Effects of constantly high soil water content on vegetative growth and grape quality in Japan with high rainfall during grapevine growing season

Vitis vinifera cv. Cabernet Sauvignon was cultivated in the Experimental Farm of the Faculty of Life and Environmental Sciences, University of Yamanashi, Japan (latitude, 35° 36′ 14.0688″ N; longitude, 138° 34′ 41.9016″ E; elevation, 250 m). The farm was located on flat land and had conventional under-drainage pipes. Soils had sandy loam texture with the following characteristics: clay 5.0%, silt 19.0%, sand 76.0%, pH 6.4, EC = 16.0 μS · cm⁻¹, bulk density 1.12 ± 0.03 g · cc⁻¹.

Nine-year-old grapevines were trained to a cordon using 101–14 Millardet et de Grasset rootstock. Each vine was planted 2 m apart with 2-m row spacing. Inter-row was covered with mown grass sward. Fruit-zone leaf removal was performed in mid-June. The average yield was adjusted to two bunches per shoot and the crop yield was adjusted to approximately 15,000 kg · ha⁻¹. Pesticide and fungicide applications were performed 9 and 10 times, respectively, from April to November in each year.

Weather data were recorded by a Meteorological Observation System (FieldMini-FMC-WJ-01, FieldPro, Tokyo, Japan) located approximately 50 m from the grapevines tested. Average temperatures, maximum and minimum temperatures and precipitation from April 1 through October 31 were summarised monthly for each growing season. Growing degree days (GDD, base threshold of 10°C) from April 1 through October 31 were calculated monthly for each growing season.

Two experimental plots each measuring 20 m × 4 m were prepared and 10 grapevines were cultivated in each plot. Three soil moisture and temperature sensors were set in each plot. The sensors (5TE soil moisture sensor, Decagon Devices, Inc., Pullman, WA) were buried underground (20 cm depth) at the distance of 30 cm from a grapevine trunk on 14 March 2017 (Figure 1). The sensors were set 5 m apart between sensors and numbered, as shown in Figure 2. The sensors were connected to sensor nodes by cables (Figure 2). Soil volumetric water content, soil temperature and electric conductivity measured by the sensors were transmitted every 10 min from each sensor node to a Gateway computer through an in-field local wireless network. The data were transmitted to a cloud server on the internet through a cellular communication network. Soil water content (%) was expressed as volumetric water content (θ). The sensors were regularly calibrated according to the manufacturer's instructions during the experimental period.

Figure 1

Figure 2

A drip irrigation tube (polyethylene irrigation tube, 0.20 mm thick, 0.6 mm pore diameter, 20 cm spacing between pores; Kami Plus Co., Tokyo, Japan) was set on the ground near each grapevine trunk in one of the two experimental plots (Figure 1). Four sheets were spread to cover the experimental plot in which the irrigation tube was set to prevent water evaporation from soil and to maintain soil moisture (Figure 1). The sheets used in this study were as follows: polyethylene film (agricultural polyethylene film 95, 0.03 mm thick, 95 cm wide; Sumikasekisui Film Co., Ltd., Tokyo, Japan), ground sheet (Dio ground sheet, 0.5 mm thick, 200 cm wide; Dio Chemicals Ltd., Tokyo, Japan), mulch sheet (Agricultural mulch sheet hard type, 0.02 mm thick, 200 cm wide; Okura Industrial Co., Ltd.) and Tyvek (house wrap hard type, 0.17 mm thick, 200 cm wide, DuPont, Wilmington, DE). In the preliminary experiment, we confirmed that 170 L water was required to equalise the soil water contents with the FC value (30–35%) in the irrigated experimental plot. Therefore, the experimental plot with the irrigation tube and sheets was irrigated with 170 L water for 10 min at 16:00 when soil water content in the experimental plot was less than 20%.

The timings of bud break, bloom, full bloom, véraison and harvest were recorded in the three growing seasons. Harvest timing was decided according to a sugar–acid ratio. Since Cabernet Sauvignon used in the present study was cultivated under extremely high temperature in the farm with much rainfall (Table 1), berries at harvest tended to have low sugar content and high total acidity. Accordingly, harvest was performed at the day over sugar–acid ratio of 15:1. Since a sugar–acid ratio in 2017 growing season was not above 15:1 on in October (13:1), harvest was performed on October 4.

Leaf water potential was measured before and after véraison using a pressure chamber (Model 600D, PMS Instrument Company, Albany, OR). Briefly, three fully developed and undamaged leaves close to bunches were randomly selected. One leaf was placed in an SWP plant sample pack (grape pack, 15 cm × 16.5 cm; Meiwa Fosis, Tokyo, Japan). After shading the leaves in the packs for 1 h, leaf water potential was measured in accordance with the manufacturer's instructions. Measurement of leaf water potential was performed at midday.

