Impact of Heat Wave on the Plant Architecture of Field Grown Jatropha curcas Accession

Heatwave is one of the common phenomena in the arid and semi-arid regions which greatly hinders crop productivity. Jatropha curcas, which is well known for its medicinal and seed biodiesel uses, is one of the crops that are negatively affected by high temperatures. Therefore, this study was aimed at monitoring the effect of a heat wave on the plant architecture of Jatropha curcas plants grown in the south east of Botswana, a semi-arid region. The field experiment was conducted in 2016 (2016/2017) and 2017 (2017/2018) cropping season using plants that were established in 2011. Data on changes in leaf numbers, changes in leaf areas, photosynthetic rates, leaf temperatures, and soluble sugar levels were measured over the spring, summer, and autumn seasons of 2016 and 2017. In 2016, the general trend of the above measured parameters was that they peaked in summer and declined in autumn. However, in the summer of 2017, the accessions were hit by a heat wave, which depressed the photosynthetic rates, concomitantly decreasing leaf numbers, leaf areas, and leaf area indices. This reduction continued into the autumn of 2017. The plant architecture of the J. curcas accessions differed in the two years, indicating that the accessions responded differently under heat waves. The observations made as the plants recovered was that immediately below the apex, 2–3 leafed lateral shoots developed, which would normally be evident much lower down the stem. This suggests that the effect of the heat wave thus appeared to have impacted the plant architecture in the autumn. Soluble sugar levels were also higher in the autumn leaves of 2017 than in the autumn leaves of 2016.

Introduction

Jatropha curcas, a plant belonging to the Euphorbiaceae family, is said to have originated in Meso America. It is now widely grown in tropical regions of Africa, Asia, and Central America [1]. It gained in popularity due to its seeds that are rich in oils used for bio-diesel. However, it also has economic importance in the pharmaceutical and cosmetic industries [2], [3]. Jatropha curcas has been reported to grow in environments of 200 and 1500 mm annual precipitation [4] and in annual precipitation of less than 800 mm in parts of Brazil [5]. Pandey et al. [6] report that in Niger, J. curcas can survive with less than 300 mm annual precipitation. Woody plants in semi-arid and arid regions shed their leaves and twigs at the worst time of the year in an effort to strike a balance between safety and survival [7]. In Botswana, Jatropha curcas is found growing under high temperatures and high light conditions with precipitation that can be as low as 490 mm per annum [8].

The three-dimensional arrangement of a plant’s body is known as its architecture. This refers to the branching pattern, leaf size, shape, and location, as well as other characteristics of the plant’s above-ground components. Plant architecture controls a crop’s vigour, yield, and resistance to pathogens in addition to the form and aesthetics of the individual plants. For this reason, horticultural growers of field and greenhouse crops as well as plant breeders, controlling the establishment of plant designs is crucial to them [9]. Leduc et al. [9] continue to point out that the architecture of plants is strongly influenced by environmental influences. Hence, gaining a deeper comprehension and management of these variables ought to facilitate the enhancement of cultural practices and production while concurrently decreasing the application of chemicals (such as growth retardants and pesticides). There is a greater need to understand how environmental influences manipulate plant architecture [9]

Plants, being sessile creatures, have developed a high degree of environmental adaptability. Temperature signals control the timing of several developmental stages and have a significant impact on biomass and plant morphology [10]. Crops frequently lose their leaves when they are severely stressed by heat. Reduced leaf numbers lessen water loss from the plant through the stomata, stems, and other plant parts. A few buds, blossoms, and developing fruit might drop off. Reduced metabolic rate is another possible plant response to heat stress. The amount of water, salt, proteins, and phytohormones that are present in the cells may need to change under certain situations [11], [12]. Because plants modify their morphology, physiology, and biochemistry in response to heat stress, phenological investigation of these changes can help to more precisely characterize the tolerance qualities at the molecular level [11], [12]. Temperature spikes of more than 5°C above average can occur during brief periods of extreme weather, lasting only a few days. As discovered by Kumudini et al. [13], extreme events that take place in the summer would have the greatest impact on plant productivity. A recent review by Barlow et al. [14] on the effect of temperature extremes, frost, and heat in wheat (Triticum aestivum L.) revealed that frost caused sterility and abortion of formed grains, while excessive heat caused a reduction in grain number and reduced duration of the grain-filling period. Environmental influences on architectural components, including light, have been researched [15]–[17]. They point out that light is the environmental component that most influences plant architecture through its effects on photosynthesis and morphogenesis. It particularly impacts bud bursting and shoot elongation. Controlling the illumination during plant culture may enable the production of plants with unique morphologies. Their results also closely linked bud with sucrose transporting stems under the influence of light. In this study, the growth of Jatropha curcas accessions was monitored over two years, during which the summer leaf temperatures differed significantly. The impact of the high temperatures on the J. curcas accessions in the summer of 2017 was compared with those of the lower temperatures in the summer of 2016, leading to the alteration of the plant architecture of the accessions in their recovery in the autumn season of 2017.

