*3.3. Principal Component Analysis (PCA) for Leaf Gas Exchange and Chlorophyll Fluorescence Traits*

Values of PCA, eigenvalues, percent, and cumulative explained variances are summarised in Table 5. Under NS conditions, seven principal components exhibited eigenvalues > 1 and accounted for 81% of total phenotypic variation. Net CO2 assimilation, Ci, Ci/Ca, *qP*, ETR, ETR /A, AES and YPP were positively correlated with PC1, which accounted for 22% of the total variation. PC2 was positively correlated with gs, *Fo* and *φPSII*, whereas WUEi and WU*Eins* were negatively correlated with PC2, which accounted for 17% of the total variation. Transpiration rate was negatively correlated with PC3, whereas WUE*ins*, *qP* and YPP were positively correlated with PC3, which contributed 11.42% of total variation. A/C*i* positively correlated with PC4 accounted for 10.67% of total variation. PC5 was positively correlated with *Fm* and *Fv* - */Fm*- *,* contributing 8% of total variation, whereas PC6 was positively correlated with Fm- , contributing 7% of total variation.

Similarly, under DS conditions, seven PCs with eigenvalues > 1 were detected, which contributed 80% of the total phenotypic variability. Yield per plant was negatively correlated with PC1, whereas *φPSII*, ETR and ETR/A were positively correlated with PC1, which accounted for 20% of total variation. Transpiration rate, net CO2 assimilation, Ci, WUEi, *Fv* - */Fm*- , *qN* and YPP were positively associated with PC2, accounting for 18% of the total variation. Stomatal conductance and A/Ci were positively correlated with PC3, whereas Ci and WUE*ins* negatively associated with PC3 contributed 14% of the total variation. Net CO2 assimilation and *qN* were positively correlated with PC4, whereas ETR/A was negatively correlated with PC4, accounting for 10% of total variation. Instantaneous water use efficiency was positively correlated with PC5, which accounted for 7% of total variation, whereas stomatal conductance and photochemical quenching were positively correlated with PC6, which contributed 6% of total variation.

Principal component biplots based on PCA analysis were used to indicate the relationships among okra accessions for leaf gas exchange and chlorophyll fluorescence parameters under NS (Figure 1A) and DS (Figure 2B) conditions. Traits presented by parallel vectors or those close to each other revealed a strong positive association, and those located nearly opposite (at 180◦) showed a highly negative association, while the vectors toward sides expressed a weak relationship. Under NS conditions, accessions LS06, LS11, LS22, LS05 and LS20 were grouped based on high *qN*. Accessions LS19, LS17 and LS18 were grouped together based on high gs, T and A/Ci. LS02, LS10 and LS24 were grouped based on high *φPSII*, *Fo*- , *Fv* - */Fm*- , A, ETR, ETR/A, AES and *qP*. Accessions LS25, LS01, LS23 and LS16 were grouped together based on high Ci/Ca, WUE**<sup>i</sup>** and WUE*ins*. Under DS conditions, accessions LS10, LS24, LS25, LS05 and LS06 were clustered together based on high *Fm*- , AES, T, C*<sup>i</sup>* and YPP. LS13, LS15, LS17 and LS09 were grouped together based on high Ci/Ca,

**Figure 1.** Principal component (PC) biplot of PC1 vs. PC2 depicting the relationships among physiological traits among 26 okra accessions evaluated under non-stressed (**A**) and drought-stressed (**B**) conditions.

#### *3.4. Heatmap Analysis for Leaf Gas Exchange and Chlorophyll Fluorescence Traits*

A heatmap based on leaf gas exchange and chlorophyll fluorescence traits under NS and DS conditions was constructed using a hierarchical clustering method to discern the relationship of 26 okra accessions based on Jaccard's coefficient (Figure 2). Under NS (Figure 2A) conditions, physiological traits were grouped into four main clusters. The first cluster consists of two subclusters, dominated by eight accessions, including LS19, LS12, LS06, LS18, LS13, LS07 and LS02, which were grouped based on high negative correlations with WUE*ins*, *qN* and YPP. The second subcluster consisted of accessions LS22, LS11, LS1, LS08, LS20 and LS14, which were negatively correlated with A/Ci and T. LS25, LS01, LS21, LS16, LS24 and LS23 dominated the fourth subcluster under NS conditions and positively

