| Journal of Phytological Sciences
Received: 18 August 2026; Revised: 24 September 2026; Accepted: 25 September 2026; Published Online: 29 September 2026.
J. Phytol. Sci., 2026, 1(1), 26902 | Volume 1 Issue 1 (September 2026) | DOI: https://doi.org/10.64189/ps.26902
© The Author(s) 2026
This article is licensed under Creative Commons Attribution NonCommercial 4.0 International (CC-BY-NC 4.0)
Yield and Quality of Cabbage in Patuakhali and
Barguna Districts of Bangladesh for Nutritional
Security
Mohammad Ghani Miah,
A.K.M. Faruk-E-Azam,*
Md. Nizam Uddin,
Muhammad Maniruzzaman, Md Shariful Islam
and Abdullah-Al-Zabir*
Department of Agricultural Chemistry, Patuakhali Science and Technology University, Dumki, Patuakhali, 8660, Bangladesh
*Email: azam@pstu.ac.bd (A.K.M. Faruk-E-Azam); zabir@pstu.ac.bd (Abdullah-Al-Zabir)
Abstract
Climate change is causing a gradual increase in soil salinity, which limits crop yield and quality. Human nutrition
and food security are primarily dependent on vegetables. The research work was conducted to examine the
impacts of soil salinity on yield and mineral accumulation of cabbage (Brassica oleracea var. capitata) grown in
tidal areas of Dumki (electrical conductivity, EC = 0.82 dS m
-1
), Nauvanga (EC = 5.90 dSm
-1
), Pakhimara (EC =
6.82 dSm
-1
), Kumirmara (EC = 7.64 dSm
-1
) of Patuakhali and Sawdagarpara (EC = 9.31 dSm
-1
) of Barguna
districts in Bangladesh during November 2024 to March 2025. The cabbage yields at Dumki, Nauvanga,
Pakhimara, Kumirmara, and Sawdagarpara were 60.5, 58.0, 56.77, 55.0, and 52.0 t ha
-1
, respectively. The lowest
yield was estimated at Sawdagarpara at the highest EC level. The edible portion was analyzed for phosphorus
(P), potassium (K), calcium (Ca), magnesium (Mg), sulfur (S), sodium (Na), zinc (Zn), iron (Fe), copper (Cu), and
manganese (Mn). Tissue analysis revealed that K concentration was highest at the non-saline baseline (Dumki)
and trended lower across the saline locations. Conversely, P concentration did not follow a strict linear decline,
peaking instead at the moderately saline site of Nauvanga (5.90 dS m⁻¹) before decreasing at higher EC levels.
Meanwhile, Ca, Mg, S, Na, Fe, and Mn concentrations generally increased up to moderate soil salinity thresholds.
Yield and mineral accumulations were reduced at the highest soil EC of 9.31 dsm
-1
. Therefore, cabbage can be
grown in low-salinity areas within the study area to support nutritional security.
Keywords: Soil salinity; Vegetable, Cabbage; Coastal area; Nutritional security.
1. Introduction
The total area of Bangladesh is 147,570 km
2,
with 29,000 km
2
of coastal area. But over 30% of cultivated areas
are coastal and offshore.
[1]
Approximately 50% of coastal lands are subject to various levels of inundation, and
as a consequence, their use is limited. This situation is likely to worsen in the future due to the impacts of climate
change.
[2]
In this area, salinity intrusion is primarily sourced from climate change and anthropogenic changes
that render the area more vulnerable. Therefore, the salinity intrusion negatively impacts water, soil,
agriculture, fisheries, ecosystem, and livelihoods in this region.
[3]
High salt ion concentrations also cause damage
to the photosynthetically active leaves and can cause chlorosis and senescence of the leaves.
[4]
Due to climate
change and associated catastrophic events such as sea-level rise, super cyclone Sidr (recent past), cyclone Aila,
and storm surge, salinity has further increased many-fold.
[5]
The increase in salinity of water and soil due to
saltwater intrusion at the coasts could be causing some negative impacts on agriculture, forestry, and
fisheries.
