Adopting coffee to climate change: arabica rootstocks enhance physiological performance of robusta under water deficit

Introduction: Drought stress is a critical limitation to robusta coffee (Coffea canephora) cultivation, particularly under prolonged dry seasons and increasing climate variability. Grafting robusta onto arabica (Coffea arabica) rootstocks is a promising strategy to enhance physiological performance under water-limited conditions.

Methods: A three-year nursery study (2020–2023) was conducted at the Central Coffee Research Institute, Karnataka, India, to evaluate the drought response of two robusta scions (S.274 and C×R) grafted onto four tetraploid arabica rootstocks (Sln.6, Sln.9, S.4595 and Sln.5B). The experiment followed a randomized block design with three replications. Physiological and biochemical traits were assessed at before stress, at incipient wilting (9.4% soil moisture) (at stress) and 15 days after rewatering (after alleviation of stress).

Results: The combination S.4595/C×R exhibited the lowest reduction in net photosynthesis (−7.7%) under stress and highest post-stress recovery. Sln.6/C×R and Sln.9/S.274 also performed well, while Sln.5B/C×R maintained stable stomatal conductance and full recovery. S.4595/C×R and Sln.5B/C×R showed minimal decline in intercellular CO_₂, high relative water content (79.63%), and epicuticular wax deposition (29.90 µg/cm^²), indicating enhanced water retention. These grafts also retained higher chlorophyll a and b content and demonstrated superior intrinsic water use efficiency.

Discussion: Arabica-rooted grafts, particularly S.4595/C×R, Sln.5B/C×R and Sln.6/C×R, significantly enhanced physiological tolerance to drought. These combinations offer promising options for developing climate-resilient coffee systems through rootstock-scion interactions, especially under increasing moisture stress scenarios.

Introduction

Coffee is the second most traded commodity worldwide, after petroleum products. It is cultivated in more than 80 tropical and subtropical nations, making a significant economic contribution to each of them. With over 6.5 million tons of green beans produced annually on over 11 million hectares and contributing over $9 billion in international trade, coffee is a highly significant agricultural product (Fabio et al., 2025). Arabica coffee, known for its exceptional quality, accounts for about 70 per cent of global coffee production, while robusta makes up the remaining 30 per cent. The genus Coffea is the most economically significant member of the family Rubiaceae. Commercial coffee cultivation focuses on Coffea arabica (Arabica) and Coffea canephora (Robusta) two economically important species.

Water stress is a major factor limiting growth and development in coffee species. However, there are noticeable differences in their ability to withstand water stress, with robusta exhibiting drought-avoidance traits and arabica having a deeper root structure (DaMatta et al., 2007; Juliet et al. 2018). Genotypic variations in root system efficiency is the key role in drought tolerance and productivity (Somashekhargouda et al., 2025). Grafting studies have demonstrated the significant role of rootstocks in perennial plants. Despite an increase in coffee production in India, particularly in regions with high annual rainfall (above 2,000 mm), drought persists from 3 to 6 months each year (Krishnan, 2017; Rajeevan et al., 2021; Patil et al., 2019). Prolonged drought can lead to floral abnormalities, reducing yields. While irrigation can mitigate drought impacts, most coffee plantations in India lack irrigation facilities. Arabica coffee also responds poorly to irrigation compared to robusta. Breeding drought-tolerant cultivars with higher carbon absorption and water-use efficiency is a potential solution. However, limited progress has been made in breeding drought-tolerant coffee varieties in India and other countries.

Grafting techniques, commonly used in perennial crops, have recently gained prominence over traditional breeding approaches for developing drought-tolerant varieties (Emily et al., 2015; Warschefsky et al., 2016; Albacete et al., 2015; Penella and Calatayud, 2018). The ability of plants to withstand drought depends largely on their genetic makeup. Coffee is a short-day plant where day length and temperature significantly influence growth. Climate change has altered the essential day length by approximately 1 h, and minimum and maximum temperatures have risen by 0.5 °C and 1 °C, respectively. Such changes can affect photosynthesis, which is vital for coffee plant growth, dry matter production, and overall productivity (Rudragouda et al., 2017; Bunn et al., 2015; DaMatta et al., 2007; Moat et al., 2017).

Drought tolerant cultivars achieve high osmotic adjustment by accumulating solutes like free proline, which enhances water-binding capacity, stomatal control, heat stability, water uptake, and cell membrane integrity (Rolli et al., 2015; Kaur and Asthir, 2015; Ma et al., 2018; Farooq et al., 2017). Water stress has been shown to cause significant reductions in gas exchange parameters (Flexas and Medrano, 2020; Zhou et al., 2013; Yordanov et al., 2016). Tolerant genotypes maintain higher mean net photosynthesis and reduce transpiration loss during water stress, enabling quicker recovery.

