Small Grains Commodity-Based Survey Guideline

Small Grains Commodity-based Survey Guideline

31 March 2008 Last revision August 2010 Melinda Sullivan and Edward Jones USDA APHIS Plant Protection and Quarantine Center for Plant Health Science and Technology

Table of Contents

Chapter 1: Introduction…………………………………………………………………………………………………………………….…5

Purpose of Document 5

What is a small grain? 5

Location of Surveys 8

Time Frame 8

Organisms to be Surveyed 8

Chapter 2: Survey Design & Sampling Methodology .………………………………………………………………..…..11

Introduction 11

Summary of Action Steps 11

Objective of Survey 12

Population to be Sampled 12

Data to be Collected 12

Degree of Precision Re- 13 quired The Frame 13

Selection of sampling plan 15 and sample selection Methods and Units of Meas- 19 ure

Pre-test 21 The Organization of Field 21 Work

Summary and Analysis of 21 Data Gaining Information for Fu- 21 ture Surveys

Chapter 3: Summary of Survey Strategies…………………………………………………………………………………..22

Visual Survey 22

Trapping 28

Soil Sampling 28

Chapter 4: Pest Tables…………………………………………………………………………………………………………..29

Pests by affected plant part 29

Pests by available survey 30 method

Chapter 5: Detailed Survey Tables………………………………………………………………………………………………31 Autographa gamma 31 Copitarsia spp. 32 Diabrotica speciosa 33 Helicoverpa armigera 34 Heteronychus arator 36 Lobesia botrana 37 Nysius huttoni 39 Spodoptera littoralis 40 Spodoptera litura 41 Cernuella virgata 42 Cochlicella spp. 43 Heterodera filipjevi 44 Heterodera latipons 45 Meloidogyne artiellia 46 Peronosclerospora philippinensis 47

Chapter 6: Identification Tables…………………………………………………………………………………………………48

Autographa gamma 48 Copitarsia spp. 51 Diabrotica speciosa 54 Helicoverpa armigera 56 Heteronychus arator 58 Lobesia botrana 60 Nysius huttoni 62 Spodoptera littoralis 64

Spodoptera litura 66 Cernuella virgata 68 Cochlicella spp. 69 Heterodera filipjevi 70 Heterodera latipons 72 Meloidogyne artiellia 74 Peronosclerospora philippinensis 76

Appendix A…………………………………...…………………………………………………………………………………………………..78

Appendix B…………………………………………………………………………………………………………………………..85

Appendix C………………………………………………………………………………………………………………………….90

Draft Log: The state of science is advancing faster than most documents in print can be updated. As such, this document is entitled “perpetual draft” with the intention of making updates as they are appropriate. Updates might include the inclusion of new high risk pests that are identified, inclusion of new survey methodology for existing pests, or removal of current pests that no longer pose a high risk or have become well established in the United States. In order to keep track of changes in the document, please find the draft log listed below. The date of the current draft is listed on the cover page.

Original Submission: March 2008 Revised Submission: May 2008

August 2010: Added Diabrotica speciosa. Added Appendix M information and removed outdated information. Updated survey chapter and appendices. Adjusted scale of photographs. Fixed several typographic er- rors. Updated hyperlinks.

Chapter 1: Introduction

Purpose of Document: Welcome to the Small Grains Commodity-based Survey Guideline. This document is intended to be a tool to assist you as you develop pest detection survey plans in your respective states for exotic pests of small grains. A detection survey determines the presence or absence of a pest but does not delimit a pest or establish the preva- lence of a pest. This is a companion document to the Small Grains Commodity- based Reference, available at the CAPS website (Figure 1.1). The Small Grains Commodity-based Survey Reference is a collection of detailed datasheets on 20 pests, endemic pests easily confused with exotic pests, and potential vectors of exotic pests. These datasheets contain information on the biology, host range, survey strategies, and identification of these pests.

The Small Grains Commodity-based Survey Guideline is the result of a concerted effort to help states focus resources on survey efforts and identification of a smaller group of target pests. This guide contains little information about biology. We must acknowledge that there is no silver bullet survey that would be wholly applicable to each state. Environment, personnel, budgets, and resources vary from state to state. However, as state participants in the Coopera- tive Agricultural Pest Survey (CAPS), you can take steps to increase the uniform- Figure 1.1 Cover Page of the ity and usability of data across political, geographic, and climatic regions, while Small Grains Commodity –based Reference. This document con- maintaining flexibility for appropriateness within individual regions. This manual is tains pest datasheets on the not intended to be a field guide to identify exotic pests in the field and distin- most threatening exotic pests of guish the exotic pest from commonly occurring pests. The purpose of this man- small grains including information ual is to provide a framework to aid cooperators in collecting the best samples on biology, survey, and identification. The document is avail- to send to a qualified taxonomist or diagnostician for pest identification. Consid- able for download from the erable diagnostic or taxonomic expertise may already exist in your state. CAPS website. The survey methods described in this document combine survey strategies for exotic pests, including arthropods, plant pathogens, and nematodes. It is important to note that these broad categories have unique biological features that dictate current methods of survey. However, each category is grouped according to an appropriate sampling method within the context of this manual

This Commodity-based Survey Guideline is intended to be implemented over several years with the initial field survey year beginning in FY 09. Portions of the recommendations may need clarification or adjustment as funding levels change, new threats are identified, or detection technologies improve. The transition to commodity based survey has just begun, and as such, end user feedback will be imperative to the creation of a useful end-product for small grains and other commodities of large economic importance. National survey methodologies as established will take precedence over the methods described in this manual. Meth- ods listed in Appendix M of the National Survey Guidelines will also take precedence over the methods described.

Table 1.1 Small grains value and usage

What is a Small Grain? The small grains, Grain 2006 U.S. Value Primary usage wheat, barley, oats and rye, are collectively some of the most important food and feed crops Barley 497,573 Animal food, malting, in the United States. All of these important crops are grasses in the family Poaceae and are culti- Oat 174,288 Human and animal food vated worldwide. The four crop species were Forage, animal food treated as a group in this manual because of the Rye 23,519 similar pest problems and agronomic practices. Wheat 7,721,028 Human food, fermenta- Related crop species like rice will be reviewed in a separate manual. Total 8, 416,408

Chapter 1: Introduction

Location of Surveys: Note that the locality scope of the Survey Guideline is limited to the contiguous United Time Frame: The Survey Guideline is States. The acreage by county is shown in Figure 1.2 and the intended to be carried out as a multi-year value for the top 5 producing states for each small grain survey. State and federal priorities, re- covered in this manual is shown in Figure 1.3. sources, and funding, however, may influence whether the survey can be carried out for multiple years. Future versions of this manual may call for ongoing surveys following the same or a slightly modified Table 1.2. Pests targeted in the CAPS Small Grain Commodity protocol. The multi-year time frame has advantages because states will have more opportunity to collect data over a

Scientific Name Common Name Type of Pest larger time-scale. Negative data collected over several years using a statisti- Autographa gamma Silver-Y moth Arthropod- cally based protocol can be influential in Moth scientific, political, and trade arenas. Copitarsia spp. Owlet moths Arthropod- Moth

Diabrotica speciosa Cucurbit beetle Arthropod- beetle

Helicoverpa armigera Old world bollworm Arthropod- Moth

Heteronychus arator African black beetle Arthropod- beetle

Lobesia botrana European grapevine Arthropod– moth Moth Organisms to be Surveyed: The Nysius huttoni Wheat bug Arthropod— scope of surveyed organisms within the Sur- bug vey Guideline is limited to a sub-group of pests from the Small Grains Commodity Sur- Spodoptera littoralis Egyptian cotton leaf- Arthropod- vey Reference from the FY 09’ Analytical worm Moth Hierarchy Process (AHP) Prioritized Pest List. Spodoptera litura Rice cutworm Arthropod- This sub-group includes 9 arthropods, 2 mol- Moth lusks, 3 nematodes, and 1 fungus-like plant pathogen. The scientific name and com- Cernuella virgata Maritime garden snail, Mollusk mon names of these pests are shown in Ta- white snail ble 1.2. Photos of each pest are given in Cochlicella spp. Conical snails Mollusk Figure 1.4, and the relative host status of each small grain is given in Table 1.3. Heterodera filipjevi Cereal cyst nema- Nematode tode Many of the pests targeted in this survey Heterodera latipons Mediterranean cereal Nematode can be detected visually or by collecting cyst nematode samples of plant tissues. As a result, 1-2 trips for each survey should be adequate. For Meloidogyne artiellia British root-knot nema- Nematode most of the arthropods, pheromone lures tode are available, and use of these lures with Peronosclerospora Philippine downy mil- Fungus-like traps will require a minimum of two trips per philippinensis dew site. Field personnel are encouraged to in-

Note: With the exception of Cernuella virgata, Lobesia botrana, and Heterodera filipjevi, no other pests on in this guideline have been detected in the continental U.S. C. virgata has been detected in the California and Washington. Lobesia botrana has been detected in California, and eradication efforts are ongoing. Heterodera filipjevi has been detected in Oregon.

A B

C D

Figure 1.2 Small grain acreage by county in 2002. A) Wheat, B) Barley, C) Oats, and D) Rye.

7 A B

Washingto n Wyo ming

Oklahoma Was hingt o n

M ontana M ontana

North Dakota North Dakota

Kansas Idaho 0 500,000 1,000,000 1,500,000 0 50,000 100,000 150,000 V alue (t ho usand $) V alue (t ho usand $)

C D

South Dakota

Pennsylvania Georgia

Io wa

M innesota Oklahoma Wisconsin

0 5,000 10,000 15,000 20,000 25,000 0 1,000 2,00 3,00 4,00 5,000 V alue (t ho usand $) 0 0 0 Value (t housand $)

Figure 1.3 Small grain value in top producing states in 2006. A) Wheat, B) Barley, C) Oats, and D) Rye.

Chapter 1: Introduction

Table 1.3. Pests targeted in the CAPS Small Grain Commodity Survey Guideline and the relative pest status of each pest on each small grain. Note: Information was not available for each pest on each small grain.

FY 09’ AHP List Rank- Pest Barley Oats Wheat Rye ing

1 Helicoverpa armigera major major major

3 Nysius huttoni minor minor major minor

6 Spodoptera litura minor

18 Meloidogyne artiellia minor minor major

20 Heterodera latipons minor minor major minor

24 Cochlicella spp. minor minor

37 Spodoptera littoralis major

41 Cernuella spp. minor minor

66 Autographa gamma minor minor major

84 Copitarsia spp. major

92 Peronosclerospora philippinensis minor

97 Heteronychus arator minor minor minor minor

98 Lobesia botrana minor

FY 10’ AHP list Diabrotica speciosa minor major

Found in Oregon Heterodera filipjevi major major major major

Chapter 1: Introduction A

B C D

E F

J K L M

Figure 1.4 Small grain pests to be surveyed for as part of Small Grains Survey Guidelines. A. Autographa gamma, B. Cer- nuella virgata, C. Cochlicella barbara., D. Copitarsia spp., E. Diabrotica speciosa, F. Helicoverpa armigera, G. Heterodera filipjevi, H. Heterodera latipons, I. Heteronychus arator, J. Lobesia botrana, K. Meloidogyne artiellia, L. Nysius huttoni, M. Per- onosclerospora philippinensis, N. Spodoptera littoralis, and O. Spodoptera litura,

Chapter 2: Survey Design & Sampling Methodology

Introduction: The purpose of this small grains survey guideline is to provide guidance and to recommend the number of samples that will allow you to state with confidence that any one of these pests is below a specified incidence in your state. The methodology described was chosen to ensure a degree of statistical confidence without the requirement of a large, non-economically feasible sample size. The guideline outlines the steps involved to conduct a survey and gives you several options or alternatives to reach a desired goal. The steps described in each section can be accomplished through a number of methods. Keep in mind that these are only possible options. Each state will have to evaluate the options to find the best system to fit their limited resources to meet the objective. Often times there are many paths to get to the same endpoint. We recognize that many states utilize GIS and complex databases and computer systems in their survey activities. Please use the methodology that is most convenient to use in your state. In some cases, these may be a good fit for Visual Sampling Plan frame and sample development. In other cases, the Na- tional Statistical Service or Farm Service Agency frame will be applicable. The state will need to contact these agencies well in advance to determine if data are available and what steps need to be completed to obtain the data. This procedure will outline the steps to develop a survey procedure and will cover:

1. The objective of the survey, 2. The population to be sampled, 3. Data to be collected, 4. Degree of precision required, 5. The frame, 6. Selection of sampling plan, 7. Sample selection, 8. Methods and units of measure, 9. The pre-test, 10. The organization of field work, 11. Summary and analysis of data, and 12. Documenting information gained for future surveys.

Summary of Action Steps Required to Conduct Survey:

1. Determine the distribution of commercial barley, rye, oats, and/or wheat fields in your state. The first questions to ask yourself are: 1. How much small grain production is in your state? and 2. How is it distributed across the state by county?

2. Determine how many samples you need to take to survey for exotic pests. First you will need to determine the confidence level (90, 95, or 99%) and detection level (1%) that you desire (Table 2). In most cases, a 95% confidence level with a 1% level of detection will be a good place to start.

*If there is a need for a higher confidence level or a higher detection level, will increase the sample size dramatically, and the survey may become cost prohibitive.

*Keep in mind that you may need to increase the sample size for refusal rate, inspection effectiveness, and deadwood described later.

3. Identify the counties where samples should be placed and number of samples per county, making sure to distribute samples based on small grain production within each selected county.

*If you have international ports in your state, international trade zones or inter-borders with cropping areas adjacent, you may want to allocate more samples in these areas/counties. The prevailing winds may also influence where you want to allocate samples.

Chapter 2: Survey Design & Sampling Methodology

4. Determine the locations (small grain fields within a given county) that will be sampled and arrange for permission from growers to conduct visual surveys and set up traps. What is the best means available in your state to get a map of growing areas or a list of growers and conversely the fields within each small grain-growing county within the state? How each state chooses to do this may vary but the end goal should be detecting small grains pests at a specific level of infestation with a specific confidence level.

*Contacting NASS (they will not share their list of growers) for possible land use samples, contacting grower associates, or mapping small grain growing areas of your state may aid in determining the locations to be sampled.

*In addition, a process must be followed to select the fields for sampling. The process needs to be well- defined and the decision of which field to sample should not be left in the hands of the individual conducting the survey. Following the process should guide them to the sample field.

5. Once you have the list and have selected the small grain field to survey, you must obtain permission from the growers to conduct a survey in their field(s).

Steps to Develop Survey Procedure: 1. Objective of Survey: The survey objective is to establish the presence or lack of presence of selected small grain pests in the states surveyed. This is where you determine which pests to be targeted with the survey. To accomplish this objective, small grain target pests will be detected in and around the vicinity of small grain fields.

2. Population to be Sampled: The population to be sampled is small grain fields and the areas immediately adjacent to small grain fields. You may also want to divide the regions or counties into different groups based cultivation practices, and risk of introduction based on known pest pathways. The key factors in population sample identification are to:

Determine the distribution of fields in your state. The first questions to ask yourself are: 1. How much small grain production is in your state?

2. How is it distributed across the state by county? And

3. Are there high risk areas?

Terminology: We are sampling fields. Fields will have sample plots in them. The field is the sample unit. The plots in the fields or adjacent to the field are subsamples associated with the sample unit. *A sample farm is a farm containing one or more sample fields or field blocks. *A sample county is a county containing one or more sample fields. *A population refers to the population of fields within a state. If we sample from the population of fields within a state, we can extrapolate back to the population from which the sample was selected. If we find a pest within our samples, we can extrapolate to the population of pests within the population of small grain fields.

3. Data to be Collected: We must decide what data is to be collected. The data to be collected will be driven by the survey objective target pests and the population distribution of fields.

Key data may include: What pest(s) is the survey intended to find, survey date, survey time, survey type (visual, trapping, soil sampling, etc.), trap type, attractant/lure used, trap number/identifier, latitude, longitude, sample submission date, sample submission time, sample identification number, symptoms observed (if any), plant

Chapter 2: Survey Design & Sampling Methodology

part affected/collected, stage of organism found (egg, larva, pupa, nymph, adult, all stages, unknown), condition of organism (live, dead), level of infestation, diagnostic elements (name of diagnostic laboratory, specialist), and diagnostic methodology (morphological, ELISA, molecular, etc.). Will a plant tissue sample be collected? Will a soil sample be collected?

We recommended that the data collected concerning each sample is reasonable and that data only be collected that are necessary to track a sample and make sound decisions.

Each PPQ regional office will work with the states to develop and provide a template to the states on what data are to be collected at the time of a survey with key sample elements.

4. Degree of Precision Required: The level of infestation to be detected establishes the required precision of the survey. For small grain, we are recommending as a standard that you detect a 1% or smaller infestation. Individual states may find this level of precision difficult to attain due to time and cost issues. These issues may result in states deviating from the standard. Table 2 .1 shows the sample size required to achieve a certain degree of precision. The degree of precision is one of the primary factors in determining the sample size. In cases where resource limitations limit sample size, the degree of precision becomes the result of a doable sample size, rather than the driver of sample size. Again Table 2 .1 is provided as a guide to the relationship between sample size and infestation detection level.

5. The Frame: Frame development is determining the locations (fields within a given county) that will be potential sample units for visual surveys and to set up traps. What is the best means available in your state to get a map of growing areas or a list of growers and conversely the fields within each small grain-growing county within the state? How each state chooses to do this may vary but the end goal should be detecting small grains pests at a specific level of infestation with a specific confidence level. Here is some specific information you need to know about frame development.

A frame is a physical device used to represent the population. The frame is made up of frame units, which represent members of the population. The frame units must be defined so that there is a clear distinction between frame units. Each frame unit must be mutually exclusive from any other unit in the frame. No part of a frame unit should be considered part or confused with another frame unit. The sample is selected from the frame. The frame units selected for the sample become sample units. In this case, small grain pest detection, the fields or field blocks become the frame unit. The field or field block is an area of continuous cultivation. If a single small grain growing operation has more than one field block (field) than each field block would be considered as a frame unit.

In a given state the fields or field blocks must be listed, mapped, or otherwise organized into a frame so that we can apply a selection process to select our sample. There are no perfect frames. The frame will be incomplete, contain duplication or both. Some frames may also be very difficult to work with. List frames tend to be incomplete or have duplication or both. Map frames can be more difficult to work with; however, today’s more computerized digital images can make this task much easier. For small grains, there are at least five different frame alternatives listed below. Each state will determine which frame will work best for their situation. A. National Agricultural Statistical Service (NASS) frame: In states where NASS does a field survey they may have a listing of growers that they use for sampling. You may be able to work with them as a state cooperator to get a listing of the growers or work with them too select a sample of fields. This will also help find growers who have been prescreened and will be more likely to cooperate with the survey.

