Integrating Non-photochemical Quenching (NPQ) Measurements for Identifying Flood-Tolerant Soybean Genotypes in the Era of Climate Change

Climate change has negatively affected agriculture worldwide, including soybean production. Studies have shown that rising temperatures and extreme weather events like droughts and floods significantly reduce soybean yields. Developing flood-tolerant soybean genotypes is crucial for ensuring food security. Conventional breeding programs are limited by laborious and imprecise visual rating methods for flooding tolerance identification. High-throughput platforms for plant phenotyping using imaging techniques offer potential solutions


Introduction
Globally flooding is one of the most damaging abiotic stresses, which affect approximately 17 million km 2 of land surface annually (Kaur et al., 2020).Climate change has been causing negative impacts on agriculture around the world, increasing impacts of biotic and abiotic stress on plant species (Brito et al., 2011(Brito et al., , 2014;;Diola, Brito, Caixeta, Pereira, & Loureiro, 2013;Pereira et al., 2022) and soybean production is no exception.Studies have demonstrated the negative impacts of climate change on soybean grain yield around world, including the waterlogging (Adegoye et al., 2023;Zhao et al., 2017).Flooding duration and growth stages are important variables which can significantly reduce soybean yield (Scott, Deangulo, Daniels, & Wood, 1989).Waterlogging imposing in critical growth period can impair root development, hinder nutrient uptake, and induce oxygen stress, all of which negatively affect overall plant health and productivity.According to Shen and co-workers (Shen, Jiao, Yuan, & Su, 2023) the critical flooding duration leading to decreases the number of pods, dry mater and grain yield is three days during the flowering-podding stage and for 100-grain weight is six days.During the reproductive phase, flood events lead to disrupts flower and pod formation, reduces seed set, and increases susceptibility to diseases and pests.To mitigate these adverse effects, improved drainage systems and the development of flood-resistant soybean varieties are essential for sustainable soybean production (M.C. Lai, Z. Y. Lai, Jhan, Y. S. Lai, & Kao, 2021;Yijun et al., 2022).
Waterlogging treatment for two days could reduce soybean yield by 27% (Linkemer, Board, & Musgrave, 1998), showing the fast effects of flooding on molecular and biochemical/physiological responses of crop and its negative impacts on plant yield components.During the vegetative stage flooding can reduce the soybean yield by 17 to 43%, whereas at the reproductive growth stage, the yield losses can reach 50 to 56% (Ye et al., 2018).As such, there is a need to develop new strategies to identify soybean genotypes that are more tolerant to flooding conditions and put them into breeding programs routine.
For a conventional soybean breeding program, taking into account its size, hundreds or thousands of plants are generated from cross between one parent from elite cultivars and another from naturally selected soybean genotype and evaluated under flooding environments.Soybean genotypes showing some flooding-tolerant trait associated to high-yield potential could be visually identified by a trained breeder's eye (Foyer et al., 2016).Although an experienced breeder can use a visual rating to identify genotypes showing low ratio of injuries caused by flooding stress under field conditions, this process is laborious, time-consuming, subjective to human bias and commonly insufficiently precise to be suitable and routinely implemented into breeding programs.Additionally, the development of an efficient, effective, an unbiased tool to quantify flooding injuries (Zhou, et al., 2021) is the key to reduce the existing gap between our capacity to associate routinely fine phenotyping tools to the genotyping in large scale and at low costs.
Nowadays, the rapid progression of genomic protocols, devices and low costs has leading an increasing number of plants genomes sequenced making available dozens of genes influencing key agronomic traits, including those related to yield components, tolerance to biotic and abiotic stress.On the other hand, these sequences has not been potentially exploited for understanding its complex functionality and interactions, owing to a lack of crop phenotypic data (Jin et al., 2021).Thus, the development of accurate tools that allow a fine phenotyping in large-scale and at low cost could lead to improve considerably the robustness and resolution of structural genomics approaches and genome-wide associations' studies.Thus, the unavailable of high-throughput phenotyping yet could be considered the main bottleneck for crop breeding (Feng, Chen, C. Zhang, Y. Zhang, & He, 2021).
