Water SA 49(1) 64–72 / Jan 2023
https://doi.org/10.17159/wsa/2023.v49.i1.3988

Research paper

ISSN (online) 1816-7950 
Available on website https://www.watersa.net

64

CORRESPONDENCE
FB Lewu

EMAIL
LewuF@cput.ac.za

DATES
Received: 9 March 2022
Accepted: 4 January 2023

KEY WORDS
honeybush
proline content
relative water content
tea plant
water deficit stress

COPYRIGHT
© The Author(s)
Published under a Creative 
Commons Attribution 4.0 
International Licence 
(CC BY 4.0)

Cyclopia, generally known as honeybush, and belonging to the Fabaceae family, originates from the Cape 
Floristic Region of the Eastern Cape and Western Cape provinces of South Africa. Currently, 6 honeybush 
species are commercially cultivated but, to date, there have been limited trials attempting to study their 
agronomic water demand. A pot trial was conducted where Cyclopia subternata plants were cultivated on 
different soil types (Stellenbosch granite, Stellenbosch shale and Stellenbosch clovelly) and subjected to 
three different water-deficit stress levels (well-watered, semi-stressed and stressed). Remarkably, irrigation 
treatments and soil types did not significantly affect the growth of the plants. However, the well-watered 
treatment consistently had higher yields compared to the other two treatments. The water-stressed  
(semi-stressed and stressed) treatments had lower relative water contents (RWC) with higher concen- 
trations of proline, which signify water stress, compared to the control treatment. Higher proline and lower 
RWC contents found in this study are indications of water stress.

Cyclopia subternata growth, yield, proline and relative water content in response 
to water deficit stress
MS Mahlare1, MN Lewu2, FB Lewu1 and C Bester2

1Department of Agriculture, Faculty of Applied Sciences, Cape Peninsula University of Technology, Private Bag X8, Wellington 7654, 
South Africa
2ARC Infruitec-Nietvoorbij, Private Bag X5026, Stellenbosch 7599, South Africa

INTRODUCTION

South Africa, a drought-prone country, is home to rooibos (Aspalathus linearis), bush (Athrixia 
phylicoides) and honeybush (Cyclopia species) teas (Joubert et al., 2011). The teas are sold as 
either black or green (fermented or unfermented, respectively) (Horn, 2019). Even though the 
commercialization of some of these remedial teas is still in its infancy stage, honeybush has gained 
recognition, while rooibos is the most well-known and well established in the industry (Van Wyk and 
Gericke, 2000; Joubert et al., 2008; Joubert et al., 2011).

Studies state that these South African indigenous tea species have essential nutrients (iron, calcium, 
magnesium, copper, and potassium) that can improve wellbeing and/or prevent diseases, and 
have economic potential (Rampedi and Olivier 2005; McGaw et al., 2007). These herbal teas are 
famous for their rich caffeine-free and organic antioxidant properties, which are helpful in colon, 
throat and lung illnesses, prevention of urinary stone and tooth caries and other medical problems  
(Soni et al., 2015).

The demand for honeybush tea has prompted concerns of over-exploitation of natural populations 
of the Cyclopia species. The increased rate of wild harvesting diminishes the natural population, thus 
making the exploitation of Cyclopia species unsustainable. Harvesting practices have contributed 
to the decrease and even disappearance of populations of the wild Cyclopia species (Du Toit et al., 
1998). Other factors threatening the growth of the honeybush industry include drought and veld 
fires. To ensure sustainable production, commercial honeybush plantations have been established  
(Joubert et al., 2011).

Commercial production is therefore becoming increasingly important to save the natural populations 
from decline while ensuring consistent supply. Cultivation of Cyclopia species will not only 
contribute to sustainability and conservation of the species but will also improve the livelihoods of 
rural harvester communities. Although cultivated honeybush plants receive water through irrigation 
in addition to rainfall, irrigation volume is at the discretion of farmers, without any understanding 
of the water requirements of the species. Presently, the shortage of water has massively increased in 
some parts of the world, including some regions in South Africa, due to a variety of reasons such 
as an ever-increasing population, industrialization, water pollution and poor management, climate 
change and others (WWAP, 2012; Connor, 2015; Long and Pijanowski, 2017).

