EFFECT OF VERTICALLY HETEROGENEOUS SOIL SALINITY ON MORPHOLOGICAL
CHARACTERISTICS, BIOMASS ACCUMULATION, ROOT DISTRIBUTION, AND TRANSPIRATION OF
SUNFLOWER (HELIANTHUS ANNUUS L.)
G. Lei1☆, Q. Zhao2☆, W. Zeng 1, 3,*,
J. Wu1, A. K. Srivastava4, C. Ao1, C. Song5,
Y. Wang5, and J. Huang 1
1State Key
Laboratory of Water Resources and Hydropower Engineering Science, Wuhan
University, Wuhan 430072, China
2 School of Water Conservancy and Environment,
Zhengzhou University, Zhengzhou 450001, China
3 State Key Laboratory of Simulation and
Regulation of Water Cycle in River Basin, China Institute of Water Resources
and Hydropower Research, Beijing 100038, China
4 Crop Science Group, Institute of Crop
Science and Resource Conservation, University of Bonn, Bonn, 53115, Germany
5 Heilongjiang Institute of Water
Conservancy and Hydropower Survey, Planning, Design and Research, Haerbin,
100120, China
*Correspondence: zengwenzhi1989@whu.edu.cn, ☆ These authors
contributed equally to this work
ABSTRACT
Finding
out the regulations of crops Morpho-Physiological Characteristics (MPC) to
vertical heterogeneous salinity is significant to understand the crop salt
tolerance mechanism. An outdoor pot experiment cultivated with sunflower (Helianthus
annuus L.; cultivar: LD5009) was conducted at four initial
salinity levels (S1: 4.08-9.79, S2: 6.72-11.58, S3: 8.01-13.62, and S4:
10.60-14.31 dS∙m-1), three types of
soil salinity distributions (A-type, greater salinity in lower soil; H-type,
homogenous salinity; V-type, greater salinity in upper soil) were manually
created and maintained by stratified irrigation in each salinity level. Results
show the inconsistent inhibitions of salinity levels and distributions on the
sunflower MPC, for S2 compared to S1, the MPC reductions were insignificant in
V-type, while the maximum leaf area and flower disc diameter, shoot biomass,
and transpiration were significantly decreased in A- and H-types (P ≤ 0.05), while the
MPC in V-type decreased over than in A-type and resembled with those in H-type
for S3 and S4. Consistent with the phenomena of more root biomass distributed
in lower salinity soil in salinity heterogeneous treatments, the MPC closely
correlated with the minimum
salinity (SMin) in potting soil (R2=0.72-0.85), SMin in the lower soil improved sunflower
growth more than it in the upper soil when SMin < 9 dS∙m-1 (S2),
while the opposite effects were presented if SMin
> 9 dS∙m-1 (S3, S4). Therefore, the status of SMin
and its vertical position might
be important factors for crop salt tolerance
determination.
Keywords: Vertical salinity
heterogeneity; Sunflower; Morphology; Biomass; Root distribution; Transpiration
https://doi.org/10.36899/JAPS.2020.6.0179
Published online August 03,2020
Abbreviations
A
|
Higher salinity in the lower soil layer
|
H
|
Uniform salinity distribution
|
V
|
Higher salinity in the upper soil layer
|
S1, S2, S3, and S4
|
Four salinity levels
|
DAS
|
Days after sowing
|
SD
SL
|
Soil depth
Soil layer
|
MPC
|
Morpho-physiological characteristics, including the
leaf area, crop height, stem diameter, and flower disc diameter, shoot and
root biomasses, and transpiration of the sunflower in this article
|
MLA, MH, MSD, and MFD
|
Maximum leaf area, height, stem diameter, and flower
disc diameter
|
CT
|
Cumulative transpiration of sunflower during the period
of pot weight measurement
|
SB, RB
|
Shoot biomass and root biomass
|
RDW
|
Root dry weight
|
RTop, RMid, and RBot
|
The ratios of the RDW in the top, middle and bottom SLs
to the total RDW
|
SHI
|
Salinity heterogeneity index
|
STop, SMid, and SBot
|
Mean of soil salinity in the top, middle and bottom SLs
during the period of sunflower growth (positional salinity heterogeneity
indices)
|
SMean, SRmean
|
Arithmetic mean of soil salinity at the top, middle and
bottom SLs and the mean of soil salinity of the three SLs weighted by the RWD
in each SL
|
SMax, SMin
|
Maximum and minimum soil salinity of the top, middle,
and bottom SLs
|
INTRODUCTION
Soil
salinity is among the detrimental abiotic factors that threaten natural and
agricultural ecosystems (Türkan and Demiral, 2009; Deinlein et al.,
2014). Approximately 80 million hectares of cultivated land worldwide have
suffered from soil salinization (Zhang et al., 2012), which has caused
economic losses of over 10 billion USD annually (Qadir et al., 2014).
Meanwhile, salinity heterogeneity is widespread in saline fields resulting from
leaching of rain and irrigation, soil evaporation, crop root uptake, and
groundwater fluctuation (Bazihizina et al.,
2012a, b; Feng et al., 2017). In particular, for vertical soil salinity
heterogeneity, studies indicated the maximum soil
salinity was three to several hundred times higher than the minimum value
within a vertical soil depth of 1 meter in various
saline soils (Bazihizina et al., 2012b).
Although
salinity heterogeneity exists both horizontally and vertically in soils (Bazihizina
et al., 2012b; Quiñones Martorello et al., 2017), most of the studies
concentrated on the plant physiological feedback to horizontal salinity
heterogeneity. These studies mainly applied split-root experiments in
greenhouses to divide root systems into several equal portions, each portion
was treated by different salt concentrations (Shani et al., 1993; Flores
et al., 2002;
Bazihizina et al., 2012a, b; Reef et al., 2015; Sun et al.,
2016; Feng et al., 2017). In contrast to uniform salinity treatments,
alleviation phenomena were found in horizontally heterogeneous salinity
treatments, such as the greater biomasses of shoots and roots in less saline
soil were observed for both halophytic and glycophytic plants (Bazihizina et
al., 2012a, Sun et al., 2016). These phenomena are mainly related to
the crops physiological mechanism under
heterogeneous salt conditions (Kong et al. 2012, 2016), including 1)
increase the root water absorption in the low-salt root zone, 2) transport Na+
in the high-salt root zone to the low-salt root zone through the phloem, 3)
exclude Na+ out of the root system through Na+/H+
reverse transportation of the plasma membrane, 4) decease the Na+
concentration in the leaves to maintain the photosynthetic rate, etc.