Materials and Methods

Study Site

The study was carried out in an agricultural field located in the former Department of Agricultural Research Ministry of Agriculture at Sebele (25° 56′ 37″ E 24° 3′ 40″ S). It is a semi-arid area with a wide range of diurnal temperatures throughout the year. The average precipitation in this area is below 490 mm annually. Precipitation occurring from October to March accounts for almost 100% of the annual rainfall [8]. Summer temperatures range from 15°C in the morning to over 40°C at midday, and winter temperatures range from 3°C early morning to 25°C in the afternoons. The heat wave occurred in mid-summer of the year 2017 (Fig. 1). The soils are reddish brown and are of the Rendzic Leptosol type. They are poor soils with high aluminum and iron content consisting of silt and clay. The field was established in December 2011 from seeds collected from the local Genetic Seed Bank in Sebele. The Botswana accessions used in this study originated from different regions of the country as follows: Tsamaya from the north, Tabala from the central region and Tlokweng from the South East region. Seeds for the Ghana accession were originally from Ghana.

Fig. 1. Air temperatures in the months/seasons of 2016 and 2017.

Experimental Design and Treatments

The field experiment was laid out in a randomized block design with five replications. The treatments were four J. curcas accessions (Tsamaya, Thabala, Tlokweng, and Ghana) randomly selected from several parts of the country. The accession from Ghana was the control. The experiment was carried out over a period of two years, in 2016, in which there was no heat wave, and in 2017, which had heatwave.

Morphological Measurements of Leaves

Measurements on the total number of leaves per plant and leaf area were taken once a month seasonally as follows: 2016–2017 spring (October and November), summer (December, January, and February), and autumn (March and April) hereafter referred to as 2016; and 2017–2018 -spring (October and November) summer (December January and February) and autumn (March and April) hereafter referred to as 2017.

Assessment of Leaf Numbers

The total number of leaves per plant was counted (five replicates per accession), and the average was used. The percentage changes in the number of leaves per plant were calculated by counting the number of leaves per plant, which was replicated three times and then averaged. This was done for each accession and monthly. The percentage changes were calculated using the month of October as the baseline. where a is the baseline month of October and b represents separately each of the months covered in the seasons of the two years. The monthly percentage changes were then grouped to calculate each season in 2016 and 2017. The percentage changes for 2016 and 2017 were calculated by averaging the months of each year.

$$\begin{array}{r}\mathrm{\%}change=(a-b/a)\times 100\end{array}$$

Assessment of Leaf Areas

Leaf area was determined using the Pompelli et al. [18] method of leaf length and leaf width.

$$\begin{array}{r}LA=(Leaflength\times LeafWidth)=0.9660\end{array}$$

It was a simple, non-costly method to use in the field. This was done for each replicate seasonally and each year of the study. To measure leaf areas the Pompelli et al. [18] method was used as follows: The maximum leaf length (L) (from lamina tip to the point of the petiole intersection to the midrib) and leaf width (W) (the widest linear length perpendicular to the midrib) were measured to the nearest of 0.1 cm. Minimum number of leaves recommended per plant was 415. Leaf areas were calculated for each leaf, and the total per plant was calculated. This was done for each replicate, and the averages were calculated. Each accession had five replicates. This was done each month (October–April) over a three-year period.

