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Structural and functional response of photosynthetic apparatus of radish plants to iron deficiency



In this work, we tried to identify some specific chlorophyll a fluorescence (ChlF) parameters, that could enable detection of iron deficiency (Fedef) in radish plants (Raphanus sativus L.), before any visual symptoms appear. Changes in ChlF kinetics, JIP-test parameters, and chlorophyll content revealed that iron deficiency negatively affected PSII activity mainly via disruption of light absorption in light-harvesting complexes and by decreasing the activity of the primary quinone acceptor of PSII (QA). Iron deficiency was clearly reflected in the changes of some JIP-test parameters, such as time to reach maximal fluorescence (FM), Area, normalized total area under the OJIP curve, and number of QA redox turnovers until FM is reached. The visible symptoms of Fedef appeared after 7 d of stress application, while ChlF measurements allowed us to detect iron deficiency during 1-3 d. Our results suggest that analysis of ChlF signals has a high potential for early detection of iron deficiency in radish plants.
DOI: 10.32615/ps.2019.132 PHOTOSYNTHETICA 57 (SI): 20-28, 2019
Special issue in honour of Prof. Reto J. Strasser
Structural and functional response of photosynthetic apparatus of radish
plants to iron deciency
Department of Plant Physiology, Institute of Biology, Warsaw University of Life Sciences WULS-SGGW,
Nowoursynowska 159, 02-776 Warsaw, Poland*
White Hill Company, Ciołkowskiego 161, 15-545 Białystok, Poland**
Department of Biometry, Institute of Agriculture, Faculty of Agriculture and Biology, Warsaw University
of Life Sciences WULS-SGGW, Nowoursynowska 159, 02-776 Warsaw, Poland***
Institute for Ecology of Industrial Areas, Kossutha St. 6, 40-844 Katowice, Poland#
In this work, we tried to identify some specic chlorophyll a uorescence (ChlF) parameters, that could enable detection
of iron deciency (Fedef) in radish plants (Raphanus sativus L.), before any visual symptoms appear. Changes in ChlF
kinetics, JIP-test parameters, and chlorophyll content revealed that iron deciency negatively aected PSII activity mainly
via disruption of light absorption in light-harvesting complexes and by decreasing the activity of the primary quinone
acceptor of PSII (QA). Iron deciency was clearly reected in the changes of some JIP-test parameters, such as time to
reach maximal uorescence (FM), Area, normalized total area under the OJIP curve, and number of QA redox turnovers
until FM is reached. The visible symptoms of Fedef appeared after 7 d of stress application, while ChlF measurements
allowed us to detect iron deciency during 1–3 d. Our results suggest that analysis of ChlF signals has a high potential for
early detection of iron deciency in radish plants.
Additional key words: nutrient deciency; OJIP curves; photosynthetic eciency; plant physiological status; principal component
Received 21 May 2019, accepted 23 September 2019.
+Corresponding author; e-mail:
Abbreviations: AM – total complementary area between the uorescence induction curve; Chl – chlorophyll; CS – cross section;
DFabs – driving forces of PSII; DFtotal – driving force of photosynthesis calculated on cross section basis; DI0/CS0dissipated energy ux
per cross section at t = 0; DI0/RC – dissipated energy ux per reaction center at t = 0; ET0/CSM – electron transport ux per cross section;
ET – electron transport; ETC – electron transport chain; F0uorescence at time 0; F0/FMquantum yield (at t = 0) of energy dissipation;
Fedef – iron deciency; FM – maximal uorescence recorded under saturating illumination at the peak P of OJIP, when all PSII RCs are
closed; Ft – uorescence at time t; FV – maximum variable uorescence; FV/F0 – ratio of photochemical to nonphotochemical quantum
eciencies; FV/FM – maximum quantum yield of primary PSII photochemistry; N – number of QA redox turnovers until FM is reached;
P2G – grouping probability, takes into account all possible ways of energetic communication between neighbouring PSII core antenna;
PIabs performance index on absorbance basis; PItotal performance index, the performance of electron ux to the nal PSI electron
acceptors; QA – primary quinone acceptor of PSII; RC – reaction center; SM/t(FM)measure of the average excitation energy of open RCs
from time 0 to t(FM), that is the time needed to obtain total RC closure; TR0/RC – trapped energy ux per reaction center; t(FM) time to
reach maximal uorescence (FM); VK – relative variable uorescence at K-step (300 µs, K-band); VL – relative variable uorescence at
L-step (150 µs, L-band); Vt – relative variable uorescence at time t; W(E) – model-derived value of relative variable uorescence in 100
ms calculated for unconnected PSII units; φ(Eo) quantum yield of electron transport; φ(Ro) quantum yield of electron transport ux
until PSI electron acceptors; Ψ0 – probability of an electron to reach the electron transport chain outside QA.
Acknowledgements: This work was supported by Warsaw University of Life Sciences WULS-SGGW (505-10-010200-N00231-99) and
European Development Fund Regional as the part of the Intelligent Development 2014-2020 Program. Project entitled ‘Trid Product
Future of the Metalworking Cluster (KKK). White Hill synergy of cooperation in the R & D area’, implemented as part of the National
Centre for Research and Development (NCBR) competition: Sub-measure 1.1.1 Industrial research and development carried out by
enterprises. The presented results of the work were nanced from project ‘Research and Development Center – White Hill Mission
Podlasie Strategy of R & D & I Success’. The project is co-nanced from the European Regional Development Fund (European Union).
More information in Table 1S, supplement.
