experiment with 5th instar larvae (Kause et al., 1999).
3.2. Phenolic and phenolic-related parameters of birch leaves
The mean total content of soluble phenolics (Table 1) accords well with previous
studies of mountain birch (Haukioja et al., 1985a,b; Tuomi et al., 1988; Nurmi et al.,
1996; Ruohoma¨ki et al., 1996). Soluble and cell-wall-bound proanthocyanidins (PAS
and PAB, respectively) are the main groups of phenolics of leaves (Table 1). PAB
represented 28% of the total content of proanthocyanidins. The total content of

V. Ossipov et al. / Biochemical Systematics and Ecology 29 (2001) 223–240

231

Table 1
Relative growth rate of E. autumnata larvae (RGR) on leaves of 40 birch trees and values of parametersa
measured in these leaves
Measured parameter

Mean
0.297

SD
0.046

CV

RGR of E. autumnata larvae
Phenolic traits
Total soluble phenolics
Gallotannins
Proanthocyanidins soluble (PAS)
Proanthocyanidins bound (PAB)
Protein precipitation capacity of tannins (PPC)
Toughness of leaves
Lignin

15.49

127.44
8.23
107.15
42.22
315.80
80.86
7.62

19.81
4.87
17.67
8.79
81.72
10.40
0.98

15.54
59.16
16.49
20.81
25.88
12.86
12.86

Nutritive compounds
Sum of individual carbohydrates
Galactose
Sum of protein-bound amino acids

80.07
48.90
128.96

9.03
7.23
17.27

11.28
14.79
13.39

a
Concentrations of chemicals in mg g ÿ 1 of dry mass; protein precipitation capacity of tannins in
extracts from birch leaves was measured by radial diffuse method (Hagerman, 1987) and results presented
as an area of tannin–protein precipitate in cm2 g ÿ 1 of dry mass of leaves; toughness of leaves in g per
mm ÿ 2. Abbreviations: (SD) standard deviation; (CV) coefficient of variation.

gallotannins was much lower and showed large variation among trees (Table 1).
Another independent method for the determination of gallotannins, summing up
individual gallotannins from the HPLC analysis, gave the same value (data not
shown). Interestingly, the total content of soluble phenolics correlated positively
with the content of gallotannins (r ¼ 0:53; P50:001), but there was no correlation
with PAS, the main group of soluble phenolics in birch leaves.
The protein precipitation capacity of leaf extracts (PPC) correlated strongly with
the concentrations of total gallotannins (r ¼ 0:73; P50:001). This also explains the
relatively high variation in PPC among trees (Table 1). In spite of the very high
concentrations of PAS in the leaf extracts, their correlations with PPC were not
significant in this study, and were in accordance with our other experiments with
mountain birch (Ossipov et al., 1997; Kaitaniemi et al., 1998; Kause et al., 1999).
This is consistent with our findings demonstrating that the specific PPC of isolated
and purified PAS from birch leaves was much lower than that of gallotannins
(Ossipova et al., in press).
Leaf toughness is an important trait contributing to plant resistance against
insects (Feeny, 1970; Coley, 1983; Coley and Barone, 1996). Toughness results from
the composition of cell walls and especially from the presence of different phenolic
compounds in the walls (Haslam, 1988). In woody plants, the most important cellwall-bound phenolic is lignin. Contrary to our expectation, the average lignin
content was very low (Table 1), and did not correlate with leaf toughness
(r ¼ ÿ0:04; P ¼ 0:82). There was also no significant correlation between toughness
and cell-wall-bound proanthocyanidins, although the content of PAB in the leaves
was about six times higher than that of lignin (Table 1).

