Fungal Diseases in Two North-West Spain Vineyards: Relationship with Meteorological Conditions and Predictive Aerobiological Model

agronomy Article Fungal Diseases in Two North-West Spain Vineyards: Relationship with Meteorological Conditions and Predictive Aerobiological Model Jose A. Cortiñas Rodríguez 1, Estefanía González-Fernández 1, María Fernández-González 1,2,* , Rosa A. Vázquez-Ruiz 3and María Jesús Aira 4 1Department of Plant Biology and Soil Sciences, Sciences Faculty of Ourense, University of Vigo, As Lagoas s/n, 32004 Ourense, Spain; [email protected] (J.A.C.R.); [email protected] (E.G.-F.) 2Earth Sciences Institute (ICT), Pole of the Faculty of Sciences University of Porto, 4169-007 Porto, Portugal 3 Department of Botany, Higher Polytechnic School, University of Santiago of Compostela, 27002 Lugo, Spain; [email protected] 4 Department of Botany, Biology Faculty, University of Santiago of Compostela, 15782 Santiago of Compostela, Spain; [email protected] *Correspondence: [email protected] Received: 19 December 2019; Accepted: 28 January 2020; Published: 3 February 2020   Abstract: Grey mould, powdery mildew, and downy mildew are the most frequent fungal diseases among vineyards worldwide. In the present study, we analysed the influence of the fungi causing these diseases (Botrytis, Erysiphe, and Plasmopara, respectively) on two viticulture areas from North-western (NW) Spain during three growth seasons (2016, 2017, and 2018). The obtained results showed the predominant concentration of the Botrytis airborne spores, mainly from the beginning of the Inflorescence emerge phenological stage (S-5) until the end of the Flowering phenological stage (S-6). Erysiphe and Plasmopara airborne spore peak concentrations were more localised around Flowering (S-6) and Development of fruits (S-7) phenological stages. We applied a Spearman’s correlation test and a Principal Component Analysis to determine the influence of the meteorological parameters on the concentration of airborne spores. Taking into account the variables with the highest correlation coefficient, we developed multiple regression models to forecast the phytopathogenic fungal spore concentrations. The Botrytis model regression equation explained between 59.4–70.9% of spore concentration variability. The Erysiphe equation explained between 57.6–61% and the Plasmopara explained between 39.9–55.8%. In general, we found better prediction results for mean daily concentrations than sporadic spore peaks. Keywords: Botrytis; Erysiphe; Plasmopara; vineyards; incidence; multiple linear regression 1. Introduction Among the cryptogamic diseases, the fungal grey mould, powdery mildew, and downy mildew epidemics have the highest incidence in European vineyards [ 1 – 4 ]. Grey mould caused by Botrytis spp. Pers.: Fr. (teleomorph: Botryotinia fuckeliana (de Bary) Whetzel) affects more than 200 plants, mainly dicot plants, and it can cause serious economic damage, especially in grapevines [ 5 – 7 ]. In addition to an important crop yield loss, this disease can also reduce the wine quality by providing an unstable colour, oxidative damages, premature aging, unpleasant flavours, and clarification difficulties [ 8 ]. The Botrytis infections, due to the fungal laccase enzyme oxidation, can compromise both the grapes and wine quality [ 9 ]. This fungus overwinters as sclerotia and mycelium in buds or trunk cracks, infecting plants again in the following spring mainly through wounds caused by hailstones, mechanical injuries or insects [10–12]. Agronomy 2020,10, 219; doi:10.3390/agronomy10020219 www.mdpi.com/journal/agronomy Agronomy 2020,10, 219 2 of 18 Powdery mildew caused by Erysiphe necator Schwein.: (anamorph: Oidium tuckeri Berk) came from the United States to Europe through England in 1845, spreading to the entire Mediterranean region and other geographical areas [ 13 ]. The American native grapevine has a high resistance level against this pathogen, while the European species Vitis vinifera is susceptible as it can present severe disease