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Research Report

Response of Leaf Optical Properties, Temperature, and Physiology to Variable Kaolin Application Rate

View ORCID ProfileCody R. Copp, Mingchang Liao, View ORCID ProfileJohn A. Bouranis
Am J Enol Vitic.  2025  76: 0760005  ; DOI: 10.5344/ajev.2025.24066
Cody R. Copp
1Department of Horticulture, Oregon State University, 4017 Agriculture and Life Sciences Building, Corvallis, OR 97331;
2Extension Service – Umatilla County, Oregon State University, 418 N Main Street, Milton-Freewater, OR 97862;
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  • For correspondence: cody.copp{at}oregonstate.edu
Mingchang Liao
1Department of Horticulture, Oregon State University, 4017 Agriculture and Life Sciences Building, Corvallis, OR 97331;
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John A. Bouranis
3Department of Environmental Science, University of Arizona, 1177 E 4th Street, Tucson, AZ 85721.
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Abstract

Background and goals Climatic changes in the Pacific Northwest have resulted in more extreme heat events and unpredictable water availability. Kaolin clay particle films are multi-use agricultural tools that can mitigate abiotic stress in grapes. This study was designed to characterize the effects of various kaolin application rates on leaf optical properties and leaf-level physiology, while also providing insight into its optimization under appropriate climatic and stress conditions.

Methods and key findings A field trial was conducted over three seasons with field-grown Syrah grapevines in northeastern Oregon to evaluate the potential of various kaolin application rates (25, 50, and 100%) to reduce water stress and maintain fruit quality. Leaf temperature, leaf water potential, stomatal conductance, and leaf optical properties were measured, and fruit was harvested to determine yield components and berry composition. Kaolin increased leaf reflectance (up to 86%) and decreased transmittance (up to 19%) and absorptance (up to 8%), commensurate with application rate. Leaf temperature trended lower (up to 2.3°C) and stomatal conductance trended higher (up to 47%) with kaolin application, while leaf water potential was largely unchanged. Yield and fruit composition were variable and were not significantly influenced by kaolin application. The effect of kaolin on water stress was most pronounced in the warmest year, but the relationships among kaolin, leaf temperature, and improved stomatal conductance were conserved across years.

Conclusions and significance Kaolin application can manage abiotic stress effectively when applied at higher rates during periods of high temperatures. Although the impact of kaolin application on fruit quality was minimal, overall vine productivity was improved. Thus, kaolin can be an important tool for climate-resilient grape production in this region.

  • light
  • particle film
  • reflectance
  • stomatal conductance temperature
  • water stress

Introduction

Global climate change and increasing average temperatures are influencing grapevine physiological performance and response to abiotic stresses such as heat or water stress (Gambetta 2016). Climate change is also increasing the frequency of extreme heat events, which are less predictable and pose an acute threat to the cultivation of high quality winegrapes (Seneviratne et al. 2021). Heat stress has been studied extensively in grapevines, with a focus on response and mitigation techniques for extreme heat events (Greer and Weston 2010, Webb et al. 2010). Mitigation techniques are often infrastructure-intensive (e.g., shade netting) or subject to resource availability (e.g., evaporative cooling, misting).

Application of kaolin clay particle films to both grapevine canopies and clusters can reduce climate-associated abiotic stress and improve fruit quality (Dinis et al. 2022). Kaolin clay increases the leaf light reflectance, particularly at ultraviolet and infrared wavelengths that would otherwise increase leaf temperature (Glenn and Puterka 2005). Kaolin application is particularly useful when irrigation water is restricted or when overhead evaporative cooling is unavailable. The increase in light reflectance and decrease in leaf temperature allow grapevine leaves to maintain photosynthetic activity under higher ambient temperature conditions, improving water use efficiency (Brillante et al. 2016, Frioni et al. 2019b, Cataldo et al. 2022). In addition to its utility for managing climate change-associated abiotic stress, kaolin provides additional uses for viticulture, such as pest suppression (Glenn and Puterka 2005).

The Pacific Northwest includes diverse viticultural areas that range in climate from cool to warm (i.e., average growing season temperatures of 13 to 19°C) (Jones et al. 2010). In this region, climate change is causing an increase in both long-term average temperatures and the frequency of acute climatic events that complicate management and threaten the fruit quality of currently-planted cultivars (White et al. 2023). Particle film application, shade cloth, and overhead sprinkler cooling systems are already used in the Pacific Northwest to mitigate the effects of heat stress on tree fruit and small fruit such as blueberry (Houston et al. 2018). Kaolin clay, which reduces canopy temperature, prevents sunburn, and improves red color in apples, is applied to orchards across the Pacific Northwest’s Columbia Basin to increase the resilience of apple production to climate-associated abiotic stress (Glenn et al. 2002).

The Columbia Basin is the warmest and most arid grape-growing region in the Pacific Northwest (Jones et al. 2010). With the confluence of increasing risk of heat stress, declining irrigation water availability, and rising cost of production, grapegrowers in this region require additional tools to mitigate abiotic stress and maintain the production of high quality winegrapes. The objective of the present study was to characterize the effects of variable kaolin clay application rate on leaf reflectance, temperature, and physiological responses (e.g., stomatal conductance) in the warm and arid climate of the Columbia Basin region. Evaluating application rate will aid judicious kaolin use by identifying response maxima and potential to reduce material costs. A field experiment was conducted over three years to observe these effects across the growing season under varying climatic conditions.

Materials and Methods

Experimental site and design

The field experiment was conducted from 2022 to 2024 in a commercial vineyard block located near Milton-Freewater, Oregon (45°57′N; 118°25′W; 262 m asl). The site has a 1% slope and is comprised of Freewater very cobbly loam soil, which is distinguished by gravelly alluvium and large cobbles on the soil surface. The vineyard block was planted to Vitis vinifera L. cv. Syrah (clone 470, ENTAV-INRA) in 2007, with 2.1 m between north-south oriented rows and 1.2 m between vines, for a vine density of 3844 vines/ha. Vines were bilaterally cordon-trained, spur pruned, and vertically shoot-positioned, with a fruiting wire 0.8 m above the ground and catch wires at 1.1 and 1.5 m above the ground. The vineyard was irrigated using a drip irrigation line at 0.5 m above the ground and inline emitters (1.6 L/hr flow rate) spaced every 0.6 m. The irrigation schedule was determined by the cooperating vineyard, but irrigation events occurred on a varying frequency of 9 to 23 days, according to environmental conditions (e.g., high temperatures) and plant water status (Supplemental Figure 1).