Chapter 2: Survey Design & Sampling Methodology NASS also has an area frame, which would be well-suited for a field sample in many instances. This frame will only be useful for states with large wheat acreages, for example Kansas.

The NASS area frame is based on land use. NASS takes all land in a state and classifies the land tracts based on land use (e.g., urban, intense agriculture, moderate agriculture, light agriculture, forest, and etc.). NASS then further classifies these tracts into segments. This allows NASS to set up an effective area frame based on land use to select a sample. NASS samples its area frame each year in June. During this June survey, NASS identifies fields in the sampled segments planted to barley, oats, rye, and wheat. Aerial photography of fields and county maps of where segments are locate within a county are available within the NASS office. They also can identify farmers who would allow pest detection sampling. NASS also can select a sample o fields to be used in our pest detection survey. This provides a possible means to facilitate selection of a high quality sample for pest detection. With proper planning and coordination, these samples should be able to be made available to state cooperators.

Note: Current year information is not available until late June each year, which may limit it use- fulness for pest detection surveys if pest surveys are planned prior to this time. If this timing coin- cides with your survey plan, it is a potentially useful fame. It is also possible to use prior year information from NASS to locate wheat fields in a general area of the state. By visiting the area, you can ascertain if the field is still planted to a small grain, is fallow, is in rotation, or if a substitute- field is available.

If a state would like to try to use one of the NASS frames, we suggest that you contact Edward (Ned) Jones with CPHST ([email protected]) to help facilitate the process.

B. Farm Service Agency (FSA): This agency has aerial photography of farm land. Each year farmers come into the FSA Offices and identify the fields and crops that they intend to plant. State cooperators may be able to work with them to develop a frame of fields. This is not a proven concept but may have potential. We believe that this information may not be well-organized and has not been used for this purpose previously. However, this may be a useful tool to obtain a list of small grain fields within a county or state. The FSA information could be used to identify small grain growers at the county level. The growers could then be contacted and permissions obtained to enter their fields to conduct the pest detection survey.

C. County Acreage Estimates: NASS has county acreage estimates for small grains in states where production is significant enough to warrant such information. This information could be helpful to allocate samples to counties.

D. Visual Sampling Plan (VSP): VSP is a free program available via the internet (http://vsp.pnl.gov/), which can be used to develop a map-based sampling frame. It was developed for the Department of Energy, Environmental Protection Agency, and the Department of Defense. It is also now sponsored by the Department of Homeland Security and The Center for Disease Control. This program will provide information on the sample size required for a specific level of detection and where to locate the samples within a geographic area. VSP requires that you input digital maps. If you do not have access to digital maps of your state or counties within your state, some digital maps are available from the following Natural Resource and Conservation Service website (http://datagateway.nrcs.usda.gov/).

Note: to access this website you must login using a USDA e-Authentification (see http://www.eauth.egov.usda.gov/index.html for details on how to get an e-Authentification login).

The program will also allow you to incorporate and identify roads, water ways, and other high risk areas. The program may not be user-friendly without a statistical sampling background and training in VSP; however, once a frame is set up in VSP, it allows a great deal of flexibility in developing a sampling plan. An example of the visual sampling output is shown in Appendix B.

Chapter 2: Survey Design & Sampling Methodology Note: the VSP example refers to room because it is setup for room sampling; however, it will do an ex- cellent job with state or county maps. If a state would like to try to use this program, we suggest that you contact Edward (Ned) Jones ([email protected]) with CPHST to help facilitate the process.

E. Grower Associations and Grain Elevators: small grain grower lists may be obtainable from various grower associations within a given state. The issues with this source and other similar sources of information include: completeness of the data, over-completeness (duplication) of the data, and the inclusion of individuals or entities that are deceased or no longer in the small grain business. Such problems are usually referred to as “deadwood.” States will need to increase their sample size to allow for these weaknesses in the frame. If acreage data is available on this list, it could be used to allocate the samples in a manner similar to that used to with the county estimate data.

6. Selection of sampling plan and sample selection: The sampling plan will be based on detection sampling. In detection sampling theory, the sample size is based on detecting a specified level of infestation (e.g. 1%), the effectiveness of the inspection method applied, and selecting a sample with a specific level of confidence (probability) that the specified level of infestation would be detected. A refusal is a sample unit whose owner denies permission to sample his/her field. The refusal rate r is the proportion of the sample which become refusals (r=(sample refusals)/(total sample). By including re, the expected refusal rate, to the equation the sample is also adjusted for the expected refusal rate. The sample size can be estimated as follows: ner = ln(1-Pr(a>0)) (1- re) ln(1-(eP))

Where: ner = the detection sample size (number of frame units, i.e., fields or field blocks) adjusted for inspection effectiveness and refusals,

P = the level of infestation to be detected,

e = the efficiency of the inspection process,

re = the expected refusal rate (expected=best guess), and

Pr(a>0) = the probability (confidence) the sample will detect a P infestation, given an “e” inspection efficiency,

ln(….) = the natural logarithm of the value in brackets (…..).

The detection sampling plan used will also be influenced by the frame selected. Each frame will require a slightly different sample selection plan, depending on conditions in the state, knowledge of the frame, and the quality of the frame.

A. The NASS Frame: NASS locates the samples and could do some up front work to obtain permission for the CAPS samples. Utilizing the NASS frame will require coordination in advance with the state NASS office. Six months lead time before June would be a smart approach.

Samples would be selected by probability proportional to size of the small grain acres in the county.

B. Farm Service Agency Data: First distribute the samples per county based on the number of FSA small grain acres planted per county (see NASS county estimates example in Appendix C and C below for a specific example of probability proportional to size). At the county level, list the field ID’s and the acres planted to small grains. Sort the list based on planted acres (largest to smallest). Develop a cumulative summary of the fields in the county.

Chapter 2: Survey Design & Sampling Methodology

acres to determine a field-by-field cumulative total acres (if possible) planted to small grains in the county. The cumulative total for the last field in the listing will be the total for the county. At the county level divide the number of samples into total acres planted to develop a ‘county acres skip interval’.

Develop a random start by multiplying a random uniform number between 0 and 1 times the ‘county acres skip interval’. Use a table of random numbers from a reliable statistics book to generate the random number. DO NOT USE EXCEL as its random number generator is not reliable. The result will be a random start. This is the first sample point. It should correspond to the field with al least that many cumulative acres. This is the first sample unit in the county. Add the ‘county acres skip interval’ to the random start to obtain the cumulative acres for the second sample point. It should correspond to the field with at least that many cumulative acres. This is the second sample unit in the county. Continue adding the ‘county acres skip interval’ to identify each of the cumulative sample points and corresponding sample fields. To ID the selected field, find the first field in the cumulative listing whose cumulative acres planted exceeds the cumulative sample point. Repeat this field selection to ID all selected fields in the county.

Two months lead time before May would be a smart approach. In some counties with large opera- tions, more than one sample unit will be located within a field farm. When this occurs, the operation will be made up of several field/blocks. The field worker will need to number the blocks and use a random number table to select the block/field sample units) for sampling. A similar approach can also be used to select a single sample unit (field) from a large operation.

C. NASS County Estimates Use the NASS County Estimates to allocate the samples to the counties. An example of allocating the estimates by probability proportionate to size is provided in Appendix C for Kansas wheat acreage in 2005. The steps are as follows:

1. The approach here is to divide the state’s total acreage by the total number of samples for the state. The result is an ‘acreage sample interval’.

*For the KS example, the total acres were 9,800,600. Divide this number by the total sample size, 300 samples in this case. The result is an ‘acreage sample interval’ with 32,668.67acres per sample.

2. Develop an acreage cumulative total for each county estimate. *See column 4 in example. In this example, Sumner County has acreage of 381,200 acres. Harper has acreage of 256,200 acres. The cumulative acreage for these two counties is 381,200 + 256,200 , which is equal to 637,400. Continue this for all counties.

3. Divide each county acreage cumulative total by the acreage sample interval (from step 1). The result is a cumulative sample by county. Round the samples to the nearest whole sample.

*For the Sumner County example, divide the 381,200 acres by 32,668.67 samples/acre from step #1. For Harper County, divide the 256,200 acres by 32,668.67 samples acre. The result is 11.67 for Kossuth Co. and 19.51 for Sioux Co. Round each number to nearest whole sample (given here in column 5), where Sumner Co. would have a cumulative sample of 12 and Harper Co. would have 20.

4. Back out each counties sample size by subtracting the previous county’s cumulative sample from the county’s cumulative sample. This result will be the number of samples needed for that county. Con- tinue this process for all the counties for all counties.

*For the Sumner and Harper Co. example, Sumner would have 12 samples and Harper Co. would have 8 samples (20-12=8). The cumulative sample for Reno, the next county on the list, is 27. So, the county sample for Pottawattamie Co. is 7 (27-20=7).

Chapter 2: Survey Design & Sampling Methodology

Table 2.1 Sample size required to reach a desired level of precision.

Confidence Inspection Detec- Sample size Sample size Sample size Sample size (%) Effective- tion no refusals 20% refusals 30% refusals 50% refusals ness threshold (%) 95 100 1 299 374 427 598

99 100 1 459 574 656 918

90 100 1 230 288 329 460

95 50 1 598 748 854 1,196

99 50 1 919 1,149 1,313 1,838

90 50 1 460 575 657 920

95 40 1 748 935 1,069 1,496

99 40 1 1,149 1,436 1,641 2,298

90 40 1 575 719 821 1,150

95 25 1 1,197 1,496 1,710 2,394

99 25 1 1,840 2,300 2,629 3,680

90 25 1 920 1,150 1,314 1,840

Chapter 2: Survey Design & Sampling Methodology

Step 4 takes you through allocating the samples to the counties. Next a process must be developed to select the fields for sampling within the county. VSP may be able to provide a solution. It can identify a set of GPS coordinates for sample points. This process will only be applicable in counties with high densities of small grains fields. If the small grains fields are not dense, locate the small grain fields using a local source such as a county agent. Then sample some or all of the small grain fields as required by the number of samples needed for that county.

If you do not have a process to follow which distributes the samples evenly within each county step, 5 starts a suggested process.

5. Identify the small grain growing areas within each county. Select a set of either north-south roads or a set of east-west roads within the small grain growing area. In eastern states, a landowner meets and bounds system of land ownership is used (not township section), which may make identi- fying the roads in corn growing areas more difficult.

6. Layout a serpentine course along the roads.

 Example: For an east- west road system, start in the northwest corner and proceed east on the northern most road until it leaves the small grain growing area. Then turn south to the next east-west road and proceed west back to the other side of the small grain growing area. Use this process to develop a route through the small grain growing area (s) of the county. You may need to skip areas that are not small grain growing areas (towns, cities, forestland, etc.).

7. Determine the total distance along the serpentine route in the-small grain growing areas (exclude non-cropland areas).

8. The total distance from step 7 should be divided by the number of samples allocated to the county. This will result in a small grain growing area route sample skip interval.

9. The skip interval should be applied to the route to identify the sample start points. If desired, a random start can be applied to the skip to randomize the first start point.

10. With the sample start points identified in step 9, the individual conducting the sampling would proceed along the route to the first sample point. If a small grain field was present at that point, it would become the sample field. If not, proceed along the route to the first small grain field visible on the right. Let this first field to the right become the sample field. If no fields are on the right before the next sample start point, then at the next sample start point turn around and proceed back to the original sample start point looking for fields on the right. Note: If no field is found, record ”no field found” for sample number XXX. If no field found is a frequent occurrence, you may want to re- Evaluate your small grain growing area route.

11. The same process would be followed from each sample start point.

D. Visual Sampling Plan - a Map-Based Solution VSP can determine the appropriate sample size and locate the samples spatially based on a number of strategies. VSP will develop a list of GPS coordinates to identify sample points. A strategy must be developed to identify a small grain field from the sample point (example: proceed north to the first small grain field sighted).

E. Growers Association Lists Using the growers association lists, the samples could be allocated to growers across the state using the same strategy employed to allocate samples at the county level with the FSA data. After the sample growers are identified, it may be necessary to identify fields for growers with more than one

Chapter 2: Survey Design & Sampling Methodology field. Sample size: The sample size will be based on the required detection level and the desired confidence level of the sample. The confidence of the sample is the probability that a sample of a specific size will detect an infestation at the required detection level or larger.

This sample size can be applied to the entire state acreage to infer that the level of infestation is less than 1% in the entire state with 95% confidence or it can be applied to a smaller area even down to an individual field. The area defined as the population from which the sample is taken is the area we can make a statement about the level of infestation (an inference). If no infestations are found, we are 95% confident that any infestation is less than 1% in the area sampled. Table 2.1 shows the required sample size for given confidence and detection levels and refusal rates at four levels of inspection effectiveness. As a general rule, assuming 100% inspection effectiveness is ambitious to say the least and not a reasonable or practical approach. Inspection effectiveness is rarely better than 90% and usually values from 20-80% are more realistic. Try to apply a realistic evaluation of inspection effectiveness.

Methods and Units of Measure: Where to locate sample field plot? Once small grain fields are selected for sampling from your state and permission obtained, we recommend that visual surveys be conducted based on a paces and paces system similar to those used for pest scouting. The paces and paces system will be used to identify the area(s) of each field to be inspected. Since most small grains are broadcast or drilled, there are no visible rows. The sample plot would be located using paces and paces rather than row and paces, where you step off a predetermined number of paces (where you would normally have discreet rows) before you step off a predetermined number of paces into the field. A random number table can be used to determine these numbers and to eliminate bias. If upon selection of an area without plants, it is suggested that you continue to walk until you have plants present. If you have predetermined more paces than there are in the field, simply use the bounce back method. For paces, turn around and count paces in the other direction. The predetermined number of paces should be reselected randomly for each sample date; however, it you feel that you need to revisit the same area multiple times throughout the growing season, it is recommended that a stake with flagging be used to mark the area of the field. Permission should be obtained to use stakes to identify the sample plot location and must be removed at the last inspection visit before harvest. Stakes and combines do not mix well. The National Agricultural Statistics Service may have plots marked off in some small grain fields to measure small grain yield and production totals as part of their yearly surveys. It is recommended that these areas be avoided to ensure that the data collected from these plots are accurate and to facilitate cooperation with NASS.

How many sample plots per field and how to sample within the field? In each sample field, locate 4 sample plots. Two plots per corner from two different corners of a field will result in four sample plots per field. This will not provide an estimate for the field but when all estimates are combined across the state a reasonable level of detection will be achieved. Once you arrive at the predetermined area based on paces and paces, do a visual observation of the area in a 2-meter circle around where you are located. Look for obvious plant disease symptom (yellowing, streaking, damage, dead tissue) and signs of pests (frass, larvae, adults). It is recommended that at least 10 plants be examined in detail. Make sure to examine stems, leaves (including the underside), flowers (if present), and seed (grain) for symptoms and signs of pests. Plant samples should be collected when specific symptoms and signs are observed that are outlined for the specific exotic pests in the detailed survey tables in this document and the small grain reference guide are observed. The template provided by the regional offices should be used to record the proper data on each sample collected.

Chapter. 2: Survey Design & Sampling Methodology

Regardless of sampling method used, you should collect something obvious even if it falls outside the recommended sampling unit/area (including areas adjacent to the small grain field). In addition, you need to account for zeros. If nothing is observed, it must be documented. Visual Survey: This type of survey involves the examination of the small grain plant for diagnostic symptoms (Fig. 2.1). In addition, the surveyor should also look for physical evidence (signs) of the pest (Fig. 2.1). In each survey site, a circular area of 6 meters and 10 plants should be chosen for visual examination. The surveyors should pay close attention to symptomatic plants first. These would be the plants that have a chlorosis (yellowing), feeding holes, or a generally unhealthy appearance. If no symptomatic plants are present, the surveyor should choose plants to examine based on convenience. So while the surveyor will examine several plants within the site, only one data recording will be necessary for the site. The surveyor may make at least 2 trips to each survey site during the survey season (see trapping, below), and will thus have the opportunity to twice conduct a visual survey. In the context of the current survey, surveyors should take note of the general condition of the plants, and further examine stems, leaves, flowers, and seed for the pests of concern. Subsample Figure 2.1. Top: Example of plant chlorosis (a symptom), Bottom: ex- sites need not be the same on subsequent visits. ample of eggs and neonates (a sign) Trapping: This type of survey involves the use of a trap to catch arthropods of interest in a specific location. Often times, trap efficiency is increased through the use of some type of chemical or physical attractant (e.g. pheromone lures). In the context of the current survey, there are six arthropods which can be surveyed via this method. The six include are Auto- grapha gamma, Copitarsia spp., Helicoverpa armigera, Lobesia botrana, Spodoptera littoralis and Spodop- tera litura. However, the commercial availability of the pheromone for Copitarsia spp. is unknown. Copitarsia spp., have traditionally been trapped via black light trapping for early detection surveys and this is the CAPS- Approved survey method.

Handle and store pheromone lures appropriately or they will not be effective. Lures need to be kept in their sealed packages until ready for use, and should be stored in the refrigerator or freezer as directed by the manufacturer. Use gloves to avoid cross-contamination with lures of different species. If trapping is used, we recommend placing at least one trap per survey site per pest; however, it is preferable to use the same number of traps as total sample sites. As such, multiple traps may be necessary at each sample site and will contain a lure for one arthropod. Since the cross reactivity of the lures is also unknown, it recommended that the traps be placed at minimum 20 m apart. It is recommended that manufacturer guidelines be followed for trap set up. Specific information (where available) on type of trap, lure, replacement interval, and trap placement are given in the detailed survey tables in this document. While this method is the preferred method for most moths, if this trapping method is chosen, it is important to note that surveyors will need to make at least two trips to the field; 1) to set up the trap and 2) to take samples from the trap. Lures need to be replaced at differ- ing time intervals (from 2-12 weeks), which may add additional trips to each field site.

Soil Sampling: Soil Sampling involves the collection of multiple cylindrical soil cores for the detection of nematodes. Frequently, the cores are combined and mixed thoroughly to form a composite. The composite sample is then processed and analyzed for the presence of target nematodes. Soil sampling for nematodes is a three step process (See Figure 2.2). In the context of the current survey, the surveyor should collect soil cores from not more than 10 sample sites within a survey site. Sample sites may be the same as those chosen in the visual survey. These cores should be combined into a composite sample for each survey site.

