INFLUENCE OF PLANTING DATE AND COTTON CULTIVAR
ON LYGUS AND FLEAHOPPER ABUNDANCE IN THE
TEXAS HIGH PLAINS AND THE RELATIONSHIP
BETWEEN BOLL AGE AND LYGUS
HESPERUS DAMAGE
by
ANDY MARSHAL CRANMER, B.S.
A THESIS
IN
ENTOMOLOGY
Submitted to the Graduate Faculty of Texas Tech University in Partial Fulfillment of the Requirements for the Degree of
MASTER OF SCIENCE
Approved
Chairperson of the Committee
Accepted
Dean of the Graduate School August, 2004 ACKNOWLEDGMENTS
1 would like to express my deepest thanks to Dr. Megha N. Parajulee, chairman of my advisory committee. Dr. Parajulee is more than the Cotton Entomologist at the Texas Agricultural Experiment Station (TAES), Lubbock, Texas; he is a great leader, mentor and a friend. This project would have not have been possible if not for his guidance, his interest, and his unwavering support. I have leamed many important skills (personal and professional) from Dr. Parajulee over the past two years that I will carry with me into the fiiture, and for that I am very grateful. It was a wonderful privilege to work for a man of Dr. Parajulee's character, and I will never forget the opportunity he provided. 1 would also like to thank those members who served on my thesis committee. Dr. James F. Leser, District Entomologist, Texas Cooperative Extension, and Dr. Chad S. Davis, Department of Agricultural Education and Communications, Texas Tech University. Dr. Leser contributed to every aspect of this project, and 1 would like to thank him for sharing his expertise, understanding, and for all the encouragement. 1 want to express my gratitude for the knowledge that Dr. Davis supplied. With his suggestions and help, I was able to conclude the task of presenting my findings. It was only with their help that I was able to complete my study, and for that I am greatly appreciative. I would like to thank Stan C. Carroll and Mjirk D. Amold for all their help, time, and wisdom. 1 will always be thankful for the opportunity to work alongside both and for the fiiendship they provided. I also want to extend thanks to my colleagues Latha Bommireddy, R. B. Shrestha, Anand Sapkota, and Lanthia Jones for their assistance and hard work throughout the past two years. 1 am grateful to Brant Baugh and Tommy Doederlein for sparking my interest to pursue this project and for their guidance. This would not have been a possibility without the love and support fi-om my family. I want to thank my parents, Lee and Linda Craimier, my brother, Kyle Cranmer, my sister, Emily Cramner, and my wife, Leigh Cranmer, for all their support, kindness, trust, and faith. I would also like to thank my wife for her encouragement and dedication and for being by my side through all of it.
11 TABLE OF CONTENTS
ACKNOWLEDGMENTS ii LIST OF TABLES iv LIST OF FIGURES v CHAPTER L INTRODUCTION AND LITERATURE REVIEW 1 II. LYGUS AND FLEAHOPPER POPULATIONS AS AFFECTED BY PLANTING DATE AND COTTON CULTIVAR 4 Introduction 4 Materials and Methods 7 Results and Discussion 9 III. COMPARISON OF SAMPLING METHODS FOR ESTIMATING LYGUS AND FLEAHOPPER ABUNDANCE IN COTTON 28 Introduction 28 Materials and Methods 32 Results and Discussion 33 IV. EFFECT OF LYGUS HESPERUS FEEDING ON DEVELOPING COTTON BOLLS 46 Introduction 46 Materials and Methods 48 Results and Discussion 51 VITA 63
REFERENCES ....64
in LIST OF TABLES
2.1 Analysis of variance statistics to compare the effects of cotton planting date and cotton cultivar on fleahopper abundance, Halfway, TX, 2002-03 13
2.2 Average number of cotton fleahoppers and Lygus per acre estimated using a vacuum sampler in cotton plots grown in 2002 and 2003, Halfway, TX 14
2.3 Two-way interaction analysis comparing the effect of planting date and cultivar on the number of fleahoppers per acre. Halfway, TX, 2002-03 15
2.4 Three-way interaction analysis comparing the effect of year, planting date, and cultivar on the nvimber of fleahoppers per acre. Halfway, TX, 2002-03... 16
2.5 Analysis of variance statistics to compare the effects of cotton planting date and cotton cultivar on Lygus abundance. Halfway, TX, 2002-03 17
3.1 Analysis of variance statistics to examine the effect of sampling methods on fleahopper abundance. Halfway, TX, 2002-03 36
3.2 Average abundance ofcotton fleahoppers and Lygus estimated using five sampling methods in cotton plots grown in 2002 and 2003, Halfway, TX ....37
3.3 Two-way interaction analysis comparing the effect of year and sampling method on the number of fleahoppers per acre. Halfway, TX, 2002-03 38
3.4 Analysis of variance statistics to examine the effectivness of sampling methods in detecting Lygus abundance, Halfway, TX, 2002-03 39
4.1 Number of outer injury and iimer damage spots in cotton bolls by
L. hesperus in relation to boll age 56
4.2 Relationship between boll size and boll age 57
4.3 Effect of Lygus feeding on seed production in relation to boll age 57
4.4 Effect of Lygus feeding on average seed weight in relation to boll age 57
4.5 Effect of Lygus feeding on average lint weight in relation to boll age 57
4.6 Average force required to penetrate the cotton boll in relation to boll age ....58
IV LIST OF FIGURES
2.1 Number of fleahoppers captured weekly on four cotton cultivars planted at two dates using the vacuum sampler 18
2.2 Number of fleahoppers captured weekly in early and late planted cotton using the vacuum sampler in 2002 19
2.3 Number of fleahoppers captured weekly in early and late planted cotton using the vacuum sampler in 2003 20
2.4 Number of fleahoppers captured weekly on four cotton cultivars using the vacuum sampler in 2002 21
2.5 Number of fleahoppers captured weekly on four cotton cultivars using the vacuum sampler in 2003 22
2.6 Number of Lygus bugs captured weekly on four cotton cultivars planted at two dates using the vacuum sampler 23
2.7 Number of Lygus bugs captured weekly in early and late planted cotton using the vacuum sampler in 2002 24
2.8 Number of Lygus bugs captured weekly in early and late planted cotton using the vacuum sampler in 2003 25
2.9 Number of Lygus bugs captured weekly on four cotton cultivars using the vacuum sampler in 2002 26
2.10 Number of Lygus bugs captured weekly on four cotton cultivars using the vacuum sampler in 2003 27
3.1 Number of cotton fleahoppers captured weekly on cotton using a combination of sampling methods (sweepnet, vacuum sampler, beat bucket, drop cloth and on-plant visual sampling). Halfway, TX 40
3.2 Number of fleahoppers captured weekly using five sampling methods (sweepnet, vacuum sampler, beat bucket, drop cloth and on-plant visual sampling). Halfway, TX, 2002 41 3.3 Number of fleahoppers captured weekly using five sampling methods (sweepnet, vacuum sampler, beat bucket, drop cloth and on-plant visual sampling), Hal^ay, TX, 2003 42
3.4 Number of Lygus bugs captured weekly on cotton using a combination of five different sampling methods (sweepnet, vacuum sampler, beat bucket, drop cloth and on-plant visual sampling), Halfway, TX 43
3.5 Number of Lygus bugs captured weekly using five sampling methods (sweepnet, vacuimi sampler, beat bucket, drop cloth and on-plant visual sampling), HalRvay, TX, 2002 44
3.6 Number of Lygus bugs captured weekly using five sampling methods (sweepnet, vacuum sampler, beat bucket, drop cloth and on-plant visual sampling), Halfivay, TX, 2003 45
4.1 Percentage of boll injury and damage by Lygus hesperus at different heat unit accumulations 59
4.2 Pressure required to penetrate the boll side or lock on cotton bolls of different ages 60
4.3 The difference in pressure required to penetrate the boll side or lock of a cotton boll after the gain of 100 heat units 61
4.4 Linear regression analysis, predicting when a cotton boll is relatively safe from Lygus hesperus injury and damage 62
VI CHAPTER I
INTRODUCTION AND LITERATURE REVIEW
Texas produces more cotton than any other state in the United States. A 17-year average (1984-2000) cotton production statistic indicates that approximately 27% of United States cotton is produced in Texas, while 59% of Texas cotton is produced in the High Plains region (Plains Cotton Growers, Inc. personal communication, 2001). The Texas High Plains constitutes the most concentrated area of cotton production in the world (Leser 1999) with acreage comprising 3 million (on average) of more than the 5 million acres of cotton planted in Texas each year. In 2000, 2001, and 2002 there were 6.4, 6.2, and 5.8 million acres planted in Texas, respectively, and 4.8, 4.3, and 4.6 million acres harvested, also respectively (Williams 2003).