symptoms in different plant parts [ 14 ]. This fungus notably decreases the grape yield and quality, altering the must and wine organoleptic characteristics as it reduces the soluble solids and increases the total acidity [ 15 ]. In red wines, infected fruits at the beginning of ripening reach a lower phenolic compounds content, which also has an impact on their sensory properties [16]. Finally, Plasmopara viticola (Berk. & Curtis) Berl. & De Toni, responsible for downy mildew, is an obligate oomycete that overwinters as oospores in soil leaves and vegetal debris. These propagules mature as a function of temperature and precipitation, causing subsequent secondary infections. Plasmopara is native to North America and was first detected in Spain in 1878. Since then, it has been considered as one of the worst grapevine diseases that occur during favourable weather conditions [ 17 ]. The fungus bears fruit only on the host plant surface, as such, it can be only diagnosed by observing sporulation or fruiting on the plant [ 18 ]. It causes direct inflorescence and bunch losses or indirect decreases of photosynthetic activity on affected leaves. In severe attacks, the plants suffer partial desiccation resulting in the premature falling of leaves, and the withering of branches [19]. The incidence of these three vine pathogens was widely studied, as well as considering the analysis of cultural control practices. Different measures, such as drainage improvement, green pruning near to flowering, defoliation near to veraison for the improvement of ventilation for bunches, and the use of a training system to achieve appropriate air circulation, can reduce the pathology severity caused by any of these fungi [ 20 – 22 ]. The plant vigour can be controlled by avoiding excessive growth and vegetative development is also beneficial to reduce the incidence of phytopathogens [ 23 ]. Regarding chemical control, contact products, such as copper in the form of wettable powder and applied in a foliar spray or sulphur as a powder for dusting, should be used as infection prevention systems, although their use should be avoided during flowering as it can affect fruit set [ 24 ]. However, when diseases are evident it is necessary to apply penetrating and systemic treatments with curative effects, regulating their frequency according to the pathogen’s intensity [25]. The main goals of this research work are to analyse the incidence of these three fungal grapevine diseases (grey mould, powdery mildew, and downy mildew) in North-western (NW) Spain vineyards and to develop prediction models to detect the airborne spore presence that fungi produce. Besides cost reduction in grape production, this kind of study also impacts environmental protection and quality since it allows a phytosanitary treatment application when a real infection is detected [26,27]. 2. Materials and Methods 2.1. Location and Climatic Characteristics of the Study Area The present study was conducted in two wine-making regions, Ribeiro and Ribeira Sacra, in the Cenlle (117 m a. s.l. 42 ◦ 18 0 55.7” N; 8 ◦ 6 0 2.54” W) and O Mato (332 m a. s.l. 42 ◦ 30 0 32.3” N; 7 ◦ 30 0 3.02” W) vineyards, respective ly (Figure 1) during 2016, 2017 and 2018. Agronomy 2020,10, 219 3 of 18 Agronomy2020,10,xFORPEERREVIEW3of19  Figure1.LocationoftheRibeiro(Cenlle)andRibeiraSacra(OMato)DesignationOriginareasinthe NorthwesternSpain. TheprevailingcultivarintheCenllevineyardisGodello,andinOMatovineyarditisMencía, bothincludedinthepreferentialcategoryaccordingtotheDesignationofOriginRibeiro(DOGN° 149,2009)andRibeiraSacra(DOGN°194,2009)regulations.TheGodellocultivarhasahighvigour andanerectbearing(tendingtogrowmoreverticallythanhorizontally)withanearlysproutand maturation.Consideringthepathogensusceptibilityoftheplantaccordingtothethreecategories establishedintheclassificationoftheGodellocultivarisclassifiedashavinglowsensitivityto Botrytis,mediumsensitivitytoPlasmopara,andsensitivitytoErysiphe.TheMencíacultivarhasa mediumvigourwithearlysproutingandsemi‐latematuration.Thiscultivarissensitivetothethree