232

V. Ossipov et al. / Biochemical Systematics and Ecology 29 (2001) 223–240

3.3. Nutritive compounds of birch leaves
HPLC analysis of protein hydrolysates indicated 17 individual amino acids; the
main components were leucine and glutamic and aspartic acids (data not shown).
The total protein content, as the sum of protein-bound amino acids, was about
130 mg g ÿ 1 of dry mass, with relatively low variability among trees (Table 1). The
proportion of free amino acids made up 0.5–0.9% of protein-bound amino acids; the
main compounds were histidine, glutamine, alanine, phenylalanine, proline, serine,
lysine and two unidentified amino acids (data not shown).
The soluble carbohydrates present in the birch leaves were glucose, fructose,
sucrose, inositol and galactose. The main compounds were galactose and sucrose.
For the characterization of this group of nutritive compounds only two parameters
were used: the content of galactose and the sum of the biochemically related
carbohydrates } glucose, fructose and sucrose (Table 1).
3.4. Phenolics as determinants of birch leaf quality for E. autumnata
In the pooled data, PAS was the only leaf trait which correlated significantly with
the RGR of E. autumnata larvae (Table 2). Since Feeny (1969, 1970), a negative
correlation between PAS and RGR has been found in numerous studies concerning
condensed tannins. In our experiment, however, PAS was not a strong determinant
of the suitability of leaves for E. autumnata larvae, explaining just 15% of the
variance in RGR (Table 2).

Table 2
Correlation coefficients and multiple regression coefficients between RGR of E. autumnata on leaves of 40
birch trees and parameters measured in these leaves
Measured parameter

Coefficient

Phenolic traits
Total soluble phenolics
Gallotannins
Proanthocyanidins soluble (PAS)
Proanthocyanidins bound (PAB)
Protein precipitation capacity of tannins (PPC)
Toughness of leaves
Lignin

ÿ 0.14
ÿ 0.04
ÿ 0.39a
ÿ 0.14
ÿ 0.01
ÿ 0.28
0.19

Nutritive compounds
Sum of individual carbohydrates
Galactose
Sum of protein-bound amino acids

0.24
ÿ 0.30
ÿ 0.04

Multiple r
r2
Significance
a

P50.05.

0.67
0.45
0.004

233

V. Ossipov et al. / Biochemical Systematics and Ecology 29 (2001) 223–240

3.5. Chemistry of trees with good and poor leaves for E. autumnata growth
The low correlation between the phenolic traits of birch leaves and their suitability
for E. autumnata larvae could be due to the nonlinear relationship between these
variables (Kause et al., 1999). The nonlinear estimation of the relationship between
the dependent variable RGR and the independent variable PAS divided our 40 study
trees at the breakpoint RGR=0.297 into two groups, with good (21 trees,
RGR>0.297) and poor (19 trees, RGR50.297) leaf quality for E. autumnata. The
use of other independent variables (total gallotannins, PAB, PPC and toughness)
gave the same breakpoint, RGR=0.297. Unlike the findings of Kause et al. (1999),
the difference between the two groups of trees in the suitability of leaves for E.
autumnata did not result significantly from differences in leaf flush phenology
(t ¼ 0:18; P ¼ 0:43).
The only leaf chemical traits that differed significantly between trees that
were good or poor for E. autumnata larvae were PAS and PAB (Table 3).
It is worth mentioning that neither the contents of individual phenolics
(gallotannins, chlorogenic and p-coumaroylquinic acids, quercetin-, myricetin-,
and kaempferol-glycosides) nor individual nutritive compounds (carbohydrates and
protein-bound amino acids) differed significantly between the two groups of trees
(data not shown).

Table 3
RGR of E. autumnata larvae on leaves of two groups of birch trees separated by nonlinear estimation of
RGR dependence on concentration of PAS and values of parameters measured in these leaves. For more
information see Table 1
Measured parameter

RGR of E. autumnata larvae

Good trees

Poor trees

Mean

Mean

0.336

SD
0.024

0.262

Significance of
differences

SD
0.031

Phenolic traits
Total soluble phenolics
Gallotannins
Proanthocyanidins soluble (PAS)
Proanthocyanidins bound (PAB)
Protein precipitation capacity of tannins (PPC)
Toughness of leaves
Lignin