In 2022, the experiment was arranged as a randomized complete block design with two treatments and four blocks, for a total of eight plots. Each plot contained 24 vines, for a total of 192 vines in the experiment. Border vines between plots were excluded from measurements. The treatments included an untreated control (CON) and kaolin treatment (Surround WP, NovaSource) applied to canopy and clusters at the maximum label rate of 56 kg/ha (K56). Kaolin was applied evenly to both sides of the entire canopy, including the fruit zone, using a piston backpack sprayer (Solo 425) at a 6% (w/v) concentration. Treatment application began on 20 July 2022 at bunch closure (Eichhorn-Lorenz [E-L] 32). Reapplications were made on 12 Aug and 1 Sept 2022 at intervals of 23 and 20 days, respectively.

In 2023 and 2024, multiple kaolin application rates were evaluated in the same vineyard block from 2022. The experiment was arranged as a randomized complete block design with four treatments and four blocks, for a total of 16 plots. Each plot contained 12 vines, for a total of 192 vines in the experiment. The treatments consisted of an untreated control (CON) and kaolin treatments applied to the whole canopy at rates of 14 (K14), 28 (K28), and 56 (K56) kg/ha. Kaolin was applied evenly to both sides of the entire canopy, including the fruit zone, using a piston backpack sprayer (Solo 425) at a 6% (w/v) concentration. Treatment application began on 28 June 2023 and 24 June 2024 at approximately pea-sized berry stage (E-L 31). Reapplications were made on 13 July and 8 Aug at intervals of 15 and 26 days, respectively (2023), and on 17 July and 7 Aug at intervals of 23 and 21 days, respectively (2024).

Weather conditions

Regional climate and precipitation data were accessed from a weather station (College Place, AgWeatherNet, Washington State University) ~10 km from the experimental site. Water year precipitation was totaled from 1 Oct to 30 Sept. Seasonal precipitation, growing degree days (base 10°C; GDD), and reference evapotranspiration (ETo) were totaled from 1 April to 30 Sept.

Measurement of leaf optical properties

Leaf reflectance, absorptance, and transmittance were determined on 18, 25, and 30 July, and 6 Aug 2024. A quantum sensor field method (Schultz 1996) and a spectrometer (LI-180, LI-COR Biosciences) were used to measure ambient, reflected, and transmitted light (400 to 700 nm). At each date, three leaves were sampled per plot within 1 hr of solar noon (~1300 hr). Sampled leaves were fully expanded and exposed, on the west side of the canopy, and located within the top third of the canopy. Reflectance was calculated as the relative proportion of reflected light compared to ambient:

reflectance=reflected lightambient light

Transmittance was calculated as the relative proportion of transmitted light compared to ambient:

transmittance=transmitted lightambient light

Absorptance was calculated as the remaining portion of light unaccounted for by reflected or transmitted light:

absorptance=1−reflectance−transmittance

Additionally, spectra were generated for the three parameters by calculating each using the photon flux density at each wavelength between 380 and 780 nm.

Leaf temperature, water potential, and gas exchange

Leaf temperature (Tleaf) and stomatal conductance to water (gs) were measured using a porometer (LI-600, LI-COR Biosciences). In 2022, three leaves per plot were sampled during a 1-hr window between 1300 and 1430 hr on 10 dates (20 and 28 July; 3, 12, 18, 25, and 31 Aug; and 7, 14, and 20 Sept). In 2023, four leaves per plot were sampled during a 1-hr window between 1300 and 1500 hr on eight dates (22 and 29 June; 5, 12, and 26 July; and 3, 16, and 28 Aug). In 2024, three leaves per plot were sampled during a 1-hr window between 1230 and 1530 hr on 10 dates (2, 9, 17, 22, and 30 July; 6, 13, 20, and 28 Aug; and 4 Sept). Sampled leaves were fully expanded and exposed, on the west side of the canopy, and located within the top third of the canopy. Leaf water potential (Ψleaf) was measured using a Scholander pressure chamber (Model 615, PMS Instruments). In 2022, the measurements were taken similarly to, and on the same dates as, Tleaf and gs. In 2023, two leaves per plot were sampled during a 1-hr window between 1300 and 1500 hr on seven dates (22 and 29 June; 5, 12, and 26 July; and 3 and 16 Aug). In 2024, three leaves per plot (to match porometer measurements) were sampled during a 1-hr window between 1230 and 1530 hr on seven dates (22 and 30 July; 6, 13, 20, and 28 Aug; and 4 Sept).

To compare the relationship between Tleaf and gs across years and environmental conditions, the departure from the mean was calculated using sample values and the sample mean across all treatments at each sample date, as follows:

xx¯−1

where x is a single measurement, x¯ is the sample mean for each measurement date, and all departure values fall between −1 and 1.

Fruit yield and composition

Fruit was harvested to determine yield, yield components, and fruit composition prior to commercial harvest on 5 Oct 2022, 27 Sept 2023, and 27 Sept 2024. Two vines per plot were harvested and the fruit was weighed. A subsample of five clusters per plot was selected for determination of yield components and fruit composition. In the lab, clusters were dissected to determine berry number and berry mass. Berry number was not determined in 2024. A 250-g sample of intact, destemmed berries was submitted to a commercial laboratory for quantification of catechin, quercetin glycosides, tannin, polymeric anthocyanins, and total anthocyanins (ETS Labs, Walla Walla, WA). Briefly, samples with consistent mass were extracted in a proprietary, wine-like solution and the resulting extract was used for quantification of specific phenolic compounds by high performance liquid chromatography (ISO 17025-accredited). Concentration of phenolic compounds is expressed in mg/L of berry extract. The remaining destemmed berries were juiced and a 60-mL sample was submitted with the berry sample to the same lab for quantification of total soluble solids (TSS), pH, titratable acidity (TA), malic acid, tartaric acid, yeast assimilable nitrogen (YAN), and potassium. Quantification was conducted using mid-infrared spectroscopy and proprietary reference calibrations for each component (Minerva, ETS Laboratories, ISO 17025-accredited).

