Survey of Soilborne Pathogens Infecting Strawberry in Santa Maria, California

ABSTRACT To determine the prevalence of the four major soilborne pathogens of strawberry in the Santa Maria growing district in California, symptomatic plant samples (n = 100) were collected from 68 fields between May and September 2022. Samples comprised 28.3% of 2021 fall-planted strawberry fields and 14.0% of 2022 summer-planted strawberry fields in the district. Recombinase polymerase amplification was used to detect Macrophomina phaseolina, Fusarium oxysporum f. sp. fragariae, Verticillium dahliae, and Phytophthora spp. in plant crown material. Macrophomina phaseolina was most prevalent, detected in 52 samples, followed by Verticillium dahliae in 17 samples, F. oxysporum f. sp. fragariae in 16 samples, and Phytophthora spp. in 14 samples. Macrophomina phaseolina was more likely in eastern field locations (P = .0159) and in instances where strawberries were planted consecutively (P = .0100). Disease incidence was more likely to be higher in samples from organic fields than conventional fields (P = .0304) and in samples from flat-fumigated fields than fields fumigated in-line (P = .0124).


Introduction
The California strawberry industry is valued at 3.4 billion dollars (USDA-NASS, 2022) but faces the growing challenge of diseases caused by soilborne pathogens.Verticillium wilt (caused by Verticillium dahliae) and Phytophthora crown and root rot (caused by Phytophthora spp.) have been present in California strawberry since before the phaseout of the soil fumigant methyl bromide (Martínez et al., 2010;Wilhelm et al., 1961).After the transition to alternative fumigants between 2005 and 2016, Macrophomina root rot (caused by Macrophomina phaseolina) and Fusarium wilt (caused by Fusarium oxysporum f. sp.fragariae) became prevalent (Koike, 2008;Koike et al., 2009).The current prevalence of these four pathogens in the California strawberry industry is unknown, which prompted a survey in which 34% of strawberry fields in the Watsonville-Salinas district of California were sampled during the 2021 growing season and tested for these pathogens (Steele et al., 2023).Sampling of diseased plants in the Santa Maria growing district was critical in determining the relative prevalence of these pathogens in California and provides a reference point for the development of disease management tools.
Unlike in the Watsonville-Salinas area, the Santa Maria and Oxnard districts plant strawberries in both fall and summer.Most California strawberry fields are planted in the fall and are harvested beginning in winter or early spring (McKee and Miljkovic, 2007).The improved market during late summer and fall months has attracted growers to plant in late spring and early summer to enable an additional harvest as early as September.Since this survey occurred from May to September 2022, both fall-and summer-planted fields in Santa Maria were sampled.The primary objective of this survey was to determine the relative prevalence of the four major soilborne pathogens in the Santa Maria growing district.Secondarily, relationships between growing practices -GPS coordinates, number of drip lines per bed, whether a field was conventional or organic, previous crop, and soil type -and each of the four pathogens were assessed.