The physiological basis of drought tolerance in Arabica coffee has been extensively studied, particularly in relation to gas exchange parameters such as mean net photosynthesis, stomatal conductance and intercellular CO₂ concentration. For instance, Dos Santos et al. (2023) emphasized the use of phenotypic plasticity indices to select drought-adapted Arabica genotypes, while another study by Santos et al. (2025) demonstrated genotype-specific anatomical and physiological traits under stress. Menezes-Silva et al. (2017) further highlighted the importance of photosynthetic and metabolic acclimation in improving drought tolerance. These studies underline the relevance of targeting gas exchange traits to evaluate drought responses in coffee, thus validating the approach adopted in the present study.

Hence, this study aimed to identify improved and drought tolerant rootstocks with comprehensive physiological and biochemical evaluations suitable for commercial use under moisture stress conditions, four arabica genotypes have been evaluated as rootstocks with two robusta scions.

Materials and methods

During the 2020–21, 2021–22, and 2022–23 growing seasons, experiment was conducted at the Central Coffee Research Institute, Coffee Research Station, Chikkamagaluru, Karnataka, India (13.22° N latitude, 75.28° E longitude, and 884 m altitude), using different rootstock-scion combinations. The experimental period experienced a mean maximum temperature of 29.6 °C, an average minimum temperature of 18.12 °C, a mean relative humidity of approximately 85 per cent and an average annual rainfall of around 2,838 mm. Daily sunshine duration ranged from 4.5 to 8.7 h, reflecting typical climatic conditions. The soil of the experimental site was deep well drained, very dark brown to red, gravelly loams formed from weathered granite gneiss. Physicochemical properties namely soil reaction slightly acidic (5.9) low in electrical conductivity (0.23 dS/m) and high in organic carbon (2.96). Arabica tetraploid rootstocks with high root biomass and water-use efficiency, including S.4595, Sln.5B, Sln.9, and Sln.6, were used as rootstocks for S.274 and C × R robusta scions. The Arabica rootstocks (S.4595, Sln.5B, Sln.9, and Sln.6) were selected based on prior screening studies that identified these genotypes for their high root biomass, deeper rooting ability and water use efficiency (Patil et al., 2019; Somashekhargouda et al., 2025). These traits were found beneficial for drought tolerance under controlled and field conditions. The Robusta scions (S.274 and C × R) were chosen due to their commercial importance, agronomic adaptability, and moderate drought sensitivity. Root mass was assessed in earlier work using dry weight measurements after 6-month seedling growth under non-stress conditions. Relevant prior findings supporting this selection are reported in Patil et al. (2019). The experiment followed a randomized block design with three replications, set up in a nursery. Grafted coffee seedlings were grown in nursery bags of 35 microns (35 cm × 25 cm) filled with a 6:3:1 ratio of jungle soil, farmyard manure (FYM) and sand. The nursery environment provided 40 per cent daylight with filtered shade, and plants received regular inputs for nourishment and protection following the standard nursery package of operations (Bharali et al., 2017; Almeida et al., 2018). Seeds began germinating 40 days after sowing (DAS) and reached the “button stage” or “butterfly stage” between 50 and 55 DAS. Grafting, performed in May using a wedge-cleft method (Patel et al., 2018) and ensured the desired rootstock-scion combinations. The seedlings were then transplanted into polybags containing sieved jungle soil, FYM, and sand (6:3:1 ratio) and maintained in the nursery until December. The optimum growing average temperature in the glasshouse was 25 °C and RH 92%. To impose soil moisture stress, grafted seedlings (18 months old) of both varieties were maintained under controlled conditions in a glasshouse. Initially, all plants were irrigated adequately to maintain soil moisture at 70% of field capacity (F.C.). This level was maintained by manually applying water through feeder pipes based on pot weight measurements. The use of feeder pipes ensured uniform water distribution within the root zone. Each container, along with the feeder pipe, was weighed at intervals of 3–4 days to determine transpirational water loss. The reduction in weight between measurements was used to estimate water loss, and the lost water was replenished to restore soil moisture to full (100%) field capacity. Water application volumes were calculated using a gravimetric approach described by Patil et al. 2019. The following formula was used to determine the container weight at 70% field capacity (WFC₇₀): WFC₇₀ = X + Y + Q₇₀, where: X = weight of dry soil plus container, Y = combined weight of stone jellies placed on the soil surface and the feeder tube, Q₇₀ = volume of water present in the container at 70% field capacity. Thus, Q₇₀ = WFC₇₀ – (X + Y).

