Original research articles

Cover crops and no-tillage show negligible effects on grapevine physiology in mediterranean vineyard agroecosystems

Abstract

This study aimed to evaluate the effects of annual or perennial cover crops and tillage regimes on whole grapevine physiology and berry composition. We studied the interactive effects of tillage and cover crops on grapevine water status, leaf gas exchange, components of yield, berry composition and resulting water footprint in two contrasting production regions (Fresno County-hot climate and Napa County-warm climate) of California. The treatments included a perennial grass (PG), resident vegetation (RV), and an annual grass (AG) grown under conventional tillage (CT) and no-till (NT) settings. Neither cover crop nor tillage affected grapevine leaf gas exchange. However, at the Napa County vineyard, NT detrimentally affected grapevine water status compared to CT. Grapevine mineral nutrition, when assessed during anthesis revealed no effects of cover cropping in either year or at either location. Cover crop type did not affect yield components or berry composition, however CT increased titratable acidity (TA) at both sites. The water footprint of vineyards at either location was not affected by cover crops or tillage. Our results provided evidence that both in hot and warm climate vineyards cover cropping had negligible beneficial effects on grapevine physiology, mineral nutrition or productivity with no detrimental effects on vineyard water footprint; tillage was beneficial in younger vineyards to improve plant water status in semi-arid regions.

Introduction

In the last decade, there has been a rise in the adoption of sustainable soil management practices that reduce soil erosion and bolster soil organic matter to counter the impacts of climate change on agricultural soils (Lal, 2004a; Powlson et al., 2011a; Lal, 2012a; Lazcano et al., 2020a). Traditionally, vineyard rows were kept bare with the use of herbicides and tillage. However, there is disagreement on the utility of this practice due to the detrimental effects of tillage on air quality and soil physical, chemical, and biological properties (Patiño-Zúñiga et al., 2009a; Ferreira et al., 2020; Gatti et al., 2022a). Thus, the adoption of cover crops and reduced tillage is considered a sustainable alternative to the traditional management of vineyard floors (Alsina et al., 2013b). Furthermore, environmental regulations and public perception serve as an additional incentive to adopt climate-smart practices (Guerra and Steenwerth, 2012).

The benefits of cover crops on the properties of soils are well documented. They can increase soil organic matter (SOM), total nitrogen, microbial biomass, β-glucosidase, and alkaline phosphomonoesterase, improve water infiltration and aggregate stability, reduce soil erosion and greenhouse gas emissions (GHG), and increase vineyard biodiversity (Ingels et al., 2005; Steenwerth and Belina, 2008b; Gattullo et al., 2020; Abad et al., 2021, Zumkeller et al., 2023). Nevertheless, the adoption of cover crops in vineyards is limited by the concern of excessive competition between the cover crop and grapevine for water and nutrients (Smith et al., 2008; Steenwerth and Belina, 2008a; Celette et al., 2009a; Steenwerth et al., 2013; Pérez-Bermúdez et al., 2016). Thus, the presence of a cover crop is generally reported to affect grapevine water status detrimentally (Naor et al., 1997; Monteiro and Lopes, 2007; Hatch et al., 2011a; Pou et al., 2011; Steenwerth et al., 2016; Tomaz et al., 2021). Despite wide acceptance of this particular effect, results depended on the specific conditions of the study, as some studies have shown that cover crops may improve early-season water status (Ingels et al., 2005; Delpuech and Metay, 2018; Reeve et al., 2016); yet others have concluded that cover cropped vineyards do not display better water status compared to those with bare soil (Celette et al., 2005; Costello, 2010; Daane et al., 2018, Torres et al., 2017). Ultimately, previous works agree that changes in grapevine physiological response to cover crop adoption are largely driven by the climatic conditions and irrigation regime at a given site (Delpuech and Metay, 2018; Tomaz et al., 2021).

There is an agreement in the literature that cover crops may reduce vegetative growth, with more pronounced yield losses in warmer regions. However, some studies had found no effect (Monteiro and Lopes, 2007; Lopes et al., 2008a; Smith et al., 2008; Costello, 2010; Jordan et al., 2016; Steenwerth et al., 2016) or yield increases when vineyards were planted with annual species such as oats or legumes (Fourie and Freitag, 2010; Ovalle et al., 2010; Steenwerth et al., 2013, 2016; Messiga et al., 2016; Fourie et al., 2017). These effects were dependent on the experimental conditions (Morlat and Jacquet, 2003; Ingels et al., 2005; Tesic et al., 2007; Lopes et al., 2008a; Smith et al., 2008; Costello, 2010; Pou et al., 2011; Steenwerth et al., 2013; Giese et al., 2015a; Gattullo et al., 2020), the cover crop species (reviewed by Abad et al., 2021) and the cover surface (Reeve et al., 2016). Consequently, any changes to berry composition as a result of cover crop adoption were closely associated with changes in yield, such as smaller berry size and purportedly greater content of berry flavonoids (Lopes et al., 2008b; Lopes et al., 2011; Lee and Steenwerth, 2013; Tomaz et al., 2021).

Cover cropping and reduced tillage management are two practices that directly alter the growing environment of grapevines. Thus, the selection of appropriate vineyard floor management practices is critical to maximise benefits to the soil while minimising the impact on grapevine function and productivity. This selection involves decisions in space (cover crop in vineyard rows vs under-vine), type (grasses vs broadleaves; monoculture or species mixture), and time including perennial vs annual species selection and timing of termination (Bowles et al., 2017b; Gatti et al., 2022b). Factors such as cultivar, vineyard age, macroclimate, soil physiochemical characteristics, and the overall goals for the use of the selected cover crop and tillage system must also be considered. These elements have been shown to contribute to the effect of the practices on grapevine functioning and production (Ingels et al., 2005; Sweet and Schreiner, 2010; Steenwerth et al., 2013; Abad et al., 2021). The adoption of reduced or no-till management preserves SOM, reduces soil erosion, improves soil structure, and is considered integral to reducing GHG emissions from the agriculture sector (Álvaro-Fuentes et al., 2008b; Gaudin et al., 2010; Dobrei et al., 2015; Wolff et al., 2018a). A greater amount of SOM exerts positive effects not only on the structure of the soil but also on the crops, even reducing many negative effects (i.e., mutagenic) of chemical compounds adopted in agriculture (Ferrara et al., 2000; Ferrara et al., 2004; Ferrara et al., 2006). Thus, the influence of tillage on soil properties, while not entirely understood, is more studied than the impact on crops themselves, and few reports have investigated the influence of tillage on grapevine physiology under the presence of a cover crop. Thus, according to previous studies, there is little evidence of tillage having a direct influence on grapevine stomatal conductance and net leaf photosynthesis (Pou et al., 2011), and although no-till practices are often promoted for their positive influence on soil infiltration and conservation of soil water, few studies have found that this effect translated to ameliorated plant water status in grapevine (Pool et al., 1990; Patiño-Zúñiga et al., 2009b; Myburgh, 2013; Steenwerth et al., 2016; Van Huyssteen and Weber, 2017). The grapevine vegetative growth has been reported to be greater under conventional tillage, while yield reductions are typically associated with no-till management, despite research that indicated no effect on production (Myburgh, 2013; Steenwerth et al., 2013; Wolff et al., 2018a). Similarly, previous studies reported a limited impact of tillage on berry composition (Van Huyssteen and Weber, 1980; Lee and Steenwerth, 2013; Reeve et al., 2016; Chrysargyris et al., 2018; Buesa et al., 2021).

Therefore, the objective of this work was to investigate the interactive effects of tillage and cover crops on grapevine water status, leaf gas exchange, components of yield, berry composition and resulting water footprint in two contrasting production regions in California, USA.

Materials and methods

1. Site description and experimental design

Field experiments were conducted at two sites (Figure 1A) for two consecutive growing seasons (2019-2020 and 2020-2021). The first site was located at a Winkler Index V vineyard in Fresno, CA (36.671°N, –119.925°W) in a Ruby Cabernet/Freedom (27 % V. vinifera hybrid) vineyard. Grapevines were planted in 2012 with a spacing of 3.0 × 1.2 m (row × vine) with a row orientation of E-W. The grapevines were cane-pruned and trained to quadrilateral cordons at 1.38 m with catch wires at 1.54 m and at 1.68 m above the vineyard floor. The soil texture of the site was classified as Hanford fine sandy loam. Hanford fine sandy loam is a coarse-loamy, mixed, super active, non-acid, thermic Typic Xerothents. (websoilsurvey.sc.egov.usda.gov). The A1 horizon is 0 to 30 cm deep with a moist, weak fine granular structure; slightly hard, very friable, nonsticky and nonplastic; many fine roots in the upper few inches; many fine interstitial pores; slightly acid; with gradual smooth boundary between 15 and 35 cm thick. The C1 horizon is 30 cm to 96 cm moist; massive; slightly hard, very friable, nonsticky and nonplastic; common fine interstitial pores; neutral; diffuse boundary 25 to 60 cm thick. The vines were drip-irrigated with two emitters per plant, delivering 4.0 L/h each at 100 % crop evapotranspiration replacement. Irrigation was scheduled daily to meet the vineyard demand according to methods reported by Torres et al. (2021) and 2900 m3/ha and 3073 m3/ha of irrigation water were applied in 2020 and 2021, respectively. The second site was located at a Winkler Index III vineyard in Oakville, CA (38.428 °N, –122.409 °W) in a Merlot (clone 181)/3309 C (V. riparia × V. rupestris) vineyard. Grapevines were planted in 2018 at a spacing of 3.0 by 2.0 m (row × vine) with a row orientation of E-W. The grapevines were spur-pruned and trained to quadrilateral cordons 1.38 m above the vineyard floor with catch wires at 1.68 m. The soil of the site was classified as Baley clay loam. The Bale soil series consists of very deep, somewhat poorly drained soils formed in stratified, gravelly and sandy alluvium from mixed sources. In these soil series, the Ap horizon is distributed from 0 to 0.15 m deep, the B horizon is distributed from 0.15 to 0.61 m, the Ab horizon is distributed from 0.61 to 1.12 m, and the C horizon is distributed from 1.12 to 1.47 m. (websoilsurvey.sc.egov.usda.gov). The vines were drip-irrigated with two emitters per plant, delivering 2 L/h each at 80 % crop evapotranspiration replacement. Irrigation at this location was scheduled weekly (Torres et al., 2021). In 2020 and 2021, 978.5 m3/ha and 824 m3/ha of irrigation were applied, respectively, at this location.

At both experimental sites, the experiments were arranged as a split-plot 3 × 2 factorial arrangement of treatments (three cover crops and two tillage managements) with four (Oakville) and three replications (Fresno). Each treatment replicate consisted of 15 grapevines. Three grapevines in the middle of each replicate were used for measurements, and the distal plants on either end served as buffer plants. Treatments included tillage as the main plot [conventional tillage (CT) and no-till (NT)], and the sub-plot was randomly applied within the main plots as i) Perennial grass (Poa bulbosa hybrid cv. Oakville Blue) (Figure 1B); ii) Annual grass (Barley, Hordeum vulgare) (Figure 1C); iii) Resident vegetation (natural weed population) (Figure 1D). Resident vegetation was mainly composed of grasses from the Poaceae family, Plantago sp., Trifolium sp., Convolvulus sp., and Barbarea vulgaris. The cover crop seed was drilled in a 1.5 m wide strip with a 1.5 m wide Frontier GS1160 (John Deere &Co. Deerfield, IL USA) seed drill according to the seed manufacturer's recommended rate prior to receiving fall/winter rains in 2019 (19 November 2019 in Napa County, 26 November 2019 in Fresno County) and 2020 (16 October 2020 in Napa County and 23 October 2020 in Fresno County) at a rate of 605 kg/ha and 84 kg/ha for the perennial grass (PG) and annual grass (AG) treatments, respectively. Resident vegetation (RV) was allowed to grow within the 1.5 m strip and mowed once with a 1.5 m wide Rears IFA60 (Rears Mfg. Co. Coburg, OR USA) flail mower (6 April 2020 and 11 April 2021 in Napa County; 12 March 2020 and at the vineyard manager's discretion. Conventional tillage was performed with a Schmeiser TSN60 tandem disk (Schmeiser Co. Selma, CA USA) within the 1.5 m planted strip according to the vineyard manager´s discretions once per year (22 April 2020 and 2 May 2021 in Napa County; 18 April 2020 and 21 April 2021) and removed cover crop was left on the field. All other cultural practices, including weed control on the berm once during March of each year with glyphosate (Zumkeller et al., 2023), were conducted according to University of California Cooperative Extension guidelines (Christensen, 2000).

