1. Introduction
Grapevines are among the most extensively cultivated plant species worldwide, representing an important crop of significant economic value [1]. In South Korea, the cultivation of table grapes is predominant, yielding a total production of 195,747 tons harvested from 14,706 hectares as of 2023 [2]. The primary grape varieties cultivated in South Korea are ‘Shine Muscat’ (43.1%), ‘Campbell Early’ (29.3%), and ‘Kyoho’ (17.5%), collectively comprising 89.8% of the total cultivation area [3].
Climate change exerts a profound influence on the growth and development of crops. Conventional climate scenarios proposed by researchers are increasingly scrutinized, presenting unforeseen and pressing challenges for grape cultivation due to the intensification and growing frequency of extreme weather events [4,5]. Extreme climate events, such as droughts, heatwaves, and floods, are manifesting with increasing frequency worldwide [6,7], with flood occurrences rising by approximately 65% over the past 25 years [8]. Frequent flooding exerts a devastating impact on both natural vegetation and agricultural crops, resulting in significant economic losses [9]. The annual precipitation in South Korea typically ranges from 1000 to 1800 mm, with approximately 50–60% occurring during the rainy season, which spans July and August. In recent years, significant changes in precipitation patterns have been observed, including an increase in localized torrential downpours and extended periods of rainfall [10]. Soil waterlogging from heavy rainfall severely impairs grapevine energy metabolism [11], adversely affecting fruit quality [12]. Furthermore, it is expected to act as a potential factor aggravating the incidence of physiological disorders, including berry cracking [13].
Plant responses to waterlogging are highly diverse and involve complex physiological and biochemical processes [14,15]. The primary consequence of waterlogging on crops is a decrease in the concentration or availability of oxygen in the root zone [16,17,18]. Reactive oxygen species (ROS) production, a common attribute of both biotic and abiotic stresses (such as drought, heat, and cold) in plants, is considered the initial stage of oxidative stress [19]. This response interferes with the gas exchange processes in plants [20], resulting in stomatal closure and a subsequent decline in photosynthetic activity [17,21]. Importantly, the sustained functionality of photosynthesis is considered a crucial indicator of a plant’s capacity to adapt to and recover from stress conditions [14,22], highlighting the necessity of a comprehensive assessment of this relationship [23]. As a result, waterlogging subjects plant roots to hypoxia stress, triggering the accumulation of toxic substances and imbalances in endogenous hormone levels, adversely affecting metabolic processes [24]. The external stress responses of plants to flooding often emerge several days or weeks following the onset of inundation [25]. Under severe conditions, plant leaves can develop chlorosis or premature senescence, ultimately leading to defoliation [26,27].
Irrigation strategies play a crucial role in the agricultural sector [28]. To achieve efficient irrigation and sustain optimal crop growth, the water supply must be meticulously regulated and consistently monitored throughout the entire growth period [29]. However, the simultaneous effects of climate change and open-field cultivation conditions pose a considerable challenge in the development of effective irrigation strategies. A considerable body of research has long reported the impacts of soil moisture on crop growth and quality [30,31,32,33,34]. However, studies simulating crop physiological responses based on meteorological analysis remain scarce, and there is a lack of research directly assessing sap flow dynamics within grapevine under water stress conditions. For instance, there is currently no available research on the varietal characteristics of ‘Jinok’, a table grape cultivar [35] that was developed in South Korea in 2004 as a potential replacement for ‘Campbell Early’ [36].
This study examined rainfall patterns in South Korea over the past 30 years and quantified the duration of consecutive rainy days to establish a theoretical framework for subsequent experimentations. To this end, it explored the physiological responses of the grapevine cultivars ‘Campbell Early’ and ‘Jinok’, as well as the dynamics of water movement within the plants under flooding or excess soil water conditions. Through the experimental findings, it aimed to transcend indirect measurement approaches, such as proline and ROS analysis, by actively and directly evaluating the physiological responses of grapevines under water stress conditions. Therefore, in this study, a seven-day consecutive rainfall event, derived from a thirty-year meteorological analysis, was simulated to assess its effects on the photosynthetic rate, leaf and stem water potential, and xylem sap flow in table grapes under experimental conditions. This analysis aimed to elucidate grapevine water stress responses under rainfall patterns characteristic of Korea and to examine the relationships among the measured parameters.
2. Materials and Methods
2.1. Collection of Precipitation Data in Korea
To analyze rainfall characteristics, meteorological data from 1995 to 2024 were obtained from the Korea Meteorological Administration (KMA) via the Open MET Data Portal
2.2. Plant Materials
The experimental materials comprised three-year-old grapevines of the cultivars ‘Campbell Early’ and ‘Jinok’ (cutting-propagated), grown in 40 L−1 plastic containers. Grapevines were planted in plastic containers filled with sandy loam soil, comprising 36.5% sand, 26.3% silt, and 37.2% clay. The experiments were carried out within a plastic greenhouse located at the experimental field (an elevation of 32 m asl, 35°51′02″ N, 127°07′51″ E) of Jeonbuk National University. The grapevines were vertically trained with three to four shoots per vine, taking into account the root zone volume. After retaining 12 leaves per shoot, the apical tips were excised. The grape clusters were managed to maintain an average of 1.5 clusters per shoot, with the number of berries per cluster adjusted to 70–80. Fertilization, pruning, and pest and disease management of the grapevines were carried out in accordance with established conventional practices. The schematic diagram of the experiment, designed to establish the theoretical framework of the study and validate the effects of soil moisture treatment, is shown in Figure 1.
2.3. Control of Soil Moisture
Soil moisture was regulated from 24 to 31 July 2017 during the fruit coloration stage, using a tensiometer (Irrometer Co., Inc., Riverside, CA, USA) integrated with an automatic irrigation controller (Solenoid Irrigation Control System Co., Ltd., Namyangju, Republic of Korea). The tensiometers were installed at a depth of 15–20 cm below the soil surface, and 1.0 L−1 of water was applied whenever the soil water potential fell below −5 kPa, −15 kPa, and −30 kPa, respectively. Drip irrigation was implemented using emitters. Additionally, for the flooding treatment, 130 L−1 rubber pots were filled with water to submerge the soil surface of the test pots containing the grapevines, reaching a depth of 10 cm above the soil surface. The soil water potential was consistently maintained at −30 kPa before and after the treatment for both cultivars. The flooding treatment pots were drained promptly following the completion of the treatment period (for seven days). Soil water potential changes were monitored using an Almemo 2890-9 (Alhborn GmbH, Holzkirchen, Germany) installed at a depth of 15–20 cm below the soil surface, and data were systematically collected. The experiment was designed with one plant per replicate, and both cultivars were evaluated across five replicates each.
