Phytotests for assessing phytotoxicity of "Blue moon" liquid detergent: Lens culinaris seeds. https://www.researchgate.net/publication/355172426

Abstract

The phytotests for phytotoxicity assessment is to analyze the developmental responses of plant seeds to hazardous materials in the environment. The effectiveness of the phytotests in testing the varied contaminants was validated and reported. However, the phytotoxicity of synthetic laundry de tergents (SLDs) is poorly understood. Accordingly, "Blue moon" liquid laundry detergents ("Blue moon"-LLD) was targeted as a contaminant in study. Lentil (Lens culinaris) tests were used to test the phytotoxicity of "Blue moon"-LLD. Consequences showed percent germination of seed (PGS, ca. 0%-80%) and root length (RL, ca. 0-5 mm) decreased significantly toward the increase in concentration (0.0%, 0.1%, 0.5% and 1.0%) of "Blue moon"-LLD after 72-h. Exposure to the "Blue moon"-LLD throughout 96-h further lowered PGS (ca. 0%-90%) and RL (ca. 0-9 mm). Correlation analysis proved a negative linearity (k =-155.84, R 2 = 0.97, 72-h; k =-173.12, R 2 = 0.98, 96-h) between test concentrations and PGS and between the concentrations and RL (k =-10.4, R 2 = 0.91, 72-h; k =-15.48, R 2 = 0.94, 96-h). It manifested that the phytotoxicity of "Blue moon"-LLD was a concentration-dependent toxicity. The study is aimed at validating the sensitivity, effectiveness, alternative use of animal toxicity tests and inexpensive phytotesting protocol for phytotoxicity assessment.

Full text

Issues in Biological Sciences and Pharmaceutical Research Vol.9(3),pp.93-100, October 2021
Available online at https://www.journalissues.org/IBSPR/
https://doi.org/10.15739/ibspr.21.010
Copyright © 2021 Author(s) retain the copyright of this article ISSN 2350-1588
Original Research Article
Phytotests for assessing phytotoxicity of “Blue moon”
liquid detergent: Lens culinaris seeds
Received 12 August, 2021 Revised 26 September, 2021 Accepted 1 October, 2021 Published 10 October, 2021
Xiang Cai1,2*
and
S.A. Ostroumov1,2
1Laboratory of Physico-Chemistry
of Biomembranes, Faculty of
Biology, Lomonosov Moscow State
University, Moscow 119991,
Russian Federation.
2Laboratory of Ecological
Department, School of Biology,
Shenzhen MSU-BIT University,
Shenzhen 518172, China.
*Corresponding Author
Email: caisan_100@yahoo.com
Tel. (86) 18859822190
The phytotests f or phytotoxicity assessment is to analyze the developmental
responses of plant seeds to hazardous materials in the environment. The
effectiveness of the phytotests in testing the varied contaminants was
validated and reported. However, the phytotoxicity of synthetic laundry
detergents (SLDs) is poorly understood. Accordingly, “Blue moon” liquid
laundry detergents (“Blue moon”-LLD) was targeted as a contaminant in study.
Lentil (Lens culinaris) tests were used to test the phytotoxicity of “Blue
moon”-LLD. Consequences showed percent germination of seed (PGS, ca. 0%-
80%) and root length (RL, ca. 0-5 mm) decreased significantly toward the
increase in concentration (0.0%, 0.1%, 0.5% and 1.0%) of “Blue moon”-LLD
after 72-h. Exposure to the “Blue moon”-LLD throughout 96-h further lowered
PGS (ca. 0%-90%) and RL (ca. 0-9 mm). Correlation analysis proved a
negative linearity (k = -155.84, R2 = 0.97, 72-h; k = -173.12, R2 = 0.98, 96-h)
between test concentrations and PGS and between the concentrations and RL
(k = -10.4, R2 = 0.91, 72-h; k = -15.48, R2 = 0.94, 96-h). It manifested that the
phytotoxicity of “Blue moon”-LLD was a concentration-dependent toxicity. The
study is aimed at validating the sensitivity, effectiveness, alternative use of
animal toxicity tests and inexpensive phytotesting protocol f or phytotoxicity
assessment.