Figure 1. Location of experimental sites in the state of California, U.S.A. (A), Perennial grass (Poa bulbosa hybrid) (B), Annual grass (Hordeum vulgare) (C), Native vegetation (D) in the vineyard.

2. Weather conditions

Weather data at both sites was obtained from California Irrigation Management Information System (CIMIS) stations nearest the experimental vineyard (station #77 in Napa County, CA and station #2 in Fresno County, CA). Growing degree day values were calculated using a base of 10 °C from 1 April through 30 September of each year.

3. Grapevine water status and leaf gas exchange (Ψ, Anet, gs)

Plant water status was measured as stem water potential (ΨS) every 2 weeks (Oakville) and 4 times (Fresno) during each growing season within 1.5 h of solar noon, and integrals were calculated as previously reported (Yu et al., 2021). Two fully expanded leaves exposed to the sun and without signs of disease and/or damage were selected per treatment-replicate. For ΨS, leaves were then covered 1.5 hours before measurements with a reflective foil-lined zip-top plastic bag to suppress transpiration. The ΨS was measured with a pressure chamber (Model 610 Pressure Chamber Instrument, PMS Instrument Co., Corvallis, OR USA).

Leaf gas exchanges of stomatal conductance (gs) and net carbon assimilation (Anet) were measured at solar noon on three fully expanded and sun-exposed leaves with a CIRAS-3 infra-red gas analyser (PP Systems, Amesbury, MA, USA) equipped with a leaf chamber with a 4.5 cm2 window. The reference CO2 was set to 400 µmol/mol CO2 at a flow rate of 100 mL/min. The window of the chamber was oriented perpendicularly toward the sun to allow for saturating light conditions, and the cuvette was left attached to the leaf for 40-60 s until a steady state was reached. Three grapevines were measured from each treatment replicate.

4. Grapevine mineral nutrient status

Grapevine petiole samples were collected for nutrient analysis at bloom at both sites. Bloom (Oakville: 29 May 2020, 25 May 2021; Fresno: 10 May 2020, 15 May 2021) was defined as when > 50 % of flowers opened. Leaves with petioles were collected from the north side of the three middle data vines in each replicate, and the blade was removed. Petioles were delivered to a commercial laboratory for mineral analysis which was carried out by using coupled plasma-mass spectrometry. Nitrogen (N) was determined via automated combustion analysis (method B-2.20), while phosphorus (P), potassium (K), sodium (Na), calcium (Ca), magnesium (Mg), zinc (Zn), manganese (Mn), boron (B), iron (Fe), and copper (Cu) were analysed via Nitric/Perchloric Acid Digestion (method B-4.20) as described by Gavlak et al. (1994).

5. Leaf area and components of yield

At the Fresno site, leaf area index (LAI) was measured in late spring to characterise grapevine canopy growth and converted into leaf area by a smartphone program, VitiCanopy, via iOS system (Apple Inc., Cupertino, CA, USA) (De Bei et al., 2016). The gap fraction ranged from 0 % to 100 % and was set to 75 %, meaning that if 75 % of pixels from each of the sub-images (25 in total) correspond to the sky while the light extinction coefficient (k), was set at 0.7 by default since this value has been described to be the most accurate for grapevine canopies following developer´s recommendations (De Bei et al., 2016). A telescoping mounting device was used to position the device 75 cm underneath the canopy effectively. The device was positioned with the maximum length of the screen being perpendicular to the cordon and the cordon in line with the middle of the screen, according to previous work (De Bei et al., 2016; Yu and Kurtural, 2020). In each experimental unit, three images were taken to capture half canopy of each vine and analysed by the software. The relationship between leaf dry mass and area was determined on a subsample of leaves using a leaf area meter (Li-Cor 3300, Lincoln, NE, USA). This subsample was also used to calculate the leaf area per vine after defoliating a vine and measure by using the leaf area meter.

Harvest commenced when the fruit reached approximately 25 °Brix in Oakville (August 25, 2020, and September 1, 2021) and 21o Brix in Fresno (October 6, 2020, and September 7, 2021). At harvest at both sites, clusters from three data vines per treatment replicate were manually removed, counted, and weighed on a top-loading balance. The leaf area to fruit ratio was calculated by dividing leaf area by crop weight.

6. Berry composition

At harvest, fifty berries were randomly collected from the three middle grapevines within each replicate and immediately processed. Berries were weighed and gently pressed by hand to squeeze the juice. Total soluble solids (TSS) were determined using a temperature-compensating digital refractometer (Atago PR-32, Bellevue, WA, USA). Must pH and titratable acidity (TA) were determined with an autotitrator (Metrohm 862 Compact Titrosampler, Herisau, Switzerland). TA was determined by titrating with 0.1 N sodium hydroxide to an end point of 8.3 pH and reported as g/L of tartaric acid.

Berry skin anthocyanin content was determined at harvest from 20 berries randomly collected from each treatment replicate. Berries were gently peeled, and skins were freeze-dried (Cold Trap 7385020, Labconco, Kansas City, MO, USA). Freeze-dried tissue was ground with a tissue lyser (MM400, Retsch, Germany). Fifty milligrams of the resultant powder were extracted in methanol: water: 7 M hydrochloric acid (70:29:1, V:V:V) to determine anthocyanin content. Extracts were filtered using a 0.45 µm filter (Thermo Fisher Scientific, San Jose, CA, USA) and analysed using an Agilent 1260 series reversed-phase high-performance liquid chromatography (HPLC) system (Agilent 1260, Santa Clara, CA, USA) coupled to a diode array detector. Separation was performed on a reversed-phase C18 column LiChrospher 100, 250 mm × 4 mm with a 5 µm particle size and a 4 mm guard column of the same material at 25 ℃ with elution at 0.5 mL per minute. The mobile phase consisted of a constant 5 % of acetic acid and the following gradient (v/v) of acetonitrile in water: 0 min 8 %, at 25 min 12.2 %, at 35 min 16.9 %, at 70 min 35.7 %, 65 % between 70-75 min, and 8 % between 80-90 min. The identification of compounds was conducted by determining the peak area of the absorbance at 520 nm for anthocyanins and made by comparison of the commercial standard retention times found in the literature as previously reported (Martinez-Luscher et al., 2019). A commercial standard of oenin (Extrasynthese, Genay France) was used for the quantification of anthocyanins.

7. Water footprint assessment

Water footprint (WF) was calculated following the methods described in Zotou and Tshrintzis (2017) with minor modifications explained in Torres et al. (2021) and below. Total WF was derived as the sum of the green, blue and grey WFs and expressed in m3 of water consumed per ton of fruit harvested. Cover crop WF was derived in the same manner and expressed in m3 of water consumed per kg of cover crop biomass. Green, blue, and grey components were given by the following equations:

(Equation 1) greenWF = PmY

where Pm is the monthly effective precipitation was calculated from the data obtained from the CIMIS stations (station #77 in Napa County, CA and station #2 in Fresno County, CA, USA) and expressed in m3∙ha-1 after applying a conversion factor of 10 and Y is the yield of grapevines expressed in tonne∙ha-1.

(Equation 2) blueWF = WUmY

where WUm is the total amount of irrigation water received by the grapevines monthly expressed in m3- ∙ ha-1 and Y is the yield of grapevines expressed in tonne∙ha-1

(Equation 3) greyWF = αARcmax-cnat Y

where α is the percentage of fertiliser that leaches to the receiving aquatic system; AR is the amount of fertiliser applied to the grapevines expressed in kg ∙ ha-1; cmax is the maximum acceptable concentration of fertiliser in the aquatic system (mg ∙ L -1); and cnat is the natural concentration of the pollutant in the aquatic system (mg ∙ L-1). For grey component calculation, only nitrogen fertilisation was considered, given that N use in agriculture presents the largest environmental concern (UC Davis, 2016). The percentage of nitrogen entering the water system of the area was assumed to be 10 %, according to Mekonnen and Hoekstra (2011). The maximum acceptable concentration of nitrogen (45 mg ∙ L-1) was obtained from CDFA (2020). According to Hoekstra et al. (2011), the natural concentration of pollutants was taken equal to zero, as proposed when data were missing.

8. Statistical analyses

Statistical analyses were conducted with R studio Version 3.6.1 (RStudio: Integrated Development for R., Boston, MA, USA) for Mac OS. After normality assessment, data were submitted to a three-way analysis of variance (ANOVA) to assess the statistical differences between the different cover crop and tillage treatments and the respective interaction effects over two years. Means ± standard errors (SE) were calculated, and when the F value was significant (P ≤ 0.05), a Tukey's ‘Honest Significant Difference’ (HSD) post hoc test was executed by using “agricolae” 1.2-8 R package. Plots were made using GraphPad Prism v8.1.2 for Windows (Graph Pad Inc., San Diego, CA, USA).

Results

1. Weather conditions at the experimental sites

Temperature minima, maxima, and their average were calculated daily (air and soil) and annually (air) from the CIMIS station data for the 2019-20 and 2020-21 seasons (Table 1). In comparison to the ten-year average (2011–2021), both sites experienced warmer and drier conditions over the course of the experiment. During both years in Fresno, total precipitation was lower than the ten-year average for the same period. Specifically, the 2019-20 season received 10.6 mm less precipitation, while the 2020-21 season received 57.1 mm less. Average daily air temperature during the growing season was also 0.1 °C higher in 2020 and 0.4 °C higher in 2021 compared to the ten-year average. Average daily soil temperatures were 0.3 °C and 0.5 °C higher in 2020 and 2021, respectively. Despite one-degree increases in average monthly temperature between the two years, mean daily air and soil temperatures were similar. The greatest number of growing degree days in Fresno were accumulated in 2021 (2488 GDD10), compared to 2020 (2358 GDD10).

In Oakville, drought conditions were more pronounced, as the 2019-20 season received 343.6 mm less precipitation than the ten-year average and 299.5 mm less during the 2020-21 year (Table 1). However, there was a 43.8 mm increase in precipitation received in the second year of the experiment compared to the first year. The average daily temperature during the growing season was 0.4 °C higher in 2020 and 0.3 °C lower in 2021 compared to ten-year average values. Average daily soil temperatures were 0.5 °C and 0.4 °C higher in 2020 and 2021, respectively. As was observed at the Fresno vineyard, average daily air and soil temperatures were similar between the two years of the study. Contrarily, the greatest number of growing degree days in Oakville (1647 GDD10) were accumulated in the 2020 growing season compared to 2021 (1519 GDD10).

Table 1. Site conditions at two commercial vineyards in Fresno and Napa Co. from experimental years (2019–2021) compared to long-term mean values (2011–2021) a, b, c.


