Using Nectar Cover Cropping in Vineyards for Sustainable Pest Management
Research investigating the use of cover crops in southern California vineyards for pest control has demonstrated that access to floral resources greatly increases natural enemy fitness, buckwheat is likely to be a better cover crop for use, cover crops may positively affect natural enemy numbers, irrigation required by the cover crop may lead to increased vine vigor and pest populations, cover crops may harbor pathogens (Xylella) which could be transmitted to vines by sharpshooters and cover crops may impact fruit yields and quality because of the additional irrigation needed to keep cover crops alive over summer.
- Determine if buckwheat flowers and cahaba vetch extrafloral nectaries increase longevity and fecundity of key natural enemies.
Determine when to sow cover crops to maximize nectar availability for natural enemies.
Determine if buckwheat and cahaba vetch, sown in alternate rows of grapes, enhances natural enemy populations and reduces pest populations below economic thresholds at study sites over a two year period.
Determine if buckwheat and cahaba vetch influence grape yield and quality.
Determine if buckwheat and cahaba vetch affect vine vigor.
Verify that buckwheat and cahaba vetch do not provide refuge for grape pathogens (e.g., Xylella) or pathogen vectors (e.g., sharpshooters).
Determine if buckwheat and vetch out compete and suppress unwanted weed species.
Determine the rate of dispersal of natural enemies from buckwheat and cahaba vetch plots.
Extend the information gained from this research to the Californian grape community through outreach and education.
Promote increased adoption of nectar cover cropping practices in Temecula, Lodi and Coachella Valley if research results merit application.
Laboratory trials were proposed to investigate if buckwheat flowers and cahaba vetch extrafloral nectaries increase longevity and fecundity of three natural enemies, G. ashmeadi (glassy-winged sharpshooter parasitoid), Anagrus epos (grape leafhopper parasitoid) and Anagyrus pseudococci (vine mealybug parasitoid). We have completed these studies for A. pseudococci and G. ashmeadi. Results showed that female A. pseudococci provided with vetch and buckwheat plants survived four and five days longer, respectively, compared with those females provided water only (Fig. 1). The total number of offspring produced by female A. pseudococci was up to four-fold higher when females were provided vetch and buckwheat compared with water only (Fig. 1). Similarly, providing G. ashmeadi with buckwheat and vetch plants enhanced G. ashmeadi longevity by nine and five days, respectively, compared with water only (Fig. 2). Offspring production was increased by up to 142% when female G. ashmeadi were provided buckwheat and vetch plants compared with water only. This suggests that vetch and buckwheat may be a suitable food source for A. pseudococci and G. ashmeadi for enhancing longevity and fecundity in the field when sown as a cover crop. Increased fitness because of access to floral resources could, in turn, enhance biological control of mealybugs through increased parasitism.
Trials with the leafhopper parasitoid, A. epos, have not been conducted. Efforts to establish A. epos and A. erythroneurae (variegated leafhopper parasitoid) colonies in 2008 were unsuccessful. In 2009, we were unable to attempt to establish Anagrus sp. colonies since labor was concentrated on insect monitoring and maintenance of the 2009 field trial and processing 2008 sticky traps. Efforts to establish A. epos and A. erythroneurae (variegated leafhopper parasitoid) colonies in spring 2010 were unsuccessful.
In June 2007, the cover crop phenology trial was set up at Ag. Ops., UCR. This trial involved sowing five buckwheat and vetch plots in the middle of each month for one year and every six weeks measuring plant height, the sowing to flowering times and length of the flowering period. Preliminary results showed that mean six week height varied with sowing date for both plant species, with shorter plants occurring during the winter months (Fig. 3). Such height information may be useful when selecting cover crops for crops that require an open canopy for prevention of moisture-loving diseases.
Fig. 4 shows that the number of days required from sowing to flowering for buckwheat was shorter during the warmer summer months of July-August. From April through to September it took buckwheat under 30 days from sowing to produce nectar-producing flowers. This information is important for growers intending to synchronize buckwheat nectar production to the phenology of natural enemies of key pests. Vetch took between 0.6-28 days longer each month to start producing nectar compared with buckwheat. This indicates that buckwheat may be a better cover crop for growers that require a quick growing plant that provides nutrition for natural enemies that are likely to contribute to the suppression of an identifiable pest problem. This is particularly important in the summer months (June-August) where buckwheat produced nectar 17-28 days faster than vetch. Conversely, once extrafloral nectaries were present on vetch plants, they produced nectar for up to 146 days longer than buckwheat flowers throughout the year (Fig. 5). There is a trade off here, speed to floral production vs. longevity of floral production. This result suggests that mixed species sowings may be useful to simultaneously take advantage of quick flowering species and those that have long flowering periods.
Consequently, information on days to nectar production and the length of nectar producing period can be used to construct guides to assist growers with cover crop sowing decisions. For example, Fig. 6 portrays a guide growers can use for strategizing buckwheat plantings. Growers could select a month along the x-axis where they require increased biological control for a particular pest problem, then the duration of flowering information could be used to determine which month the grower would need to sow buckwheat to maximize nectar production for natural enemies when the pest occurs.
In 2008 and 2009, a cover crop field study was set up at Bella Vista, Temecula aimed at investigating the effect of buckwheat and vetch cover crops on natural enemy and pest populations. Thirteen plots (28.7m x 2 rows and separated by at least 36 m) were selected in four blocks of Cabernet Sauvignon grapes around Bella Vista vineyard. One or two cover crop plots and control plots were randomly allocated per block, to total seven cover crop plots and six control plots for the entire study. For the 2008 field trial, vetch was randomly allocated the north or south side of each cover crop plot and seeds were sown in mid-February. In early-May, buckwheat was sown on the opposite side to vetch in each cover crop plot. Vetch did not establish, therefore, this side of the row was cultivated on June 11, 2008 and re-sown with buckwheat. Vetch proved to be a very poor competitor with common agricultural weeds, struggled to germinate and survive the warm spring conditions in southern California and was prone to high infestations of aphids, thrips, mites and other pests that severely impeded the growth of plants. Additionally, the only supplier of cahaba vetch seeds in the U.S. lost their entire crop to mildew fungal disease in 2009 and had no cahaba vetch seed in stock for our 2009 trials. Therefore, the 2009 cover crop trial utilized buckwheat only.