However,
unlike horizontal salinity treatments, for most plants, the vertical
nonuniformity of root distribution and water-absorbing capacity increase the
complexity of plant response to vertical salinity heterogeneity (Bazihizina et
al., 2012b; Quiñones Martorello et al., 2017). Moreover, due to the
geotropism of root development, it is difficult to control longitudinal
water-salt migration in the root zone while ensuring natural root growth at the
same time. Only a few attempts have been conducted to construct vertically
heterogeneous soil salinity, but some inconsistent conclusions have been drawn
for different plants and treatments (Northey et al., 2006; Quiñones
Martorello et al., 2017). Shalhevet and Bernstein (1968) separated the
root zone of alfalfa into two to three horizons by wax membranes and found that
the plant growth reduction was related to the mean salinity of the two portions
of the root system; the water uptake was increased in each portion when half of
the root system was under salinity treatment. However, using similar methods, Bingham
and Garber (1970) found that the top portion of the corn root system was
considerably more salt-sensitive than other portions and that corn was able to
withstand considerable salinization as long as at least one-third of the root
zone was kept salt free. Since then only a few studies have been conducted
because the similar horizontal barriers (e.g., wax membranes) were difficult to
apply and maintain during the experiments, and the root resistance through the
barriers differs from that in real soil matrices (Shalhevet and Bernstein,
1968; Bazihizina et al., 2012b). Quiñones Martorello et al.
(2017) had used stratified irrigation method with different salinity solutions
to mimic vertical salinity heterogeneity in two types of the woody root zone of
Salix matsudana x S. alba (low drought and salinity tolerance with
adventitious stem roots) and E. camaldulensis (high salinity tolerance
with a taproot and many lateral roots), and they found greater negative effects
of salinity on plants when higher salt concentrations were in deeper soil
layers (SLs), and the salt tolerance thresholds depended on the distribution of
salinity heterogeneity than on the average concentration of soil salinity in the
root zone.
The
differences in the above conclusions might be influenced by the differences in
plant salt tolerance and the root distribution, stress degree and heterogeneity
distribution of the salinity treatments; the universal conclusions remain to be
explored by comprehensively considering these factors in experimental designs.
Therefore, a moderate-salt-tolerance economic crop (Bhatt and Indirakutty,
1973; Allan et al., 1998; Zeng et al., 2016), sunflower (Helianthus
annuus L.; cultivar: LD5009) was chosen to explore the influences of
vertical salinity heterogeneity. Sunflower is a global annual oilseed crop
cultivated on nearly 25 million hectares and has 8% share in the oilseed
market, and it has promised to maintain stable yields across a variety of
environmental condition (Zeng et al., 2014; Zeng et al., 2016;
Badouin et al., 2017; Ma et al., 2017; Hussain et al.,
2018). Three common vertical distributions of salinity heterogeneity were
considered, including A (higher salinity in the lower SL), H (uniform salinity
distribution) and V (higher salinity in the upper SL) types. Four salinity
grades distinguished by the average salinity status of the root zone was applied
and ranged from slight to heavy salinity stress for sunflower. Heterogeneous
soil salinity in our study was achieved by prefilling soil with a specified
salinity in different SLs, and a stratified irrigation method was used to
maintain salinity heterogeneity. This method was relatively simple for
experimental operation purposes, and horizontal barriers were not used for
salinity heterogeneity control in this experiment, so there was no external
physical resistance to root growth.
The
objectives of this study were to test two hypotheses: (1) the MPC of sunflower
(including shoot morphology and biomass, root distribution, and transpiration)
will be affected by vertically heterogeneous soil salinity, and (2) the
alleviation degree to which the effects of vertical salinity heterogeneity on
the MPC of crops will be changed in different salinity levels. Additional aims
were to (1) determine the key salinity factor for crop salt tolerance by
proposing three types of heterogeneity indices (including positional, average,
and extreme salinity) and (2) establish quantitative relationships for the MPC
of sunflower.
MATERIALS AND METHODS
Experimental
site: To
ensure a normal natural light and temperature for sunflower growth, the pot
experiment was carried out by outdoor planting and was conducted in 2013 at the
Yonglian experiment station in the Hetao irrigation district in Inner Mongolia,
China (108°0'15.3"E, 41°4'2.16"N). The experimental area is in the
temperate zone with a continental semi-arid and arid monsoon climate, and the
meteorological data during the experiment were automatically monitored by the
meteorological station within the experiment site (Table 1).
Table
1.
Meteorology observations during the experimental period in 2013.
Month
|
Maximum temperature
(°C)
|
Minimum temperature
(°C)
|
Mean temperature
(°C)
|
Relative humidity
(%)
|
Wind speed
(m∙s-1)
|
Solar radiation
(W∙m-2)
|
Precipitation (mm)
|
Evaporation (mm)
|
4
|
29.7
|
-10.3
|
9
|
44.1
|
2.7
|
153.7
|
0
|
104.1
|
5
|
31.7
|
4.5
|
7.7
|
47.7
|
2.3
|
222.6
|
16.6
|
157.2
|
6
|
35.6
|
8.4
|
7.1
|
58.2
|
1.8
|
220
|
25.4
|
121.6
|
7
|
35.2
|
11.7
|
7.1
|
69
|
1.2
|
222.5
|
8.8
|
121.3
|
8
|
35.2
|
5
|
7.7
|
69.6
|
1.3
|
215.9
|
27.6
|
119.8
|
9
|
30.2
|
-1.9
|
8.7
|
63.8
|
1.5
|
182
|
24.4
|
97.9
|
10
|
28.8
|
-8.5
|
8.5
|
59.1
|
1.4
|
152.6
|
2.6
|
72.7
|
Experimental
system design
Figure 1. View of the
experimental scene (a) and pot device (b).
The
experimental soil was taken from the tillage soil in nearby farmland and was
silty clay loam soil, consisting of 11.64% sand, 49.81% silt, and 38.56% clay.