Fresno County

Year

Air Temperature (°C)

Soil Temperature (°C)

Precipitation (mm)

Growing Degree Days

Daily Max

Daily Min

Daily Average

Daily Max

Daily Min

Daily Average

Total

Total

2020

Mean

25.6

9.1

17.3

25.7

10.7

22.6

199.0

2358

Annual max

35.8

18.0

27.3

--

--

--

--

--

Annual min

15.6

0.6

7.6

--

--

--

--

--

2021

Mean

25.8

9.2

17.6

26.6

10.4

22.8

152.5

2488

Annual max

37.8

18.7

28.5

--

--

--

--

--

Annual min

12.5

3.1

7.7

--

--

--

--

--

20112021

Mean

25.4

9.4

17.2

25.6

10.1

22.3

209.6

2259

Napa County

2020

Mean

24.4

7.0

14.9

22.5

10

16.5

234.2

1647

Annual max

31.8

12.3

21.1

--

--

--

--

--

Annual min

17.1

2.0

8.5

--

--

--

--

--

2021

Mean

23.1

6.3

14.2

22.8

10.2

16.4

278.3

1519

Annual max

30.0

10.8

19.2

--

--

--

--

--

Annual min

12.5

2.6

7.6

--

--

--

--

--

20112021

Mean

23.2

7.1

14.5

22.8

7.9

16.0

577.8

1504

a Annual maximum (max) and annual minimum (min) indicate the greatest or lowest value observed during the respective year.

b Total precipitation occurred during the annual winter rainy season, calculated from October of the preceding year through September of the following year (e.g., 2020 values were calculated from October 1, 2019-September 30, 2020).

c Abbreviations: --: not applicable.

2. Leaf gas exchanges and plant water status over the season

In Fresno, no treatment effects were observed on season-long integrals of gs (Table 2). Likewise, season-long integrals of Anet were also not affected by the treatments applied. However, in 2020 both gs and Anet were significantly lower than in 2021 in Fresno.

Table 2. Stomatal conductance and net carbon assimilation values of Ruby Cabernet grapevines subjected to different cover crops and tillage systems, as collected at various points in the 2019-20 and 2020-21 growing seasons a, b.


Treatment

Stomatal conductance (mmol m−2 s−1)

Net carbon assimilation (μmol CO2 m–2 s–1)

2020

78 DAF

184 DAF

--

78 DAF

184 DAF

--

No Till - AG

259.5 ± 23.4

266.7 ± 54.5

--

10.2 ± 1.6

13.4 ± 0.7

--

No Till - RV

308.7 ± 34.7

230.8 ± 21.6

--

12.2 ± 1.9

13.5 ± 3.7

--

No Till - PG

380.1 ± 60.1

252.5 ± 7.4

--

15.7 ± 0.5

14.5 ± 1.9

--

Till - AG

281.2 ± 30.1

260.2 ± 24.4

--

16.2 ± 1.7

12.9 ± 1.9

--

Till - RV

262.7 ± 24.4

301.8 ± 59.9

--

14.5 ± 0.9

11.3 ± 3.9

--

Till - PG

403.0 ± 64.2

189.8 ± 3.5

--

14.8 ± 0.2

9.97 ± 2.9

--

Cover crop (CC)

ns

ns

--

ns

ns

--

Tillage (T)

ns

ns

--

ns

ns

--

CC x T

ns

ns

--

ns

ns

--

2021

26 DAF

91 DAF

128 DAF

26 DAF

91 DAF

128 DAF

No Till - AG

178.4 ± 41.92

415.0 ± 68.0

349.8 ± 56.5

12.2 ± 3.6

15.8 ± 2.9

18.5 ± 2.7

No Till - RV

139.9 ± 22.21

352.1 ± 55.8

349.6 ± 30.2

6.33 ± 1.9

16.1 ± 0.9

20.8 ± 2.7

No Till - PG

149.5 ± 18.10

293.5 ± 68.2

382.0 ± 60.8

8.67 ± 1.5

18.1 ± 3.1

19.8 ± 1.8

Till - AG

133.2 ± 16.63

418.4 ± 51.2

318.0 ± 59.9

9.27 ± 1.2

18.5 ± 1.4

20.4 ± 3.0

Till - RV

137.7 ± 30.52

360.5 ± 70.7

413.9 ± 42.5

5.57 ± 1.6

17.2 ± 1.9

19.1 ± 2.1

Till - PG

137.9 ± 7.87

421.2 ± 89.4

407.0 ± 73.9

9.07 ± 1.7

19.7 ± 2.7

19.8 ± 1.9

Cover crop (CC)

ns

ns

ns

ns

ns

ns

Tillage (T)

ns

ns

ns

ns

ns

ns

CC x T

ns

ns

ns

ns

ns

ns

Year

ns

**

Year x CC

ns

ns

Year x T

ns

ns

Year x CC x T

ns

ns

a ANOVA to compare data (p-value indicated); Letters within columns indicate significant mean separation according to Tukey's HSD test at p-value < 0.05, where "*": p-value < 0.05; "**": p-value < 0.001, "***": p-value < 0.0001.

b Abbreviations: AG: Annual grass; RV: resident vegetation; PG: perennial grass; DAF: days after flowering; na: not applicable; ns: not significant; --: not applicable.

In Oakville, gs was significantly lower among grapevines grown with AG compared to RV and PG in 2020, 96 DAF and 110 DAF (Table 3). However, a similar effect was not evident throughout the rest of the experiment. Additionally, no differences were measured in Anet , although 2020 values were lower than in 2021. A similar response was observed at the Fresno vineyard.

Table 3. Stomatal conductance and net carbon assimilation values of Merlot grapevines subjected to different cover crops and tillage systems, as collected at various points in the 2019-20 and 2020-21 growing seasons a, b.


Treatment

Stomatal Conductance (mmol m−2 s−1)

Net Carbon Assimilation (μmol CO2 m–2 s–1)

2020

61 DAF

96 DAF

110 DAF

145 DAF

61 DAF

96 DAF

110 DAF

145 DAF

No Till - AG

136.6 ± 18.9

141.5 ± 6.3 b

147.7 ± 18.2 b

220.4 ± 22.2

10.0 ± 1.35

13.1 ± 0.96

19.2 ± 7.99

16.5 ± 1.6

No Till - RV

161.3 ± 27.6

195.5 ± 26.5 a

213.7 ± 14.0 a

217.0 ± 29.1

7.7 ± 0.72

17.3 ± 0.94

14.4 ± 1.04

16.6 ± 1.7

No Till - PG

174.0 ± 28.5

182.5 ± 17.1 a

217.0 ± 29.1 a

205.4 ± 17.3

11.7 ± 2.01

14.3 ± 1.85

17.1 ± 1.67

17.0 ± 0.9

Till - AG

109.2 ± 13.0

124.3 ± 19.3 c

167.8 ± 11.7 b

159.0 ± 18.9

7.7 ± 0.24

11.4 ± 1.31

13.2 ±  0.95

14.8 ± 1.0

Till - RV

143.0 ± 25.1

194.2 ± 32.5 a

229.2 ± 10.8 a

184.4 ± 10.8

6.3 ± 2.58

16.0 ± 2.32

16.0 ± 1.75

17.2 ± 0.3

Till - PG

172.2 ± 26.3

167.2 ± 30.0 b

201.4 ± 24.5 a

237.0 ± 20.8

10.4 ± 2.44

12.9 ± 2.07

14.0 ± 2.14

19.0 ± 0.9

Cover crop (CC)

ns

*

*

ns

ns

ns

ns

ns

Tillage (T)

ns

ns

ns

ns

ns

ns

ns

ns

CC x T

ns

ns

ns

ns

ns

ns

ns

ns

2021

56 DAF

74 DAF

98 DAF

109 DAF

56 DAF

74 DAF

98 DAF

109 DAF

No Till - AG

198.3 ± 26.4

191.7 ± 18.1

179.0 ± 17.9

150.3 ± 15.9

9.0 ± 2.06

13.1 ± 2.01

13.6 ± 1.51

12.4 ± 1.2

No Till - RV

180.9 ± 23.2

156.6 ± 25.1

155.0 ± 24.4

173.6 ± 18.7

9.4 ± 1.42

11.9 ± 1.41

11.5 ± 1.15

13.2 ± 1.3

No Till - PG

209.0 ± 28.9

146.5 ± 13.3

165.7 ± 16.9

177.1 ± 25.6

11.5 ± 2.08

13.2 ± 0.47

13.2 ± 1.63

12.2 ± 1.8

Till - AG

193.5 ± 19.2

160.5 ± 32.8

194.2 ± 21.5

163.2 ± 27.1

9.5 ± 1.31

14.8 ± 1.70

11.9 ± 1.51

12.1 ± 2.0

Till - RV

231.0 ± 24.6

168.7 ± 32.1

177.4 ± 26.7

193.3 ± 23.3

10.8 ± 1.87

13.4 ± 1.29

10.9 ± 1.85

13.3 ± 1.6

Till - PG

199.3 ± 26.2

171.4 ± 38.6

145.8 ± 18.3

181.2 ± 20.3

10.5 ± 1.73

12.5 ± 2.72

10.3 ± 1.59

13.9 ± 1.1

Cover crop (CC)

ns

ns

ns

ns

ns

ns

ns

ns

Tillage (T)

ns

ns

ns

ns

ns

ns

ns

ns

CC x T

ns

ns

ns

ns

ns

ns

ns

ns

Year

ns

***

Year x CC

ns

ns

Year x T

ns

ns

Year x CC x T

ns

ns

a ANOVA to compare data (p-value indicated); Letters within columns indicate significant mean separation according to Tukey's HSD test at p-value < 0.05, where "*": p-value < 0.05; "**": p-value < 0.001, "***": p-value < 0.0001.

b Abbreviations: AG: Annual grass; RV: resident vegetation; PG: perennial grass; DAF: days after flowering; na: not applicable; ns: not significant.

In Fresno, Ψs values ranged from –1.68 to –0.70 MPa in 2020 and –1.75 to –0.73 MPa in 2021. The cover crop and tillage treatments did not affect Ψs.integrals, and there was not an interaction of cover crop and tillage or an effect of the year (data not shown). Conversely, at Oakville, Ψs integrals ranged from –1.49 to –0.64 MPa in 2020 and –1.46 to –0.77 MPa in 2021. As presented in Figure 2, in 2020, ΨS integrals were affected by cover crops. Grapevines grown with AG displayed the most negative Ψs integrals, with PG the least negative. However, this effect was not observed in the second year of the study, nor was there an interaction effect between the cover crop and tillage system. Tillage was more effective in eliciting a ΨS integrals response more so than cover crop type. Grapevine water status was significantly lower in NT vines (–1.07 MPa) than in CT vines (–1.01 MPa) over both years at the Oakville vineyard.

Figure 2. Mid-day stem water potential integrals of Merlot grapevines subjected to different cover crop and tillage systems at the Oakville vineyard (Napa County) over the course of the 2019-20 and 2020-21 growing season a

a ANOVA to compare data (p-value of the respective factor indicated). The interaction between the till and cover crop factor was not significant and upper(tillage) and lower case (cover crop). Letters above treatment bars indicate significant mean separation according to Tukey’s honest significance difference (HSD) test for tillage and cover crop factors, respectively, at p-value < 0.05, where "*": p-value < 0.05; "**": p-value < 0.001, "***": p-value < 0.0001.

3. Grapevine mineral nutrient status

Grapevine mineral nutrition was assessed at bloom, and there were year-to-year differences at both locations. At the Fresno vineyard, nitrogen (%), phosphorus (%), and zinc (mg/kg) concentrations in petioles were greater in 2020 than in 2021 (Table 4). There was also an interaction of year and tillage where calcium concentration was greater than tillage during 2020. In Fresno, manganese, magnesium, iron, and copper values were greater in 2021 than in 2020.

Table 4. Mineral nutrition measured on petioles at bloom of Ruby Cabernet grapevines subjected to different cover crops and tillage systems collected in the 2019-20 and 2020-21 seasons a, b.


