Fungicide Sensitivity of Cold Climate Grape Varieties. Patricia McManus University of Wisconsin-Madison UW-Extension

Transcription

1 Fungicide Sensitivity of Cold Climate Grape Varieties Patricia McManus University of Wisconsin-Madison UW-Extension

2 Topics Role of copper and sulfur for disease control in grapes Research results on copper, sulfur, and difenoconazole, Considerations for integrating copper and sulfur into a spray program

3

4 Role of Copper and Sulfur in Managing Diseases of Grapes Copper-based fungicides Highly effective on downy mildew Limited activity against other pathogens Sulfur Highly effective on powdery mildew Little or no activity on other pathogens

5 Role of Copper and Sulfur in Managing Diseases of Grapes Liquid lime-sulfur, liquid sulfur Dormant application may have eradicant activity on anthracnose, Phomopsis, and powdery mildew GREEN TISSUES BURNED BY LIME-SULFUR! DO NOT APPLY AFTER LEAVES EMERGE!

6 Role of Copper and Sulfur in Managing Diseases of Grapes 1. Fungicide resistance management Both copper and sulfur act by non-specific disruption of proteins Still effective after centuries of use Sterol inhibitors, strobilurins, and others can be overcome by a few mutations in pathogens fungicide resistance 1. Some forms of copper and sulfur cheaper than synthetic fungicides

7 Role of Copper and Sulfur in Managing Diseases of Grapes 3. Important in organic production Some forms of copper and sulfur are approved by OMRI Copper and sulfur often less expensive than other OMRI-approved products

8 Topics Role of copper and sulfur for disease control in grapes Research results on copper, sulfur, and difenoconazole, Considerations for integrating copper and sulfur into a spray program

9 Sensitivity to copper, sulfur, 2,4-D, and dicamba, as well as disease susceptibility

10 Lots of Unknowns for Cold Climate Varieties Cultivar BR DM PM Phom. Anthr. S Cu Brianna? +????? Edelweiss??????? Maréchal Foch Yes Yes Frontenac No? Frontenac gris No? La Crescent ?? La Crosse ?? Marquette ???? St. Croix? ?? Degree of susceptibility/sensitivity: + = slightly; ++ = moderately; +++ = highly;? = not known

11 Fungicide Sensitivity Research Objective Determine relative sensitivity of northern varieties to copper, sulfur, and difenoconazole Collaborators Matt Stasiak, Brian Shauske, Janet Hedtcke, Victoria Kartanos, Dave Jones UW-Madison research stations and UW Plant Pathology

12 Crop injury warning for products containing difenoconazole: Inspire, Inspire Super, Revus Top, Quadris Top

13 Research Sites and Varieties WM1 & WM2 PARS 1 & 2 Brianna Frontenac Frontenac gris La Crescent La Crosse Leon Millot Maréchal Foch Marquette MN1220 Noiret NY76 Petite Pearl St. Croix Valiant Vignoles

14 Treatments 1. Cuprofix Ultra 40 or Champ WG, lb actual copper/acre 2. Microthiol Disperss, 8-10 lb micronized sulfur/acre 3. Inspire Super or Inspire, lb difenoconazole per acre 4. Non-treated control

15 Treatments Applied 2 to 6 times at 2- to 3-week intervals in May- Aug 2012, 2013, 2014, 2015 (11 trials total) Applied without adjuvants and not mixed with other pesticides

16 Data Collection About every 2 weeks, foliage rated for injury 1 = no visible injury 2 = minor injury 3 = moderate injury 4 = severe injury For any given trial, same person did ratings weekly season-long Toxicity = average rating of 2.5 and statistically different from non-treated control

17 Copper injury on Brianna, PARS 2012

18 Copper injury on Marquette, WMARS, 4-Sep 2013

19 Foch at Peninsular Station, 2013 Sprayed with sulfur

20 Sprayed with sulfur Sprayed with copper Foch at Peninsular Station, 2012

21 Sensitivity to Copper Brianna M. Foch Frontenac Fronten gris LaCrescent LaCrosse Leon Millot Marquette MN1220 Noiret NY76 Petite Pearl St. Croix Valiant Vignoles

