Disease and Insect Guide Technologies, Inc. Spectrum SpecWare
Contents
1. 18 612 617 Seaman W S and M M Barnes 1984 Thermal Summation for the Development of the Navel Orangeworm in Almond Lepidoptera Pyralidae Environ Entomol 13 81 85 Sevacherian V V M Stern and A J Mueller 1977 Heat Accumulation for Timing Lygus Control Measures in a Safflower Cotton Complex J Econ Entomol 70 399 402 Tassan R L K S Hagen A Cheng T K Palmer G Feliciano and T L Bough 1982 Mediterranean Fruit Fly Life Cycle Estimations For The California Eradication Program CEC IOBC Symposium Athens November 1982 564 570 Tolley M P and W H Robinson 1986 Seasonal Abundance and Degree Day Prediction of Sod Webworm Lepidoptera Pyralidae Adult Emergence in Virginia J Econ Entomol 79 400 404 UC IPM Pest Management Guidelines Peach and Nectarine UC DANR Publication 3339 Weakley C V F G Zalom and R E Rice 1984 Monitoring Oriental Fruit Moth Development with Degree Days U C Div Agr Sci Publ 7157 Williams D W 1984 Ecology of the Blackberry Leafhopper Parasite System and its Relevance to California Grape Agroecosystems Hilgardia 52 1 32 Yu D S and R F Luck 1988 Temperature Dependent Size and Development of California Red Scale Homoptera Diaspididae and its Effect on Host Availability for the Ectoparasitoid Aphytis Melinus Debach Hymenoptera Aphelinidae Environ Entomol 17 154 161 Zajac M A F R Hall and M Cu2. About SpecWare A dialog box will appear with both the Serial Number and Registration Number Call fax or e mail Spectrum with this information The optional disease and insect models are as follows Catalog Apple Scab 3656 AS Black Rot 3656 BR Botrytis 3656 BT Brown Patch 3656 BP Cherry Leaf Spot 3656 CS Dollar Spot 3656 DS Downy Mildew 3656 DM Early Blight 3656 EB Fire Blight 3656 FB Late Blight 3656 LB Powdery Mildew 3656 PD Pythium Blight 3656 PT Sooty Blotch 3656 SB Tom Cast 3656 TC Insects 3656 IN For detailed descriptions of how to open files and choose the locations and time periods to be modeled refer to the SpecWare 6 02 Software Users Guide The Basics of Computer Modeling There are practical considerations that must be taken into account when using computer models to predict biological processes such as disease or insect activity The model must be appropriate for the particular insect or disease The data for environmental parameters must be acquired to accurately predict the life stages of the organism The type of crop and its stage of development has an effect on the development of the pest organism The region in which the model was developed is also important A useful computer model takes each of these points into account Using common names to distinguish one disease or insect from another can lead to errors For instance almost every crop plant Known to man has a disease called powdery mildew SpecW
3. Entomol 21 441 446 Reissig W H J Barnard R W Weires E H Glass and R W Dean 1979 Prediction of Apple Maggot Fly Emergence from Thermal Unit Accumulation Environ Entomol 8 51 54 Rice R E C V Weakley and R A Jones 1984 Using Degree Days to Determine Optimum Spray Timing for the Oriental Fruit Moth Lepidoptera Tortricidae J Econ Entomol 77 698 700 Rice R E F G Zalom and C Jorgensen 1982 Monitoring San Jose Scale Development with Degree days California Agri Sci Leaflet 21312 Rice R E F G Zalom and J F Brunner 1982 Monitoring Peach Twig Borer Development with Degree days U C Div Agri Pub 21302 Rice R E F G Zalom and J F Brunner 1982 Using Degree days in a Peach Twig Borer Monitoring Program Almond Facts March April 1982 60 62 Rock G C R E Stinner J E Bacheler L A Hull and H W Hogmire 1993 Predicting Geographical and Within Season Variation in Male Flights of Four Fruit Pests Environ Entomol 22 716 725 Roltsch W J M A Mayse 1993 Simulation Phenology Model for the Western Grapeleaf Skeletonizer Lepidoptera Zygaenidae Development and Adult Population Validation Environ Entomol 22 577 586 Sanderson J P M M Barnes and W S Seaman 1989 Synthesis and Validation of a Degree Day Model for Navel Orangeworm Lepidoptera Pyralidae Development in California Almond Orchards Environ Entomol
4. specify the leaf Wetness Threshold A typical setting is 6 The sensor range is from 0 15 This is a relative scale so no value is attached to the reading The model estimates three levels of infection likelinood The grower can determine which level is appropriate for his her op eration In general the IPM program usually begins when the minimum risk level is achieved The risk is measured on a scale of 1 to 3 Level 1 or Possible Infection means that an infection can occur but conditions or at least 1 condition are not optimal Thus the infection could be lighter or the risk is the lowest possible while still having a chance of infection Level 2 represents Medium Risk of Infec tion Level 3 or High Risk of Infection means that conditions are optimal for infection Individual growers can assess which level of risk meets their vineyard s management needs The model begins at any point above 43 F The primary infec tion starts at that point From then on the model estimates the risk of infection from secondary inoculum resulting from the pri mary infection Powdery Mildew Grape SpecWare predicts two infectious stages an ascospore stage and a conidial stage Thomas Gubler and Leavitt 1994 Weber Gubler and Derr 1996 Ascospores are released in the spring from the structure in which the disease overwintered Conidial spores are the result of an ascospore infection Ascospores cause primary infections and conidial spo