Fresno County

Treatment

N (%)

P (%)

K (%)

Zn (mg/kg)

Mn (mg/kg)

B (mg/kg)

Ca (%)

Mg (%)

Fe (mg/kg)

Cu (mg/kg)

2020

No Till - AG

0.76 ± 0.06

0.13 ± 0.01

3.17 ± 0.24

30.3 ± 0.3

46.0 ± 14.6

31.3 ± 1.5

1.35 ± 0.07

0.88 ± 0.03

48.3 ± 6.6

3.00 ± 0.58

No Till - RV

0.69 ± 0.06

0.15 ± 0.02

3.51 ± 0.17

30.7 ± 3.2

48.0 ± 14.8

31.3 ± 0.1

1.31 ± 0.12

0.82 ± 0.08

46.7 ± 2.2

2.00 ± 0.03

No Till - PG

1.01 ± 0.35

0.17 ± 0.06

2.89 ± 0.47

33.0 ± 6.7

68.7 ± 19.4

32.0 ± 2.1

1.47 ± 0.04

0.86 ± 0.09

101.3 ± 54.9

2.33 ± 0.67

Till - AG

0.95 ± 0.24

0.17 ± 0.03

3.56 ± 0.43

34.3 ± 6.2

65.0 ± 19.4

34.0 ± 0.6

1.44 ± 0.07

0.84 ± 0.08

94.0 ± 52.0

2.33 ± 0.33

Till - RV

0.72 ± 0.02

0.19 ± 0.05

3.59 ± 0.10

27.7 ± 4.4

43.3 ± 14.1

30.7 ± 0.9

1.28 ± 0.05

0.79 ± 0.05

48.0 ± 5.3

2.33 ± 0.33

Till - PG

0.86 ± 0.23

0.18 ± 0.04

3.41 ± 0.19

32.0 ± 4.4

65.8 ± 18.2

32.3 ± 0.7

1.37 ± 0.19

0.86 ± 0.21

98.0 ± 50.5

2.67 ± 0.33

Cover crop (CC)

ns

ns

ns

ns

Ns

ns

ns

ns

ns

ns

Tillage (T)

ns

ns

ns

ns

Ns

ns

ns

ns

ns

ns

CC x T

ns

ns

ns

ns

Ns

ns

ns

ns

ns

ns

2021

No Till - AG

0.65 ± 0.03

0.12 ± 0.01

3.16 ± 0.07

26.7 ± 4.3

68.7 ± 5.1

31.3 ± 0.4

1.79 ± 0.05

1.09 ± 0.05

155.1 ± 15.9

3.3 ± 0.44

No Till - RV

0.63 ± 0.03

0.11 ± 0.01

3.46 ± 0.17

26.7 ± 1.6

81.0 ± 15.2

31.7 ± 1.9

1.85 ± 0.05

1.14 ± 0.03

133.0 ± 24.6

3.33 ± 0.44

No Till - PG

0.72 ± 0.10

0.13 ± 0.04

3.06 ± 0.27

29.3 ± 5.2

64.3 ± 4.9

34.3 ± 3.1

1.58 ± 0.03

0.91 ± 0.10

143.0 ± 41.7

4.00 ± 0.76

Till - AG

0.66 ± 0.01

0.11 ± 0.01

3.49 ± 0.11

32.0 ± 5.9

84.7 ± 23.5

29.0 ± 1.3

1.72 ± 0.11

1.04 ± 0.07

192.1 ± 38.6

4.00 ± 0.76

Till - RV

0.64 ± 0.02

0.11 ± 0.02

3.37 ± 0.09

27.3 ± 1.8

83.3 ± 6.5

34.3 ± 5.1

1.70 ± 0.12

1.06 ± 0.07

138.0 ± 15.6

4.00 ± 1.32

Till - PG

0.64 ± 0.03

0.10 ± 0.01

3.81 ± 0.56

26.3 ± 1.9

84.3 ± 19.0

31.3 ± 1.6

1.88 ± 0.17

1.16 ± 0.75

134.0 ± 6.5

3.00 ± 0.44

Cover crop (CC)

ns

ns

ns

ns

Ns

ns

ns

ns

ns

ns

Tillage (T)

ns

ns

ns

ns

Ns

ns

ns

ns

ns

ns

CC x T

ns

ns

ns

ns

Ns

ns

ns

ns

ns

ns

Year

***

***

ns

***

***

ns

ns

***

***

***

Year x CC

ns

ns

ns

ns

Ns

ns

ns

ns

ns

ns

Year x T

ns

ns

ns

ns

Ns

ns

*

ns

ns

ns

Year x CC x T

ns

ns

ns

ns

Ns

ns

ns

ns

ns

ns

a ANOVA to compare data (p-value indicated); Letters within columns indicate significant mean separation according to Tukey's HSD test at p-value < 0.05, where "*": p-value < 0.05; "**": p-value < 0.001, "***": p-value < 0.0001.

b Abbreviations: N: Nitrogen; P: Phosphorus; K: Potassium; Zn: Zinc; Mn: Manganese; B: Boron; Ca: Calcium; Mg: Magnesium; Fe: Iron; Cu: Copper; na: not applicable; ns: not significant.

In Oakville, N, Mg, and Fe petiole concentrations were greater in 2021 than in 2020 (Table 5). Conversely, petiole concentrations of P, Zn, Mg, and Cu values were greater in 2020 compared to 2021. At Oakville, we measured lower petiole N concentrations with NT (1.18 %) when compared to CT (1.25 %). Again, an interaction of year and tillage within Ca was measured in 2020 in Oakville as well.

Table 5. Mineral nutrition measured on petioles at bloom of Merlot grapevines subjected to different cover crops and tillage systems collected in the 2019-20 and 2020-21 seasons a, b.


Napa County

Treatment

N (%)

P (%)

K (%)

Zn (mg/kg)

Mn (mg/kg)

B (mg/kg)

Ca (%)

Mg (%)

Fe (mg/kg)

Cu (mg/kg)

2020

No Till - AG

1.07 ± 0.09

0.43 ± 0.03

3.19 ± 0.18

98.8 ± 4.33

39.0 ± 4.64

43.5 ± 2.60

1.73 ± 0.14

0.63 ± 0.06

32.3 ± 3.60

10.00 ± 1.56

No Till - RV

0.88 ± 0.06

0.53 ± 0.06

3.12 ± 0.10

100.8 ± 3.57

37.3 ± 4.01

44.5 ± 1.37

1.99 ± 0.23

0.65 ± 0.05

32.0 ± 3.16

12.50 ± 1.20

No Till - PG

0.92 ± 0.09

0.51 ± 0.03

3.02 ± 0.36

101.0 ± 3.68

37.3 ± 3.07

48.0 ± 3.09

1.87 ± 0.20

0.79 ± 0.02

36.3 ± 2.18

13.00 ± 0.81

Till - AG

0.88 ± 0.04

0.51 ± 0.02

3.12 ± 20

99.5 ± 1.11

35.8 ± 0.55

46.3 ± 0.29

1.90 ± 0.08

0.68 ± 0.07

40.0 ± 1.16

12.50 ± 0.58

Till - RV

0.96 ± 0.09

0.46 ± 0.06

3.22 ± 0.17

96.3 ± 5.94

40.8 ± 4.63

45.0 ± 3.86

1.65 ± 0.14

0.60 ± 0.09

33.0 ± 5.27

10.25 ± 1.66

Till - PG

1.11 ± 0.12

0.46 ± 0.02

3.17 ± 0.19

91.8 ± 7.78

35.8 ± 4.86

47.0 ± 374

1.66 ± 0.10

0.63 ± 0.09

34.3 ± 3.31

11.00 ± 0.67

Cover crop (CC)

ns

Ns

ns

Ns

ns

Ns

ns

ns

ns

Ns

Tillage (T)

ns

Ns

ns

ns

ns

Ns

ns

ns

ns

Ns

CC x T

ns

Ns

ns

ns

ns

Ns

ns

ns

ns

Ns

2021

No Till - AG

1.39 ± 0.07

0.38 ± 0.02

3.04 ± 0.28

43.0 ± 2.45

63.0 ± 7.96

45.8 ± 1.91

1.74 ± 0.15

0.51 ± 0.05

46.3 ± 1.91

8.75 ± 0.29

No Till - RV

1.45 ± 0.07

0.39 ± 0.02

3.16 ± 0.29

40.3 ± 3.10

66.0 ± 5.06

45.8 ± 1.09

1.86 ± 0.14

0.51 ± 0.02

46.0 ± 0.82

8.75 ± 0.55

No Till - PG

1.39 ± 0.06

0.41 ± 0.02

3.09 ± 0.23

45.8 ± 1.52

65.0 ± 13.76

47.5 ± 1.67

1.80 ± 0.05

0.56 ± 0.01

51.3 ± 5.42

9.00 ± 0.82

Till - AG

1.54 ± 0.03

0.38 ± 0.02

3.17 ± 0.10

39.5 ± 2.33

70.0 ± 12.82

45.8 ± 1.28

1.95 ± 0.11

0.56 ± 0.04

44.8 ± 3.60

8.75 ± 0.33

Till - RV

1.50 ± 0.11

0.42 ± 0.04

2.99 ± 0.07

40.3 ± 4.01

77.5 ± 16.93

46.8 ± 1.44

1.92 ± 0.15

0.54 ± 0.01

42.8 ± 4.25

8.75 ± 0.55

Till - PG

1.51 ± 0.04

0.42 ± 0.03

3.44 ± 0.18

43.0 ± 1.33

79.0 ± 13.56

48.8 ± 1.36

1.98 ± 0.05

0.52 ± 0.02

52.5 ± 3.67

9.25 ± 0.55

Cover crop (CC)

Ns

ns

ns

ns

ns

Ns

ns

ns

ns

Ns

Tillage (T)

*

ns

ns

ns

ns

Ns

ns

ns

ns

Ns

CC x T

ns

ns

ns

ns

ns

Ns

ns

ns

ns

ns

Year

**

**

ns

***

***

Ns

ns

***

***

***

Year x CC

ns

ns

ns

ns

ns

Ns

ns

ns

ns

ns

Year x T

ns

ns

ns

ns

ns

Ns

*

ns

ns

ns

Year x CC x T

ns

ns

ns

ns

ns

Ns

ns

ns

ns

*

a ANOVA to compare data (p-value indicated); Letters within columns indicate significant mean separation according to Tukey's HSD test at p-value < 0.05, where "*": p-value < 0.05; "**": p-value < 0.001, "***": p-value < 0.0001.

b Abbreviations: N: Nitrogen; P: Phosphorus; K: Potassium; Zn: Zinc; Mn: Manganese; B: Boron; Ca: Calcium; Mg: Magnesium; Fe: Iron; Cu: Copper; na: not applicable; ns: not significant.

3. Yield and yield components

In Fresno, there were no differences in cluster number per vine, average cluster mass, yield per vine, or leaf area to fruit ratio (Table 6). On average, the number of clusters per vine was higher in 2021 than in 2020, although the average cluster mass was lower in 2021 compared to 2020. Year-to-year differences were also observed at the Oakville site, whereby cluster number per vine, average cluster mass and yield per vine were greater in 2021 compared to 2020, while the leaf area to fruit ratio was greater in 2020. There was no treatment effect of cover crop or tillage, nor an interaction measured at either site.

Table 6. Yield components of Ruby Cabernet (Fresno County) and Merlot grapevines (Napa County) subjected to different cover crops and tillage systems, collected in the 2019-20 and 2020-21 seasons a, b.


Fresno County

Napa County

Treatment

Cluster No.

Cluster Mass (g)

Yield (kg/vine)

Leaf Area: Fruit (m2/kg)

Treatment

Cluster No.