In recent years, high-throughput platforms for plant phenotyping that use imaging techniques have become increasingly popular.These platforms use advanced imaging technologies to capture images of plants at different stages of growth and development.The images are then analyzed using computer vision algorithms to extract quantitative phenotypic data.However, despite their potential, these platforms suffer from a significant limitation, they do not provide any information on the underlying physiological mechanisms that drive plant growth and development.This lack of understanding of the physiological mechanisms that drive plant phenotypes is a major bottleneck in high-throughput phenotyping platforms (HTPPs).However, non-photochemical quenching (NPQ) offers an alternative approach to overcome these limitations, enabling the integration of physiological measurements with HTPPs to identify suitable plant varieties for breeding and phenotyping in large scale.In sense, this approaching could be applied to improving photosynthesis, being recently considered as a major opportunity to gain a jump in yield potential (Long et al., 2022;Souza et al., 2022).In summary, NPQ is a molecular adaptation which is considered the fastest response of the photosynthetic membrane to excess light (Barbara Demmig-Adams, Gyözö Garab, & Govindjee, 2014).This process is directly or indirectly associated to the events of light harvesting by the photosynthetic antenna complexes, their structure, captured energy transfer to reaction centers, electron transport, proton translocation across the membrane, ATPase activity, and carbon assimilation (Barbara Demmig-Adams et al., 2014;Ruban & Belgio, 2014;Walker, 1988).
NPQ is a proto-protective mechanism triggered by plant when exposed to full sunlight.This mechanism allow to the plants dissipate potentially damaging excess absorbed light energy, which is considered essential in avoiding the formation of reactive oxygen species that would damage the photosynthetic apparatus (Baker, 2008).On the other hand, this protective process is slow to relax during frequent sun-shade oscillations in crop canopy, occurring diary and across growth station.Depending on the dynamics presented by a given genotype, a substantial photochemical energy can be loss, ranging between 7.5 and 30%, which could be used for photosynthesis (Werner, Ryel, Correia, & Beyschlag, 2001;Zhu, Ort, Whitmarsh, & Long, 2004).In soybean plants, this NPQ relaxation dynamic during sun-shade oscillations can lead to cost bigger than 11% of daily carbon assimilation (Wang, Burgess, de Becker, & Long, 2020).Although NPQ process is constituted by various mechanism combining different relaxation kinetics sun-shade transition (Long et al., 2022;Malnoë, 2018), the energy-dependent quenching (qE) is the major and most rapidly triggered component, which can be measured after seconds up to a few minutes when leaves are exposed to high light conditions (Ruban, 2016).
Although the development of the pulse amplitude modulated (PAM) fluorescence technique opened new opportunities leading to a refining of the NPQ studies (Oxborough & Horton, 1988;Schreiber, 1986), only in recent years the advances in chlorophyll fluorescence imaging come up as a powerful tool to mine the activity of photosynthesis at cellular, leaf, and whole-plant scale (Pérez-Bueno, Pineda, & Barón, 2019).In some situations, protocols can be adapted to monitor photosynthesis activity of different variables simultaneously, allowing associate high-throughput and capture of physiological state of plants in a breeding program context.In this way, whether a given genotype can potentially display different capacity to dissipate the excess of light energy during sun-shade oscillations, our hypothesis based on "whether the measurements of NPQ dynamics in plants exposed to different light intensity and flooding regime could lead to the identification of superior genotypes, potentially more tolerant to flooding stress".
Thus, firstly a study was conducted to evaluate the flooding-tolerance of 160 genotypes indicated for low land areas of Rio Grande do Sul State, Brazil.In a second step, those soybean genotypes highlighting some flooding-tolerance trait associated to high-yield potential were selected to additional trial.Genotypes showing the best and worst performance for number of seeds per plant and 100-seeds mass were selected for a second experiment aiming monitor some physiological responses, including gas exchange e chlorophyll fluorescence variables to defining a suitable protocol in a context of breeding program.This could leading in the establishment of an approach able to phenotype in a relatively large-scale, associating high-yield trait with NPQ performance, when soybean plants are submitted to flooding conditions.