5. A Weather timed Fungicides Spray Program for Field Tomatoes in Ontario TOM CAST The Model Ridgetown College of Agricultural Technology Ridgetown ON Ries S M 1996 RPD 705 Downy Mildew of Grape http www aces uiuc edu ipm fruits rpds 705 705 html 2002 Dec 16 Schumann G L et al 1994 Use of Environmental Parameters and Immunoassays to Predict Rhizoctonia Blight and Schedule Fungicide Applications on Creeping Bentgrass Crop Protection 13 211 218 Schwarz M R and R C Pearson 1984 Grape IPM Disease Identification Sheet No 5 http Awww nysipm cornell edu factsheets grapes diseases downy_mildew pdf 2002 Dec 16 Smith T J 1993 A Predictive Model for Forecasting Fire Blight of Pear and Apple in Washington State Acta Horiculturae 338 153 157 Spotts R A 1977 Effect of Leaf Wetness Duration and Temperature on the Infectivity of Guignardia Bidwelli on Grape Leaves Phytopathology 67 1378 1381 Steiner P W and G W Lightner 1996 Maryblyt 4 3 A Predictive Program for Forecasting Fire Blight Disease in Apples and Pears University of Maryland College Park MD Stevenson W R et al 1996 Integrated Pest Management Professional Software For Agricultural Systems Version 1 31 06 University of Wisconsin Integrated Pest Management Program 116 Thomas C S W D Gubler and G Leavitt 1994 Field Testing of a Powdery Mildew Disease Forecast Model on Grapes in C
6. apat bhii Wall Dai iy Bi di Faraone Taup Hure law Had High Eik Warning DEE CERF O07 E 8 04 b bS E O lt 38 Ligia Infection Fisk T Ys 0d High infettiien Aisa 0 18 Moderate Infection Boh 6 00 6 0m Hoderans Infection Fisk Ligh Ee ewe dary Ti ae z Copy to Fie Piri i analy me wins Te Lz persed The ability of the inoculum to infect depends on tem perature and leaf wetness Jones and Sutton 2001 Cherry Leaf Spot requires temperature and leaf wetness to assess the degree of infection For information concerning the Select Report Where and When and Forecast screens please refer to the tools section of the SpecWare 6 02 Software Users Guide On the Options screen specify the leaf Wetness Threshold A typical setting is 6 The sensor range is from 0 15 This is a relative scale so no value is attached to the reading 13 Cherry Leaf Spot continued An unusual aspect of the model is the risk factor The models were originally designed to determine the risk of infection at a constant temperature for a certain period of leaf wetness How ever in the field temperature is rarely constant Unfortunately there is no data on this subject and shifts in temperature create a situation where an infection interval is not flagged because the average temperature was too low while the actual tempera ture during a portion of the wetness period was sufficient for an infection A tool for ass
7. button On the View Report screen the infection severity for Apple Scab appears The Mills and Washington State models denote either no infection potential or a Light Medium or Heavy infection potential The Cornell model only designates Infected when an infection is predicted The Mills model as modified by Jones requires fewer hours of leaf wetness at average temperatures 47 F or below to signal a risk for infection than does the Washington State model Both of these models denote a Light Medium or Heavy infection risk depending on the number of hours of leaf wetness at a given average temperature The Cornell model requires the fewest number of leaf wetness hours at all given temperatures and simply indicates Infected or not The Cornell model signals Infected with fewer leaf wetness hours than the other two models require to even signal a Light infection Fire Blight SpecWare will predict the onset of Fire Blight symptoms in apples and pears using two models University of Maryland Steiner and Lightner 1996 Cougar Blight Smith 1993 Fiew bgt 5 naien Fespa pyg wra iia eri Wee Gpo Tem i i Di p Bain h r pe api uer E yar Rigt Lo 3 oi b3 Fali fire GEETE EIH E Ei Sh HID sbods 7 38 7 8 7 14 mH i 0 03 j rmi TL IT Sire ddidi a 1 i d i iid 1 F ae 1 1i a3 r aLL 1 15 5 2 jai 4 4 gda The Fire Blight models require air temperature and leaf wetness data For information concerning th
8. insect or disease model developed for grapes in California probably is useful for grapes in New York The local university extension service should be contacted to verify that the model is appropriate for a particular region Apple Scab SpecWare will predict the approximate Infection Degree for Apple Scab The infection severity Light Medium Heavy or Infected is triggered by the accumulation of sufficient hours of leaf wetness that occur between the base and upper temperature limits The software includes three Apple Scab models Mills modified by A L Jones 1980 Washington State University Mills 1944 erer ewe cree Cornell University Gadoury Seem and Stensvand 1994 The Apple Scab models require temperature and leaf wetness data For information concerning the Select Report Where and When and Forecast screens please refer to the Tools section of the SpecWare 6 02 Software Users Guide Apple Scab continued In the Options screen enter the low and high limits of the temperature range in the Base and Upper Limit boxes The generally accepted temperature range is between 33 and 79 F Enter the Wetness Threshold above which you desire the software to consider the foliage wet Consult your State Agricultural Extension Service for assistance in determining the appropriate temperature and leaf wetness values for your area These parameters can be saved by clicking on the Save Parameters
9. Rothwell Model Infection Warning Thresholds are listed If these thresholds are met the software will display Infection otherwise the warning section remains blank Pythium Blight SpecWare will indicate specific infection events for the onset of Pythium Blight in turf Nutter Cole and Schein 1983 a Priha Bigh Ej iasc Paperi yee gad ai phere oemt we lepat Tmtection kiisk The Pythium Blight model requires air temperature and relative humidity data For information concerning the Select Report and Where and When screens please refer to the Tools section of the SpecWare 6 02 Software Users Guide The ability to Forecast weather data is not available for Pythium Blight Both the low and the high temperatures must attain a certain level On the Options screen specify the Low Temperature Over and High Temperature Over limits Also specify the Minimum Hours gt 90 RH The generally accepted temperatures are 68 F and 86 F The generally accepted hours of relative humidity greater than 90 needed to trigger Pythium Blight range from 9 to 18 Consult with your State Agricultural Extension Service for further information regarding appropriate values for your area Pythium Blight continued On the View Report screen the Pythium Blight disease model will give an Infection Risk index of 0 3 There are three thresholds that need to be met for the onset of Pythium Blight If none or one are met the Infection Warn