22 Sensitivity to Copper Do not apply copper to Brianna Restrict copper to 1-2 sprays/season on Frontenac, Frontenac gris, LaCrescent, Leon Millot, Maréchal Foch, Marquette, and St. Croix

23 Sensitivity to Sulfur Brianna M. Foch Frontenac Fronten gris LaCrescent LaCrosse Leon Millot Marquette MN1220 Noiret NY76 Petite Pearl St. Croix Valiant Vignoles

24 Sensitivity to Sulfur Do not apply sulfur to Maréchal Foch, Leon Millot, or Brianna Restrict sulfur to 1-2 sprays/season on LaCrescent and St. Croix

25 Sensitivity to Difenoconazole Noiret was sensitive in 1 of 2 trials The following varieties were tested in at least 3 trials, and none were sensitive: Brianna, Frontenac, Frontenac gris, LaCrescent, LaCrosse, Leon Millot, Maréchal Foch, Marquette, NY76, St. Croix, Valiant, and Vignoles

26 Topics Role of copper and sulfur for disease control in grapes Research results on copper, sulfur, and difenoconazole, Considerations for integrating copper and sulfur into a spray program

27 Integrating Copper and Sulfur into a Spray Program Initial considerations Do you have a good reason to try Cu and/or S? Organic Resistance management Economics Do you have any Cu or S sensitive varieties? Are Cu and S compatible with other products you rely on?

28 ph and Copper Solubility At lower ph, copper ions released from fixed fungicides more quickly Copper fungicides should not be mixed with phosphorous acid fungicides or any product that will reduce ph below 6.5 Because some forms of copper are persistent, consider the interval between copper and PA fungicide sprays

29 Integrating Copper and Sulfur into a Spray Program Further considerations Do you need post-infection activity? Cu strictly protective, needs to go on before infection S primarily protective, but good post-infection control up until time that PM growth appears Other fungicides provide better post-infection activity against DM and PM

30 Integrating Copper and Sulfur into a Spray Program Weather at time of application and within 24 hours after Hot temps increases risk of S injury Cool temps, prolonged wetness increase risk of Cu injury

31 Integrating Copper and Sulfur into a Spray Program Weathering of fungicides after application S especially subject to wash off with 1-2 inches rain Micronized forms of Cu and S more weather-fast than wettable powder

32 Thank You! Questions?

33 Vine Nutrition of Cold-Hardy Cultivars Carl Rosen and James Crants Department of Soil, Water, and Climate University of Minnesota Northern Grapes Project Webinar April 12, 2016

34 Collaborators Tim Martinson and Chrislyn Particka, Cornell University Paul Domoto and Diana Cochran, Iowa State University Harlene Hatterman-Valenti, North Dakota State University Rhoda Burrows and Anne Fennell, South Dakota State University

35 Background Recently developed cold hardy grape varieties offer new opportunities for winemaking Optimal nutrition and soil management practices have not been established Tissue analysis is a tool used to assess nutritional status, but critical values are based on V. labrusca and V. vinifera Values may need to be adjusted for cold hardy varieties, which have a V. riparia background

36 Background Tissue analysis is traditionally based on petioles samples The use of petioles has come into question, even for traditional varieties Leaf blade tissue or whole leaf (petiole + blade) may be a better indicator of nutritional status

37 Background Optimum petiole sampling time? Bloom +: more time to correct issues -: nutrient concentrations unstable Veraison +: concentrations stable predict nutrient needs for next year -: little time to address problems before harvest

38 Current Petiole Guidelines Element Bloom Veraison N (%) P (%) K (%) S (%) no data no data Ca (%) Mg (%) Zn (ppm) Fe (ppm) Mn (ppm) Cu (ppm) B (ppm) Values tabulated by Rosen and Domoto Ranges based on data from V. vinifera and V. labrusca Western and Eastern U.S. research

39 Overall Objectives Establish/fine-tune nutrient diagnostic criteria and interpretations for recently released cold hardy grape cultivars Determine relationships between soil characteristics and tissue nutrient levels (petiole, blade, whole leaf) and juice quality

40 14-16 Study Sites, 3 Years Used in 1 2 seasons Used in all 3 seasons

41 Approach Four-year-old vines (or older) of Marquette, La Crescent, and Frontenac grape cultivars selected in replicates/cultivar per vineyard Original plan samples/cultivar over 3 years Soil samples for 0-8 and 8-16 depths collected in the springs of 2012 and 2015 Characterize physical and chemical properties Leaf blade and petiole samples collected in 2012, 2013, and 2015 at: Full bloom Midsummer (~ 30 days later) Veraison