2.4. Photosynthetic Rate, Transpiration Rate, and Crop Water Stress Index
The photosynthetic (Pr) and transpiration rates (Tr) were measured using a portable photosynthesis system (LC Pro+, ADC Bioscientific Ltd., Hoddesdon, UK). The measurements were performed under controlled conditions, with the photosynthetic photon flux density (PPFD) set at 1000 μmol·m−2·s−1, the CO2 concentration maintained at ambient, and a leaf area of 6.25 cm2. The measurements were conducted prior to treatment and at two, five, seven, and ten days post-treatment between 10:00 a.m. and 12:00 p.m., when photosynthetic activity is most stable, with six replicates per treatment group. Measurements were performed on the seventh to tenth leaves along the stem in both cultivars.
The crop water stress index (CWSI) was measured using a thermal imaging camera (Testo 882, TestoAG, Schwarzwald, Germany). Thermal images were obtained at a distance of 30 cm, with an emissivity set to 0.95, during midday, and six replicates were performed. Based on the thermal images, the leaf surface temperature was extracted from 30 points on the leaf blade, excluding the edges and veins, using IRSoft 4.0 software (TestoAG, Schwarzwald, Germany). The CWSI was calculated using the following Equation (1) [37,38].
CWSI = (TI − Twet)/(Tdry − Twet)(1)
TI, Twet, and Tdry represent the surface temperature of the target leaf, the surface temperature of a shaded leaf in the lower canopy, and the surface temperature of a fully sunlit leaf in the upper canopy, respectively.
2.5. Leaf and Stem Water Potential, and Relative Electrolyte Leakage
Leaf water potential (LWP) was measured at midday using leaves collected from the same location. Measurements were conducted using a water potential meter (Model 600 Pressure Chamber Instrument, PMS Instrument Co., Corvallis, OR, USA), determining the nitrogen gas pressure required for xylem sap to emerge from the cut surface of the petiole. Stem water potential (SWP) was measured after a two-hour equilibration period, during which the target leaf was enclosed in aluminum foil to ensure water potential equilibrium between the stem and the leaf. The measurement procedure was identical to that used for LWP.
To determine the relative electrolyte leakage (REL) of leaves, leaf discs with an area of 2 cm2 were collected using a cork borer and immersed in 20 mL of distilled water. The samples were maintained at room temperature for 24 h, after which the initial conductivity (Initial C) was measured. The samples were then incubated in a water bath at 100 °C for 10 min, followed by rapid cooling in an ice bath to terminate the reaction. The final conductivity (final C) was subsequently measured. The electrolyte conductivity was measured using a SevenEasy Conductivity meter (Mettler-Toledo, Schwerzenbach, Switzerland). The REL of the leaves was calculated using the following Equation (2).
REL (%) = initial C/final C × 100(2)
LWP and SWP, along with the REL of leaves, were measured twice—before and after the soil moisture treatment—with five replicates per treatment. LWP, SWP, and REL were measured using leaves sampled from the same position as those used for photosynthetic measurements.
2.6. Sap Flux in the Xylem
Xylem sap flow was measured using a Flow 32 system (Dynamax Inc., Houston, TX, USA). First, the trunk section of the grapevine designated for sensor attachment (diameter 1.2–1.6 cm2) was carefully smoothed using sandpaper. The measurement sensor, Dynagage (SGB16, Dynamax Inc., Houston, TX, USA), was coated with oil on its interior and attachment surface. It was then carefully affixed to the trunk surface of the grapevine, ensuring complete and secure contact. Gaps at the top and bottom of the Dynagage were sealed with rubber clay, and the entire sensor was wrapped in insulating material to minimize internal heat loss and shield it from radiant heat caused by sunlight. Following installation, the sensors were connected to the LoggerNet 4.1 software (Campbell Scientific Inc., Logan, UT, USA), and the trunk diameter for each sensor, as well as the heater resistance value of the Dynagage, were inputted. Additionally, calibration was carried out by inputting the average value of the gage zero set constant recorded between 4:00 AM and 6:00 a.m. on the following day. Xylem sap flow data were recorded at 20-min intervals using a CR-1000 data logger (Campbell Scientific Inc., Logan, UT, USA). In the flooding treatment, sap flow measurement was not possible due to the submersion of the sensor attachment area in water.
2.7. Data Analysis
Rainfall data were analyzed, and the arithmetic mean was calculated using Microsoft Excel 2019 (Microsoft Corp., Redmond, WA, USA). Duncan’s multiple range test, F-test, and correlation analysis were performed with SAS 9.4 (SAS Institute Inc., Cary, NC, USA). Furthermore, data visualization was carried out using SigmaPlot 14.0 (Systat Software Inc., Chicago, IL, USA).
3. Results and Discussion
3.1. Rainfall Characteristics in Jeonbuk Province, South Korea, over the Past 30 Years
From 1995 to 2024, the average annual precipitation in South Korea (Figure 2A) was approximately 1357 mm, with a standard deviation of ±250 mm. The data revealed a biennial pattern characterized by alternating higher and lower precipitation periods. The average annual precipitation in Jeonju and Namwon, two major grape-producing regions, was 1323 mm and 1386 mm, respectively, exhibiting no significant deviation from the national average precipitation in South Korea. Additionally, the annual precipitation from 1995 to 2024 ranged from 814 to 1987 mm in Jeonju and 811 to 2050 mm in Namwon. The monthly precipitation in South Korea and the Jeonju and Namwon regions (Figure 2B) demonstrated a trend where 54.5% to 58.0% of the annual precipitation (739 mm, 767 mm, and 796 mm, respectively) occurred during the summer months of June to August [39]. Precipitation during winter and early spring was comparatively much lower than that observed in summer [40].
The calculation of consecutive rainfall days excluded those with daily precipitation below 5 mm. A single non-rainy day was treated as a rainy day during consecutive rainfall periods. This criterion was established based on a previous study [41], which defined the allowable non-rainy period for maintaining residual soil moisture in upland crop cultivation as no more than one day. In Namwon, the region with the largest grape cultivation area in Jeonbuk State, the average number of consecutive rainfall days from June to August between 1995 to 2024 was 7.0 days (range 2–13 days), with an average precipitation of 242 mm (range 13.3–519.5 mm) over an average seven-day period, as shown in Figure 2C. The observed occurrence of 7 consecutive rainfall days was considered the basis for determining the treatment duration supporting the theoretical hypothesis of this study.
Over the past century, the average annual precipitation in South Korea has fluctuated between 700 mm and 1800 mm [42]. Notable characteristics of the country’s precipitation patterns include distinct seasonal distribution, diverse precipitation types, and considerable interannual variability [43]. Furthermore, an increasing trend has been observed in localized heavy rainfall and precipitation events occurring outside the traditional rainy season [44]. Recent studies have documented a 7.3% increase in annual precipitation, a 25% increase in July precipitation, and a 34% decrease in November precipitation [40]. These shifts are associated with an elevated risk of natural disasters, including droughts and floods, and similar patterns have been observed in various regions globally [44]. The intensified precipitation intensity and the increasing frequency of heavy rainfall in South Korea, driven by climate change, are frequently observed during the rainy season from June to August [45]. Excessive rainfall significantly affects grapevine growth in open-field cultivation, primarily due to flooding. However, in agricultural settings, the impact of grapevine field flooding is often overlooked or misinterpreted as other conditions, as it takes several days to weeks for distinct visual symptoms to occur. Thus, a detailed analysis of flood-induced damage and the development of appropriate countermeasures are critically important.