Data analysis

Analyses were conducted and figures generated using R statistical software (ver. 4.2.3; R Core Team 2023). Linear models were fitted using the ‘lmerTest’ package. Data from 2022 were analyzed separately using a one-way analysis of variance (ANOVA) with treatment as the main factor, or a two-way ANOVA with treatment and date as main factors when multiple observations were made within a year. Data from 2023 and 2024 were analyzed using a two-way ANOVA with treatment and year as main factors; when multiple observations were made within a year, data were analyzed using a three-way ANOVA with treatment and year as main factors and date as a nested factor within year. ANOVA assumptions were assessed using the Shapiro-Wilk test for normality and Levene’s test for homogeneity of variance. Data failing either of these tests were transformed for analysis and backtransformed for presentation in tables and figures where noted. Figures were generated using the ‘ggplot2’ package. Regression analyses were conducted using the ‘stats’ package. Principal component analysis (PCA) and biplot generation were conducted using the ‘ggfortify’ package.

Spectral data for leaf reflectance, transmittance, and absorptance that were collected in 2024 were also analyzed for significant treatment differences at each wavelength. Data were processed using the ‘tidyverse’, ‘dplyr’, and ‘purrr’ packages. For each wavelength, a linear model was fitted with the fraction of reflected, transmitted, or absorbed light as the response variable and the treatment group as the predictor variable. To control for false discoveries and correct for multiple hypothesis testing, the Benjamini-Hochberg procedure was used to correct for p values across all wavelengths and measurements.

Results

Weather conditions and phenological development

Weather conditions were generally above the 16-yr average with respect to precipitation, seasonal temperature, and GDD (Table 1). 2022 had the highest precipitation, highest average summer temperature, most extremely hot days (>40°C), highest summer GDD accumulation, and highest evaporative demand (ETo). While 2023 was drier and had higher seasonal GDD, weather conditions were slightly milder than in 2022 with respect to average summer temperature, extremely hot days, and ETo. 2024 was the driest year during the study but was above the 16-yr precipitation average and otherwise mild with respect to extremely hot days, GDD, and ETo. The average summer temperature and number of extremely hot days for 2024 were below the 16-yr average, suggesting that the warmest part of the year was relatively cool compared to recent years.

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Table 1

Precipitation, temperature, growing degree days (GDD), evapotranspiration (ETo), and vine phenological development from 2022 to 2024. Data were accessed from a weather station (College Place, AgWeatherNet) 10 km from the experimental site in Milton-Freewater, OR.

There was some variability in phenological development between years (Table 1). Bloom was ~20 days later in 2022 than in 2023 and 2024, presumably due to cooler spring temperatures in 2022 (Figure 1). However, the warm temperatures in July and August 2022 reduced this phenological gap at veraison and harvest. Despite a late budbreak date in 2023, warm temperatures in late April through June advanced phenological development by bloom. Budbreak in 2024 occurred relatively early, but milder temperatures across summer may have contributed to later veraison and harvest dates than expected, similar to 2022 and 2023 (Figure 1).

Figure 1
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Figure 1

Temperature and precipitation in 2022 (A), 2023 (B), and 2024 (C). Data were accessed from a weather station (College Place, AgWeatherNet) 10 km from the experimental site in Milton-Freewater, OR. Mean daily temperature is represented by the solid lines and minimum and maximum daily temperatures are represented by the dotted lines. Precipitation is represented by the gray bars.

Leaf optical properties

The kaolin treatments significantly altered leaf optical properties in 2024 (Table 2). Across measurement dates, reflectance increased with kaolin application rate, though the treatment effect varied at each measurement date (TRT × DATE: p = 0.030). Reflectance for K56 was significantly higher than CON at all measurement dates, but it was only higher than K14 and K28 for the first three measurement dates (Table 3). This suggests that the difference in reflectance among the three kaolin application rates attenuated with time as the clay residue diminished between applications (17 July and 7 Aug 2024). There was a significant treatment effect on both transmittance and absorptance across measurement dates (Table 2). Transmittance was significantly higher for CON than for the three kaolin application rates. Absorptance was highest for CON and was reduced stepwise with increasing application rate.

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Table 2

Leaf optical properties measured on several dates (17, 25, and 30 July and 6 Aug) in 2024. Values are expressed as fractions of light within the visible spectrum (400 to 700 nm). Data are means across measurement dates (n = 4). CON, K14, K28, and K56 correspond to kaolin applied at 0 (control), 14, 28, and 56 kg/ha, respectively.

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Table 3

Leaf reflectance measured on several dates in 2024. Values are expressed as fractions of light within the visible spectrum (400 to 700 nm). Data are means (n = 4). The second treatment application occurred on 17 July prior to the first measurement. The third treatment application occurred on 7 Aug following the last measurement. CON, K14, K28, and K56 correspond to kaolin applied at 0 (control), 14, 28, and 56 kg/ha, respectively.

The differences in leaf optical properties between the kaolin treatments and CON varied across wavelengths (Figure 2). Reflectance was significantly higher for K14 below 703 nm, for K28 below 710 nm, and for K56 below 730 nm. Differences in transmittance between the kaolin treatments and CON were more variable, but the fraction of transmitted light was generally lower for kaolin-treated leaves across wavelengths. The differences in absorptance between the kaolin treatments and CON were also variable, but there were significant treatment effects at important wavelengths of blue and red light corresponding to peaks in chlorophyll absorption and photosynthetic rate (An) (Keller 2020, Liu and van Iersel 2021). Absorptance was lower for all kaolin treatments compared to CON at blue light wavelengths (380 to 500 nm). Only K28 and K56 had lower absorptance values compared to CON at red light wavelengths between 620 and 680 nm.