The percentage changes in the leaf areas per plant were calculated by using the leaf area per plant as determined above, which was replicated five times and then averaged. This was done for each accession and monthly. The percentage changes were calculated using the month of October as the baseline.

where x is the baseline month of October, and y represents separately each of the months covered in the seasons of the three years. The monthly percentage changes were then grouped to calculate each season in 2016 and 2017. The percentage changes for 2016 and 2017 were calculated by averaging the months of each year.

$$\begin{array}{r}change=(x-y/x)\times 100\end{array}$$

Photosynthetic Parameters Gas Exchange Measurements

Photosynthetic rates (µmol CO₂ m⁻²s⁻¹), leaf temperature (°C), and photosynthetic photon flux density (PPFD) (µmolm⁻²s⁻¹) readings measurements were determined using a portable photosynthesis system (LICOR 6400XT equipped with a LED 2×3 cm leaf chamber, LICOR USA). Photosynthetic rates and leaf temperature measurements were taken once a month seasonally on fully expanded tagged at the 5^th or 6^th node as follows: 2016–2017 spring (October and November), summer (December January, and February), and autumn (March and April) hereafter referred to as 2016; and 2017–2018 spring (October and November) summer (December January and February) and autumn (March and April). Measurements were determined diurnally three times: 600 h–700 h, 1200 h–300 h, and 1700 h–1800 h, and diurnal averages were determined. Each day, measurements were taken on the same leaf. PPFD measurements were determined three times a day at 700 h, 1200 h, and 1800 h.

Soluble Sugar Analysis

Soluble sugar was determined by colorimetric approach according to Dubois et al. [19]. 20 mg of lyophilized leaf material were blended in 4 mL of deionized water and incubated for one hour, and then centrifuged at 3000 × g for 15 min at a temperature of 25 °C. 5 mL of concentrated sulfuric acid, 1 mL of 0.56 M phenol (C6H5OH), and 1 mL of extract were mixed together to create a total volume of 7 mL. The amount of carbohydrates was measured by utilizing d(+) glucose as a standard and measuring the absorbance at 490 nm using a spectrophotometer (UV mini-1240 UV–VIS spectrophotometer, Shimadzu, Tokyo Japan).

Statistical Analysis

All measured variables were analyzed using two-way analysis of variance (ANOVA) using R-Software version 4.2.2 and the agricolae package version 1.3–5. Treatment means effects were compared using Fisher’s least significant difference (LSD) procedure at a significance level of 5%. Pearson’s correlation coefficient was used to test if there were any associations between the measured parameters.

Results

Percentage Changes in Total Leaf Numbers per Plant and Leaf Areas in the Seasons of 2016 and 2017

In 2016, the percentage changes in the total number of leaves and leaf areas were significantly (P ≤ 0.05) higher in summer than in other seasons, while the lowest changes were recorded in the spring season irrespective of plant accession (Figs. 2A and 2C). In contrast, in 2017, the accessions displayed the highest leaf numbers and leaf areas in the spring and declined in the succeeding seasons (Figs. 2B and 2D). In the summer of 2016, the Tlokweng accession displayed higher percentage increases in the leaf numbers and leaf areas than other accessions, while Tsamaya displayed the lowest values (Figs. 2A and 2B). The opposite was true in the summer of 2017, as the Tlokweng accession displayed the least changes in the total number of leaves and leaf areas, while the Tsamaya accession exhibited the highest changes (Figs. 2C and 2D). Generally, in 2017, the accessions displayed significantly lower percentage changes in leaf numbers and areas in summer and autumn compared with the previous year (2016).

Fig. 2. The interaction of season and genotype on percentage changes in leaf numbers 2016 (A) and 2017 (B) and on percentage changes in leaf area in 2016 (C) and 2017 (D). Note: Means followed by the different letters are significant at P ≤ 0.05, according to Fisher LSD. Error bars represent the standard error of the mean. n = 5.

Percentage Changes in Leaf Numbers and Leaf Areas in 2016 and 2017

Fig. 3 shows that the percentage changes in the total number of leaves and leaf areas were significantly higher in 2016 than in 2017, irrespective of plant accession. In 2016, accessions Ghana and Tlokweng exhibited high percentage changes in the total number of leaves and leaf areas, while Tsamaya exhibited the lowest values.

Fig. 3. Percentage changes in leaf areas (A) and leaf numbers (B) in 2016 and 2017. Note: Means followed by the different letters are significant at P ≤ 0.05 according to Fisher LSD. Error bars SEM (n = 5).

Comparison of the Effects of Leaf Temperatures on the Photosynthetic Performance of J. curcas Accessions

The rate of photosynthesis was higher in 2016 than in 2017 (Fig. 4A). In 2016, though the photosynthetic performance of J. curcas accessions in spring and summer differed significantly, the two seasons were not conspicuously different compared to the autumn. The Ghana and Tlokweng accessions displayed higher performances more frequently than the Tsamaya and Tabala accessions over the two years. In 2017, the photosynthetic performance was higher in the spring (Fig. 4A) concomitant with lower leaf temperatures (Fig. 4B). Thereafter, photosynthetic performance continued to decline (Fig. 4A) simultaneous with increasing leaf temperatures (Fig. 4B). The Tabala accession was conspicuous in exhibiting the lowest photosynthetic performances concomitant with the highest leaf temperatures in throughout the two years (Figs. 4A and 4B).