Under natural environments, plants are exposed to various
environmental stresses simultaneously, e.g., changes in
temperature, light spectrum and intensity, and various com-
binations of macro- and micronutrients deciency (Goltsev
et al. 2012, 2016; Mathur et al. 2016, 2018; Kalaji et al.
2018). Nutrients availability in growth medium is among
the most important factors that aect plant growth and
development. Their deciency estimation/identication is
usually based on the presence of visual alterations, which
appear too late and indicate a substantial damage of the
Iron plays an essential role in plant biochemistry,
mainly in energy transformation needed for syntheses and
other physiological processes, such as photosynthesis,
respiration, nitrogen xation, and uptake mechanisms
(Kabata-Pendias 2011). Moreover, it takes part in DNA
synthesis through the action of the ribonucleotide reductase
(Reichard 1993). It belongs to an active cofactor of many
enzymes that are necessary for plant hormone synthesis,
such as ethylene, lipoxygenase, 1-aminocyclopropane
acid-1-carboxylic oxidase (Siedow 1991), or abscisic acid
(compounds that are active in many plant development
pathways and their adaptive responses to uctuating
environment conditions). Iron (Fe) absorbed by plants is
one of the major sources for human and animal nutrition
(Abadía 1992, Briat et al. 2015). Its deciency is one of
the most common shortages of micronutrients globally,
constituting a problem for agriculture by limiting crop
yields and posing a serious threat to public health
(Finkelstein et al. 2017). Most of Fe-decient soils
occurred in arid climate on calcareous soils (Kabata-
Pendias 2011). The main reason of Fe deciency is its low
accessibility to plants, especially on neutral and alkaline
soils (Zuo and Zhang 2011). Iron deciency (Fedef) results
in characteristic visual symptoms interveinal chlorosis
mainly in young leaves (Chen et al. 2015). Plants could
absorb Fe2+ and Fe3+ species as well as Fe chelate, while
the main process of iron absorption is a reduction of Fe3+
to Fe2+ in roots. Many antagonistic relationships of Fe with
other microelements, such as Mn, Ni, Co, Zn, Si, and Se,
were observed in plants. Moreover, Ca can suppress the Fe
absorption (Kabata-Pendias 2011).
Photosynthesis is a very sensitive process, which can be
disturbed by any stressor, including nutrients deciency
(Kalaji et al. 2017a, 2018). Although, there are many studies
related to the eect of plant mineral status on photosynthetic
apparatus (PSA) functioning and performance (Kalaji et al.
2016, 2018), detailed mechanisms of this eect are still not
well-known. Usually, the rst visible stress symptoms in
plants appear when they already have signicant changes
in the structure and functioning of photosynthetic apparatus
(Kalaji et al. 2014b, 2017a). These changes are often
irreversible, especially those related to electron transport
chain. Therefore, there is a strong need to elaborate a low-
cost and noninvasive method for early nutrient deciency
Chlorophyll (Chl) a uorescence is a quick, reliable tool
for in vivo assessment of bioenergetic status of plants (Baker
2008, Cetner et al. 2017, Kalaji et al. 2017a, Samborska
et al. 2018, 2019; Bąba et al. 2019). The changes in
uorescence signals are related, directly or indirectly, to
various stages of photosynthetic light reactions: photo-
lysis of water, reduction of photosynthetic machinery
components, electron transport, generation of the pH
gradient across thylakoid membranes, and ATP synthesis
(Goltsev et al. 2016, Kalaji et al. 2017a,b). The technique
based on detailed analysis of Chl a uorescence signals is
known as JIP-test (Strasser et al. 2004), which is frequently
used to study the changes in structure and function of
photosynthetic apparatus (Kautsky and Hirsch 1931,
Stirbet and Govindjee 2011, Kalaji et al. 2014a,b; Chen
et al. 2015, Bąba et al. 2016, Goltsev et al. 2016, Kalaji
et al. 2017a). Illumination of dark-adapted leaf tissue leads
to an increase of a prompt Chl uorescence (PF) signal,
which curves are named as chlorophyll uorescence induc-
tion curves. They are based on the theory of energy ux in
thylakoid membranes (Strasser et al. 2000). The name of
the JIP-test originates from the specic points on the curves
of Chl a uorescence signal (Stirbet and Govindjee 2012,
Tsimilli-Michael and Strasser 2013). JIP-test parameters
have been categorized into four groups: data extracted from
the recorded uorescence transient, quantum yields and
probabilities, vitality indices, and energy uxes, which are
divided in phenomenological and specic ones (Strasser
et al. 2000, 2004; Goltsev et al. 2016).
In this work, we executed an experimental procedure
to identify some specic JIP-test parameters obtained by
measuring Chl a uorescence, which enable us to detect
early Fedef in radish plants at early growth stages, before
appearance of any visual symptoms. For better under-
standing, we conducted additional chlorophyll content
measurements on plants under Fedef.
Materials and methods
Plant material: Radish is a common root vegetable plant
from Brassicaceae family, closely related to the model
plant Arabidopsis thaliana (L.) Heynh., characterized by
short life cycle (6 weeks) and low cultivation demands and
its genome is already sequenced (Kitashiba et al. 2014).
Two hybrid cultivars of radish plants (Raphanus sativus L.)
were used: ‘Fluo HF1’ and ‘Suntella F1’. However, since
responses of both cultivars to the applied stressor (Fedef)
were similar (no signicant statistical dierences were
found between the two cultivars), in the subsequent
analyses, we used the calculated average values obtained
from both of them.