In both years, six plots maintained under current vineyard practices, which included cultivation between rows to remove unwanted weed vegetation, were used as controls. Sprinkler irrigation was installed on the existing grower’s grape irrigation in the cover crop plots. Buckwheat seed was re-sown in cover crop plots two to three times throughout the trial and each cover crop plot was irrigated for two hours the day after each sowing to ensure good germination, then approximately every seven to ten days. Additionally, irrigation was supplemented with 16 gallons of water per plot, applied via water sprayer and 4WD motorbike approximately three times a week.
Information on number of irrigation days and supplemental watering were recorded in order to estimate the amount of additional water required by the cover crop plots.
Despite all of these efforts, we encountered a number of problems with establishing and maintaining a cover crop during these trials. Four out of seven allocated cover crop plots were established in the 2008 field trial and no replicated plots of buckwheat were established in the 2009 field trial. Poor establishment of cover crops in 2009 was due to a batch of poor quality seed with a low germination rate (just 10-33% in greenhouse studies) that was brought from suppliers, irrigation issues (including sprinkler head blockages and flooding), birds eating seeds before they germinated, rabbits eating large patches of germinated seedlings, extreme summer temperatures killing seeds and seedlings and severe damage to cover crop plants from tractor and vineyard workers during routine vineyard maintenance.
Monitoring of insects using weekly transparent sticky traps and bi-weekly 30 second funnel beat samples were conducted between May through until August. Leafhopper visual counts and one minute sweep net samples were conducted every two weeks during June-August. In late-July 2009, it was apparent that establishment of buckwheat replicates was unattainable, therefore we ceased all insect monitoring and concentrated labor resources on identifying and counting insects from the 2008 sticky traps stored in the freezer. All sticky trap, funnel trap and visual counts data from the 2008 trial have been statistically analyzed and results are outlined below. Sweep net sample data is currently being analyzed and preliminary results are outlined below.
During the 2008 trial, four replicates of the cover crop treatment were established with buckwheat growing on one side of the cover crop plot. The other three allocated ‘cover crop plots’ had irrigation installed, but since buckwheat did not establish, these plots were reassigned as an ‘irrigated treatment’. Consequently, the three treatments for this study were: (1) buckwheat cover crop with irrigation; (2) irrigation with no buckwheat cover crop; and (3) a cultivated control with no buckwheat cover crop or irrigation. Including an ‘irrigated treatment’ will help determine whether effects of buckwheat cover crop on insect fauna, grape yield, fruit quality and vine vigor was due to the buckwheat cover crop or the irrigation required by the cover crop plants.
Details on insect monitoring:
Two sticky traps (16.7cm x 13.2cm clear Perspex sticky trap) mounted at a height of 1.45m were placed on the north and south side of the middle row of each plot, 3.7 m apart. Traps were collected and replaced weekly from June 10 through August 9, 2008. The number of pests and natural enemies were recorded separately for each side of the sticky trap to provide information on whether insects were flying towards or away from the grape canopy and buckwheat cover crop.
To obtain visual counts of leafhoppers and predators, a total of five leaves were visually examined per plot every two weeks between June 5 and August 2, 2008. Five vines on each of the north and south side were chosen at random in each cover crop and control plot. One first generation leaf (a large, mature leaf located three to four nodes up from the basal node of a cane) was examined with an OptiVisor per vine and numbers of variegated leafhoppers, grape leafhoppers, lacewing eggs and predators were recorded.
Funnel beat sampling was carried out every two weeks between June 7 and July 9, 2008. A funnel was constructed using PVC pipes with an overall opening dimension of 0.86m by 0.86m. The frame was fitted with a static-resistant polyester material which tapered into an attachment of two wash bottle lids. To conduct a funnel beat sample, the funnel was placed under a randomly selected vine near the middle of each plot and a 16oz wash bottle was screwed into the attachment point. Using a small mallet, the main branch of the vine was struck forcefully and repeatedly and foliage was agitated for 30 seconds. The sample was swept down from the funnel into the collection bottle, labeled and placed into a large cooler for transport to the laboratory. It was noted whether vines were wet from irrigation at time of sampling and later these data were removed from statistical analyses. The number of pests and natural enemies were counted for each sample.
A sweep net was used to sample buckwheat and grape foliage in buckwheat and control plots, respectively, every two weeks between June 19 and August 14, 2008. This was conducted by vigorously shaking foliage into a sweep net for one minute and placing contents in a labeled Ziplock bag. Bags were placed into a large cooler for transport to the laboratory. Samples were stored in 75% ethanol and the number of pests and natural enemies were counted for each sample.
Sticky trap statistical analyses:
Buckwheat only grew on one side of the cover crop plot, while sticky traps were deployed on both the north and south side of the row within the cover crop plot. Therefore, the sticky trap data in the cover crop plots was further reclassified as ‘buckwheat present in the plot but not in the row’ and ‘buckwheat present in both the plot and row’. Consequently, for this data set there were four post-hoc treatments: (1) control; (2) irrigation treatment; (3) irrigation and buckwheat present in the plot but not in the row; and (4) irrigation and buckwheat present in both the plot and row.
The experimental design for the sticky trap data was a Double-Split Plot design, and since there is no obvious model for simultaneously analyzing these data across time, the data was analyzed on a per time point basis. The ten sampling dates associated with sticky trap data were averaged into five distinct bi-weekly averages in order to simplify the statistical analyses and reduce Type I error rates associated with multiple testing. Insect counts were log transformed using ln (x+1) prior to performing statistical analyses and presented as means estimated by the model and back-transformed medians.