[6]
Salinization is a major problem in Bangladesh, especially in coastal areas, where climate change is
causing more and more extreme cyclones, causing farmers’ fields to flood. Residents living in these areas are
typically dependent on agriculture, and their lives are now endangered. The natural salinity is the accumulation
of salts that has taken place over a period of time.
[7]
Soils having electrical conductivity (EC
1:5
) exceeding 2.1
dSm
−1
at 25 °C are identified as saline soils, which corresponds to a saturated paste extract (EC
e
) threshold
exceeding 4.0 dSm⁻¹ based on the official empirical conversion factor (EC
e
=EC
1.5
*5.8) established for coastal
soils of Bangladesh by the Soil Resource Development Institute (SRDI).
[8]
This conversion factor addresses the
non-interchangeability of extraction methods and provides a standardized baseline for crop-tolerance
classifications. Salt stress hampers germination, speed of germination, root/shoot dry weight, and Na
+
, K
+
ratio
in root and shoot.
[9]
Vegetables provide health benefits, being low in fat and calories but rich in vitamins, protein, and fiber. They
are also an important source of minerals like phosphorus, potassium, calcium, magnesium, iron, copper,
manganese, selenium, and zinc.
[10]
They contain essential amino acids and antioxidants that the human body
needs to function normally. Vegetables are considered one of the most important food crops because of their
high nutritional value, higher yield, and higher return.
[11]
Almost all vegetables used worldwide are free of
cholesterol. Vegetables, if eaten fresh or partially cooked, can help counter cancer, diabetes, high blood
pressure, vision loss, heart disease, and a number of intestinal disorders. Vegetable cultivation helps to
employment generation, increase income, and reduce poverty in developing countries like Bangladesh.
[12]
Vegetable crops are especially important for farmers with small holdings because of higher income per hectare
than conventional staple crops.
[13]
Cabbage is one of the most important, highly nutritious, and palatable leafy
winter vegetables widely cultivated in Bangladesh. It is a rich source of protein, minerals, and vitamin A.
Cabbage can prevent constipation, increase appetite, speed up digestion, and is very useful for diabetic
patients.
[14]
Cabbage (Brassica oleracea L. var. capitata) is an important and nutritious leafy winter vegetable. It
is among the top 20 vegetables and an important global food source.
[15]
Nutritionally, it contains vitamins A, B,
C, E, and iron, potassium, zinc, etc. It is widely distributed in Bangladesh, including Chandpur, Comilla, Gazipur,
Mymensingh, and Jessore.
[16]
For vital nutritional security, income for coastal farmers, and for productive use of
winter season fallow lands, the present study was conducted to examine the yield and minerals accumulation
performance of cabbage at different soil salinity in the southern coastal region of Bangladesh
2. Materials and methods
2.1 Sampling sites and crop management practices
Vegetables were grown, harvested, and collected from November 2024 to March 2025 across five areas in the
Patuakhali and Barguna districts. Among the five selected locations, one was saline-free (Dumki), while the
other four (Nauvanga, Pakhimara, Kumirmar, and Sawdagarpara) were classified as slightly to moderately
saline. These site classifications were established by measuring laboratory (EC
1.5
) and converting them to
standard (EC
e
) values using the SRDI regional conversion factor (EC
e
=EC
1.5
*5.8) to guarantee accurate cross-
referencing with standard FAO crop-salinity tolerance classes. As cabbage has demand in this region, and to
evaluate the feasibility of cabbage cultivation and its yield and mineral content variation across different saline
and non-saline soils, four locations with varying degrees of salinity and one salinity-free location were selected.
A randomized complete block design (RCBD) was used in the experiment, wherein each of the five geographic
locations contained three independent, physically separated field plots serving as three distinct replications
(n=3) plots per location).
The Fertilizers applied for soil preparation were as follows: cow dung 50 tons, urea 25 kg, TSP 125 kg, MOP 200
kg, and ZnSO
4
8 kg per hectare. The dose and application of fertilizers were maintained as directed by BARC
(2018).
