Article Interactive Effects of Drought–Flood Abrupt Alternation on Morpho‐Agronomic and Nutrient Use Traits in Rice 1,2,3 2,3 1, 2,3 2,3 2,3 2,3 Jie Huang , Fengyan Wu , Tiesong Hu *, Luguang Liu , Jing Wang , Xin Wang , Changmei Liang and Jia Liu State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072, China; firstname.lastname@example.org Hubei Water Resources Research Institute, Wuhan 430070, China; email@example.com (F.W.); firstname.lastname@example.org (L.L.); email@example.com (J.W.); firstname.lastname@example.org (X.W.); email@example.com (C.L.) Hubei Provincial Water Saving Research Center, Wuhan 430070, China Key Laboratory of Water Conservancy and Water Resources of Anhui Province, Bengbu 233000, China; firstname.lastname@example.org * Correspondence: email@example.com Citation: Huang, J.; Wu, F.; Hu, T.; Liu, L.; Wang, J.; Wang, X.; Abstract: The frequent occurrence of drought–flood abrupt alternation (DFAA) in Huaibei Plain Liang, C.; Liu, J. Interactive Effects has shown a great impact on local rice production. Pot experiments were performed in 2016–2018 of Drought–Flood Abrupt to investigate the effects of co‐occurring drought and flooding stresses on dry weight (DW), grain Alternation on Morpho‐Agronomic yield, nitrogen (N), phosphorus (P) and potassium (K) uptake and use efficiencies (NUE, PUE and and Nutrient Use Traits in Rice. KUE) in rice. The results showed that DFAA changed the accumulation of biomass and nutrients Agronomy 2021, 11, 2103. https:// among different organs in rice. Compared with control, DFAA significantly reduced the grain yield doi.org/10.3390/agronomy11112103 (−29.8%) and root DW (−30.0%), but increased the DW in stem and leaf (10.2% and 9.7%). The root/shoot ratio and morphological size of the root system in DFAA‐treated plants was smaller than Academic Editors: those of drought alone and flooding alone. Under DFAA stresses, the specific absorption rate of N, Pirjo Mäkelä, P and K increased significantly (47.9%, 31.8% and 32.8%, respectively), while NUE, PUE and KUE Mercè Llugany, Peter A. Roussos decreased significantly (−27.9%, −10.8% and −19.7%, respectively). The decrease of nutrient use ef‐ and Mumtaz Cheema ficiencies was mainly due to the redundant growth of branches and leaves, and the key factor lim‐ iting grain yield under DFAA conditions was the effective utilization of N. Compared with the ear‐ Received: 7 September 2021 lier drought, the subsequent flooding might have more influence on rice growth, nutrient utilization Accepted: 15 October 2021/ and yield formation, but the interaction of the two weakened the cumulative effect of drought and Published: 20 October 2021 flooding. These findings provide a scientific basis for establishing a nutrient and water management system of rice cultivation under transient soil moisture conditions. Publisher’s Note: MDPI stays neu‐ tral with regard to jurisdictional Keywords: drought; flood; root growth; N, P and K; grain yield claims in published maps and insti‐ tutional affiliations. 1. Introduction Copyright: © 2021 by the authors. Li‐ In recent years, the changing weather patterns have led to extreme changes in the censee MDPI, Basel, Switzerland. frequency, intensity, spatial extent and duration of rainfall . These extreme events occur This article is an open access article with increasing frequency and magnitude across the globe , which generally negatively distributed under the terms and con‐ affect traditional agriculture in a major way . Rain‐fed agriculture is particularly vul‐ ditions of the Creative Commons At‐ nerable to changes in weather patterns. Some areas experience severe water depletion, tribution (CC BY) license (http://crea‐ whereas others experience excessive rainfall, thereby resulting in flooding . Inevitably, tivecommons.org/licenses/by/4.0/). drought and flooding occur one after another in a given region, leading to transient fluc‐ tuations in soil moisture, among which, drought–flood abrupt alternation (DFAA) is the most common . Generally, plants are highly plastic to various stressors . Drought reduced the morpho‐ logical traits such as leaf area, shoot length and vegetative growth, as well as physiological Agronomy 2021, 11, 2103. https://doi.org/10.3390/agronomy11112103 www.mdpi.com/journal/agronomy Agronomy 2021, 11, 2103 2 of 21 traits such as the leaf water potential and sap movement in the plants . Flooding, espe‐ cially complete submergence, will dramatically change the gas exchange environment of rice plants . In order to get more energy resources, the internodes of plants under deep water are rapidly and substantially elongated with the help of the activated ethylene bio‐ synthesis and the increase in gibberellin acid/abscisic acid . Meanwhile, the activated ethylene also promotes the appearance of aerenchyma in the internodes and the increase in the number of adventitious roots . The risk of DFAA depends not only on the scale and extent of the hazard, such as the degree and duration of drought and flooding, but also on the vulnerability and adaptability of the plant to that event, such as the size, growth rates, root–shoot ratios, grain yield and chemical constituents. As an important food crop, rice must develop some growth foraging strategies to deal with a highly variable distribution of soil moisture, such as a plastic change of root system, adjustment of crown size and distribution of nutrients. Thus, understanding the adaptive mechanism of plant growth and metabolic mechanism of nutrient accumulation in rice is important in order to implement efficient and effective water and nutrient management practices to ensure sustainable rice production systems. Root phenotypic plasticity plays an important role in plant adaptation to various wa‐ ter stresses . A moderate combination of drought and flooding can improve the root system. A safe alternate wetting and drying irrigation can increase root length (RL), dis‐ tribution of roots in the soil, concentration of cytokines and root oxidation activity [12,13]. Alternate partial root‐zone irrigation can markedly improve the development of root ar‐ eas and forks [14,15]. However, some combinations of extreme drought and flooding can adversely damage root structure mainly by altering morpho‐anatomical traits, physiolog‐ ical and biochemical processes, gene expression and metabolic regulation networks . For instance, irrigation control and drainage considerably decrease root dry weight (DW), RL and root–shoot ratio at harvest, and the yield reduction for this constraint applies to different growth periods ranging from 5.7% to 23.3% . Given these findings, the re‐ sponse of roots to DFAA water stress may be perceived as more detrimental to plants when under severe drought or heavy flooding than alternate wetting and drying irriga‐ tion and controlled irrigation and drainage. Under such adverse conditions, roots must simultaneously acquire oxygen, water and nutrients. The inability to acclimate to such soil moisture fluctuation is assumed to affect the growth and function of the root system, and the accumulation of biomass and nutrient elements. In paddy field environments, soil moisture fluctuation alters the amount of available + − N (NH4 , NO3 ), P and K in soil [18,19]. The accumulation of these nutrients in plants, net photosynthetic rate and dry matter accumulation and distribution will then be affected [20– 22]. Recent research on nutrient uptake and utilization of rice under water stress mainly focuses on single water stress, and the results are inconsistent [21,23–25]. Moderate drought stress benefits the accumulation of nutrients in rice, whereas severe drought stress is harm‐ + ful to the P absorption and the K reflux from grain to straw during the ripening period . Reddy and Mittra [27,28] reported that total N