The sticky trap data were multivariate since 20 different insects were simultaneously tracked and analyzed at the same time. The complexity of this repeated measures experimental design precludes the use of standard multivariate tests and consequently, a Bonferroni correction technique was needed to address the problem of multiple comparisons. A p-value of 0.10 was used (instead of the traditional 0.05) to detect significant differences between treatments because the Bonferroni correction technique is particularly conservative and power is lost with multiple testing. To further minimize the impact of the Bonferroni correction, insect species were pooled into two major categories ‘Total Pests’ and ‘Total Beneficials’, and if significant differences occurred with the total models, further analyses were conducted on six specific groups of insects (Thrips, Leafhoppers, Other Pests, Parasitic and Predatory Wasps, Predatory Thrips and Other Beneficials). The following statistical model was independently fit to the transformed count data from each time period:
(unable to include in online report – please refer to printed report)
Where s, i, j and k equals side, treatment, plot and row, respectively, and the terms quantify the fixed treatment, row (north versus south side of the row within the plot) and trap side effects (open side versus foliage side of trap), respectively.
An initial screening was conducted to determine treatment effects on two variables, Total Pests and Total Beneficials, at each of five distinct time periods. In this case, a Bonferroni corrected significance level of 0.01 (p = 0.10/10) was used. If significant treatment effects existed in the Total Pests model for any time period, then Thrips, Leafhoppers and Other pests models were analyzed using a Bonferroni corrected significance level of 0.10/(3*p), where p equaled the number of time periods that these secondary models were assessed at. An identical approach was used for the Total Beneficials model, and if needed, the subsequent Parasitic and Predatory Wasps, Predatory Thrips and Other Beneficials models. The degrees of freedom associated with all of the test statistics of interest were adjusted using the Kenward-Roger adjustment method (Kenward and Roger, 1997) to control for the estimation uncertainty in the variance component coefficients. Tukey-Kramer at the 0.05 level of significance was used to separate means (Kramer, 1956).
Funnel beat data statistical analyses:
Funnel beat samples were collected over four dates from the middle of each buckwheat plot. Sample positioning was not row specific, therefore, for this data set there were three treatments: (1) control; (2) irrigation treatment; and (3) irrigation and buckwheat treatment. Data was analyzed using a classic one-way repeated measures model (Davis 2002). As previously indicated, all data associated with vines that were wet from irrigation during the time of sampling were removed from the analyses to avoid confounding a wet vine effect with the treatment effects. Insect counts were log transformed using ln (x+1) prior to performing statistical analyses.
The funnel beat data were multivariate since 18 different types of insects were simultaneously tracked and analyzed at the same time, therefore, a Bonferroni correction technique at the 0.01 level of significance was needed to address the problem of multiple comparisons. The following statistical model was fitted to the transformed count data:
(unable to include in online report – please refer to printed report)
An initial screening was conducted to determine treatment effects on two variables, Total Pests and Total Beneficials, where a Bonferroni corrected significance level of 0.05 (p = 0.10/2) was used. If significant treatment effects existed in the Total Pests model for any time period, then Thrips, Leafhoppers and Other Pests models were analyzed using a Bonferroni corrected significance level of 0.0333 (p = 0.10/3). An identical approach was used for the Total Beneficials model, and if needed, the subsequent Parasitic and Predatory Wasps, Predatory Thrips and Other Beneficials models. The degrees of freedom were adjusted using the Kenward-Roger adjustment method. Means comparison testing was not needed since none of the treatment or time x treatment interaction tests were found to be statistically significant.
Visual counts statistical analyses:
Visual counts were conducted on both the north and south side of the row within the cover crop plot. Therefore, for this data set there were four post-hoc treatments: (1) control; (2) irrigation treatment; (3) irrigation and buckwheat present in the plot, but not in the row; (4) irrigation and buckwheat present in both the plot and row. The five pseudo-replications (leaves) within each row were averaged into a single sample before performing statistical analyses. Additionally, the six sampling dates associated with the visual counts data were averaged into three distinct monthly dates (June, July and August) in order to simplify the statistical analyses and reduce Type I error rates associated with multiple testing. Total Leafhopper counts, Predatory insect counts and Lacewing Egg counts were log transformed using ln (x+1) prior to fitting a two-way (treatment and row) repeated measures model containing two variance components (a plot effect and a residual error term). The following primary model was used to test for time x treatment interaction:
(unable to include in online report – please refer to printed report)
An initial screening was conducted to determine whether there were significant treatment effects on Leafhopper, Predatory and Lacewing counts using a Bonferroni corrected significance level of 0.0333 (p = 0.10/3). When significant treatment effects existed, a time specific version of the classic two-factor variance components model was fitted to data in each time period (month) and resulting F score p-values did not require a Bonferroni correction. Tukey-Kramer at the 0.05 level of significance was used to separate means.
Results from sticky trap data:
There was no significant (p > 0.10) effect of treatment on total number of pests captured on sticky traps deployed at the beginning of the trial (between June 10 and August 5, 2008). For the last time period (August 12-19, 2008), treatment had significant effect on total pest counts (F = 5.70, p < 0.01). The estimated median pest count per trap side was significantly higher (72% higher) in irrigated plots compared to controls (non-irrigated plots) (Fig. 7). We speculate that these results may be due to the irrigation increasing vine vigor, which made these vines more attractive to leafhoppers. Mean cane weight was 63-69% higher for vines in the buckwheat and irrigated treatments compared with controls (see Objective 5 below; Fig. 16). When buckwheat was present in the plot but not the trap row, total pest counts were 74% higher than in control plots, however, this difference was not significant (Fig. 7). The number of total pests was equivalent between controls and plots with buckwheat present in the same row as the trap (Fig. 7).
The numbers of pestiferous leafhoppers and other pests captured on sticky traps showed similar trends to total pest numbers. Treatment effects were significant for the last time period (leafhoppers: F = 5.70, p < 0.01; other pests: F = 4.17, p < 0.01) where the estimated median leafhopper and other pests count per trap side was significantly higher (72% and 162% higher, respectively) in irrigated plots compared to controls (non-irrigated plots) and no further significant differences occurred between treatments (Fig. 7). Treatment had no significant effect on numbers of thrips captured on sticky traps deployed on all dates.