[17]
The variety of cabbage used was Atlas-70 (Green cabbage); seedlings were raised in a 1 m × 5 m
seedbed. 30-day-old seedlings were transplanted at a spacing of 50 cm × 50 cm on 3 November, 2024. Non-
saline pond water nearest to the respective locations was used for irrigation. Watering was done twice a week
up to maturity. Crop management practices such as weeding and mulching. Soil furrowing and other necessary
management practices were carried out as required. For the management of pests, integrated pest management
(IPM) was practiced. After maturity, when the heads attained a compact form, then the crop was suitable for
harvesting. To capture the full production span, vegetables were collected 3 times at 10-day intervals from each
plot. To maintain true biological replication for subsequent statistical analyses, temporal sub-samples from the
same field plot were composited together. This intra-plot pooling protocol preserved the 3 independent field
plot replications for each of the 5 locations, yielding a final set of 15 independent composite samples for
laboratory analysis. Harvesting of edible portions of Cabbage was done by cutting the plant a few cm above the
ground with a sharp knife. First harvesting was done 90 DAT. The yield of 1 m
2
area within each replicate plot
was multiplied by 10000 to obtain the yield per hectare. Soil from different locations in each vegetable field
was collected at a depth of 0-15 cm using an auger, and composite samples were prepared. The samples were
brought to the laboratory, processed, and reserved accordingly.
2.2 Analytical methods for soil and vegetable samples
Soil pH, EC, vegetable minerals and heavy metal determination were done following the standard methods
(Table 1).
2.3 Statistical analysis
Data from the 15 independent composite samples (5 locations × 3 true replicate plots) were subjected to
statistical validation. Significant mean differences among the sampling locations were calculated by performing
Analysis of Variance (ANOVA) based on the RCBD design and Tukey HSD Post-Hoc test. Moreover, the data were
subjected to Principal Component Analysis (PCA) for assessing the contribution of principal components to the
total variability of the dataset and Pearson correlation analysis for identifying the associations among the
variables using the statistical software R.
Table 1: Analytical Methods and Instruments Used for Soil and Vegetable Samples
Parameter
Extraction method/ Reagent
Instrument
Reference
Vegetable
Soil
pH
-
1:2.5 (Soil: Distilled
water)
pH meter
[18]
EC (dSm
-1)
-
1:5 (Soil: Distilled water)
EC meter
[19]
OM (%)
-
As directed by Walkley
and Black
-
[20]
N (%)
-
Kjeldahl method
Kheldahl apparatus
[21]
P (mg kg
-1
)
Di-acid mixture
(HNO
3
:HCIO
4
=2:1)
0.5M NaHCO
3
solution (pH
8.5)
Spectrophotometer
[18,22]
K and Na (mg kg
-1
)
Di-acid mixture
(HNO
3
:HCIO
4
=2:1)
1N NH
4
OAc
(pH 7.0)
Flame emission
spectrophotometer
[23]
Ca and Mg (mg kg
-1
)
Di-acid mixture
(HNO
3
:HCIO
4
=2:1)
1N NH
4
OAc
(pH 7.0)
Complexometric titration
[24]
S (mg kg
-1
)
Di-acid mixture
(HNO
3
:HCIO
4
=2:1)
CaCl
2
(0.15%)
Spectrophotometer
[25]
B (mg kg
-1
)
-
Azomethine-H method
Spectrophotometer
[26]
Zn, Cu, Fe, Mn (mg kg
-1
)
Di-acid mixture
(HNO
3
:HCIO
4
=2:1)
DTPA Extraction (for soil
Zn)
Atomic Absorption
Spectrophotometer (AAS)
[27,28]
*Note: EC = electrical conductivity, OM = Organic matter
3. Results and discussion
3.1 Soil pH and EC values
The average EC level of soil in Dumki, Nauvanga, Pakhimara, Kumirmara, and Sawdagarpara was 0.82, 5.90,
6.82, 7.64, and 9.31 dSm
-1
, respectively. The raising of EC level happened because of salinity. The closer we get
to the coastal area, the higher the soil salinity (Fig. 1). This finding is in line with previous research that has
reported higher soil salinity levels in coastal areas.
[29]
The mean EC value of all the soil samples was significantly
different (p < 0.001).
Fig. 1: Soil pH and EC values at different locations in Patuakhali and Barguna districts.