3.2. Changes in Air Temperature, Humidity, and Soil Moisture During the Experimental Period
To enhance the precision of soil water potential control, four simulations were performed to evaluate the relationship between irrigation duration and volume, as well as the variations in soil water potential induced by the supplied irrigation volume. The variations in soil water potential regulated by automated irrigation during the experimental period are shown in Figure 3A. A lower target soil water potential was associated with a greater magnitude of change induced by irrigation. The flooding treatment was not irrigated, and the average soil water potentials corresponding to the target irrigation levels of −5 kPa, −15 kPa, and −30 kPa were measured as −3.2 ± 1.7 kPa, −15.9 ± 4.4 kPa, and −28.2 ± 6.1 kPa, respectively. Based on these results, it was concluded that precise soil moisture control attaining the target soil water potential was successfully achieved. During the experimental period, the average air temperature and relative humidity were measured at 30.5 °C and 76.9%, respectively (Figure 3B).
3.3. Changes in Photosynthetic Rate and Transpiration Rate in Relation to Soil Moisture
The Pr of grapevine ‘Campbell Early’ (Figure 4A) showed no significant differences prior to the controlled soil irrigation treatment. However, after the treatment, a gradual decline was observed in the flooding and −5 kPa treatments. The −15 kPa and −30 kPa treatments demonstrated a comparatively negligible variation throughout the soil irrigation treatment period compared to the flooding and −5 kPa treatments. The Pr of the grapevine ‘Jinok’ followed a trend similar to that observed in ‘Campbell Early’ (Figure 4C). In both cultivars, the Pr seven days after the soil irrigation treatment was in the following order: −30 kPa, −15 kPa > −5 kPa > flooding treatments. The flooding and −5 kPa treatments exhibited a tendency for partial recovery 10 days after the soil irrigation treatment. In both cultivars, the Tr at seven days post soil irrigation treatment tended to be lower in the flooding and −5 kPa treatments compared to the −15 kPa and −30 kPa treatments. However, the changes in Tr during the treatment period did not closely align with those observed in the Pr (Figure 4B,D).
In a similar study, the Pr of ‘Campbell Early’ was reported to remain relatively stable during the initial three days of flooding treatment but decreased by 78% and 58% compared to the untreated group after seven and fourteen days, respectively [46]. During this experiment, the average air temperature (late July, 30.5 °C) exceeded that reported in a previous study (mid-June, early summer). Additionally, variability in soil composition within the pots is presumed to have contributed to the observed discrepancies in the experimental results. Soil moisture stress, including flooding, is considered to contribute to a reduction in CO2 assimilation [47,48,49] by inducing oxidative stress [50], which in turn cause cellular changes such as a decline in RuBP activity and disruptions in electron transport [51,52].
3.4. Differences in Leaf and Stem Water Potential, Relative Electrolyte Leakage of Leaves, and Crop Water Stress Index in Relation to Soil Moisture
The differences in LWP, SWP, REL, and CWSI under various soil moisture conditions are presented in Table 1. No significant differences in LWP and SWP were observed before the controlled soil irrigation treatments. However, the flooding and −5 kPa treatments exhibited significantly higher values seven days after treatment than the −15 kPa and −30 kPa treatments. The observed results were consistent for both cultivars.
Water potential is widely used as a key parameter for evaluating the water status of plants [30] and serves as a reliable indicator [53,54]. Although soil moisture and water potential in leaves and stems may not always serve as perfectly correlated evaluation indicators [55,56], changes in LWP and SWP that align with reductions in Pr and Tr are considered to be closely associated with the plant’s internal water absorption processes. Seven days after the controlled soil irrigation treatments, the electrolyte leakage in leaves was highest in the flooding and −5 kPa treatments, with both cultivars exhibiting similar results. These findings align with previous studies [57,58] reporting increased electrolyte leakage in grapevine leaf and root tissues under water stress conditions.
The CWSI, a metric for evaluating plant stress based on the temperature difference between the air and the leaf surface, is derived from the principle that reduced transpiration through stomata reduces heat dissipation, increasing leaf temperature [59]. This index is widely used not only for assessing crop water status [60] but also for applications in plant breeding and ecosystem monitoring [61].
The CWSI of the grape cultivar ‘Campbell Early’ varied across soil moisture conditions, with the highest value observed in the flooding treatment (1.25), followed by those at −5 kPa (1.02), −30 kPa (0.76), and −15 kPa (0.65). The grape cultivar ‘Jinok’ also had higher CWSI values under the flooding and −5 kPa treatments, consistent with the results observed for ‘Campbell Early’. The CWSI may exhibit a positive association with soil moisture and significant negative associations with Pr and stomatal conductance [62]. This study confirmed that the CWSI demonstrated trends consistent with several stress-indicating parameters, including reductions in Pr, LWP, and SWP [63], under water stress conditions such as flooding and −5 kPa treatments. In both cultivars, the CWSI exceeded 1.0 under the flooding and −5 kPa treatments, likely influenced by factors such as air temperature and crop growth conditions [64,65].
3.5. Changes in Sap Flux in the Xylem in Relation to Soil Moisture
No significant differences in trends across treatments were observed for the diurnal variation in sap flow in the xylem between the two cultivars except at the peak points (Figure 5A). In contrast, differences in cumulative sap flow between soil moisture treatments became apparent 2~3 days after treatment initiation and grew increasingly pronounced as the treatment period progressed (Figure 5B). During the soil moisture treatment period, the cumulative sap flow of grapevine ‘Campbell Early’ was 48.3 g·L−1, 59.8 g·L−1, and 60.0 g·L−1 in the −5 kPa, −15 kPa, and −30 kPa treatments, respectively, exhibiting a reduction of approximately 19.4% between the −5 kPa and −30 kPa treatments. In ‘Jinok’, the cumulative sap flow was 54.8 g·L−1, 61.1 g·L−1, and 72.8 g·L−1 in the −5 kPa, −15 kPa, −30 kPa treatments, respectively, exhibiting a reduction of approximately 24.6% between the −5 kPa and −30 kPa treatments. When soil oxygen levels are reduced due to flooding, water uptake through the roots declines and is accompanied by associated internal physiological changes [11]. A reduction in water uptake triggers physiological and morphological changes, including decreases in photosynthetic activity and stomatal conductance, which in turn affect carbohydrate storage and translocation [66,67]. Furthermore, it may compromise fruit quality, as indicated by a reduction in anthocyanin content [68]. The direct measurement of sap flow in response to soil moisture conditions in crops enables the early detection of water stress and supports the development of effective irrigation strategies. Sap flow follows a circadian rhythm, with the volume of sap movement varying based on soil moisture availability [69,70]. Under drought conditions, it can exhibit an immediate response to changes in water supply [71]. In this study, sap flow in grapevines under different soil moisture conditions exhibited trends similar to those observed in Pr, LWP, SWP, and other related parameters. Additionally, sap flow was reduced with excessive soil moisture supply.