There was no significant effect of treatment on total number of beneficial insects captured on sticky traps deployed at the first three time periods (between June 10 and July 15, 2008). For the last two time periods, treatment had significant effect on total number of beneficials (time period 4: F = 5.34, p < 0.01; time period 5: F = 11.29, p < 0.001). For both of these time periods, the estimated median number of beneficials per trap side was significantly higher (146-183% higher) in irrigated plots compared to controls (Figs. 8 & 9). For the last time period (August 12–19, 2008), the number of beneficial insects were significantly higher (114% higher) in plots containing buckwheat near the trap (but not in the trap row), compared with control plots (Fig. 9). Additionally, the number of beneficial insects was equivalent between controls and plots with buckwheat present in the same row as the trap (Fig. 9). There were no other significant differences between treatments for both dates (Figs. 8 & 9).
The numbers of parasitic and predatory wasps captured on sticky traps showed similar trends to total numbers of beneficial insects. There was a significant effect of treatment on numbers of parasitic and predatory wasps for the last two time periods (time period 4: F = 5.33, p < 0.05; time period 5: F = 11.26, p < 0.001). For time period 4, median numbers of parasitic and predatory wasps were 146% higher in the irrigated treatment compared with controls (Fig. 8). No other significant differences existed between treatments for this time period. For time period 5, median numbers of parasitic and predatory wasps were 184% higher in the irrigated treatment compared with controls and 115% higher in plots containing buckwheat near the trap (but not in the trap row), compared with controls (Fig. 9). The number of parasitic and predatory wasps was statistical equivalent between controls and plots with buckwheat present in the same row as the trap (Fig. 9).
There was a significant effect of treatment on the number of predatory thrips captured on traps between July 8 and July 15, 2008 (the third time period) (F = 3.94, p < 0.01). Predatory thrip counts were significantly higher (162-186% higher) in plots containing buckwheat near the trap (but not in the trap row), compared with controls and the irrigated treatment (Fig. 10). There were no further significant differences between treatments for this time period and all remaining time periods. Additionally, treatment had no significant effect on numbers of other beneficial insects captured on sticky traps deployed on all dates.
In summary, results from the sticky trap data indicated that irrigated plots were attractive to leafhoppers and other pests and resulted in higher pest numbers compared to controls due to increased vine vigor. However, if irrigation was coupled with presence of a buckwheat cover crop, pest numbers were similar to controls. The combined effect of buckwheat and irrigation may have been partially due to increased levels of predatory thrips in the middle of the trial (time period 3), however, buckwheat failed to increase populations of parasitic and predatory wasps and other beneficial insects since numbers were equivalent between irrigated plots and plots containing irrigated buckwheat. The combined effect of buckwheat and irrigation, which canceled the negative effects of the irrigation on pest populations, may have been attributable to buckwheat plants supplying pollen and nectar to beneficial insects and subsequently increasing longevity and fecundity, leading to higher parasitism, predation and pest control. Our laboratory studies (see Objective 1 above) demonstrated the positive effect of buckwheat on longevity of beneficial insects and parasitism of grape pests. Alternatively, only four replicated buckwheat plots could be established for this study which may have increased difficulty of detecting significant differences between pest numbers in buckwheat plots and controls.
The placement of sticky traps on the north or south side of the vine row had no significant effect on total pest counts, leafhopper counts, numbers of thrips, other pests, total beneficial insects, parasitic and predatory wasps, predatory thrips and other beneficial insects counted on sticky traps from all deployment dates. The side of the trap had no significant effect on total pest counts, leafhopper counts, other pests, total beneficial insects, parasitic and predatory wasps and predatory thrips counted on sticky traps from all deployment dates. In contrast, numbers of thrips counted on traps deployed during the last four time periods (June 6 – August 19, 2008) was significantly higher (37% – 65% higher) on the ‘open’ side of the trap which was positioned furthest from the vine foliage compared with the ‘foliage’ side of the trap which was opposite the grape canopy (time period 2: F = 15.72, p < 0.001; time period 3: F = 16.47, p < 0.001; time period 4: F = 31.50, p < 0.001; time period 5: F = 50.88, p < 0.001). This indicates that populations of thrips were predominately immigrating into the grape canopy. There was no significant effect of trap side on number of thrips captured on sticky traps deployed during the first time period (June 10-17, 2008). Additionally, the numbers of other beneficial insects counted on traps deployed during time periods 2 (F = 17.26, p < 0.001) and 3 (F = 6.99, p < 0.01) were significantly higher (60-67% higher) on the ‘open’ side of the trap compared with the ‘foliage’ side. There was no significant effect of trap side on number of other beneficial insects captured on sticky traps deployed during the remaining time periods. These results indicate that populations of other beneficial insects and thrips were predominately immigrating into the grape canopy.
Results from funnel beat data:
Table 1 shows that time had a significant effect on numbers of total pests, leafhoppers, other pests and parasitic and predatory wasps captured in funnel trap samples conducted between June 17 and July 9, 2008, whereas, there was no date effect for the remaining insect groups. Total number of pests, leafhoppers, other pests and parasitic and predatory wasps significantly increased (by 382% – 8,977%) from June 17 until July 9, 2008 (Fig. 11). The treatment and interaction between time and treatment tests were not significantly different in any of the eight insect group models.
Results from visual counts data:
Table 2 shows the effect of time, treatment, time x treatment and row on numbers of leafhoppers, predators and lacewing eggs counted during visual leaf inspections. Time had a significant effect on all insect counts, with maximum numbers of leafhoppers occurring on August 7, 2008 and maximum predator counts occurring during August 2008 (Fig. 12). The maximum number of lacewing eggs present on grape leaves occurred during July and August 2008 (Fig. 12). There was a significant row effect only for lacewing counts, where the number of lacewing eggs was 63% higher on the south side (mean = 0.39 ± 0.04) of the row compared to the north side (mean = 0.24 ± 0.02) (Table 2). South sides of vines generally have higher sunshine hours and less protection from prevailing south westerly winds. Treatment and time x treatment had a significant effect for leafhopper and predator counts but not for numbers of lacewing eggs (Table 2). Re-analyzing data by time and treatment demonstrated that treatment had a significant effect on leafhopper and predatory counts in August (leafhopper: F = 5.23, p < 0.05; predator: F = 12.44, p < 0.001) but not for June and July. For August, the median number of leafhoppers counted on grape leaves was significantly higher (41-53% higher) in plots where buckwheat was present in the same row as the trap and in irrigated plots compared with controls (Fig. 13). Leafhopper counts were 43% higher in plots containing buckwheat near the trap (but not in the same row as the trap) compared with controls, although this result was not significant probably due to low replication making it difficult to detect significant differences between treatments. There was significantly higher numbers of predators in plots containing buckwheat near the trap compared with controls, while there were no other significant differences in predator counts between treatments (Fig. 13).