126.17
9.00
100.63
39.12
322.76
80.52
7.65

20.64
3.90
20.57
8.42
78.51
8.68
0.83

128.59
7.52
113.05
45.02
309.49
81.17
7.60

19.45
5.60
12.29
8.33
86.44
11.95
1.12

Nutritive compounds
Sum of individual carbohydrates
Galactose
Sum of protein-bound amino acids

82.75
46.65
128.06

9.26
6.56
17.55

77.65
50.94
129.79

8.29
7.35
17.41

a
b

P50.001.
P50.05.

a

b
b

234

V. Ossipov et al. / Biochemical Systematics and Ecology 29 (2001) 223–240

Table 4
Correlation coefficients and multiple regression coefficients between RGR of E. autumnata on leaves of
two groups of trees and parameters measured in these leaves. For more information see Table 1
Measured parameter

Good trees

Poor trees

Phenolic traits
Total soluble phenolics
Gallotannins
Proanthocyanidins soluble (PAS)
Proanthocyanidins bound (PAB)
Protein precipitation capacity of tannins (PPC)
Toughness of leaves
Lignin

ÿ 0.20
ÿ 0.48a
ÿ 0.30
0.09
ÿ 0.60b
0.05
0.30

ÿ 0.13
ÿ 0.18
ÿ 0.09
0.35
ÿ 0.09
ÿ 0.67c
0.29

Nutritive compounds
Sum of individual carbohydrates
Galactose
Sum of protein-bound amino acids

ÿ 0.40
0.21
0.32

0.34
ÿ 0.30
ÿ 0.15

Multiple r
r2
Significance

0.69
0.48
0.005

0.90
0.81
0.0001

a

P50.05.
P50.01.
c
P50.001.
b

3.6. Leaf traits and growth of E. autumnata on good and poor trees
In the group of good trees, suitability of leaves for E. autumnata larvae correlated
negatively with the PPC of the extract (r ¼ ÿ0:60; P50:05) and total content of
gallotannins (r ¼ ÿ0:48; P50:05) (Table 4). Multiple regression analysis showed
that the traits used explained about 48% of the variation in RGR, and that the
contribution of PPC alone was about 36%. In addition, about 55% of the variation
in PPC was explained by total gallotannins, and only 15% by PAS.
In the group of poor trees, suitability of leaves for E. autumnata larvae correlated
negatively with leaf toughness only (r ¼ ÿ0:67; P50:05) (Table 4). Multiple
regression analysis indicated that all the leaf traits combined explained about 81%
of the variation in RGR. The contribution of toughness alone was 45%. Although
poor trees had significantly higher concentrations of PAS and PAB than good trees,
these traits did not correlate significantly with the growth of E. autumnata larvae
(Tables 3 and 4).

4. Discussion
Four phenolic and phenolic-related leaf traits correlated negatively with larval
growth, but in the pooled data only the concentration of PAS was a significant,

V. Ossipov et al. / Biochemical Systematics and Ecology 29 (2001) 223–240

235

although not a strong, predictor of larval growth. Within the groups of good and
poor trees for E. autumnata growth, on the other hand, concentration of
gallotannins, PPC and toughness } but not PAS or PAB } displayed significant
correlations with growth of E. autumnata larvae.
Previously, a negative correlation between total gallotannins and the performance
of E. autumnata larvae was found within the group of trees with a high concentration
of gallotannins in the leaves (Kause et al., 1999). In the present experiment, the
suitability of the leaves of good trees for E. autumnata correlated negatively
with total gallotannins and PPC, in spite of the relatively low concentration of

Fig. 1. An assumed scheme for the formation and action of phenolic and phenolic-related factors
determining the suitability of mountain birch leaves for E. autumnata larvae. Abbreviations: (PEP)
Phosphoenolpyruvate; (E4P) D-Erytrose-4-phosphate; (DAHP) 3-Deoxy-D-arabino-heptulosonate 7phosphate; (DHQ) 3-Dehydroquinate; (DHS) 3-Dehydroshikimate; (SH) Shikimate; (CH) Chorismate;
(TYR) tyrosine; (TRP) tryptophane; (PHE) phenylalanine (C6–C3) hydroxycinnamic acids; (GTS and
GTB) soluble and cell-wall-bound gallotannins; (PAS and PAB) soluble and cell-wall-bound
proanthocyanidins (+ and ÿ ) positive vs. negative effects of factors.