3.6. Analysis of Relationships Among Factors
The analysis of the relationships among eight parameters associated with water movement within grapevines under varying soil moisture conditions is presented in Figure 6. LWP (r = −0.973 **) and SWP (r = −0.906 **) were highly significantly negatively correlated with Pr. This relationship was further supported by the CWSI (r = −0.970 **), calculated using the REL (r = −0.865 **) of leaves and the surface temperature of grapevine leaves, which exhibited a highly significant negative correlation with Pr. Additionally, REL and CWSI demonstrated a highly significant positive correlation with LWP (r = 0.930 **, r = 0.988 **, respectively) and SWP (r = 0.988 **, r = 0.917 **, respectively), reinforcing these findings. Furthermore, measuring the cumulative sap flow (CSF) in the xylem of grapevine stems under varying soil moisture conditions reaffirmed the direct involvement of these physiological responses in water uptake from the roots and its movement within the plant body. Soil moisture (potential) exhibited a significant negative correlation with Pr (r = −0.901 **) and CSF (r = −0.693 *) but a significant positive correlation with LWP (r = 0.855 **), SWP (r = 0.761 **), REL (r = 0.771 *), and the CWSI (r = 0.830 **). These findings suggest that excessive soil water conditions impair root water uptake, reducing sap flow.
The reduction in sap flow within the xylem reduced LWP and SWP, while cellular stress responses increased REL and CWSI, ultimately resulting in a decline in Pr. These results demonstrate that a seven-day period of flooding or excessive soil water conditions is sufficient to elicit significant water stress responses in the grapevine cultivars ‘Campbell Early’ and ‘Jinok’. Under excessive soil moisture stress conditions, crop net photosynthesis and growth are closely linked to factors such as LWP, SWP, and the relative leaf water content [30,32,34,72]. Soil moisture stress influences water uptake and transport, resulting in high correlations among parameters such as LWP, SWP, and CWSI [34,61,73]. Although variations occur depending on the crop growth stage and the severity of water stress [74], water stress can substantially diminish fruit quality by reducing fruit size and impairing maturation [75,76].
Reports on the risks and variability of climate change indicate that its impacts are manifesting globally through diverse phenomena [7,8], including increased occurrences of excessive rainfall [40,41] and a rising frequency of floods [9]. As a result, there is an increasing need for research on the identification of simple, non-destructive stress indicators, along with the development of flood-tolerant cultivars and effective drainage strategies [77].
4. Conclusions
Recent climate change has profoundly impacted grapevine growth throughout its developmental period, manifesting in various forms, including high and low temperatures, flooding, drought, and typhoons, while increasing unpredictability and variability in yield production and quality. In South Korea, the annual average precipitation is 1357 mm, with 54.5–58.0% (740–787 mm) occurring during the summer months of June to August. The average number of consecutive rainfall days for the 1995–2024 period is 7.0 days (range 2–13 days), suggesting that open-field grapevines are exposed to soil moisture stress for an average of at least seven days each year. However, in South Korea, the stress responses of grapevines to flooding or excessive soil moisture during the rainy season are often overlooked, with the primary focus placed on the occurrence of physiological disorders during the harvest period.
Water stress in horticultural crops, including grapes, is predominantly described in the context of drought conditions. This study investigated the physiological responses of grapevines subjected to flooding or excessive soil water conditions over a seven-day period under experimental conditions. Direct physiological responses were assessed through Pr, LWP, SWP, CWSI, and sap flow rate analyses. In conclusion, the grapevine cultivars ‘Campbell Early’ and ‘Jinok’ demonstrated a reduction in CSF when subjected to flooding or excessive water stress conditions over a seven-day period during the summer. This reduction in sap flow was accompanied by a decrease in LWP and SWP and an increase in leaf CWSI and REL, collectively contributing to a detrimental effect on the photosynthetic activity. The findings were corroborated through correlation analysis, which confirmed the interrelationships among the investigated factors. On the other hand, no significant differences were observed between the two cultivars, suggesting that the choice between ‘Campbell Early’ and ‘Jinok’ may not be a critical factor when considering grapevine cultivars for flood tolerance. Our study provides foundational insights into table grapevine physiological responses to excessive soil moisture stress in the context of South Korean rainfall patterns. Furthermore, these findings are expected to provide valuable insights for research focused on climate change predictions and simulations. Future climate change is expected to lead to more pronounced and unpredictable declines in grape production. This study simulated aspects of grapevine physiology under excessive soil moisture stress conditions; it has limitations, including the absence of an evaluation of rootstock adaptability and fruit quality assessment. We deemed that the seven-day soil moisture treatment was unlikely to have exerted a statistically significant effect on fruit quality. However, the relationship between plant growth and quality warrants further investigation in future studies. Additional research is required to elucidate how soil moisture stress affects grapevine bud differentiation and overall growth (including root system development) in the subsequent year and to evaluate flood mitigation approaches such as subsurface drainage systems.
Conceptualization, Y.-M.C. and J.-H.S.; methodology, Y.-M.C., J.-H.S. and D.-G.C.; software, Y.-M.C.; validation, Y.-M.C., D.-G.C. and J.-H.S.; formal analysis, Y.-M.C. and J.-H.S.; investigation, Y.-M.C. and J.-H.S.; resources, Y.-M.C. and D.-G.C.; data curation, D.-G.C. and J.-H.S.; writing-original draft preparation, Y.-M.C. and D.-G.C.; writing-review and editing, D.-G.C. and J.-H.S.; visualization, Y.-M.C.; supervision, D.-G.C. and J.-H.S.; project administration, Y.-M.C.; and funding acquisition, D.-G.C. All authors have read and agreed to the published version of the manuscript.
The raw data supporting the conclusions of this article will be made available by the authors on request.
The authors declare no conflicts of interest.
Footnotes
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.
Enlarge this image.Figure 1. Schematic diagram of the test setup for evaluating the effects of soil moisture on water transport in table grapevines.
Enlarge this image.Figure 2. Changes in precipitation characteristics documented in Jeonju and Namwon regions of South Korea over the past 30 years (1995–2024). (A): distribution of annual average precipitation; (B): average monthly precipitation; (C): number of consecutive rainy days and total rainfall during the rainy season (June to August) in the Namwon regions.
Enlarge this image.Figure 3. Distribution of soil water potential (A) through irrigation control and changes in air temperature and relative humidity (B) during the experimental period.
Enlarge this image.Figure 4. Changes in photosynthetic rate (A,C) and transpiration rate (B,D) of table grapevine cultivar ‘Campbell Early’ (A,B) and ‘Jinok’ (C,D) under excessive soil moisture. Vertical bars denote the standard error of the means (n = 6).
Enlarge this image.Figure 5. Changes in daily (A,C) and cumulative sap flow (B,D) in the xylem of table grapevine cultivars ‘Campbell Early’ (A,B) and ‘Jinok’ (C,D) under excessive soil moisture.