After baseline measurements [before stress/pre-stress (BS)], irrigation was withheld to induce water stress. Observations were recorded at the onset of visible wilting (incipient wilting stage) [at stress (AS)]. The stress was maintained for a period of 15 days. Following this, the seedlings were re-irrigated, and further observations were taken 15 days after complete recovery to assess post-stress responses [after alleviation of stress (AAS)].

Physiological observations, including gas exchange, biochemical and growth parameters, were recorded before stress, during stress (at incipient wilting) and after alleviation of stress (15 days post-recovery). Moisture stress was induced by withholding irrigation, with wilting observed between the 10th and 15th days. Observations were repeated after seedlings were re-irrigated and had fully recovered. The matured leaves, i.e., 4th pair on the primary branch of each seedling used for measuring gas exchange and biochemical parameters. Gas exchange responses, including mean net photosynthesis (P_n), stomatal conductance (g_s), transpiration rate (E) and carboxylation efficiency (P_n/Ci), were measured using a portable photosynthesis and fluorescence system (LI-COR, LI-6400, USA). The leaf chamber settings were consistently maintained throughout the experiment, with a boundary layer resistance of 0.08 m² s mol⁻¹, a gas flow rate of 250 milliliters per minute and an atmospheric CO₂ concentration between 330 and 340 vpm. CO₂ and H₂O calibrations were performed before measurements. Uniform light source of 1,200 u moles/m²/s was provided during observations with chamber temperature of 24 °C and relative humidity at 65 per cent. All gas exchange measurements were taken between 8 and 11 a.m. on bright sunny days. Biochemical responses such as relative water content (RWC) (Barrs and Weatherley, 1962), epicuticular wax content (Baker, 1974) and chlorophyll content (Arnon, 1949) were measured by following standard protocols. Mesophyll efficiency, expressed as the ratio of Ci/g_s, was evaluated (Awati, 2004).

Statistical analysis

The experimental data were analyzed using one-way analysis of variance (ANOVA) with the help of OPSTAT software (version beta) (Field, 2017). To compare treatment means, Tukey’s honestly significant difference (HSD) test was applied as a post-hoc procedure. Critical difference (C.D.) values were determined at both 1 and 5% significance levels to assess the statistical reliability of observed differences.

Before performing ANOVA, the assumptions of data normality and equal variances were evaluated. Normality of residuals was checked using the Shapiro–Wilk test, while homogeneity of variances was assessed through Levene’s test (α = 0.05), performed in R (version 4.3.1) with the car package. The outcomes of these tests, including test statistics and associated p-values, are presented in the supplementary materials as Tables A1, A2 to support the validity of the parametric analysis. To avoid redundancy, detailed values are presented in Tables 1–5 and the key trends have been summarized across physiological and biochemical traits rather than restated in full.

Table 1

Table 1. Influence of net photosynthesis and stomatal conductance on graft combinations under different soil moisture regimes (pooled data 2020–21, 2021–22, and 2022–23) in graft combinations and seedlings.

Table 2

Table 2. Changes in intercellular CO₂ concentration and transpiration rate at different soil moisture regimes (pooled data 2020–21, 2021–22, and 2022–23) in graft combinations and seedlings.

Table 3

Table 3. Changes in carboxylation and instantaneous water use efficiency at different soil moisture regimes (pooled data 2020–21, 2021–22, and 2022–23) in graft combinations and seedlings.

Table 4

Table 4. Changes in relative water and epicuticular wax content on different graft combinations under different soil moisture regimes (pooled data 2020–21, 2021–22, and 2022–23) in graft combinations and seedlings.

Table 5

Table 5. Changes in chlorophyll fractions at different soil moisture regimes (pooled data 2020–21, 2021–22, and 2022–23) in graft combinations and seedlings.

All statistical decisions were based on a significance level of 0.01 and 0.05 unless otherwise stated.

Results and discussion

During the experiment, it was observed that soil moisture fluctuated between 26.9 per cent±0.42 under normal conditions and 9.4 per cent ± 0.48 under stress, showing a reduction of approximately 65 per cent from normal conditions. Physiological parameters were assessed before, during, and after stress alleviation.