Results from sweep net sample data:
Results from the X. fastidiosa transmission studies demonstrated that buckwheat is a host of X. fastidiosa and that GWSS can successfully transmit X. fastidiosa from buckwheat to grapevines (see Objective 6 below). Therefore, data from sweep net samples conducted on flowering buckwheat plots are particularly important for determining the possible risk buckwheat might pose to being a source of X. fastidiosa in the vineyard. Sweep net sample data are currently being statistically analyzed. Preliminary data showed that GWSS counts were 3536% higher in grape foliage compared with flowering buckwheat plants (Fig. 14). That is, only one GWSS was captured during sweep netting of buckwheat flowers across all dates and replicates (16 plots), whereas, sweep netting grape foliage resulted in 50 GWSS (22 plots). These results indicate that while it is possible for GWSS to feed off buckwheat cover crops and transmit X. fasidiosa from infected buckwheat plants to grapevines, it may be unlikely that a buckwheat cover crop would act as a significant reservoir of X. fastidiosa in the vineyard since GWSS prefer feeding on grape foliage and high populations would not be found in buckwheat cover crops. Choice and no choice trials investigating GWSS feeding preferences between grape and buckwheat are required to aid further speculation.
The number of green stink bugs and ants were 733-11,356% higher in sweep net samples from buckwheat plants compared to grape foliage. Green stink bug preferably feed on developing seeds of plants which may explain why high numbers were present on flowering and seeding buckwheat plants, while ants are unknown to feed on nectar of flowering plants. The presence of ants in the vineyard may disrupt biological control of scales, meaybugs and aphids.
On September 18, 2008, the number of grape clusters present within a 3 m section of vine in the center of each plot was counted, and 10 clusters were harvested from each section and transported to the laboratory for grape yield and quality measurements. This data is currently being statistically analyzed. Preliminary results show that the mean weight per cluster was 26% and 39% higher for those harvested from buckwheat plots and the irrigated treatment, respectively, compared with controls (Fig. 15). There was no difference in number of clusters or number of berries per cluster between treatments (Fig. 15). Mean Brix content was 2.9 and 2.5 degrees higher in control plots compared with the buckwheat and irrigated treatments, respectively (Fig 15). This was probably attributable to the extra irrigation the buckwheat and irrigated treatments received which may have diluted sugars in the berries or caused excess vine vigor, thereby decreasing the amount of sunlight reaching the berries.
Berries from each of the 10 harvested clusters were removed and the number of ‘shriveled berries’ and berries damaged by feeding insects were counted. Additionally, 25 berries were randomly selected from each cluster and berry diameter was measured using calipers. The percentage of berries scarred through insect feeding damage and those stained with leafhopper excreta was calculated. Results showed that the number of berries that were shriveled due to dehydration was 450-452% higher in control plots compared with the buckwheat plots and irrigated treatment (Fig 15). This illustrates the effect of extra irrigation grapevines received at berry maturity in the buckwheat and irrigated plots. The number of berries with broken skin from insect damage was 1811% and 1358% higher in buckwheat plots compared with controls and the irrigated treatment (Fig. 15), suggesting that the nectar provided by the buckwheat plots may have attracted insects, such as bees and yellow jackets, which then fed on ripened berries. Bees and yellow jackets were observed feeding from berries in buckwheat plots during harvest. Berry size was equivalent for all treatments (Fig. 15). The percentage of scarred berries was 38% higher in buckwheat plots compared with controls (Fig. 15). Feeding by thrips adults and larvae can scar immature berries and scar damage becomes noticeable as berries mature. Aesthetic damage resulting from thrips feeding may not be important for wine grapes when compared with table grapes.
The influence of cover crops on vine vigor was investigated in October 2008 by measuring the weight of winter prunings from three randomly selected vines in the center of each treatment plot. For each vine, the number of canes growing from each arm was recorded. All canes were removed from the vine with clippers and any remaining leaves and secondary shoots growing from the primary cane removed. Canes from each vine were placed into Ziplock bags and labeled with treatment and replicate. The average weight per cane was calculated for each vine by weighing the contents of each bag and dividing the weight by the number of canes. This data is currently being statistically analyzed. Preliminary results are shown in Figure 16. Mean weight was 63% and 69% higher in the irrigated and buckwheat treatments, respectively, compared with the control plots. This difference can be attributed to the extra irrigation the vines received in the buckwheat and irrigated treatments.
Approximately twenty five buckwheat and vetch plants were needle inoculated in the laboratory with X. fastidiosa and tested with ELISA kits after four weeks to determine whether these plants could act as a host for X. fastidiosa, the causative agent of Pierce’s Disease (PD) in grapes. Results from the buckwheat needle inoculations showed that 63% and 53% of plants became infected with X. fastidiosa as detected by ELISA and culture tests, respectively (Table 3). This demonstrates that X. fastidiosa can successfully infect and replicate in buckwheat. Results from the vetch needle inoculations showed that 45% and 15% of plants became infected with X. fastidiosa as detected by ELISA and culture tests, respectively (Table 3). This demonstrates that X. fastidiosa can also successfully infect and replicate in vetch.