Growing conditions: Plants were grown under controlled
conditions in a growth chamber in hydroponic system lled
with modied Hoagland solution (Hoagland and Arnon
1950), which allowed precise controlling of the mineral
composition and concentrations. Radish plants were grown
either on full solution (control, Cs) or on iron-decient
solution (Fedef). Both solutions were developed and
modied according to procedure described by Hoagland
and Arnon (1950). Fedef was generated by deprivation of
iron ions, while leaving the other components as in control
solution concentration. Their detailed composition is
presented in the text table.
Polyethylene pellets (PE), made from a synthetic resin,
were used as root growth medium. Comparing to other
growth substrates, it is characterized by a very low ion
absorption capacity (innovative method by Cetner et al.
2017, Samborska et al. 2018, 2019). Radish seeds were
germinated for 7 d and after that sprouts were moved into
plastic multi-pot trays (48 seedlings per tray: 24 of ‘Fluo
HF1’ and 24 of ‘Suntella F1’ cultivars) lled with PE. The
trays were set on the top of six plastic containers lled
with 20 L of aerated modied Hoagland solution (control
The experiment consisted of three phases. During the
rst phase, which lasted 16 d (measuring Chl uorescence
at term: t0), all plants grown on control solution. During
the next phase that lasted 13 d, Fedef was applied to plants
of three containers (half of the experimental set), while the
other three containers were kept on a full (control) solution
(measuring Chl uorescence at terms: t1–t5). During the
last 11 d of the experiment (recovery phase), the control
solution was applied again to all the plants (measuring Chl
uorescence at terms: t6–t7) (Fig. 1).
Altogether, plants were grown for 43 d. During this
time, in particular treatments, all solutions were changed
every week to avoid nutrient depletion (Fig. 1). The pH
of the nutrient solutions in both treatment was maintained
between 5–6. The photoperiod was 14-h and day/night air
temperature was 18/13°C, respectively. PAR was about
250 µmol(photon) m−2 s−1. Average (24 h) relative air
humidity was about 50%.
Visual symptoms: All the plants were visually checked
three times a day and presence of any visible symptoms of
the Fe deciency, on leaves, stalks or roots were spotted.
Chl content was measured in vivo by a portable meter
Dualex (Force-A Inc., France). Measurements were
conducted three times during germination (at 0, 4, 11 d),
two times during stress phase (4 and 11 d), and two times
during the recovery phase (at 17 and 24 d). Measurements
were performed with eight technical replicates, on the same
leaves chosen for Chl a uorescence measurements for
both Cs and Fe-decient plants.
Chlorophyll uorescence (ChlF) measurements were
done in vivo at the middle part of leaf blade, every time on
the same leaves. Twenty plants were chosen randomly from
one container before introducing the stress phase. Leaves
were dark-adapted for 20–30 min, using leaf clips attached
in the middle part of the leaf. The measurements were
repeated by keeping 2–5-d intervals. The rst measurement
was done before stress phase (t0), then repeated ve times
during stress phase (t1, t2, t3, t4, t5), and two times during
recovery phase (t6, t7). The experimental timetable is
described in Fig. 1. Prompt uorescence measurements
were recorded after sample illumination with red actinic
light intensity of ca. 2,500 µmol(photon) m–2 s–1 using
Handy PEA uorometer (Hansatech Instruments, Ltd.,
UK). From the measured primary parameters (F0, Fm, VK,
VL, tFM), the secondary ones, i.e. specic energy uxes
per one PSII reaction center (RC), quantum yields and
eciencies, phenomenological energy ux per excited
cross section (CS), and performance indexes (PItotal and
Component Molar mass
[g mol–1]
Molar concentration
of a stock solution [M]
Amount of stock solution to prepare
1 L of nutrient solution [ml]
Control solution
1 1 M KNO3101.10 1.0 3.5
21 M Ca(NO3)2•4H2O236.15 1.0 4.0
3 1 M NaH2PO4119.98 1.0 2.0
4 1 M MgSO4•7H2O246.47 1.0 2.0
5 1 M KCl 74.55 1.0 1.0
6 1 M K2SO4174.26 0.5 2.0
7 iron chelate - - 2.0
8micronutrient - - 1.0
Iron-decient solution
1 1 M KNO3101.10 1.0 3.5
21 M Ca(NO3)2•4H2O236.15 1.0 4.0
3 1 M NaH2PO4119.98 0.5 1.5
4 1 M MgSO4•7H2O246.47 1.0 2.0
5 1 M KCl 74.55 1.0 1.0
6 1 M K2SO4174.26 0.5 1.5
Fig. 1. The experiment schedule with germination, stress, and
recovery phases showing the duration and treatments applied
(Cs – control, Fedef – iron deciency) during each phase. During
germination phase and recovery phase, radish plants were grown
in full solutions. The stress phase started by introducing solutions
without iron on 17 d of vegetation (t1).
PIabs), were calculated by JIP-test described in Table 2S,
supplement (Tsimilli-Michael and Strasser 2007, Strasser
et al. 2004).
Statistical analysis: To estimate the signicance of dier-
ences between average values of particular ChlF parameters
in the control (t0) vs. Fedef plants (t1–t5) and recovery (t6–t7),
Student's t-test was applied. The signicance of dierences
in average values of Chl content was tested with one-
way ANOVA. The null hypothesis on lack of dierences
between means was rejected at p<0.01. In order to gain
insight into the changes in ChlF parameters in Cs and Fedef
radish plant, PCA analysis was performed by IBM SPSS
Statistics ver. 23 for Windows.
Visual symptoms: The rst visual symptoms were observed
on younger leaves, because iron is weakly reutilized
micronutrient. The rst visual symptoms were observed
after 23 d of plant vegetation and 7 d after stress treatment
introduction (t3). Plants grown under Fedef conditions were
smaller than control plants and young leaves were less
green (more yellow). Leaf veins became brighter and later
almost white (Fig. 2).