In 2002, insect pests infested a total of 5.2 million acres and caused the loss of over 184,000 bales in Texas (Williams 2003). During the last 5 years, cotton yield loss in the United States due to arthropod pests ranged from 7 to 9%. Yield loss in Texas ranged from 8 to 16%, and yield loss in the Texas High Plains ranged from 6-19%. These losses due to arthropod pests cause the loss of millions of dollars to the economy. In 2002, Texas producers lost over 53 million dollars due to arthropod pests: over 21 million of that 53 million was lost in the Texas High Plains region. Arthropod pests reduce cotton lint yield by about 10% across the United States annually (Williams 1996-2001).
The initiation of boll weevil eradication in Texas has caused secondary pests to become primary pests in some instances. With the successful completion of boll weevil eradication, the damage inflicted by historically minor or occasional insect pests may become more pronounced (Ruberson et al. 1994), and other insect pests may arise. Information on biology and ecology of these other cotton insect pests, including both fleahoppers and plant bugs, is generally lacking for the Texas High Plains. In 2002, 2,797,202 acres in Texas were reported to be infested with the cotton fleahopper, Pseudatomoscelis seriatus (Renter) causing the loss of 16,817 bales. In 1999, the cotton fleahopper was the most economically damaging insect pest ofcotton causing over 196 million dollars in control costs and losses to US producers (Williams 2002). In 2000, it was the ninth most damaging pest of cotton in the US, infesting 42% of the crop (Williams 2001). The cotton fleahopper prefers wild weed hosts (Reinhard 1926, Holtzer and Sterling 1980), but moves to cotton as the weed hosts begin to mature (Almand et al. 1976).
Plant bugs, Lygus spp., are also pests of rising status. Little research has been done regarding this pest in the Texas High Plains region, but losses can be serious. Lygus spp. infested and estimated 960,654 acres in Texas in 2002 and caused the loss of 1,501 bales (Williams 2003). There is concem that the reduction in insecticide usage for boll weevil control after completion of the various eradication programs vsall allow the development of higher Lygus populations and continue to boost Lygus spp. pest status. The adoption of transgenic cotton cultivars that express resistance to lepidopterous pests is on the increase and will further reduce the amount of insecticides being used. This could also result in higher Lygus spp. populations and increased pest status. Lygus bugs are polyphagous and their success as pests can be attributed to their ability to utilize a wide range of host plants (Hedlimg and Graham 1987). There are nine species of the genus Lygus that are important to North American agriculture. Three species are recognized pests of cotton in Texas. Lygus hesperus (Knight), the westem tamished plant bug, and Lygus lineolaris (Palisot de Beauvois), the tamished plant bug, are important pests of cotton and other crops in the westem and southem/eastem United States, respectively (Godfrey 2002). Lygus elisus (Van Duzee), a third species has been identified as an equally prevalent species in some areas of the Texas High Plains (Parajulee et al. 2003). Diehl et al. (1998) suggested that Lygus bugs infesting cotton in Arizona were a complex of Z. lineolaris, L. elisus, and L. hesperus, and that management decisions would not require identification to species. If this is tme, control should be simplified because the larger volume of research performed on L. lineolaris (which is not common to the Texas High Plains) can be applied to developing confrol strategies for L. hesperus and L. elisus. Due to the decrease in insecticide usage resulting from boll weevil eradication and the adoption of Bt cotton, behavior and ecology of potentially important pest species such as cotton fleahopper and Lygus spp. need to be studied.
This study was designed to generate biological and ecological parameters of Lygus and fleahoppers and to help design integrated approaches to manage the pests. Specific objectives of this study were: 1) to evaluate Lygus spp. and cotton fleahopper populations as affected by planting date and cotton cultivar, 2) to evaluate the efficiency of five different sampling methods on Lygus spp. and cotton fleahopper, and 3) to determine the effect of Lygus hesperus feeding on developing cotton bolls. CHAPTER 11
LYGUS AND FLEAHOPPER POPULATIONS AS AFFECTED BY PLANTING DATE AND COTTON CULTIVAR
Introduction
Field infestations and yield loss due to cotton fleahoppers, Pseudatomoscelis seriates (Renter), and Lygus spp. have become more of a concem for Texas High Plains cotton producers over the past few years. The Lygus spp. complex in the Texas High Plains includes L. hesperus (Knight) and L. elisus (van Duzee). Damage to cotton by these two pests can be observed throughout the entire growing season, but the plant can be more vulnerable to a specific species at different stages of its life.