Since both plants tested positive to X. fastidiosa, further testing was conducted to determine whether GWSS could acquire X. fastidiosa from buckwheat or vetch and successfully transmit the pathogen to grape vines. If GWSS can transfer the pathogen from the cover crop plants to grapes, then cover crop plants may act as a potential reservoir of X. fastidiosa and be detrimental to grape growers. This is an important question that needs addressing. Consequently, the ability of GWSS to transmit X. fastidiosa from the cover crop to grapes, and then from grapes to the cover crop was investigated. For this work, forty GWSS (to allow for mortality) were released into cages containing cover crop plants infected with X. fastidiosa. Insects were left for a 48-hour feeding and acquisition period, then insects were collected and five GWSS were placed into a sleeve cage on each of five grape plants. The insects were left to feed for 48 hours, after which the insects were collected into individually labeled 1.5mL microcentrifuge tubes and frozen at -80?C for processing. Following the 48 hour feeding period, the grape test plants were grown in a greenhouse and tested for X. fastidiosa infection 8, 12 and 16 weeks post-feeding using ELISA and plate culturing techniques. Using the same protocols, GWSS transmission from cover crop to cover crop and grapevine to grapevine (controls) were tested. Preliminary results show that GWSS can transmit X. fastidiosa from buckwheat plants to buckwheat plants and from buckwheat plants to grapevines (Table 4). The grapevine to grapevine controls were also positive.
Greenhouse transmission results for vetch were inconclusive. Vetch plants grown in the greenhouse were susceptible to pest problems and were extremely difficult to keep alive long enough to allow adequate testing. Four cohorts of vetch plants were set up during two years of testing and only plants from the last cohort survived long enough for testing. Results from the ELISA testing showed that 40-50% of the vetch to vetch and vetch to grape tests were positive for X. fasidiosa transmission (Table 4). However, the culture technique resulted in 0% transmission from vetch to vetch and vetch to grape (Table 4), and this test is more reliable since it detects alive X. fasidiosa cells rather than ELISA testing which detects dead X. fasidiosa cells, sometimes resulting in false positives.
Additionally, the grape to grape controls resulted in no transmission (Table 4), which may indicate there was a problem with the GWSS used for this cohort. Given these issues with greenhouse testing, field transmission tests were conducted as outlined below.
Trials that investigated natural inoculation of buckwheat and vetch under field conditions were conducted at Agricultural Operations, UCR where X. fastidiosa is known to occur. Buckwheat and vetch was sown in the field in August 2008 and after three weeks, 10 buckwheat and 10 vetch plants were randomly selected and individually covered with acetate cages. Acetate cages were 12” tall and 4” in diameter with 2 x 4” ‘windows’ on opposites covered with nylon mesh organdy. The top was also covered with nylon mesh organdy. The seam of the acetate and the fabric were glued using a hot glue gun. Cages were secured in place over plants with a 3-foot long length of 1” diameter PVC pipe positioned in the ground directly east of the plant and the cage was placed over the plant and fastened to the PVC using a size 32 rubberband (114g or 0.25lb) to prevent the cage from being blown over by afternoon winds.
125 adult GWSS were collected from the field and placed in a bug dorm with a potted grapevine (variety Redglobe). The grapevine had been needle-inoculated and infected with Xylella fastidious subspecies fastidiosa (Temecula strain of PD). Insects were left to feed for a 48-hour acquisition access period (AAP). then live GWSS were aspirated into plastic 40-dram vials (5 per vial). One vial was placed into each cage for each plant. Four potted grapevine controls (non-infected) were placed beside the buckwheat and vetch plants and fitted with nylon organdy sleeve cages. One vial of GWSS was released onto each potted grapevine. All GWSS were given a 96-hour inoculation access period (IAP), after which, insects were collected and plants labeled. Grapevine controls were returned to the greenhouse.
Buckwheat plants started dying at two-three weeks post-IAP, so all plants were collected at three weeks post-IAP and tested for PD. Four plants were too dry for culture testing, so these were tested with ELISA only in case dead cells could be detected. The remaining six buckwheat plants were tested with ELISA and culture. The vetch plants were sampled at four-weeks post-IAP by collecting a small branch from the base of the plant. Lowest leaves from each branch of the grapevine controls were collected and the lowest 2cm of petiole tissue from each leaf was used. Results show that transmission from grapevine to buckwheat and grapevine to vetch were successful in the field (Table 5). It is interesting to note that 3/10 field grown vetch acquired X. fasidiosa by GWSS, but only 3/24 greenhouse grown vetch acquired X. fasidiosa by needle inoculation. This may indicate there is an unknown element of the insect-pathogen-plant interface that is required for successful transmission between GWSS and vetch, or that vetch is a poor host for X. fasidiosa.
The ability of buckwheat and vetch to outcompete weeds was not investigated in the 2008 field trial because vetch was such a poor competitor that plots needed to be weeded by hand to ensure establishment of vetch for the trial. Vetch is a winter cover crop and did not perform well in hot weather. This objective also could not be examined in the 2009 field trial because replicated buckwheat plots could not be established and vetch was not investigated in 2009 field trial (see Objective 3).
In July 2008, insects were triple marked with yellow fluorescent SARDI pigment and a 80% milk: 20% egg white mix by spraying plants with this mixture via a 2-stroke backpack sprayer. Marking insects in this manner by spraying the plants they are visiting and living on was intended to investigate the dispersal of natural enemies from cover crop plots into the vineyard. This dispersal information will help determine how many rows of cover crops growers would require for adequate dispersal of biological control agents from resource-providing plants. Control plots were untreated to investigate the natural gradient of unmarked insects captured on sticky traps and to investigate the efficiency of buffer zones used to separate treatments by determining whether protein-marked insects are detected in the controls. An additional six transparent sticky traps were placed on the 1st, 3rd, 6th and 10th row adjacent to the center of four replicates of each treatment, Cards were placed in each cardinal direction. Sticky traps were collected and replaced three and six days after marking to determine how long insects remained marked under prevailing field conditions. Sticky traps were scanned with a UV light to determine the presence of the yellow fluorescent pigment on beneficial insects. 314 pigment marked parasitoids (out of a total of 39,141 parasitoids) were removed from sticky traps across all treatments, replicates and sampling dates for ELISA analyses. In addition, a cohort of eight parasitoids per trap (totaling 2,349 parasitoids) that scored negative to the pigment mark were removed for ELISA testing. All pigment marked and unmarked spiders (four marked/total of 77), pirate bugs (3/70) and predatory thrips (5/343) were removed for ELISA testing. Insects were removed using a toothpick, placed into individual 1.5 ml microcentrifuge tubes, labeled and frozen. Samples were sent to James Hagler (USDA-ARS Phoenix Arizona) for ELISA testing to detect milk and egg proteins.