Chl content: The data for relative Chl content are shown
in Fig. 3. During whole experimental cycle (from the 3rd d
of stress application), signicantly lower values of Chl
content were observed in Fe-decient plants in comparison
with control plants. However, during the recovery period,
these values were similar in both control and Fedef plants
(Fig. 3).
Prompt uorescence induction curves: The dierential
ChlF induction curves were calculated to evaluate the
inuence of Fedef on PSA. Each dierential curve value
was calculated as a dierence between the values of the
relative variable uorescence [Vt = (F
t F
0)/(FM F
recorded in the Fe-decient plants minus the respective
values for the control plants at a given time period t0–t7,
[i.e., for t0 period: ΔVt(t0) = Vt(t0)(–Fe) Vt(t0)(Cs)]
(Samborska et al. 2019).
The Fe decit-induced alterations were clearly visual-
ized by dierential curves. The dierential curves showed
peaks at: L (0.2 ms), K (0.3 ms), J (around 2 ms), I (around
5 ms) points, and H (10–20 ms), and more pronounced
peak G (around 100 ms). This conrmed the strong and
complex impact of Fedef on almost all light energy transfer
and conversion during the light-dependent phase of photo-
synthesis (Fig. 4).
Principal component analysis: The selected JIP-test para-
meters are shown in two PCA gures (Figs. 5, 6), where
Fig. 2. The radish plant growing under control conditions (left)
and iron deciency (right) at the end of the stress phase (t5).
The visual symptoms were observed on younger leaves.
Fig. 3. Dynamics of chlorophyll content in leaves in Raphanus
sativus L. for both cultivars (averaged values for ‘Fluo HF1’ and
‘Suntella F1’) under control condition (Cs) and iron-deciency
(Fedef) stress. The stress and recovery phase (arrow) is shown.
The asterisks are related to statistical signicance level of
dierences between Cs and Fedef plants according to analysis of
variance (ANOVA): ns not signicant (p≥0.05), ** 0.001<p<
0.01; ***p< 0.001. The values are means ± SE.
Fig. 4. Eect of iron deciency on the shape of ChlF transients
normalized between the induction phases ‘O’ (20 µs) and ‘P’
(300 ms) measured on radish plants during the stress phase
(t1–t5) and after transferring the plants back to a full nutrient
medium (recovery phase, t6– t7). Each point is an averaged value
recorded from 60–118 samples. The dierential Chl uorescence
induction curves were calculated to evaluate the inuence of
Fedef on photosynthetic apparatus. Each dierential curve value
was calculated as a dierence between the values of the relative
variable uorescence [Vt = (Ft – F0)/(FM – F0)] recorded in the
Fe-decient plants minus the respective values for the control
plants at a given time period t0–t7.
PC1 is on the bottom, on the x axis. The position of points,
related to a particular ChlF parameter on the PCA biplot
in Fig. 5A and B is determined by the PC1–PC3 values,
calculated on the basis of all values of that parameter. On
the other hand, the point, related to a given measurement is
outcome of all values of ChlF parameter, recorded at that
time (Fig. 5).
The PC1, which explains nearly a half of all variability
in PCA, reected the temporal changes in ChlF parameters
during the experiment, while the PC2, which explained
21.8% of variability is related to the dierences between
control and Fedef plants. Fedef conditions imposed on plants
during the t1–t5 period resulted in a strong increase the value
of some ChlF parameters, such as antenna organization and
electron transport rate, number of active RCs, and energy
dissipation DI0/RC and DI0/CS0. However, the maximal
dierences between control and Fe-decient plants were
observed at the end of stress phase (t4–t5) (Fig. 5).
During the whole study period, the control plants were
characterized by higher density of RC per sample area, and
higher values of Area, SM, PSII eciency (FV/FM), PIabs,
PItotal, and other ChlF parameters, indicating the higher
eciency of PSII in comparison to Fe-decient plants.
During the experimental period, values of ChlF para-
meters were not constant and depended on plant age as
indicated by uctuations of ChlF parameters even in the
control plants. Their reactions were dierentiated during
the period of growth and development, especially, when
senescence started.
In order to nd the parameters most sensitive to Fe-
deciency stress, we compared the number of statistically
signicant (p<0.01) ChlF parameters between control and
Fe-decient plants during the stress t1–t5 and recovery
t6–t7 periods. Shortly after stress application (t1), the Cs
and Fedef plants diered in 17 ChlF parameters, and this
value increased up to 22 in t2 and to 23 in t3–t5 period.
During the recovery phase, the strong decrease of 20 ChlF
parameters at the t6 and only nine at the t7 period was
observed. Among ChlF parameters studied we found that
F0, FV
, F0/FM, FV/FM, FV/F0, DI0/CS0, DI0/RC, DI0/CS0,
ET0/CSM, PIabs, PItotal, DFabs, DFtotal were sensitive to Fe-
deciency stress and changes of their values followed the
control–stress–recovery treatments.
The data from JIP-test obtained only for Fedef plants
were also compared with control plants (t0). Results
are presented on radar plot (Fig. 6). Studied parameters
showed various changes during the whole vegetative
period. The most signicant changes in JIP-test parameters
were observed at the end of stress phase (t5) and at the
end of experimental cycle, during recovery phase (t6, t7).
DFtotal and PItotal parameters decreased signicantly under
Fedef. The highest increases were observed in the case
of DI0/RC, VL, and W(E) parameters, reecting antenna
organizational changes, and DFtotal parameter, which were
strongly correlated with PC2 (Figs. 5, 6).