The soil was divided into different parts by its ECe (dS∙m-1),
which was calculated from EC1:5 (ECe=7.4×EC1:5)
(Zeng et al., 2016); EC1:5 (dS∙m-1)
was the electrical conductivity of the soil supernatant solution (the mixed
volume rate of soil with deionized water was 1:5). The air-dried fresh soils
were sieved with a 2 mm screen, and then these different-salinity soils were
evenly mixed with deionized water according to the designed salinity (shown in
Table 2). Meanwhile, the fertilizers urea (597 kg·ha-1) and calcium
superphosphate (936 kg·ha-1) were mixed into the soils, and the soil
water content was adjusted to the field capacity (~ 25.6% dry weight of soil).
The new mixed soils were filled layer by layer according to the experimental design
(see Table 2) into a cylindrical iron bucket (30 cm in diameter, 40 cm in
height, shown in Figure 1b.). The filling depth was
30 cm, and the soil density was controlled at 1.3 g·cm-3. The soil
surface was covered with a transparent film to slow down the soil evaporation,
and each pot was wrapped with a 2 cm thick insulating film to reduce heat
exchange between the potting soil and surrounding air (shown in Figure 1b).
Additionally, to effectively control the soil salt and water status of the
pots, a simple rain roof was installed on the top of pots and was expanded only
on rainy days.
Figure 2. Schematic diagram
of soil salinity vertical heterogeneity.
Constant
salinity was controlled within each 10 cm soil starting at the soil surface,
designated 0-10 cm, 10-20 cm, and 20-30 cm as the top, middle, and bottom
soils. The vertical salinity gradients of the three SLs were set into three
categories: A-, H-, and V-type (as shown in Figure
2.). Four salinity levels were used for each type
of salinity gradient; therefore, there were 12 salinity treatments, and three
replicates were conducted in each treatment. The initial salinity status of
each SL (shown in Table 2) was measured during the soil filling process.
Table
2.
Initial salinity (ECe, saturated electrical conductivity) of each
treatment in the pot experiment.
Salinity level
|
Soil depth (cm)
|
Initial salt distribution/ Mean ± SD (ECe, dS∙m-1)
|
A
|
H
|
V
|
S1
|
2.5
|
4.28 ± 1.84
|
6.3 ± 1.51
|
9.69 ± 2.46
|
7.5
|
4.33 ± 1.82
|
6.52 ± 1.24
|
9.72 ± 2.45
|
15
|
7.08 ± 1.02
|
6.57 ± 1.26
|
7.04 ± 1.07
|
25
|
9.79 ± 2.44
|
6.76 ± 1.05
|
4.44 ± 1.57
|
S2
|
2.5
|
6.72 ± 0.64
|
8.87 ± 0.93
|
11.54 ± 0.73
|
7.5
|
6.75 ± 0.67
|
8.91 ± 0.93
|
11.58 ± 0.71
|
15
|
9.22 ± 0.70
|
8.96 ± 0.97
|
9.14 ± 0.78
|
25
|
11.50 ± 0.85
|
9.04 ± 1.02
|
6.81 ± 0.44
|
S3
|
2.5
|
8.05 ± 1.53
|
10.52 ± 0.40
|
13.51 ± 1.84
|
7.5
|
11.18 ± 1.69
|
10.58 ± 0.38
|
13.59 ± 1.96
|
15
|
12.35 ± 3.11
|
10.76 ± 0.34
|
10.74 ± 0.38
|
25
|
13.62 ± 2.06
|
10.89 ± 0.39
|
8.01 ± 1.49
|
S4
|
2.5
|
10.73 ± 1.01
|
12.51 ± 1.11
|
14.16 ± 1.01
|
7.5
|
10.79 ± 0.95
|
12.55 ± 1.10
|
14.18 ± 0.97
|
15
|
12.75 ± 1.14
|
12.59 ± 1.11
|
12.71 ± 1.23
|
25
|
14.31 ± 0.88
|
12.68 ± 1.08
|
10.60 ± 1.04
|
Sunflower
(Helianthus annuus L.; cultivar: LD5009) seeds, a commercial variety, were sown
on June 18, 2013, and harvested on Sept. 29, 2013. The hole sowing method was
used in this experiment. Three seeds were initially sown in each hole, and the
sowing depth was 2-3 cm. The seedling representing average growth status was
retained, and the other two seedlings were cut off by scissors when the first
pair of cotyledons appeared. Foliar fertilizer was added during the budding and
flowering stages of sunflower.
To
reduce the vertical migration of soil salt and water in the pots, the root zone
of the sunflower was layer-irrigated through 5 mm diameter porous irrigation
hoses at depths of 5, 15, and 25 cm below the surface (shown in Figure 1b.).
The water was slowly injected by using a syringe, and the hoses were opened
only during irrigation. The potted soil water content was maintained by 70-90%
of the field capacity, the irrigation amounts used in the experiment were based
on the daily (or two-day) transpiration measurements of the sunflower, and the
irrigation amount of each SL was determined by the water consumption ratio of
the corresponding depth, which was calculated from two consecutive soil water
measurements.
Soil
salt and water measurements: The dynamic monitoring of soil water and
salt was performed by soil stratification sampling,
and the sampling holes were located at 2.5, 7.5, 15, and 25 cm below the soil
surface. The soil (~15 g) was carefully collected by a soil-specific drill
(nearly 1 cm in diameter) on days after sowing (DAS) 1, 14, 41, 60, 80, and 96.
The soil salt content was represented by ECe (dS∙m-1),
and the measurement method is described in the last section. The soil
volumetric water content (θv) was determined by fresh soil oven
drying 8 h at 105 °C.
Dynamic
observations of morphological characteristics (MPC): The MPC of leaf
area, crop height, and stem and flower disc diameter of sunflowers were
measured dynamically. The length (L) and width (W) of leaves were measured at
DAS 42, 50, 59, 67, 70, 82, 90, 96 and 99, and the leaf area was equivalent to
the area of a circle with a diameter of D = (L + 2W) / 3 (Zhao, 2015). The
height of each sunflower was measured once every alternate day from emergence
until the observations were stable. The height before flowering was equal to
the vertical distance between the soil surface and the sunflower top, while
after flowering, the crop height was the vertical distance between the soil
surface and the flower disc bottom. The diameter of the stem was measured once
every alternate day from DAS 20; the values were determined 1 cm above the soil
surface. The diameter of the flower disc was measured once every alternate day
from DAS 44, and the measured values were determined as the mean of the minimum
and maximum diameters obtained in different directions. Additionally, the times
of the emergence, budding, flowering, and maturity stages of sunflowers under
different treatments were recorded.