content in rice increases when the plants are completely submerged by flooding at seeding, booting or flowering stages, whereas P and K uptake shows the opposite trend. However, Setter et al.  argued that K content in‐ creases in the growing zone of the emerging leaf in the air under incomplete submergence conditions. The desirable N, P and K changes in plants under combined water stresses may be different from those under drought stress alone or flooding stress alone. For instance, alternate wetting and drying irrigation applied during the early stages substantially reduces tissue P and K content and redistribution to panicles in comparison with a situation when this water stress is imposed during the later growth stages, and the lowest reductions are observed in N . Similarly, Cabangon et al. also found that alternate wetting and dry‐ ing irrigation increases total N uptake by increasing the number of N‐fertilizer application splits, but not total P and total K. With the same irrigation amount, the N and P uptake of winter wheat with alternate partial root‐zone irrigation is more than that with all soil area irrigation and fixed half of root area irrigation . Agronomy 2021, 11, 2103 3 of 21 Transient soil aeration–anoxia under DFAA affects the availability of soil nutrients to rice plants [19,33]. The loss of yield under DFAA may be caused by soil permeability on the one hand and the limited availability of N, P and K on the other hand [34,35]. Evidence shows that rice cultivation with soil moisture fluctuation in China has very low fertilizer use efficiency because of the nitrification–denitrification, leaching and fixation processes [36,37]. Deep water submergence during the DFAA process, a completely oxygen‐deficient envi‐ ronment, is very conductive to the denitrification of microorganisms and accelerates the loss of soil nitrogen . Shao et al.  reported that controlled irrigation and drainage remark‐ + – + ably decreases the loss of NH4 and NO3 in paddy soil, and the NH4 concentration in sur‐ face water at tillering stage is higher than that at the following jointing–booting and panicle initiation stages. During the drought period, P and K may be fixed in soil and become una‐ vailable for root uptake, but their availability increases after submergence . Thus, soil moisture fluctuation may have a high P use efficiency (PUE) and K use efficiency (KUE) despite that water stress limits P and K uptake . Although the effects of combined drought and flooding on rice root growth and the N, P and K uptake and utilization remain poorly understood, relevant studies on the shoot growth, grain yield and the paddy water nutrient concentrations change and loss have been reported [17,19,24,33,40–43]. Rice is known as a crop that is sensitive to drought. Under DFAA conditions, rice is firstly affected by preceding drought and then is subjected to another flooding stress. How this combined stress would ultimately affect rice root growth and nutrient uptake is uncertain, and it is important to further understand the morphological and physiological mechanisms that cause rice yield loss in order to develop theoretical and scientific solutions for drought and flood management in rice cultivation. Thus, this study aimed (a) to reveal rice morphological (mainly focused on the root traits) and physiological (N, P and K uptake and utilization) performance under DFAA conditions, as well as in drought alone (D), flooding alone (F) and control treatments and, accordingly, (b) to evaluate the interactive effects of drought followed by flooding on mor‐ pho‐agronomic and nutrient use traits in rice plants. 2. Materials and Methods 2.1. Site Description The study site was at the Xinmaqiao Comprehensive Experiment Station of Irrigation and Drainage, Bengbu, China (117°21′34″ E, 33°08′56″ N) during the rice growing season (May to September) in 2016–2018. The annual average temperature and rainfall in this area are 14.3 °C and 911 mm, respectively. More than 60% of the rainfall is concentrated between July and September and falls in the form of torrential rain. Frequent drought is another climate defect in this region. Thus, most local crops are at a high risk of DFAA stresses. Weather data (i.e., precipitation, air temperature, irradiance and vapor pressure) were recorded daily and reported as monthly averages for the 3 years that the experiment was conducted (Figure 1). Agronomy 2021, 11, 2103 4 of 21 P－2016 P－2017 P－2018 T－2016 T－2017 T2 － 018 400 32 (a) 300 24 200 16 100 8 0 0 May Jun Jul Aug Sept I－2016 I－2017 I－2018 VP－2016 VP－2017 VP－2018 36 36 (b) 30 30 24 24 18 18 12 12 6 6 0 0 May Jun Jul Aug Sept Figure 1. (a) Monthly precipitation (P) and mean air temperature (T), (b) irradiance (I) and mean vapor pressure (VP) at the Xinmaqiao Comprehensive Experiment Station of Irrigation and Drain‐ age, Bengbu, China (117°21′34″ E, 33°08′56″ N) during the rice growing season (May to September) in 2016–2018. 2.2. Pot Establishment and Plant Cultivation The experiment was laid out in outdoor pots designed with three replications in each year (Figure 2). This outdoor pot experiment was carried out in a multistep circular water pool with an internal diameter of 8 m (Figure 2b,e). It was designed with seven steps of different depths to satisfy the requirements of different submergence depths. The dimen‐ sions of the experimental pots were 35 cm in inner diameter and 45 cm in height (Figure 2d). The tiny holes of 2.5 mm in the bottom of pots and the sand filter layer were composed of a water-permeable filter cloth, 3 cm coarse gravel and 2 cm fine sand from bottom to top, allowing the free seepage of water. The soil in pots was a typical black sandy loam (sub clays) –1 –1 −1 containing 8.59 g kg organic matter, 632.00 mg kg total N, 92.11 mg kg alkali‐hydro‐ −1 −1 lysable N, 16.10 mg kg available P2O5 and 93.91 mg kg available K2O. The pH of soil −3 −3 was 7.5. The bulk density and FC of 0–40 cm were 1.544 g cm and 0.42 cm cm , respectively. On the south side of the pool was a movable rain shelter (8.0 m long, 8.0 m wide and 2.5 m high) that protects the drought–stressed pots from rainfall (Figure 2a). -2 -1 Precipitation(mm) Irradiance (MJ m day ) ‐4 Mean Temp ( ) Mean VP (10 MPa) Agronomy 2021, 11, 2103 5 of 21 Figure 2. Photos of drought phase, flooding preparation and flooding phase (a–c), schematic diagrams of the pots for rice growth (d) and the profile of multistep water pool for different flooding depths(e). Longliangyouhuazhan (Oryza sativa L.), a predominant local middle‐season rice cul‐ tivar bred by China National Rice Research Institute was used in this study. Seeds were germinated and sown in a seedbed for approximately 30 days before they were trans‐ planted into pots around mid‐June in three years. Each pot had three hills arranged in a 3 −1 triangle (18 × 18 × 18 cm ), with two plants per hill. Compound fertilizer (1200 kg ha , N:P2O5:K2O = 15%:15%:15%) was applied one day before transplanting. Foliar spraying mixture of pesticide and fertilizer (foliar fertilizer (water soluble fertilizer containing amino acid, amino acid ≥ 100 g/L, Zn (Zinc) + B (Boron) ≥ 20 g/L, Henan dingpin chemical −1 −1 products Co., Ltd., China, 525 g ha ) + cyantraniliprole (300 g ha ) + pyraclostrobin (150 −1 −1 g ha ) and fipronil (450 mL ha )) was applied on 15 July and September 7 to control in‐ sects and diseases. All of the other management practices followed the local farming meth‐ ods during the entire growth period. 