Materials and Methods
Strawberry (Fragaria × ananassa Duch.) production fields experiencing plant mortality were sampled in the Santa Maria growing district approximately weekly between 25 May and 30 September 2022.A total of 100 plant samples were collected from 68 fields.In some fields, there were multiple cultivars or distinct growing practices that were sampled separately.Sampling during these months captured newly established summer-planted fields as well as fall-planted fields toward the end of their harvest season, when disease pressure is often highest.With the objective of sampling from as many diseased fields as possible, both fall-and summer-planted fields were sampled.Sampled fields were primarily determined through correspondence with growers, ranch managers, and pest control advisors who had identified symptomatic plants in their field(s).Of the 100 total samples, 72 (from 45 fields) were from fall plantings and 28 (from 23 fields) were from summer plantings (Figure 1), and 17 different cultivars were sampled (Table 1).The 45 fall-planted fields represent 28.3% of the 2021 fall-planted acreage in the Santa Maria growing district.The 23 summer-planted fields represent 14.0% of the 2022 summer-planted acreage.
Each sample was composed of eight strawberry plants showing symptoms of a root disease (i.e., stunting and foliar necrosis) collected from different locations within the most affected area of a field.Disease incidence in sampled areas of fields ranged from 0.0% to 75.3% and averaged 11.0%.Disease incidence for each sampled field was calculated from counts of plants that were at least 50% necrotic from two separate beds that averaged 93 linear bed m.
Disease diagnostics were performed at the Cal Poly Strawberry Center Pathology Lab in San Luis Obispo, CA.Diagnostics for the four major pathogens were conducted using recombinase polymerase amplification (RPA).For RPA diagnostics, DNA was extracted from eight, approximately 0.5 cm 3 pieces of necrotic crown tissue from each sample, consisting of one necrotic crown piece per plant.This ensured each strawberry plant was represented in the extraction.Because of this total extraction weight ranged from 0.6 g to 2.8 g per sample, averaging 1.4 g.RPA was then conducted for each of the four pathogens, with two technical replicates per DNA extraction, using TwistAmp exo kit and probes (TwistDx Limited, Maidenhead, UK) and the Axxin T-16 ISO RPA machine (Axxin, Fairfield, Australia).Previously developed protocols were employed for V. dahliae (Martin, F., unpublished, based on previously published primers from Bilodeau et al., 2012), M. phaseolina (Burkhardt et al., 2018), F. oxysporum f. sp.fragariae (Burkhardt et al., 2019), and Phytophthora spp (Miles et al., 2015).Cox primers and probe (Miles et al., 2015) were added to each reaction as internal controls.A negative control reaction was also included for each set of samples and was identical to sample reactions but with 2 µL of nuclease-free water rather than sample DNA.If at least one of these two RPA technical replicates was positive for a pathogen and the positive and negative control reactions amplified, indicating the DNA extraction was successful, the sample was regarded as positive for that pathogen.
If both technical replicates of RPA were negative for all four pathogens in a given sample, additional excised plant tissue from that sample was plated on half-strength acidified potato dextrose agar as a general purpose medium, Sorensen's NP-10 (Sorensen et al., 1991) for V. dahliae and M. phaseolina, and PARP (pimaricin + ampicillin + rifampicin + pentachloronitrobenzene [PCNB] agar; Kannwischer & Mitchell, 1978) for Phytophthora and Pythium spp.Complete plating methods can be found in Steele et al. (2023).
A soil sample was collected along with each plant sample, comprised of approximately 60 mL of soil pooled from the root zone of the eight collected plants.If plating an RPA-negative sample did not yield a culture of any known primary strawberry pathogens, electrical conductivity (EC) values were determined for soil collected along with that sample using the Traceable Conductivity/Total Dissolved Solids Meter (Fisher Scientific, Hampton, NH, USA).EC was determined for these samples as a basic measure of possible abiotic stress.
To determine if there were relationships between growing practices and pathogen detection, additional field information was collected: GPS coordinates, number of drip lines per bed, whether a field was conventional or organic, previous crop, and soil type as determined from SoilWeb (California Soil Resource Lab, UC Davis/UC-ANR/USDA NRCS, https://casoilresource.lawr.ucdavis.edu/gmap/).Correlations between these five field variables and the presence of the four pathogens were assessed in a multivariate model using nominal logistic regression.Correlations between the five field variables and disease incidence were assessed using standard least squares with effect leverage emphasis.The distribution of disease incidence was not normally distributed and was transformed using natural logarithm for analysis.The effect of fumigation type (in-line or flat) in conventional samples was assessed with a univariate model due to limited sample size (JMP Version 16 statistical software; SAS Institute Inc., Cary, NC).In-line fumigation involves applying a pre-plant soil fumigant after bed shaping via the drip irrigation system.Flat, or broadcast, fumigation is employed before bed shaping using shank injection of fumigant into the entire field followed by laying impermeable film to trap the fumigant in the soil.