Transpiration
measurements: The
weight of each pot was measured at 8:00-9:00 am once every alternate day from
DAS 12 to DAS 77. Then, the transpiration of the sunflower during this period
was calculated by mass conservation: the evaporation was ignored because the
soil surface in pots was covered by transparent films, therefore, the
transpiration was the difference between two consecutive pot weights minus the
irrigation amount during this period.
Shoot
and root biomass measurements: The shoots of sunflower were retrieved and
divided after harvest according to the different organs of leaves, stem, flower
disc, and seeds. The fresh organs were placed in an oven for deactivation of
enzymes 30 min at 105 °C and then oven-dried to constant weight at a constant
80 °C. The dry weight of organs was measured when it had cooled to room
temperature. The soil in the pots was excavated in 5 cm layers starting at the
soil surface, and the roots were manually selected, washed with deionized water
and sieved with a 0.2 mm screen. The clean roots were then placed in an oven
and dried at a constant 70 °C to constant weight. The dry weight of the roots
in each SL was measured.
Salinity
heterogeneity characterization: To characterize the heterogeneity of soil
salinity, three types evaluation indices of soil
salinity heterogeneity were considered: firstly, the positional
heterogeneity indices, which is the mean of soil salinity at the top (0-10
cm), middle (10-20 cm), and bottom (20-30 cm) soils throughout the sunflower
growth stage (STop, SMiddle, and SBottom,
respectively), calculated via Eqs. 1-3; the second was the average
heterogeneity index, which includes the arithmetic mean value of the three
positional heterogeneity indices (SMean), as well as the weighted
mean value of the three positional heterogeneity indices based on the root dry
weight (RDW) density in each SL (SRMean), calculated via Eq. 4-5;
and the third was the extreme index, which includes the maximum and minimum ECe
values of the positional heterogeneity index (SMax and SMin,
respectively), calculated via Eqs. 6-7.
(1)
(2)
(3)
(4)
(5)
(6)
(7)
In
Eqs. 1-3, ECe,i,j is the soil ECe at a soil
depth of i cm in the j-th measurement; RTop, RMid, and RBot
are the ratios of the RDW in the top, middle and bottom soils, respectively, to
the total RDW.
Statistical
analysis: Statistical
analyses were achieved by using R version 3.5.1 (Copyright (C) 2018 the R
Foundation for Statistical Computing ISBN 3–900,051–07-0). The least
significant difference (LSD) at a 0.05 level of probability was applied to
detect differences among the measured variables in the 12 salinity treatments
with four salinity levels and three types of salinity distributions.
Additionally, the coefficient of determination (R2) was applied to
characterize the correlations between the morpho-physiological responses of
sunflower and the soil heterogeneity indices (SHIs).
RESULTS
Soil
salinity distributions: The overall ECe values in different SLs
based on six measurements during the growth period of sunflower are shown in
Figure 3, the dynamic fluctuations were existing in each potted SL, especially
in top and bottom SLs. Compared with the initial salinity status (at Das 1),
the highest median ECe values of the top soil (SD = 2.5 and 7.5 cm)
in all measurements increased by nearly 1-5 dS·m-1 for the H and V
soil types, while the value increased 4-6 dS·m-1 for the A-type. In
contrast to the upper soil, the highest median ECe values of the
bottom soil (SD = 25 cm) increased by 6-7.5 dS·m-1 for the V-type,
which was slightly higher than the increases observed for the A (5-7 dS·m-1)
and H (5-6.5 dS·m-1) types. The average ECe values of all
measurements (the median and main distribution (between Q1 and Q3 of the
boxplots) of ECe boxplots) show that in each SL in the
higher-salinity treatments were generally higher than those in in the
lower-salinity treatments. The lower limit (Q1) of the ECe main
distribution for the three salinity distributions gradually improved with
increasing salinity levels: ECe was nearly 4 and 10 dS·m-1
for levels S1 and S2, respectively, while ECe was greater than 9 and
11.5 dS·m-1 for levels S3 and S4, respectively. Additionally, the
median values and main distributions of ECe values throughout the
whole sunflower growth period essentially maintained the initial trends (except
in several treatments for the soils at SD = 2.5 and 25 cm), the median values
of the ECe boxplots for different salinity distributions at top soil
(SD = 2.5 cm and SD = 7.5 cm) followed the order V >
H > A; at bottom soil (SD =25 cm), the order A > V > H was
obtained, and similar results were found at middle soil (SD = 15 cm), as shown in
Figure 3.
Figure 3. Statistical
results of soil salinity (ECe) measurements on DAS 1, 14, 41, 60, 80
96 (small boxplots) and average status of all measurements (big boxplots) at
different soil depths (SD =2.5, 7.5, 15, and 25 cm) with different salinity
levels (S1, S2, S3, and S4) and heterogeneity (A, H, and V) treatments. The
25th percentile (Q1), medians, and 75th percentile (Q3) of the estimation
objects were represented by the upper, middle bold lines, and lower edges of
the boxes, respectively; the vertical lines of the boxes indicated the
estimation objects extend to 1.5 × (Q3 - Q1).
Shoot morphology
and biomass response: Clear differences in the times for the seed
germination and seedling stages of sunflower were observed for different
salinity treatments (in Figure 4). The time of seed germination slowly
increased with increasing soil salinity level when the salinity level was lower
than S4, while the time abruptly increased to DAS 12-13 in the S4 treatments with
H and V soil salinity distributions, and the germination times for A-type were
shorter than those for H- and V-types at the same salinity level. Moreover, the
time to reach the seedling stage of sunflower was also increased with an
increase in salinity level. The longest increase time was obtained in the H-type
when the salinity level was lower than S4 (39, 47,
and 45 days for levels S1, S2, and S3), respectively; however, for the S4
salinity level, the longest increase (46 days) was observed in the V-type. No
significant differences (in Figure 4) of sunflower stage times among the
different treatments after seedling, but sunflower could not enter the
flowering stage in V-type when the salinity level reached S4.