Figure 2
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Figure 2

Leaf optical properties measured on 18 July 2024, one day after treatment application on 17 July 2024. Values are expressed as fractions of light at each wavelength. Each line represents the treatment mean (n = 12). CON, K14, K28, and K56 correspond to kaolin applied at 0 (control), 14, 28, and 56 kg/ha, respectively. The visible light spectrum is included below each plot. Gray shading in the comparison chart below each plot indicates that there is a significant difference (p < 0.05) at that wavelength between CON and the corresponding kaolin treatment.

Tleaf, Ψleaf, and gs

There was a significant treatment effect on Tleaf across measurement dates in 2022 and 2024, and a similar but not statistically significant trend was observed in 2023 (Table 4). In all three years, Tleaf was highest for CON and lowest for K56. There was a greater difference between CON and K56 in 2022 than in 2023 and 2024. There was a significant treatment effect on Ψleaf in 2022, but not in the other two years. In 2022, Ψleaf was, on average, lower than in 2023 and 2024. In all three years, Ψleaf was highest for K56 and lowest for CON. There was a significant treatment effect on gs in 2022, but not in the other two years. Similar to Ψleaf, gs was highest for K56 and lowest for CON.

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Table 4

Leaf temperature (Tleaf), leaf water potential (Ψleaf), and stomatal conductance (gs) for 2022 to 2024. Data are means across measurement dates (n = 4). CON, K14, K28, and K56 correspond to kaolin applied at 0 (control), 14, 28, and 56 kg/ha, respectively.

Despite high variability in Tleaf and gs across measurement dates and years, there is linearity in the relationship between Tleaf and gs. Regression analysis using the departures from the mean exhibits a negative linear relationship between Tleaf and gs in accordance with kaolin treatment levels (Figure 3). Across the range of values, a 10% reduction in Tleaf is associated with a maximum 50% increase in gs. Positive departures from mean Tleaf are associated with CON observations, and negative departures from mean Tleaf are associated with K56 observations, with K14 and K28 observations clustered around the mean. The inverse is true for departures from mean gs.

Figure 3
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Figure 3

Relationship between leaf temperature (Tleaf) and stomatal conductance (gs) from 2022 to 2024. Departure from the mean was calculated as xx¯−1, where x is a single measurement and x¯ is the sample mean for each measurement date. Data points are treatment means for each measurement date (n = 4) and were used for linear regression analysis: y = −6.16x − 3.19 × 10−11 (R2 = 0.44, p < 0.001). CON, K14, K28, and K56 correspond to kaolin applied at 0 (control), 14, 28, and 56 kg/ha, respectively.

In 2022, K56 altered the relationship between Ψleaf and gs across measurement dates compared to CON (Figure 4). As Ψleaf increased, gs was higher for K56 than CON. Thus, kaolin application appeared to increase gs at high leaf water status. While the relationship between Ψleaf and gs is often fit with a logistic function (Levin et al. 2019), the logistic models did not fit the data significantly better than a linear model. The same linear relationship between Ψleaf and gs was not clearly observed in 2023 or 2024.

Figure 4
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Figure 4

Relationship between leaf water potential (Ψleaf) and stomatal conductance (gs) in 2022. Data points are treatment means for each measurement date (n = 4). CON and K56 correspond to kaolin applied at 0 (control) and 56 kg/ha, respectively. CON linear regression equation: y = 0.4396x + 0.7937 (R2 = 0.62, p < 0.001); K56 linear regression equation: y = 0.5603x + 1.0091 (R2 = 0.63, p < 0.001).

PCA conducted on kaolin rate, Tleaf, gs, reflectance, transmittance, and absorptance data collected over three dates in 2024 demonstrates some separation of the K56 responses and largely confirms the significant treatment effects associated with Tleaf and leaf optical properties from the ANOVAs (Figure 5). The first two principal components accounted for 72% of the observed variance. Tleaf was strongly associated with leaf transmittance, but not reflectance or absorptance. The rate of kaolin application (i.e., kg/ha) was positively associated with leaf reflectance and negatively associated with absorptance. Both Tleaf and transmittance were negatively associated with gs. Ψleaf was excluded from analysis as it was not observed on all measurement dates, nor did it exhibit significant differences among treatments.

Figure 5
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Figure 5

Principal component analysis biplot of kaolin rate (kg/ha), leaf temperature (Tleaf), stomatal conductance (gs), and leaf optical properties measured across three dates (17 and 30 July and 6 Aug 2024). CON, K14, K28, and K56 correspond to kaolin applied at 0 (control), 14, 28, and 56 kg/ha, respectively.

Fruit yield and composition

There was no significant treatment effect on yield or any of the yield components in this study (Table 5). Still, there were notable trends among the treatments. The K56 treatment consistently produced among the highest vine yields and berry masses in all three years, though the CON treatment did not always produce the lowest yields or berry masses. Vine yields and cluster masses were consistent across years, but clusters per vine and berry mass varied across years.

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Table 5

Vine yield and yield components at harvest. Data are means (n = 4). Fruit was harvested on 5 Oct 2022, 27 Sept 2023, and 27 Sept 2024. CON, K14, K28, and K56 correspond to kaolin applied at 0 (control), 14, 28, and 56 kg/ha, respectively.

In 2022, there was a significant difference in malic acid concentration among treatments, such that CON had a lower malic acid concentration (Table 6). There was no treatment effect on any of the other juice variables. Across 2023 and 2024, there was a significant difference in TA among treatments, such that CON had the lowest and K56 had significantly higher TA. There was no treatment effect on any of the other juice variables across 2023 and 2024, though there were some noticeable trends. TSS trended lower with increasing kaolin application rate in 2023 and 2024, but the sugar per berry was high for K56 in all three years. K56 also exhibited lower pH values across all years. Tartaric acid, YAN, and potassium were highly variable.

