Introduction
The green leafy vegetables that provide
tremendous health-beneficial vitamins, minerals, antioxidants, and dietary
fibers are low in calories, but also cause low sodium content, lack of trans
fatty acids and saturated fat (Mazahar et al.
2015). These are also enriched with nitrate and nitrite injurious to
human health when used in surplus (Additives et
al. 2017; Roila et al. 2018). Nitrogen fertilization plays
the most important role in the growth and development of plants being limiting
nutrient which affects yields as well (Ozdemir et
al. 2010; Rehman et al. 2013; Rasool et al. 2019). Excessive fertilization,
however, usually results in the accumulation of nitrate, which is often
harmful. High N fertilization also increases the level of carotene and
decreases the level of vitamin C in plants (Chenard
et al. 2005). Moreover, the decreased nitrogen limits the growth,
yields and leaf area index (Cheema et al.
2001).
Photosynthesis is the
primary physiological process of converting solar energy into chemical energy.
The obtained chemical energy is used to synthesize organic materials from
inorganic substances such as carbon dioxide (CO2) and water (H2O),
resulting in oxygen release (O2) (Tkemaladze
and Makhashvili 2016; Xiankui and Chuankuan 2018). Photosynthetic
pigments are the centroid dependent on the number of processes of
photosynthesis, including primary reaction, photophosphorylation, and
assimilation of CO2 (Trebst and Avron
2012). Chlorophyll fluorescence is another tool associated with photosynthesis
and its underlying processes. Therefore, chlorophyll fluorescence may be used
to research the relationship between stress and photosynthesis. Any stress
effect on photosynthesis can be detected by changing the dynamics of the
induction of chlorophyll fluorescence (Kong et
al. 2016). Chlorophyll fluorescence is regarded as a fast and better
indicator among other physiological indicators in the detection of stress in
plant (Xie et al. 2019; Rasool et al.
2020). The photosynthesis and fluorescence are significantly affected by
N application rates (Stagnari et al.
2015; Wu et al. 2017). The maximum efficiency of PS II
photochemistry under dark adaptation (Fv/Fm) and photochemical quenching (qP)
decreased as N deficiency increased and non-photochemical quenching (qN)
increased. This fluorescence change affects PS II's photochemical activity and
reduces photosynthesis (Yin and Tian et al.
2013; Xue et al. 2014). It had been reported in maize that higher
rate of net photosynthesis rate (Pn), PS II activity, primary
chemical conversion efficiency, and photochemical quantum ultimately increased
the N use efficiency (Wu et al. 2019).
In this study, the
ability of chlorophyll fluorescence to investigate the effects of deficit and N
surplus on PS II in Brassica juncea L. was assessed. The specific aims
of this work were: (i) to measure the effect N concentration on biomass and
plant physiological traits; (ii) to assess the effects of deficient and surplus
N on chlorophyll fluorescence in Brassica
leaves (iii) to analyze the relationship between photosynthetic parameters and
SPAD values and how they affect each other in Brassica when subjected to different N fertilization concentration.
The results can provide a practical basis for optimal N fertilizer application
in Brassica.
Materials and Methods
Growth conditions and materials
The experiment was conducted in a greenhouse located
at Jiangsu University, Zhenjiang, Jiangsu, China (32.20N, 119.45 E) from
October 1 to December 20, 2018, during fall-winter. The average air temperature
and relative humidity in the greenhouse were 20.20°C and 77.89%, respectively. Brassica crop was grown pots filled with
perlite substrate up to 2.5 cm below from the top. The size of the used pots
was 25 cm in height and 19 cm in diameter. The same level of water and
nutrients were applied during the first 20 DAS for their proper establishment
after which experimental treatments were imposed. All the measurements were
taken at 40 DAS (rosette stage), 60 DAS (late vegetative stage)
and 80 DAS (harvesting stage).