Figure 4. Time periods for
the seed germination and growth stages of sunflower in different salinity
levels (S1, S2, S3, and S4) and heterogeneity (A, H, and V) treatments. Values
are means (n = 3) ± SE (in levels S3 and S4, the times for sunflower flowering
and maturity in H-type were measured from one sample, where n=1). The letters
above the bars represent significant differences among the 12 salinity
treatments for each growth stage of sunflower (LSD
test; P ≤
0.05). The different numbers at the ends of the bars represent the days of sunflower
each growth stage.
The
dynamic characteristics of sunflower morphology in
different treatments are presented in Figure 5. Leaf area increased first and
then decreased slowly, reaching a maximum near DAS 75. The height and stem
diameter of sunflower grew rapidly at first and then gradually stabilized after
DAS 75 and 60, respectively, while the flower disc grew linearly throughout the
measuring period. The growth of sunflower morphological features was gradually
inhibited with increasing soil salinity level; for example, the maximum leaf
area, height, stem diameter and flower disc diameter of sunflower in salinity
level S4 decreased by 75%, 40%, 50%, and 55% respectively compared to those in
salinity level S1. Moreover, at the S2 salinity level, the MPC in the V type
were larger than those in the A-type, and the smallest MPC were obtained in the
H- type, particularly, the maximum of leaf area and flower disc diameter of
sunflower in the V-type was significantly greater than those in the H-type (P ≤ 0.05). In
contrast to the S2 salinity level, the maximum MPC of sunflower at the S3
salinity level were observed in the A-type, and the growth of morphological
features in the H- and V-types were similar. Additionally, at the S4 salinity
level, minor differences in MPC were observed between the A- and H-types, while
minimum morphological feature growth was obtained in the V-type.
Figure 5. Dynamic growth of
leaf area, height, stem diameter, and flower disc diameter of sunflower under
different salinity levels (S1, S2, S3, and S4) and heterogeneity (A, H, and V)
treatments. Values are means (n = 3) ± SE. The maximum MPC values (mean values
of three replicates) in different salinity distributions are listed in the top
left of each figure. Significant differences in these values among the 12
salinity treatments are indicated by letters after the maximum MPC values (LSD
test; P ≤
0.05).
The
total shoot biomass of sunflower (in Figure 6) gradually decreased with
increasing salinity levels beyond S1. All organ biomasses of sunflower shoots
at the S2 level were considerably decreased in the A- and H-types, except stem
biomass in the A-type, but there was no significant reduction in biomass for
all organs in the V-type. However, all sunflower shoot organ biomasses
significantly decreased in all salinity distributions when the salinity level
was greater than S2, while the organ biomass reduction in the A-type was
smaller than that in the H- and V-types. Moreover, the organ biomass
distributions of sunflower shoots were different at different salinity levels
and distributions, especially the biomass distributions of reproductive organs.
At level S1, the distribution coefficients of the vegetative organs and
reproductive organs of sunflower were similar in the three salinity
distributions. However, at level S2, the partition coefficients of flower discs
increased but the partition coefficients of seeds decreased in the A- and H-types,
while the partition coefficients of flower discs changed little and the
partition coefficient of seeds increased in the V-type. At level S3, the
partition coefficients of discs and seeds in A-type did not change
significantly compared with S2, but the partition coefficient of flower discs
increased, and the partition coefficient of seeds decreased in the H- and V-types.
The seed partition coefficients at level S4 were reduced in the three types of
salinity distributions: the order was A > H > V.
Figure 6. Biomass of stem,
leaf, flower disc, and the seed of sunflower at harvest in different salinity
levels (S1, S2, S3, and S4) and heterogeneity (A, H, and V) treatments. Values
are means (n = 3) ± SE. The total shoot biomass of sunflower (mean value of
three replicates) in each salinity treatment is listed in the top left of each
figure. The letters represent significant differences of 12 salinity treatments
for organ and total biomass of sunflower shoot (LSD test; P ≤ 0.05). The
different percentages at the ends of the bars represent the relative proportion
of each shoot organ.
Root distribution
and transpiration: The
total RDW (in Figure 7) gradually decreased with increasing soil salinity; in
particular, when the salinity level was over S3, the total RDW decreased
significantly. Although there were no obvious differences in total RDW among
different salinity distributions at the same salinity level, the maximum
significant reduction (71.85%) in total RDW for the whole soil profile was
found in the H-type when the salinity level was S2 compared with the that for
S1, and at the S4 salinity level, the root biomass in the V-type salinity
distribution was less than that in the other salinity distributions. Meanwhile,
in the A-type, the RDW at the soil depth of 0-10 cm
accounted for 84.19%, 89.14%, 96.21%, and 92.45% of the total root system at
levels S1, S2, S3, and S4, respectively; these values were higher than those in
other salinity distributions except in V-type at the S2 level. In the V-type,
the decreases in RDW at a soil depth of 0-5 cm were 67.84% and 91.25% at levels
S3 and S4 respectively relative to that for S1; these values were greater than
those in the other two salinity distributions, but the relative distributions
of RDW at a soil depth of 20-30 cm (2.61% in S3) and 10-20 cm (10.51% in S4)
were higher than those in other salinity distributions.
Figure 7. Distributions of
root dry weight (RDW) of sunflower under different salinity levels (S1, S2, S3,
and S4) and heterogeneity (A, H, and V) treatments. Values are means (n = 3) ±
SE. The total root biomass (mean value of three replicates) in each salinity
treatment is listed in the bottom right of each figure. The letters at the ends
of the bars and after the total root biomass values indicate significant
differences among the 12 salinity treatments (LSD test; P ≤ 0.05). The
different percentages at the ends of the bars represent the relative proportion
of RDW distributed in each SL.
The
irrigation amount (in Figure 8) increased during the sunflower growth period
but decreased with increasing soil depth. There were no obvious differences in
total irrigation amounts among different salinity distributions at the same
salinity level. However, the irrigation amount for each SL decreased with
increasing salinity level; in particular, for salinity levels S3 and S4, the
total irrigation amounts at a soil depth of 20-30 cm were less than 400 cm3.
The irrigation amount for each SL was similar among different salinity
distributions at the S1 salinity level. However, at the S2 salinity level, the
irrigation amounts required for all SLs in the V-type were higher than those in
the A-type, and the minimum irrigation amounts were required in the H-type. In
contrast to S2, the irrigation amounts for each SL in the A-type at S3 level
were higher than those in the V-type, and the minimum amounts were also
required in the H-type. Small irrigation amounts were required for sunflower in
all salinity distributions at the S4 salinity level, especially for sunflower
in the V-type.