2.3. Experimental Design and Management Based on the analysis of DFAA historical data [44,45], this experiment designed four soil moisture control methods (Table 1) for rice jointing–booting stage when DFAA easily occurs according to China’s drought‐grading, drainage standards and some references [46,47], as follows: Agronomy 2021, 11, 2103 6 of 21 Table 1. Experimental water control design for rice jointing–booting stage in the years of 2016–2018. Drought Phase (Stage I) Flooding Phase (Stage II) Beginning and Flooding De‐ Beginning and Drought De‐ Treatment Duration Ending Dates (Mon/D) gree Duration Ending Dates (Mon/D) gree (/D) (/Plant (/D) (% FC) 2016 2017 2018 2016 2017 2018 Height) DFAA1 50(severe) 5 7/25–7/29 7/30–8/3 7/28–8/1 1/1(heavy) 7 7/30–8/5 8/4–8/10 8/2–8/8 DFAA2 50(severe) 10 7/25–8/3 7/25–8/3 7/23–8/1 1/2 9(heavy) 8/4–8/12 8/4–8/12 8/2–8/10 DFAA3 50(severe) 15 7/25–8/8 7/20–8/3 7/18–8/1 3/4 5(light) 8/9–8/13 8/4–8/8 8/2–8/6 DFAA4 60(middle) 5 7/25–7/29 7/30–8/3 7/28–8/1 3/4 9(heavy) 7/30–8/7 8/4–8/12 8/2–8/10 DFAA5 60(middle) 10 7/25–8/3 7/25–8/3 7/23–8/1 1/1(heavy) 5 8/4–8/8 8/4–8/8 8/2–8/6 DFAA6 60(middle) 15 7/25–8/8 7/20–8/3 7/18–8/1 1/2(light) 7 8/9–8/15 8/4–8/10 8/2–8/8 DFAA7 70(mild) 5 7/25–7/29 7/30–8/3 7/28–8/1 1/2 5(light) 7/30–8/3 8/4–8/8 8/2–8/6 DFAA8 70(mild) 10 7/25–8/3 7/25–8/3 7/23–8/1 3/4 7(light) 8/4–8/10 8/4–8/10 8/2–8/8 DFAA9 70(mild) 15 7/25–8/8 7/20–8/3 7/18–8/1 1/1(heavy) 9 8/9–8/17 8/4–8/12 8/2–8/10 D1~D3, D7~D9 (2016) Drought alone Continuous flooding (2~3cm) D1~D9 (2017, 2018) Flooding F1~F3, F7~F9 (2016) Continuous flooding (2~3cm) alone F1~F9 (2017, 2018) Control Continuous flooding (2~3cm) Notes: DFAA, drought followed by floods abrupt alternation; D, drought followed by no floods; F, no drought followed by floods. FC, field capacity; Mon/D, month/day. D1~D9 and F1~F9 are the parallel control groups of DFAA1~DFAA9. (1) Control treatment (without water stress), keeping 2–3 cm water level above the soil surface; (2) Nine DFAA treatments, combined with drought degree (50%, 60% and 70% of field capacity (FC)), drought duration (5, 10 and 15 days), flooding degree (1/2, 3/4 and 1/1 of plant height) and flooding duration (5, 7 and 9 days) according to the standard orthogonal table (L9 (3 )); (3) Nine drought alone treatments, drought stage following the same as DFAA treat‐ ments and the other stages following the same as the control treatment; (4) Nine flooding alone treatments, flooding stage following the same as DFAA treat‐ ments and the other stages following the same as the control treatment. Only six drought alone treatments and six flooding alone treatments were set up in 2016 because of the limited number of pots. Thus, 28 treatments were performed in 2017– 2018, and 22 treatments were performed in 2016 with the absence of D4–6 and F4–6. The entire process of water control was divided into three phases, that is, drought phase (Stage I), flooding phase (Stage II, Table 1) and recovery phase (Stage III). At the beginning, all pots (66 in 2016 and 84 in 2017–2018) were on the furthest step from the center of the water pool, maintaining 2–3 cm water level above the soil surface. Approxi‐ mately 25–35 days after transplantation, parts of pots (45 in 2016 and 54 in 2017–2018) were shifted onto the shore of the pool for drought. Their weights were recorded at 6 a.m. and 6 p.m. daily. Water was added to the pots until the control requirements of drought pots were met (Table 1). After drought (the beginning of flooding), these pots were moved to the corresponding rings from the border to the center of the pool, using bricks (235 mm long × 115 mm wide × 53 mm height) to adjust the designed depths of flooding (Figure 2b). At the end of flooding, all pots were returned to the farthest step from the center. The water table of the pool was measured at 9 a.m. daily, and water was added into or drained out as required. The experiment was repeated in 2016–2018 with only slight variation in water stress time per year, and three duplicate pots were used in each treatment excluding those destroyed at the end of DFAA, when each treatment had two additional duplicate Agronomy 2021, 11, 2103 7 of 21 pots to observe the growth indicators after water stresses. The pots were randomized com‐ plete block design according to the experiment design (Table 1). 2.4. Sampling and Measurements 2.4.1. Shoot and Root Sampling At the end of DFAA (Table 1) and at maturity (28 September 2016; 20 September 2017; 15 September 2018), rice shoot and root samples were collected. Shoot samples were divided into three parts: stems (containing both stem and leaf sheath), leaves (only leaf blade) and panicles. The number of panicles per pot, spikelets per panicle and grain yield were then examined. The unfilled (without developed grains) and filled (with developed grains) spikelets were counted separately. Then, filled grains (FGs) were computed as the ratio of filled spikelets and total number of spikelets. Root samples in the entire soil column (0–40 cm soil zone) were carefully collected and flushed. The soil samples were carefully transferred into a screen bag with a 2 mm aperture and were flushed using a hose from the tap at low pressure . The maximum root depth was measured with a ruler, and the adventitious root numbers were estimated manually. All of the collected roots were washed free of soil and dirt in a trough with running water. The cleaned fresh roots were then stored in a solution of formaldehyde– acetic acid–70% ethanol (1:1:18 ratio by volume) for preservation and further measure‐ ments. To measure the RL, root surface area (RSA), root volume (RV) and root mean di‐ ameter (RMD), we arranged the roots, floated them on shallow water (2.0 mm) in a trans‐ parent rectangular tray (250 mm × 200 mm × 20 mm, thickness of 4.5 mm), scanned them using the Epson Perfection V800 Photo Scanner (8.5” × 11.7”, 216 × 297mm, 6400 dpi × 9600 dpi) and analyzed the images by using WinRHIZO Pro2015a software (Regent Instrument Inc., Quebec, Canada). All shoot and root samples were oven dried at 75 °C for 48 h before −1 dry weights (DWs) were recorded. The root/shoot ratio (g g ), RL density (the ratio of RL −3 −1 and soil column volume, cm cm ), specific RL (SRL, the ratio of RL and root DW, m g ) 2 −3 and S/V ratio (RSA/RV ratio, cm cm ) were calculated. 2.4.2. Chemical Analysis and Calculation Oven‐dried samples (root, stem, leaf and panicle) were ground in the laboratory us‐ ing a Wiley hammer mill with 1 mm mesh size. The samples were analyzed for N, P and K concentration. The determination of nutrients was obtained by acid‐wet digestion method . During digestion, the 0.25 g ground samples were transferred to a clean 100 mL digestion flask, and 5 mL concentrated sulfuric acid (H2SO4) was added to each diges‐ tion bottle. After 2 h, 2 mL of 50% hydrogen peroxide (H2O2) was added. The flasks were heated at 285 °C for 45 min, and then allowed to cool. This process was repeated three times to make the digestion clear (colorless). The flasks were then removed from the di‐ gestion block, cooled to room temperature and made up to 100 mL with distilled water filtered through filter paper (Whatman no. 1). The digested samples were stored in plastic vials before analysis for N, P and K. N and P were determined with an auto analyzer (Smartchem 200) (reagent dosage, 3.0 uL–300 uL; spectral range, 420nm–880nm; Alliance, France) following the Kjeldahl method  and molybdo‐vanado‐phosphate method , respectively, while K was determined using a flame spectrophotometer (FP6410, INESA Scientific Instrument CO., Ltd., Shanghai, China) . −1 The accumulation (mg pot ) of N, P and K in root, stem, leaf and panicle was com‐ puted as the product of the concentration multiplied by the tissue DW. The specific ab‐ −1 sorption rate (SAR, mg g root DW) was calculated as the ratio between total nutrient −1 accumulation in plant and root DW . N use efficiency (NUE, g grain mg N) was cal‐ culated as the ratio of grain yield and plant total N content . PUE and KUE were cal‐ culated via the same method. Agronomy 2021, 11, 2103 8 of 21 2.5. Statistical