In this work, we used a combination of the Chl content
measurements, elaborated prompt uorescence dierential
curves, and application of multivariate analyses (PCA)
in order to nd parameters that can be used for early
detection of changes related to iron-deciency stress
in photosynthetic apparatus of radish plants before any
visual stress symptoms appear. Our results showed that
the 14-d period of Fe-deciency stress had a strong and
signicant impact on growth and development of radish
plants. Although iron is not a component of Chl molecule
itself, it is essential for Chl synthesis and stabilization
of chloroplast structure and function and approximately
80% of Fe is deposited in photosynthetic cells (Kruk
and Szymańska 2012, Connorton et al. 2017). The iron
and Chl contents in plant leaves are thus often correlated
(Rout and Sahoo 2015). We conrmed a signicantly
lower total Chl content in leaves of Fedef plants during the
Fig. 5. Dynamics in biplots for parameters (PC1 and PC2) of
chlorophyll uorescence for control (circles) and iron-decient
(squares) radish plants during stress phase and recovery
phase (A). Red cross symbol (+) describes chlorophyll uores-
cence parameters, which are correlated with principal components
(PC1 and PC3). Signicant dierences between control and iron
deciency appeared after 5 d of iron-deciency stress (t2) (B).
whole stress phase and its increase during the recovery
phase. The rst visual symptoms were observed 7 d after
stress introduction. However, the signicant decrease of
Chl content in Fe-decient plants was detected already 3 d
after stress application, conrming that Chl content could
be a sensitive indicator of Fedef in radish plants.
Iron is a part of Fe-S proteins, distributed across
thylakoid membrane: cytochrome b6f complex (Rieske
protein), ferredoxins, and PSI, which are involved in electron
transport chain in light-dependent phase of photosynthesis
Fig. 6. The dynamics of JIP-test parameters (selected
by coecient of variation) between iron-decient
and control (Cs) plants in time (t1–t7) presented in
radar plot. Signicant dierences, based on Student's
t-tests, between t0 and the end of stress phase (t4–t5)
are marked by * (p<0.01) and signicant dierences
between t0 and the recovery phase (t6–t7) are marked
by ** (p<0.01).
Table 1. Temporal changes in selected ChlF parameters during the control conditions (full Hoagland solution), Fe-deciency stress (full
Hoagland solution without Fe), and recovery period (full Hoagland solution) in radish plants. ●, ↑, ↓ – no dierence, signicantly higher,
and signicantly lower average value (p<0.01) of ChF parameters in Fe-decient radish plant as compared with control, respectively.
ChlF parameters Control Fe-deciency stress Recovery
F0 ↑ ↑ ↑ ↑ ↑ ●
t(FM) ↓ ↓ ↓ ↓ ↓ ↓ ↓
AM ↓ ↓ ↓ ↓ ↓ ↓ ↓
FV ↓ ↓ ↓ ↓ ●
F0/FM ↑ ↑ ↑ ↑ ↑ ●
FV/FM ↓ ↓ ↓ ↓ ↓ ●
FV/F0 ↓ ↓ ↓ ↓ ●
VL ↑ ↑ ↑ ↑ ↑ ↑ ●
SM ↓ ↓ ↓ ↓ ↓ ↓ ↓
N ↓ ↓ ↓ ↓ ↓ ↓ ↓
φ(Eo) ↓ ↓ ↓ ↓ ↓ ↓ ●
φ(Ro) ↓ ↓ ↓ ↓ ↓ ↓ ↓
TR0/RC ↑ ↑ ↑ ↑ ↑ ↑ ↑
ET0/RC ● ↓ ● ● ● ● ↑
DI0/RC ↑ ↑ ↑ ↑ ↑ ↑ ●
DI0/CS0 ↑ ↑ ↑ ↑ ●
ET0/CSM ↓ ↓ ↓ ↓ ↓ ●
RC/CSM ↓ ↓ ↓ ↓ ↓ ↓ ↓
PIabs ↓ ↓ ↓ ↓ ↓ ↓ ●
PItotal ↓ ↓ ↓ ↓ ↓ ↓ ●
DFabs ↓ ↓ ↓ ↓ ↓ ●
DFtotal ↓ ↓ ↓ ↓ ↓ ↓ ●
W(E) ↑ ↑ ↑ ↑ ↑ ↑ ↑
SM/t(FM) ↑ ↑ ↑ ● ↓ ●
P2G ● ● ● ↓ ● ↓
(Briat et al. 2015). The cytochrome b6f complex catalyses
the transfer of electrons between plastoquinol and plasto-
cyanin, while the ferredoxin takes part in electron transport
beyond the PSI and transfers electrons to NADP+ reductase
(Blankenship 2014). Moreover, iron takes part in oxygen
transport or regulation of protein stability (Connorton
et al. 2017). Therefore, the shape of ChlF curves as well
as some JIP-test ChlF parameters were aected by iron
deciency reecting its strong and complex negative
impact on the structure of photosynthetic apparatus.
This could be explained by increasing Chl a/b ratio and
decrease in antenna size, changes in their organization, and
light-harvesting eciency (M'sehli et al. 2014).
