Waterlogging tolerance and recovery capability screening in peanut: a comparative analysis of waterlogging effects on physiological traits and yield

Plant materials

Fifteen peanut varieties were selected as plant materials in this experiment, and the details of the materials were given in Table 1. The field experiment was conducted at the Zengcheng Teaching and Research Farm (23°24′N, 113°64′E) of South China Agricultural University (SCAU), which is located in Zengcheng District, Guangzhou City, Guangdong Province, China.

Waterlogging treatment

Seeds of per variety were planted in three replicate plots. Waterlogging treatment was applied to peanut plants during the pod filling stage, and the water level was kept at 2 cm higher than the soil surface during the waterlogging process. And the blank control group of each variety was also set, During the growth stage, the CK groups of all varieties were irrigated normally and kept the soil moisture at 75–80% of saturated water-holding capacity. The water in the fields was drained after waterlogging for 7 days. Other management practices followed conventional cultivation methods.

Determination of SPAD value and chlorophyll fluorescence parameters

After 7 days of waterlogging and 7 days of drainage, the SPAD value in the functional leaves of the main stem (from the top of the main stem to the base of the stem, the third open leaf) was measured using a chlorophyll meter (SPAD-502; Konica Minolta Sensing, Inc., Osaka, Japan). Chlorophyll fluorescence parameters of the same leaf were analyzed using a hand-held device MultispeQ Beta (Kuhlgert et al., 2016). And PS actual quantum yield (Φ_PS II), maximum photochemical efficiency (Fv/Fm), non-photochemical quenching (NPQ), and photochemical quenching (qL) of leaves were obtained. Three functional leaves were measured in each plot. The data of one plot was a replicate, and each treatment contained three replicates.

Determination of the activities of SOD and CAT

SOD activity was measured by monitoring the inhibition of nitro blue tetrazolium (NBT) reduction with a spectrophotometer at 560 nm; 100 µL of crude enzyme solution was added to 2.9 mL reaction solution, which was composed of 50 mM sodium phosphate buffer (pH 7.8), 60 µM riboflavin, 195 mM methionine, 3 µM ethylenediamine tetraacetic acid (EDTA), and 1.125 mM NBT; three mL reaction solution was used as the control. The mixture was placed under a 4000 lx fluorescent lamp for 60 min for chromogenic reaction, and then turned into the darkness to stop the reaction. One unit of SOD activity was defined as the amount of enzyme that inhibits the NBT reduction by 50%.

For estimating the CAT activity, 100 µL of enzyme extract was added to a mixture containing 5.9 mM of H₂O₂ and 50 mM of buffer. Recording the absorbance at 240 nm at per minute interval for 3 min. A unit of CAT activity was defined as the changes in absorbance at 240 nm per minute.

Determination of MDA content

MDA content was calculated by the thiobarbituric acid (TBA) method described by a previous report with modifications (Wassie et al., 2019). Fresh leaf samples (0.5 g) were put into liquid nitrogen and ground to powder, then were homogenized in 2 mL of 10% (v/v) TCA solution, followed by centrifugation at 3,000× g for 10 min and collection of the supernatant. The 2 mL obtained supernatant was added to an equal volume of reaction mixture, which contained 20% (v/v) trichloroacetic acid and 0.5% (v/v) thiobarbituric acid. The mixture was then heated at 100 °C water bath for 20 min and then was stopped by an ice bath, followed by centrifugation at 4,000 g for 10 min at 20 °C. To determine the MDA level, the supernatant absorbance was measured spectrophotometrically at 450, 532, and 600 nm.

Determination of relative electrolyte linkage (EL)

Electrolyte leakage was measured following the method described by the method of predecessors (Huang et al., 2017). 1.0 g fresh leaf samples were washed with deionized water for three times and then transferred to a 50-mL centrifuge tube containing deionized water. The test tube was cultured in a conical shaker at room temperature for 12 h, and a conductivity meter (Jenco-3173; Jenco Instruments, Inc., San Diego, CA, USA) was used to measure the initial electrical conductivity (EL1). Then the leaves were sterilized at 100 °C for 30 min, then cooled at room temperature, and the secondary conductivity (EL2) of the leaves was measured. The relative electrolyte linkage (REL) is calculated by the formula: (1)${\displaystyle \mathrm{REL}\left(\text{\%}\right)=\left(EL1/EL2\right)\times 100.}$

Determination of yield and yield components

Plant samples were harvested on 15 December 2020 for the determination of the yield and yield components. The representative plant samples from each plot were obtained at the physiological maturity stage to determine the yield and yield components, including the pod yields per hectare (Y), the number of total pods per plant (TP), the hundred pods weight (HPW), and the hundred kernels weight (HKW). The proportion of reduction in yield and yield components is also calculated, including the proportion of reduction in yield (RY), the proportion of reduction in HPW (RHPW), the proportion of reduction in HKW (RHKW), and the proportion of reduction in TP (RTP). The data of one plot was a replicate, and each treatment contained three replicates.