Growth Conditions and Genetic Materials for the First Trial
In the first trial, a test was conducted under semi-natural conditions using a structured low-cost facility designed for efficient water management during flooding and drainage, which is challenging under typical field conditions (Brito et al., 2022).The facility consisted of a series of fiberglass tanks connected by PVC pipes to a 500 L water reservoir, supplied with rainwater collected from the rooftops of two adjacent greenhouses.Each rectangular 500 L fiberglass water tank was equipped with independent valve-controlled water inlets and outlets, allowing precise flood and drainage control as needed (Figure 1).decision was based on its demonstrated higher tolerance during the initial growth phase of soybean development, as shown in previous studies (Goergen et al., 2023;IRGA, 2018).
An augmented block design (Federer & Raghavarao, 1975) was carried out for the evaluation of set of 160 genotypes, with 159 treatments without replicates, with 1 control (TEC IRGA 6070 RR) replicated in each of the block (fiberglass tank), so that the control cultivar was present in all fiberglass tank of the experiment.Each genotype was sowed at 0.5 m at row length at 0.4 m spacing.For the evaluation of soybean grain yield, five plants were harvested to grain yield measurements.The plot size was defined based on few seed availability in the Embrapa's germplasm bank.On the other hand, this ensured that seeds of all genotypes were multiplied in the same year.
At the establishment of experiment, the equivalent at 5 t ha -1 of lime at 0-20 cm was applied and incorporated, according to the soil analysis interpretation and local recommendations.In addition, Nutrient deficiency and soil acidity correction were conducted according to soil analysis results and local recommendations for soybean crops in order to avoid nutritional limitations and toxicity to plants.The K e P fertilization (80 kg K 2 O ha -1 and 120 kg ha -1 de P 2 O 5 ) were applied on the surface before sowing and, subsequently incorporated until 5 cm deep.
Soybean seeds were inoculated, using recommended dose (100 mL) of Bradyrhizobium japonicum (SEMIA 5079 E SEMIA 5080) at 5 × 10 9 units of colony formation mL -1 as concentration.The sowing of the experiment was done manually, after the area of each tank had been manually furrowed.Ten seeds were sown per plot and, at fifteenth day after emergence, thinning was performed to standardize the number of plant per plot.After thinning, the density was equivalent to 200,000 plants per hectare.
This set of genotypes were grown under semi-natural conditions, under nearly field capacity until plants reach between V 4 -V 5 growth development phase.Subsequently, all genotypes were submitted uniformly to flooding via water entry into the system (500 L fiberglass tanks connected by PVC pipes to a 5000 L water reservoir fed by rainwater collected on the rooftops of two adjacent greenhouses).Plants were maintained under flooding conditions by 96 h, at five centimeters water blade, when some genotypes starting showing yellowness leaves (showing signs of leaf chlorosis).After, a water drainage controller was triggered, allowing an effective and uniform water removal from the system, being at least visually that all tanks were completely drained after two hours from activating of controllers.
At harvesting, the grain weight per plant and the moisture content of the grain mass were attained from five plants per genotype.

Second Trial: Using Selected Genotypes and Chlorophyll Fluorescence Approaches
For this step, those genotypes that shown superior mass grain yield than TEC IRGA 6070 RR (a tolerant check), such as BRS 525, BT 93759 IPRO, 0580 IPRO, BS 2578 RR, 64HO130 I2X and 58I60 RSF IPRO were chosen for chlorophyll fluorescence approaches.In this step, the study aimed to test if there are some associations between the grain yield performance and its photoprotection capacity when submitted to flooding regime.As complement, three genotypes (BRS 6203, K 6022 IPRO and BA 5770 Xi) which shown the poorest grain yield performance were used to confirm this hypothesis.
Soybean plants were grown within a greenhouse; the experimental design followed a completely randomized design with three biological replicates.Each biological replicate consisted of two plants grown in a plastic pot filled with 3.0 dm -3 of peat (with an electric conductivity of 0.7±0.3,pH of 5.8±0.1, and water retention capacity of 80%, containing lime, N at 0.04%, P 2 O 5 at 0.04%, and K 2 O at 0.05%).In order to maintain all plants with the same light intensity and complement its required photoperiod, they were grown under natural light conditions plus artificial light supplementation, in order to ensure 14 h of light at approximately 400 μmol photon m -2 s -1 .The air temperature ranged from 26 °C during the day to 19 °C at night; Relative humidity as 60-80%.Four seeds were initially sown into each pot, and on the fifteenth day after emergence, thinning was performed to standardize the number of plants to two per plot.