The
transpiration process of sunflower (Figure 9) increased rapidly after DAS 40,
and cumulative transpiration (CT) reached 20 (×10-3 m3) at the S1 salinity level.
There was no obvious difference in the CT of sunflower among salinity
distributions at the same salinity level, while CT gradually decreased with
increasing salinity level; for instance, CT was less than 0.5 (×10-3
m3) in the treatment with an S4 salinity level and a V-type
distribution. The CTs of sunflower were relatively similar among the three
types of salinity distribution at the S1 salinity level. However, at the S2
level, the CT of sunflower in the V-type was higher than that of sunflower in
the A-type, and the minimum CT was found in the H-type. At the S3 level, the CT
of sunflower in the A-type was higher than that of sunflower in the V- and H-types.
In addition, at the S4 salinity level, the CTs of sunflower in the three types
of salinity distributions were similar, while the CT of sunflower in the V-type
was lower than those in the A- and H-types after DAS 65.
Figure 8. Irrigation amounts
for each SL under different salinity levels (S1, S2, S3, and S4) and
heterogeneity (A, H, and V) treatments. Values are means (n = 3) ± SE. The
cumulative irrigation (mean value of three replicates) for each salinity
treatment is listed in the top left of each figure. The letters after the
cumulative irrigation values indicate significant differences among the 12
salinity treatments (LSD test; P ≤ 0.05).
Figure 9. Cumulative
transpiration (CT) of sunflower under different salinity levels (S1, S2, S3,
and S4) and heterogeneity (A, H, and V) treatments. Values are means (n = 3) ±
SE. The CT (mean value of three replicates) in each salinity treatment is
listed in the top left of each figure. The letters after the CT values indicate
significant differences among the 12 salinity treatments (LSD test; P ≤ 0.05).
Correlations
between sunflower MPC and soil heterogeneity index (SHI): The determination
coefficients (in Figure 10) between sunflower MPC
and positional heterogeneity indices indicated that MPC was more strongly
correlated with SMid (R2 of 0.59-0.73) than with STop
(R2 of 0.59-0.67), while the weakest correlations were obtained
between MPC and SBot (R2 of
0.38-0.65). In terms of the correlations of MPC with average heterogeneity
indices, MH, MSD, and MFD were similarly correlated with SMean (R2
of 0.63-0.7) and SRmean (R2 of 0.66-0.7), while MLA, CT,
SB, and RB were more strongly correlated with SMean
(R2 of 0.74-0.84) than SRmean
(R2 of 0.64-0.73). Moreover, the determination coefficients between
MPC and extreme heterogeneity indices showed that MPC was more closely related
to SMin (R2 of 0.73-0.86) than SMax (R2
of 0.46-0.73). Overall, among the positional, average and extreme heterogeneous
indices, MLA, CT, SB, and RB were similarly closely correlated with SMean
and SMin (R2 of 0.74-0.85),
while MH, MSD, and MFD were better correlated with SMin (R2
of 0.72-0.78) than SMean (R2 of 0.65-0. 70).
Figure 10. Determination
coefficients (R2) between the morpho-physiological characteristics
(MPC) of sunflower (MLA, MH, MSD, and MBD are the maximum leaf area, height,
stem, and bud diameter during the growth period, respectively; CT indicates the
cumulative transpiration of sunflower; and SB and RB are the shoot and root
biomass of sunflower at harvest, respectively) and heterogeneous indices of
soil salinity. The significances of the above correlations were smaller than
0.01 (P < 0.01). The MPC data were obtained from 36 individual sunflowers
under different salinity levels (S1, S2, S3, and S4) and heterogeneity (A, H,
and V) treatments.
The
correlations of MPC with SMin showed that all MPC of sunflower were
negatively linearly correlated with SMin, and Figure 11 shows that
when SMin changed from 3 to 15 dS·m-1, MH, MSD, and MFD
decreased by nearly 57%, 69%, and 76%, respectively, from
their respective maximum values, while the values of MLA, CRWU, SB, and RB
decreased by nearly 92-95%. Moreover, the quantitative relationships between
MPC and SMin were established by the linear regression method (in Figure
11). Relatively good fitting effects were acquired, especially for the fitting
curves of SB and RB with SMin (R2 reached 0.8).
Figure 11. Quantitative
relationships (P < 0.01) between the morpho-physiological characteristics
(MPC) of sunflower (MLA, MH, MSD, and MFD are the maximum leaf area, height,
stem, and bud diameter during the growth period, respectively; RWU indicates
the cumulative root water uptake; and SB and RB are the sunflower shoot and
root biomasses at harvest, respectively) and the positional heterogeneity index
of minimum ECe in potting soil (SMin). The red lines are
fitting linear curves for these quantitative relationships, and the grey shaded
areas represent the 95% confidence intervals. Each point was obtained from one
individual sunflower.
DISCUSSION
Vertical
distribution of soil salinity: The median and main distribution of ECe
values in different SLs (in Figure 3) indicated that vertically heterogeneous
soil salinity was essentially achieved according to the A, H, and V-types
during the period of sunflower growth, and the initial trend in salinity with
respect to depth was maintained at the same salinity level among different
salinity distributions (in Table 2). Therefore, the experimental method used in
this research was feasible for soil salinity heterogeneity controlling as
experiments demand. While the soil salinity of each SL
was dynamic changed during the experiments (in Figure 3), which might
result from several reasons: First, although the stratified irrigation was
applied in our experiments, while the water consumptions were different among
different SLs, the greater water was usually irrigated in the upper SL because
of the greater water consumption in these layers (shown in Figure 8), which
might leach soil salt to the bottom SL with a certain extent; meanwhile, the
greater water consumption of top SL also might drive soil salt accumulation on
the top SL from lower SLs.
Additionally,
unique phenomena were observed in the top soil: the increases in the median ECe
values for all A-type measurements were greater than those for the H and V
salinity types. However, in the bottom soil (SD = 25 cm), the maximum increase
in median ECe was obtained in V-type conditions. These phenomena
might result from roots compensatory water uptake in lower salinity layers (Bazihizina
et al., 2012a; Sun et al., 2016), the water potential gradient
could drive more salt to the low-salinity soil from the high-salinity layer,
and soil salt might be transported by phloem and then extruded by the roots in
lower-salinity soil (Kong et al., 2012, 2016).
