2.1 Leaf gas exchange and water relations
No significant differences in stomatal conductance (Gs), photosynthetic rate (An), relative water content (RWC) and osmotic potential (Yp) were observed between the three genotypes. Compared to the well-watered controls, drought stress significantly decreased Gs, An, RWC and Yp in all genotypes (Table 2). Genotypes were significantly different for osmotic adjustment (OA) and highest value of osmotic adjustment (OA) was recorded in genotype L2 and lowest in L1 (Table 3).
2.2 Activity of carbohydrate metabolic enzymes in leaf
Activity of leaf vacuolar invertase (vacInv) was significantly different between the three genotypes under control conditions, and the highest activity was recorded in L3 and lowest in L1. Compared to well-watered controls, no significant differences were recorded for the activity of vacInv under drought conditions. All genotypes exhibited similar cytoplasmic invertase (cytInv) activity under control conditions, while drought caused a non-significant increase of cytInv activity. The activity of cell wall invertase (cwInv) was statistically similar among the genotypes, though L3 showed a lower activity than L1 and L2 under control conditions. Drought significantly enhanced the activity of this enzyme in comparison to the well-watered controls. (Table 4).
The activities of AGPase and UGPase were significantly different among the three genotypes where, the lowest activities of both enzymes were noticed in L2 in comparison to the other two genotypes. Compared to the well-watered controls, significant reduction of leaf AGPase activity by drought was observed. Drought did not affect the activity of UGPase. Also, the activity of fructokinase (FK) was significantly different among genotypes where, higher activity was recorded in genotype L3 in relation to the other two genotypes. Drought significantly reduced the activity of FK in comparison to well-watered controls. The activity of hexokinase (HXK) was neither affected by genotype nor by drought; whereas, interaction between water*genotype which was 0.2 to 0.07 nkat g-1 Fw was significant in genotype L2 (Table 4).
Phosphoglucomutase (PGM) activity was statistically similar among the three genotypes Activities of phosphoglucoisomerase (PGI) phosphofructokinase (PFK) varied significantly among three genotypes and highest were recorded in L3 in comparison to other two genotypes. Drought did not affect the activity of PGM, PGI and PFK. Non-significant differences were recorded among genotypes for the activity of aldolase. Compared to well-watered controls, activity of aldolase was reduced significantly under drought (Table 4).
2.3 Activity of carbohydrate metabolic enzymes in spike
The activity of vacInv was significantly different among genotypes and the highest activity was recorded in L3 in relation to L1 and L2. Compared to the well-watered controls, the activity of vacInv was not significantly affected by drought. The activity of cytInv enzymes was significantly different among three genotypes where, higher activity was recorded in L1 in comparison to other two genotypes. Compared to well-watered controls the activity of cytInv was significantly increased under drought. The activity of cwInv was identical among the three genotypes and it was unaffected by drought (Table 4).
Significant differences in the activity of AGPase were found between genotypes and it was highest for L2 in comparison to other two genotypes. No significant effect of drought on the activity of AGPase was noticed. Neither genotype nor drought affected the activity of UGPase significantly. The activities of FK and HXK was significantly varied between the genotypes, where higher activities of these enzyme were found in L2 compared to other two genotypes, and FK activity was not significantly affected by drought (Table 4). In contrast, the activity of HXK was significantly increased under drought as compared to well-watered controls (Table 4).
Differences were significant among genotypes for the activities of PGM and PFK and higher activities were recorded in L1 in comparison to other two genotypes (Table 4). Significant differences for the activity of PGI were noticed among the genotypes and higher activity was recorded in L2. However, activities of PGM and PGI were not significantly affected by drought. Compared to well-watered controls, drought significantly enhanced the activity PFK. Aldolase activity was neither affected by genotypes nor by drought (Table 4).
2.4 Abscisic acid concentration and antioxidants activity in leaf
Leaf ABA concentrations differed significantly among the three genotypes where highest ABA concentration was recorded in L2 compared to other two genotypes. Compared to the well-watered controls, leaf ABA concentration was significantly higher under drought conditions. A significant interaction between water*genotype was also notice for leaf ABA concentration where pronounced effect was recorded in genotype L3 (Table 5).