In addition, the South African Department of Water and Sanitation (DWS) has reduced agricultural 
allocations significantly, and irrigation volume for the agricultural sector is unlikely to increase 
anytime soon. For example, in 2015, DWS restricted an irrigation water allocation in KwaZulu-Natal 
by 40–100% due to a water shortage caused by insufficient rain (RSA, 2015). Also, agriculture in the 
Western Cape has had to cut its water use by 60% since 2017 (WWF, 2018). As a result, research that 
focuses on the sustainability of water-use in agriculture is gaining huge interest (Velasco-Muñoz  
et al., 2018). Environmental factors, including water stress, tend to interfere with crucial physiological 
processes and biochemical mechanisms; resulting in yield loss (Per et al., 2017).

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65Water SA 49(1) 64–72 / Jan 2023
https://doi.org/10.17159/wsa/2023.v49.i1.3988

Therefore, research on water-use and the effects of stress on plant 
growth is crucial for production sustainability in agriculture 
(Harb et al., 2010). Plants have proven to use protective 
mechanisms such as proline and carbohydrate accumulation to 
cope with water-deficit situations (Mabizela, 2020). Proline is a 
water-soluble amino acid and beneficial solute that accumulates 
in plants under different kinds of stresses, such as drought, cold, 
heat, heavy metal, nutrient, and salt stress (Siddique and Dubey, 
2017).

Relative water content (RWC) is a useful measure of plant water 
status in terms of the physiological consequences of cellular water 
deficit and may indicate the degree of water stress expressed under 
drought and heat stress (Surendar et al., 2013; Soltys-Kalina et al., 
2016). It combines leaf water potential and the effect of osmotic 
regulation to quantify plant water status (Lugojan and Ciulcas, 
2011; Kardile et al., 2018). Insufficient water in plants due to stress 
results in low RWC (Chakhchar et al., 2015).

A plant’s ability to retain turgor during water-deficit periods 
guarantees smooth metabolic processes for growth (Čereković 
et al., 2013). Several studies have stated that RWC determination 
is an efficient method of assessing drought tolerance and plant 
water status (Slabbert and Krüger, 2004; Li-Ping et al., 2006; 
Jones, 2007; Obidiegwu et al., 2015). To date, limited studies 
have been conducted to investigate the water needs of Cyclopia 
species. Therefore, the aim of this study was to evaluate the effects 
of 3 different irrigation treatments on growth, yield, proline 
and relative water content of Cyclopia subternata species of  
honeybush.

METHODS AND MATERIALS

Experimental site and layout

A greenhouse pot trial was conducted at the Agricultural Research 
Council (ARC), Infruitec-Nietvoorbij (latitude −33.914395° and 
longitude 18.861390°) in Stellenbosch, South Africa, to determine 
the effect of water stress on C. subternata. The experiment was 
conducted for 140 days (from end-July to mid-December 2020). 
The experimental design was a randomised block design (RBD) 
with 9 treatment combinations (irrigation x soil type) replicated 
at random in each of 4 block replicates. The treatment structure 
was a 3 x 3 factorial with 3 irrigation levels (well-watered, semi-
stressed and stressed) and 3 soil types (Stellenbosch granite, 
Stellenbosch shale and Stellenbosch clovelly).

Soil collection, preparation, and planting

Soil collection was carried out from three different sites at the 
ARC Nietvoorbij research farm. For each site, soil samples were 
collected from the 0–30 cm soil depth, sieved with a 3 mm sieve 
to remove large fragments, followed by baseline physicochemical 
analysis of the composited samples at a commercial laboratory 
(Bemlab, Strand). 14 kg of soil was weighed into a 30 cm plastic 
pot, using a digital scale. The soil in each pot was irrigated to 
pot capacity (PC) before planting. Nine-month-old honeybush  
(C. subternata) seedlings were transplanted to one plant per pot. 
The plants were well-watered for 5 weeks to ensure good estab-
lishment before introducing the different irrigation treatments.