The average soil pH of the study area was 7.31, 5.72, 5.66, 5.52, and 6.91 in Dumki, Nauvanga, Pakhimara,
Kumirmara, and Sawdagarpara, respectively (Fig. 1). The negative relationship between soil pH and EC levels
in the form of a power function, rather than a linear relationship, is due to the complex interplay of various
factors such as soil minerals, porosity, texture, moisture, and temperature.
[30]
The mean pH of all the soil
samples from different locations varied significantly. Except for the difference (p < 0.01) between Nauvanga
and Pakhimara, all other differences were significant at 1% level of confidence (p < 0.001). The observed high
EC levels and low pH values in some study areas could negatively impact soil quality and agricultural
productivity. Salinity can affect plant growth and yield by reducing water uptake and increasing toxic ion
concentrations in the soil. Excessive accumulation of sodium in cell walls can rapidly lead to osmotic stress and
cell death.
[31]
Similarly, soil acidity can limit the availability of essential nutrients for plant growth and can also
result in the leaching of aluminum and other toxic elements.
[32]
3.2 Elemental concentration of soil samples
As shown in Table 2, soil organic matter and ionic constituents varied across the five sampling locations in the
Patuakhali and Barguna districts. Because electrical conductivity (EC) co-varies with these site-specific soil
properties, geographic location acts as a confounding factor. Consequently, variations in plant parameters are
interpreted as being associated with the cumulative soil environment across the EC gradient, rather than being
attributed solely to an isolated salinity effect.
Table 2: Mean ionic constituents (P, K, Ca, Mg, and S) of different soils of vegetable fields at Patuakhali and Barguna
districts
SL
No.
Locations
pH
EC
(dSm⁻¹)
OM
(%)
N
(%)
P
K
Ca
Mg
S
Zn
B
mg kg
-1
01
Dumki
7.31
0.82
2.1
0.11
27.86
198.9
1214.0
388.0
65.01
0.8
0.4
02
Nauvanga
5.72
5.90
1.75
0.09
18.32
171.6
1624.0
452.4
68.92
0.97
0.38
03
Pakhimara
5.66
6.82
1.68
0.08
16.45
174.1
1856.0
499.0
71.84
0.9
0.47
04
Kumirmara
5.52
7.64
1.52
0.08
14.76
210.6
1999.5
573.6
80.98
1.1
0.39
05
Sawdagarpara
6.91
9.31
1.46
0.07
12.93
149.0
1740.0
522.0
102.33
0.88
0.41
Range
5.52-
7.31
0.82-
9.31
1.46-
2.1
0.07-
0.11
12.93-
27.86
149.0-
210.6
1214.0-
1999.5
452.4-
573.6
65.01-
102.33
0.8-
1.1
0.38-
0.47
The concentration of different elements in the soil sample is shown in Table 2. Organic matter (OM) was in low
to medium range at all the sites, ranging from 1.46% (Sawdagarpara) to 2.10% (Dumki) and generally declining
from Dumki to Sawdagarpara. This indicates moderate depletion of the soil generally encountered in coastal
soils under intensive cultivation. N had a similar trend to OM (0.07–0.11%) and it was very low to low at all
stations. Highest amount of N was found in the soil of Dumki and the lowest was in Sawdagarpara. Phosphorus
varied between sites from 12.93 to 27.86 mg kg
-1
. Dumki had the highest amount, with twice the phosphorus
found in Sawdagarpara, which had the lowest. The trend is similar to that observed at lower salinity and near-
neutral pH in Dumki, where the same conditions are expected to favor better phosphorus retention and
availability in the soil. Potassium ranged from 149.0 to 210.6 mg kg
-1
, with the highest concentration in
Kumirmara (210.6 mg kg
-1
), followed closely by Dumki (198.9 mg kg
-1
), which does not show the same trend as
seen for phosphorus. Sawdagarpara once again recorded the lowest potassium value at 149.0 mg kg
-1
, followed
by comparatively lower values for the primary macronutrients at this site. Calcium was, in fact, by far the most
abundant of the five nutrients measured, with levels ranging from 1214.0 to 1999.5 mg kg
-1
, many times higher
than those of the other nutrients. In contrast to pH and salinity, Dumki, with the healthiest pH and lowest
salinity, actually had the lowest calcium content (1214.0 mg kg
-1
). The highest calcium concentration was
observed in Kumirmara (1999.5 mg kg
-1
). This means that at the more saline sites, the soils are gaining calcium,
likely from the same saline water sources, while the less saline soils are losing salinity. The pattern for
magnesium was remarkably similar to that of calcium. The range of concentrations was 388.0-573.6 mg kg
-1
,
with Nauvanga (452.4 mg kg
-1
), Pakhimara (499.0 mg kg
-1
), and Sawdagarpara (522.0 mg kg
-1
) in between.