Cluster Mass (g)

Yield (kg/vine)

Leaf Area: Fruit (m2/kg)

2020

No Till - AG

139 ± 9.92

128.6 ± 7.9

5.92 ± 0.98

1.94 ± 0.11

No Till - AG

18 ± 1.29

64.5 ± 6.5

0.40 ± 0.17

1.74 ±  0.41

No Till - RV

122 ± 20.17

128.4 ± 16.9

5.11 ± 0.77

1.42 ± 0.68

No Till - RV

19 ± 2.67

74.2 ± 12.4

0.47 ± 0.28

1.38 ±  0.23

No Till - PG

115 ± 20.13

145.6 ± 16.8

5.44 ± 0.95

1.55 ± 0.66

No Till - PG

17 ± 1.57

73.1 ± 7.1

0.41 ± 0.08

1.54 ± 0.10

Till - AG

139 ± 25.89

112.8 ± 18.7

5.32 ± 0.62

1.72 ± 0.25

Till - AG

17 ± 1.57

82.6 ± 15.4

0.47 ± 0.32

1.37 ± 0.26

Till - RV

146 ± 26.35

121.9 ± 9.9

5.86 ± 1.02

1.58 ± 0.25

Till - RV

17 ± 1.06

80.0 ± 10.9

0.46 ± 0.26

1.54 ± 0.32

Till - PG

129 ± 36.47

157.1 ± 11.6

6.58 ± 0.98

1.60 ± 0.45

Till - PG

18 ± 0.50

78.9 ± 7.8

0.47 ± 0.24

1.41 ± 0.28

Cover crop (CC)

ns

ns

ns

ns

Cover crop (CC)

ns

ns

ns

ns

Tillage (T)

ns

ns

ns

ns

Tillage (T)

ns

ns

ns

ns

CC x T

ns

ns

ns

ns

CC x T

ns

ns

ns

ns

2021

No Till - AG

111 ± 15.59

160.2 ± 14.2

5.85 ± 0.67

1.97 ± 0.12

No Till - AG

34 ± 4.71

100.6 ± 19.0

1.16 ± 1.05

0.65 ± 0.12

No Till - RV

106 ± 23.11

134.4 ± 25.4

4.53 ± 0.75

1.64 ± 0.94

No Till - RV

32 ± 5.52

79.8 ± 5.3

0.83 ± 0.24

0.70 ± 0.13

No Till - PG

100 ± 9.33

147.7 ± 33.2

4.83 ± 0.46

1.59 ± 0.58

No Till - PG

37 ± 0.50

81.0 ± 2.7

0.88 ± 0.06

0.72 ± 0.45

Till - AG

124 ± 28.06

168.9 ± 21.3

6.71 ± 0.81

1.40 ± 0.26

Till - AG

32 ± 1.22

105.1 ± 26.6

1.09 ± 0.74

0.60 ± 0.09

Till - RV

137 ± 16.52

131.8 ± 28.5

5.91 ± 0.22

1.52 ± 0.40

Till - RV

41 ± 7.80

104.0 ± 17.1

1.52 ± 0.78

0.57 ± 0.10

Till - PG

116 ± 26.39

172.8 ± 45.0

6.66 ± 0.10

1.63 ± 0.48

Till - PG

40 ± 7.17

82.9 ± 11.3

1.11 ± 0.85

0.76 ± 0.32

Cover crop (CC)

ns

ns

ns

ns

Cover crop (CC)

ns

ns

ns

ns

Tillage (T)

ns

ns

ns

ns

Tillage (T)

ns

ns

ns

ns

CC x T

ns

ns

ns

ns

CC x T

ns

ns

ns

ns

Year

*

*

ns

ns

Year

***

**

***

***

Year x CC

ns

ns

ns

ns

Year x CC

ns

ns

ns

ns

Year x T

*

***

ns

ns

Year x T

*

***

ns

ns

Year x T x CC

ns

ns

ns

ns

Year x T x CC

ns

ns

ns

ns

a ANOVA to compare data (p-value indicated); Letters within columns indicate significant mean separation according to Tukey's HSD test at p-value < 0.05, where "*": p-value < 0.05; "**": p-value < 0.001, "***": p-value < 0.0001.

b Abbreviations: ns: not significant; AG: Annual grass; RV: resident vegetation; PG: perennial grass.

4. Grape berry composition

In Fresno juice, pH, TA, TSS, total anthocyanin content, average berry mass, and average skin mass were not affected by the cover crop, or tillage system applied. The TSS and TA were higher in 2021, and TA was lower under NT (5.92 g/L) compared to CT (6.53 g/L) (Table 7).

At Oakville, the TSS and average berry mass were higher in 2020 than in 2021. Total anthocyanin content and average skin mass were higher in 2021 than in 2020. There was a main effect of tillage on juice pH, as mean values were lower in CT (3.43) compared to NT (3.46) over the two seasons. Furthermore, there was also a year-by-tillage interaction among pH due to a greater difference between tillage treatments in 2021. Conversely, mean juice TA values were lower in NT (6.48 g/L) compared to CT (7.13 g/L) in only 2021, resulting in a year-by-tillage interaction and without the main effect of tillage.

Table 7. Berry composition of Ruby Cabernet (Fresno County) and Merlot (Napa County) grapevines subjected to different cover crops and tillage collected in the 2019-20 and 2020-21 seasons a, b.


Treatment

Juice pH

TA (g/L)

TSS (°Brix)

Total Anthocyanins (mg/g Berry FM)

Average Berry Mass (g/berry)

Average Skin Mass (g)

Fresno County

2020

No Till - AG

3.89 ± 0.04

5.37 ± 0.38

21.8 ± 1.5

1.45 ± 0.23

1.83 ± 0.09

1.31 ± 0.07

No Till - RV

3.84 ± 0.04

5.73 ± 0.23

17.2 ± 4.3

1.44 ± 0.24

1.78 ± 0.05

1.41 ± 0.12

No Till - PG

3.88 ± 0.05

5.68 ± 0.71

19.5 ± 2.6

1.48 ± 0.27

1.54 ± 0.08

1.24 ± 0.22

Till - AG

3.80 ± 0.06

6.30 ± 0.50

20.4 ± 1.3

1.20 ± 0.21

1.72 ± 0.22

1.32 ±  0.21

Till - RV

3.89 ± 0.02

5.60 ± 0.27

20.4 ± 1.2

1.55 ± 0.04

1.80 ± 0.02

1.42 ±  0.17

Till - PG

3.88 ± 0.02

5.77 ± 0.56

20.8 ± 0.8

1.40 ± 0.03

1.77 ± 0.12

1.51 ±  0.34

Cover crop (CC)

ns

ns

ns

ns

ns

ns

Tillage (T)

ns

ns

ns

ns

ns

ns

CC x T

ns

ns

ns

ns

ns

ns

2021

No Till - AG

3.86 ± 0.03

6.18 ± 0.24 b

21.1 ± 1.4

1.85 ± 0.44

1.74 ± 0.11

1.37 ± 0.29

No Till - RV

3.87 ± 0.03

5.92 ± 0.61 b

22.2 ± 1.3

1.41 ± 0.39

1.67 ± 0.08

1.25 ± 0.20

No Till - PG

3.82 ± 0.04

6.13 ± 0.78 b

19.6 ± 2.4

1.60 ± 0.30

1.68 ± 0.11

1.34 ± 0.12

Till - AG

3.77 ± 0.06

6.98 ± 0.86 a

20.8 ± 1.1

1.27 ± 0.10

1.75 ± 0.14

1.28 ± 0.23

Till - RV

3.82 ± 0.09

6.95 ± 0.95 a

21.9 ± 0.9

1.80 ± 0.35

1.78 ± 0.07

1.45 ± 0.23

Till - PG

3.88 ± 0.09

6.35 ± 1.33 a

22.1 ± 1.2

2.04 ± 0.42

1.68 ± 0.04

1.62 ± 0.20

Cover crop (CC)

ns

ns

ns

ns

ns

ns

Tillage (T)

ns

*

ns

ns

ns

ns

CC x T

ns

ns

ns

ns

ns

ns

Year

ns

***

**

ns

ns

ns

Year x CC

ns

ns

ns

ns

ns

ns

Year x T

ns

ns

ns

ns

ns

ns

Year x T x CC

ns

ns

ns

ns

ns

ns

Napa County

2020

No Till - AG

3.33 ± 0.02

7.70 ± 0.43

25.9 ± 1.0

1.16 ± 0.08

0.94 ± 0.06

0.78 ± 0.08

No Till - RV

3.32 ± 0.01

7.65 ± 0.29

25.2 ± 0.6

1.50 ± 0.44

0.94 ± 0.05

0.61 ± 0.07

No Till - PG

3.30 ± 0.01

7.85 ± 0.05

24.8 ± 0.5

1.37 ± 0.48

1.02 ± 0.08

0.63 ± 0.11

Till - AG

3.31 ± 0.02

7.50 ± 0.13

25.4 ± 0.2

1.49 ± 0.30

1.00 ± 0.10

0.61 ± 0.09

Till - RV

3.33 ± 0.02

7.50 ± 0.24

24.7 ± 1.6

1.42 ± 0.12

0.96 ± 0.06

0.59 ± 0.06

Till - PG

3.32 ±  0.02

7.68 ± 0.24

25.7 ± 0.5

1.36 ± 0.11

0.94 ± 0.07

0.57 ± 0.09

Cover crop (CC)

ns

ns

ns

ns

ns

ns

Tillage (T)

ns

ns

ns

ns

ns

ns

CC x T

ns

ns

ns

ns

ns

ns

2021

No Till - AG

3.58 ± 0.05 a

6.58 ± 0.43

24.1 ± 0.5

2.40 ±  0.44

0.91 ± 0.13

1.14 ± 0.13

No Till - RV

3.65 ± 0.10 a

6.73 ± 0.11

24.7 ± 0.5

1.20 ± 0.32

0.99 ± 0.05

1.26 ± 0.26

No Till - PG

3.59 ± 0.03 a

6.30 ± 0.30

25.6 ± 0.9

2.93 ± 0.89

0.83 ± 0.04

1.37 ± 0.08

Till - AG

3.54 ± 0.01 b

7.00 ± 0.32

24.9 ± 0.6

1.91 ± 0.39

0.96 ± 0.03

1.40 ± 0.29

Till - RV

3.54 ± 0.03 b

7.30 ± 0.33

24.4 ± 0.5

2.28 ± 0.41

1.04 ± 0.05

1.18 ± 0.21

Till - PG

3.54 ± 0.01 b

7.08 ± 0.23

24.1 ± 0.4

2.05 ± 0.19

0.89 ± 0.04

1.05 ± 0.15

Cover crop (CC)

ns

ns

ns

ns

ns

ns

Tillage (T)

*

ns

ns

ns

ns

ns

CC x T

ns

ns

ns

ns

ns

ns

Year

***

***

*

***

ns

***

Year x CC

ns

ns

ns

ns

ns

ns

Year x T

*

***

ns

ns

ns

ns

Year x T x CC

ns

ns

ns

ns

ns

ns

a ANOVA to compare data (p-value indicated); Letters within columns indicate significant mean separation according to Tukey's HSD test at p-value < 0.05, where "*": p-value < 0.05; "**": p-value < 0.001, "***": p-value < 0.0001.

b Abbreviations: TA: titratable acidity; TSS: total soluble solids; ns: not significant; AG: Annual grass; RV: resident vegetation; PG: perennial grass.

5. Vineyard water footprint

The analysis of the effect of treatments applied on WF components indicated the same pattern regardless of the growing season at both sites. In Fresno, the green water footprint was greater in 2020 than in 2021 (Table 8). However, the treatments applied did not affect the WF components at Fresno. At Oakville, year-to-year differences were observed in all WF components, with 2020 values greater than 2021 which was expected due to differences in yield between the two years (Table 6). The treatments applied did not affect the WF of the vineyard at Oakville in 2020 or 2021 either.

Table 8. Water footprint (m3/ton) of the Ruby Cabernet (Fresno County) and Merlot (Napa County) vineyard subjected to different cover crops and tillage collected in the 2019-20 and 2020-21 seasons a, b.