Irrigation and weed control

From the 6th week after transplanting (WAT), C. subternata 
plants were subjected to 3 different irrigation treatments for 105 
days (September–December 2020). The well-watered treatment 
(control) received 500 mL of water 3 times a week, semi-stressed 
received the same quantity of water twice a week while the stressed 
treatment received 500 mL of water once a week until the end 

of the study. The plants were hand irrigated with an Erlenmeyer 
flask. Weeds that emerged in the pots during the trial period were 
mostly broad-leaved plants. The weeds were either hand-pulled 
or manually removed using a garden fork immediately after 
irrigation when the soil was still wet.

Data collection

Growth parameters

Measurement of growth parameters commenced at 6 WAT on a 
monthly basis, until the trial was terminated in December 2020. 
Plant height was measured from the soil surface to the tip of the 
longest shoot, using a tape measure, stem diameter was measured 
with a digital Vernier caliper while the stem circumference 
was calculated from stem diameter values using the following  
formula:

                C = πd   (1)

where π = 3.14 and d = diameter

Total yield (shoot and root biomass)

At the end of the study (20 WAT), the above-ground biomass 
(shoot) was cut just above the soil surface using a pruning shear, 
placed in a labelled paper bag and then weighed using a sensitive 
weighing balance to obtain the fresh mass of the shoot. The fresh 
shoot was oven-dried at 70°C for 24 h. The dried samples were 
also weighed and recorded using a sensitive digital scale to 4 
decimal places. The root biomass was determined by washing 
plant roots from each pot under running water using a 0.053 mm 
sieve in order to separate the roots from the soil and prevent 
loss of fine roots. The washed roots were air-dried overnight and 
weighed using a sensitive scale. Total plant yield is the combined 
fresh weight of the above-ground biomass and the air-dried root 
biomass.

Estimation of proline content using the colorimetric 
method

Determination of the proline content of C. subternata commenced 
at 6 WAT using the modified method of Ábrahám et al. (2010). 
Leaf samples were collected at 2-week intervals during the growth 
period. The extraction procedure was done by crushing 0.1 g 
of fresh frozen leaves in 0.5 mL of 3% sulfosalicylic acid (w/v), 
using a plastic test tube and pestle. The homogenised extracts 
were centrifuged for 5 min at a speed of 13 500 r/min. A reaction 
mixture of 0.1 mL of 3% sulphosalicylic acid, 0.2 mL of glacial 
acetic acid, 0.2 mL of acid ninhydrin buffer (1.25 g ninhydrin, 
30 mL glacial acetic acid, and 20 mL of 6 M phosphoric acid) 
and 0.1 mL of centrifuged sample extract was made in a test 
tube with a pipette. The mixture was boiled for 30 min at 100°C 
then terminated in an ice bath at room temperature. After 
complete cooling, 1 mL of toluene was added to the mixture 
and mixed thoroughly, then placed on the bench for 5 min to 
allow separation of chromophore. The absorbance was read at 
520 nm on the UV-visible spectrophotometer (Ultrospec 2100 
pro, Amersham Biosciences, Waltham MA, USA) with a 10 mm 
quartz glass cuvette. From the proline standard curve, the proline 
concentrations of the C. subternata samples were determined. 
Proline content was calculated using the formula:

                    Proline content (mmoles/g)
proline (mg

�
//mL)  toluene (mL)

sample mass (g)
�

�
115 5

5
.

        (2)

where 115.5 = molecular mass of proline



66Water SA 49(1) 64–72 / Jan 2023
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Determination of relative water content (RWC)

An improved version of the method of Sade et al. (2015) was used 
to determine the RWC of C. subternata leaves. Leaf samples were 
collected fortnightly at midday (12:00) where 5 top-most leaves 
per plant were collected, cut into two halves and immediately 
stored in pre-weighed, labelled glass vials to minimize humidity 
or vapour loss. The samples were preserved on ice during 
sampling and quickly transported to the laboratory for RWC 
determination. Fresh weight (FW) of each sample was determined 
using a sensitive weighing scale. 2 mL of distilled water was added 
to each vial, kept in a dark cupboard at room temperature for  
4 h to facilitate re-hydration. Thereafter, the turgid leaf samples 
were removed from the vials and slightly blotted with a paper 
towel to remove excess water. The blotted leaves were weighed to 
determine the turgid weight (TW) and later oven-dried at 70°C 
for 48 h. The dried samples were later weighed to determine the 
dry weight (DW). Relative water content was calculated using the 
formula shown below:

RWC
FW DW
TW DW

�
�
�

�
( )
( )

100                             (3)

Statistical analysis

Data were analysed with the randomised block factorial ANOVA 
using SAS statistical software (version 9.4, SAS Institute Inc., 
Cary, NC, USA, 2013). ANOVA was used for each observation 
time (harvest/month) separately, as well as with time as sub-
plot factor (Little, 1972). The Shapiro-Wilk test was utilized in 
testing for deviation from normality (Shapiro, 1965). Fisher’s least 
significant difference was calculated at the 5% level to compare 
treatment means (Ott, 1998). A probability level of 5% was 
considered significant for all tests.

RESULTS AND DISCUSSION

Physical and chemical characteristics of the soils

The results of the baseline physicochemical analysis of the soils on 
which the C. subternata plants were grown are shown in Tables 1 

and 2. Stellenbosch granite soil had the highest coarse sand levels 
(0.5–2 mm) while the lowest was found in Stellenbosch shale. 
Stellenbosch clovelly had more clay content, with Stellenbosch 
granite having the lowest (Table 1). The textural classes for 
Stellenbosch granite, Stellenbosch clovelly and Stellenbosch shale 
fall within the coarse sandy loam, fine sandy clay loam and sandy 
clay loam, respectively. Soil pH and other soil nutrients were 
within the range for normal growth of most plants.

Growth parameters

In general, water stress and soil type had no significant influence 
(p > 0.05) on plant height, stem diameter or stem circumference 
throughout the period of the trial (Fig. 1, Table 3). A summary of 
p-values for separate ANOVAs of growth parameters per month 
is presented in Table 4.

When compared to the stressed plants, the well-watered 
(control) treatment had significantly taller plants with greater 
stem circumference in the first sampling month on Stellenbosch 
clovelly soil. Thereafter, growth and development of plants did not 
differ significantly among treatments. The results for the growth 
parameters of C. subternata in this study contrast with the findings 
of Tshikhudo et al. (2019) where plant height, stem diameter 
and the number of leaves of bush tea (Athrixia phylocoides DC). 
increased with increase in rainfall.

Stress experienced by crops during growth has a cumulative 
effect, which ultimately reduces the final biomass production 
(Kamara et al., 2003). This may be the reason why there was 
generally no significant difference in the growth of C. subternata 
grown in this trial while the cumulative effects of water stress were 
only seen in the harvested biomass (Table 5 and Fig. 2). However, 
a study by Habibi (2018) on Aloe vera demonstrated that short-
term water deficit had no significant effect on the leaf biomass. 
The short duration of the present study may be responsible for 
the non-significant differences observed in the growth of both 
the drought-stressed (semi-stressed and stressed) and the well-
watered (control) plants.

Table 1. Baseline physical characteristics of the three types of soil used in the study

Physical characteristics Stellenbosch granite Stellenbosch shale Stellenbosch clovelly

Clay (<0.002 mm) 13 20 23

Silt (0.002–0.02 mm) 17 13 6

Fine sand (0.02–0.2 mm) 33 50 37.8

Medium sand (0.2–0.5 mm) 3 5 13.0

Coarse sand (0.5–2 mm) 35 12 20.4

Stone volume (%) 0.22 7.72 0.00

Soil textural class Coarse sandy loam Fine sandy clay loam Sandy clay loam

Table 2. Baseline chemical composition of the three soil types

Soil type Ex. cations (cmol (+)/kg) Macronutrients pH
(KCl)

Resistance
(Ω)

K
(%)

Ca
(%)

Na
(%)

Mg
(%)

Acid 
saturation (%)

Na K Ca Mg NO3− P NH4+ K

SG 0.14 0.52 4.4 1.6 31.3 23.9 3.2 203 5.3 800 6.97 58.99 1.88 21.45 10.71

SC 0.13 0.52 4.7 1.2 39.7 29.6 3.3 205 5.5 910 7.17 64.82 1.79 16.55 9.67

SS 0.07 0.32 2.8 0.59 10.6 16.9 13.4 124 5.5 1 400 7.59 66.38 1.66 13.99 10.39

SG = Stellenbosch granite; SC = Stellenbosch clovelly; SS = Stellenbosch shale



67Water SA 49(1) 64–72 / Jan 2023
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Figure 1. Effects of different irrigation levels on (A) plant height, (B) stem diameter and (C) stem circumference of C. subternata in different 
months. Means with the same letters are not significantly different (p ≤ 0.05). Whiskers = standard error bars.