42 Approach Full bloom Petioles and leaves opposite the bottom flower cluster

43 Approach Midsummer (~ 30 days post-bloom) and veraison Petioles and leaves from the most recently matured leaf 5 th to 7 th leaf from the terminal

44 6 5 7

45 Approach Soil and tissue samples were sent to a commercial lab for analysis using standard protocols At harvest, grape yields were measured or estimated Grape samples were collected for juice quality analysis: Brix, ph, titratable acidity, YAN

46 Approach Data Used for Developing Nutrient Diagnostic Criteria Data from vines that had adequate yields (range ~ 4 39 lbs/vine); Eliminated highest and lowest nutrient concentration value in each cultivar Vines were also excluded if: Vines recovering from frost damage No yield per vine data provided Nutrient stress symptoms evident in vines

47 Approach 62 replicate-years remained for Frontenac 6 8 vineyards each year 75 remained for La Crescent 7 8 vineyards each year 80 remained for Marquette 9 10 vineyards each year

48 Approach Tissue Sufficiency Ranges Mean, standard deviation, maximum, and minimum nutrient concentrations were calculated for each cultivar separately and all cultivars combined Concentrations and ranges are based on all cultivars combined Sufficiency range: Mean SD to Mean + SD Sufficiency ranges were similar among cultivars, for the most part

49 Results Soil Properties Variable Mean Range Texture Loamy sand to clay loam ph O.M. (%) Bray P1 (ppm) K (ppm) Mg (ppm) Zn (ppm) B (ppm)

50 Results Tissue at bloom Element Petiole Blade Whole leaf N (%) P (%) K (%) S (%) Ca (%) Mg (%) Zn (ppm) Fe (ppm) Mn (ppm) Cu (ppm) B (ppm)

51 Results Tissue at Veraison Element Petiole Blade Whole leaf N (%) P (%) K (%) S (%) Ca (%) Mg (%) Zn (ppm) Fe (ppm) Mn (ppm) Cu (ppm) B (ppm)

52 Relationships Between Tissue Nutrients and Juice Quality Analysis of variance was performed on the full data set for the main effect of each independent variable on each juice variable (Brix, ph, TA, YAN), controlling for effects of cultivar and year Main effects with P-values less than 0.05 were considered meaningful: if there was no interaction with cultivar or year, or if the trend was in the same direction for each cultivar across all years

53 Relationships with YAN YAN increased with increases in tissue N Strongest in bloom blades Blades higher in N than petiole YAN increased with bloom blade, whole-leaf S, veraison petiole S S positively correlated with N

54 Relationships with Juice ph Juice ph increased with increases in bloom petiole K K higher in petioles than blades Juice ph increased with increases in veraison whole-leaf N, with weaker effects for blades and petioles separately Juice ph decreased with increasing yield per vine

55 Relationships with Titratable Acidity (TA) TA Increased with increasing bloom blade and whole-leaf S Mean S concentration highest in bloom blades Increased with bloom petiole P

56 Relationships with Sugar ( Brix) No independent variable was consistently related to juice sugar concentration NOTE: Juice composition, including Brix, is related to other management factors such as cropping levels, fruit exposure, pruning, training system, and harvest timing

57 What We Have Learned So Far Wide range of soil properties in the study Wide range in tissue nutrient levels Some previous petiole diagnostic ranges based on traditional cultivars will be finetuned for cold-climate cultivars N, P, K, S, Ca, Fe at bloom N, P, K, S, Zn, Fe, Mn at veraison

58 What We Have Learned So Far Tissues collected at bloom were more predictive of juice quality than those collected at veraison Tissue N and S influence juice YAN Tissue K and yield per vine influence juice ph S influences juice TA No consistent influences on juice sugar

59 What We Have Learned So Far Our most robust result is the positive correlation between tissue N and YAN Growers base harvest times on other variables (Brix, ph, TA) Thus, these variables may not respond strongly to factors other than grower targets Data analysis is still in progress; consider results presented today as preliminary

60 Thank You & Questions?