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Table 6

Juice composition at harvest. Data are means (n = 4). Fruit was harvested on 5 Oct 2022, 27 Sept 2023, and 27 Sept 2024. CON, K14, K28, and K56 correspond to kaolin applied at 0 (control), 14, 28, and 56 kg/ha, respectively. TSS, total soluble solids; TA, titratable acidity; YAN, yeast assimilable nitrogen.

There were no significant differences in berry phenolic composition between treatments in all years of the study, though some trends were evident (Table 7). In 2022, K56 had lower tannin but higher total anthocyanins and quercetin glycosides than CON. In 2023, the concentrations of tannin, polymeric anthocyanins, and total anthocyanins increased with kaolin application rate, but concentrations of catechin and quercetin glycosides were highest for CON. In 2024, K14 generally had the highest concentration across phenolic compounds, while K56 had among the lowest. There was high variability in phenolic composition between 2023 and 2024, though the effect of year was not statistically significant for total anthocyanins.

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Table 7

Berry extract phenolic composition at harvest. Data are means (n = 4). Fruit was harvested on 5 Oct 2022, 27 Sept 2023, and 27 Sept 2024. CON, K14, K28, and K56 correspond to kaolin applied at 0 (control), 14, 28, and 56 kg/ha, respectively.

Discussion

This study reports the effect of variable kaolin application rate on leaf optical properties and leaf-level physiology, such that Tleaf was reduced and, in some cases, gs was increased. The net effect of these changes on reproductive growth and fruit composition was small. This study is the first to evaluate many of these responses at different application rates, which will ultimately allow users to optimize applications and avoid excess material costs. The response of kaolin application was most pronounced in the first year of the study, which consequently had the hottest conditions during the experimental period (i.e., late June through early September). Thus, kaolin clay has potential as an alternative to water-based tools (e.g., supplemental irrigation, evaporative cooling) for reducing heat and water stress in warm climate vineyards. The present study will, in part, assist vineyard managers to use this tool under appropriate climatic and abiotic stress conditions.

Kaolin alters grapevine leaf optical properties commensurate with application rate

The propensity of kaolin to reflect light is the primary interest of previous studies that have characterized its effects on leaf optical properties. Reflectance, transmittance, and absorptance for untreated leaves in this study (Table 2 and Figure 2) are largely similar to those previously reported, though the fractions of reflected and transmitted light were slightly lower than in other reports (Cabello-Pasini and Macías-Carranza 2011, Lobos et al. 2015, Tosin et al. 2019). Kaolin application can increase the fraction of reflected light by up to ~25%, particularly at important blue and red wavelengths (Dinis et al. 2022). In this study, the maximum observed increase in leaf reflectance was just over 10% (Table 3), similar to the response observed by Tosin et al. (2019). The difference in the effect is likely due to the density of kaolin application or deposition, which is not clearly reported by Dinis et al. (2022). A consistent effect of kaolin on reflectance across wavelengths in the visible spectrum (Figure 2) is related to the white color of the substance, whereby light across wavelengths is evenly reflected. This is particularly noticeable for the local reflectance maximum at green wavelengths, which is much less pronounced for kaolin-treated leaves compared to untreated leaves (Figure 2).

In addition to reflectance, this study presents the effects of kaolin on leaf transmittance and absorptance, which are seldom reported elsewhere for grapevines (Shellie and King 2013b, Lobos et al. 2015, Tosin et al. 2019). The effect of kaolin on the fraction of transmitted light was statistically significant, but marginal in proportion to total light (Table 2). The remaining and largest fraction of light is accounted for by absorptance. Reduced absorptance is context-dependent; kaolin-treated leaves may be protected from photooxidative damage under saturating light conditions but may experience reduced photosynthesis under light-limited conditions (Dinis et al. 2022). Thus, kaolin is most often applied under high light and temperature conditions to maximize both photooxidative protection and photosynthesis. Absorptance spectra responded somewhat differently to kaolin application than reflectance spectra insofar as the response of absorptance varied by wavelength and kaolin application rate (Figure 2). Absorptance values for the lower rates of kaolin were not significantly different from the control at all or some of the red wavelengths important for photosynthesis, which means that the use efficiency of photosynthetically active radiation (PAR) may not be significantly different from the control (Liu and van Iersel 2021).

Rosati et al. (2007) measured leaf reflectance, transmittance, and absorptance with kaolin application in almond and walnut and observed that, despite increases in reflectance and decreases in absorptance, kaolin can increase the use efficiency of absorbed light. As such, a decrease in absorptance may not necessarily mean a decrease in An because grapevine leaves do not use all of incident PAR under sunny conditions for photosynthesis (Keller 2020). The use efficiency of absorbed light and the implications for leaf photooxidative stress were not evaluated in this study.

Unsurprisingly, the positive relationship between kaolin rate and reflectance and the negative relationships between kaolin rate and transmittance or absorptance are strongly linear. The fractions of reflected, transmitted, and absorbed light across the visible spectrum (400 to 700 nm) presented in Table 2 further characterize these relationships. Reflectance increased proportionately with kaolin rate, whereas the reduction in transmittance was similar among all kaolin rates compared to the untreated control. Absorptance exhibited a stepwise decrease commensurate with the increase in kaolin rate, although the maximum rate (56 kg/ha) was the only treatment for which absorptance was significantly different from the others.

It remains unclear whether the effect of kaolin on leaf optical properties is less sensitive to environmental conditions than the leaf-level physiological responses measured in this study, because optical properties were measured only in 2024. Still, the effect of kaolin on leaf optical properties was significant in 2024 despite no significant differences in Ψleaf or gs (Tables 2 and 4). Leaf optical properties are subject to variation in environmental conditions and plant development, so it is unclear whether similar results would have been observed in the other two years of the study (Cabello-Pasini and Macías-Carranza 2011). Overall, increasing kaolin rate predictably altered reflectance and absorptance despite subtle spectral differences among the treatments (Figure 2). Additional study is required to understand how the effects of varied application rate on leaf optical properties alter photosynthesis and photochemical efficiency.