Neither genotypes nor drought changed the activities of DHAR, MDHAR and GR statistically. Difference were significant among genotypes for GST where, highest activity was recorded in genotype L1 as compared to other two genotypes. Compared to the well-watered controls, drought significantly increased the activity of GST. Likewise, the interaction of water*genotype was also significant and pronounced increase which was 1.49 to 10.27 nkat g-1 FW recorded in genotypes L3. Differences were significant for the activity of POX among genotypes, where greater activity was observed in genotype L1 compared to other two. However, non-significant differences for the activity of POX were recorded between the well-watered and drought-stressed plants. Similarly, differences were also significant among genotypes where, highest activity for cwPOX was observed in genotype L3 compared to other two genotypes, Moreover, compared to well-watered controls, cwPOX was significantly affected by drought. (Table 5).
2.5 Abscisic acid and antioxidants activity within spike
The ABA concentration was significant among genotypes where, highest ABA was recorded in L1 compared to other two genotypes. As expected, ABA concentration was significantly increased by drought in comparison to well-watered controls. There was also a significant interactive effect of water*genotype on spike ABA concentration where pronounced increase of ABA by drought was recorded in genotype L3 in relation to L1 and L3 (Table 5).
Differences were significant among genotypes for GST activity and the highest value was recorded in genotype L1 and lowest in L3. Drought significantly increased the activity of GST in comparison to well-watered controls. Likewise, differences were significant among genotypes for the activity of DHAR where, highest activity was recorded in L2 in comparison to the other two genotypes. The activity of GR was significantly different between the genotypes and the highest value was recorded in L1. No significant differences were observed for the activities of DHAR and GR between the well-watered and the drought stressed plants. Significant interaction of water*genotype was observed for GR where, more pronounced decrease in the activity of GR by drought was observed in L1. Differences were significant among genotypes for the activity of POX and the highest value was observed in L3. Again, compared to well-watered controls, non-significant effect of drought was recorded for the activity of POX (Table 5). Moreover, neither genotype nor drought significantly affected the activity of cwPOX. Differences were significant among genotypes for the activity of MDHAR where the lowest value was observed for L2 as compared to other genotypes. In relation to the well-watered controls, drought did not affect activity of MDHAR (Table 5).
2.6 Agronomic parameters
Shoot biomass was identical among the three genotypes, while it was significantly reduced by drought in relation to the well-watered controls. There was significant interaction between water*genotype on shoot biomass, where more pronounced reduction in plant biomass by drought was recorded in L2 in comparison to the other two genotypes (Fig. 1a). Grain yield pot-1 (GY) and harvest index (HI) were significantly different between the three genotypes, L3 had the lowest GY and HI in comparison to the other two genotypes. In comparison to the well-watered controls, GY and HI were significantly reduced under drought (Fig. 2a &b).
Differences were also significant among genotypes for TKW with the highest value recorded for L3. Drought significantly reduced the TKW in comparison to well-watered controls (Fig. 1d). The number of grains spike-1 (NGS) was significantly different among three genotypes with the highest NGS recorded for L2 and lowest for L3. Moreover, in comparison to well-watered controls, drought significantly reduced NGS. Additionally, significant interaction of water*genotype was recorded for NGS, where pronounced grain reduction due to drought was found in genotype L1 as compared to L2 and L3 (Fig. 1e). Kernel abortion (KA) was significantly different among all genotypes. Highest KA was recorded in genotype L3 and lowest in L1 (Fig. 1f). As compared to well-watered controls, drought significantly increased KA. Moreover, interaction between water*genotype was also significant and pronounced reduction was noticed in L1.
2.7. Principal component analysis and combined correlations between yield traits and enzymatic activities
Separated PCA analyses for plants grown under well-watered and drought-stressed conditions were performed visualizing the associations between the yield traits and the enzymatic activities. Principal component 1 (Dim1) and principal component 2 (Dim2) described 26.8% and 18.4% variability among the variables for the well-watered treatment, respectively. Biplot analysis of Dim1 and Dim2 showed that cluster of NGS, GY and HI was closer to An, activity of L.cwInv and L.MDHAR, and these variables were in opposite direction of the cluster for L.vacInv, S.vacInv, and L.cwPOX. The activities of S and L.aldolase clustered closer to BM and in opposite direction to S-cytInv (Fig. 2a). Under drought, 25.3 % and 21.8% of variability was described by PC1 and PC2, respectively (Fig. 2b). Biplot of these PC’s showed that NGS, RWC, HI and GY were clustered closer to An, Gs, S.aldolase and L.MDHAR and were in opposite direction of L.vacInv and S.vacInv, KA, TKW and L.cwPOX.