Statistical analyses are currently being conducted to compare the number of marked and unmarked beneficial insects between treatments, distances and dates. Data from this experiment will be used to determine: (1) how far marked beneficial insects disperse from cover crop refuges, (2) how many cover crop rows are required to assist natural enemy dispersal in vineyards, and (3) whether control plots contained marked insects from neighboring cover crop treatments (i.e., how efficient the 36 m buffer zones were).
Preliminary results suggest that cover cropping may not prove to be a viable option for grape growers in southern California due to the difficulty of establishing cover crops in southern California climate, cost of irrigation water and both cover crops testing positive for harboring Xylella. Additionally, results from sticky trap and visual counts data showed that additional irrigation required by the cover crop may lead to increased populations of pestiferous leafhoppers and other pests. Results from our study may not justify production of a chapter for Code of Sustainable Winegrowing Workbook, however, this project is making significant contributions to our understanding of the potential that cover crops offer when used as a pest management tool in vineyards in southern California by investigating the strengths and limitations of cover cropping under the unique growing conditions representative of grape producing areas of southern California. It is important to extend the results of our project to grape growers throughout California, especially since results demonstrate that cover crops may act as reservoirs of Xylella which can be transmitted to grapevines by GWSS. In January 2011, we will develop a website on cover crops for southern California growers outlining the results of our research and listing the pros and cons of cover cropping in arid southern California. Results to date will be included in the January 2011 newsletter issued to Coachella Valley Grape Growers via Carmen Gisbert [UC Cooperative Extension Specialist, Coachella Valley]. We will summarize our research for incorporation into UCIPM Pest Management Guidelines (Joyce Strand, Associated Director for Communications, UCIPM), a key resource for grape growers and pest control advisors and present results at upcoming grower meetings including Coachella Valley and Temecula Valley (Carmen Gispert; February 2011), Napa County (Monica Cooper; May 2011) and other meetings currently being negotiated in Kern County (Jennifer Hashim-Buckey), Mendocino County (Glenn McGourty), Sonoma County (Rhonda Smith) and San Luis Obispo County (Mark Battany). Results will also be presented at applicable Chapters of the California Association of Pest Control Advisors (CAPCA) including the Southern California Chapter (Cathy Ellis, President of the Southern California Chapter). Additionally, we will publish results from this project in two manuscripts submitted to leading journals and write a report outlining the results of this research for distribution to leading grower advisers and UC extension specialists who supported this project (Carmen Gisbert [UC Cooperative Extension Specialist, Coachella Valley], Ben Drake [PCA, Temecula Valley], Nick Toscano [Extension Specialist & Area-Wide GWSS Management Team, Temecula Valley], Cliff Ohmart [IPM Director, Lodi Woodbridge Winegrape Commission; now works at SureHarvest], Peggy Evans [Executive Director, Temecula Winegrowers Association] and Phil Phillips [UC Cooperative Extension Specialist, Ventura County]. This projects end date is May 31, 2011.
During the 2008 study, the seven designated cover crop plots were irrigated via sprinkler irrigation installed on existing grape irrigation, plus supplemental watering up to three times a week using a 16 gallon water sprayer. Sprinklers were rated at two gallons per hour, and five sprinklers were installed each side of the 60 m2 plot (which encompassed two rows). On grape irrigation days, sprinklers irrigated for six hours emitting 60 gallons per side of the plot. Sprinkler and supplemental watering days were recorded and the number of gallons of water each plot received was calculated per month. One 30 m2 side of each plot received 128-300 gallons of water each month (Table 6) and by May 2008 both sides of the 60 m2 plot were watered. The estimated total number of gallons the seven irrigated plots used during the trial was 19,204 gallons (Table 6). The monthly cost of the water used by our trial was calculated using Bella Vista vineyard water bills obtained from Rancho California Water Board (Table 6). Cost of Bella Vista water was 0.0014 cents per gallon, amounting to $28.44 cents for the entire trial.
Additionally, the Rancho California Water Board allocates monthly water restrictions and charges considerable penalties for exceeding these water allocations. During June-September 2008, Bella Vista winery was charged a total of $6,813 for exceeding monthly water allocations (Table 6). In 2007 and 2009, there were no penalties charged during these months. It may be unlikely that the water requirements of our trial caused the 2008 penalties since water usage by our trial only amounted to 0.2% of Bella Vista’s water consumption during March–August. However, our trial consisted of small 60 m2 plots, whereas, vineyard growers would likely sow cover crops down the entire row, spacing cover crop refuges every 6-10 rows (depending on results from Objective 8). This would considerably increase water usage and cost of cover cropping. To illustrate this, water usage and cost of water required to maintain cover cropping throughout Bella Vista vineyard (40 acres of grapes), using only sprinkler irrigation installed on existing vineyard irrigation (no supplemental watering). This was calculated based on two strategies: (1) sowing cover crop one row in every six; (2) sowing cover crop one row in every 10. Results showed that for strategy (1), water usage was 443,997 gallons, costing $630 (Table 6). This water usage would amount to 3.8% of Bella Vista’s water consumption during March-August which may result in water allocation penalties. For strategy (2), water usage was 265,433 gallons, costing $377 (Table 6). This water usage would amount to 2.3% of Bella Vista’s water consumption during March-August. These estimated costs are for water only and does not include cost of seed and labor for cultivating soil and drilling seed.
- (Fig. 1) Mean longevity and total offspring produced when female A. pseudococci were provided with one potted vetch plant, buckwheat plant or water only in the laboratory.
- (Fig. 4) The mean number of days that a) buckwheat and b) vetch took to produce nectar producing flowers or extrafloral nectaries, respectively, when sown in the middle of each month from June 2007 until May 2008.