236

V. Ossipov et al. / Biochemical Systematics and Ecology 29 (2001) 223–240

gallotannins and the high concentration of proanthocyanidins. The significant effect
of gallotannins could operate via their high specific PPC compared with that of
proanthocyanidins (Ossipova et al., in press). Thus gallotannins may play an
important role in defending leaves from herbivores, probably by inhibiting the
herbivore’s digestive enzymes and by forming strong molecular complexes with
ingested proteins (Fig. 1, factor 1). However, high concentrations of gallotannins do
not necessarily lead to lower consumption of leaves. In some cases, the larvae
compensated for the effect of this factor on growth by consuming more (Kause et al.,
1999).
Unlike phenylpropanoids, the biosynthesis of gallotannins in higher plants
probably does not proceed via L-phenylalanine, one of the end products of the
shikimate pathway. It is assumed that they are formed from dehydroshikimic acid,
which is an intermediate compound of the shikimate pathway (Ishikura et al., 1984;
Gross, 1992). Evidence for the functioning of this pathway in mountain birch leaves
has been obtained recently (Ossipov et al., unpublished observations). The process of
gallotannin synthesis is less energy-costly than the formation of phenylpropanoids
(condensed tannins, lignin), and does not compete directly with protein synthesis for
phenylalanine. These are presumably the two main reasons why active gallotannin
synthesis and accumulation can coincide with the most active growth and
development of birch leaves (Haukioja et al., 1998). They may also explain why
gallotannins do not respond to environmental treatments in the ways the carbon
nutrient balance hypothesis (Bryant et al., 1993) and the growth differentiation
hypothesis (Lorio, 1986, Herms and Mattson, 1993) assume to be typical for
phenylpropanoids (Koricheva et al., 1998).
The second phenolic factor, which reduces the suitability of birch leaves for
E. autumnata, is that of proanthocyanidins (Fig. 1, factor 2). Earlier we have shown
that PAS are important for leaf suitability within the group of trees with a low
concentration of gallotannins (Kause et al., 1999). In the present study, PAS and
PAB were the only traits, which were significantly higher in the leaves of poor trees
as compared to good ones. However, the correlations between PAS and RGR were
low in the pooled data and not significant in the groups of good and poor trees.
Proanthocyanidins are a class of natural phenolic compounds with large variation in
chemical structure and molecular mass, and probably also in biological activity
(Haslam, 1988,1995; Reed, 1995). A potential explanation for the low correlation
between proanthocyanidins and the leaf suitability for E. autumnata is that their
content has been determined as a pooled value.
The third factor limiting the suitability of leaves for E. autumnata larvae is leaf
toughness (Fig. 1, factor 3). This was the best correlate with larval RGR in the group
of poor trees. The increase in toughness is the most obvious change in the process of
leaf growth and development. Thin and fragile leaves rapidly become thicker and
more difficult to tear apart; this may have a significant effect on the ability of insect
larvae to feed satisfactorily (Feeny, 1970; Coley, 1983; Coley and Barone, 1996). The
increase in leaf toughness is due to biochemical transformations in the cell wall,
which is composed of cellulose, hemicelluloses, pectins, proteins and various
phenolic compounds. It is known that the accumulation of lignin in the secondary