Chapter 2: Survey Design & Sampling Methodology 8. The Pre-test: It is advisable to conduct a pre-test, trying the survey procedure out in several corn fields prior to deploying the procedure Samples of soil or host on a large, state-wide scale, to evaluate the survey plan to ascertain roots are collected with if the survey plan needs any changes. the purpose of obtaining males, juveniles, or nematodes within root tissues.

9. The Organization of Field Work: One of the most important compo- Samples are processed nents of the survey is the organization of the field work. In other words, to separate nematodes how do you organize and implement the survey to have the right re- from soil and debris. sources in the correct place and data collection at the proper time?

What fields are going to be sampled? Finally, nematodes are What are the rows and paces to locate subsample units? prepared either for identi- What are the unique identifiers for the sample units and the fication using morphologi- subsample units? cal (e.g., perineal patterns) or molecular tech- What system is setup to identify plant tissue and soil samples niques. with sample units and subunits?

What vehicles, measuring tape, stakes, chaining pins, stadia Figure 2.2 Sampling nematodes gener- rod, flagging ribbon, sample bags, traps, lures, and other ally involves three steps: collection, proc- equipment are needed to conduct the survey? essing, and identification. The current survey protocol focuses on collection. A How will the equipment be carried in the field backpack, processing and identification plan should shoulder bag etc.? be developed for each state.

10. Summary and analysis of data: Good documentation is the key to any future analysis. Most data will simply be entered into NAPIS and further analysis will not be necessary.

11. Gaining information for future surveys: Do you need to do something different? Is there a problem with a particular trap or with the universe sample frame? You should plan on documenting problems for use in planning future surveys.

Specific questions about this methodology may be addressed to Edward (Ned) Jones ([email protected]).

Chapter 3: Summary of Survey Strategies Section 1: Visual Survey

Field Equipment for visual surveys  Hand Lens  Vials  Quaternary  Ice chest  ______ Plastic Bags  Paper ammonia  Stakes  ______ Tweezers  Pen (Disinfectant)  Flagging ribbon  ______ Flashlight  Wax pencil Field Maps  List of random  ______ 70% EtOH  PDA  Sharpie numbers  ______ Ice Packs ______

Visual Survey Guide: The following is a survey guide intended to help you identify and flag diagnostic symptoms of CAPS target pests in the field. It is important to note that none of these symptoms, taken singly, are a diagnostic feature for any of the pests. In the context of the current survey, surveyors should take note of the general condition of the plant, and further examine stems, leaves, flowers, and seed/seed head for the pests of concern.

If you believe you have found a target pest, look for a more comprehensive list of symptoms in the detailed survey tables in Chapter 4. Pictures of organisms, symptoms, and evidence of organisms can be found in the Small Grains Commodity Survey Reference.

Whole Plant: First take note of the whole plant and consider whether or not the specimen is healthy. Some general “whole plant” indicators of target pests follow.

1. Aestivation on stalks  Cernuella virgata (Maritime gardensnail)  Cochlicella spp. (Maritime gardensnail)

2. Defoliation (leaf fall)  Cernuella virgata (Maritime gardensnail)  Helicoverpa armigera (Old world bollworm)

3. Poor tillering/shorter spikes  Heterodera filipjevi (Cereal cyst nematode)  Heterodera latipons (Mediterranean cereal cyst nematode)  Meloidogyne artiellia (British root-knot nematode)

4. Presence of adults  Autographa gamma (Silver-Y moth)  Cernuella virgata (Maritime gardensnail)  Cochlicella spp. (Maritime gardensnail)

5. Presence of eggs/egg masses  Autographa gamma (Silver-Y moth)  Cernuella virgata (Maritime gardensnail)  Cochlicella spp. (Maritime gardensnail)  Copitarsia spp. (Owlet moths)

Chapter 3: Summary of Survey Strategies

 Helicoverpa armigera (Old world bollworm)  Lobesia botrana (European grapevine moth)  Spodoptera littoralis (Egyptian cotton leafworm)  Spodoptera litura (Rice cutworm)

6. Presence of excrement or slime trails  Autographa gamma (Silver-Y moth)  Cernuella virgata (Maritime gardensnail)  Cochlicella spp. (Maritime gardensnail)  Helicoverpa armigera (Old world bollworm)  Lobesia botrana (European grapevine moth)  Spodoptera littoralis (Egyptian cotton leafworm)  Spodoptera litura (Rice cutworm)

7. Presence of larvae/immature stages  Autographa gamma (Silver-Y moth)  Cernuella virgata (Maritime gardensnail)  Cochlicella spp. (Maritime gardensnail)  Copitarsia spp. (Owlet moths)  Helicoverpa armigera (Old world bollworm)  Spodoptera littoralis (Egyptian cotton leafworm)  Spodoptera litura (Rice cutworm)

8. Presence of pupae  Autographa gamma (Silver-Y moth)  Lobesia botrana (European grapevine moth)  Spodoptera littoralis (Egyptian cotton leafworm)

9. Slight to severe yellowing (chlorosis)  Heterodera filipjevi (Cereal cyst nematode)  Heterodera latipons (Mediterranean cereal cyst nematode)  Meloidogyne artiellia (British root-knot nematode)  Peronosclerospora philippinensis (Philippine downy mildew)

10. Stunting/less vigorous/patchy growth/yield loss  Diabrotica speciosa (Cucurbit beetle)  Heterodera filipjevi (Cereal cyst nematode)  Heterodera latipons (Mediterranean cereal cyst nematode)  Lobesia botrana (European grapevine moth)  Meloidogyne artiellia (British root-knot nematode)  Peronosclerospora philippinensis (Philippine downy mildew)

11. Whole plant toppled or uprooted  Heteronychus arator (African black beetle)

12. Wilting  Heterodera latipons (Mediterranean cereal cyst nematode)  Spodoptera littoralis (Egyptian cotton leafworm)  Spodoptera litura (Rice cutworm)

Leaves: Choose several leaves from each plant to examine.

Chapter 3: Summary of Survey Strategies

1. Chlorotic stripes on leaves  Peronosclerospora philippinensis (Philippine downy mildew)

2. Feeding damage (bare sections, holes, etc.)  Autographa gamma (Silver-Y moth)  Cernuella virgata (Maritime gardensnail)  Cochlicella spp. (Maritime gardensnail)  Copitarsia spp. (Owlet moths)  Helicoverpa armigera (Old world bollworm)  Nysius huttoni (wheat bug) - possible  Spodoptera littoralis (Egyptian cotton leafworm)  Spodoptera litura (Rice cutworm)

3. Grayish fungal growth on underside of leaves  Peronosclerospora philippinensis (Philippine downy mildew)

4. Leaf scars  Spodoptera littoralis (Egyptian cotton leafworm)  Spodoptera litura (rice cutworm) - scratch marks

5. Leaves narrow, abnormally erect, and somewhat dried out  Peronosclerospora philippinensis (Philippine downy mildew)

6. Leaves rolled/folded  Autographa gamma (Silver-Y moth)

7. Petioles cut  Autographa gamma (Silver-Y moth)

8. Presence of eggs  Autographa gamma (Silver-Y moth)  Cernuella virgata (Maritime gardensnail)  Cochlicella spp. (Maritime gardensnail)  Copitarsia spp. (Owlet moths)  Helicoverpa armigera (Old world bollworm)- [possible, not preferred]  Spodoptera littoralis (Egyptian cotton leafworm)  Spodoptera litura (Rice cutworm)

9. Presence of larvae/immatures  Autographa gamma (Silver-Y moth)  Cernuella virgata (Maritime gardensnail)  Cochlicella spp. (Maritime gardensnail)  Copitarsia spp. (Owlet moths)  Spodoptera littoralis (Egyptian cotton leafworm)  Spodoptera litura (Rice cutworm)

10. Presence of pupae  Autographa gamma (Silver-Y moth)  Lobesia botrana (European grapevine moth)

11. Presence of adults  Cernuella virgata (Maritime gardensnail)  Cochlicella spp. (Maritime gardensnail)

12. Silk webbing

Chapter 3: Summary of Survey Strategies

 Autographa gamma (Silver-Y moth)

13. Skeletonization  Autographa gamma (Silver-Y moth)  Spodoptera littoralis (Egyptian cotton leafworm)  Spodoptera litura (rice cutworm)

Stems: Examine stems

1. Bore holes  Copitarsia spp. (Owlet moths) - occasionally  Spodoptera littoralis (Egyptian cotton leafworm)  Spodoptera litura (rice cutworm)

2. Feeding damage  Copitarsia spp. (Owlet moths)  Heteronychus arator (African black beetle)  Spodoptera littoralis (Egyptian cotton leafworm)  Spodoptera litura (rice cutworm)

3. Presence of eggs  Copitarsia spp. (Owlet moths)  Helicoverpa armigera (Old world bollworm)- [possible, not preferred]  Lobesia botrana (European grapevine moth) - on pedicels

4. Presence of live mollusks  Cernuella virgata (Maritime gardensnail)  Cochlicella spp. (Maritime gardensnail)

Roots: Examine roots

1. Frass and tunneling present in soil around roots  Heteronychus arator (African black beetle)

2. Presence of egg masses of roots  Meloidogyne artiellia (British root-knot nematode)

3. Presence of females (cysts) on roots  Heterodera filipjevi (Cereal cyst nematode)  Heterodera latipons (Mediterranean cereal cyst nematode)

4. Presence of galls on roots  Meloidogyne artiellia (British root-knot nematode)

5. Presence of larvae  Diabrotica speciosa (Cucurbit beetle)

Chapter 3: Summary of Survey Strategies

Flowers: Flowers may or may not be present in the small grain varieties that you examine on the days that you choose to survey. If they are available, examine several flowers for the symptoms and signs indicated below.

1. Bore Holes  Helicoverpa armigera (Old world bollworm)

2. Feeding damage  Autographa gamma (Silver-Y moth)  Copitarsia spp. (Owlet moths)  Helicoverpa armigera (Old world bollworm)  Spodoptera littoralis (Egyptian cotton leafworm)  Spodoptera litura (rice cutworm)

3. Presence of adults  Autographa gamma (Silver-Y moth)

4. Presence of eggs/egg masses  Copitarsia spp. (Owlet moths)  Helicoverpa armigera (Old world bollworm)  Lobesia botrana (European grapevine moth)

5. Presence of larvae inside floral structures  Helicoverpa armigera (Old world bollworm)

6. Silk webbing  Lobesia botrana (European grapevine moth)- glomerules (webbed bud clusters) formed

Seed/Seed Heads: Seed may or may not be present in the small grains varieties that you examine on the days that you choose to survey. Examine several seed per plant/seed heads for the following symptoms and signs.

1. Bore holes, feeding damage  Helicoverpa armigera (Old world bollworm)  Lobesia botrana (European grapevine moth)  Nysius huttoni (wheat bug)  Spodoptera littoralis (Egyptian cotton leafworm) - possible  Spodoptera litura (rice cutworm) - possible

2. Deformation (skin and general shape)  Nysius huttoni (wheat bug) - cuboid shape  Peronosclerospora philippinensis (Philippine downy mildew) -possible

3. Presence of larvae inside seed/fruit  Helicoverpa armigera (Old world bollworm)  Lobesia botrana (European grapevine moth)

4. Seed/Fruit drop  Helicoverpa armigera (Old world bollworm)  Lobesia botrana (European grapevine moth)

Chapter 3: Summary of Survey Strategies

5. Seeds consumed  Helicoverpa armigera (Old world bollworm)  Nysius huttoni (wheat bug)

6. Sterility of seeds  Peronosclerospora philippinensis (Philippine downy mildew) - possible (shown in corn)

Chapter 3: Summary of Survey Strategies

Section 2: Trapping In general, trapping is a type of survey that involves the use of a trap to catch arthropods of concern in a specific location, rather than walking around and actively looking for arthropods. Often times, trap efficiency is increased through the use of some type of chemical or physical attractant. These attractants might be a light source, a food source, or a specific pheromone or chemical that is highly attractive to the target species.

In the context of the current survey there are six arthropods that can be surveyed for using this method. The six include are Autographa gamma, Copitarsia spp., Helicoverpa armigera, Lobesia botrana, Spodoptera littoralis and Spodoptera litura. However, the commercial availability of the pheromone for Copitarsia spp. is unknown. Copitarsia spp., have traditionally been trapped via black light trapping for early detection surveys and this is the CAPS-Approved survey method.

Additional equipment for pheromone surveys

 Lures  Hammer   ______ ______ Traps  Paper   ______ ______ Tweezers  Wire  ______ ______ ______ Rubber Gloves  Tall Stakes  ______ ______ ______ Nails (optional)

Section 3: Soil Sampling Soil sampling involves the collection of multiple cylindrical soil cores for the detection of nematodes. Fre- quently, the cores are combined and mixed thoroughly to form a composite. The composite sample is then processed and analyzed for the presence of target nematodes. In the context of the current survey, there are two nematodes (Heterodera filepjevi, H. latipons and Meloidogyne artiellia) that can be surveyed via this method.

Equipment for soil sampling

Oakfield or Veihmeyer  Quaternary ammonia sampling tube (~1 inch (Disinfectant) inner diameter).  ______ Permanent pen  ______ Plastic Bags  ______ Labels

Chapter 4: Pest Tables Table 4.1: Pest by Affected Plant Part Chapter 4: Pest Tables

Table 4.1: Affected Plant Part - Parts that may have symptoms

Plant Part Affected Scientific Name Common Name Leaves Stems Roots Flowers Seed

Autographa gamma Silver-Y moth

Copitarsia spp. Owlet moths

Diabrotica speciosa Cucurbit beetle Helicoverpa armigera Old world bollworm Heteronychus arator African black beetle

Lobesia botrana European grapevine moth Nysius huttoni Wheat bug Spodoptera littoralis Egyptian cotton leafworm

Spodoptera litura Rice cutworm Cernuella virgata Maritime gardensnail, white snail Cochlicella spp. Conical snails

Heterodera filipjevi Cereal cyst nematode

Heterodera latipons Mediterranean cereal cyst nematode Meloidogyne artiellia British root-knot nematode Peronosclerospora philippinensis Philippine downy mildew

Key to symbols

= Stems = Flowers = Leaves = Seeds/seed head = Damages roots

Chapter 4: Pest Tables Section 2: Survey Methods

Table 4.2: CAPS-Approved Survey Methods

Survey Method Available Visual Trapping Soil Other Scientific Name Common Name

Autographa gamma Silver-Y moth Copitarsia spp. Blacklight

Owlet moths trapping

Diabrotica speciosa Cucurbit beetle

Helicoverpa armigera Old world bollworm Heteronychus arator African black beetle

Lobesia botrana European grapevine moth

Nysius huttoni Wheat bug

Spodoptera littoralis Egyptian cotton leafworm

Spodoptera litura Rice cutworm

Cernuella virgata Maritime gardensnail, white snail

Cochlicella spp. Conical snails Cereal cyst nema-

Heterodera filipjevi tode

Heterodera latipons Mediterranean cereal cyst nematode

Meloidogyne artiellia British root-knot nematode Peronosclerospora philippinensis Philippine downy mildew

Key to symbols

= Visual Survey =Trapping = Soil Sampling =Visual survey of sentinel plots = Spore trapping

30 Chapter 5: Detailed Survey Tables Autographa gamma

Chapter 5: Survey Methods

Scientific Name Common Name Survey Method Available Autographa Silver-Y moth Time Frame: Due to the migratory nature of this species, adult A. gamma gamma can be observed every month from April to November, usually peaking in late summer Plant Part:

Age of Plant:

Older leaves are preferred. Only eats young leaves after destroying the old ones. Preferred Method: Traps:

Trap with lure: A plastic bucket trap (unitrap) (green canopy, yellow funnel, white bucket) with dry kill strip is the approved trap for Autographa gamma. See the plastic bucket trap protocol in Appendix A of this document for more information. The lure information is provided below:

Lure Dispenser Dispenser Lure Length of Compound Load Type Abbreviation Effectiveness a) 'Z,7- a) 0.99 gray AG 4 weeks 12:AC mg rubber b) 'Z,7- b) 0.01 septum 12:OH mg

IMPORTANT: Placing lures for two or more target species in a trap,

should never be done unless otherwise noted here.

Trap spacing: When trapping for more than one species of moth,

separate traps for different moth species by at least 20 meters.

If a suspect is found: Take a sample of the immature and adult insect (if

available). Be sure to include a sample of the host material on which it

was found. Plant samples should be labeled and placed in sealable plastic bags accompanying the insect samples. Labels should indicate date, geographic location, and identity of the host plant. Place insect specimens in a small, rigid plastic container which should be included in the plant sample bag. Do not place more than one specimen in a container. Larvae should be preserved in ethyl alcohol. Label the sample and keep it in a cool, dry place until identification can be made. Care should be taken to preserve the specimen intact, as damaged, crushed, or moldy insects are difficult to identify. Species- level identification should be made by a qualified taxonomist. Submit the specimen for identification within 72 hours after collection.

Key to symbols

= Pest Infests Stems = Pest Infests Flowers = Pest Infests Leaves = Pest Infests Seed/Seed head

= Damages young plants =Damages older plants = Damages roots

31 Chapter 5: Detailed Survey Tables Copitarsia spp.

Scientific Name Common Name Survey Method Available Copitarsia spp. Owlet moths Time Frame: May be found throughout the year during the growing season.

Plant Part:

Age of Plant:

Any age of plant attacked. Preferred Method Traps:

Blacklight trapping:

If a suspect is found: Take a sample of the immature and adult insect (if available). Be sure to include a sample of the host material on which it was found. Plant samples should be labeled and placed in sealable plastic bags accompanying the insect samples. Labels should indicate date, geographic location, and identity of the host plant. Place insect specimens in a small, rigid plastic container which should be included in the plant sample bag. Do not place more than one specimen in a container. Larvae should be preserved in ethyl alcohol. Label the sample and keep it in a cool, dry place until identification can be made. Care should be taken to preserve the specimen intact, as damaged, crushed, or moldy insects are difficult to identify. Species- level identification should be made by a qualified taxonomist. Submit the specimen for identification within 72 hours after collection.

Key to symbols

= Pest Infests Stems = Pest Infests Flowers = Pest Infests Leaves = Pest Infests Seed/Seed head

= Damages young plants =Damages older plants = Damages roots

32 Chapter 5: Detailed Survey Tables Diabrotica speciosa

Scientific Name Common Name Survey Method Available Diabrotica Cucurbit beetle Time Frame: Beetles can occur anytime during the growing speciosa. season. Adult populations tend to be highest during the flowering period; while larvae in roots tend to be higher early in the season. Plant Part:

Age of Plant:

Any age of plant attacked. Preferred Method Visual:

The larval damage resulting from root feeding can cause host death when the host is small, but the larvae will usually only induce stunted growth in larger host plants, due to a reduction in nutrient uptake. Wheat is a larval host and stunting would be the primary symptom.