Analysis Variance and correlation analyses were performed using the SPSS 21.0 statistical analysis package (IBM, Chicago, IL, USA). Data from each sampling date were analyzed separately. Analysis of variance (ANOVA) was used to determine the significance of the differences between the means of different treatments on the morpho‐agronomic and nu‐ trient use related properties. Then sources of variation due to replication, year, drought, flooding, interactions of drought × flooding and interactions of year × drought, year × flooding and year × drought × flooding were analyzed. When a significant difference was found, a least significant difference (LSD) test was used to compare the treatment means. ’ The means were considered to be significantly different at p < 0.05. Pearson s correlation coefficient (r) was used to reveal the relationships among main root traits, grain yield, total nutrient uptake, specific absorption rates and nutrient use efficiencies in a combined analysis of data over the three years. In the practice of different water stresses, it is crucial to establish and apply the rela‐ tionship between water stress intensity and plant characters. Therefore, a commonly used method called crop relative growth stress index (RGSI)  was adopted in the present work and calculated as follows: where is the relative growth stress index, and 𝑋 and 𝑋 are the water stresses and control growth characters, respectively, in this study. Thus, the loss ratio of a crop (RR) can be calculated as follows: 1𝑅𝐼𝑆𝐺 100% (1‐ ) 100% 3. Results 3.1. Morpho‐Agronomic Traits 3.1.1. Biological Yield Statistical analyses showed significant differences (p < 0.01) in biomass (root, stem, leaf and panicle), grain yield and its components (spikelets per panicle and FGs) among different drought levels, flooding levels and drought × flooding interactions in 2016–2018. Only panicle numbers under different water levels were not significant (Supplementary Table S1). These traits were not significant (p > 0.05) among year × drought levels. How‐ ever, among year levels, year × drought levels, year × flooding levels and year × drought levels × flooding levels, those characters apart from the DWs of root, stem and leaf, as well as panicle numbers were significant (p < 0.05), which might be due to the increased pre‐ cipitation, mean air temperature, sunshine hours and mean vapor pressure in July in 2017 and 2018 (Figure 2), leading to the early appearance of panicles. This condition increased the probability of a decrease in spikelets per panicle and seed setting rates during the later stage of growth (Table 2). Table 2. Biological yield and its components of Longliangyouhuazhan (Indica hybrid cultivar) under different water stresses groups at maturity. Biomass (Partitioning) Yield and its components Treatment Root DW Stem DW Leaf DW Panicle DW Root/Shoot Panicles Spikelets Filled grains Yield g/pot (%) g/pot (%) g/pot (%) g/pot (%) g/g /pot /panicle % g/pot Control 18.6 (5.6) A 126.7 (38.2) C 42.3 (12.7) B 144.2 (43.5) A 0.0592 A 30.3 A 241.9 A 76.8 C 137.9 A DFAA 13.0 (4.3) D 139.6 (46.2) B 46.4 (15.4) A 103.0 (34.1) C 0.0447 C 31.0 A 166.7 C 79.0 B 96.8 C Drought alone 14.8 (4.9) C 111.2 (37.2) D 42.4 (14.2) B 130.4 (43.7) B 0.0520 B 30.9 A 186.9 B 85.2 A 124.4 B Flooding alone 15.5 (4.9) B 167.9 (53.4) A 45.4 (14.5) A 85.4 (27.2) D 0.0514 B 30.2 A 156.6 D 65.2 D 78.8 D Notes: DFAA, drought–flood abrupt alternation group. DW, dry weight. Each value represents the average value for each water stress group in three years. Different letters indicate statistical significance at the p = 0.05 level within the same column. The values in parenthesis for each trait refer to the partitioning ratios of the biomass compositions. 𝑅𝑅 𝑅𝐺𝑆𝐼 𝑅𝐺𝑆𝐼 Agronomy 2021, 11, 2103 9 of 21 Drought and flooding caused interactive effects on the reduction of rice biomass pro‐ duction (Table 2). Three kinds of water stresses (D, F and DFAA) had significant inhibition effects (p < 0.05) on the accumulation of dry matter in root and shoot. On average, the total DW of D, F and DFAA treatments decreased by approximately 9.9%, 5.3% and 9.0%, respec‐ tively. Root DW of D, F and DFAA treatments decreased by approximately 20.7%, 16.4% and 30.0%, whereas shoot DW decreased by approximately 9.3%, 4.7% and 7.7%, respec‐ tively, compared with the treatment of control. Among different combinations of drought and flooding, the reduction effect of mild drought + light flooding (e.g., DFAA7) on total DW was less than that of severe drought + heavy flooding (e.g., DFAA2). A higher stem DW was observed in F and DFAA treatments by 32.5% and 10.2% compared with control treat‐ ment, while for D treatments, stem DW decreased by 12.2%. The reduction in the root DW was significant (p < 0.05) in most cases, except for individual treatments in which waterlog‐ ging was less severe, such as in DFAA3, F7 and F9. Compared with the two other water stresses (D and F), DFAA decreased the root DW level by approximately 11.8% and 16.3%, respectively, indicating that the subsequent flooding caused superimposed damage to the pre‐drought stressed roots. Notably, sudden increased root DW in F7 and F9 revealed the existence of overcompensation effects after mild flooding (Table 2). Differences in root DW and shoot DW among different water treatments led to a sig‐ nificant difference in root/shoot ratios (p < 0.05; Supplementary Table S1). By contrast, DFAA reduced the root/shoot ratio most (−23.8%, on average compared with control), fol‐ lowed by D (−12.6%) and F (−11.85%), indicating that the subsequent ﬂooding did not compensate for the effects of preceding drought on the balance of root and shoot growth, but rather further aggravated such effects. Among different plant parts, root DW partitioning was lower under the DFAA treat‐ ments (4.3%) than under the control treatment (5.6%). Comparable values were found in the root DW partitioning between D (4.92%) and F (4.93%) treatments and in the Panicle DW partitioning between D (43.7%) and control (43.5%) treatments. Remarkable increases were detected in stem and leaf DW partitioning among DFAA and F treatments, while that of D treatments was the opposite. Compared with control, DFAA and F treatments decreased DW distribution in the panicle by 9.4% and 29.0%, while D treatments increased by 0.2%. All three water stresses (D, F and DFAA) tended to reduce the grain yield of rice, among which F had the greatest reduction effect (−42.8%), followed by DFAA (−29.8%) and D (−9.8%). The loss of yield under water stress may be directly related to the reduction of the number of spikelets per panicle (−31.1%, −22.8% and −35.3% for DFAA, D and F, respectively). Drought alone increased the number of filled grains by 11.0%, whereas the flooding alone decreased it by 15.1%. The co‐incorporated environments of drought and flooding contributed to an increase of 2.8% in the proportion of filled grains under DFAA treatments (Table 2). 