10. SPECWARE 6 02 FOR WINDOWS DISEASE AND INSECT GUIDE Optional Disease Models e Apple Scab e Botrytis e Black Rot e Brown Patch e Cherry Leaf Spot e Dollar Spot e Downy Mildew e Early Blight e FireBlight e Late Blight e Powdery Mildew e Pythium Blight Sooty Blotch Fly Spec e Tom Cast Optional Insect Models Spectrum Technologies Inc CONTENTS Optional Disease and Insect Models The Basics of Computer Modeling Apple Pear Disease Models Apple Scab Fire Blight Sooty Blotch and Flyspeck Turf Disease Models Brown Patch Dollar Spot Pythium Blight Potato Disease Models Early Blight Late Blight Tomato Disease Model Tom Cast Cherry Disease Model Cherry Leaf Spot 15 16 17 19 21 23 25 Grape Disease Models Black Rot Downy Mildew Powdery Mildew Botrytis Disease Model References Insect Models Insect Model References Software License Agreement 27 29 31 33 34 36 40 43 Optional Disease and Insect Models SpecWare software includes models to predict infection events for the following diseases and for insects These models are provided FREE for a 30 day evaluation If the user desires continued use of any of the disease or insect models after the evaluation period or if any model was purchased initially with SpecWare the user must contact Spectrum Technologies for a registration number Before calling Spectrum click on the Help button on the main toolbar Then click on
11. a pte ETA same lf apo art Co Bourn Kaure Risk Warming leaf wetness after apple flower petal fall Both fungi are dis persed by rainfall and their spores germinate in water Jones and Sutton 2001 Both models require air temperature and leaf wetness data For information concerning the Select Report and Where and When screens please refer to the tools section of the SpecWare 6 02 Software Users Guide On the Options screen specify the leaf Wetness Threshold A typical setting is 3 so noise is not included in the readings The sensor range is from 0 15 This is a relative scale so no value is attached to the reading Sooty Blotch and Flyspeck continued The model starts after 259 hours of leaf wetness have been ac cumulated Only leaf wetness periods of at least 3 hours are counted less than 3 hours are not included After the 259 hours have been accumulated the model starts Any 3 hour leaf wetness period after the start signals a possible infection period Different areas of the country may require a different number of leaf wetness hours to start the model Presently we use only the most conservative model i e the one that will give the ear liest warning Individual users of the models can choose to ig nore those infection predictions and run the model from the data by themselves On the View report the user can see the measured wetness hours the accumulated wetness hours and any message
12. alifornia Phytopathology 84 1070 abstract Weber E D Gubler and A Derr 1996 Powdery Mildew Controlled with Fewer Fungicide Applications Practical Winery amp Vineyard January February Insect Models SpecWare uses degree days to predict specific events in the life cycles of pest insects Pages 40 through 42 of this manual contain a list of the publications that describe each Insect Model in significant detail For information concerning the Where and When and Forecast screens please refer to the Tools section of the SpecWare 6 02 Software Users Guide To build a list of crop specific insects to monitor through the growing season highlight New Group on the Select Insects screen in the left hand window As the Available Insects are chosen in the middle window the citation for that insect model is shown in the text box below the list of insects Also in the text box is information concerning where the model was developed and on what host plant it was developed Click the Add button to include the model in the Group The maximum number of insect models that can be chosen for each group is twenty Clicking on a Selected Insect in the right hand window 18 will again display the citation for that model Highlight and click the Remove button to delete an insect from the Group After adding or deleting insects in a Group click on Save Group Insect Models continued NOTE To remove a previously saved Group f
13. are has a model for powdery mildew on grapes caused by the organism with the Latin name Uncinula necator However the disease organism that causes powdery mildew on apples is Podosphaera leucotricha and on blueberries it is Microsphaera penicillata Disease and insect models that are universally applicable to several different crops are the exception not the rule Therefore disease and insect models are usually developed for a particular crop and a specific pest organism Every computer model must include the assumption that the primary environmental conditions that affect the development of the disease or the insect can be measured SpecWare uses a variety of environmental sensors to model the progression of plant diseases SpecWare uses only degree days to model insect phenology The author of the disease or insect model must do a sensitivity analysis to assure that the model is being driven by the most important environmental data For instance the development of apple scab is believed to be affected by some wavelengths of red light However the inclusion of red light data has minimal added effect on the accurate modeling of apple scab The development of apple scab is primarily driven by temperature and leaf wetness Many conditions directly related to the host plant affect insect and disease development These conditions may include the availability of insect preferred fruit on which to feed or lay eggs or the type of plant structu