The second experiment was conducted with plants maintained at 80% of field capacity until the V 4 -V 5 growth phase.After this phase, one group of plants was subjected to flooding, while another group of plants was kept as a control with 80% of available water capacity.At this growth phase (V 4 -V 5 ) they were submitted to flooding stress via a fiberglass tank (1.0 m width × 3.0 m length × 0.3 m height).The flooding treatment was imposing by a complete submersion by adding tap water to this container up to 25 mm above the soybean cotyledonary nodes.
In order to prevent pot buoyancy and ensure that plants remained completely submerged, wooden slats were screwed on top of the fiberglass tank.Pots of control plants were kept in the same environment, but substrate was maintained at 80% of field capacity for the duration of the experiment by watering regularly.
At two and four days after stress imposing, and seven days after water drainage (recovery period), the uppermost fully-developed leaf (central leaflet) was collected for chlorophyll fluorescence approaches.Using a cork borer, six leaflet disks per genotype were placed in a 96-well flat bottom tissue culture plate (FB012931, Fisher scientific, USA) using a forceps.All leaf disks were positioned with the adaxial surface of the leaf facing down on the plate.To maintain the humidity inside the well, wet paper towel disks were placed on botton of the well.
Plates were sealed with parafilm, packed inside a closed Styrofoam box, and kept for dark adaptation overnight.
The chlorophyll fluorescence measurements were taken the next day.
Nonphotochemical quenching (NPQ) adjustments to light fluctuations were quantified using a chlorophyll fluorescence imager, specifically the MAXI version of the Imaging-PAM fluorometer, M-series, and the Imaging Win software (Heinz Walz GmbH, Effeltrich, Germany).The Chl a fluorescence emission transients were captured by a CCD (charge-coupled device) camera with a resolution of 640 × 480 pixels.The leaflet disks containing soybean samples were carefully and individually fixed on a support at a distance of 18.5 cm from the CCD camera.To determine the initial fluorescence (F 0 ), the soybean leaflet disks were exposed to a weak, modulated measuring beam (0.5 μmol m -2 s -1 , 100 μs, 1 Hz), at which point the primary quinone (QA) electron acceptor of photosystem II (PSII) is oxidized, and most of the PSII reaction centers are considered "open".Next, a saturating white light pulse of 2,400 μmol m -2 s -1 (10 Hz) was applied for 760 ms to ensure the measurement of the maximum fluorescence emission (F m ) when the QA is maximally reduced, and PSII reaction centers are referred to as "closed".Following this, fluctuating light conditions were applied by illuminating the samples for 15 minutes at 1251 μmol m -2 s -1 , followed by 15 minutes at 36 μmol m -2 s -1 .During this period, repeated Fm' measurements were quantified by applying saturating pulses of 2,400 μmol m -2 s -1 every 40 seconds during the exposure to high light and every 90 seconds during the exposure to low light.
At the end of experiment, the Leaf area was measured using an LI-3100 area meter (LI-COR, Lincoln, NE) and plant height was quantified using a graduated ruler taking as reference measurements the length between the cotyledonary node and the apex of the apical bud; the total plant fresh weight was measured immediately after harvest procedures using a semi-analytical balance.

Statistical Analysis
For the first trial, which was conducted under an augmented block design, the mass grain yield (from five randomly harvested plants per row) was quantified for each genotype, and its average values are shown in a scatter graph in Figure 2. As highlighted in the figure, were chosen for the second experiment the genotypes that exhibited superior mass grain yield compared to TEC IRGA 6070 RR (recognized as a flood tolerant genotype) which were BRS 525, BT 93759 IPRO, 0580 IPRO, BS 2578 RR, 64HO130 I2X, and 58I60 RSF IPRO.As negative checks were chosen three genotypes (BRS 6203, K 6022 IPRO, and BA 5770 Xi) with the poorest grain yield.