Muegge et al. 2001 observed that the cotton plant is most susceptible to yield damage and square loss during the first three weeks of fruiting and that squares up to pinhead size may be damaged by fleahoppers. During the last five years, an average of two million acres of Texas High Plains cotton was infested by the cotton fleahopper (Anonymous 2002). In 2002, an estimated 2,797,202 acres of Texas cotton were infested by the cotton fleahopper, causing the loss of 16,817 bales. In 1999, the fleahopper was the most economically damaging insect pest of cotton nationwide causing over $196 million m costs and losses to U.S. producers (Williams 2000). In 2000, the fleahopper was the 9**^ most damaging cotton pest in the U.S. infesting 42% of the crop (Williams 2001). A reason that this pest is so common and such a major problem year after year is that the cotton fleahopper prefers wild weed hosts (Reinhard 1926, Holtzer and Sterling 1980), and builds large populations in these hosts before moving into cotton as the weed hosts begin to mature (Almand et al. 1976). The fact that the fleahopper is polyphagous and can survive by moving from one host to another is the reason it is so successful as a pest. One question we wanted to answer was whether the fleahopper will exhibit a preference for different cotton cultivars of Gossipium hirsutum L. (American upland cotton). The genetic variability among cultivars can manifest phenotypic fraits that are atfractive to some insects and repellent to others. One study found that the glabrous characteristics of one strain of cotton suppressed populations of the cotton fleahopper as effectively as some insecticides (Lukefahr et al. 1968). More of Lukefahr's research showed that the resistance of some cotton plants to the cotton fleahopper is related to the density of trichomes on the foliage, though with different results. Lukefahr et al. (1970) found that plants with hairier leaves were less appealing to the fleahopper, which results in less damage. Field tests conducted in Texas (Lukefahr et al. 1966) indicated that a glabrous-nectariless cotton cultivar exhibited resistance to cotton fleahoppers. It has been proven that characteristics expressed by different cotton cultivars may influence the preference of the cotton fleahopper for that cultivar. Identification and usage of cotton characteristics that repel the cotton fleahopper could save millions of dollars in confrol costs and losses.
Lygus bugs are becoming a noticeable concem for cotton producers in the Texas High Plains. Lygus may feed on small squares and damage developing anthers, cause squares to abort, or cause feeding injury to developing small bolls (Leigh et al. 1988). In the past five years, Lygus has infested an average of 600,000 acres and caused the loss of an average of 27,000 bales of cotton annually in Texas. Tamished plant bug (TPB) feeding causes swollen nodes, shortened intemodes, deformed leaves, non-fertile squares, terminal abortion, and may induce vegetative growth in cotton plants (Scales and Furr 1968, Wene and Sheets 1964, Tugwell et al. 1976, Hanney et al. 1977). This eventtially results in yield loss and lower profits. The amoimt of damage induced by Lygus has been directly correlated with plant characteristics by many researchers over many years.
The amount of damage Lygus bugs will cause to cotton bolls is likely to depend on the relative phenology ofthe crop and the species of Lygus (Wilson et al. 1984). Early season populations cause damage to squares while populations occurring later in the season cause damage to developing bolls. Since the bolls are located farther from the plant terminal than the squares, Lygus distribution on the plant may affect the relative availability of squares and bolls as feeding sites (Wilson et al. 1984). Lygus distribution within the plant canopy could also be influenced by cotton cultivar. Laster and Meredith (1974) and Burris et al. (1997) found that smooth leaf and frego-bract cotton cultivars were significantly more sensitive to TPB. The effect of ttichome densities on pest insects have been studied, and several of these studies have indicated that the trichome density can greatly affect Lygus and fleahopper abundance and development. Tingey and Pillemer (1977) showed a significant effect of frichomes on the activities of cotton fleahoppers and Lygus spp. and suggested a potential role in plant resistance to Lygus spp. Benedict et al. (1983) used three genotypes to study growth and behavior of L. hesperus. Phenotypes used were designated smooth leaf (glabrous, no hairs), hirsute (medium length, normal hair density), and pilose (short, dense hairs). In a no-choice cage study, they observed that more eggs were laid on the pilose phenotype followed by the hirsute and smooth leaf, in that order. This would indicate that female bugs could be expected to move from glabrous cotton to more preferable hosts before oviposition. Although the pilose was preferred for oviposition, it was not as suitable as the other phenotypes for grovv1;h (Benedict et al. 1983). Tingey et al. (1975) showed that nymphs reared on a pilose line had a significantly lower growth rate than those reared on a normal hirsute line. Tingey et al. (1973, 1975) also indicated that L. hesperus may show reduced oviposition in response to glabrous phenotypes resulting in lower populations.
Field studies have also shown that plants with the glabrous characteristic have hypersensitivity to plant bug feeding, resulting in increased feeding damage (Jones et al. 1976, Schuster and Frazier 1976, Meredith and Schuster 1979). There is research being conducted at this time on the effect of nectariless cotton on TPB infestations, but few varieties of this type are available to producers. Field research on plant bugs and cotton fleahoppers is difficult because of the unpredictability of population occurrence in a specific location. The objectives of this study were to quantify the influence of planting date and cotton cultivar on seasonal abundance pattems of cotton fleahoppers and Lygus bugs in the Texas High Plains. Materials and Methods
Field experiments were conducted in 2002 and 2003 in Hale County at the Helms Research Farm located near the Texas Agricultural Experiment Station at Halfway, TX. In both years, a randomized complete block design in a 4x2 factorial arrangement was used to assign treatments to plots. The two experimental factors were cultivar and planting date. The cultivar freatment included four commercial varieties. Cultivar selection was based on plant architecture, leaf pubescence, and adaptability ofthe cultivar to the region. All cultivars chosen for the study were roimdup ready stripper varieties with the early maturity characteristic. Stoneville (ST) 2454R is a smooth leaf variety. Paymaster (PM) 2326RR and PM 2167 exhibit the semi-smooth leaf characteristic, and PM 2145RR was chosen for its hairy leaf characteristic. Planting date freatments included timely (early May) and late (early June). The timely planting was scheduled to occur within the optimum planting date window (late April-mid May) recommended for the southern High Plains and the late planting date coincided with the insurance replanting cut-off date for the region (June 12). Treatments were replicated four times. Plots were 105 ft X 24 rows of 30-inch width. Irrigations were applied through a center pivot system using the LEPA (Low Energy Precision Application) irrigation management system. In 2002, timely or optimum planting plots were planted on May 7, and late planted plots were planted on June 7. In 2003, plots targeted for optimum planting date were planted on May 7, and late planted plots were planted on June 11. A John Deere MaxEmerge vacuum planter was used with a seeding rate of 13 pounds of seed per acre both years. A pre-emergence systemic insecticide (Temik) was applied at planting at a rate of 3.5 pounds formulation per acre in both years for thrips confrol. Harvests were conducted on December 20, 2002 and December 1, 2003 using a John Deere 7445 stripper, mechanically altered to take relatively large yield samples (4 rows by 50 feet) from each experimental unit.
Insect sampling began on June 17 during the 2002 season, and continued on a weekly basis throughout the growing season until September 26. Sampling during the 2003 season began on June 25 and continued weekly until August 28. A vacuum sampler (Model 1612, J. W. Hock Company, Gainesville, FL) was used to monitor populations of fleahoppers and Lygus bugs in all 32 plots. Sampling was conducted by walking down a designated row within a plot for 30 seconds with the vacuum cone placed directly over the cotton terminal. This was roughly equivalent to 100 row feet. The mesh bag was removed from the cone after the 30 seconds and the captured insects were transferred to a bag and placed in a cooler. Samples were then taken to the laboratory and placed in a freezer until they could be processed. Processing consisted of removing the insects from the freezer bags, separating them by species then counting them. Samples were taken in each of the 32 plots on a weekly basis. In both years, numbers of Lygus hesperus and Lygus elisus were combined imless otherwise noted. Sample units were converted to numbers per acre.