The eect of decreasing Fe content in plant tissue
was detectable when we compared the shape of prompt
uorescence dierential curves of control and Fe-decient
radish plants. The positive appearance of L-band showed
the eects of iron deciency on PSII connectivity. This
can indicate the possible physiological role of this nutrient
in connectivity changes in photoprotection as shown in
shade-acclimated plants (Živčák et al. 2014). Moreover,
the appearance of K-band indicated ungrouping reaction
centers and inactivation of the oxygen-evolving complex
(OEC), particularly, Mn-complex in PSII donor side (Yusuf
et al. 2010, Stirbet et al. 2014). On other hand, the
appearance of the positive band around J-step after Fe
removal reected the withdrawal of electrons from QA,
more closed reaction centers at that time, i.e., reduced
electron ux rate from QB to plastoquinone. The drops in
J-step during recovery phase indicated that it was probably
no longer blocked by stress and accelerations of electron
transport reactions in the recovering plants. The J–I phase
reects the dynamics of the reduction of the plastoquinone
pool between the PSII and PSI, weaker and slower
reduction between QA to QB. It consists of two phases: the
fast (around 5 ms I-band) and slow (around 10–20 ms,
H-band), reecting the existence of two molecules with
dierent rate of reduction – fast and slow reducing by
PSII. The comparison between the two groups of plants
conrmed that variations in the dierential curves appear
as a result of changes in relative volumes of the PQ pool
(the number of electrons required to fully reduce the PQ
pool to I-step). At a decreased PQ pool capacity, the rate
of reduction was higher and this resulted in positive values
of the transient band (as we observed in Fe-decient
plants). Conversely, during the late recovery phase (t6–t7),
the relative size of a PQ pool increased in the fast phase
(J-step), which resulted in slightly negative values for that
band. In the last I–P phase, Fedef was detected by much
more pronounced positive peaks (G), which reected the
reduced size pool and faster reduction PSI end acceptors
(i.e., NADPH+). During the recovery phase, while J and
I peak disappeared, the peaks around K, H, and G were
still visible on the dierential curve after the addition of
Fe, which indicated, among others, the slower recovery
of PSI-end acceptors pool size. The detailed analyses
of the shape of Chl a uorescence combined with PCA
analysis are very sensitive tools for early detection of
environmental stress (Allakhverdiev 2011, Kalaji et al.
2016, 2018; Cetner et al. 2017, Samborska et al. 2018,
2019). The PCA analysis and inspection of the Table 1
of temporal changes in ChlF parameters during control–
stress–recovery sequence provided additional insight into
the reaction of photosynthetic apparatus to iron deciency
in radish. Fe deciency strongly decreased both PSII and
PSI activity and electron transport rate (Terry and Abadía
1986, Molassiotis et al. 2006), which is indicated by a
decrease of some JIP-test parameters, such as maximum
eciency of PSII (FV/FM) and ratio of photochemical to
nonphotochemical quantum eciencies (FV/F0).
During the initial period (t0), we did not found any
signicant dierences in measured ChF parameters
between radish plants, which grew with the control solution
(Table 1). However, just at t1, a strong decrease of values
related to eciency of photosynthetic apparatus para-
meters, such as t(FM), Area, SM, N, φ(Eo), φ(Ro), RC/CSM,
PIabs, PItotal, DFabs, DFtotal, and an increase of some
parameters, such as F0, WE, VL, TR0/RC, DI0/RC, SM/tFM,
were observed. In the t2, additionally, an increase of F0/
FM and a decrease of maximum quantum yield of primary
photochemistry reactions in PSII RC were denoted. Among
the parameters, which we found to be the most correlated
to changes along control–stress–recovery sequence, were:
F0, FV
, F0/FM, FV/FM, FV/F0, DI0/CS0, DI0/RC, DI0/CS0,
ET0/CSM, φ(Eo), PIabs, PItotal, DFabs, DFtotal, SM/tFM. By taking
into account their high sensibility, in combination, they
could be used in as reliable indicator of Fe deciency in
radish plant.
We found a few JIP-test parameters, such as AM, FM,
RC/CSM, which were at the end of recovery phase still
signicantly lower in Fe-decient plants compared to
control and probably more time was needed for their full
recovery (Table 1).
Conclusion: Iron deciency aected photosynthetic
machinery functioning and performance in radish plants.
However, this eect could be reversed after elimination of
the studied stress factor. We found some JIP-test parameters
connected with the appearance of visible symptoms,
which can be used as an early sensitive indicator for iron-
deciency stress detection (Kalaji et al. 2017b).
The earliest observed changes were denoted in JIP-test
parameters (26 parameters related to photochemical
reaction). PSII activity was interrupted at the level of
photon absorption in light-harvesting complexes and QA
reduction at PSII acceptor side. Parameters, such as tFM,
Area, SM, N, and VL, were the most indicative ones to
iron deciency in radish plants. However, we conrmed
that it should not be diagnosed only on the basis of these
chosen parameters. Taking into account the complex role
of iron in plant biological and biochemical processes, iron
deciency imposed a strong stress, but did not provoke
any irreversible changes to photosynthetic apparatus in
radish plants.
Our results showed that the visible symptoms of iron
deciency in radish plants appeared after 7 d of stress
application. On the other side, chlorophyll a uorescence
allowed us to detect the stress earlier (1–3 d). Both
observation (visual and that based on ChlF) were noticeable
only in direct comparison with the control plants grown in
optimal growth medium.
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We conrmed that the measurement of chlorophyll a
uorescence can be used for early detection of iron
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© The authors. This is an open access article distributed under the terms of the Creative Commons BY-NC-ND Licence.
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In this review, using the network analysis, based on the bibliometric data, collected from Web of Science Core Collection database, we followed the development of chlorophyll fluorescence research (CFR) during 1947-2018. We confirmed dramatic increase in diversity of CFR from late 90-ties and vigorous development of this discipline in the last ten years. They are parallel to an increase in number of research areas and institutions involved and were triggered by the accumulation of knowledge and methodological, technological, and communication advances, especially modern fluorimeters and fluorescence techniques. The network analysis of keywords and research areas confirmed CFR changed into modern, multidisciplinary, highly collaborative discipline, in which in spite of many 'core' disciplines as plant science, environmental sciences, agronomy/food science and technology, the promising, modern areas developed: biochemistry and molecular biology, remote sensing, and big data artificial intelligence method. Additional key words: collaboration; globalization; plant physiological status; trends in chlorophyll fluorescence research.