Again, the lowest salinity site (Dumki) had lower levels of magnesium, and the higher salinity sites had
increasing magnesium levels - reinforcing the notion that there is a strong relationship between saline intrusion
in this coastal region and increased concentrations of secondary nutrients. The sulfur concentrations ranged
from 65.01 to 102.33 mg kg
-1
and followed the same trend as salinity, increasing with salinity across the sites.
The lowest (65.01 mg kg
-1
) and highest (102.33 mg kg
-1
) values of sulfur contents were observed in Dumki and
Sawdagarpara, respectively. The trend of increase in sulfur content observed from Dumki to Nauvanga,
Pakhimara, Kumirmara, and Sawdagarpara was similar to that of EC, Ca, and Mg. Zinc was greater than 0.6 mg
kg
-1
the critical deficiency level, from 0.80 mg kg
-1
(Dumki) to 1.10 mg kg
-1
(Kumirmara) indicating adequate
availability of Zn in the study sites.
[33]
Boron level ranged from 0.38 mg kg⁻¹ (Nauvanga) to 0.47 mg kg⁻¹
(Pakhimara) which is above the critical level of 0.20 mg kg⁻¹.
[33]
This shows that Zn and B fertilization was not
urgent for crop cultivation during the study period.
3.3 Yield of cabbage
The average yield of cabbage in Dumki, Nauvanga, Pakhimara, Kumirmara, and Sawdagarpara was 60.5, 58.0,
56.77, 55.0, and 52.0 t ha
-1
, respectively. The yield was obtained higher from Dumki to Sawdagarpara because
of high organic matter, and other nutrients (Table 2) (Fig. 2). Similarly, a remarkable decrease in the yield from
26.9 to 9.6 t ha
−1
and from 15.8 to 4.9 t ha
−1
in cauliflower and broccoli, respectively occurred as the electrical
conductivity of the saturated-soil extract (EC
e
) increased from 2.0 dS m
−1
(NSC) to 6.0 dS m
−1
(S4) in research
conducted by Pascale et al., 2005.
[34]
A significant mean difference in cabbage yield was observed across all
locations except Nauvanga and Pakhimara. As the study was conducted in single season and limited locations,
the result obtained here might be changed due to variation of locations and seasons.
Fig 2: Yield of cabbage at different locations in Patuakhali and Barguna districts.
3.4 Phosphorus and potassium concentration in cabbage
Phosphorus and Potassium concentration in cabbage in Dumki, Nauvanga, Pakhimara, Kumirmara, and
Sawdagarpara were 5540.4, 6399, 5275.2, 5022, 3795.67, and 26052.3, 22151, 23062.7, 24000.7, 19166.7 mg
kg
-1
, respectively. Phosphorus concentration was highest in Nauvanga at EC level 5.90 dSm
-1
, and Potassium
concentration was highest in Dumki at EC level 0.82 dSm
-1
(Fig. 3). Adhikari et al. (2023) treated romaine lettuce
with different doses of NaCl solutions and observed almost similar results to this experiment.
[35]
Tukey’s post
hoc comparisons showed a significant difference (p < 0.001) for P among all the locations. Homeostasis of macro
and micro-elements, particularly in white cabbage and kale, was not disturbed significantly at low to moderate
salinity, while the K level did not decrease significantly, and Ca was even increased in white cabbage. Salinity
may elicit phytochemical accumulation in selected vegetables grown on saline soils without undesirable
disruption of macro- and microelement homeostasis, depending on salt concentration and variety.
[36]
Mean K
also exhibited significant variations (p < 0.001) among the sampling locations, like P.
Fig. 3: Concentration of P and K in cabbage at different locations in Patuakhali and Barguna districts.