Table 3. Mean growth of C. subternata established on three different types of soil at different sampling times

Sampling time Soil type Plant height (cm) Stem diameter (mm) Stem circumference (mm)

1 Stellenbosch granite 17.9083 ± 1.79 a 0.69659 ± 0.10 a 2.2632 ± 0.41 a

Stellenbosch shale 18.4510 ± 1.99 a 0.69737 ± 0.09 a 2.4456 ± 0.63 a

Stellenbosch clovelly 18.6031 ± 1.52 a 0.78639 ± 0.23 a 2.1376 ± 0.39 a

LSD 1.38 0.13 0.36

2 Stellenbosch granite 23.248 ± 2.58 a 1.3674 ± 0.26 a 4.3648 ± 0.54 a

Stellenbosch shale 22.801 ±2.75 a 1.3098 ± 0.25 a 4.3931 ± 0.86 a

Stellenbosch clovelly 23.729 ± 3.45 a 1.4395 ± 0.23 a 4.0709 ± 0.86 a

LSD 2.51 0.22 0.61

3 Stellenbosch granite 26.557 ± 4.54 a 2.7348 ± 0.52 a 8.8084 ± 1.12 a

Stellenbosch shale 25.897 ± 3.75 a 2.6197 ± 0.50 a 8.6203 ± 1.66 a

Stellenbosch clovelly 26.515 ± 5.61 a 2.8529± 0.41 a 8.3426 ± 1.71 a

LSD 4.25 0.43 1.22

There is no significant difference (p ≥ 0.05) among treatments per sampling time. N = 12; LSD = least significant difference. Data are mean ± standard 
deviation.

Table 4. Summary of p-values for separate ANOVAs of growth parameters per month

Effect Df Plant height Stem diameter Stem circumference

1 2 3 1 2 3 1 2 3

Rep 3 0.6831 0.3165 0.5993 0.1744 0.6363 0.5498 0.1988 0.3037 0.1943

Irrigation 2 0.1358 0.3525 0.7881 0.5454 0.4991 0.4634 0.0084 0.75500 0.8855

Soil 2 0.5587 0.9875 0.9375 0.2916 0.4898 0.5370 0.2335 0.4934 0.7318

Irrigation x soil 4 0.0948 0.6838 0.6838 0.7972 0.7724 0.7989 0.7940 0.0957 0.1535

1, 2, 3 = sampling months; N = 12  



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Yield

The results of the effect of irrigation treatments and soil type 
on the yield of C. subternata are presented in Fig. 2 and Table 5, 
respectively. A summarised presentation of p-values for separate 
ANOVAs on shoot and root biomass is shown in Table 6.

All three irrigation treatments significantly affected the yield 
(fresh and dry shoots) (p ≤ 0.05). Highest shoot and root yields 
were recorded in the control treatment on Stellenbosch shale soil, 
with a progressive yield decline observed with increase in stress 
level. However, there were no significant differences (p > 0.05) in 
the root yield of the well-watered (5.05 g) and the semi-stressed 
(4.33 g) treatments. Stellenbosch clovelly consistently had poor 
shoot and root yields among the three soil types while there were 
no significant differences (p > 0.05) between the biomass yields 
from Stellenbosch granite and Stellenbosch shale.

Eziz et al. (2017) noted that plant growth and biomass production 
generally decrease with decrease in water availability. However, 
plants may behave contrary to this, where the cumulative effect of 
stress during growth may only be visible in the reduced biomass 
yield (Kamara et al., 2003); which was also observed in this study. 