consideredfungalpathogens[28]. Forclimaticcharacterization,weconsideredthemeteorologicaldataofthemaximum,minimum andmeantemperature,relativehumidity,daylight(sunshine)hours,rainfallandwind‐speed variables(Table1),providedbytwostationslocatedveryclosetothestudiedvineyards,theLeiro andMonfortestationsbelongingtotheweatherserviceMeteogaliciahttps://www.meteogalicia.gal (accessedon21/06/2019). Table1.Meteorologicalparameters,maximumtemperature,minimumtemperature,average temperature,averagerelativehumidity,sunshine,windspeedandrainfall,inthestudyarea(2016– 2018). RibeiroRibeiraSacra Year201620172018201620172018 AnnualAverage MeteorologicalData MaxT(°C)22.823.923.720.621.921.4 MinT(°C)7.36.48.26.76.17.3 MeanT(°C)13.813.915.212.813.113.7 MeanRH(%)78.475.875.980.976.978.6 Sunshine(hours)5.35.94.98.18.48.4 Wind‐Speed(Km/h)2.11.82.22.11.82.5 AnnualTotalRainfall(L/m 2 )1211.8814.5775.2940.4616.2660.5 MaximumDailyrainfall(l/m 2 )49.0100.839.442.877.525.7 Date10Jan10Dec28  Feb10  Jan10Dec11Mar Maximumtemperature(MaxT),minimumtemperature(MinT),averagetemperature(MeanT), averagerelativehumidity(MeanRH). Figure 1. Location of the Ribeiro (Cenlle) and Ribeira Sacra (O Mato) Designation Origin areas in the Northwestern Spain. The prevailing cultivar in the Cenlle vineyard is Godello, and in O Mato vineyard it is Menc í a, both included in the preferential category according to the Designation of Origin Ribeiro (DOG N ◦ 149, 2009) and Ribeira Sacra (DOG N ◦ 194, 2009) regulations. The Godello cultivar has a high vigour and an erect bearing (tending to grow more vertically than horizontally) with an early sprout and maturation. Considering the pathogen susceptibility of the plant according to the three categories established in the classification of the Godello cultivar is classified as having low sensitivity to Botrytis, medium sensitivity to Plasmopara, and sensitivity to Erysiphe. The Menc í a cultivar has a medium vigour with early sprouting and semi-late maturation. This cultivar is sensitive to the three considered fungal pathogens [28]. For climatic characterization, we considered the meteorological data of the maximum, minimum and mean temperature, relative humidity, daylight (sunshine) hours, rainfall and wind-speed variables (Table 1), provided by two stations located very close to the studied vineyards, the Leiro and Monforte stations belonging to the weather service Meteogalicia https://www.meteogalicia.gal (accessed on 21/06/2019). Table 1. Meteorological parameters, maximum temperature, minimum temperature, average temperature, average relative humidity, sunshine, wind speed and rainfall, in the study area (2016–2018). Ribeiro Ribeira Sacra Year 2016 2017 2018 2016 2017 2018 Annual Average Meteorological Data Max T (◦C) 22.8 23.9 23.7 20.6 21.9 21.4 Min T (◦C) 7.3 6.4 8.2 6.7 6.1 7.3 Mean T (◦C) 13.8 13.9 15.2 12.8 13.1 13.7 Mean RH (%) 78.4 75.8 75.9 80.9 76.9 78.6 Sunshine (hours) 5.3 5.9 4.9 8.1 8.4 8.4 Wind-Speed (Km/h) 2.1 1.8 2.2 2.1 1.8 2.5 Annual Total Rainfall (L/m2)1211.8 814.5 775.2 940.4 616.2 660.5 Maximum Daily rainfall (l/m2)49.0 100.8 39.4 42.8 77.5 25.7 Date 10 Jan 10 Dec 28 Feb 10 Jan 10 Dec 11 Mar Maximum temperature (Max T), minimum temperature (Min T), average temperature (Mean T), average relative humidity (Mean RH). Agronomy 2020,10, 219 4 of 18 2.2. Fieldwork and Laboratory Analysis We studied the phenological stages for both grapevine cultivars following the [ 29 ] scale adopted by the BBCH (Biologische Bundesanstalt, Bundessortenamt and Chemical industry) as a standardized scale. Phenological observations were applied on 10 vines of each cultivar and this information was correlated with atmospheric spore (or sporangia for Plasmopara) concentrations. The study was carried out during the active grapevine cycle, from the 1 st of March to the grape harvest date in the month of September. We used a volumetric method by means of a Hirst type Lanzoni VPPS-2000 ® (Lanzoni s.r.l., Bologna, Italy) pollen-spore trap [ 30 ] for the sampling of