Evaluation of waterlogging tolerance

The waterlogging tolerance coefficient (WTC) of all indicators was calculated using the following equation: (2)${\displaystyle WTC=\left(WK/CK\right)\times 100}$

where CK is the mean value of an indicator under the control treatment and WK is the mean value of an indicator under waterlogging treatment.

Membership function values of various indicators of different varieties: (3)${\displaystyle u\left(X_j\right)=\left(X_j-X_{\min }\right)/\left(X_{\max }-X_{\min }\right)\left(j=1,2,\dots ,n\right).}$

where µ(X_j) represents the subordinate function value of the j-th comprehensive indicator, Xj represents the j-th comprehensive indicator value, X_max represents the maximum value of the j-th comprehensive indicator, and X_min represents the minimum value of the j-th comprehensive indicator.

The index weight calculation formula of each comprehensive indicator is as follows: (4)${\displaystyle w_j=p_j/\sum _{j=1}^n{p}_j\left(j=1,2,\dots ,n\right)}$

where w_j is the index weight of the j-th comprehensive indicator among all comprehensive indicators and p_j is the contribution rate of the j-th comprehensive indicator.

The comprehensive evaluation value of waterlogging tolerance of different peanut varieties: (5)${\displaystyle D=\sum _j^n\left[u\left(X_j\right)\times w_j\right]\left(j=1,2,\dots ,n\right)}$

where D indicates the comprehensive evaluation value of waterlogging tolerance of peanut varieties. The higher the D value, the stronger the tolerance to waterlogging stress of peanut varieties; the lower the D value, the weaker the tolerance to waterlogging stress of peanut varieties.

Statistically analysis

Experimental data was statistically analyzed using Microsoft Excel 2010 and SPSS 22.0 (SPSS., Chicago, IL, USA), and the image was generated using Origin 2017. All data are means of three replicates (n = 3). Comparisons among multiple groups were performed using Fisher’s protected least significant difference (LSD) test. Probability values p < 0.05 were considered statistically significant. SPSS 22.0 software was used for variance analysis, principal component analysis, and cluster analysis of data. And the D value of different varieties was analyzed by cluster analysis at an Euclidean distance of 5.

Response of different indexes to waterlogging and correlation analysis among them

Figures S1–S11 displayed the response of leaf indexes of 15 peanut varieties to 7 days of waterlogging and 7 days of drainage. Waterlogging significantly affected the photosynthetic characteristics and antioxidant capacity of peanut leaves. However, there were great differences in the response of different varieties to waterlogging. As shown in Table 2, after waterlogging for 7 days, the WTC of REL, MDA content, SOD activity, and CAT activity, NPQ and qL of leaves of some peanut varieties (HH 2, YH 65, YH 22) increased, and the WTC of SPAD value, Φ_PS II, Fv/Fm of peanut varieties (KN 1715, DBW and SLLK) decreased. After 7 days of drainage, the WTC of REL, MDA content, SOD activity and CAT activity of leaves of peanut variety YY 45 decreased compared with that of 7 days of waterlogging, but these indicators of YSHS still increased. And after drainage, the WTC of SOD activity and CAT activity of leaves of peanut varieties (KN 1715, JH 7) decreased compared with that of after waterlogging for 7 days, but these indicators of (YY 13, HH 2, DBW, HY 10, and HJ 16) still increased. Besides, after 7 days of drainage, Φ_PS II, Fv/Fm, NPQ and qL increased or decreased to different degrees in comparison with those after 7 days of waterlogging. And the WTC of HPW, HCW, Y, and TP of most varieties (YYHS, HH 2, KN 1715, HY 4, DBW, YH 65, YH 22, JH 7, HY 10, FH 1, JH 16, and HY 39) decreased, indicating that waterlogging had a negative impact on yield and yield components.

Besides, from the correlation coefficient matrix (Table 3), there was a positive correlation between Fv/Fm and SPAD value of different peanut varieties after 7 days of waterlogging and 7 days of drainage (0.646 and 0.518, respectively). Meanwhile, HPW and HKW showed an extremely significant positive correlation (0.829), and Y was significantly positively correlated with TP (0.820). However, there may be information overlap between different indicators, and every single indicator plays a different role in the waterlogging tolerance of peanut. Therefore, it is difficult to accurately evaluate the waterlogging tolerance of different peanut varieties by using these indicators directly. To make up the deficiency of a single indicator evaluation of waterlogging tolerance, the principal component analysis method was used.