Results
Macrophomina phaseolina was the most prevalent pathogen detected in diseased plants in the Santa Maria growing district in 2022, present in 52.0% of samples.The other three pathogens followed at lower prevalence (Figure 2).Within the most sampled cultivar Monterey (n = 42), 50.0%were positive for M. phaseolina, 7.1% were positive for V. dahliae, 23.8% were positive for F. oxysporum f. sp.fragariae race 1, and 9.5% were positive for Phytophthora spp.Verticillium dahliae was more common in summer-than fall-planted strawberry samples, and M. phaseolina was more common in samples from the east side of the Santa Maria district (east of Highway 101) than the west side (Figure 3).Of the 100 samples, 61 were positive for one of the four pathogens, 15 were positive for two pathogens, and three were positive for three pathogens.There were 20 total instances of pathogen co-occurrence, with Phytophthora spp.and M. phaseolina occurring together most often (Table 2).
Unexpectedly, root-knot nematode (RKN; Meloidogyne spp.) was detected in six samples from four different fields.Upon noting root galls during plant collection or processing, root microscopy and extractions from rhizosphere soil were performed to confirm the presence of Meloidogyne sp.Soil extractions from four of the six RKN-positive samples were sequenced at the California Department of Food and Agriculture Plant Pest Diagnostics Center and were identified as M. hapla with a protocol  Subbotin (2020).Of the six samples positive for RKN, three were also positive for F. oxysporum f. sp.fragariae, two were also positive for M. phaseolina, and one was also positive for Phytophthora sp.There were 21 samples negative for all four major pathogens through RPA and plating; the average disease incidence in these fields was 3.8%.Upon plating these 21 samples, six yielded Pythium sp., two yielded Rhizoctonia sp., and one yielded a culture identified as Truncatella angustata through ITS sequence analysis.Five had soil EC values regarded as slightly saline (1.2 dS m −1 to 2.5 dS cm −1 ) for   their respective soil types.This left seven samples in which no known primary pathogens to strawberry were detected and soil was non-saline.
In a multivariate model assessing presence of M. phaseolina against field variables described above, M. phaseolina was more likely as field longitude decreased, meaning a more eastern field location (P = .0159).Macrophomina phaseolina was 4.2 times more likely in samples from fields where strawberries were planted consecutively than where another crop preceded strawberry (P = .0100).There were no significant model effects when assessing field variables with V. dahliae, F. oxysporum f. sp.fragariae race 1, or Phytophthora spp., nor with assessing field variable effects on whether a sample was positive for at least one of the four pathogens.
In a multivariate model assessing field variables against disease incidence, incidence was more likely to be higher in samples from loam soil (predicted at 10.8%) than sandy soil (predicted at 4.0%; P = .0015).Incidence was also more likely to be higher in samples from organic fields (predicted at 9.8%) than conventional fields (predicted at 4.5%; P = .0304).Multivariate model outcomes are summarized in Table 3.In a univariate model assessing disease incidence across bed-and flat-fumigated fields, incidence was more likely to be higher in samples from flat-fumigated fields (predicted at 14.9%) than in-line fumigated fields (predicted at 4.1%; P = .0124).