Fresno County

Napa County

Treatment

Green Water Footprint (m3/ton)

Blue Water Footprint (m3/ton)

Grey Water Footprint (m3/ton)

Total Water Footprint (m3/ton)

Treatment

Green Water Footprint (m3/ton)

Blue Water Footprint (m3/ton)

Grey Water Footprint (m3/ton)

Total Water Footprint (m3/ton)

2020

No Till - AG

170 ± 9.3

248 ± 13.6

50 ± 2.7

468 ± 25.7

No Till - AG

2803 ± 369.3

1170 ± 154.1

116 ± 15.2

4088 ± 538.7

No Till - RV

197 ± 10.2

288 ± 14.9

58 ± 3.0

542 ± 28.0

No Till - RV

2344 ± 376.1

978 ± 157.0

97 ± 15.5

3419 ± 548.6

No Till - PG

180 ± 9.3

263 ± 13.5

53 ± 2.7

496 ± 25.5

No Till - PG

2347 ± 173.5

979 ± 72.4

97 ± 7.2

3423 ± 253.0

Till - AG

211 ± 63.2

308 ± 92.4

62 ± 18.5

500 ± 174.1

Till - AG

2316 ± 274.0

966 ± 114.3

95 ± 11.3

3378 ± 399.6

Till - RV

173 ± 18.4

254 ± 26.8

51 ± 5.4

478 ± 50.6

Till - RV

2366 ± 337.9

987 ± 141.0

98 ± 13.9

3451 ± 492.9

Till - PG

159 ± 29.4

233 ± 43.0

47 ± 8.6

439 ± 81.0

Till - PG

2281 ± 319.5

952 ± 133.3

94 ± 13.2

3328 ± 466.0

Cover crop (CC)

ns

ns

ns

ns

Cover crop (CC)

ns

ns

ns

ns

Tillage (T)

ns

ns

ns

ns

Tillage (T)

ns

ns

ns

ns

CC x T

ns

ns

ns

ns

CC x T

ns

ns

ns

ns

2021

No Till - AG

137 ± 13.9

276 ± 28.1

52 ± 5.3

466 ± 47.3

No Till - AG

1213 ± 332.9

359 ± 98.6

87 ± 23.8

1659 ± 455.3

No Till - RV

187 ± 32.6

377 ± 65.6

72 ± 12.5

635 ± 110.6

No Till - RV

1481 ± 97.4

439 ± 28.9

106 ± 7.0

2026 ± 133.3

No Till - PG

177 ± 38.2

357 ± 77.1

68 ± 14.6

603 ± 129.9

No Till - PG

1417 ± 142.5

420 ± 42.2

101 ± 10.2

1938 ± 194.9

Till - AG

121 ± 9.8

244 ± 19.8

46 ± 3.8

412 ± 33.4

Till - AG

1231 ± 225.8

365 ± 66.9

88 ± 16.2

1684 ± 308.8

Till - RV

133 ± 28.1

277 ± 56.7

51 ± 10.8

452 ± 95.5

Till - RV

932 ± 106.4

276 ± 31.5

67 ± 7.6

1275 ± 145.6

Till - PG

138 ± 56.6

278 ± 114.1

53 ± 21.7

469 ± 192.4

Till - PG

1208 ± 229.1

358 ± 67.9

87 ± 16.4

1653 ± 313.4

Cover crop (CC)

ns

ns

ns

ns

Cover crop (CC)

ns

ns

ns

ns

Tillage (T)

ns

ns

ns

ns

Tillage (T)

ns

ns

ns

ns

CC x T

ns

ns

ns

ns

CC x T

ns

ns

ns

ns

Year

*

ns

ns

ns

Year

**

**

**

**

Year x CC

ns

ns

ns

ns

Year x CC

ns

ns

ns

Ns

Year x T

ns

ns

ns

ns

Year x T

ns

ns

ns

ns

CC x T x Year

ns

ns

ns

ns

CC x T x Year

ns

ns

ns

ns

a ANOVA to compare data (p-value indicated); Letters within columns indicate significant mean separation according to Tukey's honest significance difference (HSD) test at p-value < 0.05, where "*": p-value < 0.05; "**": p-value < 0.001, "***": p-value < 0.0001.

b Abbreviations: ns: not significant; AG: Annual grass; RV: resident vegetation; PG: perennial grass.

Discussion

1. Cover crop and tillage system did not affect leaf gas exchange

At both sites, there were no effects of cover crop or tillage on gs or Anet over the two seasons monitored in this paper. This may indicate that despite different climatic and site conditions, whole grapevine physiology was not affected by the presence of a cover crop or tillage. These results are corroborated with previous work that has measured leaf gas exchange between grapevines grown with and without inter-row cover crops and found negligible differences (Celette et al., 2009b; Sweet and Schreiner, 2010; Hatch et al., 2011b; Reeve et al., 2016). Previous works that reported changes to leaf gas exchange of the grapevine have either contrasting applied water amounts (Torres et al., 2021), variation in leaf area to shoot ratio (Martinez-Lüscher and Kurtural, 2021) or soil spatial variability that affected grapevine water status (Brillante et al., 2018, Yu et al., 2021). Since neither factor had a significant effect on these variables, it is plausible that cover crops or tillage would not affect grapevine leaf gas exchange in the short term in warm climate viticulture.

2. Tillage was more influential than cover crop type on grapevine water status and mineral nutrition

Much of the literature regarding competition between cover crops and grapevine suggested that the presence of a cover crop increased the competition for nutrients, namely nitrogen (Calderón et al., 2001; Celette et al., 2009b; Reeve et al., 2016) and, consequently, we hypothesised that RV and AG would decrease grapevine mineral nutrition status; however, no effects of cover crop on grapevine mineral nutrition were found under our experimental conditions. In Fresno, the nutrient status of the grapevines at bloom only differed between years and was not affected by treatments, indicating little to no competition with the cover crop for nutrients in mature vineyards under arid conditions.

However, Oakville tillage appeared to have an effect on grapevine mineral nutrition, and CT grapevines demonstrated a higher nitrogen content at bloom compared to NT in both years. Higher N in both leaves and juice in response to tillage was previously reported (Rodriguez-Lovelle et al., 2000b; Guerra and Steenwerth, 2012). In one particular three-year study, NO3-N petiole values of grapevines with inter-row tillage were found to be up to 2 × greater than those of no-till grapevines, suggesting a possible temporal offset between soil N availability and plant uptake related to tillage (Steenwerth et al., 2013b; Reeve et al., 2016). It was well demonstrated that soil tillage affects the decomposition and mineralisation of N from plant residues and existing pools which regulates the inorganic N pool available for uptake by the grapevines (Guerra and Steenwerth, 2012). The type of cover crop did not influence nitrogen content in the present study, nor was there an interaction between cover crop and tillage. Similarly, small differences in P and S contents have been noticed between a tilled and cover-cropped table grape vineyard in the Puglia region, southern Italy, with higher values in the leaves of the cover-cropped vineyard (Tarantino et al., 2020).

It was also hypothesised that PG would improve grapevine water status due to spatial and temporal complementarity, whereby the shallow rooting depth would be less likely to compete with grapevines, and peak water use of PG would occur during grapevine dormancy. In Fresno, no treatment effects were observed on grapevine water status nor among WF components. This result is particularly important as it indicated that despite different growth cover crops (AG is a tall stature grass and, thus, produces more biomass than the low stature PG, Figure 1), there was no competition with the grapevines for water due to vineyards were sufficiently irrigated, as also indicated by a lack of differences in Ψs between treatments. In Oakville, PG did improve grapevine water status compared to RV and AG in one instance during 2020, but this effect was not observed in the second year of the study nor over the two seasons. Furthermore, there was no interaction effect between the PG cover crop, and NT factor, which is particularly important as the greatest benefits to the soil from a permanent cover crop were observed under no-till environments (Rodriguez-Lovelle et al., 2000a; Morlat and Jacquet, 2003; Volaire and Lelièvre, 2010).

While under our experimental conditions, the type of cover crop again had little influence on grapevine water status in contrast with previous studies (Ingels et al., 2005), CT improved grapevine water status (i.e., more positive Ψs) compared to grapevines under NT. Thus, although it is commonly accepted that cover crops may exert some competition with grapevines for soil water, Steenwerth et al. (2016) previously reported reduced soil water content under no-till settings, and no association was found with Ψs. While contradictory to some reports that indicated tillage did not affect grapevine water status (Van Huyssteen and Weber, 1980; Steenwerth et al., 2013; Myburgh, 2013), this result provided further evidence of tillage in semi-arid regions to preserve water in the soil through early season cultivation. This was based on the notion that while evaporative losses of the upper tilled layer of soil immediately increase, overall losses are minimised as a barrier that restricts capillary water movement is created, which preserves moisture in the deeper layers of the soil (Hillel, 1998; Myburgh, 2013b). Furthermore, seasonal grapevine water status in irrigated viticulture was shown to be more influenced by subsoil conditions than the topsoil, which dries quite early in California vineyards (Yu et al., 2021). As the presence of vegetation was shown to deplete water out of the upper portion of the soil more rapidly than bare soil (Monteiro and Lopes, 2007b; Celette et al., 2008; Novara et al., 2018), it is possible that the complete termination and incorporation of vegetation helped preserved moisture in the soil compared to NT, where vegetation was able to remain in competition with the grapevines. However, no conclusions can be made as to the mechanism of reduced water stress under CT vines, as root structure was not examined in the present study (Hunter, 1998; Myburgh, 2013b). Ultimately, these differences in vine water status between tillage systems in Oakville did not affect WF components, as irrigation amounts remained unchanged.

3. Minimal effects observed on yield components and berry composition

Regarding grapevine yield and berry composition, most differences were observed between years at the Fresno vineyard. Although no yield components were affected by cover crop or tillage, minimal effects of tillage on berry composition were seen. The TA was significantly higher in CT compared to NT in both years, as has been previously reported when permanent grass was compared to conventionally tilled soil (Reeve et al., 2016), even in a table grape vineyard (Ferrara et al., 2021). This may suggest that tillage hastens the ripening process; however, no statistically significant effects were observed on Brix, which would support such a claim as the climate keeps warming in the study areas (Kennedy, 2002; Gambetta and Kurtural, 2021). Other studies that investigated the influence of vineyard floor management in mature vineyards reported similar findings with reduced effect of soil management practices as grapevines aged. It was possible that mature grapevines may be more resilient to the adoption of cover crops due to their well-established root systems that can more effectively compete with the cover crop (Van Huyssteen and Weber, 1980; King and Berry, 2005; Steenwerth et al., 2013b; Fourie et al., 2017b; Gattullo et al., 2020). Combined, these results provided evidence that the use of annual or perennial grass cover crops and/or no-till practices may be implemented in mature irrigated vineyards in the San Joaquin Valley with little to no effect on production.

In the Oakville vineyard, TA was again significantly higher under CT compared to NT in 2021. However, this effect was only seen in the second year of the study resulting in a year-by-tillage interaction without a significant main effect. The juice pH was also reduced under CT grapevines, which has been a reported effect of cover crop adoption rather than tillage as a result of the release of potassium (K) when the cover crop decomposed (Wheeler et al., 2005; Guerra and Steenwerth, 2012; Chrysargyris et al., 2018b; Cataldo et al., 2020). While several studies have reported no reductions to yield in response to cover crops, others that assessed permanent cover crops observed decreased yield after 2 to 3 years (Morlat and Jacquet, 2003; Tesic et al., 2007; Lopes et al., 2008a; Steenwerth and Belina, 2008b; Hatch et al., 2011b; Giese et al., 2015b). It is not clear whether competition for water or N was the primary cause, as the two factors are interconnected (Celette et al., 2008, 2009b). The absence of effect on yield, as seen in this study and in others, may be a result of the shorter length of the experiment and/or shallower rooting depth of the perennial grass used compared to deeper rooting and higher biomass-producing grasses investigated in the aforementioned studies. However, even considering 3-year trials, effects on yield are generally limited and mainly at the beginning of the trial when the cover crops are sowed. Ultimately, the adoption of cover crops under both tillage systems in the present study did not affect production despite great differences in soil type, vineyard age, and climate between the two sites.

Conclusions

Under the experimental conditions of this study, the use of inter-row cover crops had negligible beneficial effects on grapevine physiology, mineral nutrition or productivity, with no detrimental effects on vineyard water footprint, in both hot and warm climate vineyards. Additionally, differences between the cover crop species used in this study were not evident. The main effects of inter-row management were evidenced when comparing conventional tillage vs no tilling. Thus, conventional tilling accounted for increased pH and, consequently, decreased must acidity, and decreased water stress over the season, especially, when studying tillage on younger vineyards where it was beneficial to improve vine water and nutritional status in Napa Valley.