- (Fig. 5) The mean number of days buckwheat and vetch produced nectar via flowers or extrafloral nectaries, respectively, when sown in the middle of each month from June 2007 until May 2008.
- (Fig. 6) Days to flowering and length of flowering period for a buckwheat cover crop sown in the middle of each month from June 2007 until May 2008.
- (Fig. 7) Estimated mean (± SEM) number of pestiferous insects counted on sticky traps deployed in four treatments in a vineyard during August 12th, 2008 and August 26th, 2008 (time period 5) (BW = buckwheat; bars contains back-transformed median counts per trap side; different letters indicate signficant differences [p < 0.10] between treatments).
- (Fig. 8) Estimated mean (± SEM) number of beneficial insects and parasitic and predatory wasps counted on sticky traps deployed in four treatments in a vineyard during July 29th, 2008 and August 12th, 2008 (time period 4) (see Fig. 7).
- (Fig. 9) Estimated mean (± SEM) number of beneficial insects and parasitic and predatory wasps counted on sticky traps deployed in four treatments in a vineyard during August 12th, 2008 and August 26th, 2008 (time period 5) (see Fig. 7).
- (Table 2) F scores and p-values for a two-way repeated measures model analyzing row, time, treatment and time x treatment interaction effects on the number of different insect groups (transformed counts) counted during visual inspections of grape leaves between June 19th, 2008 and August 14th, 2008.
- (Fig. 11) Mean (± SEM) number of four groups of insects captured in funnel trap samples during June 17th, 2008 and July 29th, 2008.
- (Table 3) ELISA and culture test results for needle-inoculated plants
- (Table 4) ELISA and culture test results for greenhouse insect transmission experiment involving placing GWSS on needle-inoculated host for acquisition.
- (Fig. 10) Estimated mean (± SEM) number of predatory thrips counted on sticky traps deployed in four treatments in a vineyard during July 8th, 2008 and July 22nd, 2008 (time period 3) (see Fig. 7).
- (Fig. 13) Estimated mean (± SEM) number of leafhoppers and predatorys counted during visual inspections of grape leaves in four treatments in a vineyard during August 2008 (BW = buckwheat; bars contains back-transformed median counts per leaf; different letters indicate signficant differences [p < 0.10] between treatments).
- (Table 6) Water usage and cost of water per month during an irrigated cover cropping trial conducted at Bella Vista vineyard in 2008.
- (Fig. 3) The mean six week height of a) buckwheat and b) vetch plants sown in the middle of each month from June 2007 until May 2008.
- (Fig. 12) Mean (± SEM) number of leafhoppers, predators and lacewing eggs counted during visual inspection of 10 leaves per experimental plot every two weeks from June 6th through August 21st, 2008.
- (Fig. 16) Mean cane weight per vine when canes were removed in October 2008 from three vines located in each treatment.
- (Fig. 2) Mean longevity and total offspring produced when female G. ashmeadi were provided with one potted vetch plant, buckwheat plant or water only in the laboratory.
- (Table 1) F scores and p-values for one-way repeated measures model analyzing time, treatment and interaction effects on the number of different insect groups (transformed counts) captured in funnel trap samples conducted between June 17th, 2008 and July 9th, 2008 (significant p-values are in bold).
- (Fig. 14) Numbers of insects captured during 1 min sweep net samples on flowering buckwheat plants and grape foliage (control).
- (Fig. 15) Grape yield and quality measurements for 10 clusters harvested from each treatment plot on September 18th, 2008.
- (Table 5) ELISA and culture test results for field transmission experiment.
Impacts and Contributions/Outcomes
Work completed and reported here is the first significant set of studies that have investigated the strengths and limitations of cover cropping under the unique growing conditions representative of grape producing areas of southern California. Consequently, this project is making significant contributions to our understanding of the potential that cover crops offer when used as a pest management tool in vineyards in southern California. The contributions this work had delivered here in this progress report are:
- Identification of cover crop species that can be used in southern California including: (A) Growth time required to flowering and duration of flowering and how this host plant phenology can be manipulated and used by growers during different times of the year; (B) Improved understanding of how cover crops influence pest and natural enemy abundances; (C) Identification of the risk cover crops pose in relation to harboring Xylella and insects that vector this pathogen; and (D) Quantification of the effects cover crops have on grape yield, fruit quality and vine vigor.
The economic and practical feasibility of cover crops for pest control in vineyards in southern California will be quantified. This is particularly important with respect to water usage. The amount of water applied to cover crop plots was recorded during each year’s field trial, and the grower’s water bills are currently being used to calculate the cost of irrigating the cover crop.
- Finish constructing guides based on days to nectar production and the length of nectar producing period to assist growers with cover crop sowing decisions.
Finish statistical analyses for each objective.
Write information for incorporation in the Code of Sustainable Winegrowing Workbook.
Develop a website on cover crops for southern California growers outlining the results of our research and listing the pros and cons of cover cropping in arid southern California.
Summarize our research for incorporation into UC IPM Pest Management Guidelines
Present results at upcoming grape grower meetings throughout California.
Write two manuscripts for submission to leading journals.
Write a report outlining the results of this research for distribution to leading grower advisers and UC extension specialists who supported this project.
Lodi Woodbridge Winegrape Commission
2545 West Turner Road
Lodi, CA 95242
Office Phone: 2093674727
Viticulture/Pest Management Advisor
University of California
82-675 Highway 111
Indio, CA 92201
Office Phone: 7608638294
Professor of Entomology & Entomologist
University of California
3401 Watkins Drive
Riverside, CA 92521
Office Phone: 9518274562
Director of Integrated Plant Protection Centre
Oregon State University
2701 SW Campus Way
Corvallis, OR 97331
Office Phone: 5417379082
Owner and Manager of Bella Vista
41220 Calle Contento
Temecula, CA 92592
Office Phone: 9516765250
Sun World International
52-200 Industrial Way
Coachella, CA 92236
Office Phone: 6613925002
University of California
3401 Watkins Drive
Riverside, CA 92521
Office Phone: 9518275826