Discussion
Macrophomina phaseolina was by far the most prevalent soilborne pathogen in the Santa Maria district, detected in 52.0% of sampled fields, signaling the need for extra attention to this pathogen.Survival of microsclerotia is key to persistence of this pathogen in the soil without a host for up to 15 years (Gupta et al., 2012) and may contribute to its high prevalence in the district and limit the ability of crop rotation in infested sites to mitigate disease.Soil moisture, temperature and relative humidity are the most important factors for M. phaseolina disease initiation and development (Pandey and Basandrai, 2021).The optimal growth temperature of M. phaseolina isolates from various crops including strawberry is between 25°C and 35°C in vitro; isolates still grow well at 20°C and growth is very slow at 15°C (Viejobueno et al., 2022).Average air temperature between 2022 June and 2022 September at the Santa Maria II CIMIS station was 17.4°C, while at the Salinas CIMIS station between 2021 August and 2021 November, when the Watsonville-Salinas survey (Steele et al., 2023) took place, it was 15.1°C (California Irrigation Management Information System, 2023).The higher average temperature in Santa Maria compared to Salinas may partially explain the prevalence of M. phaseolina in Santa Maria (52.0%) compared to Watsonville-Salinas (29.7%).In Watsonville-Salinas, prevalence of the four pathogens was more even as all were between 22.0% and 31.1% (Steele et al., 2023).
A pooled t-test showed that the average distance from the Pacific Ocean of sampling locations was significantly lower in the Watsonville-Salinas survey (12.1 km) than in Santa Maria (17.1 km) (P < .0001).Samples coming from generally more inland locations experiencing higher temperatures in Santa Maria may also explain the higher prevalence of M. phaseolina in the district.This is further supported as within the Santa Maria district, M. phaseolina detection was higher among east Santa Maria samples (73.3%) than west (50.0%) and statistically more likely as longitude of field location decreased (more eastern; P = .0159).If concerned about Macrophomina root rot, growers may opt for more coastal field sites when possible to potentially mitigate disease pressure, especially with higher temperatures during the growing season.
Fewer drip irrigation lines per strawberry plant row in Santa Maria may also contribute to the higher M. phaseolina prevalence.In Watsonville-Salinas, strawberry beds with two rows of strawberry plants and two drip irrigation lines per bed are considered standard practice (Hoffmann et al., 2020;Subbarao et al., 2007).In the Santa Maria survey, three (11.0%)or more commonly four (89.0%) rows of plants and two (26.0%) or three (76.0%)drip lines were utilized.As a result, Watsonville-Salinas employs a 2:2 plant row to drip line ratio, while in Santa Maria this varies from 4:2 (21.0%), to 3:2 (5.0%), to 4:3 (68.0%), and 3:3 (6.0%).Macrophomina phaseolina microsclerotia populations have been shown to decrease in high soil moisture conditions, possibly due to parasitization by soil bacteria and abnormal microsclerotia germination (Dhingra and Sinclair, 1975).Lower moisture distribution from drip lines to strawberry plants in Santa Maria may result in drier soil around strawberry plants and higher water stress.Employing a lower plant row to drip line ratio when possible may mitigate disease pressure due to M. phaseolina.This has been preliminarily supported in a field trial at the Cal Poly Strawberry Center (K.Blauer, personal communication) and is supported by studies in other host crops (Rai et al., 2022) but requires further research in strawberries.At sites with a history of Macrophomina root rot, growers may choose to use a higher ratio of drip irrigation lines to plant rows to limit disease pressure.
Only a limited number of options are available for the growers during the season upon discovery of soilborne pathogens.However, prior to the next season's planting, growers can choose management practices according to the diseases that were found in their field based on their cropping practices (conventional or organic) such as selecting resistant cultivars, crop rotation, anaerobic soil disinfestation, or pre-plant soil fumigation.
A dominant resistance gene to Fusarium wilt of strawberry (FW1) was identified in several cultivars grown in California production (Pincot et al., 2018; Table 1).Fusarium oxysporum f. sp.fragariae (Fof) isolates of varying countries of origin have been identified that either can (race 2) or cannot (race 1) cause disease on FW1-resistant cultivars (Henry et al., 2021).In this survey, there were three samples in which an FW1-resistant cultivar yielded no major pathogen through RPA or plating.Cases like these are of interest to race 2 research as the RPA method for Fof employed here does not detect Fof race 2 (P.Henry, personal communication).Identification and sequencing of Fusarium spp.cultures isolated from samples like these would be prudent in future diagnostics as the emergence of Fof race 2 in California strawberry has recently been observed (Dilla-Ermita et al., 2023).However, for fields infested with Fof race 1, FW1 cultivars remain a useful management strategy.
None of the cultivars sampled here are resistant to disease caused by any of the other three pathogens (M.phaseolina, V. dahliae, and Phytophthora spp.) and breeding efforts for resistance to those diseases are ongoing.Some cultivars have been deemed "moderately resistant" to one or more of the three other diseases, but such designations were not emphasized here because the genetics of resistance has been more complex than that of FW1, i.e., polygenic (Pincot et al., 2020).Pathogens to which cultivars are moderately resistant have been detected in such cultivars, both in the Watsonville-Salinas survey (Steele et al., 2023) and here.Because of the high prevalence of M. phaseolina in Santa Maria, strawberry growers may weigh more heavily the partial resistance to Macrophomina root rot that is available in cultivar selection.Strawberry breeding programs have made resistance to Macrophomina root rot a priority, and this survey emphasizes the need for such cultivars.