airborne reproductive structures. The volumetric traps were placed at a height of two meters, according to the vine’s foliar arrangement on each studied vineyard. We identified and quantified the three considered pathogens spores/sporangia (Botrytis,Erysiphe and Plasmopara) in the collected samples. We followed the Spanish Aerobiology Network (REA) proposed protocol [ 31 ] for spore count and sample preparation. Slide counts were performed on two longitudinal transects along the slides and the airborne fungal spore concentrations were expressed as a daily average of fungal spores/m 3 of air recommended terms were used for the aerobiological terminology [32]. Table 2shows the phytochemical treatments applied in the plots of the study. In the Ribeiro D.O: (Cenlle), a mean of three treatments/year against Botrytis was applied from stage 6 (flowering), six treatments/year against Mildew +Oidium mainly from stage 5 (inflorescence emerges), and two specific treatments/year against Mildew in the 7th and 8th stages (development of fruits and ripening of berries). In the Ribeira Sacra D.O. (O Mato), no treatments against Botrytis were applied, four treatments/year (none in 2017) against Mildew +Oidium, mainly in stage 5 (Inflorescence emerge) and four specific treatments/year against Mildew (none in 2017). For all cases, the fungicides used until Flowering (E6) are of the systemic type in years that had a high incidence of fungi, and from this moment of contact (mainly sulphur-based powder products until Fruit set, and copper in wet dust until Softening of berries). Table 2. Number of phytosanitary treatments applied in the studied plots. Against S0 S1 S5 S6 S7 S8 Botrytis Cenlle 2016 1 2 Cenlle 2017 1 1 Cenlle 2018 2 2 1 O Mato 2016 O Mato 2017 O Mato 2018 Mildew +Oidium Cenlle 2016 2 2 2 Cenlle 2017 2 1 3 1 Cenlle 2018 1 1 1 1 2 O Mato 2016 1 2 1 O Mato 2017 O Mato 2018 2 1 2 Mildew Cenlle 2016 1 Cenlle 2017 2 Cenlle 2018 2 2 O Mato 2016 2 2 O Mato 2017 O Mato 2018 1 1 2 Phenological stages: Bud development (S0), Leaf development(S1), Inflorescence emerge (S5), Flowering (S6), Development of fruits (S7) and Ripening of berries (S8). 2.3. Statistical Analysis In order to determine the influence of the main meteorological variables on airborne spore concentrations, we applied Spearman’s correlation test, as the considered variables didn’t show a Agronomy 2020,10, 219 5 of 18 normal distribution. We considered the correlations for the same day and the previous 1–7 days as spore production can be directly affected by meteorological conditions or indirectly through its effect on the colonised substrates [ 26 ]. Moreover, we applied a Principal Component Analysis (PCA) to complement the analysis of these variables, considering the meteorological influence of all variables as a whole. For this analysis we considered for both vineyards the maximum, mean, and minimum temperatures; relative humidity; rainfall; and wind-speed meteorological parameters, independent of the vineyard location. With the obtained results, we developed models based on Lineal Regressions using the meteorological variables with the highest correlation coefficients as estimators of the fungal spore concentrations. For model validation, we carried out an internal validation and we studied the residual scores as they show the differences between observed and predicted data for each analysed year. 3. Results 3.1. Total Spore Concentrations and Spatial Distribution The active grapevine period slightly varied according to the vineyard location and the considered year. The sprouting phenological phase (S-0) began between mid-March to the beginning of April, while the harvest date occurred between the end of August to mid-September. Within these dates, the collection of aerobiological samples was carried out and the fungal spores were counted. The Botrytis Seasonal Spore Integral (SSIn) was markedly higher than for the other considered pathogens, with a maximum of 49,620 spores in the O Mato vineyard in 2018 and SSIn values of 27,656 and 