3.5 Calcium and Magnesium concentration in cabbage
Calcium and Magnesium concentration in cabbage in Dumki, Nauvanga, Pakhimara, Kumirmara, and
Sawdagarpara were 3682.33, 4283, 4321.67, 4371.67, 3038.33, and 1876, 2563.33, 2783.67, 2791, 2660.67 mg
kg
-1
, respectively. Calcium and Magnesium concentration were highest in Kumirmara at EC level 7.64 dSm
-1
because of high OM content (Fig. 4). Faruk-E-Azam et al. (2018) reported that lower Ca and Mg were found in
most vegetables collected from saline areas of southern Bangladesh and they also stated that a high EC does not
always reduce tissue Ca or Mg if the saline soil is also rich in high concentrations of those nutrients.
[37]
This
supports the findings of this study. The mean Ca of Pakhimara and Kumirmara differed at the 5% confidence
level, with a p-value of 0.039. But Nauvanga and Pakhimar did not show any significant difference for Ca. All
other mean differences were significant at 1% level. The mean Mg content of Sawdagarpara varied significantly
with both Pakhimara and Kumirmara at the 1% level (p < 0.01), and with Nauvanga at the 5% level (p < 0.05).
All other differences were significant at the 0.01% confidence level (p < 0.001). Under salinity stress, major
elements Ca, K, and Mg were not significantly affected in the more salt-tolerant kale and white cabbage, and
only significantly reduced by salinity in Chinese cabbage, a more sensitive cultivar.
[38]
The nutrient content of
microelements varied among species.
Fig. 4: Concentration of Ca and Mg in cabbage at different locations in Patuakhali and Barguna districts.
3.6 Sulfur and Sodium concentration in cabbage
Sulfur and Sodium concentrations in cabbage in Dumki, Nauvanga, Pakhimara, Kumirmara, and Sawdagarpara
were 3636.67, 3838, 4763.33, 4794, 3612.33, and 9890.7, 10758, 11396.3, 11587, 10918.7 mg kg
-1
,
respectively. Sulfur and Sodium concentrations were highest in Kumirmara at EC level 7.64 dSm
-1
because of
high OM content (Fig. 5). As per Ferreira et al. (2020), Na content in ‘Raccoon’, shoot increased approximately
2.1-fold at low K and 5.2-fold at adequate K content when two spinach cultivars (‘Raccoon’ and ‘Gazelle’) were
treated with 5–120 mM NaCl solutions.
[39]
On the other hand, sulfur was found to decrease by about 31% in
‘Raccoon’ and 16–21% in ‘Gazelle’ as salinity increased. Sulfate-rich salinity can increase plant S content,
whereas NaCl salinity may reduce S concentration through dilution, impaired sulfate uptake, or nutrient
imbalance.
[39]
All the mean differences for S were significant (p < 0.001), except for the insignificant differences
between Dumki – Sawdagarpara and Pakhimara – Kumirmara. On the other hand, the mean Na content in
cabbage varied significantly for most of the sampling locations. Mean value did not differ only between
Nauvanga and Sawdagarpara.
Fig. 5: Concentration of S and Na in cabbage at different locations in Patuakhali and Barguna districts.
3.7 Zinc and iron concentration in cabbage
Zinc and iron concentrations in cabbage in Dumki, Nauvanga, Pakhimara, Kumirmara, and Sawdagarpara were
27.87, 39.07, 38.07, 37.13, 19.9, and 92.6, 45.4, 184.33, 170.33, 138.53 mg kg
-1
, respectively. Zinc concentration
was highest in Nauvanga at EC level 5.90 dSm
-1
, and Iron concentration was highest in Pakhimara at EC level
6.83 dSm-1 (Fig. 6). Unlike macronutrients, micronutrients did not show many differences among the sampling
locations. Kumirmara, Nauvanga, and Pakhimara did not show any significant differences in Zn. Sawdagarpara
and Dumki differed significantly from all other locations. In the case of Fe, only one mean difference between
Pakhimara and Kumirmara was insignificant. All other differences varied significantly (p < 0.001).