14. e Select Report Where and When and Forecast screens please refer to the Tools section of the SpecWare 6 02 Software Users Guide On the Options screen choose Apple or Pear As the season progresses enter the 50 Green Tip Date First Bloom Date and Last Petal Fall Date Whenever a Spray Date or a Trauma Event Date occurs enter those as well After each entry click the Save Parameters button to avoid having to re enter the dates Fire Blight continued On the View Report screen the results of the University of Maryland model and the Washington State University model Cougar Blight appear University of Maryland Model developed by P W Steiner and G W Lightner SpecWare will predict specific infection events and the appearance of blossom canker and shoot blight symptoms The model uses three cumulative heat unit measures to indirectly monitor development of the host the pathogen insect vectors and Fire Blight symptoms Steps Green Tip from green tip date until Canker blight symptoms Blossom from first blossom date until Blossom blight symptoms 198 Degree Hours gt 65 requirement met Wetness dew or rain requirement met Average Temperature gt 60 gI W G is initiated by entering a 50 green tip date on the options screen B H W and T are active only during the bloom period as entered on the options screen EIP EIP Epiphytic Infection Potential is an index for infection risk EIP is the perc
15. entage of 198 DH gt 65F that have accumulated in the last 80DD gt 40F apple or 120DD gt 40F pear An EIP of 100 is the threshold for infection Symptoms Cumulative DD gt 55F are used to predict symptom development once infection has occurred The number in the symptom col umn represents the percentage of the threshold met by the conditions A symptom value of 100 indicates that symptoms are present That is 100 of the temperature or degree day requirements have been met for the blossom canker or shoot blight symptoms to be readily apparent The following describes the symptom and the threshold Ck Canker Blight Canker blight is predicted with the accumulation of at least 196 DD gt 55 F after green tip BI Blossom Blight The model assumes an abundance of inoculum conditions need to be met for a blossom infection to occur Four 1 Flowers with stigmas and petals intact need to be present 2 Accumulation of at least 198 DH gt 65 F within the last 80 DD gt 40 F apple or 120 DD gt 40 F pear 3 Occurrence of dew or rain of 0 10 inch or more during the current or previous day 4 Daily average temperature greater than or equal to 60 F When all minimum conditions are met in sequence infection occurs and the first blossom blight symptoms can be seen after an additional accumulation of 103 DD gt 55 F The cumulative DH gt 65F are reduced by one third one half or reset to zero if the temperature does not surpas
16. essing the temperature shifts during a wetness period is the risk rating Basically if the model is run on a 15 minute interval the risk of infection at that point is cal culated For example if at a certain temperature 8 hours of wetness are required and it is wet at that temperature for 1 hour the risk is 1 8 If the sum of the risks is 1 or greater there has been in all likelihood an infection period and the period is flagged as such There are three levels of infection risk light moderate and high The user can decide what risk level is acceptable for economic control The View option gives a report of the temperature leaf wet ness infection flag warning and the risk factor Black Rot Black Rot is a disease caused by the fungus Guignardia bidwelli It overwinters in in old mummified berries In spring the primary inoculum is released which starts the initial round of infection Those initial spores are dispersed by rain and wind After the initial infection period secondary infections are spread by rain splash This model predicts infection periods of Black Rot based upon the Spotts model The Black Rot model requires air temperature and leaf wet ness data For information concerning the Select Report Where and When and Forecast screens please refer to the tools section of the SpecWare 6 02 Software Users Guide On the Options screen specify the Wetness Threshold or the point on the scale the ope
17. he range of 70 F to 85 F and on days with a maximum temperature greater than 95 F The index will always be between zero and 100 Conidial Index 0 30 Light infection risk 40 50 Medium infection risk 60 100 Heavy infection risk 16 Botrytis The disease Botrytis is caused by the pathogen Botrytis cinerea The pathogen is spread in the air and infects primarily post veraison berries and flowers The disease develops best in cool humid It appears as gray cottony structures on the infected plant weather eran Gpe parts The Botrytis model requires air temperature and leaf wetness data For information concerning the Select Report Where and When and Forecast screens please refer to the tools section of the SpecWare 6 02 Software Users Guide There are no Options to be entered for Botrytis The model is based on work done at the University of California at Davis The model is adjusted for temperature and does not calcu late values for temperatures greater than 40C UC Davis recom mends taking action at an index of 0 5 or above There are three levels of infection risk light moderate and high The user can decide what risk level is acceptable for economic control The View option gives a report of the temperature leaf wetness infection flag warning and the risk factor 17 Disease Model References Bolkan M A and W R Reinert 1994 Developing and Implementing IPM S
18. hold Temperatures and Duration of the Nymphal Stages of the Meadow Spittlebug Philaenus Spumarius Environ Entomol 8 682 685 Croft B A M F Michels and R E Rice 1980 Validation of a PETE Timing Model for the Oriental Fruit Moth in Michigan and Central California Lepidoptera Olethreutidae Great Lakes Entomol 13 211 217 Engle C E and M M Barnes 1983 Developmental Threshold Temperature and Heat Unit Accumulation Required for Egg Hatch of Navel Orangeworm Lepidoptera Pyralidae Environ Entomol 12 1215 1217 Grout T G W J Dutoit J H Hofmeyr and G I Richards 1989 California Red Scale Homoptera Diaspididae Phenology on Citrus in South Africa J Econ Entomol 82 793 798 Hartstack A W Jr J P Hollingsworth R L Ridgeway and J D Lopez 1976 MOTHZV 2 A Computer Simulation of Heliothis Zea and Virescens Population Dynamics User Manual 1976 U S D A ARS S 127 20 Horton D R B S Higbee T R Unruh and P H Westigard 1992 Spatial Characteristics and Effects of Fall Density an Weather on Overwintering Loss of Pear Psylla Homoptera Psyllidae Environ Entomol 21 1319 1332 Integrated Pest Management for Apples and Pears University of California Statewide Integrated Pest Management Project Div Agr Sci Publ 3340 Integrated Pest Management for Walnuts University of California Statewide Integrated Pest Management Project Di