Keywords: Phytotests, “Blue moon”, seed germination, root elongation, Lens
culinaris
INTRODUCTION
The potential application of plant seeds to ecotoxicity tests
for hazardous materials catches significant attention of eco-
toxicologists to phytotests. The seed germination (SG) and
the root elongation (RE) of the seeds were measured in the
phytotests (Bellino et al., 2018; Di Salvatore et al., 2008; EPA,
1996; Khan et al., 2019). SG and RE are two significant
endpoints for the phytotoxicity assessments of contaminants
(Bellino et al., 2018; Di Salvatore et al., 2008; Luo, et al.,
2019). The xenobiotic effects and oxidative stress on the SG
and RE were well documented at the lethal or sublethal
concentration of contaminants (Bengtson Nash et al., 2005;
Chang et al., 2015). The xenobiotics might cause a hormetic
response at low concentrations. However, concentrated
xenobiotic solution could inhibit SG and RE until sterilizing
the seeds (Bengtson Nash et al., 2005; Ostroumov, 1990). On
the other hand, the chemical oxidative stress might lead to
an irreversible damage to SG and RE because of the reactive
oxygen species (ROS) (Gomes et al., 2019; Khan et al., 2019;
Mtisi and Gwenzi, 2019). Therefore, SG and RE could be the
effective endpoints for toxic contaminants. In addition,
dozens of phytotests were carried out by trial and error of
various plants to validate the phytotesting sensitivity
(Bellino et al., 2018; Bhat et al., 2019). For example,
Ostroumov et al. (2014, 2014s and 2017) substantiated that
SG and RE were also highly sensitive endpoint measures of
phytotoxicity (Ostroumov, 2017; Ostroumov et al., 2014;
Ostroumov and Solomonova, 2014). So far, it has been
proved that SG and RE are both effective and sensitive

Issues Biol. Sci. Pharma. Res. 94
endpoints.
To date, a large quantity of plant species has been reported
in the successful cases of phytotoxicity tests. For examples,
tomato (Solanum lycopersicum) (Bellino et al., 2018, Di
Salvatore et al., 2008, Pan and Chu 2016), lettuce (Lactuca
sativa) (Bagur-González et al., 2010, Di Salvatore et al., 2008;
Lago-Vila et al., 2019; Mtisi and Gwenzi, 2019), maize (Zea
mays) (Bhat et al., 2019; Gomes et al., 2019), wheat
(Triticum aestivum) (Chang et al., 2015, Lian et al., 2020),
Chinese cabbage (Brassica rapa) (Luo et al., 2019), carrot
(Daucus carota) (Pan and Chu, 2016), cucumber (Cucumis
sativus) (Pan and Chu, 2016), lentil (Lens culinaris) (Khan et
al., 2019; Ostroumov, 2017), macrophytes (Elodea canadensis
(Ostroumov and Solomonova, 2014) and Ceratophyllum
demersum (Ostroumov et al., 2014)), etc. Most of them are
recommended by the United States Environmental
Protection Agency (USEPA) as model test plants (EPA, 1996).
Among them, the lentil (Lens culinaris) tests showed a wide
range of sensitivity and effectivity toward varied toxic
contaminants (Khan et al., 2019; Ostroumov, 2017).
The phytotesting protocol that prioritized Lens culinaris
possessed the following advantages. Compared to the
chemical tests, the phytotests were not only able to measure
the results but also show the dynamical biotic response to
toxicants (Bengtson Nash et al., 2005; Bhat et al., 2019).
Unlike the microbial tests, the phytotests could play critical
role in vitro and in vivo tests like animal tests (Bhat et al.,
2019). Apart from animal tests, however, the phytotests
concern the vascular terrestrial plants rather than living
animals. It has therefore never challenged bioethics
(Ostroumov, 2017). Besides, the phytotests cost less than
chemical, microbial and animal tests (Bhat et al., 2019, Pan
and Chu, 2016). All of these advantageous illustrations
determined that the phytotests are potentially alternative
and inexpensive biotests for toxicity assessments.