correlated with *qP*. Under DS, physiological traits were grouped into three main clusters and six subclusters. The first cluster is dominated by accessions LS19, LS09, LS03, LS15, LS14 and LS17, based on their positive correlations with ETR and ETR/A. LS26, LS22, LS04, LS20, LS13 and LS11 dominated the second cluster under DS conditions, with positive correlations with WUE*i*, WUE*ins*, *qN* and YPP. AES was positively correlated with LS25 and LS05 in the third cluster under DS conditions.

#### **4. Discussion**

Okra is one of the most important commercial vegetable crops grown for its fresh fruits and dry seeds. Drought is the major impediment to okra production in dry regions. To adapt to drought stress, plants have undergone many biochemical, molecular, and physiological changes. These changes increase the plants' tolerance to drought stress. Drought stress influences plant performance by reducing gas exchange and altering chlorophyll fluorescence formation. Gas exchange and chlorophyll fluorescence confer drought tolerance in okra [11,27]. Plants alter gene expression, disrupting the production of photosynthetic pigments and regulating stomatal function to adapt to and tolerate stress conditions [27]. Developing new strategies for maintaining high yield under drought-stress conditions is one of the major challenges in the current crop production system.

In this study, various physiological drought responses were assessed in okra accessions. Reductions in okra's stomatal conductance and transpiration rates have been associated with water conservation that allows plants to tolerate drought stress and the loss of physiological functions [9]. Stomatal closure leads to a reduction in CO2 assimilation and minimises the rate of water loss through transpiration. This role of drought-induced stomatal closure limits CO2 uptake by the leaves and possibly leads to increased susceptibility to photodamage [11]. Similar findings were reported for okra accessions under water shortages [11,27]. These physiological changes increase the plants' resistance to drought stress, enabling the crop to survive in environments with limited water availability.

Drought tolerance should be considered as a comprehensive evaluation of carbon assimilation during global climate change challenges [28]. In the current study, okra accessions exhibited a reduction in net CO2 assimilation under drought-stressed conditions (Table 4). The decrease in net CO2 assimilation during water-stressed conditions might be reversible initially. However, drought in the pod-filling stage might cause irreversible damage to the photosynthetic pathway, thereby affecting carbon assimilation [29]. Further, utilisation of assimilates is relevant in addition to the photosynthetic performance of leaves. The evaluated okra accessions revealed high water use efficiency under drought-stressed conditions (Table 4). Enhancing water use efficiency to sustain okra production under water-limited conditions remains the most important task for water management. Hence, specific responses for enhancing water use efficiency could be achieved with more precise data on crop stress detection [11]. Drought-tolerant accessions exhibited high WUEi and WUE*ins* compared to drought-susceptible accessions (Table 2). This indicates that the evaluated accessions use water efficiently, attributed to drought escape mechanisms such as the transpiration rate. Drought-tolerant accessions use water efficiently, maintain tissue water status, reduce water loss and produce stable yield during water shortages [30].

Chlorophyll fluorescence is a non-invasive measurement detecting the authenticity of photosystem II [31]. Chlorophyll fluorescence parameters, including photosystem II photochemistry, minimum fluorescence, maximum fluorescence, photochemical quenching and electron transport rate are useful for detecting drought-stress severity, genetic variation and determining damage to *PSII* [32]. *Fv* - */Fm* is considered the most important parameter of chlorophyll fluorescence, widely used to evaluate drought-stress response. In this study, a reduced *Fv* - */Fm* value was recorded under drought-stress conditions, corroborating with results reported by Ahmed and El-Sayed, [27]. According to Paknejad et al. [33], reduced *Fv* - */Fm* under drought-stress conditions indicates the presence of a protective mechanism of light absorption in response to water shortages. Hence, the *Fv* - */Fm* parameter can be applied to determine the potential efficiency of *PSII.*