Key to symbols

= Pest Infests Stems = Pest Infests Flowers = Pest Infests Leaves = Pest Infests Seed/Seed head

= Damages young plants =Damages older plants = Damages roots

33 Chapter 5: Detailed Survey Tables Helicoverpa armigera

Scientific Name Common Name Survey Method Available Helicoverpa Old world Time Frame: Adults appear in April to May and can be observed armigera bollworm until October, because of the migratory nature of this species. Plant Part:

Age of Plant:

In general, any age of plant may be attacked. In grains, the larvae feed on the head when the grains are in the milky stage. Prefer to lay eggs immediately before and after flowering. Preferred Method Traps:

Trap with lure: Use one of the following traps for H. armigera: 1) A plastic bucket trap (unitrap) (green canopy, yellow funnel, white bucket) with dry kill strip, 2) Heliothis trap (plastic mesh cone trap), 3) Texas (Hartstack) trap. Trap comparison trials are currently being conducted to evaluate the efficacy of the three traps.

See the plastic bucket trap protocol in Appendix A of this document for more information. The Texas (Hartstack) trap is not available commercially. See Hartstack et al. (1979) or Johnson and McNeil for images and trap design.

The lure information is provided below:

Lure Dispenser Dispenser Lure Length of Compound Load Type Abbreviation Effectiveness a) 'Z,11- a) 2 mg gray HA 4 weeks 16:AL b) 0.08 rubber b) 'Z,9- mg septum 16:AL c) 0.208 c) 'BHT mg

IMPORTANT: Placing lures for two or more target species in a trap, should never be done unless otherwise noted here.

Trap spacing: When trapping for more than one species of moth, separate traps for different moth species by at least 20 meters.

Hartstack, A.W., Witz, J.A, and Buck, D.R. 1979. Moth traps for the tobacco budworm. J. Econom. Entomol. 72: 519-522.

Johnson, D. and McNeil, S. n.d. Plans and Parts List: "Texas" Style Cone Trap for Monitoring Certain Insect Pests. ENTFACT-010.University of Kentucky College of Agriculture.

= Pest Infests Stems = Pest Infests Flowers = Pest Infests Leaves = Pest Infests Seed/Seed head

= Damages young plants =Damages older plants = Damages roots

34 Chapter 5: Detailed Survey Tables Helicoverpa armigera

plastic bags accompanying the insect samples. Labels should indicate date, geographic location, and identity of the host plant. Place insect specimens in a small, rigid plastic container which should be included in the plant sample bag. Do not place more than one specimen in a container. Larvae should be preserved in ethyl alcohol. Label the sample and keep it in a cool, dry place until identification can be made. Care should be taken to preserve the specimen intact, as damaged, crushed, or moldy insects are difficult to identify. Species- level identification should be made by a qualified taxonomist. Submit the specimen for identification within 72 hours after collection.

Key to symbols

= Pest Infests Stems = Pest Infests Flowers = Pest Infests Leaves = Pest Infests Seed/Seed head

= Damages young plants =Damages older plants = Damages roots

35 Chapter 5: Detailed Survey Tables Heteronychus arator

Scientific Name Common Name Survey Method Available Heteronychus African black Time Frame: Most damage by the African black beetle occurs arator beetle during the spring to early summer when the adults are most active crawling on the soil surface and again after new adults emerge in mid summer to fall. Plant Part:

Age of Plant:

Any age of plant attacked. Preferred Method Visual:

Stems experience external feeding, and the whole plant may be toppled or uprooted. Adult damage to plants typically involves chewing of the cortex of stems just below the surface of the ground. The damaged area of the stem has a frayed (shredded) appearance, which distinguishes it from the damage caused by cutworms. The fraying is caused by the beetles consuming the soft tissues but leaving the fibrous material. If young plants are infested, a reduction in plant stand is often observed. Older plants are weakened and prone to lodging. The grubs (larvae) prefer to feed on organic matter in the soil, but may cause some root damage.

Key to symbols

= Pest Infests Stems = Pest Infests Flowers = Pest Infests Leaves = Pest Infests Seed/Seed head

= Damages young plants =Damages older plants = Damages roots

36 Chapter 5: Detailed Survey Tables Lobesia botrana

Scientific Name Common Name Survey Method Available Lobesia European Time Frame: The first flight of adults occurs in spring when daily botrana grapevine moth average air temperature is above the minimal threshold temperature of 10 °C for 10 to 13 days. The second flight period begins in summer. Plant Part:

Age of Plant:

Specific information on small grains is lacking. On grape, moth observed when plants are flowering. Preferred Method Traps:

Trap with Lure: There are two delta traps approved for L. botrana: 1) Paper delta trap (orange/ red, three-sided sticky interior); ends left open, and 2) Large plastic delta trap (red). The lure information is provided below:

Lure Dispenser Dispenser Type Lure Compound Load Abbreviation 'E,Z,7,9-12:AC 0.5 mg gray rubber LB septum

IMPORTANT: Placing lures for two or more target species in a trap, should never be done unless otherwise noted here.

Trap spacing: When trapping for more than one species of moth, separate traps for different moth species by at least 20 meters.

Note: The paper delta trap used for this species is the same type used in the pink bollworm program: orange/ red in color, with adhesive applied to all three of the interior trapping surfaces. It is not the same trap as used for gypsy moth (which has only two sticky surfaces).

Additional Resources: PPQ Website and Information Key to symbols

= Pest Infests Stems = Pest Infests Flowers = Pest Infests Leaves = Pest Infests Seed/Seed head

= Damages young plants =Damages older plants = Damages roots

37 Chapter 5: Detailed Survey Tables Lobesia botrana

UC IPM Datasheet

Key to symbols

= Pest Infests Stems = Pest Infests Flowers = Pest Infests Leaves = Pest Infests Seed/Seed head

= Damages young plants =Damages older plants = Damages roots

38 Chapter 5: Detailed Survey Tables Nysius huttoni

Scientific Common Name Name Survey Method Available Nysius Wheat Time Frame: The bug moves to wheat as most weeds mature and wheat huttoni bug reaches the milk-ripe stage. Plant Part:

Bug is a seed feeder, but foliage can be damaged Age of Plant:

Older plants (flowering to grain-filling stage) Preferred Method Visual Survey:

Visually inspect wheat kernels during the water ripe to milky ripe stages of development for piercing marks. Damage usually occurs at field edges

If a suspect is found: Take a sample of the immature and adult insect (if available). Be sure to include a sample of the host material on which it was found. Plant samples should be labeled and placed in sealable plastic bags accompanying the insect samples. Labels should indicate date, geographic location, and identity of the host plant. Place insect specimens in a small, rigid plastic container which should be included in the plant sample bag. Do not place more than one specimen in a container. Larvae should be preserved in ethyl alcohol. Label the sample and keep it in a cool, dry place until identification can be made. Care should be taken to preserve the specimen intact, as damaged, crushed, or moldy insects are difficult to identify. Species-level identification should be made by a qualified taxonomist. Submit the specimen for identification within 72 hours after collection.

Key to symbols

= Pest Infests Stems = Pest Infests Flowers = Pest Infests Leaves = Pest Infests Seed/Seed head

= Damages young plants =Damages older plants = Damages roots

39 Chapter 5: Detailed Survey Tables Spodoptera littoralis

Scientific Name Common Name Survey Method Available Spodoptera Egyptian cotton Time Frame: Damage may occur from spring to fall, anytime littoralis leafworm plants are actively growing Plant Part:

Age of Plant:

Any age of plant attacked. Preferred Method Traps:

Trap with lure: Trap with lure. A plastic bucket trap [unitrap] with dry kill strip is the approved trap for Spodoptera littoralis. The lure information is provided below:

Lure Dispenser Dispenser Lure Length of Compound Load Type Abbreviation Effectiveness a) 'Z,E,9,11- a) 1.99 laminate ECL 12 weeks 14:AC mg b) 'Z,E,9,12- b) 0.01 14:AC mg

The plastic bucket trap (also known as the Universal moth trap or unitrap) should have a green canopy, yellow funnel, and white bucket and should be used with dry kill strip. For instructions on using the trap (see Appendix A” Plastic Bucket Trap Protocol”).

IMPORTANT: Placing lures for two or more target species in a trap, should never be done unless otherwise noted here.

Trap spacing: When trapping for more than one species of moth, separate traps for different moth species by at least 20 meters (65 feet). As of June 2010, S. litura and S. littoralis lures should be placed in different traps and separated by at least 20 meters (65 feet).

Key to symbols

= Pest Infests Stems = Pest Infests Flowers = Pest Infests Leaves = Pest Infests Seed/Seed head

= Damages young plants =Damages older plants = Damages roots =Damage evident on individual plants

40 Chapter 5: Detailed Survey Tables Spodoptera litura

Scientific Common Name Name Survey Method Available Spodoptera Rice cutworm Time Frame: S. litura may be detected any time the hosts are in litura an actively growing stage with foliage available, usually spring and fall. Plant Part:

Age of Plant:

Any age of plant attacked. Preferred Method Traps:

Trap with lure: Trap with lure. A plastic bucket trap [unitrap] with dry kill strip is the approved trap for Spodoptera litura. The lure information is provided below: Lure Dispenser Dispenser Lure Length of Compound Load Type Abbreviation Effectiveness a) 'Z,E,9,11- a) 1.76 laminate CL 12 weeks 14:AC mg b) 'Z,E,9,12- b) 0.24 14:AC mg

IMPORTANT: Placing lures for two or more target species in a trap, should never be done unless otherwise noted here.

If a suspect is found: Take a sample of the immature and adult insect (if available). Be sure to include a sample of the host material on which it was found. Plant samples should be labeled and placed in sealable plastic bags accompanying the insect samples. Labels should indicate date, geographic location, and identity of the host plant. Place insect specimens in a small, rigid plastic container which should be included in the plant sample bag. Do not place more than one specimen in a container. Larvae should be preserved in ethyl alcohol. Label the sample and keep it in a cool, dry place until identification can be made. Care should be taken to preserve the specimen intact, as damaged, crushed, or moldy insects are difficult to identify. Species-level identification should be made by a qualified taxonomist. Submit the specimen for identification within 72 hours after collection.

Key to symbols

= Pest Infests Stems = Pest Infests Flowers = Pest Infests Leaves = Pest Infests Seed/Seed head

= Damages young plants =Damages older plants = Damages roots =Damage evident on individual plants

41 Chapter 5: Detailed Survey Tables Cernuella spp.

Scientific Name Common Name Survey Method Available Cernuella Maritime Time Frame: Annual life cycle; breeding from fall through winter. virgata gardensnail, Aestivate on plant heads and stalks in summertime. white snail Plant Part:

Age of Plant:

Usually found on top of plants during summertime, but have been found feeding on new growth earlier in season Preferred Method Visual Survey:

See Floyd (2008) Look for the presence of relatively small snails up to 15 mm (0.59 inches) in diameter with prominent spiral banding on shell, the presence of eggs , juveniles, and empty snail shells, and the presence of ribbon-like excrement and slime trails on plants and structures.

Snails are nocturnal with their activity closely linked to moisture availability. Surveys are best carried out at night using a flashlight, or in the morning or evenings following a rain event.

Look on top of plants and structures (fence posts) during dry periods.

Plant Symptoms:  Rasping and defoliation of plants  Aestivate on plant heads and stalks in summertime.

Floyd, J. 2008. New Pest Response Guidelines: Temperate Terrestrial Gastropods. USDA-APHIS-PPQ-Emergency and Domestic Programs, Riverdale, Maryland.

If a suspect is found: Label the sample and keep in a cool dry place until identification can be made. All specimens should be submitted to Patrick Marquez (Western Region) or John Slapcinsky (Eastern Region). Both Domestic Identifiers are able to identify (even immature specimens) to the species level for this genus.

Key to symbols

= Pest Infests Stems = Pest Infests Flowers = Pest Infests Leaves = Pest Infests Seed/Seed head

= Damages young plants =Damages older plants = Damages roots =Damage evident on individual plants

42 Chapter 5: Detailed Survey Tables Cochlicella spp.

Scientific Name Common Name Survey Method Available Cochlicella Conical snails Time Frame: Snails are most abundant in the spring and summer, acuta and C. especially near the edges of fields. barbara Plant Part:

Age of Plant:

Any age of plant attacked. Preferred Method Visual Survey:

See Floyd (2008) Look for snail eggs, juveniles and adults, as well as clues that suggest the presence of mollusk pests which may include: empty snail shells, mucus and “slime” trails, and/or ribbon-like feces.

On rainy or humid days, inspect containers that are suspended inches above the ground, garbage bins, driveways, low-growing bushes, and ground-lying trash.

During dry or hot days, snails are attached, often in clusters of several to many individuals, to plants fences, robust weeds. and other objects; due to this behavior survey during dry weather may actually be easier, especially if snail density is low

Plant Symptoms:  Aestivates on the ears and stalks of cereals, contaminates grain (particularly barley) at harvest, clogs farm machinery, causes delays during harvest, causes damage to harvesting equipment.  Rasping and defoliation of plants  Foul crops and pastures with their slime.

Key to symbols

= Pest Infests Stems = Pest Infests Flowers = Pest Infests Leaves = Pest Infests Seed/Seed head

= Damages young plants =Damages older plants = Damages roots =Damage evident on individual plants

43 Chapter 5: Detailed Survey Tables Heterodera filipjevi

Scientific Name Common Name Survey Method Available Heterodera Cereal cyst Time Frame: In Oregon, symptoms began to appear in wheat in filipjevi nematode March (3-5 leaf stage). Surveys should begin at this time and continue throughout the growing season. Plant Part:

Age of Plant:

Second-stage juveniles begin to attack the plant roots at plant emergence. Preferred Method Soil Sampling:

Use soil sampling ,collection of host roots, or of a combination of both methods.

Signs: Close examination (using the naked eye or a dissecting scope) of roots will reveal the presence of white lemon-shaped females after gently shaking or washing the roots to remove adhering soil.

Symptoms: Slight to severe yellowing and stunting of cereal stands can be observed at an early stage of nematode infestation. Later, infested fields show patchy plant growth associated with poor tillering. Leaf tips often become discolored: reddish yellow on wheat, red on oats, and yellow on barley.

Symptoms occur in patches that enlarge as the nematode population increases.

These symptoms are similar to those caused by other biotic (soilborne fungi) and abiotic stresses (drought, nutrient deficiency).

If a suspect is found: Take soil cores according to preferred methodology and submit to a nematology diagnostic laboratory where nematodes will be extracted from the soil and identified. Sieving, Fenwick-can, and modified Fenwick-can are the best techniques for extraction of cysts and juveniles.

For host root collection, target symptomatic plants via visual survey. Roots with attached cysts should be placed in plastic bags with soil from the rhizosphere and submitted to a nematology diagnostic lab for nematological analysis (extraction and identification). Microscopic examination of the roots is necessary to distinguish cysts caused H. filipjevi from tip swellings or root galls caused by other nematodes.

Key to symbols

= Pest Infests Stems = Pest Infests Flowers = Pest Infests Leaves = Pest Infests Seed/Seed head

= Damages young plants =Damages older plants = Damages roots =Damage evident on individual plants

44 Chapter 5: Detailed Survey Tables Heterodera latipons

Scientific Name Common Name Survey Method Available Heterodera Mediterranean Time Frame: Under Mediterranean conditions, eggs can be latipons cereal cyst observed by early March, when well-developed nematode white females can be easily observed on the roots. From April onwards, white females turn to brown cysts coated by a sub-crystalline layer. Plant Part:

Age of Plant:

Second-stage juveniles begin to attack the plant roots at plant emergence. Preferred Method Soil Sampling:

Use soil sampling, collection of host roots, or of a combination of both methods.

Signs: Before plant flowering, close examination (using the naked eye or a dissecting scope) of roots will reveal the presence of white lemon- shaped females after gently shaking or washing the roots to remove adhering soil.

Symptoms: Slight to severe yellowing and stunting of cereal stands can be observed at an early stage of nematode infestation. Later, infested fields show patchy plant growth associated with poor tillering and shorter spikes. Plants also tend to wilt during warmer portions of the day.

Symptoms occur in patches that enlarge as the nematode population increases.

These symptoms are similar to those caused by other biotic (soilborne fungi) and abiotic stresses (drought, nutrient deficiency).

For host root collection, target symptomatic plants via visual survey. Roots with attached cysts should be placed in plastic bags with soil from the rhizosphere and submitted to a nematology diagnostic lab for nematological analysis (extraction and identification). Microscopic examination of the roots is necessary to distinguish cysts caused H. latipons from tip swellings or root galls caused by other nematodes.

Key to symbols

= Pest Infests Stems = Pest Infests Flowers = Pest Infests Leaves = Pest Infests Seed/Seed head

= Damages young plants =Damages older plants = Damages roots =Damage evident on individual plants

45 Chapter 5: Detailed Survey Tables Meloidogyne artiellia

Scientific Name Common Name Survey Method Available Meloidogyne British root-knot Time Frame: In climates with cool, wet winters and warm, dry artiellia nematode summers, M. artiellia is active during spring and winter months and inactive from late spring through summer. Plant Part:

Age of Plant:

Any age of plant attacked. Prefer to lay eggs immediately before and after flowering. Preferred Method Soil Sampling:

Use soil sampling, collection of host roots, or of a combination of both methods.

Signs: Soil and roots from plants (stunted, chlorotic) are collected and the roots examined with the aid of a stereomicroscope for the presence of galls and nematode egg masses adhering to the small galls. Root galls induced by M. artiellia are very small and often are covered by large egg masses that represent the only visible signs of the nematode infection.

Symptoms: In wheat, spikes are sparse and reduced in size. Chlorosis of aboveground plant parts is possible.

If a suspect is found: Take soil cores according to preferred methodology and submit to a nematology diagnostic laboratory where nematodes will be extracted from the soil and identified.

For host root collection, target symptomatic plants via visual survey. Microscopic examination of the roots is necessary to differentiate swollen roots caused M. artiellia from tip swellings caused by other nematodes. Roots should be placed in plastic bags with soil from the rhizosphere and submitted to a nematology diagnostic lab for nematological analysis.