The experimental design was RCBD Split-Split plot with year as main plot, planting date and variety as sub-plot in a factorial combination, and week as sub-sub-plot (a repeated measurement). The same experiment was repeated for two years v^th re- randomization of treatments in the second year. The variable week was constmcted by pairing similar sample dates between 7/22-8/21 from the two years. Though the test was sampled from June to September, only five weeks contained all the factors necessary for a balanced model and only these five weeks were used in the analysis. The data were analyzed using PROC GLM (SAS Institute 2003). Analysis of variance was performed to test the effect of year, week, cultivars, planting date, and their interactions using weekly data as repeated measurements (Mcintosh 1983). Variation between weeks was expected, so the main effect of week and its interactions were not considered important and were excluded from the results and discussion of this study. Mean separations were performed on all main effects, and two and three-way interaction analyses were performed for planting date*variety and year*planting date*variety effects that had significant F-tests for that specific effect. All means were separated using LSD, and interaction mean separations were protected by an F-test at the simple main effect level. Results and Discussion
Cotton fleahopper. In examining effects of interest for number of fleahoppers per acre (years combined) we observed that planting date, cultivar, planting date/cultivar interaction and year/planting date/cultivar interaction all had highly significant F-tests, indicating at least one difference between means (Table 2.1). There was also a significant effect of year on fleahopper numbers. This was expected, as populations of insects may vary between years. Weekly fleahopper population trends comparing the two years ofthe study are shown in Figure 2.1. Fleahopper numbers showed similar population peaks (similar in numbers) toward the end of the season in both years followed by a sharp decline, however the population peak and decline occurred approximately two weeks earlier in 2003 than in 2002 (Figure 2.1). Seasonal mean numbers of fleahoppers (for the five week period used in the main analysis model described above) were significantly higher in 2003 than in 2002 (Table 2.2). This could be due to many factors including climate, weather, and host plant populations.
Weekly fleahopper population trends compeiring timely and late planted cottons for years 2002 and 2003 are shown in Figures 2.2 and 2.3, respectively. In 2002, timely and late planted cotton had similar fleahopper numbers imtil early-August, when the population in the late planted cotton built to a peak of over 4500 fleahoppers per acre compared to less than 1000 in the timely planted plots (Figure 2.2). This could be due to the abundance of blooms in the late planted cotton. In 2003, fleahopper numbers in timely and late planted cotton had very similar curve shapes, with an approximately one week lag between the two (Figure 2.3). Later planted cotton fruited later than the early planted; therefore, more food was available to fleahoppers later in the season. There were significant differences in fleahopper abundance when comparing cotton planted at the two different dates. Timely planted cotton harbored significantly more fleahoppers with 1995.0/A than did late planted with 1350.4/A (Table 2.2). However, sampling in 2002 was conducted into late September when high numbers of fleahoppers were detected in later planted cotton, while in 2003 sampling was terminated in early September due to tune restrictions. There could have been a different conclusion had sampling been continued further into the season in 2003.
Significant differences were also observed in fleahopper abundance when looking at the effect of cotton cultivar. PM 2145RR had significantly higher numbers than ST 2454 R and PM 2167 (Table 2.2). The ST variety used in this sttidy was a smooth leaf variety and harbored the lowest average number of fleahoppers of the varieties tested. Weekly sampling detected higher nimibers of fleahoppers in the PM 2145RR in both 2002 and 2003, with population peaks in early September and mid-August (Figures 2.4 and 2.5).
Two-way interaction analysis was performed on the planting date*cultiyar crossed effect as indicated by a significant F-test for that effect. All comparisons are of simple main effects, or one effect at a specific level of another. Analysis revealed that significantly more fleahoppers were captured on PM 2145RR than any of the other cultivars when considering cultivar at the timely planting date (Table 2.3). The other three cultivars varied in the numbers of fleahoppers that they hosted, but their mean numbers were statistically the same. There were no significant differences in numbers of fleahoppers on the different cultivars when comparing the cultivars at the late planting date (Table 2.3). Numbers of fleahoppers captured on timely and late planted cotton were not significantly different on cultivars ST 2454R and PM 2326RR. However, timely planted cotton supported significantly more fleahoppers than late planted on cultivars PM 2167RR and PM 2145RR (Table 2.3). These data suggest that the degree of variation in crop atfractiveness through the growing season varies with crop cultivar.
The three way interaction of year*planting date*cultiyar also had a significant F- test (Table 2.1) for fleahopper numbers and a three way interaction analysis for that effect is presented in Table 2.4. In 2002, there were no significant differences in fleahopper numbers when comparing cultivar or planting date. In 2003, however, there were significant differences in number of fleahoppers captured on the different cultivars that were planted in timely fashion. Significantly more fleahoppers were captured on PM 2145RR, the hairy leaf variety than on the other cultivars. Significantly more fleahoppers
10 were captured on PM 2167RR (semi-smooth) than on PM 2454RR (smooth). No significant differences were noted between the cultivars in the 2003, late-planted cotton (Table 2.4). No significant differences were found between fleahopper numbers in early or late planted plots in 2002 regardless of variety. Significant differences were observed in 2003 between planting dates on PM 2167RR and PM 2145RR. Timely planted PM 2167 had significantly more fleahoppers than did late planted PM 2167 (Table 2.4). The PM 2145RR also harbored significantly more fleahoppers on its timely planting when sampling continued until late September than it did on its later planting (Table 2.4). The year effect was significant at all planting date/cultivar combinations (Table 2.4).
The hairy leaf cotton (PM 2145RR) harbored the highest number of fleahoppers per acre while the smooth leaf cultivar (ST2454R) harbored the fewest (Table 2.2). Interaction analysis revealed that this pattem was confined to the timely planted cotton, and was consistent in both years though only significant in 2003. In the late planted cotton there were no significant differences in fleahopper abundance among cultivars in either year. Sampling during the 2003 season was terminated in early September which most likely influenced this analysis. A late season population peak would most likely have centered on the younger and so more attractive late planted cotton and altered the average for the planting date effect.