Micronutrient and sodium contents in cabbage shoots reduced with the increase in NaCl concentration, while
increasing the Fe2
+
content by 46.5%, that of Zn
2+
by 19.9%, that of Mn2
+
by 37.7%, and that of Na by 40.8%. It
was observed that increasing the SO
4
2−dose. Similarly, increasing SO4
2−
increased the contents of Cu
2+
, Mn
2+
,
and Na
+
in the shoot by 79.7, 9.5, and 33.8%, respectively.
[40]
Fig. 6: Concentration of Zn and Fe in cabbage at different locations in Patuakhali and Barguna districts.
3.8 Copper and Manganese concentration in cabbage
Copper and Manganese concentration in cabbage in Dumki, Nauvanga, Pakhimara, Kumirmara, and
Sawdagarpara were 5.23, 8.93, 6.07, 6.2, 5.6, and 20.3, 21.8, 35.7, 24.33, 21.73 mg kg
-1
, respectively. Copper
concentration was highest in Nauvanga at an EC of 5.90 dSm-1, and Manganese concentration was highest in
Pakhimara at an EC of 6.83 dSm-1 (Fig. 7). In the case of Cu, Nauvanga showed a notable and significant
difference from all other sampling locations. Besides, Dumki showed a significant difference (p < 0.05) from
Kumirmara. All other differences were statistically insignificant. Mean content of Mn did not show much
significant variation across the sampling sites. Only the mean value for Pakhimara differed significantly from
those of the other locations. T. ciliata was highly affected by salinity for its mineral, proximate, antinutrient, and
phytochemical composition. The flower buds and leaves treated with control and 50 mM contained significantly
higher amounts of macro and micronutrients compared to the other treatments, with the exception of the heavy
metals (Zn and Cu), which increased with rising salinity, and were considerably greater in the roots. Higher
moisture and N content were found at low salinity, while higher ash content in leaves was recorded under high
salinity.
[41]
Fig. 7: Concentration of Cu and Mn in cabbage at different locations in Patuakhali and Barguna districts.
3.9 Principal component analysis (PCA)
Results of principal component analysis are shown in Fig. 8. PCA was conducted using individual replicate
observations. The first principal component accounts for 43.8% of the dataset's variability, and the second
principal component accounts for 35.1%. Almost all the data points formed distinct clusters, except for
Pakhimara and Kumirmara, which were in the same cluster, indicating they are similar to each other. Among
the variables, EC, Mg, Na, Zn, and Ca had a strong positive contribution to PC1, and on the other hand, pH, EC,
Fe, Mn, and Na exerted a strong positive contribution to PC2 (Table 3). Correlations among EC, Fe, Mg, and Na;
Mn and S; Cu, Zn, and Ca; and yield, K, and P were positive. The variable pH stood apart from the other variables
and had an almost opposite direction (180°) to most of the variables, except yield and K. This means that pH
had a negative correlation with most of the variables.
Fig 8: Principal Component Analysis (PCA) of the parameters.
Table 3: PCA Loadings for PC1 and PC2
Variables
PC1
PC2
pH
-0.358
0.214
EC
0.320
0.264
Yield
-0.221
-0.379
P
-0.067
-0.450
K
-0.135
-0.341
Ca
0.215
-0.398
Mg
0.399
0.098
S
0.349
-0.159
Na
0.413
0.041
Zn
0.202
-0.390
Cu
0.084
-0.216
Fe
0.275
0.143
Mn
0.275
-0.089
3.10 Analysis of the correlation coefficient
The heatmap in Fig. 9 shows the Pearson correlation matrix of the analyzed variables, where blue color
indicates positive and red indicates a negative correlation. Replicate samples (n=15) were used for correlation
analysis. Yield showed a very strong positive correlation with K (r= 0.81, p < 0.001) and P (r= 0.83, p < 0.001).