Analysis of associations between field variables and pathogen prevalence demonstrated that M. phaseolina was 4.2 times more likely in samples from fields where strawberries are planted consecutively than where another crop preceded strawberries (P = .0100).In the Santa Maria region, crops utilized in rotation (i.e., lettuce, broccoli, cauliflower, Brussels sprouts, celery, and carrots) do not experience an economically important impact from M. phaseolina.Crop rotation also diversifies the soil microbiome (Yang et al., 2020) while planting strawberry consecutively where M. phaseolina microsclerotia are already present in the soil or in strawberry crown material increases inoculum levels.
Although no significant relationships were found between any of the four pathogens and soil or fumigation type, the authors advise evaluating such relationships in future surveys with different cropping and pathogen systems.Higher predicted disease incidence in flat-fumigated fields than fields fumigated in-line was unexpected (Gordon et al., 2016).The univariate model that yielded this result is limited by flat-fumigated sample size (flat-fumigated: n = 9; fumigated in-line: n = 56) and confounding variables may be at play.For example, growers experiencing higher disease pressure may be more likely to employ flat fumigation before planting the following year than those choosing to employ inline fumigation.
Root-knot nematode (Meloidogyne sp.) was not expected as a soilborne pathogen of strawberry in this region and was therefore not a target for diagnostics in this survey.The four fields (six samples) that yielded RKN are spread throughout the Santa Maria district rather than clustered.Meloidogyne spp.are known to cause disease in a wide range of crops including strawberry.The northern root-knot nematode, M. hapla, is an important pest of strawberry in the northeastern U.S. (LaMondia, 2002) and has been the Meloidogyne sp.most frequently associated with strawberry in California (Westerdahl, 2009).Aboveground symptoms of RKN infection in strawberry include wilting, stunting, chlorosis, and reduced flower and fruit production (Westerdahl, 2009).Inconspicuous root knots, or galls, are the most unique symptom as stunting and wilting are caused by other soilborne pathogens as well.When field sampling for root-knot nematode, plants should be taken from different areas of the field as nematodes have patchy distribution (Desaeger, 2018).California strawberry growers, especially those that rotate with vegetables such as lettuce and carrots (Vestergård, 2019), forage and seed legumes, tubers, or grasses should be aware of the risk for RKN infestation as these crops are also hosts (Desaeger, 2018).Growers employing an FW1 cultivar should be especially vigilant as M. hapla has been shown to affect resistance mechanisms to Fusarium spp. in other commodities such as chrysanthemum, cotton, squash, and alfalfa (Caperton et al., 1986;Griffin and Thyr, 1988;Johnson and Littrell, 1969;Yang et al., 1976).
Strawberry is one of the most sensitive horticultural crops to soil salinity.In this survey, soil EC was evaluated for samples in which no primary strawberry pathogens were detected through RPA or plating.Of those 12 samples tested for soil EC, five were slightly saline (1.2 dS m −1 to 2.5 dS m −1 ).The average disease incidence for these samples was 2.8%.Irrigated water with an EC of 1.0 dS m −1 was enough to cause 3% plant mortality in "Monterey", and 1.5 dS m −1 caused 20% plant mortality (Ferreira et al., 2019).However, this effect is highly variable with cultivar, as no plant mortality was seen in "San Andreas" at irrigation water of 1.0 dS m −1 in the same study.Salinity should not be ruled out as a primary cause of strawberry plant death, especially at lower disease incidence, and at least significant yield loss.It is important to note that concentrations of different ions result in different outcomes for plant physiology and survival.EC is a general measurement of all ions present and changes with soil water content, porosity, texture, and organic matter (Doerge et al., 1999).Although measuring specific ion concentrations in the soil was not within the scope of this project, it is advisable especially in fields in which symptomatic plants are observed without detection of a major soilborne pathogen.
Only one of the 400 pairs of technical RPA replicates had differing results.None of the four major pathogens were isolated through plating, meaning there were no discrepancies between RPA and plating results.Identical plating methods were utilized in the 2021 Watsonville-Salinas survey (Steele et al., 2023), but in that survey, there were six instances in which a sample tested negative for the four pathogens through RPA but positive for one of the four pathogens through plating.In Watsonville-Salinas samples, crown pieces were selected randomly for RPA and plating from pooled plant material.In contrast, during the Santa Maria survey, one crown piece was consciously selected from each plant in the sample for both RPA and plating.The authors chose to alter the methods this way to avoid diagnostic result discrepancies between RPA and plating and would advise similar processing methods in future surveys.The Watsonville-Salinas discrepancies also demonstrate the potential for individual symptomatic plants taken from the same area of an infected field to differ in terms of pathogen detection.

Figure 1 .
Figure 1.Map of sampled fall-planted (red), and summer-planted (yellow) and other strawberry-planted fields (gray) in the 2021-2022 growing season in Santa Maria, CA.

Figure 2 .
Figure 2. Overall prevalence of the four major soilborne pathogens in Santa Maria, CA.

Figure 3 .
Figure 3. Prevalence of the four major pathogens across fall (A) and summer (B) plantings, and east (C) and west (D) Santa Maria.

Table 3 .
Summary of multivariate model assessing field variable correlations to pathogen detection and disease incidence.