Berry characteristics were measured according to a previously described method (Kobayashi et al., 2020). Briefly, three bunches were randomly collected from irrigated or non-irrigated grapevines every week from véraison (July 26) to harvest (October 4) in the 2017 growing season. Ten berries (three from the top of the bunch, four from the middle of the bunch and three from the bottom of the bunch) were collected from each bunch. The transverse diameter of each berry was measured using a digital calliper (AD-5764A-100, A&D Co., Tokyo, Japan). The weights of the 10 berries were measured using an electronic balance (EK2000i, A&D Co.). Soluble solids content (Brix) and total acid content (g · 100 mL⁻¹) in juices prepared by hand-pressing each bunch were measured with a refractometer (PALBX1ACID2, Atago, Tokyo, Japan).

Ten bunches were collected at harvest (4 October 2017, 1 October 2018 and 28 September 2019, respectively). The number of berries on each bunch was counted. The weights of each bunch and 10 berries (three from the top of the bunch, four from the middle of the bunch, and three from the bottom of the bunch) collected from each bunch were measured using the electronic balance. Bunch lengths and the transverse diameters of the 10 berries were measured using the digital calliper. Juices were prepared by hand-pressing each bunch. Soluble solids content (Brix) and total acid content (g · 100 mL⁻¹) in juice were measured as described earlier. The measurement of total anthocyanins in berry skins was performed in accordance with a previously described method (Kobayashi et al., 2020). Anthocyanin content was calculated using a standard calibration curve and expressed as micrograms of malvidin 3-glucoside per cm² of berry skin.

Data are expressed as means ± standard errors of biological replicates and subjected to the Student's t-test using Excel Statistics Software 2012 (Social Survey Research Information, Tokyo, Japan).

The experimental farm in this study belonged to Region V on the Winkler Index. The GDD from April 1 to October 31 in the three growing seasons of 2017 through 2019 demonstrated that Cabernet Sauvignon was cultivated under extremely high temperatures (Table 1). Average temperatures and maximum and minimum temperatures were not significantly different among the growing seasons. The climate at the experimental farm was distinctive in that there was much rainfall from April to October. Precipitation from July in each growing season mostly exceeded 100 mm. Remarkably, the precipitation in October 2017, September 2018 and October 2019 exceeded 450, 250 and 300 mm, respectively (Table 1).

To monitor soil volumetric water content in real time, a wireless sensor networking system was built (Figures 1 and 2). The system detected the increase in soil water content due to rainfall in the experimental plots in real time (Figure 3A). The system was also capable of detecting irrigation water (Figure 3B); it immediately detected the increase in soil water content in the experimental plot that had soil water content controlled to more than 20%, when the plot was irrigated for 10 min at 16:00. Soil water content peaked 10–20 min after irrigation and decreased to 30% with time. These results suggested that the system could perform real-time monitoring of soil water content in an experimental plot and that soil water content in the experimental plot could be controlled to more than 20% using an irrigation system.

Figure 3

Profiles of soil water content in the experimental plots, which were collected from April 21 to October 31 in the 2017 growing season, are shown in Figure 4. Malfunction of the wireless sensor networking system, which was mostly due to dead batteries, rarely led to data loss from each sensor. In the 2017 growing season, short periods of data loss due to dead batteries in the sensor nodes were observed from 10:30 to 11:20 on May 26 and 11:50 to 12:40 on September 8 for B2D3; from 13:00 to 13:10 on August 30 and at 13:20 on September 29 for AC11; at 12:40 on September 29 for AE64; from 9:40 to 11:10 on May 26 for B467; from 10:20 to 10:30 on May 26 for AE75 and from 15:00 to 15:50 on April 21 and at 10:50 on May 26 for AE86. A long period of data loss occurred from 10:40 on October 14 to October 31 for AC11, and from 21:20 on August 21 to 12:40 on August 30 for AE86. Since the sensor nodes of AC11 and AE86 were malfunctioned, they were replaced with new sensor nodes. Malfunctions of the system also occurred in the 2018 and 2019 growing seasons with similar frequency to the 2017 growing season (data not shown).