Similarly, P exerted a positive correlation with both Ca (r= 0.73, p < 0.01) and Zn (r= 0.73, p < 0.01). Sulfur had
a positive correlation with Ca (r= 0.74, p < 0.01), Na (r= 0.82, p < 0.001), Mn (r= 0.70, p < 0.01), and Fe (r= 0.72,
p < 0.01). Among all the associations, Zn vs Ca had the strongest correlation (r = 0.94, p < 0.001). On the other
hand, pH showed a negative correlation with almost all variables except yield and K. This finding is consistent
with the PCA results. Notable negative associations of pH were observed with Ca (r= -0.84, p < 0.001), Zn (r= -
0.82, p < 0.001), Mg (r= -0.77, p < 0.001), Na (r= -0.81, p < 0.001), and S (r= -0.79, p < 0.001). Besides, EC had a
strong negative correlation with yield (r= -0.90, p < 0.001) and K (r= -0.82, p < 0.001). The variables EC, Mg, Na,
Mn, S, Fe, and K, yield, P, Cu, Ca, Zn formed two separate blue color clusters in the heatmap exhibiting close
positive relations among the cluster elements. This observation also supports the results of the PCA
determination.
Fig. 9: Heatmap showing the degree of correlation among the parameters
*Note: * p < 0.05, ** p < 0.01, *** < 0.001
4. Study limitations
Although this study successfully assessed the effects of varying soil salinity levels on cabbage yield and mineral
concentration in selected coastal areas of Bangladesh, its findings are limited by the evaluation of a single crop
season, a limited number of locations, and the absence of detailed physiological, soil quality, and economic
analyses. Further multi-season, multi-location, and controlled studies are necessary to validate the results and
develop robust recommendations for sustainable cabbage production in saline environments.
5. Conclusions
The EC levels of Dumki, Nauvanga, Pakhimara, Kumirmara in Patuakhali district, and Sawdagarpara in Barguna
district were 0.82, 5.90, 6.82, 7.64, and 9.31 dSm
-1
, respectively. Across these five coastal study locations,
cabbage yield declined with increasing soil EC and was strongly negatively correlated with EC, while mineral
accumulation showed element-specific responses. Moderate-EC locations maintained relatively high yields and
concentrations of several mineral nutrients, whereas the highest-EC location generally showed reduced yield
and several mineral concentrations. Moreover, cabbage yield showed a strong positive correlation with P and
K. The elevated concentrations of K and Na observed in cabbage tissues reflect the complex elemental uptake
dynamics across these coastal production systems. The trend in mineral concentration was K > Na > P > S > Mg
> Ca > Fe > Zn > Mn > Cu. Therefore, these findings indicate the potential for cabbage production in moderately
saline coastal environments; however, controlled multi-season experiments are required to establish salinity
tolerance thresholds and separate salinity effects from site-specific soil and management factors.
Acknowledgement
The authors would like to acknowledge the use of Grammarly Premium (Grammarly Inc., San Francisco, CA,
USA) for assistance with English language editing, grammar correction, spelling improvement, punctuation
refinement, sentence structure enhancement, and the identification of typographical errors during the
preparation of this manuscript.
CRediT Author Contribution Statement
Mohammad Ghani Miah: Formal analysis, Investigation, Methodology, Writing - Review & editing. A.K.M.
Faruk-E-Azam: Conceptualization, Formal analysis, Investigation, Methodology, Supervision, Visualization,
Validation, Writing - Original draft, Writing - Review & editing. Md. Nizam Uddin: Conceptualization,
Visualization, Writing - Original draft. Muhammad Maniruzzaman: Methodology, Visualization, Writing -
Original draft, Writing - Review & editing. Md Shariful Islam: Data curation, Formal analysis, Software, Writing
- Review & editing. Abdullah-Al-Zabir: Formal analysis, Investigation, Methodology, Visualization, Writing -
Review & editing. All authors have read and approved the final version of the manuscript for publication and
agree to be accountable for all aspects of the work, ensuring that questions related to the accuracy or integrity
of any part of the work are appropriately investigated and resolved.
Funding Declaration
This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-
profit sectors.
Data Availability Statement
The datasets generated and/or analyzed during the current study that support the findings are available from
the corresponding author upon reasonable request.
Conflict of Interest
There is no conflict of interest.
Artificial Intelligence (AI) Use Disclosure
The authors declare that artificial intelligence (AI)-assisted tools were used only for language refinement,
grammar improvement, and manuscript structuring purposes during the preparation of this work. All technical
content, experimental implementation, results, and interpretations were independently developed and verified
by the authors.
Supporting Information
Not applicable.
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