Acknowledgements

The authors would like to acknowledge the Wine Group, especially Mr Terry Violett, for his support and vision for the project as well as the access to the vineyard, equipment, and farming practices for their in-kind support for the project. The authors also acknowledge the farming staff at the Department of Viticulture and Enology Oakville Experimental Vineyard. A graduate stipend was provided to MZ and JEM from the Department of Enology and Viticulture. MZ has received research support Jastro-Shields Trust to complete her research.

References

  • Abad, J., Hermoso de Mendoza, I., Marín, D., Orcaray, L., & Santesteban, L. G. (2021). Cover crops in viticulture. A systematic review (1): Implications on soil characteristics and biodiversity in vineyard. OENO One, 55(1), 295–312. https://doi.org/10.20870/oeno-one.2021.55.1.3599
  • Alsina, M. M., Fanton-Borges, A. C., & Smart, D. R. (2013). Spatiotemporal variation of event related N2O and CH4 emissions during fertigation in a California almond orchard. Ecosphere, 4(1). https://doi.org/10.1890/ES12-00236.1
  • Álvaro-Fuentes, J., López, M. V., Cantero-Martinez, C., & Arrúe, J. L. (2008). Tillage Effects on Soil Organic Carbon Fractions in Mediterranean Dryland Agroecosystems. Soil Science Society of America Journal, 72(2), 541–547. https://doi.org/10.2136/sssaj2007.0164
  • Bowles, T. M., Jackson, L. E., Loeher, M., & Cavagnaro, T. R. (2017). Ecological intensification and arbuscular mycorrhizas: A meta-analysis of tillage and cover crop effects. Journal of Applied Ecology, 54(6), 1785–1793. https://doi.org/10.1111/1365-2664.12815
  • Buesa, I., Miras-Ávalos, J. M., De Paz, J. M., Visconti, F., Sanz, F., Yeves, A., Guerra, D., & Intrigliolo, D. S. (2021). Soil management in semi-arid vineyards: Combined effects of organic mulching and no-tillage under different water regimes. European Journal of Agronomy, 123, 126198.
  • Calderón, F. J., Jackson, L. E., Scow, K. M., & Rolston, D. E. (2001). Short-Term Dynamics of Nitrogen, Microbial Activity, and Phospholipid Fatty Acids after Tillage. Soil Science Society of America Journal, 65(1), 118–126. https://doi.org/10.2136/sssaj2001.651118x
  • Cataldo, E., Salvi, L., Sbraci, S., Storchi, P., & Mattii, G. B. (2020). Sustainable viticulture: Effects of soil management in Vitis vinifera. Agronomy, 10(12), 1949.
  • Celette, F., Findeling, A., & Gary, C. (2009). Competition for nitrogen in an unfertilized intercropping system: The case of an association of grapevine and grass cover in a Mediterranean climate. European Journal of Agronomy, 30(1), 41–51. https://doi.org/10.1016/j.eja.2008.07.003
  • Celette, F., Gaudin, R., & Gary, C. (2008). Spatial and temporal changes to the water regime of a Mediterranean vineyard due to the adoption of cover cropping. European Journal of Agronomy, 29(4), 153–162. https://doi.org/10.1016/j.eja.2008.04.007
  • Celette, F., Wery, J., Chantelot, E., Celette, J., & Gary, C. (2005). Belowground Interactions in a Vine (Vitis vinifera L.)-tall Fescue (Festuca arundinacea Shreb.) Intercropping System: Water Relations and Growth. Plant and Soil, 276(1–2), 205–217. https://doi.org/10.1007/s11104-005-4415-5
  • Chrysargyris, A., Xylia, P., Litskas, V., Mandoulaki, A., Antoniou, D., Boyias, T., Stavrinides, M., & Tzortzakis, N. (2018). Drought stress and soil management practices in grapevines in Cyprus under the threat of climate change. Journal of Water and Climate Change, 9(4), 703–714.
  • Costello, M. J. (2010). Growth and yield of cultivated grape with native perennial grasses nodding needlegrass or California barley as cover crops. HortScience, 45(1), 154–156.
  • Daane, K. M., Hogg, B. N., Wilson, H., & Yokota, G. Y. (2018). Native grass ground covers provide multiple ecosystem services in Californian vineyards. Journal of Applied Ecology, 55(5), 2473–2483.
  • Delpuech, X., & Metay, A. (2018). Adapting cover crop soil coverage to soil depth to limit competition for water in a Mediterranean vineyard. European Journal of Agronomy, 97, 60–69.
  • Dobrei, A., Nistor, E., Sala, F., & Dobrei, A. (2015). Tillage Practices in the Context of Climate Change and a Sustainable Viticulture. Notulae Scientia Biologicae, 7(4), 500–504. https://doi.org/10.15835/nsb749724
  • Ferrara, G., Loffredo, E., Simeone, R., Senesi, N. (2000). Evaluation of antimutagenic and desmutagenic effects of humic and fulvic acids on root tips of Vicia faba. Environmental Toxicology 15: 513-517. https://doi.org/10.1002/1522-7278(2000)15:5<513::AID-TOX22>3.0.CO;2-S
  • Ferrara, G., Loffredo, E., Senesi, N. (2004). Anticlastogenic, antitoxic and sorption effects of humic substances on the mutagen maleic hydrazide tested in leguminous plants. European Journal of Soil Science, 55: 449-458. https://doi.org/10.1111/j.1365-2389.2004.00611.x.
  • Ferrara, G., Loffredo, E., Senesi, N. Marcos, R. (2006). Humic acids reduce the genotoxicity of mitomycin C in human lymphoblastoid cell line TK6. Mutation Research Genetic Toxicology and Environmental Mutagenesis, 603: 27-32. https://doi.org/10.1016/j.mrgentox.2005.10.014.
  • Ferrara, G., Nigro, D., Torres, R., Gadaleta, A., Fidelibus, M.W., Mazzeo, A. (2021). Cover crops in the inter-row of a table grape vineyard managed with irrigation sensors: effects on yield, quality and glutamine synthetase activity in leaves. Scientia Horticulturae, 281: 109963. https://doi.org/10.1016/j.scienta.2021.109963.
  • Ferreira, C. S., Veiga, A., & Caetano, A. (2020). Assessment of the Impact of Distinct Vineyard Management Practices on Soil Physico-Chemical Properties. https://journals.sagepub.com/doi/10.1177/1178622120944847
  • Fourie, J. C., & Freitag, K. (2010). Soil management in the Breede River Valley wine grape region, South Africa. 2. Soil temperature. South African Journal of Enology and Viticulture, 31(2), 165–168.
  • Gatti, M., Garavani, A., Squeri, C., Capri, C., Diti, I., D’Ambrosio, R., Frioni, T., Scotti, C., & Poni, S. (2022a). Inter-row floor management is a powerful factor for optimising vine balance in a non-irrigated organic Barbera vineyard in northern Italy. European Journal of Agronomy, 136, 126490. https://doi.org/10.1016/j.eja.2022.126490.
  • Gambetta, G, & Kurtural, SK. (2021). Global warming and wine quality: Are we close to the tipping point? Oeno One 55: 353-361. doi: 10.20870/oeno-one.2021.55.3.4774
  • Gattullo, C.E., Mezzapesa, G.N., Stellacci, A.M., Ferrara, G., Occhiogrosso, G., Petrelli, G., Castellini, M., Spagnuolo, M. (2020). Cover crop for a sustainable viticulture: effects on soil properties and table grape production. Agronomy, 10: 1334. https://doi.org/10.3390/agronomy10091334.
  • Gaudin, R., Celette, F., & Gary, C. (2010). Contribution of runoff to incomplete off season soil water refilling in a Mediterranean vineyard. Agricultural Water Management, 97(10), 1534–1540.
  • Giese, G., Wolf, T. K., Velasco-Cruz, C., Roberts, L., & Heitman, J. (2015a). Cover Crop and Root Pruning Impacts on Vegetative Growth, Crop Yield Components, and Grape Composition of Cabernet Sauvignon. American Journal of Enology and Viticulture, 66(2), 212–226. https://doi.org/10.5344/ajev.2014.14100
  • Giese, G., Wolf, T. K., Velasco-Cruz, C., Roberts, L., & Heitman, J. (2015b). Cover Crop and Root Pruning Impacts on Vegetative Growth, Crop Yield Components, and Grape Composition of Cabernet Sauvignon. American Journal of Enology and Viticulture, 66(2), 212–226. https://doi.org/10.5344/ajev.2014.14100
  • Guerra, B., & Steenwerth, K. (2012). Influence of Floor Management Technique on Grapevine Growth, Disease Pressure, and Juice and Wine Composition: A Review. American Journal of Enology and Viticulture, 63(2), 149–164. https://doi.org/10.5344/ajev.2011.10001
  • Hatch, T. A., Hickey, C. C., & Wolf, T. K. (2011). Cover crop, rootstock, and root restriction regulate vegetative growth of Cabernet Sauvignon in a humid environment. American Journal of Enology and Viticulture, 62(3), 298–311.
  • Hillel, D. (1998). Environmental soil physics: Fundamentals, applications, and environmental considerations. Elsevier.
  • Hunter, J. J. (1998). Plant spacing implications for grafted grapevine II soil water, plant water relations, Canopy Physiology, Vegetative and Reproductive Characteristics, Grape Composition, Wine Quality and labour requirements. South African Journal of Enology and Viticulture, 19(2), 35–51.
  • Ingels, C. A., Scow, K. M., Whisson, D. A., & Drenovsky, R. E. (2005). Effects of cover crops on grapevines, yield, juice composition, soil microbial ecology, and gopher activity. American Journal of Enology and Viticulture, 56(1), 19–29.
  • Jordan, L. M., Björkman, T., & Heuvel, J. E. V. (2016). Annual under-vine cover crops did not impact vine growth or fruit composition of mature cool-climate ‘Riesling’grapevines. HortTechnology, 26(1), 36–45.
  • Kennedy, J. (2002). Understanding grape berry development. Practical Winery & Vineyard, 4, 1–5.
  • King, A. P., & Berry, A. M. (2005). Vineyard δ15N, nitrogen and water status in perennial clover and bunch grass cover crop systems of California’s central valley. Agriculture, Ecosystems & Environment, 109(3), 262–272. https://doi.org/10.1016/j.agee.2005.03.002
  • Lal, R. (2004). Soil carbon sequestration to mitigate climate change. Geoderma, 123(1–2), 1–22. https://doi.org/10.1016/j.geoderma.2004.01.032
  • Lal, R. (2012). Climate Change and Soil Degradation Mitigation by Sustainable Management of Soils and Other Natural Resources. Agricultural Research, 1(3), 199–212. https://doi.org/10.1007/s40003-012-0031-9
  • Lazcano, C., Decock, C., & Wilson, S. G. (2020). Defining and Managing for Healthy Vineyard Soils, Intersections With the Concept of Terroir. Frontiers in Environmental Science, 8. https://www.frontiersin.org/article/10.3389/fenvs.2020.00068
  • Lee, J., & Steenwerth, K. L. (2013). ‘Cabernet Sauvignon’ grape anthocyanin increased by soil conservation practices. Scientia Horticulturae, 159, 128–133. https://doi.org/10.1016/j.scienta.2013.05.025
  • Lopes, C. M., Monteiro, A., Machado, J. P., Fernandes, N., & Araújo, A. (2008a). Cover cropping in a sloping non-irrigated vineyard: II–Effects on vegetative growth, yield, berry and wine quality of ‘Cabernet Sauvignon’grapevines. Ciência Téc. Vitiv, 23(1), 37–43.
  • Lopes, C. M., Santos, T. P., Monteiro, A., Rodrigues, M. L., Costa, J. M., & Chaves, M. M. (2011). Combining cover cropping with deficit irrigation in a Mediterranean low vigor vineyard. Scientia Horticulturae, 129(4), 603–612.
  • Martinez-Luscher, M., Brillante, L., & Kurtural, SK. (2019). Flavonol profile is a reliable indicator of canopy architecture and the exposure of grapevines to solar radiation. Frontiers in Plant Science 10. doi: 10.3389/fpls.2019.00010
  • Messiga, A. J., Gallant, K. S., Sharifi, M., Hammermeister, A., Fuller, K., Tango, M., & Fillmore, S. (2016). Grape Yield and Quality Response to Cover Crops and Amendments in a Vineyard in Nova Scotia, Canada. American Journal of Enology and Viticulture, 67(1), 77–85. https://doi.org/10.5344/ajev.2015.15013
  • Monteiro, A., & Lopes, C. M. (2007). Influence of cover crop on water use and performance of vineyard in Mediterranean Portugal. Agriculture, Ecosystems & Environment, 121(4), 336–342. https://doi.org/10.1016/j.agee.2006.11.016
  • Morlat, R., & Jacquet, A. (2003). Grapevine root system and soil characteristics in a vineyard maintained long-term with or without interrow sward. American Journal of Enology and Viticulture, 54(1), 1–7.
  • Myburgh, P. A. (2013). Effect of shallow tillage and straw mulching on soil water conservation and grapevine response. South African Journal of Plant and Soil, 30(4), 219–225. https://doi.org/10.1080/02571862.2013.867459
  • Naor, A., Gal, Y., & Bravdo, B. (1997). Crop load affects assimilation rate, stomatal conductance, stem water potential and water relations of field-grown Sauvignon blanc grapevines. Journal of Experimental Botany, 48(9), 1675–1680.
  • Novara, A., Cerdà, A., & Gristina, L. (2018). Sustainable vineyard floor management: An equilibrium between water consumption and soil conservation. Current Opinion in Environmental Science & Health, 5, 33–37. https://doi.org/10.1016/j.coesh.2018.04.005
  • Ovalle, C., Del Pozo, A., Peoples, M. B., & Lavín, A. (2010). Estimating the contribution of nitrogen from legume cover crops to the nitrogen nutrition of grapevines using a 15N dilution technique. Plant and Soil, 334(1), 247–259.
  • Patiño-Zúñiga, L., Ceja-Navarro, J. A., Govaerts, B., Luna-Guido, M., Sayre, K. D., & Dendooven, L. (2009a). The effect of different tillage and residue management practices on soil characteristics, inorganic N dynamics and emissions of N2O, CO2 and CH4 in the central highlands of Mexico: A laboratory study. Plant and Soil, 314(1–2), 231–241. https://doi.org/10.1007/s11104-008-9722-1
  • Patiño-Zúñiga, L., Ceja-Navarro, J. A., Govaerts, B., Luna-Guido, M., Sayre, K. D., & Dendooven, L. (2009b). The effect of different tillage and residue management practices on soil characteristics, inorganic N dynamics and emissions of N2O, CO2 and CH4 in the central highlands of Mexico: A laboratory study. Plant and Soil, 314(1), 231–241. https://doi.org/10.1007/s11104-008-9722-1
  • Pérez-Bermúdez, P., Olmo, M., Gil, J., García-Férriz, L., Olmo, C., Boluda, R., & Gavidia, I. (2016). Cover crops and pruning in Bobal and Tempranillo vineyards have little influence on grapevine nutrition. Scientia Agricola, 73(3), 260–265. https://doi.org/10.1590/0103-9016-2015-0027
  • Pool, R. M., Dunst, R. M., & Lakso, A. N. (1990). Comparison of Sod, Mulch, Cultivation, and Herbicide Floor Management Practices for Grape Production in Nonirrigated Vineyards. Journal of the American Society for Horticultural Science, 115(6), 872–877. https://doi.org/10.21273/JASHS.115.6.872
  • Pou, A., Gulías, J., Moreno, M., Tomàs, M., Medrano, H., & Cifre, J. (2011). Cover cropping in Vitis vinifera L. cv. Manto Negro vineyards under Mediterranean conditions: Effects on plant vigour, yield and grape quality. OENO One, 45(4), 223. https://doi.org/10.20870/oeno-one.2011.45.4.1501
  • Powlson, D. S., Whitmore, A. P., & Goulding, K. W. T. (2011). Soil carbon sequestration to mitigate climate change: A critical re-examination to identify the true and the false. European Journal of Soil Science, 62(1), 42–55. https://doi.org/10.1111/j.1365-2389.2010.01342.x
  • Reeve, A. L., Skinkis, P. A., Vance, A. J., Lee, J., & Tarara, J. M. (2016). Vineyard Floor Management Influences ‘Pinot noir’ Vine Growth and Productivity More than Cluster Thinning. HortScience, 51(10), 1233–1244. https://doi.org/10.21273/HORTSCI10998-16
  • Rodriguez-Lovelle, B., Soyer, J., & Molot, C. (2000a). NITROGEN AVAILABILITY IN VINEYARD SOILS ACCORDING TO SOIL MANAGEMENT PRACTICES. EFFECTS ON VINE. Acta Horticulturae. https://doi.org/10.17660/ActaHortic.2000.526.29
  • Rodriguez-Lovelle, B., Soyer, J., & Molot, C. (2000b). INCIDENCE OF PERMANENT GRASS COVER ON GRAPEVINE PHENOLOGICAL EVOLUTION AND GRAPE BERRY RIPENING. Acta Horticulturae, 526, 241–248. https://doi.org/10.17660/ActaHortic.2000.526.24
  • Smith, R., Bettiga, L., Cahn, M., Baumgartner, K., Jackson, L. E., & Bensen, T. (2008). Vineyard floor management affects soil, plant nutrition, and grape yield and quality. California Agriculture, 62(4).
  • Steenwerth, K., & Belina, K. M. (2008a). Cover crops and cultivation: Impacts on soil N dynamics and microbiological function in a Mediterranean vineyard agroecosystem. Applied Soil Ecology, 40(2), 370–380. https://doi.org/10.1016/j.apsoil.2008.06.004
  • Steenwerth, K., & Belina, K. M. (2008b). Cover crops enhance soil organic matter, carbon dynamics and microbiological function in a vineyard agroecosystem. Applied Soil Ecology, 40(2), 359–369. https://doi.org/10.1016/j.apsoil.2008.06.006
  • Steenwerth, K. L., Calderón-Orellana, A., Hanifin, R. C., Storm, C., & McElrone, A. J. (2016). Effects of various vineyard floor management techniques on weed community shifts and grapevine water relations. American Journal of Enology and Viticulture, 67(2), 153–162.
  • Steenwerth, K. L., McElrone, A. J., Calderón-Orellana, A., Hanifin, R. C., Storm, C., Collatz, W., & Manuck, C. (2013). Cover crops and tillage in a mature Merlot vineyard show few effects on grapevines. American Journal of Enology and Viticulture, 64(4), 515–521.
  • Sweet, R. M., & Schreiner, R. P. (2010). Alleyway Cover Crops Have Little Influence on Pinot noir Grapevines (Vitis vinifera L.) in Two Western Oregon Vineyards. https://www.ajevonline.org/content/61/2/240.abstract
  • Tarantino, A., Mazzeo, A., Lopriore, G., Disciglio, G., Gagliardi, A., Nuzzo, V., & Ferrara, G. (2020). Nutrients in clusters and leaves of Italian table grapes are affected by the use of cover crops in the vineyard. Journal of Berry Research, 10 (2): 157-173. https://doi.org/10.3233/JBR-190428.
  • Tesic, D., Keller, M., & Hutton, R. J. (2007). Influence of Vineyard Floor Management Practices on Grapevine Vegetative Growth, Yield, and Fruit Composition. American Journal of Enology and Viticulture, 58(1), 1–11.
  • Tomaz, A., Coleto Martínez, J., & Arruda Pacheco, C. (2021). Effects of cover crops and irrigation on ‘Tempranillo’ grapevine and berry physiology: An experiment under the Mediterranean conditions of Southern Portugal. OENO One, 55(3), 191–208. https://doi.org/10.20870/oeno-one.2021.55.3.4629
  • Torres, R., Ferrara, G., Soto, G., López, J.A., Sanchez, G., Mazzeo, A., Pérez-Pastor, A., & Domingo, R. (2017). Effects of soil and climate in a table grape vineyard with cover crops. Irrigation management using sensors networks. Ciência e Técnica Vitivinícola, 32(1): 72-81. https://doi.org/10.1051/ctv/20173201072.
  • Torres, N., Yu, R. Martinez-Luscher, J., Kostaki, E., & Kurtural, SK. (2021). Effects of irrigation at different fractions of crop evapotranspiration on water productivity and flavonoid composition of Cabernet Sauvignon grapevine. Frontiers in Plant Science 12. DOI=10.3389/fpls.2021.712622
  • Van Huyssteen, L., & Weber, H. W. (1980). The effect of selected minimum and conventional tillage practices in vineyard cultivation on vine performance. https://doi.org/10.21548/1-2-2416
  • Van Huyssteen, L., & Weber, H. W. (2017). The Effect of Selected Minimum and Conventional Tillage Practices in Vineyard Cultivation on Vine Performance. South African Journal of Enology & Viticulture, 1(2). https://doi.org/10.21548/1-2-2416
  • Volaire, F., & Lelièvre, F. (2010). Role of Summer Dormant Perennial Grasses as Intercrops in Rainfed Mediterranean Vineyards. Crop Science, 50(5), 2046–2054. https://doi.org/10.2135/cropsci2010.01.0021
  • Wheeler, S. J., Black, A. S., & Pickering, G. J. (2005). Vineyard floor management improves wine quality in highly vigorous Vitis vinifera’Cabernet Sauvignon’in New Zealand.
  • Wolff, M. W., Alsina, M. M., Stockert, C. M., Khalsa, S. D. S., & Smart, D. R. (2018). Minimum tillage of a cover crop lowers net GWP and sequesters soil carbon in a California vineyard. Soil and Tillage Research, 175, 244–254. https://doi.org/10.1016/j.still.2017.06.003
  • Yu, R., Zaccaria, D., Kisekka, I., & Kurtural, S. K. (2021). Soil apparent electrical conductivity and must carbon isotope ratio provide indication of plant water status in wine grape vineyards. Precision Agriculture, 22(4), 1333–1352. https://doi.org/10.1007/s11119-021-09787-x
  • Zumkeller, M, Yu, R, Torres, N, Marigliano, ME, Zaccaria, D., & Kurtural, SK., (2023). Site characteristics determine the effectiveness of tillage and cover crops on the net ecosystem carbon balance in California vineyard agroecosystems. Frontiers in Plant Science, 13 https://doi.org/10.3389/fpls.2022.1024606