According to Khan et al. (2018), water stress can cause a severe 
reduction in crop yield, and both the severity and duration of the 
stress are critical. Water availability is a key factor for sustainable 
crop production. Its scarcity can have an adverse effect on the 
physiological and biochemical processes of the plants, thereby 
causing low yield. The drought-induced yield (root, fresh and 
dry shoot) decline was comparable to the findings of Zhao  
et al. (2006), who found that there was a severe reduction in the 
fresh and dry weights of Brassica napus under water-limiting 
conditions. Stress at the vegetative stage of plants may lead to 
reduced stomatal conductance, net photosynthesis and yield 
(Kerepesi and Galiba, 2000; Fathi and Tari, 2016). The observed 
yield reduction due to water stress in this study may, therefore, 
be attributed to impairment of physiological and biochemical 
processes like photosynthesis, respiration, translocation, ion 
uptake, and carbohydrate and nutrient metabolism (Ali and 
Anjum, 2016) during growth. During the period of stress, plants 
adopt coping mechanisms such as stomatal closure. However, 
stomatal closure prevents the intake of CO2 into the plant cells, 
thereby interfering with the Calvin cycle, which will eventually 
reduce the potential yield of the crop (Ali and Anjum, 2016).

Figure 2. Effect of diverse water stress levels on the root and shoot biomass of C. subternata. FW = fresh weight; DW = dry weight. Means with the 
same letter are not significantly different (p ≤ 0.05). Whiskers = standard error bars.

Table 5. Effect of different soil types on the yield of C. subternata

Soil type Shoot weight (g) Root weight (g)

Fresh Dry

Stellenbosch granite 14.048 ± 6.20 a 5.0531 ± 2.12 ab 4.3146 ± 1.63 ab

Stellenbosch shale 15.625 ± 7.43 a 6.2229 ± 2.57 a 4.8604 ± 1.37 a

Stellenbosch clovelly 9.022 ± 5.27 b 3.8219 ± 2.03 b 3.6188 ± 1.38 b

LSD 3.41 1.39 0.81

FW = fresh weight; DW = dry weight. N = 12; LSD = least significant difference; means with the same letter are not significantly different (p ≤ 0.05).  
Data are mean ± standard deviation.

Table 6. Summary of p-values for separate ANOVAs on shoot and root biomass

Effect df Shoots (FW) Shoots (DW) Roots

Rep 3 0.7772 0.7974 0.0002

Irrigation 2 <0.0001 <0.0001 0.0013

Soil 2 0.0014 0.0061 0.0145

Irrigation x soil 4 0.3941 0.5658 0.3069

N = 12; FW = fresh weight; DW = dry weight



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Relative water content (RWC)

RWC is the proportion of water in a leaf, expressed as the 
percentage of its maximum volumetric water capacity at full 
turgor (Blum, 2011). It has a direct connection with soil water 
content and is mostly used as an indicant of water stress in plant 
leaves. Changes in leaf RWC due to the different irrigation levels 
in this study are depicted in Fig. 3. At both sampling times, the 
well-watered treatment consistently had significantly higher  
(p ≤ 0.05) RWC (87% and 86%, respectively), while the stressed 
treatment recorded the lowest values (79% and 76% respectively), 
although there was no significant difference between the semi-
stressed (81% and 82%) and the stressed treatments (p > 0.05).

Mabizela (2020) reported similar results, where the stressed 
and semi-stressed plants had lower RWC compared to the well-
watered treatment with the variance showing from the third day 
after stress initiation. The low RWC in the stressed treatment 
indicates a stressed plant population compared with the control. 
Lower RWC in stressed C. subternata leaves used in this study 
is in accordance with the findings of studies on other species 
(Arjenaki et al., 2012; Kabbadj et al., 2017). A study on olives 
supports the outcomes of this research, where the lowest RWC 
values were reported for severely water-stressed olives (Boussadia 
et al., 2008). Higher RWC in plant leaves means that the plants 
had the least water stress, and vice versa.

At the onset of drought, a reduction in stomatal conductance 
can reduce availability of CO2 for photosynthesis, subsequently 
leading to inhibition of underlying biochemical processes such 

as Rubisco carboxylation and electron transport activity, and 
reducing relative water content and even pigment content (Khalil 
et al., 2020). The reduction in the leaf RWC due to the strain 
caused by limited water availability may be attributed to reduction 
in stomatal conductance after stomatal closure in response to 
drought stress. As a result of this, there is an observed decrease 
in the RWC of the stressed C. subternata plants compared to the 
well-watered plants (Boussadia et al., 2008).