17,240 spores for the 2016 and 2017 years, respectively. The Erysiphe SSIn noted a record in 2016 for both studied vineyards of 17,269 spores in Cenlle and 12,946 spores in O Mato. Plasmopara was the pathogen with the lowest atmospheric presence. The highest SSIn value was recorded in 2018 at the O Mato vineyard with 5656 spores, varying between 1363 for 2017 and 3618 for 2016 SSIn, and from 679 for 2017 to 3605 for 2018 SSIn values in Cenlle (Table 3). Taking into account the maximum daily values we also found a clear Botrytis spore’s dominance with a maximum of 1547 spores/m 3 in O Mato on 9 June 2018. The highest daily peaks of Erysiphe and Plasmopara were recorded during the 2016 season in the O Mato vineyard, with 597 Erysiphe spores/m 3 on 3 June 2016 and 502 Plasmopara spores/m3on 7 July 2016. Considering the pathogen relation with the different grapevine phenological phases, we found a considerable variability depending on the pathogen, season, and vineyard location. The Botrytis and Erysiphe airborne spore presence were almost constantly along the grapevine growth cycle, while the Plasmopara sporangia did not show a continuous daily record. For the considered 2016–2018 period, we found 29 days/season average of Plasmopara 0-record in Cenlle, and 20 days/season in O Mato. The highest Botrytis incidence was detected from the inflorescence emergence (S-5) phenological stage until the end of flowering (S-6). At the Cenlle plot, the maximum atmospheric Botrytis spore peak was recorded in mid-June in 2016, the end of May in 2017, and several spore peaks were detected between the beginnings of June and the end of July in 2018, with a maximum peak on 7 July. At the O Mato plot, the Botrytis spore peaks occurred within the May–July period, with the maximum peaks on 27 May 2016, on 4 June 2017, and 9 June 2018. We also found early infections during the leaf development (S-1) phenological stage at the Cenlle vineyard in 2017, and at the O Mato vineyard in 2016 and 2017 (Figure 2). Agronomy 2020,10, 219 6 of 18 Table 3. SSIn data, daily maximum spore concentration and maximum date for Botrytis,Erysiphe, and Plasmopara in Ribeiro (Cenlle) and Ribeira Sacra (O Mato) DOs during the study period (spores/m 3 of air). Cenlle Botrytis Erysiphe Plasmopara Study Period 19 September 2016 to 18 September 2016 SSIn 16,806 17,269 1910 Daily Maximum 637 399 104 Maximum Date 22 June 16 May 8 June Study Period 16 March 2017 to 30 August 2017 SSIn 15,378 3344 679 Daily Maximum 696 423 54 Maximum Date 28 May 2017 26 May 2017 8 May 2017 Study Period 29 March 2018 to 10 September 2018 SSIn 24,214 3116 3605 Daily maximum 1210 316 460 Maximum date 7 July 2018 4 June 2018 7 July 2018 O Mato Study period 24 March 2016 to 30 September 2016 SSIn 27,656 12,946 3618 Daily Maximum 1435 597 502 Maximum Date 27 May 2016 3 June 2016 7 July 2016 Study Period 04 March 2017 to 08 September 2017 SSIn 17,240 1686 1363 Daily Maximum 826 108 45 Maximum Date 4 June 2017 19 June 2017 3 June 2017 Study Period 07 April 2018 to 07 September 2018 SSIn 49,620 5632 5656 Daily Maximum 1547 197 345 Maximum date 9 June 2018 29 May 2018 22 July 2018 SSIn—Seasonal Spore Integral. Most of the Erysiphe and Plasmopara infections coincided with the end of flowering (S-6) and development of fruits (S-7) phenological stages. At the Cenlle vineyard, there were several Erysiphe and Plasmopara spore peaks detected in the May–July period in 2016, while the maximum Erysiphe spore peak was on 26 May 2017 and 4 June 2018, and the maximum Plasmopara sporangia peaks were registered at the beginning of May in 2017, and during July in 2018. At the O Mato vineyard, the highest Erysiphe spore peaks were also detected in the May–July period in 2016 with a maximum spore peak on 3 June. In 2017 and 2018, the highest daily spore peaks were lower than in 2016, registered on 19 June and 29 May, respectively. The Plasmopara highest sporangia peaks occurred at the beginning of July in 2016 and the end of July in 2018, while in 2017 the peak was detected at the beginning