Kaolin application can improve grapevine water stress response under warm conditions

The effect of kaolin on physiological responses related to water relations and gas exchange is widely documented in grapevine and other crop plants. It is commonly reported that kaolin application increases An, transpiration (E), and gs, especially under high temperature conditions that would otherwise reduce these variables (Frioni et al. 2019a, 2019b, Dinis et al. 2022). Indeed, kaolin is thought to prevent high temperature-induced inhibition of these processes rather than functionally promoting them. Kaolin application has also been observed to have no effect (Cataldo et al. 2022) or even reduce An, E, and gs under variable environmental conditions (Shellie and King 2013b, Lobos et al. 2015, Brillante et al. 2016).

In the present study, the improvement—or maintenance—of gs with kaolin application was most pronounced in 2022, which had the most extreme environmental conditions with respect to average summer temperature, summer GDD, summer ETo, and greatest number of extremely hot (>40°C) days (Tables 1 and 4). This study provides some evidence that the relative effect of kaolin on the relationship between Tleaf and gs is conserved across years and variable weather conditions (Figure 3). The effect on the relationship between absolute Tleaf and gs, however, may scale with ambient weather conditions in a way that is difficult to characterize here. Some reports assert that the effectiveness of kaolin at reducing Tleaf and increasing gs is more pronounced under warmer conditions (Shellie and King 2013b, Dinis et al. 2022). In other studies, ambient temperatures were mild enough (i.e., <35°C) that kaolin had less effect (Lobos et al. 2015, Cataldo et al. 2022). The effectiveness of kaolin to reduce Tleaf and improve An is likely temperature-dependent, though the exact relationship is unclear.

The response of Ψ to kaolin application is less variable than gs, and there is often no difference between treated and untreated leaves (Lobos et al. 2015, Dinis et al. 2022). Tleaf has a less direct effect on Ψ than, for example, gs, and thus one would expect a smaller effect of kaolin application on Ψ. Yet, grapevines can regulate Ψ through stomatal closure under the same stressful conditions in which kaolin may be more effective. Cataldo et al. (2022) observed that under extreme heat and drought conditions that severely depressed gs, kaolin increased both predawn water potential and Ψleaf relative to the untreated control. Though Ψ appears to be more resistant to kaolin application by the magnitude of the response observed in this study (Table 4), this relationship may be altered under high temperature conditions.

The relationship between water status (e.g., Ψ) and gs can describe the water stress response of a plant, or how resistant a plant is to reductions in productivity under increasing water deficits. In particular, the relationship between Ψleaf and gs is used in grapevine studies to characterize the leaf-level response to increasing water deficit (Levin et al. 2019). Brillante et al. (2016) reported no difference in the relationship between stem water potential (Ψstem) and gs among kaolin-treated and untreated leaves, even across a wide range of Ψstem values. The present study observed a difference between treated and untreated leaves, though kaolin’s ability to alter this water stress response was limited at low Ψleaf (<−1.4 MPa) (Figure 4). Cataldo et al. (2022) observed that kaolin can maintain An at high temperatures and low Ψ; gs however, was significantly higher for kaolin-treated leaves only at moderate Ψleaf values between −1.5 and −1.2 MPa.

The effect of kaolin on the water stress response (i.e., gs) may actually be nonlinear, increasing from high to moderate Ψ and decreasing as Ψ reaches severely water-stressed values. At the inflection point, the vine-level effect of increasing water deficit likely outweighs the positive impact of kaolin on leaf-level physiology. Under high water deficit, gs is more strongly governed by Ψ and decoupled from temperature, the primary target of kaolin clay application (Gambetta et al. 2020). The linearity of the relationship observed in this study in 2022 may be attributable to both the narrow range of Ψ values and other environmental factors that influence gs (Figure 4). A strong linear relationship was not observed in 2023 or 2024 and may be due, in part, to higher average Ψleaf across the season (Table 4 and Supplemental Figure 1). In conjunction with the observations of Cataldo et al. (2022) described above, this study provides discontinuous evidence that the effect of kaolin is maximized at moderate Ψ values (e.g., −1.5 to −1.2 MPa). Ultimately, kaolin can provide some relief to mild water stress, but supplemental irrigation is more effective at relieving severe water stress when it is available (Frioni et al. 2019b).

Water stress responses are also influenced by genotype and can be assessed along a spectrum of isohydric to anisohydric responses, or at what water status threshold (e.g., Ψ) grapevines increase stomatal closure to regulate Ψ (Levin et al. 2019, Gambetta et al. 2020). Despite grapevines having tighter stomatal control than some other species, different varieties exhibit wide variation from iso- to anisohydry and some studies have noted conflicting responses (Chaves et al. 2010, Levin et al. 2019, Serrano et al. 2024). Variable responses of gs to Ψ by genotype may partially explain why the highest average gs values were observed in 2022 despite the lowest average Ψleaf among all three years (Table 4).

In 2023, when average gs values were lowest, vines experienced moderate levels of water stress early in the season, followed by rewatering (Supplemental Figure 1); in 2022, vines were more slowly acclimated to water stress conditions. A study evaluating water stress recovery in potted vines reported that Syrah vines—the same variety used in this study—subjected to high water stress recovered only 66% of gs capacity after rewatering (Dayer et al. 2017). It is therefore plausible that early water stress contributed to low average gs values in 2023 compared to the other two years. The dynamic response of gs to the timing, intensity, and genotypic influence of water stress cannot be fully explained in the present study and is further complicated by the variable stress responses exhibited by Syrah (Gambetta et al. 2020).