For the three soil types, in the first sampling period, there were 
no significant differences in the leaf RWC of C. subternata grown 
on granite and clovelly soil types (p > 0.05). The same observation 
was made for the comparison between granite- and shale-derived 
soils. However, water stress significantly decreased (p ≤ 0.05) the 
relative water content of plants grown in Stellenbosch clovelly 
when compared with Stellenbosch shale (Table 7). In contrast, the 
second sampling time showed no significant differences among 
the treatments. A summary of the p-values for ANOVAs for 
relative water content per period is presented in Table 8.

Soil texture is highly influential for water uptake, and may impede 
root elongation, availability of water, oxygen and nutrients (Khalil 
et al., 2020). The high percentage of clay in clovelly soil may be 
responsible for the low leaf RWC in the first sampling period. High 
clay content in soil increases soil hardness and strength when soil 
is drying out. As soil strength increases, the more difficult it is 
for plant roots to access water and nutrients, hence, the lowest 
RWC in the leaves of C. subternata plants growing on clovelly 
soil. However, in the second sampling period, since this was a 
pot experiment, the packaging of the soil might have altered the 
actual field structure, allowing more macropores in the soils with 
high clay content than is likely to exist in the field (Khalil et al., 
2020). The presence of these macropores may have contributed 
to the non-significant effects observed among all treatments in 
response to the water treatment.

Figure 3. Relative water content of C. subternata in response to three different irrigation treatments at different sampling times. RWC = relative 
water content. Means with the same letter are not significantly different (p ≤ 0.05). Whiskers = standard error bars.

Table 7. Effects of soil type on relative water content of C. subternata 
at different sampling times

Sampling time Soil type RWC (%)

1 Stellenbosch granite 82.766 ± 7.31ab

Stellenbosch shale 86.362 ± 7.66a

Stellenbosch clovelly 78.400 ± 9.81b

LSD 5.16

2 Stellenbosch granite 84.764 ± 8.24a

Stellenbosch shale 80.241± 7.57a

Stellenbosch clovelly 79.450 ± 9.65a

LSD 5.99

RWC = relative water content; N = 12; LSD = least significant difference. 
Means with the same letter are not significantly different (p ≤ 0.05). Data 
are mean ± standard deviation.

Table 8. Summary of p-values for ANOVA of relative water content per 
month

Effect Df RWC (%)

1 2

Rep 3 0.0445 0.4147

Irrigation 2 0.0072 0.0062

Soil 2 0.0145 0.1639

Irrigation x Soil 4 0.0146 0.1311

1, 2 = sampling time; N = 12; RWC = relative water content



70Water SA 49(1) 64–72 / Jan 2023
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Proline

Several abiotic factors, such as water stress, high temperatures 
and salinity, can cause protein modification, membrane injury 
and osmotic stress in plants (Meena et al., 2019). Plants respond 
to water stress by building-up osmolytes such as proline, glycine 
betaine, glycerol and many more, in order to minimize and tolerate 
cell injury (Sharma et al., 2019). Figure 4 shows that the stressed 
C. subternata plants in this study consistently had significantly 
higher proline contents in all sampling periods, while the lowest 
proline content was found in the well-watered (p ≤ 0.05) plants. 
Significantly higher proline content was observed in the stressed 
plants compared to the other two treatments in the first sampling 
period. However, no significant difference was observed among 
all treatments in the second and third sampling periods (p > 0.05).