19. ing will be blank If 2 or 3 of the thresholds are met the software will tell you how many are met and which still need to be met for the continued progression of the disease Early Blight Potato SpecWare will predict sporulation and thereby the secondary spread of the Early Blight pathogen on potato leaves mm Ecole Eih Pooti Fasci Mapori hms d a pte onee Ter lepat Pat Ps bH Panty amp Buy Tall Hearse Tanp FOeye fom j E Warning FL 0 5 7 l 14 8 7 Fok DOE L E W FP Deyr reached rr O ue Se E Er D e r A A a ae jh a Stevenson Binning Connell Wyman and Curwen 1996 The Early Blight Potato model requires air temperature relative humidity and rainfall data For information concerning the Select Report Where and When and Forecast screens please refer to the Tools section of the SpecWare 6 02 Software Users Guide There are no Options to be entered for Early Blight On the View Report screen the P Days and RV s Rating Values are shown The P Day is a measure of the temperature conditions contributing to potato growth Potatoes grow between 45 F and 86 F with the optimum temperature being 70 F The calculation of P Days assumes that the plants spend three hours at the maximum temperature for the day five hours at the minimum temperature for the day and the remaining 16 hours between the daily maximum and minimum Early Blight Potato continued te
20. ion have been met information concerning the remaining unmet thresholds will be given The Infection Warning Thresholds are listed at the end of the disease report screen Dollar Spot SpecWare will indicate specific infection events for the onset of Sclerotinia Dollar Spot in turf The software includes two Dollar Spot models Hall Model Hall 1984 a Scheer Dol 5 peel gates f tepai yee amd ahar pira onem Te lepat PILE 74 8 F E 0 Infeenies Infecnicn a0 1 PF Dit 0 OG Indecnion Infecnicom pF ETE 166 06 Of Eateries Inter en PF 5 7 0 07 Indecnice Infecti mi a B S FF E 0 28 Inftettiicn Infection 74 i i FP F R Dn bapi isn UT 7 3 4 I 7 u e Infectia Err TE h F Pi d oe Da Pee Len Hail Atel Inbectian Barning Thradhs lta ear Feng alure gets FE ngh Bele for T y dayi of Haan Teepecamure abere 4 with Faim foc thras dave Aidlesbechuwl High Teaperacure above TI Aolel Infection Warning Threshy ide with Gl abvve 308 any three day in raren Pri Wie ad Fie Mills Rothwell Model Mills and Rothwell 1982 The Dollar Spot model requires air temperature relative humidity and rainfall data For information concerning the Select Report Where and When and Forecast screens please refer to the Tools section of the SpecWare 6 02 Software Users Guide There are no Options to be entered for Dollar Spot On the View Report screen the Hall Model Infection Warning Thresholds and the Mills
21. mperature No P Days are accumulated below 45 F or above 86 F Sprays are not recommended for Early Blight control until 300 P Days have accumulated The Warning column in dicates when this threshold has been reached The spray interval for Early Blight is indicated by the RV Rating Value The RV is a result of the accumulation of P Days hours of relative humidity and rainfall The 5 day RV is used to establish the appropriate spray interval for the crop Contact your State Agricul tural Extension Service for more information about using the RV for timing Early Blight sprays 10 Late Blight Potato SpecWare predicts the spread of the Late Blight pathogen on im Lale Bighi Potala ele Fogat wits ane When Deer Foresaa Yer epee bitt Fie wi 0 E 0 Heer Ipiiy Hesry Jpoey b Heap Fpray 3 Hesry Jpray 10 Beery Jpray aD Hoary pee D Hesry Jpray potato leaves using BLITECAST Krause 1975 The Late Blight Potato model requires air temperature relative humidity and rainfall data Massie and Hyre For information concerning the Select Report Where and When and Forecast screens please refer to the Tools section of the SpecWare 6 02 Software Users Guide Itis recommended that the earliest Process Date on the Where and When screen be the date that distinct green rows are seen in the field On the Options screen enter the Blight First Forecast Date as predicted or observed to limit
22. nservative than con stant temperature since it may include borderline events The View option gives a report of the temperature leaf wet ness infection flag warning and the risk factor 14 Downy Mildew Downy Mildew is caused by the pathogen Plasmapora viticola The pathogen overwinters in dead leaves and sometimes in dead berries and shoots The initial inoculum or liberated spores are splash dispersed After the initial round of infection a secondary cycle of spores is started which are splash or wind dispersed Once a secondary spore lands on a leaf or twig or grape cluster it can germinate in a short period of time if a thin film of water is present The infection takes 5 to 18 days to de velop new inoculum depending on humidity and temperature An understanding of the wetness periods when infection might occur will help in the proper timing of fungicides This model ficeeeeeed notes when primary infection could occur and when secondary infection is possible The model is based on Cornell University UC Davis and University of Illinois spray recommendations The Downy Mildew model requires leaf wetness RH and temperature data to calculate the appearance of spores after the initial infection 15 Downy Mildew continued For information concerning the Select Report Where and When and Forecast screens please refer to the tools section of the SpecWare 6 02 Software Users Guide On the Options screen