In the present study, drought-tolerant okra accessions showed an efficient photosynthetic affinity compared to sensitive accessions. Photosystem *II* is highly drought tolerant. However, under drought-stress conditions, photosynthetic electron transport through *PSII* is inhibited [24]. The decrease in *PSII* might be due to the photo-protective increase in thermal energy dissipation induced by the excess of absorbed light [34]. However, there are contradictory reports on the direct effect of *PSII* functionality under drought-stress conditions. A study reported that, under mild water stress, *PSII* is not affected [35], while another study reported that, under drought-stress conditions, damage occurs to both photosystem I and photosystem II [36]. The current study found that *PSII* was significantly affected by drought stress. Under drought-stress conditions, the *PSII* thermal energy dissipation was strongly limited due to damage to *PSII* structure and functionality. A decrease in photochemical quenching was observed in the studied okra accessions under droughtstress conditions. Similar results were reported by Ashraf et al. [37] in the study of gas exchange characteristics and water relations in some elite okra cultivars under water-deficit conditions. The decrease in *qP* is attributable to either a decrease in the rate of consumption of reductants and ATP produced from non-cyclic electron transport relative to the rate of excitation of open *PSII* reaction centres or damage to *PSII* reaction centres [24].

Positive correlations were observed between non-photochemical quenching and intrinsic water use efficiency under drought-stress conditions, indicating a protective mechanism by the plants against reactive oxygen species that harm antenna pigments and closing reactions in the photosystem. Drought stress also affects the electron transport rate (ETR) and alternative electron sink (AES) [38]. An increase in alternative electron sink was observed among the studied okra accessions under drought-stress conditions. Drought-tolerant accessions indicated higher AES values. An increase in AES was reported as an indicator of drought stress [39]. Alternative electron sink is the second most important mechanism after photosynthesis used to remove electrons, which occurs at high rates in the leaves under drought stress conditions [40].

#### **5. Conclusions**

Drought is one of the most important factors affecting physiological traits and yield in crop plants, including okra. In the present study, it was observed that drought stress affected physiological processes such as reduced stomatal conductance, transpiration rate, net carbon dioxide assimilation, maximum quantum efficiency, effective quantum efficiency of *PSII* photochemistry, photochemical quenching and electron transport rate among the studied okra accessions. These physiological traits could be useful for drought-tolerance breeding in okra. Principal component analysis-based biplots allowed the identification of drought-tolerant accessions such as LS05, LS06, LS07 and LS08 based on high A, T, *Fm*- , *Fv*- */Fm* and ETR, and LS10, LS11, LS18 and LS23 based on high *AES*, *Ci*, *Ci/Ca*,*WUEi*, *WUEins*, *φPSII* and AES. The selected genotypes are high yielding (≥5 g/plant) under drought-stress conditions. These accessions are suitable candidates for parental genotypes for drought-tolerance breeding in okra to enhance water use efficiency under waterlimited conditions.

**Author Contributions:** Conceptualisation, S.S.M., H.S. and A.S.G.; methodology, S.S.M.; validation, S.S.M., H.S., A.S.G. and J.M.; formal analysis, S.S.M.; investigation, S.S.M.; resources, H.S. and A.S.G.; data curation, S.S.M.; writing—original draft preparation, S.S.M.; writing—review and editing, S.S.M., H.S., A.S.G. and J.M.; supervision, H.S. and A.S.G.; project administration, S.S.M., H.S. and A.S.G.; funding acquisition, H.S. and A.S.G. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was funded by the National Research Foundation, South Africa, grant number MND200618533646, the Agricultural Research Council through the PDP program, grant number 10013464 and the Moses Kotane Institute, grant number 215041664.

**Institutional Review Board Statement:** Not applicable.

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** Not applicable.

**Acknowledgments:** The University of KwaZulu-Natal is acknowledged for the support of the project, as well as the Agricultural Research Council through the Professional Development Programme for providing plant material, funding and research support. The National Research Foundation, South Africa and Moses Kotane Institute are acknowledged for funding this study.

**Conflicts of Interest:** The authors declare no conflict of interest.

### **References**


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