![View Image - Figure 6. Scatter plot matrix and Pearson’s coefficients of grapevine cultivars ‘Campbell Early’ and ‘Jinok’ physiological parameter under excessive soil water moisture. Soil water potential (SWT), Pr (photosynthetic rate), Tr (transpiration rate), LWP (leaf water potential), SWP (stem water potential), REL (relative electrolyte leakage of leaves), CWSI (crop water stress index), and CSF (cumulative sap flow in the xylem). ns, *, and ** correspondingly indicate not significant or significant differences at p [less than] 0.05 and p [less than] 0.01, respectively (n = 8).](https://media.proquest.com/media/hms/THUM/12/AwGjb?_a=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&_s=DpLI7mFJvJkDKEFtRVbeeiFCBB0%3D "View Image - Figure 6. Scatter plot matrix and Pearson’s coefficients of grapevine cultivars ‘Campbell Early’ and ‘Jinok’ physiological parameter under excessive soil water moisture. Soil water potential (SWT), Pr (photosynthetic rate), Tr (transpiration rate), LWP (leaf water potential), SWP (stem water potential), REL (relative electrolyte leakage of leaves), CWSI (crop water stress index), and CSF (cumulative sap flow in the xylem). ns, *, and ** correspondingly indicate not significant or significant differences at p [less than] 0.05 and p [less than] 0.01, respectively (n = 8).")
Enlarge this image.Figure 6. Scatter plot matrix and Pearson’s coefficients of grapevine cultivars ‘Campbell Early’ and ‘Jinok’ physiological parameter under excessive soil water moisture. Soil water potential (SWT), Pr (photosynthetic rate), Tr (transpiration rate), LWP (leaf water potential), SWP (stem water potential), REL (relative electrolyte leakage of leaves), CWSI (crop water stress index), and CSF (cumulative sap flow in the xylem). ns, *, and ** correspondingly indicate not significant or significant differences at p [less than] 0.05 and p [less than] 0.01, respectively (n = 8).
Effects of excessive soil moisture on the leaf (LWP) and stem (SWP) water potentials, relative electrolyte leakage (REL) of leaves, and crop water stress index (CWSI) of table grapevine cultivars ‘Campbell Early’ and ‘Jinok’.
| Cultivar | Soil Water | Leaf Water Potential (-MPa) | Stem Water Potential (-MPa) | Relative Electrolyte Leakage (%) | Crop Water Stress Index | ||
|---|---|---|---|---|---|---|---|
| Before | After | Before | After | ||||
| Campbell Early | Flooding | 1.5 a z | 1.8 a | 0.8 a | 1.0 a | 5.4 b | 1.25 a |
| −5 kPa | 1.5 a | 1.6 b | 0.8 a | 0.8 b | 3.8 ab | 1.02 b | |
| −15 kPa | 1.5 a | 1.4 c | 0.8 a | 0.7 b | 1.8 a | 0.65 d | |
| −30 kPa | 1.5 a | 1.4 c | 0.8 a | 0.7 b | 1.6 a | 0.76 c | |
| Jinok | Flooding | 1.4 a z | 1.8 a | 0.8 a | 1.0 a | 4.6 b | 1.28 a |
| −5 kPa | 1.5 a | 1.6 b | 0.9 a | 0.9 b | 1.9 a | 1.00 b | |
| −15 kPa | 1.4 a | 1.4 c | 0.8 a | 0.8 b | 1.1 a | 0.77 c | |
| −30 kPa | 1.4 a | 1.4 c | 0.9 a | 0.8 b | 1.3 a | 0.72 c | |
| Significance | |||||||
| Cultivar (A) | ns | ns | ns | * | ns | ns | |
| Soil Water Status (B) | ns | ** | ns | ** | * | ** | |
| A × B | ns | ns | ns | ns | ns | ** | |
z Means separation within columns for each cultivar according to DMRT (p < 0.05). ns, *, and ** correspondingly indicate not significant or significant differences at p < 0.05 and p < 0.01, respectively.
References
1. Anderson, K.; Nelgen, S. Global Wine Markets, 1961 to 2009: A Statistical Compendium; University of Adelaide Press: Adelaide, Australia, 2011.
2. KOSIS (Korean Statistical Information Service). Available online: https://kosis.kr (accessed on 23 December 2024).
3. KREI (Korea Rural Economic Institute). Agricultural Observation Monthly Report (Short-Term) ‘Fruit’; Korea Rural Economic Institute: Naju, Republic of Korea, 2024.
4. Leolini, L.; Moriondo, M.; Fila, G.; Costafreda-Aumedes, S.; Ferrise, R.; Bindi, M. Late spring frost impacts on future grapevine distribution in Europe. Field Crops Res.; 2018; 222, pp. 197-208. [DOI: https://dx.doi.org/10.1016/j.fcr.2017.11.018]
5. Prosdocimi, M.; Cerdà, A.; Tarolli, P. Soil water erosion on Mediterranean vineyards: A review. Catena; 2016; 141, pp. 1-21. [DOI: https://dx.doi.org/10.1016/j.catena.2016.02.010]
6. IPCC. Contribution of working group I to the fifth assessment report of the intergovernmental panel on climate change. Climate Change 2013: The Physical Science Rasis; Stocker, T.F.; Qin, D.; Plattner, G.K.; Tignor, M.; Allen, S.K.; Boschung, J.; Nauels, A.; Xia, Y.; Bex, V.; Midgley, P.M. Cambridge University Press: Cambridge, UK, 2013; 1535.
7. IPCC. Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation. A Special Report of Working Groups I and II of the Intergovernmental Panel on Climate Change; Field, C.B.; Barros, V.; Stocker, T.F.; Qin, D.; Dokken, D.J.; Ebi, K.L.; Mastrandrea, M.D.; Mach, K.J.; Plattner, G.-K.; Allen, S.K. et al. Cambridge University Press: Cambridge, UK, 2012; 582.
8. FAOIFADUNICEFWFPWHO. Building climate resilience for food security and nutrition. The State of Food Security and Nutrition in the World 2017; FAO: Rome, Italy, 2017.
9. Pedersen, O.; Perata, P.; Voesenek, L.A.C.J. Flooding and low oxygen responses in plants. Funct. Plant Biol.; 2017; 44, pp. iii-vi. [DOI: https://dx.doi.org/10.1071/FPv44n9_FO] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/32480612]
10. Yoon, P.Y.; Kim, T.W.; Yang, J.S.; Lee, S.O. Estimating quantiles of extreme rainfall using a mixed Gumbel distribution model. Kor. Water Res. Ass.; 2012; 45, pp. 263-274.
11. Liao, C.T.; Lin, C.H. Effect of flooding stress on photosynthetic activities of Momordica charantia. Plant Physiol. Biochem.; 1994; 32, pp. 479-485.