23. on the Report by Date screen Insect Model References Aliniazee M T 1976 Thermal Unit Requirements for Determining Adult Emergence of The Western Cherry Fruit Fly Diptera Tephritidae In the Willamette Valley of Oregon Environ Ent 5 397 402 Aliniazee M T 1979 A Computerized Phenology Model for Predicting Biological Events of Rhagoletis indifferens Diptera Tephritidae Can Ent 111 1101 1109 Bethell R S 1978 Pear Pest Management U C Div Agr Sci Publ 4086 pp 22 41 Bettiga L J H Kido And N F Mccalley 1992 Orange Tortrix IN Grape Pest Management 2nd Edition U C Div Agr Sci Publ 4105 Bimboni H G 1970 The Relation of Variation in Temperature to the Rate of Development of Immature Stages of California Red Scale Aonidiella aurantii Maskell on Citrus Masters Thesis Department Of Entomology University Of California Riverside Brunner J F And R E Rice 1984 Peach Twig Borer Anarsia Lineatella Zeller Lepidoptera Gelechiidae Development in Washington and California Environ Entomol 13 607 610 Charmillot P J R Vallier and S Tagini Rosset 1979 Plum Fruit Moth Grapholitha Funebrana Tr Study of The Life Cycle in Relation to the Sums of Temperature and Considerations on the Activity of the Adult Moths Bulletin de la Societe Entomologique Suisse 52 19 33 Chmiel S M and M Curtis Wilson 1979 Estimation of the Lower and Upper Developmental Thres
24. ot and Anthracnose Pitblado 1985 Bolkan and Reinert 1994 Tom Cast calculates a disease severity value DSV to predict the development of these diseases M iaci fia 1 Jal ee cra in wees Dac aci Hapori hes ana e an Upis Tosza eee A Wer Ere Faricds Wee Taap Be Po Write ed Hie Fira The Tom Cast model requires air temperature and leaf wetness data For information concerning the Select Report and Where and When screens please refer to the Tools section of the SpecWare 6 02 Software Users Guide The ability to Forecast weather data is not available for Tom Cast On the Options screen Specify the Temperature Base Upper Limit and leaf Wetness Threshold On the View Report screen an increasing number of leaf wetness hours and a higher temperature cause the DSV Tom Cast continued disease severity value to increase at a faster rate A Cumulative DSV of 15 to 20 is usually viewed as the threshold for initiating a spray program Contact your State Agricultural Extension Service for further information regarding disease management in your area 12 Cherry Leaf Spot The pathogen responsible for Cherry Leaf Spot is Blumeriella jaapi Itis a fungus that overwinters in diseased leaves Pri mary inoculum spores are released into the air The secondary inoculum that which follows the first infection is splash dis Derpy Leal Spa xi Tasi ept ame srad wen Orton Doppa fee
25. p Development Scaffolds Fruit Journal Sept 18 2000 Vol 9 No 27 Laing J E and J M Heraty 1984 The Use of Degree Days to Predict Emergence of the Apple Maggot Rhagoletis Pomonella Diptera Tephritidae in Ontario Can Ent 116 1123 1129 Lin S Y H and J T Trumble 1985 Influence of Temperature and Tomato Maturity on Development and Survival of Keiferia Lycopersicella Lepidoptera Gelechiidae Environ Entomol 14 855 858 Osborne L S 1982 Temperature Dependent Development of 21 Greenhouse Whitefly and Its Parasite Encarsia Formosa Environ Entomol 11 483 485 Peach Twig Borer IN Integrated Pest Management For Almonds University of California Statewide IPM Project Div Agr Sci Publ 3308 Pickel C N C Welch and D B Walsh 1990 Timing Lygus Sprays Using Degree Days in Central Coast Strawberries Santa Cruz County Agricultural Extension Publication Pickel C P R S Bethell and W W Coates 1986 Codling Moth Management Using Degree Days University Of California Statewide IPM Project Publication 4 Pinhassi N D Nestel and D Rosen 1996 Oviposition and Emergence Of Olive Scale Homoptera Diaspididae Crawlers Regional Degree Day Forecasting Model Environ Entomol 25 1 6 Pitcairn M J F G Zalom and R E Rice 1992 Degree Day Forecasting of Generation Time of Cydia Pomonella Lepidoptera Tortricidae Populations in California Environ
26. rator wishes to consider the leaf to be wet the scale is 0 15 A typical threshold is 6 Black Rot continued This model uses temperature and leaf wetness period to esti mate the onset of an infection period The temperature is com pared with the period of leaf wetness needed to produce an ob servable infection If the wetness period exceeds the required period for that temperature the period is given an infection flag warning An unusual aspect of the model is the risk factor The models were originally designed to determine the risk of infection at a constant temperature for a certain period of leaf wetness How ever in the field temperature is rarely constant Unfortunately there is no data on this subject and shifts in temperature create a situation where an infection interval is not flagged because the average temperature was too low while the actual tempera ture during a portion of the wetness period was sufficient for an infection A tool for assessing the temperature shifts during a wetness period is the risk rating Basically if the model is run on a 15 minute interval the risk of infection at that point is cal culated For example if at a certain temperature 8 hours of wetness are required and it is wet at that temperature for 1 hour the risk is 1 8 If the sum of the risks is 1 or greater there has been in all likelihood an infection period and the period is flagged as such This approach is more co
27. re that the insects use as cover from their enemies Diseases may be affected by plant nutritional status or the presence of non disease fungal species that compete with the disease causing organism for space or resources Pears and apples can both be infected with fire blight and SpecWare allows the user to specify apples or pears in the fire blight model This feature is present because the rate of infection is different for apples versus pears In fact the rate of infection is slightly different even among different varieties of apples To carry this example further soft rapidly growing tissue is more susceptible to fire blight than is older harder tissue In this case the grower s experience concerning how much nitrogen to apply and the effects of that fertilizer application for a particular cultivar should be considered as part of the IPM program to control fire blight Developing disease and insect models must necessarily be accomplished at some particular geographic location This is important because for each region of the country different climatic conditions exist different organisms that compete for space are present and slightly different genetic variations occur in the pest species For that reason some models such as apple scab and fire blight specify that they are from New York or Washington or Maryland Also for reasons of regional differences the insect models show the location in which they were developed For example an