Key to symbols

= Pest Infests Stems = Pest Infests Flowers = Pest Infests Leaves = Pest Infests Seed/Seed head

= Damages young plants =Damages older plants = Damages roots =Damage evident on individual plants

46 Chapter 5: Detailed Survey Tables Peronosclerospora philippinensis

Scientific Name Common Name Survey Method Available Peronsclerospora Philippine downy Time Frame: Symptoms can be observed as early as 9 days after philippinensis mildew planting. Plant Part:

Age of Plant: Young plants infected but plants of any age can show symptoms. Preferred Method Visual Survey, Sentinel Plots, Spore Trapping:

Use visual survey, sentinel plots, spore trapping, or a combination of methods. For visual survey collect symptomatic plants. Spore traps, similar to those used in soybean rust monitoring, can be used to detect spores. Unsprayed, susceptible plants (sentinel plots) that are scouted regularly can also be used for early detection.

Signs: Downy (grayish) fungal structures are observed primarily on the underside of the leaves.

Symptoms: Chlorotic stripes/streaks are usually the first symptom observed. As the plant ages, leaves may narrow, become abnormally erect, and appear somewhat dried-out. As the corn plant matures, tassels become malformed and produce less pollen, ear formation is interrupted, and sterility of seeds can result.

If a suspect is found: To confirm disease, collect plants showing typical symptoms and downy fungal growth. Place samples in plastic bags. Double bag the samples and deliver promptly to a diagnostic laboratory.

Key to symbols

= Pest Infests Stems = Pest Infests Flowers = Pest Infests Leaves = Pest Infests Seed/Seed head

= Damages young plants =Damages older plants = Damages roots =Damage evident on individual plants

47 Chapter 6: Detailed Diagnostic Methods Autographa gamma

Chapter 6: Diagnostic Methods

Scientific Name, Common Name Tools Diagnostic Method Available Autographa CAPS-Approved Method: Morphological. gamma (Silver-Y Moth) Microscope Required?: YES. To be certain of the presence of A. gamma it is necessary to examine morphological features under a microscope.

Mistaken Identities: Present in Unites States: Autographa californica, Autographa psuedogamma, Syngrapha celsa, Trichloplusia ni

Not present in United States: Cornutiplusia circumflexa, Syngrapha interrogationis

Morphological Guides:

Carter, D.J. 1984. Pest Lepidoptera of Europe with special reference to the British Isles. Dr. W. Junk, Boston.

Emmett, B.J. 1980. Key for identification of lepidopterous larvae infesting Brassica crops. Plant Pathology 29: 122-123.

Nazmi, N., E. El-Kady, A. Amin, and A. Ahmed. 1981. Redescription and classification of subfamily Plusiinae in Egypt. Bulletin de la Societe Entomologique d’Egypte 63: 141-162.

Sannino, L. and B. Espinosa. 2000. Comparative morphological study on pupae of Plusiinae and observations on the vice-like abdominal structures (Lepidoptera, Noctuidae). Atlanta 31: 229- 243.

Egg: Hemispherical; strongly and irregularly ribbed and reticulated; whitish, blue-gray around micropyle.

Larva: Semilooper with three pairs of prolegs only. Head with dark patch below ocelli or entirely black, glossy. Body varies from green with pale erratic longitudinal markings to almost black. Length [of late instar larvae] variable, 30-40 mm. Head green, often with a conspicuous black streak extending posteriorly from ocellar region; in dark specimens, the black streak may be expanded to form a large blotch; body tapered towards head; prolegs present on abdominal segments 5, 6, and 10 only; body varying in color from yellowish green to greenish gray; dorsal line green bordered on either side by a sinuous, narrow, white line; irregular, narrow subdorsal line white; a white or yellowish white band between subdorsal and dorsal marginal lines; spiracles white, peritreme narrow, dark green or black; pinacula white, slightly raised; prothoracic and anal plates concolorous with integument; thoracic legs varying in color from greenish brown to black.

Pupa: Pale green when just formed, gradually turning darkish starting from dorsum; black just before adult emergence. Cuticle generally

Key to symbols

=Hand lens =Microscope =Isozymes

48 Chapter 6: Detailed Diagnostic Methods Autographa gamma

rugose, granulose on head thorax and appendages, smooth on the rest of body. Dorsal cephalic margin of A1-7 finely punctuate by very small papilliform reliefs. Body cephalic end squat, little prominent and flattened. Lanceolate portion of the labium long a little more than half of the total length. Prothoracic femora length, 8-10 times prothoracic femora width. Caudal end of wings and maxillae extending to caudal margin of A6. Maxillae very long, circling forewing tips. Metathoracic legs not visible. Abdominal spiracles elliptical (ratio length/width ca. 3-3.5/1), rather elevated and, on A3- 6, with the cephalic margin prominent with respect to the caudal. Vice-like structures with the caudal jowl regularly rounded and provided with uniformly distributed papilliform reliefs; cephalic jowl in the middle prominent. Semiannular structures, with 6-8 transversal linear thin ridges, of which the inferior and the superior ones are only sketched. Some papilliform reliefs are present underlying the prominent caudal margin. The area beneath the said structures is little rounded and has some papilliform reliefs. Cremaster as typical in the group, with a ratio length/width ca. 1/1 and the basal portion wide twice the apical. It is dorsally canaliculated at the base and irregularly rugose moving towards the posterior end (particularly on the swelling). Body length 17.4 ± 0.2 mm (range 16.0-18.8, No. = 34); body width (across the thorax) 5.3 ± 0.1 mm (r. 5-6.2, No. - 34).

Adults:

Head: Vertex and frons with densely brownish gray, erect hairs. Eyes naked, large, obscure, and densely lashed. Antennae filiform, brownish, about three-fourths of forewing, scape lighter than shaft; labial palpi strong, well developed and upturned with densely rough brownish scales. Tongue developed and coiled.

Wings: Adults of A. gamma can differ in appearance, depending on generation. Specimens of the spring generation are often small, with a more grayish color, and the later generations are often brownish and with a larger wingspan. Wings are 20 mm from mid-thorax to wing tip. Forewing large, dorsally with median area purplish-gray, marked with golden gamma shapes, subterminal line dentated with dark shades; orbicular and reniform spots oblique, constructed on middle; ventrally paler.

Venation: Sc reaching costal margin at about eight-elevenths length of wing; R1 from cell at about seven-twelfths length of cell; R2 from end of accessory cell; R3 and R4 stalked at about one-half way to margin, spaced distally; R5 connate basally with the stem of R3+R4; M1 free, M2, M3 Cu, proximated basally, spaced distally; Cu2 from cell at about five-sixths length of cell; 2A and 3A complete.

Male genitalia: Male genitalia with uncus well developed, hairy, and curved with hook end; tegumen elongate and moderately broad, vinculum moderately narrow; saccus well developed and elongate; valves elongated and broad apically; costa moderately sclerotized; cucullus moderately broad without corona, but with moderately large setae; clasper attached to the middle of valve far from clavus, elongate, finger-like with 6 small setae apically; clavus present, rounded apically and setose; aedeagus large, vesica moderately chitinized and armed with well sclerotized thorn-like cornutus.

Female genitalia: Female genitalia with anal lobes moderate, triangular and clothed with long setae, anterior apophysis shorter

Key to symbols

=Hand lens =Microscope =Isozymes

49 Chapter 6: Detailed Diagnostic Methods Autographa gamma

than posterior apophysis; ostium moderate, colliculum large and well chitinized, ducta bursa moderately long, tubular and somewhat chitinized; corpus bursa large, elongate and well chitinized at the entrance; ductus seminalis present near the top of the ductus bursa.

Additional Resources: Mini-Pest Risk Assessment

Field Screening Aid

Simplified screening aid

Key to symbols

=Hand lens =Microscope =Isozymes

50 Chapter 6: Detailed Diagnostic Methods Copitarsia spp.

Scientific Name, Common Name Tools Diagnostic Method Available Copitarsia spp. CAPS-Approved Method: Morphological. (Owlet moths) Adults can be identified through genitalia dissections. Larvae can only be identified to genus.

Microscope Required?: YES. To be certain of the presence of Copitarsia spp., it is necessary to examine morphological features under a microscope.

Mistaken Identities: Agrotis spp., Euxoa spp., Polia spp., and Orthosia spp.

Morphological Guides:

Riley, D.R. 1998. Identification key for Copitarsia, Spodoptera exigua, and Peridorma saucia, US Department of Agriculture, Animal and Plant Health Inspection Service (Internal Report). Pharr, TX.

Simmons, R.B., and Pogue, M.G. 2004. Redescription of two often confused Noctuid pests, Copitarsia decolora and Copitarsia incommoda (Lepidoptera: Noctuidae: Cucullinae). Annual Entomology Society of America 97(6) 1159-1164.

Simmons. R.B, and Scheffer, S.J. 2004. Evidence of cryptic species within the pest Copitarsia turbata (Herrich-Shaffer) (Lepidoptera: Noctuidae). Annals of Entomology Society of America 97(4): 675 680.

Copitarsia decolora: Description. Medium-sized, light brown or gray moths with well- defined orbicular and reniform spots.

Discussion. C. decolora varies slightly in coloration from lighter to medium brown. Females tend to be larger and have darker hindwings than males. Mitochondrial DNA evidence indicates at least two morphologically cryptic species within C. decolora: one ranging from southern Mexico to Ecuador, the other occurring in Ecuador, Colombia and Peru (Simmons and Scheffer, 2004).

Diagnosis. C. decolora lacks the brush-like androconia found in male C. incommoda. Male C. decolora have a blunt digitus and corona of spines on the valve. Female C. decolora are recognizable due to the speculate, heavily sclerotized antevaginal plate.

Male. Head. Brown; antenna light brown, biserrate and ciliated; palpus light brown, apex white.

Thorax. Patagium brownish gray; mesothorax pale brown; metathorax gray to white; fore, mid, and hindleg mixed with white and brown scales, tibial spurs striped with brown; tarsi white.

Wings.

Key to symbols

=Hand lens =Microscope =Isozymes

51 Chapter 6: Detailed Diagnostic Methods Copitarsia spp.

Forewing. Length = 13 to 18 mm (average = 16.1 mm, SD = 1.3 mm, n= 14). Ground color light brown or gray; antemedial and postmedial lines, double row of brown zigzag lines, with white between them; basal area with well defined brown lines; reniform spot brown outlined in white; orbicular spot ground color with white inner and black outer margin; outer margin with triangular black spots between wing veins; fringe grayish brown.

Hindwing. Ground color white; wide marginal band brown; veins toward wing margin brown; fringe brown basally, remainder white.

Abdomen. First three abdominal segments light gray, remainder of abdomen gray; genital tuft gray; sclerotized patches present in pleural membrane near second abdominal segment; hair brushes, scent pouches and modified S2 absent; terminal tergite weakly sclerotized medially, more heavily sclerotized laterally, forming two circular areas.

Genitalia. Tegumen rounded; uncus apically swollen, bearing long setae; saccus extended into narrow point; valve sinuate, tapering to pointed apex; corona present; ampulla attenuate, apex extending beyond costal margin of valve; digitus spatulate; juxta a broad plate with pointed lateral margins, medio-ventral plate with rounded, sinnuate margins, dorsal margin V-shaped with a pair of ventrally produced arms with dorsally curved apices; spinose pad present above aedeagus; apex of aedeagus with a small sclerotized plate (sp) consisting of one large and two pointed projections, a large serrate sclerotized plate (lp) opposite small plate; vesica elongate; cornuti various sized elongate spines in both clusters and solitary in a spiral line in basal one-quarter of vesica.

Female. As in male, except antennae filiform and cilated; forewing length = 14 to 18 mm (average = 16.8 mm, SD = 1.2 mm, n =24); hindwing darker than males.

Genitalia. Papillae anales, posterior apophyses unmodified; anterior apophyses reduced in length, thickened; S8 unmodified; antevaginal plate U-shaped, spiculate texture, symmetrical; ductus bursae sclerotized, spinose; corpus bursae deeply ridged, spherical, three lines of signa; appendix bursae larger than corpus bursae, membranous, irregular in shape; ductus seminalis from posterior of appendix bursae.

Copitarsia incommoda:

Description. Medium-sized, pale brown moths, with well-defined orbicular and reniform spots, and light brown hindwings.

Discussion. C. incommoda varies slightly in coloration from lighter to medium brown. Females tend to be larger and have darker hindwings than males.

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52 Chapter 6: Detailed Diagnostic Methods Copitarsia spp.

Diagnosis. C. incommoda is often confused with C. decolora. Males of C. incommoda can be identified externally by their brush-like androconia on the second abdominal segment (sometimes only after dissection), which are absent in C. decolora. Male C. incommoda has a rounded digitus, and valves lack a corona of spines that are present in C. decolora. Female C. incommoda can be identified by the smooth texture of the U-shaped antevaginal plate, compared with the spiculate antevaginal plate found in C. decolora.

Male. Head. Brown; antenna pale brown, filiform and ciliated; palpus brown.

Thorax. Patagium brown; mesothorax lighter, tawny brown; metathorax cream to white; fore, mid, and hindleg mixed white and brown, tibial spurs striped with brown, tarsi white.

Wings. Forewing. Length = 14 to 18 mm (average = 16 mm, SD = 1.3 mm, n = 15). Ground color light brown; antemedial and postmedial lines, a double row of brown zigzag lines with white between them; basal area with well-defined brown lines; reniform spot ground color with white inner and black outer margin; orbicular spot ground color outlined in black; outer margin with triangular black spots between wing veins; fringe brown.

Hindwing. Ground color brown mixed with white scales basally; fringe light brown basally, rest white.

Abdomen. Brown, genital tuft white; hair brushes, scent pouches and modified S2 present; terminal tergite as in C. decolora.

Genitalia. As in C. decolora, except corona absent; digitus slender, apex round, not spatulate; apex of aedeagus with a small sclerotized plate (sp) consisting of one large, one small, and three minute pointed projections; a series of variously sized, heavily sclerotized spines opposite small plate (ss); cornuti in a similar pattern to that of C. decolora, but more robust.

Female. As in male, except forewing length = 14 to 19 mm (average = 17.2 mm, SD = 1.3 mm, n = 18); hindwing darker than males.

Genitalia. As in C. decolora, except lateral lobes of U- shaped antevaginal plate larger than C. decolora.

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53 Chapter 6: Detailed Diagnostic Methods Diabrotica speciosa

Scientific Name, Common Name Tools Diagnostic Method Available Diabrotica CAPS-Approved Method: Morphological. speciosa (Cucurbit beetle) Diabrotica speciosa is almost identical to D. balteata, which is widely present in the southern United States. Confirmation by a chrysomelid specialist is required.

Microscope Required? YES. To be certain of the presence of D. speciosa, it is necessary to examine morphological features under a microscope.

Mistaken Identities: D. speciosa can also be confused with Diabrotica viridula (not present in the United States) and other pestiferous Diabrotica species in South America.

Morphological Guides:

Araujo Marques, M. 1941. Contributio ao estudo dos crisomeledeos do gunero Diabrotica. Bol. Escola Nac. Agron., 2:61-143. (In Portuguese)

Baly, J.S. 1886. The Colombian species of the genus Diabrotica, with descriptions of those hitherto uncharacterized. Part I. Zoological Journal of the Linnean Society, 19:213-229.

Christensen, J.R. 1943. Estudio sobre el g'nero Diabrotica Chev. en la Argentina. Rev. Facultad de Agronomia y Veterinaria, 10:464-516. (In Spanish)

Defago, M.T. 1991. Caracterizacion del tercer estadio larval de Diabrotica speciosa. Rev. Peruana de Ent., 33:102-104. (In Spanish)

Krysan, J.L. 1986. Introduction: biology, distribution, and identification of pest Diabrotica. In: [Krysan JL, Miller TA, eds.] Methods for the Study of Pest Diabrotica. New York, USA: Springer.

Eggs: Eggs are ovoid, about 0.74 x 0.36 mm, clear white to pale yellow. They exhibit fine reticulation that under the microscope appears like a pattern of polygonal ridges that enclose a variable number of pits (12 to 30). Eggs are laid in the soil near the base of a host plant in clusters, lightly agglutinated by a colorless secretion. The mandibles and anal plate of the developing larvae can be seen in mature eggs.

Larvae: Defago (1991) published a detailed description of the third instar of D. speciosa. First instars are about 1.2 mm long, and mature third instars are about 8.5 mm long. They are subcylindrical; chalky white; head capsule dirty yellow to light brown, epicraneal and frontal sutures lighter, with long light-brown setae; mandibles reddish dark brown; antennae and palpi pale yellow. Body covered by sparse, short, dark setae; light brown irregular prothoracic plate; dark brown anal plate on the ninth segment, with a pair of small urogomphi. A pygopod is formed by the tenth segment, which serves as a locomotion and adherence organ.

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54 Chapter 6: Detailed Diagnostic Methods Diabrotica speciosa

Pupae: Pupae are 5.8 to 7.1 mm long and white. Females with a pair of tubercles near the apex. Mature third instars build an 8 x 4 mm oval cell in the soil in which they pupate, and tenerals remain for about 3 days.

Adults: Full descriptions of D. speciosa are given by Baly (1886), Araujo Marques (1941), and Christensen (1943). Adults are 5.5 to 7.3 mm long; antennae 4 to 5 mm. General color grass-green (USDA, 1957); antennae filiform and dark (reddish-brown to black) and nearly equal to the body in length, first three basal segments lighter; head ranging from reddish brown to black; labrum, scutellum, metathorax, tibiae and tarsi black; elytra each with three large oval transverse spots, basal spots larger and usually reddish toward the humeral callus, the rest yellow. Ventrally, head and metathorax dark brown, prothorax green, mesothorax and abdomen light brown or yellow-green. Pronotum bi-foveate, convex, smooth, shiny, ¼ wider than long. Male antennae proportionally longer than female antennae. Males with an extra sclerite on the apex of the abdomen that makes it look blunt, compared with the rather pointed female apex.

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55 Chapter 6: Detailed Diagnostic Methods Helicoverpa armigera

Scientific Name, Diagnostic Method Available Common Name Tools Helicoverpa CAPS-Approved Method: Morphological. armigera (Old World Helicoverpa armigera can be visually screened to some degree, Bollworm) but definitive screening and identification requires dissection. Helicoverpa armigera and the native, abundant species, Helicoverpa zea are very similar looking.

Final identification is by dissection of (adult) male genitalic structures.

Microscope Required? Yes. To be certain of the presence of H. armigera, it is necessary to examine morphological features under a microscope.

Mistaken Identities: Present in United States: Helicoverpa zea, Heliothis virescens

Not present in United States: Helicoverpa punctigera, Helicoverpa assulta.

Hardwick, D.F. 1965. The corn earworm complex. Memoirs of the Entomological Society of Canada 40: 1-247.