3.1.2. Root Morphology RLD, RMD, SRL, RSA, RV, S/V ratio and maximum root depth and adventitious root numbers showed significant differences (p < 0.05) under different water stresses (Figure 3). Compared with control treatment, water stresses significantly inhibited root morpho‐ logical growth, for example, RLD treated by DFAA, D and F decreased by 38.2%, 15.8% and 29.7% respectively at the end of water stress, and 18.0%, 0.7% and −18.5% respectively at maturity (Figure 3a). The effects were prominent under prolonged drought + long‐term deep flooding conditions (e.g., DFAA9). While SRL treated by DFAA, D and F increased by an average of 24.1%, 18.7% and −9.2% respectively at the end of water stress, and 12.1%, 20.9% and 23.9% respectively at maturity (Figure 3a,b). This finding may be attributed to the reduced RMD as it contributes to the increased RL per unit root biomass. The subse‐ quent flooding failed to compensate for the effects of previous droughts on RMD, espe‐ cially when the severe drought lasted too long, such as in DFAA3. Agronomy 2021, 11, 2103 10 of 21 DFAA Drought alone Flooding alone 2.00 (a) At the end of DFAA 1.75 1.50 1.25 1.00 0.75 0.50 0.25 0.00 -0.25 Max. root Adventitious RLD RMD SRL RSA RV S/Vratio roots depth 2.00 At maturity (b) 1.75 1.50 1.25 1.00 0.75 0.50 0.25 0.00 -0.25 Max. root Adventitious RLD RMD SRL RSA RV S/Vratio depth roots Figure 3. Changes of relative values of rice root traits under different water stresses (a) at the end of drought–flood abrupt alternation (DFAA) and (b) at maturity. Root traits include root length den‐ −3 −1 sity (RLD, cm cm ), root mean diameter (RMD, mm), specific root length (SRL, m g ), root surface 2 −1 3 −1 area (RSA, cm pot ), root volume (RV, cm pot ), the ratio of root surface area and root volume 3 −3 −1 (S/V ratio, cm cm ), maximum root depth (cm) and adventitious root numbers (no. pot ) under different water treatments. The boxes represent the range of relative values in rice root traits. Round dots (●) in the boxes represent the means for each group. The up arrow (↑) refers to the means of water stress groups greater than the value of the normal group; the down arrow (↓) refers to the means of water stress groups lower than the values of normal group; the flat arrow to the right (→ ) refers to the means of water stress groups comparable to the values of normal group. The changes of RSA, RV and adventitious root numbers were consistent with that of RLD (Fig. 3). Regression analysis indicated that RSA was significantly correlated with root DW, RL and adventitious root numbers (r = 0.564**, 0.825**, 0.459**, n = 78). Under the same drought degree (%FC, such as D1, D2 and D3), RSA first increased and then decreased, and RV always decreased, but adventitious root numbers had non‐significant difference with prolonged drought duration. Under incomplete flooding conditions, RSA, RV and the num‐ ber of adventitious roots increased at maturity. However, under complete submergence (e.g., F9), RSA and RV increased, but the number of adventitious roots decreased. As for the maximum root depth, D increased it by 7.2% at the end of water stresses, whereas DFAA and F decreased it by 10.3% and 9.3% (Figure 3a). There was no significant difference (p > 0.05) found between DFAA and F treatments, indicating that drought stress promoted the development of deep roots, while flooding stress limited it. 3.2. Accumulation and Partitioning of N, P and K Drought and flood stress affected the concentration, accumulation and distribution of N, P and K, and then affected the effective utilization of them. The concentrations of N, P and K in the tissues from water stress to maturity were statistically different, except for the panicle (p < 0.05, Figure 4a–c). At maturity, the K concentrations were not significant in the panicle among the various groups (p > 0.05, Figure 4f). Nevertheless, the differences of N, P and K concentration in root, stem and leaf were still highly significant (p < 0.05). Water stresses (D, F and DFAA) tended to increase N concentration in shoot tissues (apart from stem in D) at maturity. Compared with control treatment, panicle N concentration Relative values to control treatment Relative values to control treatment Agronomy 2021, 11, 2103 11 of 21 in DFAA, D and F groups increased by 21.5%, 5.2% and 27.0%, on average, respectively (Figure 4d). N concentration in the root was reduced by D and completely underwater treatments, but it was increased by light flooding (e.g., F7). The co‐effect of severe drought and heavy flooding tended to decrease root N concentration in DFAA treatments. In con‐ trast, drought reduced P concentration in organs more than flooding, especially in panicle (Figure 4b,e). K concentration decreased in the root under three water stresses, and the decrease was proportional to the flooding duration (Figure 4c,f). At maturity, the distri‐ bution of K concentration in the organs of DFAA treatments was obviously lower than the normal value, but most of them were between the D and F treatments. It indicated that the compensation effect existed between pre‐drought and post‐flood stress. At the end of DFAA At maturity DFAA Drought alone Flooding alone DFAA Drought alone Flooding alone 2.5 1.75 (a) (d) 2.0 1.50 DFAA1,DFAA3 1.5 1.25 1.0 1.00 D4,D7,D8 D3,D6,D9 0.5 0.75 DFAA1,DFAA5 0.0 0.50 Root Stem Leaf Panicle Root Stem Leaf Panicle 1.75 DFAA1, F1,F5,F9 2.5 DFAA5, (b) (e) DFAA9 1.50 F9 DFAA7,DFAA8 D2,D3 2.0 1.25 F2,F6,F7 1.5 D7,D8 D7,D8 1.00 1.0 0.75 DFAA1 DFAA5, 0.5 0.50 DFAA9 F1,F5,F9 0.25 0.0 Root Stem Leaf Panicle Root Stem Leaf Panicle 2.0 2.0 F6,F7 (c) (f) DFAA1,DFAA2, DFAA3 1.5 DFAA7 1.5 D2,D3 D4,D5 DFAA1,DFAA5 1.0 1.0 DFAA7,DFAA8 0.5 0.5 0.0 0.0 Root Stem Leaf Panicle Root Stem Leaf Panicle Figure 4. The relative value changes of rice tissue concentrations of nitrogen (N), phosphorus (P) and potassium (K) under different water stresses (a–c) at the end of drought–flood abrupt alternation (DFAA) and (d–f) at maturity. The relative values plotted on the y‐axis were calculated by the ratios of water stress groups to the normal group. The boxes represent the range of relative values in rice root traits. Round dots (●) in the boxes represent the means for each group. The ellipses plotted over the bars refer to some outstanding treatments, marked with the arrows and text next to the side. Amounts of N, P and K taken up by plants among different water treatments were highly variable (Figure 5a,c,e). Compared with control, the total N accumulation under drought alone and flooding alone decreased by 7.4% and 4.1%, respectively. However, this trend was not observed in DFAA. The combination of drought and heavy flooding, such as in DFAA1, DFAA5 and DFAA9, seemed to be conducive to N accumulation in plants, especially in the stem (Figure 5a). By contrast, all three water stresses tended to reduce the total P accumulation, with a mean reduction of 19.6% in DFAA, 25.7% in D and 29.5% in F, respectively (Figure 5c). Furthermore, the total K accumulation decreased by 13.5% in D, 12.1% in F and 10.2% in DFAA (Figure 5e). Under some treatments, nutrient uptake exceeded that of the normal group. The compensation effects after water stresses may be the reason for the increased total N of F6 (50% submergence 7 days, especially in panicle) and total K of DFAA7 (70% FC 5 days+50% submergence 5 days, especially in stem). Relative values of K concentration Relative values of P concentration Relative values of N concentration Relative values of K concentration Relative values of P concentration Relative values of N concentration Agronomy 2021, 11, 2103 12 of 21 (a) Root Stem Leaf Panicle (b) Root Stem Leaf Panicle a a a a b b 4800 a b a a a c a a a a c b b a b b b c 300 c c b b b b b c a a c b b b 4 a b b a a b a a a a (d) Stem Leaf Panicle Root Stem Leaf Panicle Root 700 (c) a b b a b a 500 a a b c b b c c a c b c 12 c b b 2 c b b a a c b b b b a a a b b b a b b a 18 a a a a (f) Root Stem Leaf Panicle Root Stem Leaf Panicle 4500 (e) a a a 95 3600 a b a b a a a a c c a b b c b c 2700 c 30 c c b 1 c b c b b b b b b b b b a a a a a b a a 45 a a 0 Figure 5. The accumulation (a,c and e) and partitioning (b,d and f) of tissue nitrogen (N), phosphorus (P) and potassium (K) in rice under different water stresses at maturity. Each treatment was performed on means of three years (n = 9 for DFAA1–DFAA9, D1–D3, D7–D9, F1–F3 and F7–F9, n = 6 for D4–D6 and F4–F6). Different letters indicate the significant difference at 0.05 level. DFAA, drought followed by flooding; D, drought followed by no flooding (drought alone); F, no drought followed by flooding (flooding alone). When different tissues were compared, the percentages of N, P and K in stem and panicle were higher than those in roots, irrespective of moisture treatment (Figure 5b,d,f). In most drought alone instances, the percentages of N and P were higher in panicles but lower in stem and root than those in the control treatment. Moreover, drought tended to increase the accumulation of K in stem but decreased it in the other tissues. In most flood‐ ing alone instances, the percentages of N, P and K were lower in panicles but higher in stem and leaf compared with the control treatment. When moisture treatments were com‐ pared, panicle N, P and K content percentages of DFAA tended to be lower than those of drought alone, but higher than those of flooding alone. The opposite result was observed in the stem of DFAA. All water stress treatments tended to reduce the percentages of N and K content in roots. However, root P content percentage seemed to increase in DFAA and F treatments, but decreased in D treatments. 