V. Ossipov et al. / Biochemical Systematics and Ecology 29 (2001) 223–240

237

wall of forming xylem cells is the main cause of their high durability (Sarkanen and
Hergeret, 1971; Luck et al., 1994). However, the presence of this phenolic polymer in
the primary cell walls of autotrophic tissues is not characteristic; in plant leaves,
lignin is localized mainly in xylem vessels (Stafford, 1988). A low content of lignin
and its unequal distribution in leaf tissues may explain why this phenolic polymer did
not participate directly in the formation of birch leaf toughness.
Instead of lignin, other phenolic compounds, such as proanthocyanidins,
flavonoid glycosides, and derivatives of hydroxybenzoic and hydroxycinnamic
acids have been found in the cell walls of autotrophic tissues (Shen et al., 1986;
Stafford, 1988; Strack et al., 1989; Keller et al., 1996). Birch leaves contain
relatively large amount of PAB, but there was no correlation between PAB and leaf
toughness.
Earlier work has demonstrated that gallotannin concentrations decrease rapidly
during leaf maturation, and we have suggested that this may be due to the
transformation of soluble gallotannins into insoluble cell-wall-bound constituents
(Ossipov et al., 1997). From a physiological point of view, this process may be
directly related to the formation of cell walls. It is even possible that the function of
the high PPC of gallotannins may be primarily for the contacting and binding of
gallotannins with the proteins and polysaccharides of the cell wall, and only
secondarily as a defensive mechanism against insects (Haslam, 1988, 1995). We
therefore suggest that the increasing toughness of birch leaves in the process of
maturation may be due to the accumulation of gallotannins or ellagitannins, the
products of gallotannin transformation, in the cell walls (Salminen et al.,
unpublished observations).
Summing up, the suitability of birch leaves for the main birch defoliator,
the larvae of E. autumnata, depends on the combined action of three phenolic
and phenolic-related factors: gallotannins, proanthocyanidins and toughness
(Fig. 1). The relative role and intensity of these factors, however, may differ in
different trees, depending on the age and developmental stage of the leaves
and on environmental factors. In the group of good trees, for instance, the
suitability of leaves for E. autumnata larvae was affected by all three phenolic
factors, but the concentration of gallotannins and their high ability to reduce
the digestibility of nutritive compounds may have been decisive. In the group
of poor trees, gallotannin concentrations and leaf toughness were the same as
in the good trees; the main chemical barrier limiting larval growth was
presumably formed by the more active accumulation of both PAS and PAB. We
assume that the leaves of good trees are incapable of maintaining the synthesis of
defensive proanthocyanidins at the level that is characteristic for trees resistant
against insects.

Acknowledgements
The authors wish to acknowledge grants from the Academy of Finland and from
the Turku University Foundation.

