Research Journal of Agricultural Science, 49 ( 4), 2017

STUDIES REGARDING SOME MORPHOMETRIC AND BIOMASS

ALLOCATION PARAMETERS IN THE URBAN HABITAT ON PLANTAGO
MAJOR

Adina-Daniela DATCU1,2*, F. SALA1, Nicoleta IANOVICI2

1Banat’s University of Agricultural Sciences and Veterinary Medicine „King Michael I of
Romania” from Timișoara, Soil Science and Plant Nutrition
2West University of Timișoara, Biology-Chemistry Department
*E-mail address: dana_datcu19@yahoo.com

Abstract. The present paper presents data obtained from a biomonitoring study conducted in
the summer and fall of 2015 on Plantago major in Timișoara, Romania. P. major is a common perennial
herb used as a bioindicator due to its adaptability to environmental conditions and occurrence in many
urban habitats. Therefore, this species became of interest in habitat quality assessing. The studied
parameters were leaves areas (LA) and lengths using Digimizer software, which allows a nondestructive,
cheap and quick approach. Through other methods Specific Leaf Area (SLA), Total Dry Mass (TDM) and
Dry Biomass Allocation Ratio (DBAR) were calculated. While Leaf Area presented significant variations
among seasons and study zones, SLA values did not range so much. Furthermore, a strong association
between leaves lengths and areas was obtained. On the other hand, TDM presented the highest values for
the samples collected from Green Forest during the summer and the smallest values for the probes
sampled from Urban area during the autumn. Biomass allocation ratios had also variations, and
appeared that plants invested differently in aboveground or underground structures depending on season
and habitat type.

Keywords: biomonitoring, Digimizer, Leaf Area, urban zone, biomass allocation ratio.

INTRODUCTION
Air pollution is a topic of global concern and many studies have suggested the
necessity of using bioindicators to monitor air quality (KLUMPP et al., 1994). Advantages of
biomonitoring have been frequently discussed (WITTIG, 1993). Biological responses can be
considered more representative than data supplied by chemical or physical detectors, in that
they are spatially and temporally extensive; moreover, they allow for estimating both the levels
of pollutants and, even more importantly, the impact on biological receptors (CALZONI et al.,
2007). A large variety of organisms, such as lichens (LARSEN et al., 2007), herbs and trees,
have already been used in the biomonitoring of air pollution (HIJANO et al., 2005). Herbs can
be used in habitat quality assessment due to their wide distribution and high accessibility
(KARDEL et al., 2009).
Plantago major L. (common or greater plantain), member of the Plantaginaceae
family, is a perennial herb with rosette leaves. It is a very familiar weed and may be found
anywhere on roadsides, meadow-land, cultivated fields, waste areas, and canal banks (GALAL
AND SHEHATA, 2014). This species has already been used in biomonitoring in Timișoara,
Romania (IANOVICI et al., 2009). There are studies that compare the anatomical particularities
and the ecological adaptations of Plantago species from Romania (IANOVICI et al., 2011;
IANOVICI, 2011), but Plantago also was studied for its interactions with bacteria, viruses and
micoritic fungi (BLASZKOWSKI et al., 2006). Ecophysiological parameters such as Leaf
Relative Water Content – LRWC – were determined for this species (DATCU, 2014). The first
studies about quantifying the degree of colonization by the vesicular-arbuscular mycorrhizas
were realized on the species of the Plantago genus (IANOVICI, 2010). In 2010, a review

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synthetized the Romanian specialty literature in regards to Plantago species (IANOVICI et al.,
2010).
Less attention has been given to morphological and plant biomass parameters as
indicators of long-term habitat (urban) change, although parameters such as the specific leaf
area (SLA) have been recognized to vary depending on microclimatic conditions
(BALASOORIYAA et al., 2009). Leaf area (LA) is an important variable for most eco-
physiological studies in terrestrial systems regarding light interception, photosynthesis
efficiency, response to irrigation or fertilizers and yield of crop plants (BLANCO AND
FOLEGATTI, 2003). Determining this parameter with the Digimizer software is faster and
cheaper, allowing the user to store and process data, and review photos. It is also a non-
disruptive technique (IANOVICI et al., 2015).
The specific leaf area (SLA, foliar area per dry mass unit) is an important feature in
plant ecology because it is associated with many critical aspects of plant growth and survival,
which can lead to variations in the relative growth potential rate and plant behavior (LI et al.,
2005). Numerous authors have provided wide-ranging reviews of biomass allocation among
plants (e.g. REICH, 2002), the aboveground / underground biomass allocation ratio being a
parameter of interest in such studies.
The aim of this study was to apply an easy and fast method of calculating leaves areas
and specific leaf area on plants with bioindicator potential and to calculate and compare the
total dry mass and aboveground / underground biomass allocation ratio for Timișoara,
Romania.