Kaolin has variable effects on fruit composition and may delay ripening in cool years

Measured improvements in An with kaolin application are presumed to improve photosynthate (i.e., sugar) production, but the consequences for fruit sugar accumulation are less direct. Kaolin application has seldom been reported to increase TSS (Shellie and King 2013a). Vine productivity and sugar accumulation are complicated by increases in fruit size promoted by kaolin application, which is consistently reported for other fruit (Spiers et al. 2008, Glenn 2012). For grapevines, larger berries have a higher photosynthate demand and thus may have lower concentration (i.e., TSS) despite a similar or higher sugar content (i.e., g/berry) (de Rességuier et al. 2024). This was observed in the present study insofar as berry mass trended higher and TSS trended lower with kaolin application and rate, but sugar content (g/berry) was largely the same (Tables 5 and 6). Increased fruit size in kaolin-treated vines with little-to-no change in TSS has previously been reported (Shellie 2015, Frioni et al. 2019a). Thus, kaolin can improve whole vine sugar production such that a greater mass of sugar is produced and translocated to a larger yield of fruit in kaolin-treated vines. This is arguably of less enological significance because berry sugar concentration (TSS) is the primary berry sugar trait evaluated for fruit and wine quality.

The inverse has also proved to be true: sugar accumulation in kaolin-treated vines with reduced An may lag behind untreated vines during ripening (Cataldo et al. 2022) and at maturity (Brillante et al. 2016, Dinis et al. 2020). In the present study, the greatest reduction in TSS for kaolin-treated vines, though not statistically significant, was observed in the final and coolest year (Table 6). It is important for practitioners to consider that kaolin application may delay sugar accumulation, particularly when temperatures are mild or cool.

The effect of kaolin on acid dynamics in ripening berries is likely a function of both delayed ripening and a cooling effect on clusters, which can slow degradation of malic acid. In this study, pH trended lower and TA higher with kaolin application (Table 6), in agreement with other reports (Frioni et al. 2019a, Dinis et al. 2020). Even more studies report an effect only on pH (Brillante et al. 2016), no effect (Shellie and King 2013a, Teker 2023), or even the opposite effect observed in this study (Lobos et al. 2015). The effect of kaolin on malic acid was significant only in 2022, which was the year with the greatest summer GDD and number of days above 40°C. The effect of kaolin and cluster cooling on malic acid is not consistent among other published reports, so any effect of kaolin application on fruit ripening rate is likely contributing to differences in malic acid.

Among the most reported effects of kaolin application on fruit composition are changes to phenolic compounds. The results of this study are quite variable and not statistically significant but do follow some of the trends observed in other reports (Table 7). Kaolin application consistently increases berry anthocyanin concentration (Song et al. 2012, Shellie and King 2013a, Lobos et al. 2015, Brillante et al. 2016, Dinis et al. 2016, Frioni et al. 2019a, 2019b, Valentini et al. 2021). The effect of kaolin is likely twofold; first, that reduced berry temperature optimizes stimulation of anthocyanin synthesis, and second, that reduced berry temperature slows the degradation of these temperature-sensitive compounds (Dinis et al. 2016, 2022, Keller 2020). Dinis et al. (2016) provided direct gene expression evidence for stimulation of anthocyanin synthesis while also suggesting that differences in anthocyanins between treated and untreated fruit at successive harvests are related to anthocyanin degradation in untreated fruit.

It is unclear why kaolin application did not influence anthocyanin concentration in this study, but variable varietal response may have contributed. Luzio et al. (2021) reported differences in the response of anthocyanins to kaolin application in seven varieties, which did not include the variety used in this study, Syrah. Unfortunately, there appear to be no reports of Syrah anthocyanins and kaolin application. The resistance of Syrah in this study to anthocyanin alterations is likely complex but may be influenced, among other attributes, by the loose cluster morphology (i.e., reduced berry temperature) and unique anthocyanin profile (e.g., higher proportion of more stable acylated anthocyanins) of Syrah (Smart and Sinclair 1976, Ortega-Regules et al. 2006).

The reported effects of kaolin on total phenolics and other phenolic compounds are less consistent, but an increase in concentration has been observed (Brillante et al. 2016, Dinis et al. 2016, Frioni et al. 2019b, Valentini et al. 2021). The present study does not clarify the complex influences of environmental conditions, abiotic stress, and kaolin on non-anthocyanin phenolic compounds. Lobos et al. (2015) observed similarly variable responses as reported here. In contrast to anthocyanins, reports of improved phenolic concentrations with kaolin application do not align neatly with significant improvements in leaf-level physiology (Brillante et al. 2016).

Practical considerations for optimizing kaolin application in vineyards

The present study contributes to the existing literature on vineyard kaolin applications by evaluating the effect of variable application rate on leaf optical properties, Tleaf, and leaf-level physiology. Application rate was evaluated in 2023 and 2024 by using 100, 50, 25, and 0% of the maximum label rate (56, 28, 14, and 0 kg/ha/application) for the predominant commercial kaolin product in the United States (Surround WP, NovaSource). The label for this product recommends a range of 14 to 56 kg/ha for insect pests, sunburn, and heat stress, but the results of this study indicate that the most consistent and greatest improvement for the measured responses was achieved at 56 kg/ha. This rate produced significantly lower Tleaf, higher Ψleaf, and higher gs in 2022 and was the only rate to significantly reduce Tleaf in 2024 (Table 4). For other measurements of yield and fruit composition, the response, while not statistically significant, was usually scalar with the application rate (Tables 5 to 7). Relatively few studies report the rate (kg/ha or w/v and v/ha) of kaolin application and instead report only the concentration of the mix (w/v), which complicates comparisons of the application rate effect across studies. The studies reviewed herein that report application rate (kg/ha or w/v and v/ha) used a high application rate between 56 and 60 kg/ha (Shellie and King 2013a, 2013b, Shellie 2015, Ferrari et al. 2017).

Increases in global mean temperature will indubitably affect grape cultivation, but extreme heat events pose a more acute and unpredictable challenge (Gambetta 2016). A higher frequency of extreme heat events is forecasted for grapegrowing areas in the region of this study (McKinnon and Simpson 2022). The number of days over 40°C is used herein to approximate the frequency of extreme heat events that would suppress physiological function or even cause damage to vegetative and reproductive organs (Keller 2020). Consequently, the effect of kaolin on leaf-level physiology was strongest in 2022, which had the highest number of days over 40°C, highest average summer temperature, and highest summer GDD (Table 1). Because ambient temperatures of 30°C can produce leaf and fruit surface temperatures greater than 40°C, kaolin application may be useful when temperatures exceed 35°C for several days or for single 40°C days (Riley 2014, Frioni et al. 2019a). The weather conditions in 2023 and 2024 at the study site may not be the ideal conditions for judicious kaolin application, and ultimately, the vintage effect was more significant than kaolin application effect for most measured variables.