Experimental details and measurements
The
treatments consisted of four levels of nitrogen (N): 0% (N0), 50% (N50%),
100% (N100%), 150% (N150%) and 200% (N200%) of
the standard N concentration in Hoagland’s solution which were equivalent to
concentrations of N as 0, 7.5, 15, 22.5, 30 mM, respectively. Where N0 was kept as control (CK). A
completely randomized block design with three replications for each treatment
was designed. At the end of the experimental period, the total leaf area per
plant was measured by a leaf area meter (Handheld Laser Leaf Area Meter,
CI-203, CID Bio-Science, Camas, Washington, U.S.A.). The shoot fresh weight
(SFW) and shoot dry weight (SDW) and dry matter content (DMC%) were determined.
Leaf gas exchange measurements
The
leaf gas exchange parameters of Brassica
leaves during its growth and development leaves were measured at 9:00–11:00
a.m. The measured leaf gas exchange parameters were net photosynthetic rate (Pn,
μmol m−2s−1),
leaf stomatal conductance (gs, molm−2s−1),
intercellular CO2 concentration (Ci,
μmol mol-1) and transpiration rate (Tr, mmol m−2s−1).
During the measurements the basic conditions of photosynthetic active radiation
(PAR), temperature and CO2 concentration were maintained at 800 μmol m-2 s-1,
28°C and 500 μmol mol-1,
respectively. The data were measured using a portable LI-6400XT photosynthesis
measurement system (LI-COR, Lincoln, NE, U.S.A.). The water use efficiency
(WUE, μmol mmol−1)
was calculated from the measured values of Pn and Tr
using the following equation:
%201070-1076_files/image002.png){kind=small}
= %201070-1076_files/image004.png){kind=small}
(1)
Where
Pn is the net photosynthetic rate and Tr is the
transpiration rate.
Leaf chlorophyll content and chlorophyll fluorescence
The
leaf chlorophyll content (Chl) was measured using the 502 SPAD (Minolta,
Japan). Chlorophyll content was determined at 40 DAS (rosette stage),
60 DAS (late vegetative stage) and 80 DAS (harvesting stage).
A
portable fluorimeter (MiniPAM; Walz, Effeltrich, Germany) was used to measure
Leaf chlorophyll fluorescence. The targeted plants were covered with black
plastics and held in dark 30 min before chlorophyll fluorescence traits
measured. The system was made to run according to the manufacturer's
instructions after the dark adaptation of 30 min. Fluorescence data was
collected containing the following parameters as Fm, dark-adapted minimum
fluorescence (Fo), maximum fluorescence (Fm), light adapted maximum
fluorescence (Fmʹ), maximal PS II quantum yield (Fv/Fm), Quantum yield of
non-regulated heat dissipation in PSII Y(NO), the nonphotochemical quenching
(NPQ), and the quantum efficiency of open PSII reaction centres (Fv'/Fm') was
determined. Brassica juncea L. plants were sampled at 40, 60, and 80 DAS in
each pot to measure the fluorescence induction kinetics parameters. In each
procedure, three regions of concern were selected for calculation in a single
leaf. The calculated values were estimated on an average. The measurement of
fluorescence was computer-controlled and the procedures were as follows; at
initial, switched on the measuring light and actinic light then switched on
saturation pulse light after an adaptation of the 20 s and increase kept on
increasing the actinic. The saturation pulse light was kept on switching after
each 20 s adaptation and the same procedure was repeated 12 times under the
photosynthetically active radiation intensity (PAR) as 1, 21, 41, 76, 134, 205,
249, 298, 371, 456, 581 and 726 μmol
m-2 s-1, respectively.
Statistical analysis
All the data obtained were subjected to variance
analysis (ANOVA) to differentiate significant differences (P < 0.05). Using Statistix 8.1 software, these mean data were
statistically analyzed using a randomized complete block design, and mean
results were compared at (P < 0.05)
through the Tukey test. Regression and correlation coefficients were calculated
by standard methods with S.P.S.S. software (v. 13.0, S.P.S.S. Inc.).