Gas exchange responses of graft combinations under drought

The results indicated that under adequate soil moisture conditions, graft combinations such as S.4595/C × R, Sln.5B/C × R, Sln.6/C × R, and Sln.9/S.274 recorded significantly higher intercellular CO₂ concentration, stomatal conductance, mean net photosynthesis, transpiration, intrinsic water-use efficiency, and lower carboxylation efficiency (Tables 1–3). Under enough soil moisture, grafted plants exhibited better mean net photosynthesis than individual plants, but minimal variation observed in stomatal conductance and transpiration rates between the two groups. During periods of soil water deficit, transpiration and stomatal conductance rates were notably higher in non-grafted plants compared to grafted plants.

Among various adaptive strategies for drought tolerance, increasing water-use efficiency for biomass production is a particularly relevant mechanism (Blum, 2015; Condon et al., 2019; Da Costa et al., 2021; Hamerlynck et al., 2000). Different genotypes exhibit distinct physiological pathways associated with drought tolerance. Therefore, factors such as water-use efficiency, photosynthetic rate, stomatal conductance and relative water content under various water stress conditions must be considered when screening genotypes for tolerance to drought (Tombesi et al., 2015; Seleiman et al., 2021). Rootstocks significantly influence the size, shape, and vigor of the scion, with notable effects on leaf physiology, including photosynthesis and related parameters (Warschefsky et al., 2016; Basu et al., 2016; Chaves and Oliveira, 2004).

In all combinations, there was a clear reduction in photosynthesis when stress is applied, with most combinations showing a decrease trend in mean net photosynthesis ranging from ~15% to ~55%. Among the graft combinations, S.4595/C × R shows the smallest decline of mean net photosynthesis under stress (−7.7%), demonstrated t strong drought tolerance. After stress alleviation, many combinations show some level of recovery, but it rarely returns to pre-stress levels. The recovery was more pronounced in combinations like Sln.6/C × R, Sln.5B/S.274, and Sln.5B/C × R. The highest mean mean net photosynthesis seen in Sln.5B/C × R (8.51 ± 0.2 μmoles/m²/s), indicating a robust photosynthetic capacity before, during and after stress (Table 1 and Figure 1A). Similar results were also observed by Georg and Lianhong, 2015 saying that gross photosynthesis is a key term in plant biology. The lowest mean net photosynthesis is observed in C × R (5.40 ± 0.13 μmoles/m²/s), reflecting a more limited response across all stages. Similar patterns of reduced photosynthesis and improved recovery in tolerant Arabica genotypes have been reported under water deficit (Dos Santos et al. 2023; Menezes-Silva et al., 2017; Chandra et al., 2011), supporting the validity of using gas exchange traits as key indicators of stress response in Coffea species.

Figure 1

Figure 1. (A) Net photosynthesis (P_n) and (B) stomatal conductance (g_s) of various graft combinations and seedling genotypes measured under stress (AS) and after alleviation of stress (AAS). Bars represent mean values ± standard error (SE). Red bars correspond to measurements taken during stress conditions, while teal bars represent post-stress recovery. Several graft combinations, particularly those involving Sln.5B/C × R, Sln.9/S.274 and S.4595/C × R, exhibited higher P_n and g_s values under stress and rapid recovery after stress alleviation, indicating improved physiological tolerance. P_n is expressed in μμmol m⁻² s⁻¹ and g_s in mol m⁻² s⁻¹.

The response to stress and the ability to recover vary between different seedling/graft combinations. Some combinations exhibit tolerance under stress and show a quick recovery, while others suffer more significant reductions that are harder to reverse. The combination of S.4595/CxR and Sln.5B/C × R stands out for its overall high photosynthetic activity, while C × R shows a more moderate performance.

The stomatal conductance among the graft combinations, Sln.5B/C × R (BS − 0.054 ± 0.001 moles/m²/s, AS − 0.043 ± 0.001 moles/m²/s, and 0.054 ± 0.001 moles/m²/s) shows minimal reduction in stomatal conductance during stress and complete recovery after alleviation, reflecting strong tolerance and post stress recovery capacity (Table 1 and Figure 1B). Song et al. (2020) reported that for accurately recognizing the degree of crop drought and formulating counter measures in Maize, change from stomatal limitations (SL) to non-stomatal limitations (NSL) of photosynthesis and their critical conditions is vital. Further, S.4595/C × R shows high tolerance, with a smaller reduction in stomatal conductance and better recovery (Table 1 and Figure 1). This combination appears quite resilient to stress. Overall, combinations like S.4595/C × R and Sln.5B/C × R are more resilient to stress and have relatively high mean stomatal conductance even under stress conditions. Enhancing photosynthetic efficiency during stress remains a key strategy for improving drought tolerance (Patil et al., 2019). Strong positive correlation (0.734, p < 0.01), suggesting that higher stomatal conductance is associated with enhanced photosynthetic activity (Table 6). Wataru et al. (2020) reported that a close correlation between steady-state photosynthetic rate and stomatal conductance was noticed in rice under various environmental conditions. The strong positive correlation observed between stomatal conductance (g_s) and mean net photosynthesis (P_n) reflects the close physiological relationship between stomatal behaviour and carbon assimilation under drought. Stomatal opening regulates CO₂ diffusion into the leaf; therefore, reductions in g_s directly limit the availability of CO₂ for the Calvin cycle, resulting in lower P_n. Under water deficit, partial stomatal closure is a protective mechanism to reduce transpiration, but this also restricts internal CO₂ concentration (Ci), reducing photosynthetic electron transport and carboxylation efficiency.