Fig. 4. Comparison of (A) Photosynthetic rates and (B) Leaf temperatures in the seasons of 2016 and 2017. Means followed by the different letters are significant at P ≤ 0.05, according to Fisher LSD. Error bars represent the standard error of the mean. n = 5.

Diurnal Photosynthetic Photon Flux Density in 2016 and 2017

Fig. 5 shows the diurnal variation of the photosynthetic photon flux density (PPFD), with readings peaking at midday and declining towards late afternoon in both 2016 and 2017. At each time and in each year, the PPFD readings differed significantly (P ≤ 0.05).

Fig. 5. Diurnal variation of the photosynthetic photo flux density in 2016 and 2017 J. curcas accessions. Note: Means followed by different letters are significant at P ≤ 0.05 according to Fisher LSD. Bars represent SEM (n = 3).

Total Soluble Sugars

Fig. 6 depicts that the highest soluble sugars were observed in 2016 during autumn. Significantly low soluble sugars were recorded in spring, irrespective of cropping year. Total soluble sugar levels in 2016 peaked in summer and declined in autumn. However, in 2017 the total soluble sugar levels continued to increase into the autumn season. Generally, the total soluble sugars were significantly (P ≤ 0.05) greater in 2017 than in 2016 (Fig. 6).

Fig. 6. Seasonal variation of the total soluble sugar levels in 2016 and 2017 in the J. curcas accessions. Means followed by different letters are significant at P ≤ 0.05 according to Fisher LSD. Bars represent SEM (n = 3).

Comparison of J. curcas Accession in 2016 Season and 2017

Fig. 7A shows the apical shoot of a J. curcas accession in 2016, the year that did not experience a heat wave. Fig. 8B shows both the apical shoot and lateral shoots of a J. curcas accession in the autumn of 2017. The lateral shoot just below the apex had two leaves which was not the case in the 2016 stems.

Fig. 7. Variation of total soluble sugar levels of the various J. curcas accessions in the seasons of 2016 and 2017. Note: Bars represent SEM (n = 3).

Fig. 8. Apical shoots of J. curcas accessions in autumn of 2016 (A) and 2017 (B).

Correlations of Photosynthesis Leaf Numbers and Leaf Areas

Table I shows that photosynthesis positively correlated with leaf area index, changes in total number of leaves per plant and changes in leaf area. Leaf temperature negatively correlated with all the studied parameters. Leaf area index positively correlated with changes in total number of leaves per plant and changes in leaf area (Table I).

Table I. Correlations for Leaf Architecture Parameters

Leaf architecture parameters	Photosynthesis	Leaf temp	Leaf area index	% Changes in leaf no	% Changes in leaf area
Photosynthesis	1
Leaf temp	−0.77	1
Leaf area index	0.64	−0.61	1
% Changes in leaf no	0.74	−0.68	0.96	1
% Changes in leaf area	0.69	−0.67	0.96	0.98	1

Discussion

The results show that in the summer of 2017 leaf temperatures rocketed from 30.05°C in spring to 35.55°C in summer (Fig. 4A), causing changes in the total number of leaves per plant and leaf areas to tumble (Figs. 2 and 3) compared to those in the summer of 2016 that experienced lower temperatures. The leaf temperatures in the summer of 2017 were far above the plant optimum of 25°C reported by Thebud et al. [20] and Hatfield and Prueger [21]. Therefore, a simultaneous reduction in leaf numbers and leaf areas with an increase in leaf temperature confirms that high-temperature stress negatively affects growth and development. This is also highlighted by the negative correlation between leaf temperature and photosynthesis; changes in leaf area and total leaf number show that an increase in leaf temperatures decreases the rates of this parameter (Table I). Parthasarathi et al. [22] report that high temperatures stressed shoots in a variety of ways, causing sunburns, searing of leaves and stems, senescence of leaves, inhibition of roots and shoots, fruit damage, and discoloration, among other morphological signs that ultimately resulted in a reduction in agricultural output. High temperatures can occasionally cause leaves to dry up and roll, sear their edges and tips, and in some circumstances, necrosis has been observed in sugarcane [22], [23]. The results of this study are consistent with Parthasarathi et al. [22], who found that extreme temperatures have a significant impact on the photosynthesis of leaves [22]. The high summer temperatures of 2017 resulted in depressed photosynthetic performance, chlorosis, leaf roll, and leaves senesced prematurely. The impact of the heat wave continued in the autumn season, with the leaf numbers and leaf areas (Figs. 2C and 2D) continuing to decline, displaying no recovery. The continual decline in the autumn of the leaf numbers and leaf areas suggested the magnitude of the damage. Research has recorded many physio-biochemical and molecular processes to be dysfunctional at high temperatures that are above the optimum which is associated with negatively impacting crop development and production [24].