MPC
and biomass of sunflower shoot under different salinity
levels and vertical distributions: Salinity affects the germination and emergence
processes of plants by lowering the osmotic potential and causing toxicity,
which inhibits seed water uptake and changes the nucleic acid metabolism
enzymes activities (Katembe et al., 1998; Parihar et al., 2015). Our
study found that the emergence of sunflower was significantly delayed in
high-salinity treatments. Because sunflower seeds were directly sown in the top
layer of soils with different salinities, differences in sunflower emergence
were caused by differences in the initial salinity of the top soil among the
different treatments. The emergence of sunflower was abruptly prolonged to
12-13 days from 8 days in the H- and V-types when the salinity level was
greater than S3, which indicated that the soil ECe threshold for
sunflower emergence is about 11.4 - 13.6 dS∙m-1
(from Figure 3). Delgado and Sánchez‐Raya (2007), Liu et al. (2010)
also reported similar postponement phenomena of sunflower germination and
emergence in their studies.
The
seedling time of sunflower gradually increased with increasing soil salinity in
our study, the results indicated plants were sensitive to salinity during early
vegetative growth stage (Parihar et al., 2015), similar results were
observed by Uniyal and Nautiyal (1998); Wu et al. (2016) and Alam et al.
(2011) for Ougeinia dalbergioides Benth. and Oryza sativa L. Pokkali.
Noticeably, the seedling times of sunflower in the A- and V-types were shorter
than that in the H-type when the salinity level was lower than the S4 level (SMin smaller than 11.5 dS∙m-1),
which provided evidence that sunflower growth in heterogeneous soil salinity
distributions can relieve salinity stress at the seedling stage compared with
that in homogeneous-salinity soil. After the seedling stage, the growth stage
of sunflower in this experiment was not significant among the different
salinity treatments, which implied sunflower decrease the sensitivity to
salinity than vegetative growth, Maas and Poss (1989) also found the similar
phenomena for the reproductive development of cowpea, wheat, and sorghum.
Meanwhile, at the S4 salinity level, the compensation effects of plant growth
and root water uptake were restricted by the heavy salinity stress existed in the
whole roots zone (SMin greater than 11.5 dS∙m-1).
In this situation, sunflower could not supply sufficient photosynthate to the
reproductive organs and seeds, particularly in the V-type, sunflower did not
enter the flowering and maturity stages (Jenks et al., 2007).
Cells
will dehydrate and shrink to reduce cell elongation and division when plants
suffer salinization for a few moments to hours, while over several days or
weeks, cell division and elongation reductions will result in the slower
appearance of certain organs and reductions in size (Jenks et al., 2007; Munns
and Tester, 2008; Volkov and Beilby, 2017). The present results showed that the
growth of sunflower morphological features among different salinity
distributions were similar at the S1 level, while the growth of sunflower
morphological features and biomass accumulation were inhibited with increasing
salinity levels, and the degree of MPC reduction varied at different salinity
distributions and salinity levels. At the S2 level, the
MPC decreases in the V-type were slightly less than the decreases in the A-type,
and the greatest reductions were observed in the H-type. Similar to the MPC of
sunflower, comparing shoot biomass at the S1 level, obvious reductions were
observed in the A (except stem biomass) and H-types,
particularly in H-types; however, the biomass reductions and organ distribution
changes in the V-type were slight. These results indicated that compared with
salinity homogeneity, salinity heterogeneity alleviated the salinity stress on
morphological feature growth and biomass accumulation in sunflower when the
salinity of the whole soil was not too high (SMin smaller than 11.5
dS∙m-1); Bazihizina et al. (2009), Sun et al.
(2016), Feng et al. (2017), and Xiong et al. (2018) observed
similar responses for Atriplex nummularia, alfalfa, and Lycium
chinense in horizontally heterogeneous salinity soil, and Shalhevet and Bernstein
(1968), Bingham and
Garber
(1970),
and Quiñones Martorello et al. (2017) found similar results for alfalfa,
corn, Salix matsudana x S. alba and Eucalyptus camaldulensis Dehnh
in vertically heterogeneous salinity soil. Interestingly, the experiment
results showed that lower salinity in lower soil will diminish the damage to
morphological feature growth of sunflower under the mild salinity (SMin
< 9 dS·m-1, as shown in Figure 3), which might be because plant
roots rapidly expand into deeper, less saline soil when the salinity is higher
in upper soil (Kent and Lauchli, 1985; Verma et al., 2014), Quiñones
Martorello et al. (2017) also found the reductions of Salix sp.
and E. camaldulensis shoot biomass were decreased when deeper
soil had lower salinity than upper soil. However, when the salinity level
exceeded S2, the characteristics and biomass of sunflower in the A-type were
higher than those in the other salinity distributions, and worse growth and
less biomass of sunflower were observed in the V-type when the salinity level
was S4. These results indicated that when salinity stress was high overall (SMin > 9 dS·m-1,
as shown in Figure 3), because most of the roots are distributed in the
upper soil (Figure 9), lower salinity in the upper soil would create more
opportunities to alleviate damage to RWU and retain fewer absorbed toxic ions
in the plant, therefore benefit sunflower morphological feature growth.
Root
distribution and transpiration under different salinity levels and vertical
distributions: Roots are
essential to plant survival, and studies indicated that plants can adjust root
proliferation and water absorption efficiency to adapt to soil environmental
stresses (Steudle, 2000; Bazihizina et al., 2012b; Dara et al.,
2015; Ma et al., 2017). In this study, the root total biomass,
irrigation amount, and transpiration of sunflower (Figure 7-9) presented the
same trends with different salinity treatments. These indices gradually
decreased with increasing soil salinity levels, especially at S3 and S4
salinity levels. Reductions in root biomass and water uptake under salinity
stress were also observed by Munns (1993), Dolatabadian et al. (2011), Sun
et al. (2016), Soda et al. (2017), etc.