King, A.B.S. 1994. Heliothis/Heliocoverpa (Lepidoptera: Noctuidae). pp 39-106. In: G. A. Matthews, J. P. Tunstall (eds.), Insect Pests of Cotton. CAB International, Wallingford.

Kirkpatrick, T.H. 1961. Comparative morphological studies of Heliothis species (Lepidoptera: Noctuidae) in Queensland. Queensland Journal of Agricultural Science 18: 179-194.

Pogue, M.G. 2004. A new synonym of Helicoverpa zea (Boddie) and differentiation of adult males of H. zea and H. armigera (Hubner) (Lepidoptera:Nocutidae:Heliothinae). Ann. Entomol. Soc. Am. 97(6): 1222-1226.

Egg: Yellowish-white and glistening at first, changing to dark-brown before hatching; pomegranate-shaped, 0.4 to 0.6 mm in diameter; the apical area surrounding the micropyle is smooth, the rest of the surface sculptured in the form of approximately 24 longitudinal ribs, alternate ones being slightly shorter, with numerous finer transverse ridges between them; laid on plants which are flowering, or are about to produce flowers.

Larva: The first and second larval instars are generally yellowish- white to reddish-brown in color, without prominent markings; head, prothoracic shield, supra-anal shield and prothoracic legs are very dark-brown to black, as are also the spiracles and tuberculate bases to the setae, which give the larva a spotted appearance; prolegs are present on the third to sixth, and tenth, abdominal segments. A characteristic pattern develops in subsequent instars. Fully grown larvae are approximately 30 to 40 mm long; the head is brown and mottled; the prothoracic and supra-anal plates and legs are pale-brown, only claws and spiracles remaining black; the skin surface consists of close-set, minute tubercles. Crochets on the

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56 Chapter 6: Detailed Diagnostic Methods Helicoverpa armigera

prolegs are arranged in an arc. The final body segment is elongated.

Color pattern: a narrow, dark, median dorsal band; on each side, first a broad pale band, then a broad dark band; on the lateral line, a broad, very light band on which the row of spiracles shows up clearly. The underside is uniformly pale. On the basic dorsal pattern, numerous very narrow, somewhat wavy or wrinkled longitudinal stripes are superimposed. Color is extremely variable and the pattern described may be formed from shades of green, straw- yellow, and pinkish- to reddish-brown or even black.

Pupa: Mahogany-brown, 14 to 18 mm long, with smooth surface, rounded both anteriorly and posteriorly, with two tapering parallel spines at posterior tip.

Adult: Stout-bodied moth of typical noctuid appearance, with 3.5 to 4 cm wing span; broad across the thorax and then tapering, 14 to 18 mm long; color variable, but male usually greenish-grey and female orange-brown. Forewings have a line of seven to eight blackish spots on the margin and a broad, irregular, transverse brown band. Hindwings are pale-straw color with a broad dark- brown border that contains a paler patch; they have yellowish margins and strongly marked veins and a dark, comma-shaped marking in the middle. Antennae are covered with fine hairs.

Additional Resources: Mini-Pest Risk Assessment

Field Screening Aid

Male Genetalia Dissection Instructions

Additional Dissecting Instructions

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57 Chapter 6: Detailed Diagnostic Methods Heteronychus arator

Scientific Name, Common Name Tools Diagnostic Method Available Heteronychus CAPS-Approved Method: arator (African Morphological. black beetle) Microscope Required?: No. African beetle larvae can be identified with the naked eye, since their anal opening is horizontal, compared with a vertical opening in other species. However, microscopic detail will aid in identification and diagnosis.

Mistaken Identities: Not present in United States.: Australaphodius frenchi

Morphological Guides:

Smith, T.J., Petty, G.J., and Villet, M.H. 1995. Description and identification of white grubs (Coleoptera: Scarabaeidae) that attack pineapple crops in South Africa. African Entomology 3: 153-166.

Cumpston, D.M. 1940. On the external morphology and biology of Heteronychus sanctae Helenae Blanch and Metanastes vulgivagus Olliff (Col., Scarabaeidae, Dynastinae). Proceedings of the Linnaean Society of New South Wales 65: 289-300.

Endrodi, S. 1985. The Dynastinae of the world. Dordrecht, Netherlands: Dr. W. Junk.

Smith et al. (1995) provided detailed illustrated descriptions and a laboratory and field key to third star larvae. Cumpston (1940) also described the features of the larvae that allow H. arator to be distinguished from other species. Keys to identify adults from related species are given by Enrodi (1985).

Eggs: White, oval, and measuring approximately 1.8 mm long at time of oviposition. Eggs grow larger through development and become more round in shape. Eggs are laid singly at a soil depth of 1 to 5 cm. Females each lay between 12 to 20 eggs total. In the field, eggs hatch after approximately 20 days. Larvae can be seen clearly with the naked eye.

Larvae: There are three larval instars. Larvae are creamy-white except for the brown head capsule and hind segments, which appear dark where the contents of the gut show through the body wall. The head capsule is smooth textured, measuring 1.5 mm, 2.4 mm, and 4.0 mm at each respective instar. The third-instar larva is approximately 25 mm long when fully developed. African black beetle larvae are soil-dwelling and resemble white 'curl grubs.’ They have three pairs of legs on the thorax, a prominent brown head with black jaws, and are up to 25 mm long. The abdomen is swollen, baggy, and gray/blue-green due to the food and soil they have eaten. Larvae eat plant roots, potentially causing significant damage to turf, horticultural crops, and ornamentals. Turf is the preferred host of the larvae.

Pupae: The larvae, when fully grown, enter a short-lived pupal stage. The pupae measure approximately 15 mm long and are typically coleopteran in form (cylindrical shape), initially pale yellow, but becoming reddish-brown nearer to the time of

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58 Chapter 6: Detailed Diagnostic Methods Heteronychus arator

emergence.

Adults: Beetles are 12 to 15 mm long; shiny black dorsally and reddish-brown ventrally. The females are slightly larger than males. Males and females are readily differentiated by the shape of the foreleg tarsus. The tarsus of the male is much thicker, shorter, and somewhat hooked compared with that of the female, which is longer and filamentous. A less obvious sexual difference is in the form of the pygidium at the end of the abdomen. In the male, it is broadly rounded, and in the female, it is apically pointed. The beetle is the main pest stage.

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59 Chapter 6: Detailed Diagnostic Methods Lobesia botrana

Scientific Name, Common Name Tools Diagnostic Method Available Lobesia botrana CAPS-Approved Method: Morphological. (European Larvae can be keyed out using Gilligan et al. (2008). Identification grapevine moth) of adults requires dissection of the male genitalia; use Brown, 2009 and Passoa, 2009.

Brown, J. 2009. Adult Lepidoptera Workshop.

Gilligan T.M., Wright, T.J., and Gibson, L. 2008. Olethreutine Moths of the Midwestern United States. An Identification Guide. Bulletin of the Ohio Biological Survey, new series, Volume 16 (2), 334 pp.

Passoa, S. 2009. Screening Key for CAPS Target Tortricidae in the Eastern and Midwestern United States (males). Lab Manual for the Lepidoptera Identification Workshop. University of Maryland.

Microscope Required?: YES. To be certain of the presence of L. botrana, it is necessary to examine morphological features under a microscope.

Mistaken Identities: L. botrana can be confused with Endopiza viteana (present in the United States) and Eupoecilia ambiguella (not present in the United States).

Morphological Guides:

Bradley, J. D., W. G. Tremewan, and A. Smith. 1979. Lobesia botrana (Denis & Schiffermüller), pp. 69-70, British Tortricoid Moths Tortricidae: Olethreutinae. The Ray Society, London, England.

Castro, A. R. 1943. Fauna entomologica de la vid en España. Estudio sistematicobiologico de las especies de mayor importanica económica. Instituto español de entomologia, Madrid.

Hannemann, H. 1961. Tribus: Olethreutini Obraztsov, pp. 180-220, Die Tierwelt Deutschlands und de Angrenzenden Meeresteile. Veb Gustav Fischer Verlag.

Razowski, J. 1989. The genera of Tortricidae (Lepidoptera). Part II: Palaearctic Olethreutinae. Acta Zoological Cracoviensia 32: 107-328.

Vennette, R. C., Davis, E.E., Dacosta, M., Heisler, H., and Larson, M. 2003. Mini Risk Assessment – Grape berry moth, Lobesia botrana (Denis & Schiffernuller) [Lepidoptera: Tortricidae]. Appendix C. Mini-Pest Risk Assessment

Eggs: The egg of L. botrana is of the so-called “flat type”, with the long axis horizontal and the micropile at one end. Elliptical, with a mean eccentricity of 0.65, the egg measures about 0.65 to 0.90 x 0.45 to 0.75 mm. Freshly laid eggs are pale cream or yellow, later becoming light gray and translucent with iridescent glints. The chorion is macroscopically smooth but presents a slight polygonal reticulation in the border and around the micropile. As typically occurs in the subfamily Olethreutinae, eggs are laid singly, and

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60 Chapter 6: Detailed Diagnostic Methods Lobesia botrana

more rarely in small clusters of two or three.

Larvae: There are usually five larval instars. Neonate larvae are about 0.95 to 1 mm long, with head and prothoracic shield deep brown, nearly black, and body light yellow. Mature larvae reach a length between 10 and 15 mm, with the head and prothoracic shield lighter than neonate larvae and the body color varying from light green to light brown, depending principally on larval nourishment.

Pupae: Female pupae are larger (5 to 9 mm) than males (4 to 7 mm). Freshly formed pupae are usually cream or light brown but also light green or blue, and a few hours later become brown or deep brown.

The sexes may be distinguished by the position of genital sketches that are placed in the IX and VIII abdominal sternites in males and females, respectively. Moreover, the male genital orifice is placed between two small lateral prominences. When adult emergence is imminent, pupae perforate the cocoon, resting the exuvia fixed outwardly in a characteristic position by cremaster spines.

Adults: Adults are 6 to 8 mm long with a wingspan of about 10 to 13 mm. The head and abdomen are cream colored; the thorax is also cream with black markings and a brown ferruginous dorsal crest. The legs have alternate pale cream and brown bands. Forewings have a mosaic-shaped pattern with black, brown, cream, red and blue ornamentation. The ground color is bluish gray and fasciae brown, shaped by a pale cream border; scales lining the costa, termen and dorsum are darker than the wing ground color.

Cilia are brown with a paler apical tip and a cream basal line along the termen. The underside is brownish gray, gradually darker towards the costa and apex. Cilia and cubital tuft are grayish brown with a paler basal line.

There is no clear sexual dimorphism, but the sexes may be easily separated by their general morphology and behavior: as in the pupal stage, males are smaller than females, they have a narrower abdomen with an anal fine comb of modified scales (hair pencils), and when disturbed they exhibit movements more quick and nervous than those of females.

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61 Chapter 6: Detailed Diagnostic Methods Nysius huttoni

Scientific Name, Diagnostic Method Available Common Name Tools Nysius huttoni CAPS-Approved Method: Morphological. (Wheat bug) The size and color of N. huttoni bugs are extremely variable. The insects resemble many native lygaeids. Identification can be made by careful observation under a microscope by four key characters by a Hemipteran specialist.

Microscope Required?: Yes. To make a species level identification it is necessary to examine morphological features under a microscope.

Mistaken Identities: Nysius huttoni can be confused with 12 native Nysius species and Rhypodes cognatus (present in the United States) and Nysius vinitor (not present in United States).

Morphological Guides: Eyles, A.C. 1960. Variations in adult and immature stages of Nysius huttoni White (Heteroptera: Lygaeidae) with a note on the validity of the genus Brachynysius Usinger. Trans. R. Entoml Soc. 112(4): 53-72.

Lariviere, M.C., and Larochelle, A. 2004. Fauna of New Zealand. Vol. 50. Heteroptera (Insecta: Hemiptera) catalogue

Notes on taxonomy: Nysius huttoni is an extremely variable species, with three inter-breeding forms based on the extent of wing development (Aukema et al., 2005).

Eggs: Oval, length about three times width; mean length about 0.8 mm, mean width about 0.3 mm. Straw yellow to creamy white; cephalic (head) end more orange when first laid, deep orange when about to hatch.

Nymphs: Generally pale gray to orange, marked with varying degrees of brown, black, and gray; length from about 0.5 mm in instar I to about 2.0 mm in instar V. Head dark brown to black with longitudinal pale gray to orange stripes. Instars I-IV with pronutum (and wing pads in instars III-IV) dark brown to black; in instar V, pronutum pinkish to gray, variably marked with brown and black, lateral margins and mesal line pale, apex of wing pads and broad U-shaped mark on pronotum black. Dorsal surface of abdomen grayish blue, each segment with transverse row of whitish spots surrounded by narrow red ring. Legs pale brown, spotted with black.

Adults: Length 3.5-4.3 mm; width 1.3-1.8 mm. Dorsally clothed with short, appressed, golden to silvery, sericeous pubescence, intermixed with erect, simple setae. Head wider than long, black, mesal area yellow to reddish yellow. Antennae about twice as long as head width, brown to black, 1st segment sometimes yellowish. Pronutum trapeziform, distinctly punctuate, brown, humeral angles and base of meson yellow; scutellum shiny black. Hemelytra brown, variably mottled and spotted with yellow, corial margins uniformly brown, apical margin of each corium bordering the membrane with three dark-brown spots sometimes coalesced into extensive dark area. Membrane nearly clear, cross-hatched with white lines,

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62 Chapter 6: Detailed Diagnostic Methods Nysius huttoni

basal area often fuscous. Undersurface mostly black, abdomen mottled with yellow, coxal clefts yellow. Femora dark brown with apices, dorsal line, and edges broken by yellow, tibiae yellow, tarsi and claws yellow to brown.

Adults can be divided into three size groups: large (3.5-4.3 mm), medium-sized (3.0-3.8mm), and small (2.3-3.2 mm). All individuals of the large group are long winged or macropterous, but adults in the medium-sized and small groups have three forms ranging from macropterous, sub-bracypterous, to brachypterous (short winged).

Additional Resources: PaDIL-Fact Sheet and Images

Identification aid

Field screening aid

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63 Chapter 6: Detailed Diagnostic Methods Spodoptera littoralis

Scientific Name, Diagnostic Method Available Common Name Tools Spodoptera CAPS-Approved Method: Morphological. littoralis (Egyptian Cotton It is difficult to distinguish from S. litura without close examination of Leafworm) the genitalia.

Microscope Required?: Yes. To be certain of the presence of S. littoralis it is necessary to examine morphological features under a microscope.

Mistaken Identities: Present in United States: S. dolichos, S. ornithogalli, S. latifascia and other Spodoptera species.

Not present in United States: S. litura

Morphological Guides:

Brown, E.S. and C. F. Dewhurst. 1975. The genus Spodoptera (Lepidoptera, Noctuidae) in Africa and the Near East. Bulletin of Entomological Research, 65:221-262.

Pinhey, E.C.G. 1975. Moths of Southern Africa. Descriptions and colour illustrations of 1183 species. Moths of Southern Africa.

Mochida, O. 1973. Two important insect pests, Spodoptera litura F.) and S. littoralis (Boisd.)(Lepidoptera:Noctuidae), on various crops - morphological discrimination of the adult, pupal and larval stages. Applied Entomology and Zoology, 8:205-214.

Pogue, MG. 2002. A world revision of the genus Spodoptera Guenée (Lepidoptera: Noctuidae). Memoirs of the American Entomological Society 43.

Eggs: Spherical, somewhat flattened, 0.6 mm in diameter, laid in clusters arranged in more or less regular rows in one to three layers, with hair scales derived from the tip of the abdomen of the female moth. The hair scales give the eggs a “felt-like appearance”. Usually whitish-yellow in color, changing to black just prior to hatching, due to the big head of the larva showing through the transparent shell.

Larvae: Upon hatching, larvae are 2-3 mm long with white bodies and black heads and are very difficult to detect visually. Larvae grow to 40 to 45 mm and are hairless, cylindrical, tapering towards the posterior and variable in color (blackish-gray to dark green, becoming reddish-brown or whitish-yellow). The sides of the body have dark and light longitudinal bands; dorsal side with two dark semilunar spots laterally on each segment, except for the prothorax; spots on the first and eighth abdominal segments larger than the others, interrupting the lateral lines on the first segment.

Pupae: When newly formed, pupae are green with a reddish color on the abdomen, turning dark reddish-brown after a few hours. The general shape is cylindrical, 14-20 x 5 mm, tapering towards the posterior segments of the abdomen. The last segment ends in two

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64 Chapter 6: Detailed Diagnostic Methods Spodoptera littoralis

strong straight hooks.

Adults: Moth with gray-brown body, 15 to 20 mm long; wingspan 30 to 38 mm; forewings gray to reddish brown with paler lines along the veins (in males, bluish areas occur on the wing base and tip); the ocellus is marked by two or three oblique whitish stripes. Hindwings are grayish white, iridescent with gray margins and usually lack darker veins

Additional Resources: Mini-Pest Risk Assessment

New Pest Response Guideline

Screening Aid

Wing Diagnostics

Simple Field Key of Late Instars

Expanded Key to Late Instars

Final draft - Key to Spodoptera

Passoa (2009) - Slides 13-15, 45, 46

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65 Chapter 6: Detailed Diagnostic Methods Spodoptera litura

Scientific Name, Diagnostic Method Available Common Name Tools Spodoptera litura CAPS-Approved Method: (Rice cutworm) Morphological-It is difficult to distinguish from S. littoralis without close examination of the genitalia.

Consult appropriate keys by Todd and Poole (1980) and Pogue, (2002). To separate from other noctuids, use the key developed by Todd and Poole (1980).

Pogue, MG. 2002. A world revision of the genus Spodoptera Guenée (Lepidoptera: Noctuidae). Memoirs of the American Entomological Society 43.

Todd, E. L. and Poole, R.W. 1980. Keys and illustrations for the armyworm moths of the Noctuidae genus Spodoptera guenee from the Western Hemisphere. Ann. Entomol. Soc. Am. 73: 722- 738.

Microscope Required? Yes. To be certain of the presence of S. litura it is necessary to examine morphological features under a microscope.

Mistaken Identities: Present in United States: S. dolichos, S. ornithogalli, S. latifascia and other Spodoptera species.

Not present in United States: S. littoralis

Morphological Guides:

Hill, D.S. 1975. Agricultural insect pests of the tropics and their control. Cambridge Univ. Press, London.