Plants are thought to be permanently damaged by high temperatures [25], [26]. Chaudhary et al. [23] explain that heat stress modifies the anatomical, morphological, and functional characteristics of leaves and flowers as well as the shoot and root structures, branching patterns, leaf surface and orientation, and cellular metabolism and gene expression that normally govern these processes. The modification of the morphological characteristics, including shoot structure, reported by Chaudhary et al. [23], is evident in the accessions change in plant architecture. In their attempt to recover in the autumn of 2017, the accessions displayed several lateral shoots, each having two or three leaves. This had not been observed in accession shoots in the autumn of 2016 or in the spring of both 2016 and 2017, which experienced no heat wave. This observation is in agreement with Bita and Gerats [27], who reported that plant architecture changes point to hypocotyls and petioles elongating, resembling morphological responses of shade avoidance.

The effect of high temperature on the J. curcas accessions suggests that high temperatures triggered hormonal activities. Plant architecture and biomass are significantly impacted by temperature signals, which also control the timing of certain developmental events [10]. Temperature-induced changes in plant architecture appear to require the intricate integration of several hormone signaling networks. On some days, the leaf temperatures of the accessions ranged from 46°C (Tsamaya accession) −49°C (Ghana accession). At first, auxin was believed to be the mediating factor in the apical dominance or the suppression of shoot branching by the expanding shoot tip of plants. Recently, research showing the functions sugars play in encouraging branching has brought attention to the significance of the shoot tip sink strength during apical dominance [28]. Part of the reason for this increasing focus on sugars and sucrose being one of the mobile products of photosynthesis is that whereas changes in sucrose occur quickly, auxin depletion dynamics after decapitation are too sluggish to explain initial bud expansion [29], [30]. In this study, the sugar levels of the accession leaves in 2017 were higher than those in the leaves of the accessions in 2016. This implied that higher temperatures of 2017 caused an increase in the levels of total soluble sugars. Dorado et al. [31] highlighted that the stressed plants experienced significant changes in the primary metabolism of their leaves, which were characterized by a decrease in starch and an increase in soluble sugars, nitrogen, and proline. It has been demonstrated that light is necessary to promote sugar signaling [32], sugar transport [33], and sugar metabolism [34]. The results of this study are in agreement with Rabot et al. [32] as the PPFD in the summer of 2017 was higher, possibly triggering the increase of sugar levels, which continued to increase in the autumn, influencing the change in plant architecture.

During the seasons of 2016, when the air and leaf temperatures were within optimal ranges [21], [35], the Ghana and Tlokweng accessions exhibited lower sugar levels than the Tsamaya and Tabala accessions. However, in the summer of 2017, the sugar levels of the Ghana and Tlokweng accessions increased (Fig. 7) concomitant with increasing air and leaf temperatures (Figs. 1 and 4). This increase in sugar levels of the accessions continued in autumn as the temperatures remained high (Fig. 7) and was associated with the accessions displaying several lateral shoots each having two or three leaves, an apparent change in plant architecture, which had not been observed in the autumn of 2016.

Conclusion

The heat wave that hit the J curcas accessions in the summer of 2017 impacted the accessions, increasing the leaf temperatures and subsequently leading to a decline in leaf number, leaf area, and photosynthesis. The apparent recovery process in the autumn of 2017 was characterized by 2–3 leaved lateral shoots immediately beneath the apex of the accessions, which had not been previously observed in the autumn of 2016. The 2016 terminal shoots of the accession demonstrate the difference in plant architecture between the accessions impacted by heat waves (2017) and those not impacted by heat (2016). The plant architecture varied among the accession in both years, suggesting different responses to heatwaves. It appears that the sugar levels increased triggered by heatwave contributed to the variations in the plant architecture. The Tabala and Tsamaya accessions appeared more heat tolerant than the Ghana and Tlokweng accessions in displaying higher sugar levels.