The phytotesting protocol is used for testing a broad
variety of contaminants. It can be to test some single-
components of a detergent, such as antibiotics (Bellino et al.,
2018; Gomes et al., 2019; Luo et al., 2019; Pan and Chu,
2016), herbicides (Bengtson Nash et al., 2005), sodium
dodecyl sulfate (SDS) (Chang et al., 2015, Lazareva and
Ostroumov, 2009), the nanomaterials (Khan et al., 2019;
Lago-Vila et al., 2019; Lian et al., 2020; Ostroumov et al.,
2014), various heavy metals (Bagur-González et al., 2010; Di
Salvatore et al., 2008), etc. Also, it is applicable for toxicity
tests of contaminant mixtures like coal ash (Mtisi and
Gwenzi, 2019), synthetic detergents (Ostroumov and
Solomonova, 2014; Warne and Schifko, 1999), industrial
effluents (Bhat et al., 2019), etc. The phytotoxicity of the
synthetic multicomponent detergent (e.g., SLDs), however,
remains unclear, except that toxicity of the single-
components (e.g., alkaline agents, surfactants, builders,
enzymes, etc.) of detergents were reported. (Bajpai and
Tyagi, 2007; Ostroumov and Solomonova, 2014; Warne and
Schifko, 1999).
Lens culinaris is a widespread plant species in the
terrestrial ecosystems. It shows a favorable performance of
phytotoxicity assessment. Hence, Lens culinaris is a model
plant for environmental risk assessment (Khan et al., 2019).
Furthermore, Lens culinaris seeds are the elementary
vegetable foodstuffs through the trophic webs to affect
humans. Thus, Lens culinaris phytotests can account for
human health assessment as a bioindicator (Lago-Vila et al.,
2019, Pan and Chu, 2016).
The study carried out an array of Lens culinaris tests that
subcategorized SG tests and RL tests, dividedly. Seed
germination index (SGI) and root length index (RLI) worked
out for the qualitative assessment of phytotoxicity. The
objective of study is to build a validated phytotesting system
for liquid detergent ecotoxicity tests, in which 1) SGI and REI
are calculated for ecotoxicological assessment; 2) correlation
analysis can show relationship between test concentrations
and SG or RE. Finally, a sensitive, effective, alternative and
inexpensive phytotesting protocol of using Lens culinaris
seeds was validated.
MATERIALS AND METHODS
“Blue moon” detergent and Lens culinaris seeds
“Blue moon”-LLD are supplied by Blue Moon group Co., Ltd,
(Guangzhou, China). The formulation of “Blue moon”-LLD is
composed of anionic surfactant (8%-18%), preservatives
(2%-6%), stabilizers (< 1%), enzymes (0.3%-0.8%),
conditioners (< 1%), colorant (< 1%) and fragrances (< 1%),
etc. The 10 g liquid detergent dissolved in 3 L water (≈
0.3%) is best ratio for laundry cleaning. Hence, the test
concentrations were determined at 0.0%, 0.1%, 0.5% and
1.0%. Lens culinaris seeds were purchased from Ailimeng
Seed Sci-Tech Co., Ltd (Shanghai, China). All the solutions
used in this work were prepared with ultrapure water.
Phytotestsing preparations
Phytotesting preparations include test solution and test seed
preparation. To prepare the stock solution (1.0% test
solution), the commercial “Blue moon”-LLD mixture was
pipetted and diluted at the ratio of 1:100 (v/v). Other test
solutions (0.1% and 0.5% test solutions) were prepared on
the basis of the stock solution. The ultrapure water was set
as blank control (0.0% test solution) for the guarantee of
Lens culinaris seed viability. All the test solutions were
prepared freshly for the phytotests. The rest of stock
solution was stored in a fridge (4 °C) for subsequent use.
To prepare test seeds, the handpicked seeds were
immersed (5 min) and rinsed (3 times) using ultrapure
water before the phytotests. A sheet of round filter paper
(110 mm Whatman No. 1) was laid on the bottom of each
glass Petri dish (100 × 15 mm). Finally, the sanitary seeds
were divided evenly into 12 dishes at random. Each Petri
dish therefore contained 30 seeds.