Mochida, O. 1973. Two important insect pests, Spodoptera litura F.)and S. littoralis (Boisd.)(Lepidoptera: Noctuidae), on various crops - morphological discrimination of the adult, pupal and larval stages. Applied Entomology and Zoology, 8:205-214.

Pearson, E.O. 1958. The insect pests of cotton in tropical Africa. Commonwealth Inst. Entomol., London.

Diagnosis: Some males may look different from females externally, for example, most males have a yellowish forewing patch between the antemedial and postmedial lines below vein M. The orbicular spot is more solid in the male. Forewing length is 14-17 mm, and forewing background color ranges from brown to cream. Male genitalia with juxta triangulate; base of ampulla narrower than in S. littoralis; dorsal lobes of coremata almost as long as ventral lobes. Female genitalia with distal margin of ventral plate of ostium bursa a broad V-shaped notch; ductus bursae longer than S. littoralis.

Eggs: Spherical, somewhat flattened, sculpted with approximately 40 longitudinal ribs, 0.4 - 0.7 mm in diameter; pearly green, turning black with time, laid in batches covered with pale orange-brown or pink hair-like scales from the females body.

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66 Chapter 6: Detailed Diagnostic Methods Spodoptera litura

Larva: Newly hatched larvae are tiny, blackish green with a distinct black band on the first abdominal segment. Fully grown larvae are stout and smooth with scattered short setae. Head shiny black, and conspicuous black tubercules each with a long hair on each segment. Color of fully grown larvae not constant, but varies from dark gray to dark brown, or black, sometimes marked with yellow dorsal and lateral stripes of unequal width. The lateral yellow stripe bordered dorsally with series of semilunar black marks. Mature larvae are 40-50 mm. Two large black spots on first and eight abdominal segments.

Pupa: Reddish brown in color, enclosed inside rough earthen cases in the soil, 18-22 mm long, last abdominal segment terminates in two hooks.

Adult: Body whitish to yellowish, suffused with pale red. Forewings dark brown with lighter shaded lines and stripes. Hind wings whitish with violet sheen, margin dark brown and venation brown. Thorax and abdomen orange to light brown with hair-like tufts on dorsal surface. Head clothed with tufts of light and dark brown scales. Body length 14-18 mm, wing span 28-38 mm.

Additional Resources: Mini-Pest Risk Assessment

PaDIL images

New Pest Response Guideline

Screening Aid

Wing Diagnostics

Simple Field Key of Late Instars

Expanded Key to Late Instars

Passoa (2009) - Slides 13-15, 45, 46

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67 Chapter 6: Detailed Diagnostic Methods Cernuella virgata

Scientific Name, Common Name Tools Diagnostic Method Available Cernuella virgata CAPS-Approved Method: (Maritime Morphological- Confirmation requires a morphological Gardensnail) identification. All specimens should be submitted to Patrick Marquez (Western Region) or John Slapcinsky (Eastern Region). Both Domestic Identifiers are able to identify (even immature specimens) to the species level for this genus.

Microscope Required?: No.

Mistaken Identities: C. virgata closely resembles the white Italian snail (Theba pisana) in appearance and pest status. C. virgata can be distinguished from T. pisana based on more pronounced spiral banding and the umbilicus (the hole about which the shell spirals) appears as a circular hole rather than being partially obscured as in the white Italian snail.

Morphological Guides:

Baker, G.H. 1988. The life history, population dynamics and polymorphism of Cernuella virgata (Mollusca: Helicidae). Australian Journal of Zoology 36: 497-512.

The shell of C. virgata is globose-depressed, and white or yellowish- white in color with dark-brown bands or spots. Snail size is 6 to 19 mm high x 8 to 25 mm wide. The small size and prominent spiral banding are the main diagnostic characteristics of this mollusk. It is important to note that banded and unbanded morphs have been found throughout Australia.

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68 Chapter 6: Detailed Diagnostic Methods Cochlicella spp.

Scientific Name, Common Name Tools Diagnostic Method Available Cochlicella acuta CAPS-Approved Method: and C. barbara Morphological- Confirmation requires a morphological (Conical snails) identification. All specimens should be submitted to Patrick Marquez (Western Region) or John Slapcinsky (Eastern Region). Both Domestic Identifiers are able to identify (even immature specimens) to the species level for this genus.

Microscope Required?: No.

Mistaken Identities: Both species (Cochlicella acuta and C. barbara) of conical snail are fawn or brown. The size and shape of the shell of mature specimens can be used to separate the two species. The shells of mature pointed snails are 12 to 18 mm long and the ratio of the shell length to its diameter at the base is always greater than two. The shells of mature small pointed snails are 8 to 10 mm long and the ratio of the shell length to its diameter at the base is always two or less.

Morphological Guides:

Kerney, M.P., and Cameron, R.A.D. 1979. A field guide to the land snails of Britain and North-west Europe. William Collins Sons and Co. Ltd., London.

C. acuta: 10-20 (rarely 30) x 4-7 mm. Shell a very elongated cone, with 8-10 slightly convex whorls with moderate sutures. Umbilicus minute, obscured by reflected columellar lip. Mouth elliptical, taller than broad, lacking internal rib. Shell white or ginger, often with darker bands and blotches, color and pattern very variable. Growth ridges irregular and rather weak. Prefers maritime habitat, usually in dunes and coastal grassland, occasionally calcareous ground inland.

C. barbara: 8-12 x 5-8 mm. Shell is elongated cone of 7-8 very slightly convex whorls with shallow sutures. Umbilicus minute and partly obscured by columellar lip. Mouth elliptical and lacking internal rib. Shell thick and white, with some variation in color and banding as in C. acuta. Growth-ridges slightly more pronounced than in C. acuta, especially on last whorl. Prefers dry exposed sites near the sea, especially dunes.

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69 Chapter 6: Detailed Diagnostic Methods Heterodera filipjevi

Scientific Name, Common Name Tools Diagnostic Method Available Heterodera CAPS-Approved Method: filipjevi (Cereal Morphological-Confirmation of H. filipjevi is by morphological cyst nematode) identification. Keys are available for identification by morphological characteristics of the cyst, second-stage juvenile, male, and female. Handoo (2002) provides a key to the species within the H. avenae group, as well as a thorough review of morphological studies to date.

Handoo, Z. 2002. A key and compendium to species of the Heterodera avenae group (Nematoda: Heteroderidae). Journal of Nematology 34(3): 250-262.

Microscope Required?: Yes. To be certain of the presence of H. filipjevi, a combination of morphological and molecular features must be used. It is necessary to examine specimens under a microscope.

Mistaken Identities: H. filipjevi has been confused with several other cyst nematode species that parasitize cereals, including (but not limited to) H. avenae, H. bifenestra, H. hordecalis, H. latipons, H. mani, H. pakistanensis, H. tucomanica, and H. zeae.

Morphological Guides:

Handoo, Z.A. 2002. A key and compendium to species of the Heterodera avenae group (Nematoda: Heteroderidae). Journal of Nematology 34: 250-262.

Holgado, R., Rowe, J.A., and Magnusson, C. 2004. Morphology of cysts and second stage juveniles of Heterodera filipjevi (Madzhidov, 1981) Stelter, 1984 from Norway. Journal of nematode morphology and systematics 7(1): 77-84.

Diagnosis: Heterodera filipjevi is diagnosed by the following morphometrics (morphological measurements): Cyst length elongate 690 µm (490-830); bullae and underbridge present; vulval slit length 7 µm (6-8); second stage juvenile stylet length 27 µm (22-31) with slightly concave anteriorly directed knobs; tail length 57 µm (49-63); hyaline tail terminus length 35 µm (31-39) (Handoo, 2002).

Eggs: Cylindrical with rounded edges.

Second-stage juveniles (J2s): Body length ranges from 455-557 µm, and the tail is tapering to a rounded tip. The length of the tail is 52-67 µm and its hyaline part measures 30-41 µm, corresponding to more than 50% of the total tail length. The head is offset and usually with three annules, and the distance from the head to the valves of the median bulb is 59-79 µm. The lateral fields have four lines, of which the inner two are more distinct, and the outer bands are heavily areolated. The stylet is robust with anchor-shaped basal knobs, and measures 22-25 µm in length. The ratio of hyaline tail to the true tail is 1.2-1.7 (Holgado et al., 2004).

Cysts: Newly formed cysts are lemon-shape, similar to H. avenae, H. latipons, and H. hordecalis and partially covered with a white sub- crystalline layer. The cyst wall has ridges running in zigzag patterns, and irregularly arranged punctations and pores. The cyst is golden to light warm brown and is almost transparent, with the outline of individual

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70 Chapter 6: Detailed Diagnostic Methods Heterodera filipjevi

eggs clearly visible. The cyst length is 455-874 µm and 253-747 µm in width. The vulval cone is bifenestrate with horseshoe-shaped semifenestra and has an underbridge. The vulval slit varies between 6.0 and 10.8 µm and the width of the vulval bridge is 7.2-13.1 µm. The fenestral length ranges from 38.4 to 58.4 µm and the length of the semifenestrae are 19.3-32.0 µm. The ratio between fenestral length and width was in the range of 1.7-2.8. The dimensions of the underbridge were 53-110 µm in length and 4.0-11.3 µm in width. The bullae are weak to medium, distinct, and mostly globular in shape with a pale to medium brown color. Their position and arrangement vary between focal planes (Holgado et al., 2004).

Females: Gravid females are pearly-white and lemon-shaped, with protruding neck and vulva cone. The cuticle bears a zigzag pattern that runs concentrically around the neck and vulval regions. The head is offset, with a squarish and prominent labial disc. The female stylet has sloping knobs. Ovaries are paired and convoluted. The vulva is slit-like, protruding posteriorly. The anus is distinct (Holgado et al., 2004).

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71 Chapter 6: Detailed Diagnostic Methods Heterodera latipons

Scientific Name, Common Name Tools Diagnostic Method Available Heterodera CAPS-Approved Method: latipons Morphological- Confirmation of H. latipons is by morphological (Mediterranean identification. Keys are available for identification by morphological cereal cyst characteristics of the cyst, second-stage juvenile, male, and female. nematode) Mulvey (1972) provides a key to 39 species of Heterodera, including H. latipons, based on characteristics of cysts. Handoo (2002) provides a key to the species within the H. avenae group, as well as a thorough review of morphological studies to date.

Handoo, Z. 2002. A key and compendium to species of the Heterodera avenae group (Nematoda: Heteroderidae). Journal of Nematology 34(3): 250-262.

Mulvey, R.H., and Golden, A.M. 1983. An illustrated key to the cyst forming genera and species of Heteroderidae in western hemisphere with species morphometrics and distribution. Journal of Nematology 15: 1-59.

Microscope Required?: Yes. To be certain of the presence of H. latipons using morphological features it is necessary to examine specimens under a microscope. Mistaken Identities: H. latipons may occur by itself or in mixed populations that include closely related H. avenae or H. trifolii. H. latipons has been confused with several other cyst nematode species that parasitize cereals, including (but not limited to) H. avenae, H. bifenestra, H. filipjevi, H. hordecalis, H. mani, H. pakistanensis, H. torcomanica, H. zeae, and a more taxonomically distant species, Punctodera punctata.

Morphological Guides:

Franklin, M.T. 1969. Heterodera latipons n. sp., a cereal cyst nematode from the Mediterranean region. Nematologica15:535 542.

Handoo, Z.A. 2002. A key and compendium to species of the Heterodera avenae group (Nematoda: Heteroderidae). Journal of Nematology 34: 250-262.

Diagnosis: H. latipons cysts are typically ovoid to lemon-shaped as those of H. avenae. They belong to the H. avenae group because they have short vulva slits The fenestration of H. latipons cysts shows two distinct semi-fenestrae, which are more than a semifenestral width apart. The underbridge is strong and shows a pronounced thickening in the middle from which the name of the species is derived. The extremities of the underbridge are bi-trifurcate. Bullae are few to absent.

Eggs: length 100-124 m; width 44-56 m.

Second-stage juveniles (J2s): Body length 401-478 m; body width 19- 22 m; tail length 42-54 m; length of the hyaline tail tip 20-31 m; stylet length 23-25 m; laterial field with four incisures.

Cysts: Cysts are typically ovoid to lemon-shaped as those of H. avenae

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72 Chapter 6: Detailed Diagnostic Methods Heterodera latipons

with short vulva slits (< 16 μm). Fenestral length 58-76 m; fenestral width 15-27 m; semi-fenestral length 13- 19 m; vulval slit length 6-9 m; vulval bridge length 18-39 m; underbridge length 80-125 m; underbridge width 7-14 m; sub-crystalline layer present

Females: Body length (excluding neck) 348-645 m; body width 277- 510 m; neck length 58-103 m; stylet length 21-28 m

Males: Body length 960-1406 m; body width 25-32.5 m; stylet length 22-29 m; spicule length 32-36 m; lateral field with four longitudinal incisures.

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73 Chapter 6: Detailed Diagnostic Methods

Scientific Name, Common Name Tools Diagnostic Method Available Meloidogyne CAPS-Approved Method: artiellia (British 1. Assessment of root galls will indicate a possible root knot root-knot nematode infection. nematode) 2. Morphological: The length of at least 20 second-stage juveniles, the head and stylet morphology of males, and the nature perineal patterns of females from samples.

Microscope Required?: Yes. To be certain of the presence of M. artiellia using morphological features it is necessary to examine specimens under a microscope.

Mistaken Identities: M. artiellia can be confused with other root-knot nematodes. M. artiellia can be easily distinguished morphologically from other root- knot nematodes reported in the United States as follows: M. artiellia second-stage juveniles (J2s) have tail 18-26 µm long, whereas the J2 of M. acrita, M. arenaria, M. christiei, M. cruciana, M. megatyla, M. hapla, M. incognita, M. graminis, M. javanica, M. querciana, and M. thamesi have tail length of >30 µm. Body length parameters of M. artiellia J3 range 300-370 µm and overlap with those of M. acrita (345-396 µm), M. incognita (360-393 µm), and M. javanica (340-400 µm), but they are smaller than those (>370 µm) of other root knot nematodes reported in the United States (Greco et al., 1999).. Female M. artiellia also have a cuticular perineal pattern with a very distinct inner area containing the vulva and anus. This area is marked by a few coarse striae in an eight-shaped figure with a large base and a small top.

Morphological Guides:

Franklin, M.T. 1961. A British root-knot nematode, Meloidogyne artiellia n. sp. Journal of Helminthology R.T. Leiper supplement: 85 92.

Franklin, M.T. 1978. Meloidogyne, pp. 98-124, Plate VII. In J. F. Southey [ed.], Plant Nematology. Ministry of Agriculture Fisheries and Food; Her Majesty's Stationery Office (HMSO), London.

Eggs: (n=20), length 75-111 μm; breadth 34-43 μm.

Juveniles: (n=10-20), body length 301-370 µm; body breadth 10-16 µm; tail length 18-26 µm; stylet length 14-16 µm. The most striking feature of the larvae is the short tail with rounded tip. It is about 24.5 μm long, and two and one half times as long as the body diameter at the anus.

Females: (n=8-10 specimens), length 650-760 µm; width 340-460 µm; stylet 12-16 µm; vulva 15-22 µm.

Body swollen, pear- or flask-shaped, tapering gradually anteriorly to a small head; smooth, rounded posteriorly, with terminal vulva. Annules visible in neck region and around tail. The broad “neck” narrows abruptly at the head which is 4-5 µm across. In face view, there appear to be six almost equal lips, and a small labial cap around the mouth aperture. The amphids open as short slits on the

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74 Chapter 6: Detailed Diagnostic Methods

inner edge of the lateral lips. Each of the four sub-lateral lips has a small papilla, but none was visible on the lateral lips. Optical sections show a delicate, six-radiate skeletal structure around the anterior end of the stylet, but it disappears below the level of the lips. Dorsal views of the head show a constriction on the lateral lips about one-third behind the anterior edge. These lips could, therefore, be described as consisting of two unequal annules. The excretory pore lies ventrally one or two stylet lengths behind the head. The cuticular (perineal) pattern around the vulva and anus is characteristic. It is formed of striae and ridges of the cuticle, the latter being more pronounced nearer the vulva an anus. In general outline, the pattern is roughly that of a figure eight, the upper, smaller area enclosing the phasmids which are usually quite distinct, the anus situated at the center and the vulva occupying the diameter of the lower, larger part of the pattern. At the top of the arch, which is morphologically the dorsal part of the tail, the pattern is usually angular. Cuticular folds curve towards the anus from each side but leave a smooth unpatterned area around the vulva. The vulva is further from the anus in relation to the tail length than in most other species of the genus. The distance from the anus to vulva is about three times that from the anus to a line joining the phasmids. The exact position of the tail tip is difficult to determine because the lateral lines are marked only by the position of the phasmids and by slight irregularities in the striae.

Males: (n=7-15), length 0.82-1.37 µm; width 23-36 µm; stylet 17-27 µm; a=31-40; *b=10-15; c=60-100, where a=length/greater diameter; b=length/distance from head end to end of oesophagus; c=length/length of tail (anus to tip)] *Measurements for b were made from the anterior end to the posterior edge of the oesophageal bulb, as the end of the glandular region overlaps the intestine and is difficult to define.

Body annulated, annules about 1.5 µm wide. Lateral fields with four incisures at the tail, but along the greater part of their length a fifth incisure is present in the center of each field. The lateral fields continue round the tail which is twisted through about 90º. Phasmids small, approximately adanal. Head with labial cap and six nearly equal lips. Face views show the slit-like amphid openings on the lateral lips; papillae not seen, nor was the stellate skeletal structure, such as that in the female. In dorso-ventral view a constriction is seen on the lateral lips about one-third from the front. A tubular guide surrounds the anterior end of the stylet which has well- developed, rounded, basal knobs. Pro-corpus narrow, two to three body-widths long, followed by a spindle-shaped muscular corpus about twice as long as wide. The oesophageal glands stretch for about three body-widths ventro-laterally along the intestine. Nerve ring one bulb-length behind muscular bulb. Two body-widths behind the oesophageal bulb is a conspicuous hemizonid and immediately behind it is the excretory pore with its duct running back for a short distance. Spicules typical for the genus, curved with anterior thicker part and tapering posteriorly to a point. A small gubernaculum, about one-third the length of the spicules, lies dorsally in the cloaca wall. Tail very slightly longer than the anal body diameter.

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75 Chapter 6: Detailed Diagnostic Methods

Scientific Name, Common Name Tools Diagnostic Method Available Peronosclerospora CAPS-Approved Method: philippinensis Morphological-Condiophore structure and dimension and spore (Philippine downy (conidia) shape and size (Smith and Renfro, 1999). mildew) Isozymes- Comparisons have been used to identify Peronosclerospora spp., including P. philippinensis (Bonde et al., 1984; Micales et al., 1988).