The obtained results are comparable to those reported by 
Mabizela (2020) on proline contents of C. subternata, where 
proline concentration increased massively in stressed treatments, 
increased slightly in semi-stressed plants, and was constant in 
control treatments. Higher proline content were also reported 
in wheat, Amaranthus species and Achillea species after being 
subjected to water stress (Keyvan, 2010; Slabbert and Krüger, 
2014; Gharibi et al., 2016). Low proline content in plants indicates 
minimum water stress, and vice-versa. The high and significant 
levels of proline that were observed between treatments during 
the third sampling period may be attributed to the plants having 
reached the reproductive stage and having started flowering. 
Proline can accumulate in plants under both stress and non-stress 
conditions, although it is produced at low levels in all tissues in 

unstressed conditions (Kavi Kishor et al., 2015). As a metabolite 
and signal molecule, proline plays a crucial role in the synthesis 
of protein and the response of plant cells to environmental 
stresses (Mattioli et al., 2009). Proline levels may increase during 
wounding and pathogen attack in some tissues, different stages 
of plant growth and development, nodule formation, fertilization, 
cytokinesis, apoptosis, senescence, and cell wall lignification. 
Under normal physiological (un-stressed) conditions, plants 
accumulate high amounts of proline during the transition to 
flower initiation (Kavi Kishor et al., 2015), thus suggesting 
that proline may have a role to play in flower initiation and its 
subsequent development. Soil type did not have any significant 
effect (p > 0.05) on the proline contents of the plants (Table 9). A 
summary of p-values for ANOVAs of the accumulation of proline 
per month is presented in Table 10.

CONCLUSION

From this study, it is evident that different deficit irrigation levels 
and soil type had no significant effects on growth parameters of  
C. subternata. Likewise, soil type had no impact on the proline, 
RWC and the yield of the plants. Water stress increased the proline 
content, resulting in lower RWC. However, deficit irrigation had a 
significant effect on the yield (root, fresh and dry shoot biomass). 
The higher the water stress, the lower the shoot and root biomass 
yield and vice-versa. Although, the well-watered and the semi-
stressed plants gave higher shoot yield, more research is still 
needed to determine the tea quality of the stressed and unstressed 
C. subternata plants.

ACKNOWLEDGMENTS

The Department of Science and Innovation (DSI) of South Africa 
for funding the project; the Department of Higher Learning and 
Training for supporting the study financially through Nurturing 
Emerging Scholars Programme (NESP); the staff of Soil Science 
division, ARC Infruitec-Nietvoorbij for technical support and 
providing their facilities; Dr M van der Rijst for assistance with 
statistical analysis.

Figure 4. Effects of three irrigation levels on proline content of C. subternata at different sampling times. Means with the same letter are not 
significantly different (p ≤ 0.05). Whiskers = standard deviation bars.

Table 9. Proline content of C. subternata cultivated on three different 
types of soil at different sampling times

Sampling time Soil type Proline (µmol/g FW)

1 Stellenbosch granite 25.818 ± 26.42

Stellenbosch shale 21.996 ± 19.42

Stellenbosch clovelly 33.053 ± 26.18

LSD 17.95

2 Stellenbosch granite 24.258 ± 9.89

Stellenbosch shale 22.562 ± 16.08

Stellenbosch clovelly 30.284 ± 19.57

LSD 11.61

3 Stellenbosch granite 37.616 ± 21.31

Stellenbosch shale 31.220 ± 16.90

Stellenbosch clovelly
LSD

39.156 ± 26.20
18.77

There is no significant difference (p ≥ 0.05) among treatments per 
sampling time. N = 12; LSD = least significant difference. Data are mean 
± standard deviation.

Table 10. Summary of p-values for ANOVA of the accumulation of 
proline per period

Effect df Proline (µmol/g FW)

1 2 3

Rep 3 0.0724 0.135 0.2323

Irrigation 2 0.0595 0.0287 0.5083

Soil 2 0.4465 0.3688 0.6566

Irrigation x soil 4 0.3799 0.3793 0.8046

1, 2, 3 = sampling months; N = 12



71Water SA 49(1) 64–72 / Jan 2023
https://doi.org/10.17159/wsa/2023.v49.i1.3988

CONTRIBUTION OF AUTHORS

Mary-Jane Seji Mahlare – data collection, sample analysis, 
writing the initial draft, writing revision; Dr Muinat N Lewu – 
conceptualization, methodology, validation, student supervision, 
writing revision, project leadership, project management; Prof 
Francis B Lewu – conceptualization, methodology, validation, 
writing revision, student supervision; Dr Cecilia Bester – 
conceptualization, methodology, project leadership, project 
management, funding acquisition.

CONFLICT OF INTEREST

The authors declare no conflict of interest.

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