3.3. N, P and K Uptake and Use Efficiencies The effects of year, drought (D), flooding (F) and the interactions of Y × F, D × F and Y×D × F on SARs (SAR‐N, SAR‐P and SAR‐K), nutrient use efficiencies (NUE, PUE and KUE) and nutrient ratios (N:P, N:K and K:P) were significant (p < 0.05). Only the effect of Y × D on all above traits and the effect of year on SAR‐K and N:P were not significant (p > 0.05; Supplementary Tables S2 and Table 3). Compared with the control, SAR‐N, SAR‐P -1 -1 -1 N accumulation (mg pot ) K accumulation (mg pot ) P accumulation (mg pot ) Control Control Control DFAA1 DFAA1 DFAA1 D1 D1 D1 F1 F1 F1 DFAA2 DFAA2 DFAA2 D2 D2 D2 F2 F2 F2 DFAA3 DFAA3 DFAA3 D3 D3 D3 F3 F3 F3 DFAA4 DFAA4 DFAA4 D4 D4 D4 F4 F4 F4 DFAA5 DFAA5 DFAA5 D5 D5 D5 F5 F5 F5 DFAA6 DFAA6 DFAA6 D6 D6 D6 F6 F6 F6 DFAA7 DFAA7 DFAA7 D7 D7 D7 F7 F7 F7 DFAA8 DFAA8 DFAA8 D8 D8 D8 F8 F8 F8 DFAA9 DFAA9 DFAA9 D9 D9 D9 F9 F9 F9 Distribution of N (%) Distribution of P (%) Distribution of K (%) Control Control Control DFAA1 DFAA1 DFAA1 D1 D1 D1 F1 F1 F1 DFAA2 DFAA2 DFAA2 D2 D2 D2 F2 F2 F2 DFAA3 DFAA3 DFAA3 D3 D3 D3 F3 F3 F3 DFAA4 DFAA4 DFAA4 D4 D4 D4 F4 F4 F4 DFAA5 DFAA5 DFAA5 D5 D5 D5 F5 F5 F5 DFAA6 DFAA6 DFAA6 D6 D6 D6 F6 F6 F6 DFAA7 DFAA7 DFAA7 D7 D7 D7 F7 F7 F7 DFAA8 DFAA8 DFAA8 D8 D8 D8 F8 F8 F8 DFAA9 DFAA9 DFAA9 D9 D9 D9 F9 F9 F9 Agronomy 2021, 11, 2103 13 of 21 and SAR‐K were increased by 47.9%, 31.8% and 32.8% in DFAA (except for DFAA3). Un‐ der drought alone treatments, SARs were also higher than those of the control, but this trend was not as evident as that of SAR‐P and SAR‐K in flooding alone treatments. Nota‐ bly, SAR‐N tended to be reduced by short‐term light flooding (F7) or too long heavy flood‐ ing (F9), while SAR‐P and SAR‐K tended to be reduced by most cases. Regression analysis showed that SAR‐N, SAR‐P and SAR‐K had a strong negative correlation with root DW, RLD and RSA (r = −0.592**~0.894**) but a positive correlation with SRL (r = 0.098~0.129; Table 4). These results indicated that the plastic change of the root system greatly affected the nutrient absorption capacity. Moreover, SAR‐N, SAR‐P and SAR‐K also showed a pos‐ itive correlation with grain yield (r = 0.108~0.348). A clear negative relationship was observed between nutrient use efficiencies and SARs (Table 3). Compared with the control, the three moisture regimes exhibited a differ‐ ent pattern of response to the nutrient utilization. NUE decreased by 2.5%, 27.9% and 43.4% on average in drought alone, DFAA and flooding alone treatments, respectively. KUE showed a similar trend to NUE among different treatments, while PUE performed differently. Under drought alone conditions, PUE increased by 1.6%–30.7% compared with control treatment, while under flooding alone conditions, PUE decreased by 4.5%– 75.5% (except for some light flooding cases, e.g., F3, F6 and F7). Regarding DFAA treat‐ ments, pre‐drought tended to weaken the effect of subsequent flooding on PUE, because −1 their mean values (121.4 g g ) were higher than those in flooding alone treatments (89.2 g −1 g ). In most DFAA instances, the nutrient use efficiencies were higher than those of F but lower than those of D even though there was a higher SAR (Table 3). Similar to SARs, the morphological characteristics of rice roots also had a certain effect on the nutrient use ef‐ ficiencies (Table 4). NUE, PUE and KUE were negatively correlated with root DW, RMD and adventitious roots (r = −0.156~−0.542**), but were correlated with SRL, RSA and max‐ imum root depth (r = 0.202~0.530**). Notably, there was a very significant positive corre‐ lation between grain yield and nutrient use efficiency (r = 0.801**~0.926**, Table 4 and Figure 6). Table 3. Specific absorption rates (SAR), nutrient use efficiencies (NUE, PUE and KUE) and nutrient ratios in rice under different water stresses at maturity. Specific Absorption Rates Use Efficiencies Nutrient’s Ratios Treatment mg nutrient/g root DW g grain/g nutrient mg/mg SAR‐N SAR‐P SAR‐K NUE PUE KUE N:P N:K K:P Control 225.3 C 28.4 C 162.0 D 33.5 A 140.3 B 46.5 A 4.12 D 1.39 B 3.12 D DFAA 334.4 A 34.7 A 220.1 A 24.0 B 121.4 c 36.7 C 5.13 A 1.54 A 3.36 B Drought alone 266.7 C 29.2 B 211.6 B 32.5 A 162.7 A 42.2 B 5.04 B 1.30 B 3.98 A Flooding alone 272.7 B 24.9 D 178.5 C 19.5 C 89.2 D 29.4 D 4.57 C 1.55 A 2.89 C Notes: DFAA drought–flood abrupt alternation group. Specific absorption rates, the ratio of root length and root DW, m −1 g ; DW, dry weight. Each value represents the average value for each water stress group in three years. Different letters indicate statistical significance at the p = 0.05 level within the same column. Agronomy 2021, 11, 2103 14 of 21 (a) (b) (c) (d) Figure 6. Relationships of (a) relative total nutrient content (RTN, RTP and RTK) and relative grain yield (RGY), and (b– d) relative nutrient use efficiencies (NUEc, PUEc and KUEc) and RGY at maturity in 2016–2018. RTN, relative total N content; RTP, relative total P content; RTK, relative total K content. “NS” means not significant; ** indicates significant differences at 0.01 probability levels. DFAA, drought followed by flooding; D, drought followed by no flooding (drought alone); F, no drought followed by flooding (flooding alone). Table 4. Correlation analysis of the main morpho‐agronomic traits at the end of water stresses with grain yield, total uptake of N, P and K, specific absorption rates (SAR‐N, SAR‐P and SAR‐K), nutrient use efficiencies (NUE, PUE and KUE) at maturity in 2016–2018. Total Total Total a Traits Grain Yield SAR‐N SAR‐P SAR‐K NUE PUE KUE N P K Grain Yield 1.000 0.268 0.397 0.423 * 0.108 0.240 0.348 0.926 ** 0.826 ** 0.801 ** Stem DW −0.856 ** 0.056 −0.154 −0.352 −0.046 −0.138 −0.300 −0.860 ** −0.792 ** −0.847 ** Leaf DW −0.623 ** 0.226 0.351 −0.226 0.200 0.345 −0.024 −0.617 ** −0.822 ** −0.622 ** Root DW 0.058 −0.130 0.031 −0.087 −0.894 ** −0.704 ** −0.720 ** −0.156 −0.234 −0.222 RLD −0.254 0.303 0.459 * 0.307 −0.700 ** −0.734 ** −0.620 ** 0.378 * 0.437 * 0.232 SRL −0.222 0.263 0.089 0.342 0.098 0.011 0.129 0.278 0.387 * 0.277 RMD −0.139 −0.507 ** −0.403 * −0.453 * −0.038 −0.143 −0.123 −0.380 * −0.542 ** −0.383 * RSA 0.180 0.203 0.232 0.110 −0.676 ** −0.702 ** −0.592 ** 0.287 0.251 0.305 Max. root depth 0.771 ** 0.391 * 0.568 ** 0.566 ** −0.140 0.017 0.234 0.483 ** 0.530 ** 0.202 Adventitious roots 0.048 −0.325 −0.022 −0.055 −0.075 −0.260 −0.085 −0.158 −0.253 −0.277 Notes: Data from different water stresses (control, DFAA, drought alone and flooding alone) in the three years of 2016– 2018 were included (n = 78). SAR‐N, SAR‐P and SAR‐K, specific absorption rates of N, P and K, respectively; NUE, PUE and KUE, use efficiencies of N, P and K, respectively; DW, dry weight; RLD, root length density; SRL, specific root length; RMD, root mean diameter; RSA, root surface area. * Significant at