28. res cause secondary infections Your State Agricultural Extension Service a Pomiar Mhira Gage Select Repor Where ond aken Daton Forecen Verw Henen Meare Weare whe War Aecorpors Wivurr Infection Teepe recurs It gh Esan feds bighi Relius Lighr Lighe Ligne 20 Lugar 10 Ligh hho o oo Cc SCO TOTT oo E Winia Dai File can advise you about which stage is important in your area The Powdery Mildew models require air temperature and leaf wetness data For information concerning the Select Report and Where and When screens please refer to the Tools section of the SpecWare 6 02 Software Users Guide The ability to Forecast weather data is not available for Powdery Mildew On the Options screen specify the Temperature Base Upper Limit and leaf Wetness Threshold Powdery Mildew Grape continued On the View Report screen Ascospore Infection risk is determined using the daily average temperature and the hours of leaf wetness A modified Mills Table 2 3 the original Mills leaf wetness value is used to determine the development of a Heavy Ascospore Infection the point at which treatment should begin Three consecutive days with temperatures between 70 F and 85 F are required to initiate the Conidial Index Thereafter the index increases by 20 with each day having six hours between 70 F and 85 F The index decreases by 10 on days with less than six hours in t
29. rom the Select Insects screen use the Remove button to remove all of the insect models from the Group and then exit Insect Models Upon re launching Insect Models the Group will no longer be present Choosing an Insect Group on the Select Insects screen and then going to the Model Detail screen allows the user to enter separate Event and Spray Dates for each insect at each logger location A drop down menu at the top of the screen lists each of the insects in the chosen Group The left hand and lower text boxes display the degree day targets for each Event and supporting information for each insect model in the Group Highlight the Event or Biofix in the left hand box and enter the LESILE ET TELE nad Ltn Seal Vine ate liit Ding ee e470 1 ig FETTA cast nt ng Ad Lie f bar Ef e fu f Jp paper vg bial Coogi fF s Datel tow legac bigal dg Rus LL a an Fe be fe Pi papa Paii Laamani Jn Eion Ui Hanga Tam hy i ey Ali Crkinrriem Meiri uhan 19 Event Date in the right hand box Click Set Event Date to record the date Highlighting Biofix Start and entering a date will cause all subsequent Events to be calculated using that date as a starting point To mark Spray Dates in the reports enter the date in the right hand box and click Set Spray Date Insect Models continued IMPORTANT It is possible to have multiple generations of a particular insect per year As the season progresses not all generation
30. rtis Wilson 1989 Heat Unit Model for the Development of Meadow Spittlebug Homoptera Ceropidae on Strawberry Environ Entomol 18 347 350 Zalom F G W W Barnett R E Rice and C V Weakley 1992 Factors Associated With Flight Patterns of the Peach Twig Borer Lepidoptera Gelechiidae Observed Using Pheromone Traps J Econ Entomol 85 1904 1909 Software License Agreement Spectrum Technologies retains certain rights regarding the use of this software Please refer to the Software License Agreement in the SpecWare 6 02 for Windows Software User s Guide 22 Spectrum Technologies Inc 2002 All rights reserved Spectrum Technologies Inc 23839 W Andrew Rd Plainfield IL 60544 800 248 8873 or 815 436 4440 Fax 815 436 4460 E Mail info specmeters com www specmeters com
31. s a threshold of 64F during one two or three days respectively However once 400 DH gt 65 F have accumulated EIP 200 no negative adjustments are made Fire Blight continued Sh Shoot Blight The program forecasts only very early shoot blight symptoms These early symptoms usually develop with the accumulation of 103DD gt 55 F following the first appearance of either blossom or canker blight symptoms in the immediate area The average daily temperature must be 60 F or greater Cougar Blight Model developed by T J Smith Under the Cougar heading there is a lettered Pathogen Potential a to e that is used to estimate the presence of Fire Blight innoculum For each level of innoculum present a numbered Infection Risk 0 to 4 predicts the severity of an infection Pathogen Potential No Fire Blight in area in past two seasons Fire Blight in local area in past two seasons Fire Blight in local area last year Fire Blight in orchard last year Active cankers present nearby 9Qandcoy Infection Risk 0 Very Low 1 Low 2 Low Moderate 3 Moderate 4 High Sooty Blotch and Flyspeck Sooty blotch is a disease complex i e it is composed of more than 1 pathogen of two fungi Peltaster fruticola and Leptodon tium elatius Flyspeck is caused by another fungus Zygiophiala jamiacace nis SpecWare predicts the period of risk for infection based on Appie Dootp Bike ch Gatect Pepest yee and ah
32. s not ing the start of an infection period Brown Patch SpecWare will indicate specific infection events for the onset of Schumann Clarke Rhyzoctonia Brown Patch in turf w Alppresctoree Baers Pah Fasci Mapori Yates gd a pte oemt Te lepat fn fae ior Warning E Teig EHPA Talin Aaa Heare Fall e249 es MT 4 i Vis 4 5 P E rpp for 10 hyure 2 JOPPES 8 Le EI E n J 14 L fi i LEPE gaT ER i e PE oF a 1 heen Fil Tanp below TH the 5 eo TLL Fl LETE 1 2 0 3 OE Le cram ah 1 PE 5 oo J Haste LORE N G ird 78 F 4 4 6 68 d a pi arm H rnirg Theme ae foi Teeperapore Meam above TO 541 Teepareture Lew ibiF 4 hir Pempeeuie Pleas abhi ie Air Temperatura Lew abore EF al b z EF Lh Th Daat P hiari Varna L tented Ie lacivs Bupidiey pEi dar at Legos 10 Bere Fainiall of a Leet 0 1 inched Pri wis Teel Fie Rowley and Burpee 1994 The Brown Patch model requires air temperature soil temperature relative humidity and rainfall data For information concerning the Select Report Where and When and Forecast screens please refer to the Tools section of the SpecWare 6 02 Software Users Guide There are no Options to be entered for Brown Patch On the View Report screen for Brown Patch an Infection Warning appears The infection warning column will indicate how many of six thresholds have been met for the onset of Brown Patch If most of the thresholds for infect