Phytotesting procedures
The phytotests were carried out by incubating Lens culinaris

Figure 1 : Morphology of Lens culinaris seeds imaged after 96-h
exposure to “Blue moon”-LLD. The SG tests after 96-h incubation in
(a) 0.0% (control), (b) 0.1%, (c) 0.5% and (d) 1.0% “Blue moon”-
LLD (20 mL) at 20.0±1.5 °C. Moreover, the magnified (3 times as
large) images focused on Lens culinaris RE after 96-h testing in (e)
0.0% (control), (f) 0.1%, (g) 0.5% and (h) 1.0% “Blue moon”-LLD.
seeds for 72-h or 96-h of exposure to “Blue moon”-LLD
solution at various concentrations (0.0% (control), 0.1%,
0.5% and 1.0%). Each Petri dish contained 30 test seeds.
Each group encompassed test dishes in triplicate (i.e., 3 of
the total 12 dishes tested at same concentration) at 0.0%
(control), 0.1%, 0.5% and 1.0% of “Blue moon”-LLD
solution. Consequently, the samples in triplicate were
moistened with a test solution (20 mL, 0.0%, 0.1%, 0.5% or
1.0% concentration). All the test samples were incubated in
the dark at 20.0±1.5 °C. After 72-h and 96-h, the number of
germinated seeds was counted manually, while the length
Cai and Ostroumov 95
of elongated root was measured with twitter and ruler.
Notably, 1-plus mm of RL was valid for the germinated seeds
in this study (Di Salvatore et al., 2008; Gomes, et al., 2019).
Morphological analysis
A high-resolution digital camera (Nikon, Tokyo, Japan) was
employed to characterize morphology of each test sample
for 96-h exposure to the concentrations of 0.0% (control),
0.1%, 0.5% and 1.0%. The most characteristic images were
selected and combined together as shown in Figure 1 (a),
(b), (c) and (d). The magnified images (Figure 1 (e), (f), (g)
and (h)) were listed on the right side, while original ones
(Figure 1 (a), (b), (c) and (d)) are on the left.
Data analysis
Microsoft Excel 2019 was used to calculate PGS (%) and RL
(mm). The results of PGS and RL were expressed in forms of
mean ± standard error. The Excel worksheet offers t-test to
examine the statistical difference (p < 0.05, significance; p >
0.05, insignificance) between control (0.0%) and test
groups (0.1%, 0.5% and 1.0%).
To assess the phytotoxicity, the raw data were further
converted to SGI by Eq. (1) and RLI by Eq. (2) as follows,
(1)
(2)
where NT (i) and NC represent the number of germinated
seeds in test (i) and in control, respectively. LT (i) and LC
denote the mean root length in test (i) and in control. Based
on SGI and RLI values, four empirical assessments of
phytotoxicity were reported, such as (1) slight (-0.25 ≤ SGI
or RLI < 0), (2) moderate (-0.5 ≤ SGI or RLI < -0.25), (3) high
(-0.75 ≤ SGI or RLI < -0.5), and (4) extreme toxicity (-1 ≤ SGI
or RLI < -0.75) (Bagur-González et al., 2010; Mtisi and
Gwenzi, 2019).
Linear analysis
The linear analysis was to understand the concentration-
response correlation. Origin Program 2018 software was
used to plot the decrease in PGS and RL along with the
increasing concentration in Figure 4. The mean values of
PGS (Figure 4 (a)) and RL (Figure 4 (b)) were expressed
with scatterplots. The error bars denoted standard errors.
The software also established linear analysis of the
scattering points versus test concentrations. The linear
regression equations showed the correlation coefficients (k)
and the determination coefficient (R2).
RESULTS AND DISCUSSION
Morphological images
The morphological characteristics of Lens culinaris SG and

Issues Biol. Sci. Pharma. Res. 96
Table 1. Summary of Lens culinaris SG phytotests for “Blue moon”-LLD. The tests were carried out at each concentration
(0.0% (control), 0.1%, 0.5% and 1.0%) kept at 20.0±1.5 °C in the dark for 72 h and 96 h, respectively.