The data from the second trial were subjected to analysis of variance using SigmaPlot version 15 (Systat Software Inc., San Jose, CA, USA).Additionally, the statistical significance of physiological (NPQ) and morphometric (leaf area and plant height) variables between flooded and control genotypes were determined using SigmaPlot version 15.When statistically significant differences were detected, appropriate statistical procedures were employed to quantify the effects of each genetic background in each time exposure and water regime.These analyses were done at two time of stress exposure (at 48 and 96 h) and at the end of its recovery period (seven days after water drainage).Subsequently, the Least Significant Difference (LSD) among the means was determined using the Student-Newman-Keuls test (p < 0.05).

Results
The authors decided to define a sequence of trials for the study to verify whether the genotypes that exhibited higher grain yield also demonstrated common responses to the photoprotection mechanism known as non-photochemical quenching.In this step of the study, 160 genotypes were subjected to a flooding regime when soybean plants reached the V 4 -V 5 growth phase, and this flooding condition was maintained for 96 hours (Figure 1).Initially, in Figure 2 the six genotypes (represented by blue points) with higher grain yields than the flooding-tolerant check named TEC IRGA 6070 RR (Irga, 2018;Goergen et al., 2023) were selected for the next phase of the study.Additionally, three genotypes (surrounded by an ellipse and represented by orange points) with the poorest grain yield were also chosen to be included in the next phase of the study.In the second step, as depicted in Figure 3, it is evident that the ten genotypes selected prior to the experiment displayed NPQ (non-photochemical quenching) responses corresponding to their grain yield performance observed during the first trial.Generally, under flooded conditions (Figure 3, Graphs B, D, and F), the three genotypes with the lowest grain yield during the first trial also exhibited a reduced capacity for protective dissipation of excess absorbed light energy as heat.Conversely, the seven genotypes that showed better grain yield performance exhibited higher values for non-photochemical quenching, indicating a greater capacity to dissipate excess light energy.
At 48 hours (Figure 3B) and at 96 hours (Figure 3D) after stress imposition, the BA 5770 Xi and BRS 6203 genotypes, which displayed lower grain yield, also demonstrated the lowest values for non-photochemical quenching.This trend was observed for both high light intensity (first fifteen minutes at 1251 µmol m -2 s -1 PFD) and low light intensity (36 µmol m -2 s -1 PFD), as mentioned in Graphs 3B, 3D, and 3F.
Seven days after water drainage (Figure 3F), the same tendency curves for sensitive genotypes are highlighted for those flooded plants, particularly for BA 5770 Xi and BRS 6203, which show the lowest capacity to dissipate excess energy, both under high and low light intensity.When examining the curves of the control plants (Figure 3E), it becomes evident that their lower light energy dissipation capacity could be associated with genes constitutively expressed or repressed in these two genotypes.This intrinsic trait could contribute to explain its grain yield performance (Figure 2).On the other hand, the BRS 525 genotype, which showed a higher grain yield capacity, also exhibited the highest energy dissipation capacity seven days after water drainage (Figure 3F).Generally, most of the genotypes that demonstrated higher grain yield (Figure 2) also exhibited the highest values of non-photochemical quenching at seven days after water drainage (Figures 3 and 4).
In Figure 4, regardless of light intensity (high 1251 µmol m -2 s -1 PFD or 36 µmol m -2 s -1 PFD), some genotypes showed the same tendency in both water regimes and time of flooding exposure.For instance, the O580 IPRO genotype highlighted a tendency to maintain a higher photo-protective capacity regardless of light intensity, water regime, and time of flooding stress exposure.

Genotypes distribution
Seed grain yield (g pl It's worth noting that most of the carbon assimilate is processed in the leaves.Interestingly, genotypes like BRS 525, 58I60 RSF IPRO, BS 2578 RR, and BR 93579 IPRO maintained or even increased their leaf area when subjected to the flooding regime (Figure 5A).This indicates their ability to sustain photosynthetic activity even under flooded conditions.On the other hand, there is an inverse relationship between leaf area and plant height for sensitive genotypes such as BRS 6203, BA 5770 Xi, and K6022 IPRO (Figures 5A and 5B).These genotypes showed a significant increase in height at the expense of their leaf area.The ability of certain genotypes to maintain a higher growth ratio of leaf area during the flood period could be advantageous as it enables them to support rapid growth once the floodwaters recede.