Lygus. The two species of Lygus on the Texas High Plains that were captured were Lygus hesperus and Lygus elisus. Low numbers forced us to combine species before analyzing data. An identical analysis model was used to analyze Lygus as that used for fleahoppers. Analysis revealed significant differences in the seasonal abundance of Lygus for the main effects of planting date and year. No other effects of interest showed significant differences (Table 2.5). Lygus population trends for 2002 and 2003 are presented in Figure 2.6. In 2002, Lygus numbers were generally higher than in 2003, with a large population peak occurring around the first of September. Numbers remained generally low through 2003, though a much smaller population peak occurred that coincides temporally with the peak observed in 2002. There was year effect in 2002 versus 2003 (Table 2.2) with significantly more Lygus captured in 2002. In 2002, weekly
11 Lygus numbers were higher in the late planted cotton surpassing those in the timely planted cotton and showing a large population peak in early September (Figure 2.7). The same was tme in 2003 with numbers of Lygus in the late planted cotton surpassing those in the timely planted in July, then building to a peak in late August (Figure 2.8). Unlike 2002, the Lygus population in the timely planted cotton did continue to build through August and reached a peak similar temporally though smaller than that reached in the late planted cotton (Figures 2.7 and 2.8). Planting date significantly affected the number of Lygus per acre with significantly lower numbers in late planted compared to timely planted cotton (Table 2.2). Cotton is planted at different times across the High Plains due to weather. It was of interest to see if planting date had any effect on Lygus abundance. Our results suggested that earliness may be the key to minimizing yield loss due to Lygus. There were no significant differences in the numbers of Lygus captured on any of the four cultivars tested (Table 2.2). ST2454R, a cultivar with a smoother leaf characteristic than any of the other varieties tested, supported a numerically higher number of Lygus than the other varieties (Table 2.2) and during the August and September peaks, showed highest weekly numbers in 2002 (Figure 2.9). In 2003 however, highest numbers were observed weekly on the PM 2145RR, the hairy variety followed by ST 2454R, the smooth variety (Figure 2.10).
Many cotton cultivars are available to producers in Texas, and identification of any effect of cultivars or the traits involved on Lygus population development would benefit growers. No significant difference was observed among the cultivars tested here and no numerical pattem was evident, but the potential benefits make future study of the effects of different cultivars on Lygus colonization, growth and development a must. Two and three way interactions of year, planting date and cultivar effects had non significant F-tests and summary tables were not produced (Table 2.5).
12 Table 2.1. Analysis of variance statistics to compare the effects ofcotton planting date and cotton cultivar on fleahopper abundance. Halfway, TX, 2002-2003
Source DF Type III SS Mean Square F Value Pr>F year 1 388657240.5 388657240.5 383.89 <.0001 pd 1 33249809.4 33249809.4 32.84 <.0001 year*pd 1 48095642.8 48095642.8 47.51 <.0001 cultivar 3 31466943.2 10488981.1 10.36 <.0001 year* cultivar 3 8364822.6 2788274.2 2.75 0.0438 pd* cultivar 3 28558495.7 9519498.6 9.4 <.0001 year*pd* cultivar 3 26978279.6 8992759.9 8.88 <.0001 week 4 156969072.8 39242268.2 38.76 <.0001 year*week 4 64411069.6 16102767.4 15.91 <.0001 pd*week 4 33103893.7 8275973.4 8.17 <.0001 year*pd*week 4 14952661.2 3738165.3 3.69 0.0064 cultivar*week 12 10678791.7 889899.3 0.88 0.5693 year*cultivar*week 12 8548308.3 712359 0.7 0.7469 pd*cultivar*week 12 11308373.4 942364.5 0.93 0.5172 y ear* pd* cultivar* week 12 11556563 963046.9 0.95 0.4972 year(block) 6 19363338.6 3227223.1 3.19 0.0053 year*pd*cultivar(block) 42 80407341.3 1914460.5 1.89 0.0021
Tests of Hypotheses Using the Type III MS for year(block) as an Error Term Source DF Type III SS Mean Square F Value Pr>F year 1 388657240.5 388657240.5 120.43 <.0001
Tests of Hypotheses Using the Type III MS for year*pd*cultivar(block) as an Error Term Source DF Type III SS Mean Square F Value Pr>F pd 1 33249809.39 33249809.39 17.37 0.0002 cultivar 3 31466943.19 10488981.06 5.48 0.0029 pd* cultivar 3 28558495.66 9519498.55 4.97 0.0048 year*pd* cultivar 3 26978279.64 8992759.88 4.7 0.0064
13 Table 2.2. Average number ofcotton fleahoppers and Lygus per acre estimated using a vacuum sampler in cotton plots grown in 2002 and 2003, Halfway, TX
Year Number of fleahoppers/A" Number of LygusIA^
2003 2774.8 a 30.5 b
2002 570.6 b 105.6 a
Planting Date
Timely 1995.0 a 88.2 a Late 1350.4 b 47.9 b Cotton Cultivar
Stoneville 2454R 1335.1 b 80.6 a Paymaster 2326RR 1753.3 ab 58.8 a Paymaster 2145RR 2147.5 a 74.1 a Paymaster 2167RR 1454.9 b 58.8 a
'By year, planting date and cotton cultivar, means within a column followed by the same letter are not significantly different (P>0.05, ANOVA).
14 Table 2.3. Two-way interaction analysis comparing the effect of planting date and cultivar on the number of fleahoppers per acre
Cultivar Timely planted Late planted
Stoneville 2454R 1316.0 b A 1354.7 a A Paymaster 2326RR 1908.0 b A 1598.7 a A Paymaster 2145RR 2927.2 a A 1367.8 a B Paymaster 2167RR 1830.0 b A 1080.3 a B
Means within a column followed by the same lower case letter are not significantly different (P>0.05, LSD).
Means withm a row, followed by the same uppercase letter are not significantly different (P>0.05, ANOVA)
All LSDs protected using simple main effect F-test in ANOVA.
15 Table 2.4. Three-way interaction analysis comparing the effect of year, planting date, and cultivar on the number of fleahoppers per acre*'"'''
Year Cultivar Timely planted Late planted
2002 Stoneville 2454R 287.5 a A a 487.9 a A a Paymaster 2326RR 644.7 a A a 818.9 a A a Paymaster 2145RR 697.0 a A a 853.8 a A a Paymaster 2167RR 392.0 a A a 383.3 a A a
2003 Stoneville 2454R 2343.5 c A P 2221.6 a A CO . Paymaster 2326RR 3171.2 be A P 2378.4 a A p Paymaster 2145RR 5157.5 a A P 1881.8 a B p Paymaster 2167RR 3267.0 b A P 1777.2 a B p
'By year, means within a column followed by the same lower case letter are not significantly different (P.0.05, LSD).
""Means within a row, followed by the same uppercase letter are not significantly different (P>0.05, ANOVA).
"^Means by cultivar and planting date, followed by the same Greek letter are not significantly different (P>0.05, ANOVA).
•"AU LSDs protected using simple main effect F-test in ANOVA.