12. Hardie, W.J.; Considine, J.A. Response of grapes to water deficit stress in particular stages of development. Amer. Enol. Vitic.; 1976; 27, pp. 55-61. [DOI: https://dx.doi.org/10.5344/ajev.1976.27.2.55]
13. Choi, Y.M.; Choi, D.G. Relationship between cracking occurrence and growth or fruit characteristics in ‘Jinok’ and ‘Campbell Early’ Grapes. Hortic. Sci. Technol.; 2023; 41, pp. 656-665. [DOI: https://dx.doi.org/10.7235/HORT.20230056]
14. Chen, H.; Qualls, R.G.; Blank, R.R. Effect of soil flooding on photosynthesis, carbohydrate partitioning, and nutrient uptake in the invasive exotic Lepidium latifolium. Aquat. Bot.; 2005; 82, pp. 250-268. [DOI: https://dx.doi.org/10.1016/j.aquabot.2005.02.013]
15. Insausti, P.; Grimoldi, A.A.; Chaneton, E.J.; Vasellati, V. Flooding induces a suite of adaptive plastic responses in the grass Paspalum dilatatum. N. Phytol.; 2001; 152, pp. 291-299. [DOI: https://dx.doi.org/10.1111/j.0028-646X.2001.257_1.x]
16. Shabala, S. Plant Stress Physiology; CAB International: Wallingford, UK, 2012; pp. 1-318. [DOI: https://dx.doi.org/10.1079/9781845939953.0000]
17. Else, M.A.; Coupland, D.; Dutton, L.; Jackson, M.B. Decreased root hydraulic conductivity reduces leaf water potential, initiates stomatal conductance, and slows leaf expansion in flooded plants of castor oil (Ricinus communis) despite diminished delivery of ABA from the roots to shoots in xylem sap. Physiol. Plant; 2001; 111, pp. 46-54. [DOI: https://dx.doi.org/10.1034/j.1399-3054.2001.1110107.x]
18. Pezeshki, S.R. Wetland plant responses to soil flooding. Environ. Exp. Bot.; 2001; 46, pp. 299-312. [DOI: https://dx.doi.org/10.1016/S0098-8472(01)00107-1]
19. Carvalho, L.C.; Vidigal, P.; Amâncio, S. Oxidative stress homeostasis in grapevine (Vitis vinifera L.). Front. Environ. Sci.; 2015; 3, 20. [DOI: https://dx.doi.org/10.3389/fenvs.2015.00020]
20. Blanke, M.M.; Cooke, D.T. Effects of flooding and drought on stomatal activity, transpiration, photosynthesis, water potential, and water channel activity in strawberry stolons and leaves. Plant Growth Regul.; 2004; 42, pp. 153-160. [DOI: https://dx.doi.org/10.1023/B:GROW.0000017489.21970.d4]
21. Mielke, M.S.; de Almeida, A.A.F.; Gomes, F.P.; Mangabeira, P.A.O.; Silva, D.D.C. Effects of soil flooding on leaf gas exchange and growth of two neotropical pioneer tree species. N. For.; 2005; 29, pp. 161-168. [DOI: https://dx.doi.org/10.1007/s11056-005-0247-7]
22. Li, S.; Pezeshki, S.R.; Goodwin, S. Effects of soil moisture regimes on photosynthesis and growth in cattail (Typha latifolia). Acta Oecol.; 2004; 25, pp. 17-22. [DOI: https://dx.doi.org/10.1016/j.actao.2003.10.004]
23. Pezeshki, S.R.; DeLaune, R.D. Responses of seedlings of selected woody species to soil oxidation-reduction conditions. Environ. Exp. Bot.; 1998; 40, pp. 123-133. [DOI: https://dx.doi.org/10.1016/S0098-8472(98)00026-4]
24. Ruperti, B.; Botton, A.; Populin, F.; Eccher, G.; Brilli, M.; Quaggiotti, S.; Trevisan, S.; Cainelli, N.; Guarracino, P.; Schievano, E. et al. Flooding responses on grapevine: A physiological, transcriptional, and metabolic perspective. Fron. Plant Sci.; 2019; 10, 339. [DOI: https://dx.doi.org/10.3389/fpls.2019.00339]
25. Salvatierra, A.; Toro, G.; Mateluna, P.; Opazo, I.; Ortiz, M.; Pimentel, P. Keep calm and survive: Adaptation strategies to energy crisis in fruit trees under root hypoxia. Plants; 2020; 9, 1108. [DOI: https://dx.doi.org/10.3390/plants9091108]
26. Pezeshki, S.R. Plant response to flooding. Plant Environment Interactions; Wilkinson, R.E. Marcel Dekker: New York, NY, USA, 1994; pp. 289-312.
27. McGee, T.; Shahid, M.A.; Beckman, T.G.; Chaparro, J.X.; Schaffer, B.; Sarkhosh, A. Physiological and biochemical characterization of six Prunus rootstocks in response to flooding. Environ. Exp. Bot.; 2021; 183, 104368. [DOI: https://dx.doi.org/10.1016/j.envexpbot.2020.104368]
28. Morison, J.I.L.; Baker, N.R.; Mullineaux, M.P.; Davies, W.J. Improving water usein crop production. Philos. Trans. Royal Soc. B Biol. Sci.; 2008; 363, pp. 639-658. [DOI: https://dx.doi.org/10.1098/rstb.2007.2175]
29. Fereres, E.; Soriano, M.A. Deficit irrigation for reducing agricultural water use. Exp. Bot.; 2007; 58, pp. 147-159. [DOI: https://dx.doi.org/10.1093/jxb/erl165] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/17088360]
30. Jones, H.G. Monitoring plant and soil water status: Established and novel methods revisited and their relevance to studies of drought tolerance. Exp. Bot.; 2007; 58, pp. 119-130. [DOI: https://dx.doi.org/10.1093/jxb/erl118] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/16980592]
31. Kang, S.B.; Jang, H.I.; Lee, I.B.; Park, J.M.; Moon, D.K. Effect of waterlogging condition on the photosynthesis of ‘Campbell Early’ grapevine. Kor. Hortic. Sci. Technol.; 2008; 26, pp. 372-379.
32. Lawlor, D.W.; Cornic, G. Photosynthetic carbon assimilation and associated metabolism in relation to water deficit in higher plants. Plant Cell Environ.; 2002; 25, pp. 275-294. [DOI: https://dx.doi.org/10.1046/j.0016-8025.2001.00814.x]
33. Pettigrew, W.T. Physiological consequences of moisture deficit stress in cotton. Crop Sci.; 2004; 44, pp. 1265-1272. [DOI: https://dx.doi.org/10.2135/cropsci2004.1265]
34. Snider, J.L.; Collins, G.D.; Whitaker, J.; Perry, C.D.; Chastain, D.R. Electron transport through photosystem II is not limited by a wide range of water-deficit conditions in filed grown Gossypium hirsutum. Agron. Crop Sci.; 2014; 200, pp. 77-82. [DOI: https://dx.doi.org/10.1111/jac.12044]
35. Choi, Y.M.; Jung, S.M.; Choi, D.G. Effect of fruit set levels and contact between berries on fruit quality in ‘Jinok’ and ‘Campbell Early’ grapes. Hortic. Sci. Technol.; 2024; 42, pp. 117-126. [DOI: https://dx.doi.org/10.7235/HORT.20240010]
36. Yun, H.K.; Park, K.S.; Roh, J.H.; Kwack, Y.B.; Jun, J.H.; Jeong, S.T.; Jang, H.I.; Kim, S.H.; Shin, Y.U. Table grape ‘Jinok’. HortScience; 2008; 43, pp. 2222-2223. [DOI: https://dx.doi.org/10.21273/HORTSCI.43.7.2222]
37. Idso, S.B.; Jackson, R.D.; Pinter, P.J.; Reginato, R.J.; Hatfield, J.L. Normalizing the stress-degree-day parameter for environmental variability. Agric. Meteor.; 1981; 24, pp. 45-55. [DOI: https://dx.doi.org/10.1016/0002-1571(81)90032-7]