Authors


Maria Zumkeller

Affiliation : Department of Viticulture and Enology, University of California Davis 1 Shields Avenue Davis, CA 95616

Country : United States


Nazareth Torres

https://orcid.org/0000-0002-0597-4635

Affiliation : Department of Agronomy, Biotechnology and Food, Group of Advanced Viticulture and Fruticulture, Public University of Navarra, Campus de Arrosadia 31006 - Pamplona-Iruña

Country : Spain


Runze Yu

Affiliation : Department of Viticulture and Enology, California State University Fresno 2360 E Barstow Avenue Fresno, CA 93704

Country : United States


Lauren E. Marigliano

https://orcid.org/0000-0002-1441-6563

Affiliation : Department of Viticulture and Enology, University of California Davis 1 Shields Avenue Davis, CA

Country : United States


Daniele Zaccaria

Affiliation : Department of Land, Air and Water Resources, University of California Davis 1 Shields Avenue Davis, CA 95616

Country : United States


Justin D. Tanner

https://orcid.org/0000-0003-2434-6885

Affiliation : Department of Viticulture and Enology, University of California Davis 1 Shields Avenue Davis, CA 95616

Country : United States


Sahap Kaan Kurtural

skkurtural@ucdavis.edu

Affiliation : Department of Viticulture and Enology, University of California Davis 1 Shields Avenue Davis, CA 95616

Country : United States

Attachments

No supporting information for this article

Article statistics

Views: 3020

Downloads

XML: 17

Citations

PlumX