Discussion
Plants have different capacities to dissipate potentially damaging excess absorbed light energy when exposed to full sunlight (Baker, 2008;Guidi, Lo Piccolo, & Landi, 2019;Smirnoff, 1993;Zhang et al., 2016).High light exposure drives a rapid saturation of the photosynthetic reaction centers and their eventual closure, leading to a reduction in the fraction of energy utilized in photosynthesis and the subsequent build-up of harmful excess excitation energy in the photosynthetic membrane (Björkman & Demmig-Adams, 1995).According to the authors, this excess energy can damage the most delicate part of the photosynthetic apparatus, the PSII reaction center, which drives water splitting and oxygen evolution (Barber, Ferreira, Maghlaoui, & Iwata, 2004;Zavafer, Koinuma, Chow, Cheah, & Mino, 2017).When subjected to biotic or abiotic stresses such as flooding, plants often exhibit a decrease in net assimilate rate, which is generally associated with an increase in both relative stomatal and non-stomatal limitations, especially during the initial days after stress imposition (Bailey-Serres & Voesenek, 2008;Fernandez, 2006;Liu, Cheng, Xiao, Guo, & Wang, 2014).For our study, the authors decided to discuss the use of the non-photochemical quenching (NPQ) approach as an alternative to detrimental gas exchange measurements.The monitoring of photosynthesis and stomatal conductance can be utilized to quantify the ability of a given genotype to withstand growth under flooding conditions.However, using the infra-red gas analyzer (IRGA) measurements is restricted to only a few samples due to the time-consuming nature of gas exchange analysis and the limited windows of time suitable for employing this approach.In sense, as an alternative method for this study, the authors chose non-photochemical quenching (NPQ).This approach enables the monitoring of the state of photosynthesis even when dealing with a large number of samples, without facing the bottlenecks imposed by gas exchange approaches.
In the context of this study, the existence of genetic variability was evident within the group of evaluated genotypes for their capacity for energy dissipation via the mechanism of photoprotection (Figures 3 and 4).Analyzing the NPQ response curves, it is highlighted that those genotypes with lower grain yield performance during the first trial (K 6022 IPRO, BA 5770 Xi, and BRS 6203) also show reduced NPQ values, regardless of light intensity and exposure time during the flooding regime.Additionally, even seven days after water drainage, these genotypes continue to exhibit the lowest values for their non-photochemical dissipation capacity especially under high light intensity (Figure 3).
Combining the data of the low Fv/Fm (data not shown) with respective NPQ values indicates chronic photoinhibition for these genotypes even after seven days of water drainage (Figures 3F and 4F).According to these authors (Laisk et al., 1997), the quantum yields of photochemical and non-photochemical excitation quenching are constant and equal to 0.80 in a variety of treatments, leading to the understanding that the capacity for photochemical quenching will be reduced as the NPQ increases.On the other hand, it is necessary to consider that the increase in NPQ values in plants exposed to any abiotic stress, such as flooding, could lead to an improvement in the equilibrium for both photochemical and non-photochemical quenching, achieved by dissipating the excess light energy as heat.
In this study, genotypes that demonstrated a higher ability to accelerate their NPQ (Non-Photochemical Quenching) relaxation mechanism during short stress periods or even after water drainage in soybean flooding areas could potentially achieve a substantial gain in photochemical energy, which would be utilized for photosynthesis.One genotype, 58I60 RSF IPRO, exhibited the highest grain yield and showed remarkable response curve dynamics for NPQ values, regardless of light intensity and stress exposure time.This highlights the vital role of adjusting photoprotective mechanisms to contribute to carbon gain during flooding events, which are very common in early summer in Brazil's southern region.