Table 6

Table 6. Correlation between gas exchange and biochemical parameters.

In drought-tolerant combinations, higher g_s under stress suggests better maintenance of leaf water status and hydraulic conductance, enabling sustained CO₂ uptake and supporting higher P_n. This coordinated response indicates that stomatal regulation is a key determinant of photosynthetic performance and drought resilience in these graft combinations.

Among the graft combinations S.4595/C × R (AS − 210 ± 5.12 ppm, AAS − 254 ± 6.20 ppm) and Sln.5B/C × R (AS − 241 ± 5.88 ppm, AAS- 251 ± 6.13 ppm) demonstrated better tolerance to stress with minimal decreases in intercellular CO₂ concentration (Ci) during stress and higher recovery after stress alleviation (Table 2). A decline in intercellular CO₂ concentration (Ci) can substantially affect the efficiency of photosynthesis by altering various biochemical mechanisms, such as the activity of Rubisco, regulation of stomatal function, and the assimilation of carbon. These effects are especially pronounced under abiotic stress conditions like drought and salinity (Flexas et al., 2016; Bhardwaj et al., 2021; Das et al., 1999). These combinations are among the more resilient to stress, with a higher mean Ci than many other combinations. The graft combinations, Sln.5B/S.274 and S.4595/C × R show moderate declines in transpiration during stress and manage to recover well and have strong recovery potential (Table 2). Intercellular CO₂ concentration (Ci) showed moderate positive correlation (0.651, p < 0.05) with mean net photosynthesis, indicating that photosynthetic performance is related to the plant’s capacity for carbon fixation (Table 6) (Suman et al., 2011).

Further, Sln.6/C × R, Sln.5B/C × R, and S.4595/CxR show relatively high stability and moderate reduction in carboxylation efficiency during stress. These combinations exhibit moderate tolerance to stress and show a good recovery post-stress. Among the grafts, S.4595/CxR, Sln.5B/C × R, and Sln.6/C × R stand out with the highest IWUE values under stress conditions, demonstrating excellent water use efficiency (Table 3). Intrinsic Water Use Efficiency showed moderate positive correlation (0.622, p < 0.05) (Table 6), suggesting that higher photosynthesis is associated with better water use efficiency (James, 2019). Bertrand et al. (2019) also reported the improved gas exchange parameters in Coffea arabica scions when grafted on Coffea canephora rootstocks. Using drought-tolerant rootstocks with high carbon exchange rates and water-use efficiency combined with commercially important scion materials appears to be an effective strategy for addressing drought challenges and increasing coffee yield (Lemos et al., 2018; Silva et al., 2016; Bounce, 2019). Very strong positive correlation (0.811, p < 0.01), reflecting a close link between photosynthesis and CO₂ concentration in the intercellular spaces (Table 6).

Two key physiological traits that regulate water-use efficiency are photosynthetic rate (P_n) and transpiration rate (E), which are fundamental leaf functions. These results corroborate prior work by Silva et al. (2016) and Da Costa et al. (2021). Additionally, certain Coffea arabica rootstocks have been reported to enhance carbon uptake in arabica scions (Freschi, 2016; Yamori et al., 2020). Mean net photosynthesis is highly correlated with Chl a, Intercellular CO₂ and stomatal conductance, indicating that these factors likely play a critical role in the plant’s overall photosynthetic efficiency (Matos et al., 2020; Flexas et al., 2004) (Table 6).