Bonde M.R., Peterson, G.L., Dowler, W.M., and May, B. 1984. Isozyme analysis to differentiate species of Peronosclerospora causing downy mildews of maize. Phytopathology 74(11): 1278-1283.

Micales, J.A., Bonde, M.R., and Peterson, G.L. 1988. Isozyme analysis and aminopeptidase activities within the genus Peronosclerospora. Phytopathology 78:1396-1402.

Smith, D.R. and Renfro, B.L. 1999. Pg. 26, 28. In: D. G. White (ed.) Compendium of Corn Diseases, 3rd ed. APS Press, St. Paul, MN. 78 pp.

Microscope Required?: Yes. To make a species level identification it is necessary to examine morphological features under a microscope.

Mistaken Identities: Peronosclerospora spp. and other downy mildew genera (including Sclerospora and Scleropthora).

Morphological Guides:

Smith, D.R. and Renfro, B.L. 1999. Pg. 26, 28. In: D. G. White (ed.) rd Compendium of Corn Diseases, 3 ed. APS Press, St. Paul, MN. 78 pp.

Weston, W.H. 1920. Philippine downy mildew of maize. J. Agric. Res., 19: 97-122.

Peronosclerospora philippinensis is an obligate parasite that will not grow on artificial media.

Hyphae/Mycelium: The mycelia are branched, slender (8 µm in diameter), irregularly constricted, and inflated. The small haustoria (2 x 8 µm) are simple and vesiculiform to subdigitate.

Conidia/conidiophores: Erect conidiophores (15-26 x 150-400 µm) grow out of stomata and are dichotomously branched two to four times. Branches are robust. Sterigmata are ovoid to subulate, slightly curved, and 10 µm long. The conidia (17-21 x 27-39 µm) are elongate ovoid to round cylindrical, hyaline, and slightly rounded at the apex.

Oospores: Oospores are rarely produced and are not produced in corn tissue. When produced, oospores are spherical, smooth- walled, approximately 22 µm in diameter; they germinate by a side

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76 Chapter 6: Detailed Diagnostic Methods

germ tube.

Additional Resources: Recovery Plan

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Appendix A

Appendix A– Protocol for Plastic Bucket Traps

Appendix A: Plastic Bucket Trap Protocol

Appendix B

Appendix B– Example of Visual Sampling Plan Output Sampling to Compute a Nonparametric (Distribution-Free) One-Sided Upper Tolerance Limit to Test that a Large Portion of Room Surfaces Does Not Contain Contamination

Summary This report summarizes the sampling design developed by VSP based on inputs provided by the VSP user. The following table summarizes the sampling design developed by VSP. A figure that shows the sample placement on the map is also provided below.

Summary of Sampling Design

Primary Objective of Design Use a nonparametric (distribution-

free) one-sided upper tolerance

limit (UTL) to test if the true Pth per-

centile of a population exceeds the

action level

Required fraction of the population 0.99 (P=99)

to be less than the action level

Required percent confidence on 95% the decision made using the UTL Method used to compute the num- Hahn and Meeker (1991, page 169) ber of samples, n (See equations below) Sample placement method Simple random sampling Calculated total number of sam- 299 ples Number of samples on map a 299

Number of selected sample areas 35 that are not rooms Total sampling area b 126458008079.67 ft2 Total cost of sampling c $46,000.00

a This number may differ from the calculated number because of 1) grid edge effects, 2) adding judgment samples, or 3) selecting or unselecting sample areas (rooms). b This is the total surface area of all selected rooms and other selected sample areas on the map of the site. c Including measurement analyses and fixed overhead costs. See the Cost of Sampling section for an expla- nation of the costs presented here.

Floor Plan Map

Appendix B– Sample Output from Visual Sampling Plan Output

Primary Sampling Objective The primary objective of this sampling effort is to make a decision whether an unacceptably large portion (fraction) of a specified surface area (target population) is contaminated above a specified action level (AL) or is otherwise defective. It is presumed that suitable actions have been identified to be implemented for either way the decision may go.

Population Parameter of Interest The population parameter of interest is the true Pth percentile of the population of contaminant concentra- tions, where 0 < P < 100, in this case, the 99th percentile (P = 99). The true Pth percentile is the value above which (100 - P)% of the population lies and below which P% of the population lies. The objective is to reject the null hypothesis if the true Pth percentile exceeds the specified action level (AL). But, the true Pth percentile will never be known with 100% confidence because all possible measurements from the population can- not be obtained. Hence the decision whether to reject the null hypothesis is made using the computed upper tolerance limit (UTL) for the Pth percentile, that is, by computing the upper 100(1-a)% confidence limit on the Pth percentile (see Decision Rule below). For the current design a is 0.05, which means that the decision will be made using the computed UTL for the 95% confidence limit on the 99th percentile.

Hypothesis Being Tested The null hypothesis (baseline assumption) is as follows:

Ho: The true Pth percentile £ AL or equivalently, Ho: Less than P% of the population < AL

The Ho is rejected if UTL < AL, in which case the alternative hypothesis (Ha) is accepted as being true, where: Ha: More than P% of the population < AL

Sampling Design Options VSP requires that the VSP user select either • simple random sampling (SRS), or • systematic grid sampling with a random start location

to determine the room surface locations at which measurements are made or samples are collected and subsequently measured. For this design, simple random sampling was used.

Decision Rule and Number of Samples, n The null hypothesis is rejected and the alternative hypothesis is accepted if the nonparametric (distribution- free) UTL for the Pth percentile is less than the specified action level (AL). The nonparametric UTL is simply the maximum of the n measurements obtained from the population of interest, where n is computed using the following equation

n = ln (α) ln (P/100)

(from Hahn and Meeker 1991, page 169). These authors discuss the statistical meaning, use, and computa- tion of nonparametric tolerance limits and the number of samples required (pages 91, 92,169, and 326).

Appendix B– Sample Output from Visual Sampling Plan Output

The following table displays the values of the input parameters used for this design:

Parameter Value

Input

P 99

a 0.05

(5%)

Confidence (1- 95%

Output n 299

Statistical Assumptions 1. Representative measurements have been obtained from a defined target population using simple random sampling or a systematic grid pattern that has a randomly selected starting location. 2. The n measurements are statistically independent, i.e., there is no spatial correlation (no spatial patterns) of contaminant levels throughout the target population. 3. The maximum of the n measurements is not an invalid value, i.e., it is not a mistake or an unacceptably certain value due to faulty sample handling, transport, treatment, storage, or measurement.

Sensitivity Analysis The sensitivity of the calculation of number of samples was explored by varying P and CL and examining the resulting changes in the number of samples. The following table shows the results of this analysis.

Number of Samples CL=99 CL=97 CL=95 CL=93 CL=91

P=91 49 38 32 29 26 P=95 90 69 59 53 47

P=99 459 349 299 265 240

P = Required Percent of the Population to be Less Than the Action Level. CL = Confidence Level (1-a) (%)

Cost of Sampling The total cost of the completed sampling program depends on several cost inputs, some of which are fixed, and others that are based on the number of samples collected and measured. Based on the numbers of samples determined above, the estimated total cost of sampling and analysis at this site is $150500.00, which averages out to a per sample cost of $503.34. The following table summarizes the inputs and resulting cost estimates. COST INFORMATION Cost Details Per Analysis Per Sample 299 Samples Field collection costs $100.00 $29900.00 Analytical costs $400.00 $400.00 $119600.00 Sum of Field & Analytical costs $500.00 $149500.00 Fixed planning and validation costs $1000.00 Total cost $150500.00

Appendix B– Sample Output from Visual Sampling Plan Output Recommended Data Analysis Activities Post data collection activities generally follow those outlined in EPA's Guidance for Data Quality Assessment (EPA, 2000). The data analysts should become familiar with the context of the problem and goals for data collection and assessment. The n data should be verified and validated before being used to test the null hypothesis. The VSP user should enter the validated and verified n data values into the VSP dialog box and click on appropriate tabs to obtain the following statistical summaries of the data. If there is strong evidence that the n data are normally distributed, the VSP user may want to use VSP to determine the number of samples, n, required to compute the normal distribution UTL and then use that UTL (rather than the nonparametric UTL) to test the null hypothesis.

Summary statistics: n, minimum and maximum of the n measurements, range of the n data, mean, median, standard deviation, variance, skewness, percentiles, and the interquartile range

Statistical Tests of Normality Assumption: Shapiro-Wilk test (if n £ 50) (Gilbert 1987), Lilliefors test (if n > 50) (EPA 2000).

Graphical Displays of the Data: Histogram, box-and-whisker plots and quantile-quantile (probability) plots (EPA 2000).

References

EPA. 2000. Guidance for Data Quality Assessment, Practical Methods for Data Analysis, EPA QA/G-9, EPA/600/R-96/084, July 2000, Office of Environmental Information, U.S. Environmental Protection Agency.

Gilbert, R.O. 1987. Statistical Methods for Environmental Pollution Monitoring, Wiley & Sons, New York, NY.

Hahn, G.J. and W.Q. Meeker. 1991. Statistical Intervals. Wiley & Sons, Inc, New York, NY.

This report was automatically produced* by Visual Sample Plan (VSP) software version 4.6d. Software and documentation available at http://dqo.pnl.gov/vsp Software copyright (c) 2007 Battelle Memorial Institute. All rights reserved. The report contents may have been modified or reformatted by end-user of software.

The Coordinates of the samples locations are also provided in VSP. An example follows:

Area: Area 50 X Coord Y Coord Label Value Type Historical 631055.6529 -64807.1884 Random 584983.0099 -36313.6935 Random 599159.2077 -91893.5971 Random 627511.6034 -63400.1022 Random 592071.1088 -34906.6073 Random 620423.5045 -82395.7655 Random 606247.3066 -53902.2706 Random 583210.9852 -72897.9339 Random 611563.3808 -44404.4390 Random

Area: Area 45 X Coord Y Coord Label Value Type Historical 535577.1217 100631.1291 Random 586546.8165 40721.0918 Random 522834.6980 64164.1499 Random 548319.5454 48535.4445 Random 516463.4861 95421.5606 Random 567433.1809 56349.7972 Random

Appendix B– Sample Output from Visual Sampling Plan Output

541948.3335 79792.8552 Random 529205.9098 43325.8761 Random 508499.4713 74583.2868 Random 533984.3187 58954.5814 Random

Area: Area 37 X Coord Y Coord Label Value Type Historical 606396.3807 104494.0744 Random 595959.9799 80333.4572 Random 575087.1785 93380.1905 Random 616832.7814 106426.9237 Random 548996.1767 84682.3683 Random 590741.7796 97729.1015 Random 569868.9782 110775.8348 Random

Area: Area 25 X Coord Y Coord Label Value Type Historical 588507.0856 9206.5621 Random 632300.0599 35792.7963 Random 574821.7811 21022.6662 Random 596718.2683 3298.5100 Random 629562.9990 12160.5881 Random 651459.4862 -29195.7763 Random 580295.9029 -2609.5420 Random 624088.8772 23976.6922 Random 645985.3644 6252.5361 Random 591244.1465 32838.7703 Random 635037.1208 -11471.6201 Random

Appendix C

Appendix C– NASS County Estimates Example NASS County Estimates KS Wheat (2006)

Cum. County District Planted Acres Cumulative Cum. Fraction Sample County Sample Sumner 60 381,200 381,200 11.66867335 12 12 Harper 60 256,200 637,400 19.51105034 20 8 Reno 60 253,900 891,300 27.28302349 27 7 McPherson 50 223,800 1,115,100 34.13362447 34 7 Kingman 60 210,500 1,325,600 40.57710752 41 7 Sedgwick 60 198,300 1,523,900 46.64714405 47 6 Sherman 10 193,500 1,717,400 52.5702508 53 6 Mitchell 40 190,900 1,908,300 58.41377059 58 5 Thomas 10 187,200 2,095,500 64.144032 64 6 Ford 30 184,500 2,280,000 69.79164541 70 6 Greeley 20 175,200 2,455,200 75.15458237 75 5 Barton 50 172,700 2,627,900 80.44099341 80 5 Finney 30 170,700 2,798,600 85.6661837 86 6 Pratt 60 169,000 2,967,600 90.83933637 91 5 Rice 50 163,200 3,130,800 95.83494888 96 5 Rawlins 10 161,400 3,292,200 100.7754627 101 5 Smith 40 151,600 3,443,800 105.4159949 105 4 Dickinson 50 151,000 3,594,800 110.0381609 110 5 Scott 20 149,500 3,744,300 114.6144114 115 5 Sallie 50 147,300 3,891,600 119.123319 119 4 Pawnee 60 146,100 4,037,700 123.5954942 124 5 Stafford 60 144,600 4,182,300 128.0217538 128 4 Ness 20 136,900 4,319,200 132.2123135 132 4 Cheyenne 10 135,900 4,455,100 136.3722629 137 5 Jewell 40 135,900 4,591,000 140.5322123 141 4 Wichita 20 134,400 4,725,400 144.6462461 145 4 Marion 50 133,200 4,858,600 148.7235475 149 4 Gray 30 132,900 4,991,500 152.7916658 153 4 Hamilton 30 132,600 5,124,100 156.850601 157 4 Osborne 40 129,900 5,254,000 160.8268881 161 4 Barber 60 129,500 5,383,500 164.7909312 165 4 Logan 20 126,500 5,510,000 168.6631431 169 4

Appendix C: NASS County Estimate Example

Cum. County District Planted Acres Cumulative Cum. Fraction Sample County Sample Rush 50 125,400 5,635,400 172.5016836 173 4 Harvey 60 125,300 5,760,700 176.337163 176 3

Ottawa 40 121,500 5,882,200 180.0563231 180 4 Rooks 40 120,900 6,003,100 183.7571169 184 4 Cloud 40 116,500 6,119,600 187.3232251 187 3

Decatur 10 115,700 6,235,300 190.864845 191 4 Ellis 50 115,200 6,350,500 194.3911597 194 3 Hodgeman 30 113,900 6,464,400 197.877681 198 4 Edwards 60 113,800 6,578,200 201.3611412 201 3 Norton 10 112,700 6,690,900 204.8109299 205 4 Phillips 40 110,500 6,801,400 208.1933759 208 3 Gove 20 109,000 6,910,400 211.5299063 212 4 Lincoln 50 107,300 7,017,700 214.8143991 215 3 Ellsworth 50 105,300 7,123,000 218.0376712 218 3 Lane 20 104,000 7,227,000 221.2211497 221 3 Stanton 30 103,400 7,330,400 224.3862621 224 3 Kearny 30 102,500 7,432,900 227.5238251 228 4 Sheridan 10 101,500 7,534,400 230.6307777 231 3 Russell 50 100,600 7,635,000 233.710181 234 3 Wallace 20 100,200 7,735,200 236.7773402 237 3 Republic 40 98,500 7,833,700 239.7924617 240 3 Haskell 30 96,900 7,930,600 242.7586066 243 3 Trego 20 94,300 8,024,900 245.6451646 246 3 Graham 10 92,100 8,117,000 248.4643797 248 2 Cowley 90 89,900 8,206,900 251.2162521 251 3 Meade 30 89,000 8,295,900 253.9405751 254 3 Washington 40 87,900 8,383,800 256.6312267 257 3 Stevens 30 86,100 8,469,900 259.2667796 259 2 Clay 40 85,900 8,555,800 261.8962104 262 3 Grant 30 81,900 8,637,700 264.4031998 264 2 Marshall 70 79,800 8,717,500 266.8459074 267 3 Kiowa 60 75,500 8,793,000 269.1569904 269 2 Clark 30 75,300 8,868,300 271.4619513 271 2 Cherokee 90 75,400 8,943,700 273.7699733 274 3 Morton 30 72,700 9,016,400 275.9953472 276 2 Comanche 60 71,700 9,088,100 278.1901108 278 2 Seward 30 62,600 9,150,700 280.10632 280 2 Butler 90 56,800 9,207,500 281.8449891 281 1 Labette 90 56,100 9,263,600 283.5622309 284 3 Crawford 90 42,100 9,305,700 284.8509275 285 1

Appendix C: NASS County Estimate Example

Planted Cum. County District Acres Cumulative Cum. Fraction Sample County Sample Wilson 90 41,600 9,347,300 286.1243189 286 1 Montgomery 90 39,000 9,386,300 287.3181234 287 1 Neosho 90 38,900 9,425,200 288.5088668 289 2 Morris 80 32,300 9,457,500 289.4975818 289 0 Allen 80 30,200 9,487,700 290.422015 291 2 Nemaha 70 29,500 9,517,200 291.3250209 291 0 Anderson 80 27,900 9,545,100 292.1790503 292 1 Coffey 80 25,600 9,570,700 292.9626758 293 1 Riley 70 25,000 9,595,700 293.727935 294 1 Lyon 80 20,400 9,616,100 294.3523866 294 0 Woodson 90 17,800 9,633,900 294.8972512 295 1 Franklin 80 16,100 9,650,000 295.3900782 295 0 Linn 80 14,500 9,664,500 295.8339285 296 1 Geary 80 13,900 9,678,400 296.2594127 296 0 Osage 80 12,000 9,690,400 296.6267371 297 1 Chase 80 11,700 9,702,100 296.9848785 297 0 Bourbon 90 10,400 9,712,500 297.3032263 297 0 Jackson 70 9,000 9,721,500 297.5787197 298 1 Brown 70 8,900 9,730,400 297.851152 298 0 Miami 80 8,500 9,738,900 298.1113401 298 0 Atchinson 70 8,300 9,747,200 298.3654062 298 0 Pottawatomie 70 8,300 9,755,500 298.6194723 299 1 Wabaunsee 80 7,400 9,762,900 298.845989 299 0 Greenwood 90 5,800 9,768,700 299.0235292 299 0 Douglas 80 5,300 9,774,000 299.1857641 299 0 Jefferson 70 5,200 9,779,200 299.3449381 299 0 Shawnee 80 5,200 9,784,400 299.504112 300 1 Elk 90 4,500 9,788,900 299.6418587 300 0 Johnson 70 4,200 9,793,100 299.7704222 300 0 Leavenworth 70 3,900 9,797,000 299.8898027 300 0 Doniphan 70 1,700 9,798,700 299.9418403 300 0 Chataquua 90 1,500 9,800,200 299.9877559 300 0 Wyandotte 70 400 9,800,600 300 300 0

Kansas Total 9,800,600 300 Total samples Divide by 300 samples

32,668.6667 acres/sample or 32,669 acres/sample