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Nutrients deficiency (ND) in plants is one of the main factors adversely affecting plant growth and yield of agricultural and horticultural production. Usually detection of NDs in plants is based on visible symptoms or destructive chemical analysis. Recently chlorophyll a fluorescence is one of the most used approaches to investigate photosynthesis light-dependent reactions. It is widely accepted that it can inform about structural and functional changes in photosynthetic apparatus, especially under abiotic stresses including NDs. The aim of this research was to study the influence of sulphur deficiency on photosynthetic efficiency of two cultivars radish (Raphanus sativus L. sativus) – ‘Fluo HF1’ and ‘Suntella F1’ and to assess the potential of chlorophyll a fluorescence measurements in early detection of this stress. Our results showed the sulphur deficiency has decreased the electron transport rate, chlorophyll content, grana size, and, at some degree, net photosynthesis and stomatal conductance. The changes in photosynthetic machinery performance were observed earlier than the visible effects of sulphur deficiency. However, the photosynthetic apparatus of radish plants was not considerably affected by this stress. Some sensitive parameters of OJIP test were altered but we were not able to identify the sulphur deficiency stress based on the alteration of only one of these parameters. We conclude that the detection of specific stress reactions of plants to sulphur deficiency should be based on integrative analysis of the response of the photosynthetic machinery. Such stress induced reactions can be detected by Principal Component Analysis of a large number of JIP-test parameters.
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In natural conditions, plants growth and development depends on environmental conditions, including the availability of micro- and macroelements in the soil. Nutrient status should thus be examined not by establishing the effects of single nutrient deficiencies on the physiological state of the plant but by combinations of them. Differences in the nutrient content significantly affect the photochemical process of photosynthesis therefore playing a crucial role in plants growth and development. In this work, an attempt was made to find a connection between element content in (i) different soils, (ii) plant leaves, grown on these soils and (iii) changes in selected chlorophyll a fluorescence parameters, in order to find a method for early detection of plant stress resulting from the combination of nutrient status in natural conditions. To achieve this goal, a mathematical procedure was used which combines principal component analysis (a tool for the reduction of data complexity), hierarchical k-means (a classification method) and a machine-learning method—super-organising maps. Differences in the mineral content of soil and plant leaves resulted in functional changes in the photosynthetic machinery that can be measured by chlorophyll a fluorescent signals. Five groups of patterns in the chlorophyll fluorescent parameters were established: the ‘no deficiency’, Fe-specific deficiency, slight, moderate and strong deficiency. Unfavourable development in groups with nutrient deficiency of any kind was reflected by a strong increase in Fo and ΔV/Δt0 and decline in φPo, φEoδRo and φRo. The strong deficiency group showed the suboptimal development of the photosynthetic machinery, which affects both PSII and PSI. The nutrient-deficient groups also differed in antenna complex organisation. Thus, our work suggests that the chlorophyll fluorescent method combined with machine-learning methods can be highly informative and in some cases, it can replace much more expensive and time-consuming procedures such as chemometric analyses. Electronic supplementary material The online version of this article (10.1007/s11120-017-0467-7) contains supplementary material, which is available to authorized users.
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Iron plays a crucial role in biochemistry and is an essential micronutrient for plants and humans alike. Although plentiful in the Earth’s crust it is not usually found in a form readily accessible for plants to use. They must therefore sense and interact with their environment, and have evolved two different molecular strategies to take up iron in the root. Once inside, iron is complexed with chelators and distributed to sink tissues where it is used predominantly in the production of enzyme cofactors or components of electron transport chains. The processes of iron uptake, distribution and metabolism are overseen by tight regulatory mechanisms, at the transcriptional and post-transcriptional level, to avoid iron concentrations building to toxic excess. Iron is also loaded into seeds, where it is stored in vacuoles or in ferritin. This is important for human nutrition as seeds form the edible parts of many crop species. As such, increasing iron in seeds and other tissues is a major goal for biofortification efforts by both traditional breeding and biotechnological approaches.
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Iron deficiency is the most common micronutrient deficiency globally and represents a major threat to public health. Biofortification, the process of enhancing micronutrient content and bioavailability in staple crops, represents an exciting sustainable food-based strategy to combat and prevent iron deficiency, particularly in resource-limited settings. In this review, we examine the evidence to date of the efficacy of iron-biofortified staple food crops on improving iron status in at-risk populations, including rice, pearl millet, and beans. Three randomized efficacy trials of iron biofortified interventions were included in this analysis, conducted in the Philippines, India, and Rwanda. Iron status (hemoglobin, serum ferritin, soluble transferrin receptor (sTfR), C-reactive protein, alpha-1 acid glycoprotein) was measured at enrollment, midline, and endline in each trial. The primary outcomes evaluated included hemoglobin, serum ferritin, sTfR, and total body iron. A meta-analysis using random effects models was conducted to examine the effects of interventions on hematological outcomes, with the DerSimonian and Laird method. In meta-analyses of data from the three trials, iron-biofortified interventions significantly increased serum ferritin concentrations and total body iron. Evidence to date from randomized trials suggest that iron-biofortified crops are an efficacious intervention to improve iron status. In particular, findings from all three trials also indicate that the effects of biofortified staple crops were highest among individuals who were iron deficient at baseline, suggesting the greatest potential to benefit. Assessment of functional outcomes and consideration of other high-risk populations such as young children, are warranted to elucidate the impact of iron-biofortified interventions on human health.