238

V. Ossipov et al. / Biochemical Systematics and Ecology 29 (2001) 223–240

References
Bank, R., Jansen, E., Beekman, B., te Koppele, J., 1996. Amino acid analysis by reverse-phase highperformance liquid chromatography: improved derivatization and detection conditions with 9fluorenylmethyl chloroformate. Anal. Biochem. 240, 167–176.
Bryant, J.P., Reichardt, P.B., Clausen T, .P., Werner, R.A., 1993. Effects of mineral nutrition on delayed
inducible resistance in Alaska paper birch. Ecology 74, 2072–2084.
Coley, P.D., 1983. Herbivory and defensive characteristic of tree species in a lowland tropical forest. Ecol.
Monographs 53, 209–229.
Coley, P.D., Barone, J.A., 1996. Herbivore and plant defenses in tropical forests. Annu. Rev. Ecol. Syst.
27, 305–335.
Dixon, R.A., Paiva, N.L., 1995. Stress-induced phenylpropanoid metabolism. Plant Cell 7, 1085–1097.
Douglas, C.J., 1996. Phenylpropanoid metabolism and lignin biosynthesis: from weed to trees. Trends
Plant Sci. 1, 171–178.
Feeny, P., 1969. Inhibitory effect of oak leaf tannins on the hydrolysis of protein by trypsin.
Phytochemistry. 8, 2119–2126.
Feeny, P., 1970. Seasonal changes in oak leaf tannins and nutrients as a cause of spring feeding by winter
moth caterpillars. Ecology 51, 565–581.
Feeny, P., 1976. Plant apparency and chemical defence. In: Wallace, J.W., Mansel, R.L. (Eds.), Recent
Advances in Phytochemistry, Vol. 10. Biochemical Interactions Between Plants and Insects, Plenum
Press, New York, pp. 1–40.
Gross, G., 1992. Enzymatic synthesis of gallotannins and related compounds. In: Stafford, H., Ibrahim, R.
(Eds.), Recent Advances in Phytochemistry, Vol. 26. Phenolic Metabolism in Plants, Plenum Press, New
York, pp. 297–324.
Hagerman, A.E., 1987. Radial diffusion method for determining tannin in plant extracts. J. Chem. Ecol.
13, 437–449.
Haslam, E., 1988. Plant polyphenols (syn. vegetable tannins) and chemical defence } a reappraisal. J.
Chem. Ecol. 14, 1789–1805.
Haslam, E., 1995. Natural polyphenols: complexation with peptides and proteins as a mechanism of action
in medicine. In: Autus, S., Ga´bor, M., Vetschera, K. (Eds.), Flavonoids and Bioflavonoids. Akade´miai
Kiado´, Budapest, pp. 13–33.
Haukioja, E., Niemela¨, P., Sire´n, S., 1985a. Foliage phenols and nitrogen in relation to growth, insect
damage, and ability to recover after defoliation, in the mountain birch Betula pubescens ssp. tortuosa.
Oecologia 65, 214–222.
Haukioja, E., Suomela, J., Neuvonen, S., 1985b. Long-term inducible resistance in birch foliage: triggering
cues and efficacy on a defoliator. Oecologia 65, 363–369.
Haukioja, E., Neuvonen, S., Hanhima¨ki, S., Niemela¨, P., 1988. The autumnal moth in Fennoscandia. In:
Berryman, A.A. (Ed.), Dynamics of Forest Insect Populations. Patterns, Causes, and Implications.
Plenum Press, New York, pp. 164–178.
Haukioja, E., Ossipov, V., Koricheva, J., Honkanen, T., Larsson, S., Lempa, K., 1998. Biosynthetic origin
of carbon-based secondary compounds: cause of variable responses of woody plants to fertilization?
Chemoecology 8, 133–139.
Herms, D.A., Mattson, W.J., 1992. The dilemma of plants: to grow or defend. Quart. Rev. Biol. 67,
283–335.
Inoue, K., Hagerman, A., 1988. Determination of gallotannin with rhodanine. Anal. Biochem. 169,
363–369.
Ishikura, N., Hayashida, S., Tazaki, K., 1984. Biosynthesis of gallic and ellagic acids with 14C–labeled
compounds in Acer and Rhus leaves. Bot. Mag. (Tokyo) 97, 355–367.
Kaitaniemi, P., Ruohoma¨ki, K., Ossipov, V., Pihlaja, K., Haukioja, E., 1998. Delayed induced
changes in the biochemical composition of host plant leaves during an insect outbreak. Oecologia 116,
182–190.
Kallio, H., Ahtonen, S., Raulo, J., Linko, R., 1985. Identification of the sugars and acids in birch sap. J.
Food. Sci. 50, 266–269.