38. Jackson, R.D. Canopy temperature and crop water stress. Adv. Irrig.; 1982; 1, pp. 43-85.
39. Cha, E.J.; Kimoto, M.; Lee, E.J.; Jhun, J.G. The recent increase in the heavy rainfall events in August over the Korean Peninsula. Kor. Earth Sci. Soc.; 2007; 28, pp. 585-597. [DOI: https://dx.doi.org/10.5467/JKESS.2007.28.5.585]
40. Jang, G.H.; Jeong, J.I.; Cha, Y.M.; Yang, H.Y.; Choe, Y.J.; Gwon, W.T. The recent trends in precipitation and characteristics of drought years. Mag. Kor. Soc. Harzard Mitig.; 2011; 11, pp. 54-64.
41. Ji, G.H. Study on subsurface drainage system for the multipurpose paddy field. Kor. Soc. Agric. Engin.; 1981; 23, pp. 15-20.
42. MOCT (Ministry of Construction and Transportation of Korea). Comprehensive Long-Term Water Resources Plan; MOCT (Ministry of Construction and Transportation of Korea): Sejong, Republic of Korea, 2006.
43. Park, C.Y.; Moon, J.Y.; Cha, E.J.; Yun, W.T.; Choi, Y.E. Recent changes in summer precipitation characteristics over South Korea. Kor. Geogr. Soc.; 2008; 43, pp. 324-336. (In Korean)
44. Roy, S.S.; Balling, R.C. Trends in extreme daily precipitation indices in India. Int. Climatol.; 2004; 24, pp. 457-466.
45. Kim, C.S.; Suh, M.S. Change-point and change pattern of precipitation characteristics using Bayesian method over South Korea from 1954 to 2007. Atmosphere; 2009; 19, pp. 199-211.
46. Jang, H.I.; Yu, D.J.; Han, J.H.; Lee, I.B.; Lee, H.J. Photosynthetic characteristics of Vitis vifera × V. labrusca ‘Campbell Early’ grapevine cultivar under flooding condition. Hortic. Environ. Biotechnol.; 2006; 47, pp. 65-70.
47. de Souza, C.R.; Maroco, J.P.; dos Santos, T.P.; Rodrigues, M.L.; Lopes, C.; Pereira, J.S.; Chaves, M.M. Control of stomatal aperture and carbon uptake by deficit irrigation in two grapevine cultivars. Agric. Ecosyst. Environ.; 2005; 106, pp. 261-274. [DOI: https://dx.doi.org/10.1016/j.agee.2004.10.014]
48. Mouthinho-Pereira, J.M.; Correia, C.M.; Goncalves, B.M.; Bacelar, E.A.; Torres-Pereira, J.M. Leaf gas exchange and water relations of grapevines grown in three different conditions. Photosynthetica; 2004; 42, pp. 81-86. [DOI: https://dx.doi.org/10.1023/B:PHOT.0000040573.09614.1d]
49. Pou, A.; Flexas, J.; Alsina, M.; Bota, J.; Carambula, C.; Herralde, F.; Galmes, J.; Lovisolo, C.; Jimenez, M.; Ribas-Carbo, M. et al. Adjustments of water use efficiency by stomatal regulation during drought and recovery in the drought-adapted Vitis hybrid Richter-110 (V. berlandieri × V. rupestris). Physiol. Plant.; 2008; 134, pp. 313-323. [DOI: https://dx.doi.org/10.1111/j.1399-3054.2008.01138.x]
50. Flexas, J.; Bota, J.; Galmes, J.; Medrano, H.; Ribas-Carbo, M. Keeping a positive carbon balance under adverse conditions: Responses of photosynthesis and respiration to water stress. Physiol. Plant.; 2006; 127, pp. 343-352. [DOI: https://dx.doi.org/10.1111/j.1399-3054.2006.00621.x]
51. Medrano, H.; Escalona, J.M.; Bota, J.; Gulias, J.; Flexas, J. Regulation of C3 plants in response to progressive drought: Stomatal conductance as a reference parameter. Ann. Bot.; 2002; 89, pp. 895-905. [DOI: https://dx.doi.org/10.1093/aob/mcf079] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/12102515]
52. Medrano, H.; Escalona, J.M.; Cifre, J.; Bota, J.; Flexas, J.A. A ten-year study on physiology of two Spanish grapevine cultivars under field conditions: Effects of water availability from leaf photosynthesis to grape yield and quality. Func. Plant Biol.; 2003; 30, pp. 607-619. [DOI: https://dx.doi.org/10.1071/FP02110] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/32689046]
53. Santesteban, L.G.; Miranda, C.; Marín, D.; Sesma, B.; Intrigliolo, D.S.; Mirás Avalos, J.M. Discrimination ability of leaf and stem water potential at different times of the day through a meta-analysis in grapevine (Vitis vinifera L.). Agric. Water Manag.; 2019; 221, pp. 202-210. [DOI: https://dx.doi.org/10.1016/j.agwat.2019.04.020]
54. Suter, B.; Triolo, R.; Pernet, D.; Dai, Z.; Van Leeuwen, C. Modeling stem water potential by separating the effects of soil water availability and climatic conditions on water status in grapevine (Vitis vinifera L.). Fron. Plant Sci.; 2019; 10, 1485. [DOI: https://dx.doi.org/10.3389/fpls.2019.01485]
55. Groenveld, T.; Obiero, C.; Yu, Y.; Flury, M.; Keller, M. Predawn leaf water potential of grapevines is not necessarily a good proxy for soil moisture. BMC Plant Biol.; 2023; 23, 369. [DOI: https://dx.doi.org/10.1186/s12870-023-04378-6]
56. Williams, L.E.; Trout, T.J. Relationships among vine-and soil-based measures of water status in a Thompson Seedless vineyard in response to high-frequency drip irrigation. Amer. Enol. Vitic.; 2005; 56, pp. 357-366. [DOI: https://dx.doi.org/10.5344/ajev.2005.56.4.357]
57. Bauerle, T.L.; Richards, J.H.; Smart, D.R.; Eissenstat, D.M. Importance of internal hydraulic redistribution for prolonging the lifespan of roots in dry soil. Plant Cell Environ.; 2008; 31, pp. 177-186. [DOI: https://dx.doi.org/10.1111/j.1365-3040.2007.01749.x]
58. Huang, X.; Lakso, A.N.; Eissenstat, D.M. Interactive effects of soil temperature and moisture on Concord grape root respiration. Exp. Bot.; 2005; 56, pp. 2651-2660. [DOI: https://dx.doi.org/10.1093/jxb/eri258]