Results
Effect of N concentration on growth of Brassica
At the final harvest, (80 DAS), the Brassica plants were evaluated under
different N rates (Fig. 1). N treatments showed a significant effect on the
above-ground biomass of Brassica when
measured at 80 DAS (Fig. 2). Shoot fresh weight (SFW) increased significantly (P < 0.05) with an increased
concentration of N, but there was no significant increase above 22.5 mM concentration (Fig. 2). Shoot dry
weight (SDW) ranged from 93.67 to 188.0 g per pot at 0 (N0%) -30 mM (N200%) N rate. The maximum
SDW was found at 30 mM but there was
no significant difference compared to SDW when measured at N concentration of
22.5 mM. A significant decrease (P < 0.05) was observed when the N
concentration application reduced from 22.5 to 15.0 mM. A similar trend was observed in the leaf area which
significantly lower in plants grown under control (N0%) and low N (N50%)
supply than N100%, N150% and N200%. However, N100%,
N150% and N200% which remained insignificant with each
other. Leaf area ranged from 0.144 to 0.260 m2plant-1 at
0 mM N to 22.5 mM N concentration, respectively (Fig. 2). Based on SDW, at the
harvest stage, 22.5 mM N rate was
optimum for plant growth. At the final harvest, the maximum amount of shoot
fresh and dry weight, dry matter content and leaf area per plant increased
100.70, 86.33 and 80.56% of the control treatment respectively.
Effects on chlorophyll contents (Chl)
%201070-1076_files/image006.png)
Fig.
3: Effect of
different Nitrogen concentrations on SPAD values. *
*Values within the same measured day followed with different letters are significantly different at p < 0.05 according to Tukey’s test.
%201070-1076_files/image008.png)
Fig. 1: Growth of Brassica
under different Nitrogen application at 80 DAS (days after sowing) prior to
harvest
%201070-1076_files/image010.jpg)
Fig. 2: Growth response of Brassica under nitrogen application on
harvesting at 80 DAS. (a) Shoot fresh weight (SFW); (b) Shoot dry weight (SDW);
(c) Leaf area (LA); (d) Dry matter content (DMC)
Comparing
with control (N0), the leaf chlorophyll contents significantly
increased (P < 0.05) in the other
treatments with the increase in N rates (Fig. 3). While comparing the effect of N concentration
on leaf chlorophyll contents, the highest and lowest increase was observed
under N200% (30.9, 23.4 and 51.53) and N50% (9.0, 7.24
and 27.65) at 40, 60 and 80 DAS respectively. Among SPAD values, the
significant difference between N150% and N200% was
observed at 60 DAS as compared to measurements taken on 40 and 80 DAS under the
same treatments. Overall SPAD values increased during the first two stages of
measurements while decreased in all treatments during stage near to harvest.
Leaf gas exchange traits
Leaf
gas exchange parameters comprising Pn, gs and Tr
showed different response under lower to higher N application when compared to control
(N0) at different stages.
No significant difference was found for Pn
at N100%, N150%, and N200% when measured at 40
DAS. Similar trends were observed in stomatal conductance showing no
significant increase with the increase in N concentration above N100%
(15 mM) at the 40 DAS.
While taking the measurements at 60 DAS, the
maximum Pn was found in N200% with an increase of 64.25%
as compared to control treatment and the maximum stomatal conductance was
observed in N150%. The transpiration rate increased with an increase
in N concentration during the first two growth stages, however, it showed a
decline when the N concentration crossed the N100%.
Afterward, higher N concentration showed a
decline in photosynthesis rate when the concentration increased above N100%
(15 mM). The Pn decreased
up to 30.62 and 50.89% at N150% and N200%, respectively
(Table 1) at the harvesting stage. At 80 DAS, the maximum stomatal conductance
was observed in N100%.
Irrespective of treatments, photosynthesis along
with associated leaf gas exchange traits showed decline under all N treatments
at 80 DAS when compared with the measurements taken 60 DAS. This decline in
photosynthetic parameters can be explained due to the leaf senescence. However,
Ci did not follow the same trend as of Pn, gs, and Tr
(Table 1). Thus, the fall in Pn is not completely due to leaf
senescence but also due to stomatal control that underwent the effect of N
concentration. The calculated water use efficiency was highest in N100%
(2.80, 2.39) and N150% (2.54, 2.44) without causing a significant
difference between subsequent measured stages of 60 and 80 DAS, respectively.
Effects of N fertilizer on chlorophyll fluorescence
parameters
The ANOVA showed that Fm and Fv/Fm significantly (P < 0.05) increased with increasing N
application rate until N150%, where it reached to its peak value
followed by a significant decrease in N200% compared to N150%.