16 Table 2.5. Analysis of variance statistics to compare the effects ofcotton planting date and cotton cultivar on Lygus abundance. Halfway, TX, 2002-03
Source DF Type III SS Mean Square F Value Pr>F year 1 451693.5905 451693.5905 37.64 <.0001 pd 1 129882.0679 129882.0679 10.82 0.0012 year*pd 1 27418.4935 27418.4935 2.28 0.1323 cultivar 3 29126.2198 9708.7399 0.81 0.4903 year* cultivar 3 16982.3887 5660.7962 0.47 0.7024 pd* cultivar 3 27608.2409 9202.747 0.77 0.5139 year*pd*cultivar 3 52654.8924 17551.6308 1.46 0.2261 week 4 495240.6096 123810.1524 10.32 <.0001 year*week 4 765061.3555 191265.3389 15.94 <.0001 pd*week 4 105879.0269 26469.7567 2.21 0.0699 year*pd*week 4 96391.6589 24097.9147 2.01 0.095 cultivar*week 12 116504.879 9708.7399 0.81 0.641 year* cultivar * week 12 85006.8173 7083.9014 0.59 0.8486 pd* cultivar* week 12 197716.7491 16476.3958 1.37 0.1817 year*pd* cultivar* week 12 132823.152 11068.596 0.92 0.5257 year(block) 6 214604.2642 35767.3774 2.98 0.0083 y ear*pd* cultivar(block) 42 403213.14 9600.3129 0.8 0.8025
Tests of Hypotheses Using the Type III MS for year(bloc;k ) as an Error Term Source DF Type m SS Mean Square F Value Pr>F year 1 451693.5905 451693.5905 12.63 0.012
Tests of Hypotheses; Using the Type III MS for year*pd *cultivar(block) as an Error Term Source DF Type III SS Mean Square F Value Pr>F pd 1 129882.0679 129882.0679 13.53 0.0007 cultivar 3 29126.2198 9708.7399 1.01 0.3973 pd* cultivar 3 27608.2409 9202.747 0.96 0.4212 year*pd*cultivar 3 52654.8924 17551.6308 1.83 0.1567
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CO fl CM o > CO CO bO CM _fl 'to fl 3 fl CO O < o o Td 00 ft - CM CO 3 .s CO 00 CO 1^ o o CO c bfi 3 fl Ix> <^ o s-1 00 CO 5 CM O 00 CO 5 CM 0) XI 00 ejov/sjequinisi CN bO fe 25 CN oO CN fl . 1—1 l-l Q. u O CO fl > bo 'co 3 fl < 00 S3 fl o fl O o o fl o 2^ 3 "O Ql Q: Q^ (U Q^ 01 Q^ Q: ^ CO IO N- CO bO ^ CM CM CM fl X) Q> v^ u. u- u. C 3 I o o ul-l X) 0^ OIOOIOOIOOIO CN Tt CO CO CM CM T- t- bO fe ejoV/sjequiriN 26 o O) o CO CN CM t-i 0a) 00 CO TJ- CM ^ fl o CO > CM • 0) Ui 3 CM < fl CM CO h- fl CM fl iO CO o CoM fl >» o 3 00 O (/I Xi c 05 3 I o CM O 00 CO CM CN fl bo ejoV/sjequinN fe 27 CHAPTER 111 COMPARISON OF SAMPLING METHODS FOR ESTIMATING LYGUS AliD FLEAHOPPER ABUNDANCE IN COTTON Introduction An essential part of all integrated pest management programs is an accurate sampling method. The choice of a sampling method should maximize precision while minimizing sampling time and cost (Gomez and Gomez 1984). Time is the limiting factor when sampling for insect pests and to be able to determine which ofthe available sampling methods are quickest and most accurate would be very beneficial. An acceptable method both minimizes costs and maintains a maximum precision level (Cochran 1977). There are a number of different methods available, but many factors influence the accuracy of the various methods in different ways. This can make it difficult to choose which method is best for a given suite of pests, predators and plant phenologies. Efficiency of the sampling method being used depends on the stage of the crop (height, density), sampling technique, envirorunental conditions, and the distribution and activity of the pest or predator being sampled. Most often in method evaluations, a relative sampling method is compared to an absolute sampling method. Absolute sampling is labor intensive, and in many cases, almost impossible to accomplish. The pest management approach to insect control caimot operate without accurate estimates of pest and natural enemy population densities, or without reliable estknates of plant damage and its effect on yield (Ruesink and Kogan 1975). Identification of methods that are both accurate and time saving is essential for increased yields and profits. The most widely used sampling method in the southwest is sweepnetting because it is easy and inexpensive (Ellington et al. 1984). Sweepnetting is also the most frequently used relative sampling tool for making insect counts on vegetation (Southwood 1978). Many plant species as well as a number of insect species are often sampled using this method. Many scientists have reported that the most commonly used 28 relative sampling method for determining Lygus densities in cotton is the sweepnet (Race 1960, Young and Tugwell 1975, Byerly et al. 1978, Wilson and Gutierrez 1980, Ellington et al. 1984, Fleisher et al. 1985). The sweepnet has been shown to be effective in sampling cotton in early season, but has often been criticized for its inability to capture insects later in the season. Saugastad et al. (1967) found that population estimates of certain insects determined by sweepnetting were influenced by time of day and the person performing the sampling, while sweepnet estimates of other insects were most affected by plant height. In addition, the sampling efficiency is influenced by plant phenology (Wilson and Gutierrez 1980). The effectiveness of sweepnet sampling in cotton has been found to be directly influenced by plant height as well as insect population densities and insect distribution pattems (Byerly et al. 1978, Ellington et al. 1984). Smith et al. (1976) found that adult insects were located higher on plants and were sampled more efficiently than immature insects that were located on the lower portions of the plant. As cotton plants mature, the accuracy of the sweepnet to determine Lygus and fleahopper abundance could be and probably will be affected. Precision is reduced by the inability of the sweepnet to penetrate the plant canopy as the plant grows (Byerly et al. 1978, Ellington et al. 1984). Byerly et al. (1978) found that the sweepnet is an effective way to monitor Lygus before cotton plants begin to bloom, but after bloom the sweepnet is ineffective in penettating the canopy of a cotton plant. Although the sweepnet is the most common method used for sampling Lygus in cotton, it has often been criticized for being the least precise (Schotzko and O'Keeffe 1986). The accuracy of sweepnet population estimates is affected by many factors such as plant canopy density (Schotzko and O'Keeffe 1986). A second type of relative sampling is the drop cloth or beat sheet. The drop cloth method uses a cloth placed on the soil surface between two rows of cotton and then vigorously shaking the plants on either side so that insects are dislodged from the plant and fall onto the cloth where they can be quickly counted. This method is attractive because it is less time consuming than absolute sampling and has the ability to sample the whole plant. Nuessly and Sterling (1984) found that there was no difference in time 29 spent in tiie collection of samples using both drop cloth and D-Vac. They concluded that the drop cloth was easier to use but did not speed the sampling procedure and did not consistentiy collect as many arthropods as did the D-Vac. Shepard et al. (1974) found that when sampling soybeans, sweepnet population estimates for most insect species were low when compared with a ground-cloth sampling method. When comparing drop cloth and suction sampling, Smith and Stewart (1999) reported that drop cloth was much more effective in capturing insects. It is essential that accurate estimates of insect populations be made in order for producers to be able to justify or warrant an insecticide treatment. In the past, beat sheets have been used extensively to give field scouts insight into infestations of plant bugs and fleahoppers in cotton. The drop cloth has proven itself to be an effective way to sample for many insects but it can be time consuming