Concentration (%)
72 h
96 h
PGS (%)
SGI
PC
PGS (%)
SGI
PC
0.0 (control)
83.33 ± 3.93
0.00
-
88.89 ± 2.27
0.00
-
0.1
41.67 ± 6.80
-0.50
High
41.67 ± 3.41
-0.53
High
0.5
0.00 ± 0.00
-1.00
Extreme
0.00 ± 0.00
-1.00
Extreme
1.0
0.00 ± 0.00
-1.00
Extreme
0.00 ± 0.00
-1.00
Extreme
SG: seed germination, “Blue moon”-LLD: “Blue moon” liquid laundry detergent, PGS: percent germination of seed (mean ± standard error),
SGI: seed germination index, PC: phytotoxicity class.
Table 2. Summary of Lens culinaris RE phytotests for “Blue moon”-LLD. The tests were carried out at each concentration
(0.0% (control), 0.1%, 0.5% and 1.0%) kept at 20.0±1.5 °C in the dark for 72 h and 96 h, respectively.
Concentration (%)
72 h
96 h
RL (mm)
RLI
PC
RL (mm)
RLI
PC
0.0 (control)
5.2 ± 0.5
0.00
-
9.0 ± 1.2
0.00
-
0.1
3.2 ± 0.5
-0.57
High
5.6 ± 0.5
-0.71
High
0.5
0.0 ± 0.0
-1.00
Extreme
0.0 ± 0.0
-1.00
Extreme
1.0
0.0 ± 0.0
-1.00
Extreme
0.0 ± 0.0
-1.00
Extreme
RE: root elongation, “Blue moon”-LLD: “Blue moon” liquid laundry detergent, RL: root length (mean ± standard error), RLI: root length index,
PC: phytotoxicity class.
RE over 96-h incubation were imaged in Figure 1. Figure 1
(a) showed the morphology of Lens culinaris SG tested at
0.0% (control), (b) at 0.1%, (c) at 0.5% and (d) at 1.0%.
Most (ca. 90%) of germinated seeds were observed in
Figure 1 (a), which validated the viability of Lens culinaris
seeds (Chang et al., 2015; Gomes, et al., 2019). As the
concentration increased, the number of SG plummeted at
0.1% concentration (Figure 1 (b)). All of the seeds
unfortunately perished at 0.5% (Figure (c)) and 1.0%
concentrations (Figure (d)). The observation was consistent
with the PGS (%) calculation presented in Table 1 and Figure
2. To better observe RE morphology, Figure 1 (e) was
magnified (3 times as large) from Figure 1 (a). In turn,
Figure 1 (f), (g) and (h) were from (b), (c) and (d),
accordingly. The blooming RE appeared in the control
sample (Figure 1 (e)), while undeveloped RE could be found
in 0.1% (Figure 1 (f)) and 0.5% (Figure 1 (g)) test group,
respectively. The magnified image (Figure 1 (h)) of 1.0%
test group showed the ungerminated seeds, and no RE was
measurable. In summary, the morphological RE (shown as
RL (mm) parameter in Table 2 and Figure 3) decreased in
proportion to SG (shown as PGS (%) in Table 1 and Figure
2).
SG phytotests
The PGS values obtained in SG phytotests were listed in
Table 1 and graphed in Figure 2. Table 1 showed the highest
PGS value (83.33% ± 3.93%, p < 0.05, 72-h) in control, the
intermediate PGS value (41.67% ± 6.80%, p < 0.05, 72-h) in
0.1% test group. However, no obvious PGS (0.0%, p < 0.05)
in both 0.5% and 1.0% test groups were observed. The
similar PGS values (Table 1) could be obtained in control
(88.89% ± 2.27%, p < 0.05), 0.1% (41.67% ± 3.41%, p <
0.05), 0.5% and 1.0% (0.0%, p < 0.05) test groups over 96-h
of exposure. The statistical difference (p-test, p < 0.05) was
significant. It manifested that Lens culinaris SG was
sensitive to “Blue moon”-LLD (Bagur-González et al., 2010).
However, the statistical difference (p-test, p > 0.05) between
72-h and 96-h testing was insignificant. It revealed that 72-h
phytotests had already been able to satisfy the phytotoxicity
assessment (Ostroumov, 2017; Ostroumov, et al., 2014). The
results of SG phytotests were graphed in Figure 2. All the SG
results were consistent with the morphological images
(Figure 1) and the following RE results (Table 2 and Figure
3).