Similar response was observed for Fm' and Fv'/Fm' with increase in N
concentration up to 22.5 mM but
further increase in N up to 30 mM decreased only when measured at 80 DAS. While
Y(NO) and NPQ showed the opposite trend compared to Fm and Fv/Fm as NPQ values
decreased with the increase in N application rates. An increment was found in
chlorophyll fluorescence parameters as the N application rate increased for Brassica. Compared to control (N0),
maximal PS II quantum yield (Fv/Fm) increased by 9.81, 9.96,10.10 and 11.12% at
40 DAS as N rates increased from 7.5, 15, 22.5, to 30 mM and by 4.63, 7.19,
20.56% and 2.06%, as N rates increased from 7.5, 15, 22.5, to 30 mM. However, the increasing rate became
redundant at 30 mM (N200%)
N rate at 80 DAS (Table 2).
Responses of ETR under different N concentration
The effect of N concentration increased with the
development in the growth period. The ETR varied with N concentration, and N100%
(15 mM) resulted in a peak curve.
With the increase in PAR initially, the ETR of the Brassica leaves increased initially but after a certain value of
PAR, a decrease in ETR occurred at each stage of measurement. At 40 DAS, the N concentration
had not significant effect on ETR (Fig. 4a). The ETR increased primarily as PAR
increased. N0, the control treatment resulted in the lowest ETR
curve while the largest values were found in N100% (15 mM). Moreover, the reduction in ETR
became apparent when increased beyond 400 μmol
m-2 s-1. The results suggested that ETR was mainly
affected by PAR, while less affected by N concentration at the 40 DAS.
ETR remained highest in N100% when
measured at 60 DAS (Fig. 4b). According to results, N100% showed the
highest values of ETR while there was no significant difference between N0(0),
N150% (22.5 mM) and N200%
(30 mM) which in turn shows
that the ETR decreased with the excessive application of N and with excessive
deficiency in N application. The difference among treatments reached a maximum
at 60 DAS. ETR curves showed decline under all N treatments at 80 DAS (Fig. 4c),
when compared with the measurements taken 60 DAS. The decreasing trend of ETR
was ordered as N100%>N50%>N0>N150%>N200%,
suggesting that adequately low N could accelerate the transportation of the
photosynthetic electron, whereas extremely low or high concentration of N had
no positive effect on ETR.
Regression relationship between gs, Chl
(SPAD) and Pn
The significant linear relationship was obtained
between gs, Chl (SPAD), and Pn (P < 0.001) at 40, 60 and 80 DAS. The coefficients (R2)
between gs and Pn were 0.92 and 0.93 and 0.92 at 40, 60
and 80 DAS, respectively. The R2 of the linear regression between
SPAD and Pn was 0.85, 0.78 and 0.34 at 40, 60 and 80 DAS,
respectively (Fig. 5).
Discussion
Table 1: Effect of different
nutrient concentration on leaf gas exchange parameters
|
DAS |
Treatments |
Pn |
gs |
Ci |
Tr |
WUE |
|
|
|
(μmol
m-2 s-1) |
(mol m-2 s-1) |
(μmol
mol-1) |
(mmol m-2 s-1) |
(μmol
mol-1) |
|
40 |
N0 |
13.22d |
0.407c |
299.2a |
7.39d |
1.77b |
|
N50% |
18.57c |
0.573b |
292.3a |
8.84c |
1.79b |
|
|
N100% |
23.88ab |
0.643a |
277.8b |
10.57b |
2.67a |
|
|
N150% |
25.04a |
0.687a |
271.8b |
12.39a |
2.02b |
|
|
N200% |
25.24a |
0.690a |
256.1c |
12.40a |
2.04b |
|
|
60 |
N0 |
9.15d |
0.160d |
249.5d |
3.63b |
2.52ab |
|
N50% |
16.19c |
0.507c |
294.6a |
9.83a |
1.66c |
|
|
N100% |
23.57b |
0.650b |
259.4c |
8.82a |
2.80a |
|
|
N150% |
24.73ab |
0.760a |
262.8c |
10.10a |
2.54ab |
|
|
N200% |
25.60a |
0.630b |
278.6b |
10.39a |
2.28b |
|
|
80 |
N0 |
6.51d |
0.233c |
308.9a |
5.50c |
1.18b |
|
N50% |
12.00c |
0.370b |
296.2abc |
6.76b |
1.78ab |
|
|
N100% |
21.44a |
0.657a |
287.7bc |
8.98a |
2.39a |
|
|
N150% |
16.87b |
0.423b |
284.3c |
6.19b |
2.44a |
|
|
N200% |
12.53c |
0.387b |
304.5ab |
6.39b |
1.65b |
Values within the same columns followed with
different letters are significantly different at p < 0.05 according to
Tukey’s test. DAS = days after sowing; Pn net photosynthetic rate; gs, leaf
stomatal conductance; Ci, intercellular CO2 concentration and Tr, transpiration
rate.