MATERIALS AND METHODS

The study was conducted in Timișoara, Romania. The biological material to be
analyzed was represented by samples belonging to the species Plantago major. The specimens
were harvested in the 2015 summer, when the plants were in the flowering phenophase, and
autumn season respectively, corresponding to the fructifying phenophase. The research was
realized in two types of sites: urban area (U zone), represented by Titu Maiorescu Street, from
Timișoara, Romania and Green Forest (GF zone), located in the North-East part of the city,
representing an Urban Green area. The plants were brought in the laboratory, then washed and
organs were separated using a scalpel. From each plant a leaf was scanned, using a scanner (HP
Scanjet G3010) along with a piece of millimeter paper. The resulting images were processed
using the Digimizer Free Image Analysis Software, resulting the leaf area (LA) (cm2).
Digimizer also offers the possibility to analyze lengths of the leaves. Therefore a regression
was realized between lengths and areas of the leaves.
To determine the specific leaf area (SLA), the scanned leaves were then placed in an
oven (Sauter Model) for 2 hours at 85° C, then weighed using the analytical balance (Kern
Model), in order to determine Dry Weight (DW). SLA was calculated by dividing dry leaf
weight to leaf area (g * cm-2).
On the other hand, for the calculation of the biomass parameters, the organs of the
harvested samples were detached with a scalpel, washed and weighted using an analytical
balance, resulting FW – fresh weight. The samples were then placed in an oven for two hours
at 85° C. After drying, the organs were weighted obtaining the dry weight (DW) for each
organ.
TDM (g) was calculated as the sum of all organs dry weights.
DBAR - Dry biomass allocation ratio- was calculated by dividing the sum of all dry
weights specific to the aboveground organs to dry root weight (POORTER, 1999).
The statistical processing was realized using the GraphPad Prism 6 software.
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RESULTS AND DISCUSSION

A wide range of LA values was obtained for the P. major samples collected from the
investigated areas and between the studied seasons (Figure 1). The highest values of this
parameter were found for the samples which were sampled in summer from GF. Overall, leaf
area was bigger for the GF collected samples. Regarding U area, the biggest values for this
parameter appeared also for the samples harvested during summer. A t test indicated that
summer collected samples had significant higher values (p < 0.05) when compared to that
specific for fall. We also remarked a significant bigger value of this parameter for the samples
belonging to GF area (p < 0.01) when compared to those specific for U area.

Figure 1. Mean ± SD of LA (cm2) depending on investigated seasons and zones

Figure 2 represents the linear regression between foliar lengths (cm) and areas (cm2).
Following the completion of statistical analysis, a strong association between this two
parameters was noticed (r2 = 0.9026).

Figure 2. Regression between lengths of the leaves (cm) and LA (cm2)

Specific leaf area (SLA) presented small variations among the investigated seasons
and areas for the analyzed species (Figure 3). Thus the smallest mean values of this parameter
were obtained for the samples collected during summer. For this season, a slight grow was
recorded for the GF collected samples, by comparison with those from U area. The highest
average values appeared to GF samples collected during autumn.

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After completion of t test, no significant differences were found between the SLA
from the both seasons (p > 0.05). Also the values from the investigated sites were not
significantly different (p > 0.05).

Figure 3. Mean ± SD of SLA (g * cm-2) depending on investigated seasons and zones

The samples from GF area showed for both seasons higher values than those from U
zone (Figure 4). Also, TDM for both studied areas, was higher for samples harvested in the
summer. Through t test it was revealed that the samples collected in the summer had a
significantly higher TDM (p < 0.05), compared to the autumn collected samples. Probes
collected from the GF area in both seasons did not show significant differences compared to
those in the U area (p > 0.05).

Figure 4. Mean ± SD values of TDM (g)

The highest biomass allocation ratio was obtained for the summer collected samples
from GF area (Figure 5), the mean value in this case being 7.202. For this probes the
aboveground part was the most developed in comparison with the subterranean part,
represented by the root.
On the other hand, biomass allocation to aboveground in comparison with
underground was the smallest, with an average value of 2.618, for P. major individuals
collected from the U area in the summer. The plants which were collected during fall invested
more in aboveground structures, especially the ones that represent U area. For GF area there
was a bigger interval of variation for this parameter.
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Figure 5. Min to max values of dry biomass allocation ratio for both investigated areas and
seasons.

Leaf area is an important parameter for studies realized on light interception,

photosynthesis efficiency, the response to irrigation or fertilizers and the yield of crops
(BLANCO AND FOLEGATTI, 2003). Estimation of leaf area is also important in studies on plant
nutrition and competition between plants, plant-soil-water relationships, measures to protect
plants and heat transfer in plants (PANDEY AND SINGH, 2011). There are different techniques
used to determine LA: planimeters methods, photogravimetric methods (the gravimetric
method based on the weight of the paper cut-out of the silhouette leaf compared to the weight
of known areas on the same paper) and area-length regressions (IANOVICI et al., 2015).
Scanning leaf with is a quick and cheap technique which provide the possibility for automatic
calculation of this parameter.
Models of optimal biomass allocation in plants predict decreasing root allocation with
increasing nutrient availability (BLOOM et al., 1985). Regarding the allocation of all
environmental factors, it is known that irradiance has the strongest effect, but nutrient levels
also have a large effect, which becomes more pronounced after a size correction, as does the
effect of temperature. However, in most cases, important foliar functional traits (SLA) are far
more variable than allocation traits across species, a statement that, with the exception of
nutrient stress, extends to most environmental effects (POORTER et al., 2012). Moreover, plants
change their reproductive allocation patterns in response to competition. When plants are not
crowded, they behave more like ‘r-selected’ species, allocating a large proportion of their
biomass to reproductive structures (high reproductive effort). When plants are crowded, on the
other hand, they behave more ‘K’ like, allocating less of their biomass to reproductive
structures and a greater proportion to competitive structures such as stems and leaves (WEINER,
2004). Therefore, further studies on crowded and not crowded are useful.

CONCLUSIONS
Digimizer Free Image Analysis Software is a useful analysis tool that allows a quick
and easy approach of the samples. By aggregating the data obtained with this software with
DW for each leaf, the specific leaf area can be calculated very quickly.
Leaves areas had the biggest values for the samples collected in summer from GF
zone.
There is a strong association between LA and lengths of the leaves.
Although, in this study, LA has shown large variations depending on the vegetation
season, the SLA grew slightly in Plantago during autumn.
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TDM and biomass allocation ratio had also the biggest values on summer GF probes.
In conclusion, it was noticed that P. major individuals show a phenotypic plasticity.

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