p < 0.05. ** Significant at p < 0.01. Irrespective of the moisture treatment (i.e., DFAA, drought alone or flooding alone), N:P ratios were larger than that of the control, and the mean value of DFAA was greater than that of drought alone but lower than that of flooding alone (Table 3). The effect of different water stresses on N:K was not significant (p > 0.05). DFAA, drought alone and flooding alone all tended to increase K:P, whose values in DFAA were lower than those in drought alone but were on par with those in flooding alone in most instances. Agronomy 2021, 11, 2103 15 of 21 4. Discussion 4.1. Co‐Occurring Drought and Flooding Altered Biomass Accumulation and Partitioning In terms of plant growth, our results highlighted the dramatic changes of rice biolog‐ ical yield and its root morphology, such as shoot and root DW, RLD, RMD, SRL, RSA, RV, S/V ratio, adventitious root numbers and maximum root depth. The root growth response was thought to be related to the difference of soil permeability under different water stresses . Under less soil moisture (drought stress), root penetration ability was im‐ proved with the increase of oxygen concentration in the up soil, thereby root depth and capillary lateral roots increased to improve their ability to absorb substantial soil water and nutrients . At the same time, the aboveground plants reduced their growth via‐ bility by reducing the leaf size, vegetative growth and other physiological traits, such as photosynthesis, which ultimately lead to the cumulative reduction of plant biomass . However, under the alternation from drought to flash deep flooding, the pre‐drought stressed roots had to adopt another adaptive strategy to cope with the sudden shift to an anaerobic environment . Internode elongation in stems [8,60] and an increase in the number of adventitious roots were observed at the end of most DFAA conditions (Figure 3). Although the aerenchyma developed well in rice roots, long‐term deep ponding water, especially complete submergence, hinders the exchange of gas between air and plant . 2+ The accumulation of toxic substances (e.g., Fe , H2S, CH4, organic acids) seriously poisons the root system and impairs its function . Thus, sudden flooding stress in the later stage may be very harmful to the capillary lateral roots induced by early drought stress , although the flooding resistant species actually develop a tolerance mechanism and well develop the morphology, physiology and anatomical structure and will develop the plant’s underground and above ground biomass under waterlogging submergence con‐ ditions . Therefore, most root morphological traits such as root DW, RLD, RMD and RSA in DFAA remained lower than those of the control, even lower than those of drought alone and flooding alone in most cases (Table 2 and Figure 3). Fortunately, an increase in SRL under DFAA conditions appeared to offer the possibility of increasing nutrient up‐ take per unit root DW (Figure 3B and Table 2). Undoubtedly, the abovementioned root plastic changes in DFAA will affect the absorption of water and nutrients, and then affect the process of accumulation, translocation and allocation of the above‐ground biomass  ( Table 2; Table 4). Interestingly, the reduction effect of DFAA on root DW was greater than that of either drought or heavy flooding in isolation (−30.0%, −20.7% and −16.4% in DFAA, drought alone and flooding alone, respectively; Table 2). However, the effect of DFAA on stem and leaf DW tended to be positive (10.2% and 9.7% higher than that of control). From the dry matter partitioning (Table 2), the plant seemed to transfer more dry matter to stems and leaves than to panicles. This condition eventually resulted in a significantly lower root/shoot ratio under DFAA conditions (Table 2). This finding was consistent with that obtained by Feng and Luo  and Shao et al.  but not with that by Guo et al. . In the study of Guo et al., the root/shoot ratio gradually normalized during the recovery period after a short‐term decrease when DFAA occurred at the tillering stage. The differ‐ ences may be attributed to the different fertility stages in the occurrence of DFAA. How‐ ever, one thing in common is that the root DW decreased whether DFAA occurred at till‐ ering stage or at jointing–booting stage, whereas the shoot DW appeared to be reduced less, especially the stem DW, and may even increase [17,67]. This finding suggested that the root and shoot might have different adaptive mechanisms when DFAA occurred at the jointing–booting stage. The preceding drought increased the sensitivity of roots to the subsequent flooding, that is, the roots adopted some escape strategies, e.g., RLD became smaller and deep roots disappeared (Figure 3). For shoots, the response might be an es‐ cape mechanism  or a tolerance mechanism . Results seemed to indicate the latter, because the drought‐stressed stems tended to increase after the subsequent flooding (Ta‐ ble 2). Unfortunately, the above different adaptation mechanisms resulted in redundant Agronomy 2021, 11, 2103 16 of 21 growth of stem and leaf, which might be one of the reasons for the reduction of grain yield under DFAA conditions. 4.2. Co‐Occurring Drought and Flooding Altered N, P and K Uptake and Utilization The availability of N, P and K plays an important role in plant growth; nevertheless, the physiological factors in nutrient, soil, plant or root absorption sites may interact an‐ tagonistically or synergistically . Many studies have reported the single effect of drought or flooding on nutrient uptake in rice plants, e.g., nutrient element uptake de‐ creased when drought stress intensity increased , while under deep flooding condi‐ tions, the N content increased and P and K contents decreased [27,28]. Moreover, both increases and decreases in NUE have been reported under alternate wetting and drying + − irrigation [41,69]. Due to NH4 being the main source of N in flooded soils, and NO3 being + − more common in drought soil, the cooperation of NH4 and NO3 can improve the growth + − and yield significantly compared to growth on either NH4 or NO3 alone of equal amount . Rice plants with DFAA seemed to benefit more than with control and flooding alone. Indeed, the total N content of the plant in DFAA was comparable with the normal group (Figure 5a). However, a significant shift in N partitioning was observed in favor of DFAA to the stem and leaf (luxury consumption), with panicle N partitioning that was smaller (Figure 5b). In addition, a significantly lower NUE in DFAA than drought alone in this study indicated that the consequent flooding stress was more severe and caused a greater inefficient utilization of N compared with drought alone (Table 3). This finding is sup‐ ported by previous pot experiments conducted in Nanjing, China, where both N uptake and NUE in rice of Nanjing 44 were reduced when DFAA occurred at tillering stage . Even though panicle N and P concentrations in DFAA were higher than those in Control in most cases and panicle K in DFAA was comparable with that in control (Figure 4), panicle N, P and K content were reduced (Figure 5). This indicates that the reduced N, P and K contents of the panicle in DFAA treatments were mainly attributed to the reduced panicle DW (Table 2). When total DW of DFAA at maturity was 91.04% of that in control, the total N in DFAA was 98.13% of that in control while the corresponding values for P (80.40%) and K (89.77%) contents were lower (Table 2 and Figure 5). The reduced P and K contents, especially the P content in DFAA in comparison to control indicate the greater sensitivity of P uptake to this transient soil water environment of drought and flooding. This is mainly because P in soil is mostly immobile and unavailable to plants, and further restricted when moisture stress occurs . Additionally, once P is absorbed, plants may improve the use efficiency of P by translocating P from senescent tissues to tissues with greater demand . Supporting this contention, PUE (−10.81%) was reduced less by DFAA relative to NUE (−27.88%) and KUE (−19.74%) in this study (Table 3). Apparently, NUE, PUE and KUE varied with the different combinations of drought and flooding, and the subsequent flooding tended to aggravate the effect of pre‐drought on the availability of N, P and K because lower nutrient use efficiencies were observed in DFAA than that in drought alone. However, due to the existence of a compensation effect between drought and flooding, the nutrient use efficiencies in DFAA were higher than that in flooding alone (Table 3). As the plants were cultured in pots in this experiment and the water in the pool was static without leakage or drainage, soil water stress may not have restricted the avail‐ ability of N, P and K to rice roots. Therefore, further research will be carried out in the field to understand the actual growth of field crops more accurately. 