and less effective for highly active and flying insects (Herbert and Harper 1983). The beat bucket is another relative sampling method that is used to determine insect population abundance in cotton. The beat bucket method consists of placing cotton plants inside a five gallon white bucket and shaking the plants vigorously. The plants are then removed and insects that were dislodged inside the bucket are counted and recorded. ICnutson and Wilson (1999) stated that the beat bucket method was faster and more reliable in determining predator populations than was the sweepnet, shake bucket, or visual search of the plant, and was less tedious than using a drop cloth. They concluded that the beat bucket was the most cost-effective method for commercial field monitoring of arthropod predators. However, the beat bucket method samples only the top 1/3 of tall plants late in the season, so its efficiency depends on insect distribution pattems within the plant canopy. The vacuum sampling method has been used to sample a variety of insects in a diverse number of crops and comparisons to other sampling methods have been made investigating benefits and drawbacks of its use (Benedict and Cothran 1975, Gonzales et al. 1977, Pmess et al. 1977, Shepard et al. 1974, Simonet et al. 1978 and 1979, Smith et al. 1976). Using a vacuum sampler for insect sampling may be common; however, its 30 effectiveness as a sampling tool for Lygus and fleahopper in cotton has not been examined. As plants mature, the vacuum sampler experiences the same problems as the sweepnet in that it samples only the top portion of the plant. A number of different vacuums have been used to sample insects ranging from very large and cumbersome machines to more evolved smaller models. The primary disadvantage associated with the vacuum sampler is that it is difficult to maneuver and hard to transport from one location to another. The older D-Vac played an important role in sampling cotton arthropods (Dietrick 1961) for many years and was the most reliable and accurate method for sampling Lygus and fleahopper in cotton. However, utility in pest management has been very minimal. Absolute arthropod density estimates or whole plant samples are usually taken by researchers and are needed to validate the accuracy of relative sampling methods (Southwood 1978). Whole plant sampling has proven to be more accurate in estimating insect population abundance than that of relative sampling but has the same problems as some ofthe other methods: it is time consuming and impractical (Byerly et al. 1978, Ellington et al. 1984, Fleisher et al. 1985). Knutson and Wilson (1999) also made the observation that visual sampling proved to consume more time per sample and that larger numbers of samples were required to estimate various arthropod densities relative to the sweepnet and beat bucket methods. Other problems that are encountered while visually inspecting a plant are that the highly active and flying insects will often flush before being observed (Layton 2000). This can result in lower number estimates than are actually present just prior to begiiming the sample and can lead to false conclusions and incorrect recommendations. Moreover, the efficiency of visual sampling is dependant on the sampler, so it is also a form of a relative sample. Layton (1999) recommends visual sampling for Lygus once plants begin to bloom because of the inability of the sweepnet and drop cloth to be used effectively. However impractical and time consuming, absolute sampling is the most accurate way to determine population densities. 31 Many studies have been done on sampling method comparisons but there is limited information when targeting specific insects such as Lygus and fleahopper in cotton. The objective of this study was to find the most efficient and least expensive way to determine population estimates of both insect pests. Because the efficiency of a sampling method is influenced by crop phenology during the growing season, we evaluated four relative sampling methods including the sweepnet, drop cloth, beat bucket, and vacuum sampler together with the visual sampling method. Materials and Methods Field experiments were conducted in 2002 and 2003 in Hale County at the Helms Farm located near the Texas Agricultural Experiment Station at Halfway, TX. In both years this experiment was conducted in the same group of plots used in the experiment testing planting date and cultivar (Chapter II). All samples were taken in plots planted to cultivar Paymaster (PM) 2326RR. The statistical model used to analyze the effectiveness of the five sampling methods was constmcted to include year and week as repeated measurements. All samples used in the einalysis were taken from the timely planted cotton. Insect sampling began on June 17 during the 2002 season and continued until September 26. Sampling during the 2003 season began on June 25 and ended on August 28. In both years sampling was conducted on a weekly basis. Five sampling methods (vacuum, drop cloth, beat bucket, sweepnet, and visual sampling) were evaluated to compare relative efficiency in arthropod monitoring. PM 2326RR was chosen based on its reputation as a well performing variety and its adaptation to the region. Sampling methods used to monitor insect populations included the vacuum sampler (30 second vacuum time/plot-100 row feet), sweepnet (100 sweeps/plot-300 row feet), beat bucket (8 plants/plot), drop cloth (24 row ft/plot), and visual inspection (10 plants/plot). Insects monitored using these methods were: fleahoppers Pseudatomoscelis seriatus, Lygus hesperus and Lygus elisus. 32 The experimental design was RBD Split-Split plot (year as main plot, treatment sampling methods as sub-plot and week as sub-sub-plot or repeated). Five sampling dates were used from each year consisting of data from (7/22-8/21) to create the variable week and maintain a balanced model. Results and Discussion Cotton fleahopper. Fleahopper abundance varied with year and sampling methods (Table 3.1). Fleahopper nimibers were generally higher in 2003 than 2002 with a large population peak in mid-August (Figure 3.1). A peak also occiured in mid-August of 2002, but it was of a much smaller magnitude. Seasonal mean numbers of cotton fleahoppers captured were significantly higher in 2003 than 2002 (Table 3.2). This could be due to a number of different situations that occurred one year and not the next such as increased rainfall, a greater population of altemate hosts, and or different cultural practices in adjacent fields. Weekly fleahopper catches in plots using the five sampling methods in 2002 and 2003 are presented in Figures 3.2 and 3.3, respectively. In 2002, beat bucket and visual sampling outperformed the other methods on every sample date they were used (Figure 3.2). In 2003 much the same pattem was observed, with beat bucket and visual sampling detecting the highest numbers of fleahoppers (Figure 3.3). Beat bucket demonstrated the ability to detect significantly more fleahoppers than did any of the other sampling methods (Table 3.2). Visual sampling detected significantly lower numbers than did the beat bucket, but significantly more than did the drop cloth, sweepnet, or the vacuum (Table 3.2). These numbers were also numerically sttiking. Beat bucket and visual sampling detected 7000 more fleahoppers/A than the highest of the other three methods. Beat bucket detected over 17000 more fleahoppers/A than the vacuum sampler method. This supports past research that has tried to determine the most efficient way to