33. s will develop at the same rate This is due to differences in food quality and in parameters such as relative humidity Therefore no attempt was made to extrapolate data from a model published for a single generation to include second and third generations insect activity as However based on the users personal observations of the season progresses events in subsequent generations can be approximated by updating the Biofix Date on the Model Details screen The Report by Insect screen lists the insects in the chosen Group and their associated Events For each individual insect model the first two columns display the Predicted degree day accumulations and the range of those degree day predictions for each event The third and fourth columns show the Computed degree day accumulations that have been associated with a particular event and the Date of occurrence For Events that have yet to occur the Percent amount of the target degree days that have been met is shown The fifth column displays the Event ineee Models Yardi Oieup sepia ee ee a r ra ie he i a a Insect Models continued The Report by Date screen displays the modeled insects and their associated events in the sequence in which those events occurred The Date and the daily High and Low temperatures are shown to the left of the columns of accumulated degree day data If Spray Dates have been entered on the Model Details screen they are also displayed
34. the calculation for the progression of the disease only to later dates The ability to enter the Blight First Forecast Date allows SpecWare to avoid having to spend time recalculating the initial infection date every time the model is used Enter the Last Spray Date as a record 11 of spray activity Click on Save Parameters to avoid having to re enter the dates Late Blight Potato continued On the View Report screen Rain favorable Days Severity Value and spray Warning are reported Cool wet weather with periods of relative humidity greater than 90 provide ideal growing conditions for Late Blight Hyre and Wallin have each developed methods for predicting the initial occurrence of Late Blight Once Late Blight is triggered a single method common to both Hyre and Wallin is employed to predict the progression of the disease Accumulation of Rain favorable Days and Severity Values begins at plant emergence Severity Values are based on the average temperature and the number of hours the crop experiences 90 or greater relative humidity during that period The warning Blight Triggered initially occurs with the accumulation of 10 consecutive Rain Favorable days or with the accumulation of a Severity Value of 18 Spray warnings are the result of further accumulations of Rain Favorable days and Severity Values Tom Cast SpecWare uses Tom Cast a TOMato disease foreCASTing program designed to predict Early Blight Septoria Leaf Sp
35. trategies to Assist Farmers An Industry Approach Plant Disease 78 545 550 Broome J C et al 1995 Development of an Infection Model for Botrytis Bunch Rot of Grapes Based on Wetness Duration and Temperature Phytopathology 85 97 102 Gadoury D M R C Seem and A Stensvand 1994 N Y Fruit Quarterly 2 4 5 8 Gruber et al 1999 UC IPM UC Management Guidelines for Downey Mildew on Grape http Awww ipm ucdavis edu PMG r302101111 html 2002 Dec 16 Hall R 1984 Relationship Between Weather Factors and Dollar Spot of Creeping Bentgrass Canadian Journal or Plant Science 64 167 174 Jones A L et al 1980 A Microcomputer based Instrument to Predict Primary Apple Scab Infection Periods Plant Disease 64 69 72 Jones A L and Sutton T B 2001 Diseases of Tree Fruits of the East Michigan State University Extension 19 20 57 60 Krause R A L B Massie and R A Hyre 1975 Blitecast a Computerized Forecast of Potato Late Blight Plant Disease Reporter 59 95 98 Mills S G and J D Rothwell 1982 Predicting Diseases the Hygrothermograph Greenmaster 18 4 14 Mills W D 1944 Efficient Use of Sulfur Dusts and Sprays During Rain to Control Apple Scab N Y Agriculture Experiment Station Ithaca Extension Bulletin 630 Nutter F W H Cole and R D Schein 1983 Disease Forecasting System for Warm Weather Pythium Blight of Turfgrass Plant Disease 67 1126 Pitblado R E 1985
36. v Agr Sci Publ 3270 pp 36 41 Johnson D T and R L Mayes 1983 Studies of Larval Development and Adult Flight of the Peachtree Borer Synanthedon Exitiosa Say in Arkansas J Georgia Entomol Soc 19 216 223 Jones V P D G Alston J F Brunner D W Davis and M D Shelton 1991 Phenology of the Western Cherry Fruit Fly Diptera Tephritidae in Utah and Washington Ann Entomol Soc Am 84 488 492 Jones V P D W Davis S L Smith and D B Allred 1989 Phenology of Apple Maggot Rhagoletis Pomonella Diptera Tephritidae Associated with Cherry and Hawthorn in Utah J Econ Entomol 82 788 782 Jones V P S L Smith and D W Davis 1990 Comparing Apple Maggot Adult Phenology in Eastern and Western North America IN Dowell R V L T Wilson And V P Jones Eds Apple Maggot in the West History Biology and Control University of California Division of Agriculture and Natural Resources Publication 3341 Jorgensen C D R E Rice S C Hoyt and P H Westigard 1981 Phenology of the San Jose Scale Homoptera Diaspididae Can Ent 113 149 159 Judd G J R M G T Gardner and D R Thomson 1993 Temperature Dependent Development and Prediction of Hatch of Overwintered Eggs of the Fruit tree Leafroller Archips Argyrospilus Walker Lepidoptera Tortricidae Can Entomol 125 945 956 Kain D and A Agnello 2000 Insects Update on Pest Management and Cro
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