RE phytotests
The RL values in RE phytotests were given in Table 2 and
depicted in Figure 3. Table 2 showed the RL value (5.2 ± 0.5
mm, p < 0.05) in 0.0%, the RL value (3.2 ± 0.5 mm, p < 0.05)
in 0.1%, and no RL (0.0 mm, p < 0.05) in 0.5% and 1.0% test
groups. Table 2 also presented a decreasing trend towards
RL values (9.0 ± 1.2 mm in controls, 5.6 ± 0.5 mm in 0.1%,
0.0 mm in 0.5% and 1.0% test groups, all p < 0.05) after 96-
h period of RE phytotests. Compared to SG, RE was a more
dynamical and quantitative endpoint of “Blue moon”-LLD
toxicity assessment. For example, RE results in control after
72-h differed significantly from the counterparts after 96-h
in statistical analysis, which implied that seed roots could
sustain the elongation in healthy environment with time
going on. (Chang et al., 2015; Di Salvatore et al., 2008). This
is largely due to the direct exposure of the roots to the “Blue

Cai and Ostroumov 97
Figure 2: The PGS variations of Lens culinaris seeds after 72-h and 96-h testing for “Blue moon”-LLD
at different concentrations. The SG phytotests (72-h and 96-h testing) of “Blue moon”-LLD at each
concentration (0.0% (control), 0.1%, 0.5% and 1.0%) were measured as PGS (mean ± standard error,
%). The column and error bars represent the mean values of PGS and their standard errors,
respectively. The statistical analysis shows the significant difference (p < 0.05) between every test and
control
-0.1 0.0 0.1 0.2 0.3 0.4 0.5 1.0
0
2
4
6
8
10
12
RL (mm)
Concentration (%)
72 h
96 h
Figure 3: The RL variations of Lens culinaris seeds after 72-h and 96-h testing for “Blue moon”-LLD at
different concentrations. The RE phytotests (72-h and 96-h testing) of “Blue moon”-LLD at each
concentration (0.0% (control), 0.1%, 0.5% and 1.0%) were measured as RL (mean ± standard error, %).
The column and error bars represent the mean values of RL and their standard errors, respectively. The
statistical analysis shows the significant difference (p < 0.05) between every test and control.
moon”-LLD solution (Figure 1). This demonstrated Lens
culinaris RE phytotests were more sensitive than SG
phytotests for testing phytotoxicity (Bagur-González et al.,
2010; Bellino et al., 2018; Mtisi and Gwenzi, 2019; Pan and
Chu, 2016). For better comparisons, all the RE phytotesting
results were illustrated in Figure 3.

Issues Biol. Sci. Pharma. Res. 98
0.0 0.1 0.2 0.3 0.4 0.5
0
2
4
6
8
10
0.0 0.1 0.2 0.3 0.4 0.5
0
20
40
60
80
100 72 h, y = 4.77 - 10.4x, R2 = 0.91
96 h, y = 7.48 - 15.48x, R2 = 0.94
RE (mm)
Concentration (%)
b
72 h, y = 77.83 - 155.84x, R2 = 0.97
96 h, y = 86.44 - 173.12x, R2 = 0.98
PGS (%)
Equation
Plot
Weight
Intercept
Slope
Resid ual Sum of Square
Pearso n's r
R-Square (COD)
Adj. R-Square
a
Figure 4: Correlation analysis of the PGS (%) and the RE (mm). (a) The PGS (mean ± standard error), and the (b) RE
(mean ± standard error) as the function of “Blue moon”-LLD concentrations over 72-h and 96-h testing were analyzed,
respectively. Error bars represent the standard errors.
Figure 5: Schematic diagram of Lens culinaris phytotests.