Figure 4

The averages of soil temperatures (means ± standard deviations) from April to October in the non-irrigated experimental plot were 22.3 ± 3.7°C as detected by B2D3; 22.7 ± 3.2°C by AC11 and 22.6 ± 3.5°C by AE64 in the 2017 growing season; 21.1 ± 4.0°C as detected by B2D3; 21.5 ± 4.2°C by AC11 and 21.3 ± 4.4°C by AE64 in the 2018 growing season and 21.9 ± 3.9°C as detected by B2D3; 22.0 ± 4.4°C by AC11 and 21.4 ± 3.5°C by AE64 in the 2019 growing season. In contrast, the averages of soil temperatures (means ± standard deviations) from April to October in the irrigated experimental plot were 24.6 ± 3.7°C as detected by B467; 24.4 ± 4.0°C by AE75 and 24.8 ± 3.8°C by AE86 in the 2017 growing seasons; 21.3 ± 4.2°C as detected by B467; 21.4 ± 4.1°C by AE75 and 19.4 ± 2.9°C by AE86 in the 2018 growing seasons and 23.4 ± 4.4°C as detected by B467; 22.7 ± 4.5°C by AE75 and 21.4 ± 4.5°C by AE86 in the 2019 growing season. The results suggested that sheet treatment for controlling soil water content to more than 20% prevented the decline of soil temperature by irrigation water and that soil temperature in the irrigated experimental plot was comparable with that in the non-irrigated experimental plot in the three growing seasons.

Soil water content in the non-irrigated experimental plot was less than 20% except after rainfall (Figure 4). The averages of soil water contents from April to October in the non-irrigated experimental plot were 18.9% as detected by B2D3; 15.4% by AC11 and 15.9% by AE64 in the 2017 growing season (Figure 4A). In this study, to prepare the experimental plot having constantly high soil water content, soil water content in the irrigated experimental plot was controlled at constantly more than 20% water content in soil by irrigation. Soil water content in the irrigated experimental plot was constantly controlled to more than 20% (Figure 4B). The averages of soil water contents from April to October in the irrigated experimental plot were 29.9% as detected by B467; 25.2% by AE75 and 24.1% by AE86 in the 2017 growing season. The annual averages of soil water contents from April to October were 16.8 ± 2.0%, 18.4 ± 1.9% and 18.5 ± 1.9% (means ± standard deviations for three sensors) in the non-irrigated experimental plot and 26.4 ± 3.0%, 24.2 ± 4.2% and 23.4 ± 3.0% (means ± standard deviations for three sensors) in the irrigated experimental plot for the 2017, 2018 and 2019 growing seasons, respectively.

In the experimental plots, soil field capacity (FC) that indicates the upper limit of water storage in soil was calculated according to Zotarelli et al. (2013). FC values calculated from B467, AE75 and AE86 in the 2017 growing season were 34.9 ± 2.1%, 30.6 ± 1.4% and 31.5 ± 2.0%, respectively.

Thus, real-time monitoring of soil water content by the wireless sensor networking system suggested that our experimental conditions and the use of an irrigation system realised constantly high soil water content (>20%) during the grapevine growing season.

The timings of bud break, bloom, full bloom and harvest in grapevines of the experimental plot with soil water content controlled to more than 20% by irrigation were the same as those in the non-irrigated experimental plot in the three growing seasons (Table 2). The constantly high soil water content delayed the timing of véraison in the three growing seasons. Grapevines in the irrigated experimental plot showed extended timing of véraison by 10 days, 4 days and 1 day in the 2017, 2018 and 2019 growing seasons compared with those in the non-irrigated experimental plot, respectively. No morphological differences in shoot length, node diameter and internode length during vegetative growth were observed between irrigated and non-irrigated grapevines (data not shown).

Leaf water potential was measured before and after véraison to estimate water status in the experimental plots. No significant differences in leaf water potential were noted between irrigated and non-irrigated plots (Table 3) except the leaf water potential on 21 July 2018. Midday leaf water potential values ranged from −0.40 to −0.99, suggesting no water stress in both experimental plots during the three growing seasons, in accordance with the report by van Leeuwen et al. (2007). The results suggested that the non-irrigated experimental plot had sufficient soil water content for grapevine growth and that soil in the irrigated experimental plot was supplied with an excess of water for grapevine growth.

Changes in transverse berry diameter, berry weight, soluble solids content and acid content were recorded in the 2017 growing season (Figure 5). The weight of 10 berries, soluble solids content and acid content in irrigated grapevines was occasionally lower than those in non-irrigated grapevines. However, all berry qualities except acid content at harvest were comparable between irrigated and non-irrigated grapevines.

Figure 5

During the three growing seasons, there were no significant differences in bunch weight, bunch length, berry number per bunch, weight of 10 berries and soluble solids content at harvest between irrigated and non-irrigated grapevines (Table 4). Transverse berry diameters at harvest in irrigated grapevines were significantly smaller than those in non-irrigated grapevines in the 2018 and 2019 growing seasons. Although there was no significant difference, there was a certain tendency that anthocyanin contents in berry skins of irrigated grapevines decreased by treatment with constantly high soil water content compared with those of non-irrigated grapevines during the three growing seasons (Table 4). Constantly high soil water content decreased anthocyanin accumulation by approximately 80%.