This study can also guide future work that interrogates the role of kaolin in irrigation scheduling. Measurements of Ψ are often used to initiate irrigation according to thresholds that are empirically correlated with desirable vegetative growth and fruit quality responses (van Leeuwen et al. 2009, Levin and Nackley 2021). Moderate water stress is associated with Ψstem values approaching −1.1 MPa and Ψleaf values between approximately −1.3 and −1.1 MPa (van Leeuwen et al. 2009, Deloire et al. 2020). In the present study, gs was over 26% higher for kaolin-treated leaves above approximately −1.3 MPa, indicating an altered water stress response (Figure 4). Under moderate water stress, the Ψleaf irrigation threshold could theoretically be decreased by 0.1 to 0.2 MPa without a significant penalty to gs.

In regions with a Mediterranean climate characterized by warm summers and wet winters, the altered water stress response may allow producers to save water by delaying irrigation initiation, albeit with important implications for fruit yield and quality (Kar et al. 2023). Munitz et al. (2020) imposed various Ψstem thresholds for irrigation onset and reduced water use by 9 to 22 mm (20 to 32%) by delaying onset by 0.2 MPa within the range of −1.2 to −0.8 MPa. Kaolin application could confer similar water savings when Ψ is consistently monitored. Such irrigation strategies are increasingly important for grapegrowers in the western U.S., where water availability is increasingly unpredictable and precarious (Bambach et al. 2022). The present study did not investigate the interaction of kaolin and irrigation scheduling, so future work is required to understand whether kaolin can be used to delay irrigation initiation and contribute to climate-resilient water management.

Conclusion

This study characterized the effect of kaolin clay application rate on leaf optical properties, leaf-level physiology, and fruit composition across three climatically varied years in a warm, semiarid, grapegrowing region. Kaolin increased leaf reflectance and reduced absorptance across the wavelengths of the visible spectrum, commensurate with the application rate. Similarly, the greatest reduction in Tleaf and improvement in gs was observed with the highest application rate. The effects were, however, far less pronounced in the final two years, which had both cooler average summer temperatures and fewer extreme heat events. The impact on fruit quality was minimal, though there is some evidence presented here that kaolin application improved overall vine productivity. In the warmest year, kaolin altered the water stress response of vines by improving gs at moderate Ψleaf (−1.4 to −1.0 MPa) without modifying water supply. Abiotic stress can be managed with kaolin most effectively when it is applied at a higher rate and reserved for periods of high temperatures.

Supplemental Data

The following supplemental materials are available for this article in the Supplemental tab above:

Supplemental Figure 1 Leaf water potential (Ψleaf) across the 2022 (A), 2023 (B), and 2024 (C) seasons. Irrigation events are represented by the vertical dashed lines. CON, K14, K28, and K56 correspond to kaolin applied at 0 (control), 14, 28, and 56 kg/ha, respectively.

Footnotes

  • This work was conducted with financial support from the Oregon Wine Research Institute, the Agricultural Research Foundation, and ETS Laboratories. The authors would like to thank Aidan Wiggins and Melinda Cramp for data collection assistance and the vineyard cooperators for field space and plot maintenance.

  • Copp CR, Liao M and Bouranis JA. 2025. Response of leaf optical properties, temperature, and physiology to variable kaolin application rate. Am J Enol Vitic 76:0760005. DOI: 10.5344/ajev.2024.24066

  • By downloading and/or receiving this article, you agree to the Disclaimer of Warranties and Liability. If you do not agree to the Disclaimers, do not download and/or accept this article.

  • The data underlying this study are available on request from the corresponding author.

  • Received November 2024.
  • Accepted January 2025.
  • Published online March 2025

This is an open access article distributed under the CC BY 4.0 license.

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Response of Leaf Optical Properties, Temperature, and Physiology to Variable Kaolin Application Rate
View ORCID ProfileCody R. Copp, Mingchang Liao, View ORCID ProfileJohn A. Bouranis
Am J Enol Vitic.  2025  76: 0760005  ; DOI: 10.5344/ajev.2025.24066
Cody R. Copp
1Department of Horticulture, Oregon State University, 4017 Agriculture and Life Sciences Building, Corvallis, OR 97331;
2Extension Service – Umatilla County, Oregon State University, 418 N Main Street, Milton-Freewater, OR 97862;
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Mingchang Liao
1Department of Horticulture, Oregon State University, 4017 Agriculture and Life Sciences Building, Corvallis, OR 97331;
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John A. Bouranis
3Department of Environmental Science, University of Arizona, 1177 E 4th Street, Tucson, AZ 85721.
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Response of Leaf Optical Properties, Temperature, and Physiology to Variable Kaolin Application Rate
View ORCID ProfileCody R. Copp, Mingchang Liao, View ORCID ProfileJohn A. Bouranis
Am J Enol Vitic.  2025  76: 0760005  ; DOI: 10.5344/ajev.2025.24066
Cody R. Copp
1Department of Horticulture, Oregon State University, 4017 Agriculture and Life Sciences Building, Corvallis, OR 97331;
2Extension Service – Umatilla County, Oregon State University, 418 N Main Street, Milton-Freewater, OR 97862;
  • Find this author on Google Scholar
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  • ORCID record for Cody R. Copp
  • For correspondence: cody.copp{at}oregonstate.edu
Mingchang Liao
1Department of Horticulture, Oregon State University, 4017 Agriculture and Life Sciences Building, Corvallis, OR 97331;
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  • Find this author on PubMed
  • Search for this author on this site
John A. Bouranis
3Department of Environmental Science, University of Arizona, 1177 E 4th Street, Tucson, AZ 85721.
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  • ORCID record for John A. Bouranis
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