The graft combinations S.4595/C × R and Sln.5B/C × R consistently maintained higher mean net photosynthesis (P_n), stomatal conductance (g_s) and intrinsic water use efficiency (IWUE) during drought stress, reflecting efficient coordination between carbon assimilation and water conservation. These combinations also showed more stable internal CO₂ concentration (Ci) and better recovery after rehydration, indicating superior stomatal control and hydraulic regulation under stress. Collectively, these physiological traits highlight their stronger drought tolerance compared to the other graft combinations.

Biochemical responses of graft combinations under drought

There is a noticeable decline in relative water content (RWC) after stress (AS) for all combinations, followed by some recovery after stress alleviation (AAS). Combinations with C × R as the rootstock generally showed higher RWC at all stages compared to those with S.274. High relative water content (79.63% ± 1.94) and epicuticular wax content (28.90 ± 0.71 μg/cm²) recorded in S.4595/C × R followed by Sln.9/S.274 (78.36 ± 1.91% & 28.64 ± 0.70 μg/cm²) and Sln.5B/C × R (78.82 ± 1.92% & 26.77 ± 0.65 μg/cm²) during stress condition (Table 4). This suggests that the wax layer plays a role in preventing water loss and improving tolerance to stress and showed positive correlation (Shepherd and Griffiths, 2016; Kosma et al., 2018; Laskos et al., 2021). The accumulation of water and wax content in leaves under stress conditions serves as an essential criterion for evaluating drought tolerance. This accumulation increases leaf thickness, reduces leaf area and enhances leaf turgidity, thereby aiding plants in coping with stress conditions (Camila Medeiros et al., 2017; Tattini et al., 2015; Adhikari and Baniya, 2020; Wohlfahrt and Gu, 2015). Further, epicuticular wax shows strong correlations with chlorophyll ‘a’ and Mean net photosynthesis, suggesting a potential relationship between leaf surface properties and photosynthetic activity (Zhang et al., 2021) (Table 6). Kamila et al. (2021) showed similar kind of the correlation between the wax components and the content of photosynthetic pigments and tocopherols in rye, whose biosynthesis, similarly to the biosynthesis of wax precursors, is mainly located in chloroplasts. Further, Lee and Suh (2015) stated that drought stress induces MYB94 gene, which activates wax biosynthesis genes, thereby reducing water loss and enhancing abiotic stress tolerance in the plant. Similarly, SnRK2.6 and SnRK2.3 upregulate wax biosynthesis genes, linking ABA signaling to physiological drought protection via enhanced cuticular wax production (Fan et al., 2015).

Chlorophylls a and b are essential components of the light-harvesting complex, directly involved in the capture of solar energy and excitation of electrons in photosystems I and II during photosynthesis. Under drought stress, chlorophyll degradation is a common response due to oxidative damage or downregulation of pigment biosynthesis. Therefore, retention of chlorophyll content under stress conditions is an important indicator of physiological stability and drought tolerance (Nounjan et al., 2020; Zhou et al., 2013). Combinations with C × R rootstock, such as S.4595/C × R, Sln.6/C × R, and Sln.5B/C × R, consistently exhibited higher chlorophyll ‘a’ content both before and after stress. These combinations showed better stress tolerance and chlorophyll retention under stress conditions. Combinations grafted onto S.274, such as Sln.6/S.274 and Sln.9/S.274, showed relatively lower chlorophyll content (Table 5 and Figure 2A). This suggests that S.274 rootstock may not be as effective in maintaining chlorophyll levels during stress. The S.4595/C × R combination demonstrated the most robust recovery, with chlorophyll levels almost returning to pre-stress levels after stress alleviation (Figure 2). This indicates strong tolerance and an ability to cope with stress. Sln.6/C × R also showed good recovery, with a relatively small drop from pre-stress levels, suggesting this combination is well-suited for environments where stress may be alleviated over time. Similar results observed by Noppawan et al. (2020) in rice where chlorophyll retention and high photosynthesis contribute to drought tolerance. The combinations with C × R rootstock, particularly S.4595/C × R, Sln.6/C × R, and Sln.5B/C × R, are recommended for environments where stress and subsequent recovery are common, as they showed the best chlorophyll retention and recovery. Sln.5B/C × R exhibited the highest chlorophyll ‘b’ content across all three stages, with notable values at BS = 0.72 ± 0.018 mg/g fr.wt, AS = 1.22 ± 0.030 mg/g fr.wt, and AAS = 0.92 ± 0.022 mg/g fr.wt (Table 5 and Figure 2B). It showed a significant increase in chlorophyll ‘b’ content after stress, highlighting its ability to adapt to stress conditions by producing more chlorophyll. S.4595/C × R is another combination that performed well, especially during stress alleviation (AAS), maintaining 0.89 ± 0.022 mg/g fr.wt. The content increased from 0.74 ± 0.018 mg/g fr.wt (BS) to 1.09 ± 0.027 mg/g fr.wt (AS), and showed a slight decline after alleviation, but still retained good chlorophyll content (Table 5 and Figure 2). Overall, Sln.5B/C × R and S.4595/C × R showed the most impressive adaptive responses to stress, with significant increases in chlorophyll ‘b’ content after stress exposure. These combinations should be considered for environments where stress tolerance and recovery are key. The increase in chlorophyll ‘b’ content during stress observed in several combinations, especially those with C × R rootstock, might reflect an adaptive strategy, where plants increase chlorophyll synthesis to maximize photosynthesis under challenging conditions (Patil et al., 2019; Petite et al., 2000). S.4595/C × R and Sln.5B/C × R are the top performers in both chlorophyll ‘a’ and chlorophyll ‘b’ content, showing excellent stress tolerance and recovery after stress alleviation (Table 5). Additionally, maximum chlorophyll ‘b’ content emerged as a crucial parameter for assessing graft combinations under drought stress (Patil et al., 2019).