Table 2: Effect of nutrient
concentration on chlorophyll florescence parameters in Brassica
|
DAS |
Treatment |
Fm |
Fv/Fm |
Y(NO) |
Fm' |
Fv'/Fm' |
NPQ |
|
40 |
N0 |
0.482bc |
0.693c |
0.239b |
0.459c |
0.691c |
0.066a |
|
N50% |
0.489bc |
0.761b |
0.237bc |
0.459c |
0.750b |
0.051ab |
|
|
N100% |
0.498ab |
0.762b |
0.230c |
0.484b |
0.752b |
0.028ab |
|
|
N150% |
0.514a |
0.763ab |
0.307a |
0.508a |
0.756ab |
0.026ab |
|
|
N200% |
0.479c |
0.770a |
0.239b |
0.467bc |
0.765a |
0.011b |
|
|
80 |
N0 |
0.389b |
0.720b |
0.239b |
0.4587a |
.750a |
0.017b |
|
N50% |
0.407b |
0.723b |
0.250b |
0.3827b |
0.747a |
0.045a |
|
|
N100% |
0.417b |
0.750a |
0.277a |
0.3992b |
0.715b |
0.017b |
|
|
N150% |
0.469a |
0.759a |
0.241b |
0.4634a |
0.757a |
0.017b |
|
|
N200% |
0.397b |
0.720b |
0.284a |
0.3907b |
0.713b |
0.012b |
Values within the same columns followed with
different letters are significantly different at p < 0.05 according to Tukey’s
test. DAS, days after sowing; Fm,
maximum fluorescence; Fv/Fm, maximal PS II quantum yield; Y(NO), Quantum yield
of non-regulated heat dissipation in PS II, Fmʹ, light adapted maximum
fluorescence; Fv'/Fm', the quantum efficiency of open PSII reaction centres and
NPQ, the nonphotochemical quenching.
%201070-1076_files/image012.png)
Fig. 4:
Effect of nutrient
concentration on electron transport rate (ETR) curves. Graph (a) represent ETR
curves at 40 DAS, (b) at 60 DAS, and (c) at 80 DAS
%201070-1076_files/image014.jpg)
Fig. 5: Linear regression relationship between gs, SPAD and Pn. Graphs (a, d) refer measurements at 40 DAS, (b, e) refer measurements taken at 60 DAS and (c, f) to measurements conducted at 80 DAS
Several studies have elucidated the sensitivity of
leaf growth to N availability. Studies on leaf size variation in response to N
supply are based on cell production and expansion which actually are the
contributors to leaf size distribution (Sorin et
al. 2016). However, the contribution of N supply at different
developmental stages of the crop stimulates the leaf growth differently.
Reduction in leaf size is more prominently when the plant is subjected to N
deficiency at the early stages of leaf development when cell division is still
continued (Roggatz et al. 1999).
The application of N above a certain level could not promote the growth of Brassica. Non-significant difference in
leaf area of Brassica with N
application above 15 mM could be
explained with excessive N application contributed to nitrate accumulation in
root zone resulting in non-significant difference in growth traits with
increase in N application often correlated with the decrease in photosynthetic
ability (Ullah et al. 2017).
Similar findings were achieved that a moderate dose of N resulted in maximum
leaf area and dry matter as compared to a high dose of N in sunflower (Zeng et al. 2014).