Correlation analysis
The PGS versus “Blue moon”-LLD concentration were well-
fitted with negative linear correlation (k = -155.84, R2 =
0.97, 72-h; k = -173.12, R2 = 0.98, 96-h) shown in Figure 4
(a). Likewise, a negative linearity (k = -10.4, R2 = 0.91, 72-h;
k = -15.48, R2 = 0.94, 96-h) between RL and “Blue moon”-
LLD concentrations was given in Figure 4 (b). The linear
models estimated that SG and RE diminished linearly until
no detection. This suggested the phytotoxicity was a
concentration-response effect on Lens culinaris SG and RE
(Chang et al., 2015; Mtisi and Gwenzi, 2019). Threshold
value is also a key parameter to assess environmental risks
and human health in toxicological researches (Mtisi and
Gwenzi, 2019). Up to now, many articles encouraged the use
of the half maximal effect concentration (EC50) as threshold
value for toxicity assessments (Mtisi and Gwenzi, 2019; Pan
and Chu, 2016; Warne and Schifko, 1999). Finally, the linear
regression equations (Figure 4 (a) and (b)) could estimate
EC50 of SG at 0.25% of PGS and EC50 of RE at 0.25% of RL,
respectively. The threshold EC50 could be regarded as the
Chinese national standard of detergent discharge.
Phytotoxicity assessment
To assess the phytotoxicity of “Blue moon”-LLD, the PGS
were converted to SGI by Eq. (1) and listed in Table 1. RLI
were converted from RL by Eq. (2) and listed in Table 2. If
the control was regarded as no toxicity (0.00), SGI (-0.50,
72-h; -0.53, 96-h) in 0.1% test group indicated that the

phytotoxicity class (PC) was high (Bagur-González et al.,
2010; Mtisi and Gwenzi, 2019). According to this, SGI values
in 0.5% and 1.0% test samples (Table 1 and Figure 1 (c), (d),
(g) and (h)) equated to -1.00. it suggested “Blue moon”-LLD
at 0.5% and 1.0% concentration was extremely phytotoxic.
Similarly, RLI (-0.57, 72-h; -0.71, 96-h) in 0.1% showed high
phytotoxicity. Also, extreme phytotoxicity was exhibited by
RLI (-1.00, 72-h; -1.00, 96-h) in both 0.5% and 1.0% test
samples. 0.1% test sample attested that RLI (-0.57, 72-h; -
0.71, 96-h) were both less than SGI (-0.50, 72-h; -0.53, 96-
h). In summary, the lower the value of SGI and RLI was, the
higher phytotoxicity would be. Thus, RLI was the more
restricted phytotoxic index than SGI due to the higher
sensitivity of RE than SG (Mtisi and Gwenzi, 2019).
Future perspective and outlook
The procedure of Lens culinaris phytotesting protocol was
described through a schematic diagram in Figure 5. The
Lens culinaris phytotesting method systematically include
two parts, SG and RE phytotests. All PGS and RL data (Table 1
and 2) supported that SG and RE were sensitive and
effective endpoints to phytotoxicity assessment. In
consequence, both SG and RE phytotests ensure the
technical qualification for future application.The
diagrammatic structure of phytotests (Figure 5) explains
why the method is convenient and applicable for
phytotoxicity assessments (Bhat et al., 2019). Comparing to
animal tests, the phytotests will never challenge bioethics.
Moreover, phytotests can keep the results in conformity with
animal tests (Ostroumov, 2017). In the future perspective,
the sustainable, ecofriendly and non-animal tests can
facilitate the technical progress and application. In addition,
cost-efficiency, low risk, and data reproducibility also shed
the light on the applicable prospect of environmental risks
and human health assessments.
CONCLUSION
Lens culinaris phytotests for phytotoxicity assessment of
“Blue moon”-LLD were validated in the study. In the
phytotests, the Lens culinaris seeds were used to screen for
phytotoxicity at various concentrations. SG and RE
decreased linearly until no observable measurements as the
concentration increased. Liner correlation analysis showed
that either PGS or RL versus concentration was a
concentration-response relationship. EC50 could be the
threshold value of “Blue moon”-LLD effluent in wastewater
dischargement. SGI and RLI showed that no toxicity in
control, high toxicity in 0.1%, and extreme toxicity in 0.5%
and 1.0% test samples. In conclusion, Lens culinaris test is a
sensitive, effective, inexpensive and alternative phytotest for
environmental risks and human health assessments.
ACKNOWLEDGEMENTS
The facilities used in the research work were kindly offered
Cai and Ostroumov 99
by the Faculty of Biology in Moscow State University, and
supported by SMBU University in the claimed principle. It is
particularly worthwhile to appreciate the Shenzhen
government patronage of this scientific project.
Conflict of Interests
The authors declare that there is no conflict of interests
regarding the publication of the paper.
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