Figure 2

Figure 2. (A) Chlorophyll ‘a’ and (B) chlorophyll ‘b’ content (mg/g fresh weight) in different graft combinations and seedling lines under stress (AS) and after alleviation of stress (AAS). Bars represent mean ± standard error (SE). Orange and green indicate stress and recovery phases, respectively. Combinations such as Sln.5B/C × R, Sln.6/C × R, and S.4595/C × R demonstrated better retention and rebound of chlorophyll pigments, indicating enhanced tolerance to water stress through improved pigment stability and recovery.

The higher chlorophyll a and b content in C × R rooted grafts compared to S.274-rooted combinations suggests more stable pigment retention and sustained photosynthetic capacity under drought. This may be due to more efficient osmotic regulation and antioxidant activity, which protects the chloroplasts from oxidative stress during water deficit.

Multivariate analysis of physiological and biochemical traits under drought stress

Principal component analysis (PCA) was employed to examine the complex interactions among physiological and biochemical traits across graft combinations and drought stress stages. The first two principal components (PC1 and PC2) explained 78.3% of the total variance, with PC1 accounting for 61.2% and PC2 17.1% (Figure 3). The PCA biplot showed a clear separation of samples based on stress stages before stress (BS), at stress (AS) and after alleviation of stress (AAS) indicating dynamic trait responses to water deficit. Key traits contributing to variation included net photosynthetic rate (P_n), intrinsic water use efficiency (IWUE) and epicuticular wax content, which loaded strongly on PC1. Chlorophyll a and b also contributed to PC2, highlighting their role in stress stage specific variation (Figure 3). Grafts exposed to stress (AS) were distinctly separated from non-stressed (BS) and post-recovery (AAS) groups, emphasizing the impact of drought on physiological function. These results are consistent with previous reports that PCA can effectively reduce dimensionality and identify key physiological traits related to drought tolerance (Rani et al., 2022; Flexas et al., 2004). The positioning of certain grafts along the positive axis of PC1 suggests enhanced drought tolerance through improved gas exchange, osmotic adjustment and biochemical protection mechanisms. This multivariate analysis underscores the utility of PCA in identifying trait combinations that contribute to drought adaptation in coffee, supporting its application in selection strategies for stress-resilient rootstock scion combinations (Araujo et al., 2020; Matta et al., 2008). Graft combinations S.4595/C × R and Sln.5B/C × R clustered in the positive quadrant of PC1, closely associated with traits such as P_n, IWUE, and wax content. This clustering reflects their superior physiological adaptation to drought stress, while combinations with S.274 aligned negatively, indicating weak trait expression under stress. High IWUE reflects better water use regulation, epicuticular wax reduces non-stomatal water loss and stable P_n ensures continued carbon assimilation under limited water. These traits collectively form a coordinated drought-tolerance mechanism in the top-performing combinations.

Figure 3

Figure 3. Principal component analysis (PCA) biplot illustrating the distribution of graft combinations under different drought stress stages based on physiological and biochemical traits. The first two principal components (Dim1 and Dim2) explain 78.3% of the total variance (61.2 and 17.1%, respectively). Each point represents a graft combination at a specific stress stage before stress (BS), at stress (AS), or after alleviation of stress (AAS) colored by stage and enclosed within 95% confidence ellipses. Arrows indicate the direction and magnitude of trait contributions, with longer vectors representing traits with stronger influence on principal component separation. Traits such as photosynthetic rate (P_n), intrinsic water use efficiency (IWUE), wax content, and chlorophyll levels (Chl a, Chl b) were major contributors to PC1 and PC2, effectively distinguishing drought response patterns among graft combinations.