Contrast
to homogeneous salinity stress, heterogeneous salinity stress can trigger root
compensatory growth and extraction in low-salinity soil, which will alleviate
the salt stress for plant growth (Kong et al.,
2012; Sun et al., 2016; Feng et al., 2017). Bingham and Garber (1970)
also found that the root biomass and water uptake of Zea mays in soils with a
uniform salinity distribution were smaller than those in vertically
heterogeneous salinity soil (with two-thirds of the root system irrigated with
saline solution). This phenomenon was also observed in our study, such as
relative to the status of total root biomass, irrigation amount and
transpiration in S1, the reductions of these values in higher salinity level
were varied in different salinity distributions. The greatest decrease in total
root biomass and transpiration were observed in the homogeneous salinity
distribution (H) when the salinity levels were S2 and S3.
The
root biomass and transpiration in the V-type were greater than those in the A-
and H-types when the salinity level was S2 (SMin
< 9 dS·m-1, as shown in Figure 3), which provided evidence
for the hypothesis by Bazihizina et al. (2012b), which suggested that
the roots of phreatophyte
genotypes can explore into deep soils when growing in higher superficial
salinity soil. Moreover, Quiñones Martorello et al. (2017) also found
the total root biomass of E. camaldulensis was greater when lower
salinity was present in deep soil than under uniform salinity and lower
salinity in upper soil, because many roots of E. camaldulensis (nearly
50%) and the high water extraction of roots in the lower soil enable the plant
to uptake highly saline water (~ 40 dS∙m-1) from groundwater (Feikema
and Bandara, 2012). However, in our experiment, at the S4 salinity level (SMin
> 11.5 dS·m-1),
the greatest root biomass reduction was found in V-type even when the salinity
in deeper soil was smaller, which indicated that if the salinity of the lower
soil was greater than the specific threshold (11.5 dS·m-1), the
serious inhabitation of sunflower root growth would happen.
Correlations
between soil salinity heterogeneity and sunflower MPC: The above analysis
showed that the level and heterogeneous distribution of soil salinity affected
the MPC of sunflower. The correlations between MPC and positional stress
indices showed that the MPC of sunflower were more correlated with SMid
than with STop and SBot. Two aspect reasons might for
this result, first, the salinity in the top and bottom soils difficult to
reflect the salinity status of pot soils due to the stronger fluctuations;
second, the analysis from this research showed that the relationships between
MPC and positional salinity were affected by salinity level, while SMid
could better represent the information of soil salinity level. Moreover, the
correlations between MPC and SMean were
better than those between MPC and SRMean, which indicated that the
MPC of sunflower depended more on the arithmetic mean soil salinity than the
root distribution. Whereas this phenomenon differed from some studies at the
field scale that reported the significant effects of the root distribution on
salt tolerance of crops (Ma et al., 2017; Lei et al., 2019). This
difference might result from denser roots in the potting soil; additionally,
root compensatory water and nutrition uptake existed in the
heterogeneous-salinity soil, which could weaken the effects of realistic root
distribution, Sun et al. (2016) also suggested that compensatory water
uptake was not controlled by the compensatory root growth.
However,
the strongest correlation between MPC and SHI was found between MPC and SMin.
Because SMin indicates the least saline part of the soil, this
correlation implied that compensatory root growth and water uptake in low saline
soils might effectively alleviate the salinity stress for the MPC of sunflower.
The results of root distribution might support this hypothesis in our study,
the relative more root biomasses were found in upper soil in A salinity type
and lower soil in V salinity type (in Figure 7). This finding was consistent
with the conclusions for alfalfa obtained by Bazihizina et al. (2012a)
and Sun et al. (2016) as for horizontal salinity heterogeneity. Based on
correlation analysis between MPC and SHI, linear quantitative relationships
were established. These relationships indicated that MLA, CRWU, SB, and RB of
sunflower were more sensitive to SMin than MH, MSD, and MFD,
especially for CRWU, SB, and RB.
Conclusion:
Soil
salinity heterogeneity affects the MPC of sunflower, but the impact varies with
the salinity level. At lower salinity levels (SMin < 9 dS·m-1),
soil heterogeneity can better alleviate the salinity stress on sunflower growth
than salinity homogeneity: the MPC reductions of sunflower in heterogeneous
soil are less than those in homogenous soil, and a minimum salinity in the
lower soil can improve sunflower growth more than a minimum salinity in the upper
soil. However, at higher salinity levels, once the minimum salinity of the soil
is substantially greater than 9 dS·m-1, the mitigation of salinity
stress on sunflower growth by salinity heterogeneity will be weakened, while minimum salinity in the upper soil will be more
beneficial to the MPC of sunflower. Moreover, correlation analysis between MPC and SHI indicated that the minimum salinity of potting
soil is the key factor for the MPC of sunflower,
and good linear relationships were found between SMin and MPC in
sunflower. However, although salinity heterogeneity was maintained in this
experiment, the soil salinity in the top and bottom soils might be influenced
by irrigation methods, the process of compensatory water uptake in less saline
soil was not directly observed; meanwhile, the effects of heterogeneous
distribution and levels of soil salinity on plant MPC were only analyzed at pot
scale. Therefore, more detailed and greater scale experiments of crop response
mechanisms to vertically heterogeneous soil salinity are still needed for
further exploration.
Acknowledgments:
We
are grateful for financial support from the Major Program of the National
Natural Science Foundation of China (NSFC) (Grant Nos. 51879196 and 51790533)
and the Open Research Fund of the State Key Laboratory of Simulation and
Regulation of Water Cycle in River Basin (China Institute of Water Resources
and Hydropower Research) (Grant No. IWHR-SKL-KF201814).
The authors also appreciate Dr. Qian long from Sun Yat-Sen University, China
for pre-reviewing the manuscript and giving us many constructive suggestions.
Author
Contributions: Conceptualization,
G.L. and Q.Z.; Methodology, Q.Z.; Software, G.L.; Validation, G.L. C.S., Y.T.,
and W.Z.; Formal Analysis, A.K.S., C.A., and Q.Z.; Investigation, Q.Z.;
Resources, Q.Z. and J.W.; Data Curation, G.L. and Q.Z.; Writing – Original
Draft Preparation, G.L.; Writing – Review & Editing, W.Z. and Q.Z.;
Visualization, G.L.; Supervision, J.H. and W.Z.; Project Administration, Q.Z.
and G.L.; Funding Acquisition, W.Z.
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