The N contents in leaves are distributed mainly
in the complex of photosynthetic proteins, thus affecting photosynthesis.
Photosynthesis intensity may reflect plant growth potential and stress
tolerance intensity (Han 2011; Wei et al.
2016). Photosynthesis demonstrates the N supply influenced by the target
leaves in reaction to the leaf dry matter. The N deficiency affected leaf N
content, which then decreased the Pn (Hiratsuka
et al. 2015). The Pn and gs decreased at
lower and higher N nutrition while higher values of Ci can be interpreted due
to higher mesophyll resistance. The present study findings are found to be
consistent with the findings of N effect on sunflower where high-N grown plants
had lower intercellular CO2 concentration (Ci) when compared with
low-N grown plants (Cechin and Fumis 2004).
This reduction in Pn may be possible due to a carboxylation
efficiency depression followed by a decrease in Rubisco leaves concentration
and activity (Nakaji et al. 2001).
The increased Pn with increase in N resulted in increased total
assimilatory area to a certain extent of N application followed by a decreasing
trend of Pn. In order to sustain better growth, the importance of N
as a stimulator component of photosynthetic apparatus, an optimal amount of N
application is required varying according to development growth.
The maximal PS II quantum yield and Fv/Fm
increased up to N150%. Similar findings were evident from the study
conducted on cotton that excessive N decreased that Fv/Fm due to
photoinhibition (Wu et al. 2019).
The complex of photosystem II (PS II) appears to be associated with a
significant inhibition of photosynthesis by high salt accumulation caused due
to high doses of N. High nitrate or nitrite accumulation significantly reduces
PS II activity and inhibits the quantity of PS II electron transport and CO2 assimilation in
maize, suggesting that high application of N causes salt accumulation in the
rootzone (Foyer et al. 1994).
The higher the N concentration above the N100%,
the higher the decrease in ETR showing the blockage in ETR and Pn.
Our results are consistent with the findings on rice studied under N
application where ETR increased initially and then decreased as N application
amount increased (Long et al. 2013),
suggesting that ETR and Pn increase with the increase in N nutrition
up to a specific level while further increment shows adverse effects and cause
photosynthesis inhibition and lower photochemical quantum yield. Hence at too
low or at over N fertilization, the stomatal closure is therefore correlated
with ETR down-regulation, which is offset by increased thermal dissipation
(NPQ). This rise (NPQ) would dissipate some excitation energy at the cost of
photochemical usage, resulting in a reduction of PS II control and a decrease
in electron transport quantities (Zribi et
al. 2009).
Conclusion
The application of N had a major impact on Brassica growth and physiological
features. Prior to harvesting, Pn and gs peaked in N100%,
while both Pn, gs and Fv/Fm decreased as the N rate
increased from 22.7 to 30 mM. These
findings suggested that both low and high levels of N blocked the
transportation of photosynthetic electrons and reduced the photosynthetic rate,
and also reduced the degree of openness of the Brassica PS II reaction. The N increase in Brassica assists to improve the ETR and the degree of the openness
of PS II reaction center, achieving higher photochemical quantum yield. It was
concluded that 15 mM to 22.5 mM N concentration in liquid nutrients
solution is more suitable for practical application. It was thus possible to
verify the potential of fluorescence sensing to detect the differences among N
rates.
Acknowledgements
This research was funded by “National Key R&D
Projects, grant number 2018YFF0213600”, “National
Natural Science Foundation of China, grant number 61233006”, "Natural Science
Foundation of Jiangsu Province of China, grant number BK20180864" and
"Jiangsu Synergy Innovation Center Program of Modern Agricultural
Equipment and Technology, grant number 4091600028". The authors declare no
conflict of interest.
Author Contributions
Ikram Ullah, Mao Hanping, and Qaiser Javed designed
the research; Ikram Ullah and Muhammad Saif Ullah conducted the experiments and
collected data; Ghulam Rasool and Muddassir Ali contributed to data analysis;
Ikram Ullah wrote the original manuscript; Mao Hanping and Ahmad Azeem
contributed to review and editing the manuscript. All authors approved the
final manuscript.
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