Comprehensive evaluation of waterlogging tolerance of different peanut varieties

Cluster analysis of different peanut varieties based on D1 value after 7 days of waterlogging

The higher the D1 value, the stronger the tolerance to waterlogging stress of peanut varieties; the lower the D1 value, the weaker the tolerance to waterlogging stress of peanut varieties. As indicated in Table 5, the D1 value of YY 45 ranked first, followed by HY 4, and the D1 value of SLLK ranked last, indicating that YY 45 has the highest waterlogging tolerance while SLLK has the lowest. Therefore, we used the hierarchical cluster analysis to cluster D1 values. Figure 1 displayed that 15 peanut varieties could be divided into three categories: waterlogging-tolerant varieties (HY 4, YY 45, YY 13, YH 65, and HY 39), intermediate varieties (FH 1, JH 16, KN 1715, YH 22, JH 7, HH 2, HY 10, and YSHS) and waterlogging-sensitive varieties (DBW and SLLK).

Comprehensive evaluation of recovery capability of different peanut varieties

The indicators used for identifying waterlogging tolerance and recovery capability and their relationship with yield and yield components

Correlation analysis was carried out between the D1 value and the WTC of each physiological index after 7 days of waterlogging (Table 8). The D1 value strongly and positively correlated with the Φ_PSII(W), SPAD(W), Fv/Fm(W), and the correlation coefficient was 0.845, 0.845, 0.708, respectively. Besides, there was a significant negative correlation between NPQ(W) and D1 value, and the WTC was −0.707. Therefore, the WTC of Φ_PS II(W), NPQ(R), Fv/Fm(W), and SPAD values measured after 7 days of waterlogging can be used as important indexes for the identification of waterlogging tolerance.

The correlation between D2 value and the WTC of each physiological index after 7 days of drainage was also analyzed (Table 9). A significant positive correlation of D2 value was observed with Φ_PSII(D) (r = 0.855). And there was a positive relation between D2 value and Fv/Fm(D)(r = 0.625). However, there was a significant negative correlation between NPQ(D) and D2 value, and the correlation coefficient was −0.609. Therefore, the WTC of Φ_PS II(D), Fv/Fm(D) and NPQ(D) measured after 7 days of drainage can be used as important indexes for the identification of recovery capability.

To determine the relationship between D1 value, D2 value, and the proportion of reduction in yield and yield components, a linear model among them was fitted. As shown in Fig. 2, the R² between the RTP and RY is the highest (0.6732), followed by the R² between the D2 value and the RY (0.4458). In conclusion, both the D2 value and the RTP have significant effects on the final yield. The lower the RTP and the higher the D2 value, the less the yield loss under waterlogging. However, there was no significant correlation between the D1 value and RY. In addition, no significant correlation was found between the D1 value and D2 value, suggesting that the waterlogging tolerance of the variety did not affect the recovery capability.

Yield and yield components of peanut varieties with different waterlogging recovery capability

Peanut with different recovery capacities had different yield decline under waterlogging stress (Fig. 3). For example, YY 13 is a cultivar with high recovery capability and YY 45 is a cultivar with intermediate recovery capability. And RTP of the two cultivars were −1.67% and −3.51%. However, the RY of YY 13 was only 2.71%, while that of YY 45 was 39.76%. Besides, HH 2 belongs to the variety with high recovery capability, and YH 65 belongs to the variety with intermediate recovery capability. It is found that the TP of the two varieties decreased by 34.89% and 33.40% respectively under waterlogging, which did not reach a significant difference, but the yield of HH 2 decreased by 49.86%, while the yield of YH 65 decreased by 56.61%. It showed that the recovery capability of peanut affected the final pod yield.

And among peanut varieties with similar recovery capability, the RY varied greatly among varieties. Among the cultivars with high recovery capability (YY 13, YSHS, HH 2, FH 1, HY 4), the D2 values of YY 13 and HY 4 were 0.6909 and 0.6447, respectively, but the RY of YY 13 and HY 4 was 2.71% and 56.32%, respectively. The RTP of YY 13 was 1.67% while that of HY 4 was 44.21%. In cultivars with intermediate recovery capability (YY 45, JH 7, JH 16, YH 65, YH 22, DBW, HY 39), the yield of YY 45 and HY 39 decreased by 38.62% and 70.08%, respectively, and the TP of YY 45 increased by 3.47% while that of HY 39 decreased by 60.91%. In the cultivars with low recovery capability, including HY 10, SLLK, and KN 1715, the RTP of HY 10, SLLK, and KN 1715 was 39.03%, 59.85% and 64.07%, respectively, and the RY of them was 62.35%, 60.46% and 78.74%, respectively. The results indicated that the yield of the peanut varieties with lower recovery capability decreased greatly, while the yield of the peanut varieties with the same recovery capability was affected by RTP.