V. Ossipov et al. / Biochemical Systematics and Ecology 29 (2001) 223–240

239

Kause, A., Ossipov, V., Haukioja, E., Lempa, K., Hanhima¨ki, S., Ossipova, S., 1999. Multiplicity of
biochemical factors determining quality of growing birch leaves. Oecologia 120, 102–112.
Keller, H., Hohlfeld, H., Wray, V., Hahlbrock, K., Scheel, D., Strack, D., 1996. Changes in the
accumulation of soluble and cell wall-bound phenolics in elicitor-treated cell suspension cultures and
fungus-infected leaves of Solanum tuberosu. Phytochemistry 42, 389–396.
Koricheva, J., Larsson, S., Haukioja, E., Keina¨nen, M., 1998. Regulation of woody plant secondary
metabolism by resource availability: hypothesis testing by means of meta-analysis. Oikos 83, 212–226.
Lange, M.B., Lapierre, C., Sandermann Jr., H., 1995. Elicitor-induced spruce stress lignin. Structural
similarity to early developmental lignins. Plant Physiol. 108, 1277–1287.
Lorio, O.L., 1986. Growth-differentiation balance: a basis for understanding southern pine beetle-tree
interactions. For. Ecol. Manage. 14, 259–273.
Luck, G., Liao, H., Murray, N., Grimmer, H., Warminski, E., Williamson, M., Lilley, T., Haslam, E.,
1994. Polyphenols, astringency and proline-rich proteins. Phytochemistry 37, 357–371.
Neuvonen, S., Haukioja, E., 1984. Low nutritive quality as defence against herbivores: Induced responses
in birch. Oecologia 63, 71–74.
Neuvonen, S., Haukioja, E., Molarius, A., 1987. Delayed inducible resistance against a leaf-chewing insect
in four deciduous tree species. Oecologia 74, 363–369.
Neuvonen, S., Haukioja, E., 1991. The effects of inducible resistance in host foliage on birch-feeding
insects. In: Tallamy, D.W., Raupp, M. (Eds.), Phytochemical Induction by Herbivores. Wiley, New
York, pp. 277–291.
Nurmi, K., Ossipov, V., Haukioja, E., Pihlaja, K., 1996. Variation of total phenolic content and lowmolecular-weight phenolics in foliage of the mountain birch trees (Betula pubescens ssp. tortuosa). J.
Chem. Ecol. 22, 2033–2050.
Ossipov, V., Nurmi, K., Loponen, J., Prokopiev, N., Haukioja, E., Pihlaja, K., 1995. HPLC isolation and
identification of flavonoids from white birch Betula pubescens leaves. Biochem. Syst. Ecol. 23, 213–222.
Ossipov, V., Nurmi, K., Loponen, J., Haukioja, E., Pihlaja, K., 1996. HPLC separation and identification of
phenolic compounds from leaves of Betula pubescens and Betula pendula. J. Chromatogr. A 721, 59–68.
Ossipov, V., Loponen, J., Ossipova, S., Haukioja, E., Pihlaja, K., 1997. Gallotannins of birch Betula
pubescens leaves: HPLC separation and quantification. Biochem. Syst. Ecol. 25, 493–504.
Ossipova, S., Ossipov, V., Haukioja, E., Loponen, J., Pihlaja, K. Proanthocyanidins of mountain birch
leaves: quantification and properties. Phytochem Anal., in press.
Reed, J.D., 1995. Nutritional toxicology of tannins and related polyphenols in forage legumes. J. Anim.
Sci. 73, 1516–1528.
Rhoades, D., Cates, R. (1976) Toward a general theory of plant antiherbivore chemistry. In: Wallace,
J.W., Mansel, R.L. (Eds.), Recent Advances in Phytochemistry, Vol. 1. Biochemical Interactions
Between Plants and Insects. Plenum Press, New York, pp. 168–213.
Ruohoma¨ki, K., Chapin III, F.S., Haukioja, E., Neuvonen, S., Suomela, J., 1996. Delayed inducible
resistance in mountain birch in response to fertilization and shade. Ecology 74, 30–38.
Ruohoma¨ki, K., Haukioja, E., Repka, S., Lehtila¨, K., 1997. Leaf value: effects of damage to individual
leaves on growth and reproduction of mountain birch shoots. Ecology 78, 2105–2117.
Sarkanen, K., Hergeret, H., 1971. Classification and distribution. In: Sarkanen, K., Ludwig, C. (Eds.),
Lignins. Occurrence, Formation, Structure and Reactions. Wiley Interscience, New York, pp. 43–94.
Statistica for Windows, 1994. Quick reference. StatSoft Inc., Tulsa, OK.
Shen, Z., Haslam, E., Falshow, C., Begley, M., 1986. Procyanidins and polyphenols of Larix gmelini bark.
Phytochemistry 26, 2629–2635.
Stafford, H., 1988. Proanthocyanidins and the lignin connection. Phytochemis