of June, with a markedly lower value (Figure 2). Agronomy 2020,10, 219 7 of 18 Agronomy2020,10,xFORPEERREVIEW7of19  Figure2.Phenology,sporeconcentrations,andphytosanitarytreatmentsappliedinthethreestudy yearsforRibeiro(Cenlle)andRibeiraSacra(OMato)vineyards. MostoftheErysipheandPlasmoparainfectionscoincidedwiththeendofflowering(S‐6)and developmentoffruits(S‐7)phenologicalstages.AttheCenllevineyard,therewereseveralErysiphe andPlasmoparasporepeaksdetectedintheMay–Julyperiodin2016,whilethemaximumErysiphe sporepeakwason26May2017and4June2018,andthemaximumPlasmoparasporangiapeakswere registeredatthebeginningofMayin2017,andduringJulyin2018.AttheOMatovineyard,the highestErysiphesporepeakswerealsodetectedintheMay–Julyperiodin2016withamaximum sporepeakon3June.In2017and2018,thehighestdailysporepeakswerelowerthanin2016, registeredon19Juneand29May,respectively.ThePlasmoparahighestsporangiapeaksoccurredat thebeginningofJulyin2016andtheendofJulyin2018,whilein2017thepeakwasdetectedatthe beginningofJune,withamarkedlylowervalue(Figure2). 3.2.AnalysisofMeteorologicalParameters Takingintoaccounttheannualaveragemaximumtemperaturevalue,itwashigherinRibeiro (Cenlle)witha2°CdifferenceoverRibeiraSacra(OMato)forthesameconsideredyears.Thesame occurredwithminimumandmeantemperaturesbutwiththelowestdifferenceinthiscase,around 1°C.Forbothvineyards,CenlleandOMato,2017waswarmerthantheothertwoconsideredyears withamaximumtemperatureof23.9°Cand21.9°Crespectively.Meanandminimumtemperatures werehigherin2018,with15.2°Cand13.7°Cmeantemperatures,and8.2°Cand7.3°Cminimum temperatures,respectively.TheaveragerelativehumiditywashigherinRibeiraSacrathaninRibeiro, reachingitsmaximumin2016with80.9%.Thesamehappenedwiththesunshinehours,withthe maximumvaluesforRibeiraSacrafoundin2017and2018.Therainiestyearwas2016forbothRibeiro Figure 2. Phenology, spore concentrations, and phytosanitary treatments applied in the three study years for Ribeiro (Cenlle) and Ribeira Sacra (O Mato) vineyards. 3.2. Analysis of Meteorological Parameters Taking into account the annual average maximum temperature value, it was higher in Ribeiro (Cenlle) with a 2 ◦ C difference over Ribeira Sacra (O Mato) for the same considered years. The same occurred with minimum and mean temperatures but with the lowest difference in this case, around 1 ◦ C. For both vineyards, Cenlle and O Mato, 2017 was warmer than the other two considered years with a maximum temperature of 23.9 ◦ C and 21.9 ◦ C respectively. Mean and minimum temperatures were higher in 2018, with 15.2 ◦ C and 13.7 ◦ C mean temperatures, and 8.2 ◦ C and 7.3 ◦ C minimum temperatures, respectively. The average relative humidity was higher in Ribeira Sacra than in Ribeiro, reaching its maximum in 2016 with 80.9%. The same happened with the sunshine hours, with the maximum values for Ribeira Sacra found in 2017 and 2018. The rainiest year was 2016 for both Ribeiro (with 1211.8 mm) and Ribeira Sacra (940.4 mm) areas. Nevertheless, the rainiest day was 10 December 2017 for both vineyards (Table 1). 3.3. Statistical Results The statistical analysis between the spore daily concentrations and the daily values of the main meteorological variables along the grapevine reproductive cycle was conducted, while also considering the daily values of the meteorological variables during the previous 7 days in regards to the presence of spores in the atmosphere of the vineyard. The statistical analysis between the spore concentrations and the main meteorological variables showed that rainfall and relative humidity had a statistically significant influence in most cases. Nevertheless, the influence sign was not so clear for temperature, Agronomy 2020,10, 219 8 of 18 as we found the same number of positive and negative correlations for maximum and mean temperature. The parameters with the highest influence on each pathogen varied depending on the vineyard location and the study year. Within the significant Botrytis correlations, we found the highest Spearman’s r positive coefficients for the Botrytis spores obtained four