59. Jones, H.G.; Stoll, M.; Santos, T.; de Sousa, C.; Chaves, M.M.; Grant, O.M. Use of infrared thermography for monitoring stomatal closure in the field. Exp. Bot.; 2002; 53, pp. 2249-2260. [DOI: https://dx.doi.org/10.1093/jxb/erf083]
60. Costa, J.M.; Ortuno, M.F.; Lopes, C.M.; Chaves, M.M. Grapevine varieties exhibiting differences in stomatal response to water deficit. Func. Plant Biol.; 2012; 39, pp. 179-189. [DOI: https://dx.doi.org/10.1071/FP11156]
61. Grant, O.M.; Daviesa, M.J.; Jamesa, C.M.; Johnsona, A.W.; Leinonenb, I.; Simpsona, D.W. Thermal imaging and carbon isotope composition indicate variation amongst strawberry (Fragaria × ananassa) cultivars in stomatal conductance and water use efficiency. Environ. Exp. Bot.; 2012; 76, pp. 7-15. [DOI: https://dx.doi.org/10.1016/j.envexpbot.2011.09.013]
62. Chen, R.; Hu, X.; Wang, W.; Ran, H.; Song, T.; Guo, Y. Evaluation of the crop water stress index as an indicator for the diagnosis of grapevine water deficiency in greenhouses. Horticulturae; 2020; 6, 86. [DOI: https://dx.doi.org/10.3390/horticulturae6040086]
63. Pagay, V.; Kidman, C.M. Evaluating remotely-sensed grapevine (Vitis vinifera L.) water stress responses across a viticultural region. Agronomy; 2019; 9, 682. [DOI: https://dx.doi.org/10.3390/agronomy9110682]
64. Stegman, E.C.; Soderlund, M. Irrigation scheduling of spring wheat using infrared thermometry. Trans. Chin. Soc. Agric. Eng.; 1992; 35, pp. 143-152. [DOI: https://dx.doi.org/10.13031/2013.28581]
65. Yuan, G.; Luo, Y.; Sun, X.; Tang, D. Evaluation of a crop water stress index for detecting water stress in winter wheat in the North China Plain. Agric. Water Manag.; 2004; 64, pp. 29-40. [DOI: https://dx.doi.org/10.1016/S0378-3774(03)00193-8]
66. Pucciariello, C.; Voesenek, L.A.; Perata, P.; Sasidharan, R. Plant responses to flooding. Front. Plant Sci.; 2014; 5, 226. [DOI: https://dx.doi.org/10.3389/fpls.2014.00226]
67. Geigenberger, P. Response of plant metabolism to too little oxygen. Curr. Opin. Plant Biol.; 2003; 6, pp. 247-256. [DOI: https://dx.doi.org/10.1016/S1369-5266(03)00038-4]
68. Kobayashi, Y.; Yamamoto, T.; Ikeda, H.; Sugihara, R.; Kaihori, H.; Kawabata, M.; Suzuki, S. Effects of constantly high soil water content on vegetative growth and grape quality in Japan with high rainfall during grapevine growing season. Folia Hortic.; 2020; 32, pp. 135-145. [DOI: https://dx.doi.org/10.2478/fhort-2020-0013]
69. Peng, X.; Hu, X.; Chen, D.; Zhou, Z.; Guo, Y.; Deng, X.; Zhang, X.; Yu, T. Prediction of grape sap flow in a greenhouse based on random forest and partial least squares models. Water; 2021; 13, 3078. [DOI: https://dx.doi.org/10.3390/w13213078]
70. Sun, J.X.; Wang, L.J.; Han, W.H.; Gong, D.Z.; Gao, L.I.; Li, H.R.; Mao, L.I.; Hao, W.P. The effects of irrigation amount on sap flow in stems of wine grape and its consequence for grape yield and quality. Irrig. Drain.; 2021; 40, pp. 18-24.
71. Benyahia, F.; Campos, F.B.; Abdelkader, A.B.; Basile, B.; Tagliavini, M.; Andreotti, C.; Zanotelli, D. Assessing grapevine water status by integrating vine transpiration, leaf gas exchanges, chlorophyll fluorescence and sap flow measurements. Agronomy; 2023; 13, 464. [DOI: https://dx.doi.org/10.3390/agronomy13020464]
72. Pace, P.F.; Cralle, H.T.; El-Halawany, S.H.; Cothren, J.T.; Senseman, S.A. Drought-induced changes in shoot and root growth of young cotton plants. Cotton Sci.; 1999; 3, pp. 183-187.
73. Sena Gomes, A.R.; Kozlowski, T.T. Growth responses and adaptations of Fraxinus pennsylvanica seedlings to flooding. Plant Physiol.; 1980; 66, pp. 267-271. [DOI: https://dx.doi.org/10.1104/pp.66.2.267] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/16661419]
74. Struthers, R.; Ivanova, A.; Tits, L.; Swennen, R.; Coppin, P. Thermal infrared imaging of the temporal variability in stomatal conductance for fruit trees. Int. Appl. Earth Obs. Geoinfor.; 2015; 39, pp. 9-17. [DOI: https://dx.doi.org/10.1016/j.jag.2015.02.006]
75. Girona, J.; Mata, M.; Campo, J.; Arbones, A.; Bartra, E.; Marsal, J. The use of midday leaf water potential for scheduling deficit irrigation in vineyards. Irrig. Sci.; 2006; 24, pp. 115-127. [DOI: https://dx.doi.org/10.1007/s00271-005-0015-7]
76. Korkutal, I.; Carbonneau, A.; Bahar, E. Effects of early water stress levels on berry set and berry development in Merlot cv. (Vitis vinifera L.). Afr. Biotech.; 2011; 10, pp. 15921-15932. [DOI: https://dx.doi.org/10.5897/AJB11.2513]
77. Choi, Y.M.; Jung, S.M.; Choi, D.G. Effects of heavy rain during rainy season and drainage methods on soil water content, photosynthesis characteristics, and growth in ‘Jinok’ and ‘Campbell Early’ Grapes. Kor. Agric. Forest Meteor.; 2017; 19, pp. 1-9. [DOI: https://dx.doi.org/10.5532/KJAFM.2017.19.1.1]
© 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
Details
; Choi, Dong-Geun 2 ; Ju-Hee, Song 3
1 Plant Resources Research Institute, Jeonbuk State Agricultural Research & Extension Services, Namwon 55720, Republic of Korea;
2 Department of Horticulture, College of Agriculture & Life Sciences, Jeonbuk National University, Jeonju 54896, Republic of Korea;
3 Department of Horticulture, Korea National University of Agriculture and Fisheries, Jeonju 54872, Republic of Korea