4.3. Influence of Root Plasticity on N, P and K Uptake and Utilization Under DFAA conditions, the rice plant tried to reduce its root size to avoid the re‐ dundant consumption of nutrients (Figure 3), whereas the absorption capacity of roots was significantly improved (p < 0.05) to maintain the nutrient supply to the aboveground parts as much as possible (Table 3). This response is a remarkable manifestation of plant self‐regulation to adapt to the changing environment [71,72]. The specific absorption rates of N, P and K in most DFAA conditions were significantly higher than those in drought Agronomy 2021, 11, 2103 17 of 21 alone and flooding alone conditions (Table 3 and Supplementary Table S2). However, if the degree of DFAA is too heavy, such as in DFAA3, with a long‐term severe drought + deep flooding, the absorptive capacity of roots will be limited due to a serious decline in root activity . There was a significant negative correlation between root traits (root DW, RLD, RSA) and SARs (SAR‐N, SAR‐P and SAR‐K; Table 4). This view that small root systems under transient soil moisture do not limit the absorption capacity of roots has also been confirmed in many previous reports [31,39,74,75]. Moreover, according to the corre‐ lation analysis (Table 4), root plasticity did not seem to affect the final total N, total P and total K contents at maturity. However, nutrient use efficiencies decreased in most DFAA cases although the root absorptive capacity increased (Table 3). From Figure 6 and Table 4, we found that there was a strong positive correlation between nutrient use efficiencies and GY, which indicated that the reductions of nutrient use efficiencies in DFAA were mainly driven by the decrease in GY, because there was almost no difference in variation of nutrient uptake with the variations of GY (Figure 6a). This conclusion is not very con‐ sistent with the point of Ye et al. , who proposed increased nutrient uptake with in‐ creased GY and decreased nutrient use efficiency with increasing GY. This difference was mainly due to the combination of drought and flooding in different degrees. Zhang et al.  also demonstrated that a moderate alternate wetting and drying could improve root growth, facilitate the reuse of stored carbon to cereals, accelerate grain filling and promote grain yield, while in our study, the opposite trend was observed due to the fact that DFAA had a stronger degree of drought or flooding (Supplementary Tables S1 and S2). Notably, there were significant breakpoints in the relationship between relative PUEc or KUEc and relative GY (RGY; Figure 6c,d), but not between relative NUEc and RGY (Figure 6b). This may be related to the imbalance of N, P and K absorption (Table 3). The content ratios of N:P, N:K and K:P under water stresses, except N:K under drought alone and K: P under flooding alone, were all higher than that of control. Thus, the importance of P in the yield‐forming process of rice under DFAA increased (i.e., uptake of P was much smaller than that of N and K), which is in accordance with the viewpoint of Somaweera et al. . Additionally, correlation analysis revealed a positive correlation between max‐ imum root depth and NUE (r = 0.483**), PUE (r = 0.530**) and KUE (r = 0.202). Therefore, the abundance of N and K in DFAA‐stressed plants may improve P use efficiency. Thus, further research is needed to study how to reduce the impact of this extreme climate on rice growth through some fertilizer measures or oxygen release agent in actual practice during post‐DFAA recovery periods. 5. Conclusions The present study aimed to investigate the interaction of drought and flooding on root growth and nutrient absorption in rice. Several indicators reveal that roots and shoots may adopt different adaptation mechanisms when DFAA occurs. Roots seemed to adopt an escape strategy, whereas shoots tended to adopt a tolerance strategy. Compared with drought alone and flooding alone, DFAA tended to induce a smaller root structure, such as the smaller number of roots DW, RLD, RMD, RSA, RV and adventitious roots, and a larger crown, such as the increased accumulation in stem and leaf biomass (10.2% and 9.7%). However, grain yield in DFAA was ultimately reduced by 29.8% as a result of the reduced nutrient uptake and utilization efficiencies of N, P and K. Among the DFAA‐ stressed plants, total P decreased by 19.6%, followed by total K (−10.2%) and total N (−1.9%), which highlighted the importance of P in the yield‐forming process of rice. There‐ fore, our results suggest that post‐drought exposure to flooding may impede the root up‐ take of P, thus hindering root growth and organ biomass redistribution, thereby reducing rice yield and nutrient availability. Therefore, fertilization application measures under DFAA conditions are the urgent problem to be studied in order to adapt to the future changing climate and soil environment. Agronomy 2021, 11, 2103 18 of 21 Supplementary Materials: The following are available online at www.mdpi.com/2073‐ 4395/11/11/2103/s1, Table S1: Biomass, yield and its components of Longliangyouhuazhan (Indica hybrid cultivar) under different water stresses at maturity, Table S2. Specific absorption rates, nu‐ trient use efficiencies and nutrient’s ratios of Longliangyouhuazhan (Indica hybrid cultivar) under different water stresses at maturity. Author Contributions: Conceptualization, J.H., T.H. and F.W.; investigation, J.H.; writing—original draft preparation, J.H.; resource, J.L.; writing—review and editing, T.H., J.W., X.W. and C.L.; super‐ vision and funding acquisition, L.L. and F.W. All authors have read and agreed to the published version of the manuscript. Funding: This research was funded by the National Natural Science Foundation of China (51709098, 52179022, 51339004 and 51909083); the National Key Research and Development Program of China (2018YFC1508305); the Financial Project of Hubei Province (2021‐218‐006‐001). Institutional Review Board Statement: Not applicable. Informed Consent Statement: Not applicable. Data Availability Statement: Not applicable. Acknowledgments: The authors are very grateful to the Xinmaqiao Comprehensive Experiment Station of Irrigation and Drainage for providing the study site and meteorological data. In addition, all of the authors sincerely thank the anonymous reviewers for their review and helpful comments. Conflicts of Interest: The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manu‐ script, or in the decision to publish the results. 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Agronomy – Multidisciplinary Digital Publishing Institute
Published: Oct 20, 2021
Keywords: drought; flood; root growth; N, P and K; grain yield