days before (Botrytis-4) vs. rainfall, and Botrytis-4 vs. relative humidity correlations for Cenlle in 2017. In the same Cenlle vineyard in 2018, we found the Botrytis-1 vs. minimum temperature, and Botrytis vs. mean temperature correlations. We also found a high Spearman’s r positive coefficient for the Botrytis-2 vs. relative humidity correlation at the O Mato vineyard in 2016. For the Erysiphe airborne spores we found that the highest Spearman’s r significant coefficient was negative, corresponding to Erysiphe-2 vs. minimum temperature, and Erysiphe-2 vs. mean temperature correlations at Cenlle vineyard in 2016. At the O Mato vineyard, we found also high correlations, positive in this case, between Erysiphe vs. minimum temperature, and Erysiphe vs. mean temperature in 2017. The strongest correlations found for Plasmopara airborne sporangia corresponded to Plasmopara vs. minimum temperature, Plasmopara vs. mean temperature positive correlations at the Cenlle vineyard in 2017, and Plasmopara-6 vs. rainfall, Plasmopara-2 vs. relative humidity positive correlations at the O Mato vineyard in 2016. However, we also found considerable negative correlations for Plasmopara-7 vs. maximum temperature and Plasmopara-7 vs. mean temperature at the O Mato vineyard in 2016 (Table 4). In both analyzed areas, the Principal Components PC1 and PC2 included meteorological variables and the PC3 grouped the three phytopathogenic fungi spore concentrations. For Cenlle, PC1 includes the maximum and mean temperatures, humidity, and rainfall and PC2 includes the minimum temperature and wind speed. In the case of O Mato, PC1 include the temperatures and the wind speed, whereas PC2 includes the water-related parameters. Most of the variables had significant positive loads, except wind speed (PC2 in Cenlle and PC1 in O Mato). For graphic representation, we selected PC2 versus PC3 for the Cenlle vineyard, and PC1 versus PC3 for the O Mato vineyard (Figure 3). In the obtained charts we showed in detail the relation between fungal airborne spores and the main meteorological variables. In both vineyards we observed a high positive association degree between meteorology and fungal spores counts. Agronomy 2020,10, 219 9 of 18 Table 4. Spearman’s rank correlation of different parameters for the studied cultivars. Spore concentrations (Botrytis,Erysiphe and Plasmopara) and the main meteorological parameters. (plevel: * <0.05; ** <0.01; N.S.: not significative). 2016 2017 2018 Cenlle Botrytis Erysiphe Plasmopara Botrytis Erysiphe Plasmopara Botrytis Erysiphe Plasmopara Rainfall −0.167 * Botrytis −0.365 * Erysiphe-7 0.355 * Plasmopara-2 0.401 ** Botrytis-4 0.196 * Erysiphe-7 0.172 * Plasmopara-4 −0.190 * Botrytis-1 N.S. −0.255 ** Plasmopara RH 0.382 * Botrytis-2 −0.321 * Erysiphe-2 0.342 * Plamopara-2 0.507 ** Botrytis-4 0.248 ** Erysiphe-5 N.S. 0.263 ** Botrytis-5 0.203 ** Erysiphe−7N.S. T max 0.288 ** Botrytis 0.440 ** Erysiphe-2 −0.335 * Plasmopara-2 −0.228 ** Botrytis-4 −0.180 * Erysiphe-7 −0.300** Plasmopara-6 0.387 ** Botrytis N.S. 0.387 ** Plasmopara T min 0.323 ** Botrytis −0.674 * Erysiphe-2 0.346 * Plasmopara-2 N.S. N.S. −0.411 ** Plasmopara-7 0.634 ** Botrytis-1 0.197 * Erysiphe 0.489 ** Plasmopara T mean 0.307 ** Botrytis −0.666 ** Erysiphe-2 N.S. −0.188 * Botrytis-4 −0.154 * Erysiphe-5 −0.362 ** Plasmopara-6 0.556 ** Botrytis N.S. 0.480 ** Plasmopara O Mato Rainfall 0.365 ** Botrytis-5 0.394 ** Erysiphe-6 0.227 ** Plasmopara-6 N.S. −0.272 ** Erysiphe-2 N.S. 0.224 ** Botrytis-6 0.231 ** Erysiphe-7 N.S. RH 0.593 ** Botrytis-2 0.491** Erysiphe-6 0.377** Plamopara-2 0.224 ** Botrytis-3 −0.354 ** Erysiphe-2 0.163 * Plasmopara-4 0.373 ** B otrytis-7 0.359 ** Erysiphe-6 N.S. T max −0.386 ** Botrytis-7 −0.476 ** Erysiphe-7 −0.309 ** Plasmopara-7 N.S. 0.483 ** Erysiphe 0.186 * Plasmopara N.S. −0.297 ** Erysiphe-6 N.S. T min −0.153 * Botrytis-7 −0.231 ** Erysiphe-6 −0.177* Plasmopara-7 0.248 ** Botrytis 0.509 ** Erysiphe 0.209 ** Plasmopara 0.331 ** Botrytis N.S. N.S. 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