To analyse and rationalise the effects of drought stress on physiological and biochemical traits in grafted coffee plants, conducted one-way ANOVA followed by Tukey’s HSD post-hoc comparisons across three stages viz., before stress (BS), at stress (AS) and after alleviation of stress (AAS) (Figure 4). Significant differences (p < 0.05) were found across most traits (Figure 4). Net photosynthetic rate (P_n) and stomatal conductance (g_s) declined significantly at AS, indicative of stomatal closure and reduced carbon assimilation under water-limited conditions. However, intrinsic water use efficiency (IWUE) was significantly elevated during AS, likely due to reduced g_s with relatively sustained P_n. Relative water content (RWC) decreased markedly at AS but showed partial recovery during AAS. Epicuticular wax content increased under AS, likely functioning as a drought avoidance mechanism by minimizing cuticular water loss. Both chlorophyll a and b declined at AS and showed signs of recovery under AAS, suggesting pigment degradation and partial re-synthesis in response to stress and rehydration. Intercellular CO₂ concentration (Ci) decreased under AS, consistent with stomatal limitation to gas exchange (Figure 4). These results align with prior findings that drought stress triggers coordinated physiological and biochemical adjustments in coffee, many of which show tolerance or reversibility depending on genotype and rootstock–scion interaction (DaMatta et al., 2007).

Figure 4

Figure 4. Boxplots showing the effects of drought stress stages before stress (BS), at stress (AS), and after alleviation of stress (AAS) on nine physiological and biochemical traits in grafted coffee plants. Traits include: (A) Net photosynthetic rate (P_n, μmol CO₂ m⁻² s⁻¹), (B) stomatal conductance (g_s, mol H₂O m⁻² s⁻¹), (C) intercellular CO₂ concentration (C_i, μmol mol⁻¹), (D) relative water content (RWC, %), (E) intrinsic water use efficiency (IWUE, μmol CO₂ mol⁻¹ H₂O), (F) epicuticular wax content (μg cm⁻²), (G) chlorophyll a (Chl a, mg g⁻¹ FW), and (H) chlorophyll b (Chl b, mg g⁻¹ FW). Different lowercase letters above the boxes indicate statistically significant differences between stages within each trait according to Tukey’s HSD post-hoc test (p < 0.05). Boxes show the interquartile range (IQR), lines indicate medians, and whiskers extend to 1.5 × IQR.

Key physiological traits associated with drought resilience across graft combinations included high IWUE, greater retention of chlorophyll a and b, higher relative water content (RWC), and increased epicuticular wax deposition. These features were most prominent in S.4595/C × R and Sln.5B/C × R, indicating a robust multi-trait strategy for drought adaptation.

Conclusion

This study identified S.4595/C × R, Sln.5B/C × R, Sln.9/S.274, and Sln.6/CxR as superior drought-tolerant rootstock-scion combinations based on lower reductions in P_n, g_s, CE, E, chlorophyll stability and wax accumulation under moisture stress. These combinations demonstrate promising potential for climate-adapted coffee cultivation under water-limited conditions.

Data availability statement

The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.

Author contributions

SP: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Resources, Software, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing. KY: Data curation, Formal analysis, Investigation, Resources, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing. HY: Conceptualization, Data curation, Formal analysis, Investigation, Resources, Software, Supervision, Validation, Writing – original draft, Writing – review & editing. JD: Data curation, Resources, Supervision, Visualization, Writing – original draft, Writing – review & editing. MG: Data curation, Formal analysis, Resources, Supervision, Writing – original draft, Writing – review & editing. CB: Resources, Supervision, Writing – original draft, Writing – review & editing. MS: Resources, Supervision, Writing – original draft, Writing – review & editing.

Funding

The author(s) declared that financial support was not received for this work and/or its publication.

Acknowledgments

The authors gratefully acknowledge the Coffee Board of India and the Central Coffee Research Institute (CCRI), Chikkamagaluru, Karnataka, India for providing the necessary facilities, institutional support and an enabling environment for the preparation of this review. Their continued encouragement and access to resources were instrumental in completing this work.

Conflict of interest

The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Appendix

Table A1

Table A1. Shapiro–Wilk test for normality of physiological parameters under different moisture regimes.

Table A2

Table A2. Levene’s test for homogeneity of variances in physiological parameters under different moisture regimes.