2.7.1. Correlation of leaf parameters with yield-related traits
RWC correlated significantly and positively with aldolase, cwPOX, OA, An, Gs, E, BM, GY, NGS, TKW and HI. However, this correlation was strong (***) with aldolase, An, Gs, E, BM, GY, NGS and HI, moderate (**) with TKW and weak (*) with cwPOX and OA. RWC chowed a strong significant and negative correlation with ABA, cwInv, GST, negative Yp and KA. It was negative but weak with vacInv. (Table 6). A strong significant and positive correlation of ABA was recorded with GST and Yp moderate with cwInv and cytInv and weak with KA. ABA showed a strong negative correlation with An, Gs and E moderately negative with NGS and weakly negative with aldolase, cwPOX, BM, GY and NGS. A moderate positive correlation of cwInv was recorded with GST and Yp. It was strong and negative with TKW moderate and negative with An, Gs and E while weak and negative with aldolase, BM and GY. CytInv showed a weak positive correlation with GST and Yp while it was weak and negative with An. VacInv has a weak positive correlation with Yp, moderately negative with HI and weakly negative with GY and NGS. A strong positive correlation of aldolase was estimated with cwPOX, An, Gs, E, BM and TKW and it was moderate and positive with GY while the correlation of aldolase was strong and negative with GST and Yp.
Moderate positive correlation of cwPOX was measured with Gs, E and TKW and it was weakly positive with An and BM while correlation of cwPOX was moderate and negative with GST, Yp and KA. MDHAR showed moderate and positive correlation with OA, NGS, GY and HI and it was moderately negative with KA. A strong positive correlation of GST was estimated with Yp while it was weak and negative with KA. This correlation was strong and negative with An, Gs, E, BM and GY, moderate and negative with NGS, TKW and HI. Negative Yp showed negative correlation with most of the yield related traits except KA. However, this correlation was strong with An, Gs, E, BM, GY and HI while it was moderate and weak with NGS and TKW respectively. A strong and positive correlation of OA was estimated with An while it was weak and positive with NGS moreover, moderate and negative correlation was recorded with KA.
A strong positive correlation of An was noticed with most of yield related traits except TKW where it was moderately positive. A moderate but negative correlation of An was recorded with KA. Correlation of Gs was similar to An except for NGS, TKW and HI where it was moderate and positive. The correlation of Gs weak and negative with KA. E was also showed similar correlation to Gs except it was weak and positive with NGS and HI. BM showed moderate and positive correlation with GY and TKW while it was weak and positive with NGS and HI. A strong and positive correlation of GY recorded with NGS and HI however, correlation was weak and positive with TKW. Like GY, correlation of NGS was strong and positive with HI. In contrast, KA showed strong and negative correlation with GY, NGS and HI (Table 6).
2.7.1. Correlation of leaf parameters with yield related traits
A strong and positive correlation of ABA was recorded with activities of GST, it was moderate and positive with activities of PFK and weak and positive with An. Correlation of ABA was moderate and negative with Gs and weak but negative with E (Table 7). CwInv showed strong and positive correlation with vacInv. A strong positive correlation of vacInv was estimated with UGPase and PFK, moderate and positive with GST and weak and positive with PGM. CytInv showed weak and negative correlation with aldolase, An, BM GY and TKW. The correlation of vacInv was weak and positive with KA and correlation weak and negative with PGM, BM, GY and HI.
UGPase showed moderate and positive with PFK and weak and positive with KA, moderate and negative with TKW and weak and negative with An. A strong and positive correlation of PGM was estimated with PFK while strong and negative with TKW. PFK showed strong and positive correlation with GST. It was strong and negative with TKW moderate and negative with An, Gs and BM and weak and negative with E and GY. Aldolase showed weak and positive correlation with An and weak but negative with GST. A moderately and positive correlation of GST was estimated with KA however, it was strong and negative with An, Gs, E, BM and GY and moderate negative with NGS, TKW and HI.