Generally, genotypes that displayed higher grain yield also exhibited a broader range of curves when comparing a given genotype under high and low light intensities (Figure 3).The exceptional performance of these genotypes, particularly for 58I60 RSF IPRO, could be attributed to its superior ability to accelerate the violaxanthin-xanthophyll cycle.This heightened capacity may lead to a faster induction and relaxation of non-photochemical quenching, even when these genotypes were subjected to a flooding regime.Consequently, these genotypes could enhance their electron transport rate through PSII, thereby improving their carbon assimilation performance during the stress period and/or accelerating their recovery after water drainage.

Conclusion
In conclusion, the genotypes that exhibited higher grain yield mass in the first trial (BRS 525, BS 2578, 64HO130 I2X, 58I60 RSF IPRO, BT 93759 IPRO, and O580 IPRO) also showed the highest NPQ values associated with a broad range between high and low light intensity, irrespective of the water regime and time of exposure.Among these genotypes, 58I60 RSF IPRO, 64HO130 I2X and BRS 525 displayed superior potential and could be further exploited in breeding efforts, considering their grain yield capacity, plant leaf area, and photoprotective capacity under flooding conditions.It is essential to extend this study to field conditions in the future to gain more comprehensive insights into the hypotheses presented here.This approach, in conjunction with breeding efforts, could confirm the ability of certain genotypes to efficiently dissipate excess light energy during flooding periods, thereby developing plant models to withstand extreme climate events both presently and in future scenarios.6.2 < 6.4 < 6.4 < 6.4 < 6.4Not found Not found 6.3 6.3 6.4 6.9 5.6 6.4 6.1 6.0Not found <6.4Not found 5.9 5.8 5.3

Figure 2 .
Figure 2. Scatter plot showing soybean grain yield of 160 genotypes flooded under semi-natural conditions using a low-cost phenotyping facility.The x-axis represents the genotypes dispersion.Each data point in the graph represents the mean grain yield of five biological replicates (each plant's grain yield representing a biological replicate) for a particular genotype and time point.Blues points represent higher grain yield genotypes and oranges points those poorest grain yield genotypes

Figure 3 .
Figure 3. Impact of water treatments (control at left and flooded at right) on NPQ during light oscillation in soybean genotypes selected from the first trial.Light was turned on under high light (1251 µmol m -2 s -1 PFD) followed of low light (36 µmol m -2 s -1 PFD) by fifteen minute in each light regime.At left are graphs representing the control treatment, whereas at right are those showing genotypes under flooding stress.(A; B)and (C; D) graphs refer to analysis done at 48 and 96 h h after stress imposing for flooded treatments, respectively.(E; F) graphs are showing analysis carry out at seven days after water drainage of the flooded treatment (recovery period).For each time point analysis are average of six replicates (n = 3 biological replicates, with two disks by leaflet)

FFigure 4 .
Figure 4. Shows the impact of water treatments (Control and flooded) on NPQ (Non-Photochemical Quenching) during light oscillation in soybean genotypes selected from the first trial.The light oscillation consisted of high light exposure (1251 µmol m -2 s -1 PFD) followed by low light exposure (36 µmol m-2 s-1 PFD) for fifteen minutes in each light regime.Each bar represents the last data point analyzed in the high and low light conditions, displayed on the left and right sides, respectively.The bars represent the average ± standard errors (SE) of six replicates (n = 3 biological replicates, with two disks per leaflet).Statistical analysis was conducted using the Student-Newman-Keuls method, and different lowercase letters are used to indicate statistically significant differences (p ≤ 0.05) between genotypes within each water regimes GDM Genética do Brasil S.A. Brasmax/GDM Genética do Brasil S.A. Nidera/Syngenta Seeds Ltda.DonMario/GDM Genética do Brasil S.A. GDM Genética do Brasil S.A. GDM Genética do Brasil S.A. Centro Educacional Integrado Ltda-CEI Expo Grain Comércio de Sementes Ltda.GDM Genética do Brasil S.A. Brasmax/GDM Genética do Brasil S.A. GDM Genética do Brasil S.A. DonMario/GDM Genética do Brasil S.A. DonMario/GDM Genética do Brasil S.A. Nidera/Syngenta Seeds Ltda.FTS Sementes S.A. GDM Genética do Brasil S.A.