Still the Gold Standard Resource on Trace Elements and Metals in Soils This highly anticipated fourth edition of the bestselling Trace Elements in Soils and Plants reflects the explosion of research during the past decade regarding the presence and actions of trace elements in the soil-plant environment. The book provides information on the biogeochemistry of these elements and explores how they affect food quality. Incorporating data from over 1500 new resources, this edition includes the most up-to-date information on the relationship of trace elements to topics such as: •Soil natural/background contents •Sorption/desorption processes •Anthropogenic impact and soil phytoremediation •Phytoavailability and functions in plants •Contents of food plants The book discusses the assessment of the natural/background content of trace elements in soil, bioindication of the chemical status of environmental compartments, soil remediation, and hyperaccumulation and phytoextraction of trace metals from the soil. The table of contents reflects the IUPAC’s recommendation for numbering element groups, giving the new edition an updated organizational flow. Trace Elements in Soils and Plants, Fourth Edition illustrates why trace elements’ behavior in soil controls their transfer in the food chain, making this book an invaluable reference for agronomists, soil and plant scientists, nutritionists, and geochemists.
Magnesium (Mg) is one of the significant macronutrients which is involved in the structural stabilisation of plant tissues and many enzymes such as PSII. The latter efficiency and performance were analysed, using chlorophyll (Chl) a fluorescence induction kinetics and microscopic images, to detect the changes in structure and function of photosynthetic apparatus of radish plants grown under Mg deficiency (Mg def). Plants grown under Mg def showed less PSII connectivity and fewer active primary electron acceptors (Q A) oxidizing reaction centres than control plants. Confocal and electron microscopy analyses showed an increased amount of starch in chloroplasts, and 3,3-diaminobenzidine (DAB)-uptake method revealed higher H 2 O 2 accumulation under Mg def. Prominent changes in the Chl a fluorescence parameters such as dissipated energy flux per reaction centre (DIo/RC), relative variable fluorescence at 150 μs (Vl), and the sum of the partial driving forces for the events involved in OJIP fluorescence rise (DFabs) were observed under Mg deficiency. The latter also significantly affected some other parameters such as dissipated energy fluxes per cross-section (DIo/CSo), performance index for energy conservation from photons absorbed by PSII antenna until the reduction of PSI acceptors (PItotal), and relative variable fluorescence at 300 μs (Vk). This work emphasises the use of chlorophyll fluorescence in combination with microscopic and statistical analyses to diagnose the effects of nutrients deficiency stress on plants at an early stage of its development as demonstrated for the example of Mg def. Due to the short growth period and simple cultivation conditions of radish plant we recommend it as a new standard (model) plant to study nutrients deficiency and changes in plant photosynthetic efficiency under stress conditions.
In this study, pot experiments were performed to investigate the effects of high temperature stress (44 °C) in maize plants colonized with and without arbuscular mycorrhizal fungi (AMF). Various parameters characterizing photosynthetic activity were measured in order to estimate the photosynthetic efficiency in maize plants. It was observed that density of active reaction centers of PSII, quantum efficiency of photosystem II (PSII), linear electron transport, excitation energy trapping, performance index, net photosynthesis rate increased in AMF (+) plants at 44 °C ± 0.2 °C. Efficiency of primary photochemical reaction (represented as Fv/Fo) increased in AMF (+) plants as compared to AMF (-) plants. AMF seems to have protected water splitting complex followed by enhanced primary photochemistry of PSII under high temperature. Basic morphological parameters like leaf width, plant height and cob number increased in AMF (+) plants as compared to AMF (-) plants. AMF (+) plants grew faster than AMF (-) plants due to larger root systems. Chl content increased in AMF (+) plants as compared to AMF (-) maize plants. AMF hyphae likely increased Mg uptake which in turn increased the total chlorophyll content in AMF (+) maize plants. This subsequently led to a higher production in photosynthate and biomass. Thus AMF (+) plants have shown better photosynthesis performance as compared to AMF (-) maize plants under high temperature stress.
Nitrogen starvation has been stated to reduce chlorophyll a and accessory pigments, decrease photosynthetic efficiency, as well as modify chloroplast thylakoid membranes. However, the impact of N-deficiency on light-dependent reactions of photosynthesis has not been well understood. In this study, efficiency and structure of light-harvesting complex under N-deficiency conditions were investigated in two radish cultivars (Raphanus sativus var. sativus 'Fluo HF1' and 'Suntella F1'). Light-dependent reactions of photosynthesis were investigated by measuring in vivo chlorophyll a prompt fluorescence signal. Acquired data were utilised in two ways: by plotting fast induction curves and calculating OJIP-test biophysical parameters. Detailed analysis of difference curves as well as OJIP-test results showed that major disturbances were associated with photosystem II and its subunits, including decoupling of light-harvesting complexes, dysfunction of oxygen-evolving complex, and reaction centres inactivation. The maximum quantum yield of photosystem II primary photochemistry was severely restricted, causing an inhibition in electron transport through successive protein complexes in the thylakoid membrane. Structural changes were demonstrated by recording images using Transmission Electron Microscopy (TEM). TEM investigations showed intensive starch accumulation under N-deficiency. Rare thylakoid stacks distributed in tiny layers of stroma around grains and chloroplast periphery were observed in cells of N-deficient plants. The application of principal component analysis (PCA) on OJIP-test results allowed characterizing the dynamics of stress response and separating parameters according to their influence on plants stress response. 'Suntella F1' genotype was found to be more sensitive to nitrogen deficiency as compared to 'Fluo HF1' genotype.