sample fleahoppers in cotton (Knutson and Wilson 1999, Benedict and Cothran 1975, Gonzales et al. 1977, Pmess et al. 1977, Shepard et al. 1974, Simon et al. 1978 and 1979, Smith et al. 1976). It has been documented tiiat the sweepnet and vacuum sampler lose 33 effectiveness as cotton plants mature and the research presented here supports this conclusion. The F-test for the year*sampling method term was highly significant (Table 3.1) so an interaction analysis was performed for the two effects. The results are presented in Table 3.3. In both years, beat bucket or visual sampling detected numerically higher fleahoppers than the other methods. In 2002, visual sampling detected the most fleahoppers and separated statistically from the drop cloth, vacuum sampler and sweepnet. In 2003, beat bucket detected significantly more fleahoppers than the other methods with 34285.7/A. Visual sampling detected 13200.0 fleahoppers/A, a number significantly higher than the drop cloth, vacuum sampler or sweepnet~the latter two of which detected numbers not significantly different from each other. Many more fleahoppers were captured in 2003 than in 2002, and the year effect was significant for both visual sampling and beat bucket (Table 3.3). This analysis strongly indicates that regardless of population level, visual sampling and beat bucket are more effective at detecting cotton fleahoppers than the other methods tested. At the higher population level of 2003, the beat bucket was more effective at detecting fleahoppers than visual sampling, while in 2002 at a lower population density, visual method out-performed the beat bucket. It is possible that at lower fleahopper densities, the precision of on-pleint, visual sampling makes it superior to the faster beat bucket. Visual sampling requires the sampler to spend large amounts of time handling the plants. Insects are generally counted slowly, particularly relative to the beat bucket. At higher fleahopper densities this may increase the number of fleahoppers that escape unseen and are not counted. In this case the quickness ofthe beat bucket may make it the more effective method. Plant phenology is probably a factor as well. The beat bucket is most effective on medium sized plants. Plants that are too small or too large cannot be effectively sampled by the method. Though large plants take time to sample visually, increasing escapes, this is not the case with small plants. 34 These results suggest that the beat bucket method should be used at higher populations, when the plants are of a size that the bucket can contain effectively. Visual sampling should be used at lower population levels and on smaller plants. Lygus. Due to low numbers, the two species of Lygus, L. hesperus and L. elisus, were combined to total Lygus, and this number was used in the analysis. The same analysis model used for fleahopper analysis was also used for Lygus numbers. ANOVA indicated significant effects of year and seimpling method and a significant effect on seasonal population abundance of or ability to detect Lygus (Table 3.4). Lygus populations were higher in 2002 than, with two population peaks: one in late June and one in late-July. Lygus numbers in 2003 showed a peak in mid-August and a rising popidation when sampling was terminated in early September (Figure 3.4). Plots of numbers of Lygus bugs detected by the five methods for 2002 and 2003 are presented in Figures 3.5 and 3.6. In 2002, beat bucket detected more Lygus than all the other methods on each sample date it was used. In 2003, the beat bucket method also performed relatively well, capturing much higher numbers of Lygus on several sample dates (Figure 3.6). A population peak was detected using sweepnet sampling in late-August. Concurrent in time with this peak, beat bucket counts fell to zero. This valley in the curve is suspicious, and may be due to some sort of error, such as improper recording of data. Variability of effectiveness ofthe methods suggests that any single sampling method may be more or less effective depending on the time of year the sampling is occurring. Beat bucket captured significantiy more Lygus on a seasonal basis than all the other methods tested (Table 3.2). Drop cloth, sweepnet, visual and vacuum did not differ significantly in their ability to detect Lygus. Numerically, visual sampling was the next most effective method to beat bucket followed by drop cloth, sweepnet, and vacuum sampler, in that order. Performance ofthe vacuum sampler was very poor. This method only managed to detect less than five percent of the Lygus detected by the beat bucket. It appears that of the methods tested here, the beat bucket is by far the most effective tool for sampling Lygus bugs, though effectiveness to an absolute method should be investigated. All interactions in this model had non-significant F-tests and tables were not constmcted. 35 Table 3.1. Analysis of variance statistics to examine the effect of sampling methods on fleahopperabundance . Halfway, TX, 2002-2003 Source DF Type III SS Mean Square F Value Pr>F year 1 5514293769 5514293769 90.01 <.0001 method 4 13269005358 3317251339 54.15 <.0001 year*method 4 7979726187 1994931547 32.56 <.0001 week 6 9863860067 1643976678 26.84 <.0001 year*week 6 7949504972 1324917495 21.63 <.0001 week*method 24 20100155646 837506485 13.67 <.0001 year*week*method 24 17922346874 746764453 12.19 <.0001 year(block) 6 142538437 23756406 0.39 0.8862 year*method(block) 24 1617775367 67407307 1.10 0.3475 Tests of Hypotheses Using the Type III MS for year(block) as an Error Term Source DF Type III SS Mean Square F Value Pr>F year 1 5514293769 5514293769 232.12 <.0001 Tests of Hypotheses Using the Type III MS for year*cultivar(block) as an Error Term Source DF Type III SS Mean Square F Value Pr>F method 4 13269005358 3317251339 49.21 <.0001 year*method 4 7979726187 1994931547 29.60 <.0001 36 Table 3.2. Average number ofcotton fleahoppers and Lygus per acre estimated using five sampling methods in cotton plots grown in 2002 and 2003, Halfway, TX Year Number of fleahopper Number of Lygus 2003 11539 77.9 2002 2663.4 523.6 Sampling Method Beat bucket 19273 a 1075.4 a Visual 10183 b 167.3 b Drop Cloth 3095 c 123.6 b Sweepnet 1509 c 96.8 b Vacuum sampler 1447 c 40.4 b Means followed by the same letter are not significantly different (P>0.05, ANOVA). 37 Table 3.3. Two-way interaction analysis comparing the effect of year and sampling method on the number of fleahopperspe r acre, Hal^ay, TX, 2002-2003 Method 2002 2003 Visual 7165.2 a A 10.0 13200.0 b B Beat bucket 4260.4 ab A 6.0 34285.7 a B Drop cloth 1037.1 b A 7.0 5152.3 b A Vacuum sampler 535.2 b A 8.0 2358.5 c A Sweepnet 319.3 b A 9.0 2698.6 c A Means within a column followed by the same lower case letter are not significantly different (P>0.05, LSD). Means within a row, followed by the same uppercase letter are not significantly different (P>0.05, ANOVA) All LSDs protected using simple main effect F-test in ANOVA. 38 Table 3.4. Analysis of variance statistics to examine the effectiveness of sampling methods in detecting Lygus abundance. Halfway, TX, 2002-2003 Source DF Type III SS Mean Square F Value Pr>F year 1 13904678.7 13904678.7 14.76 0.0002 method 4 42483872.47 10620968.12 11.28 <.0001 year*method 4 28815718.36 7203929.59 7.65 <.0001 week 6 5192442.95 865407.16 0.92 0.4826 year*week 6 8726540.82 1454423.47 1.54 0.1662 week*method 24 21240153.12 885006.38 0.94 0.5484 year*week*method 24 24802963.59 1033456.82 1.10 0.3509 year(block) 6 15259142.67 2543190.45 2.70 0.0156 year*method(block) 24 80882466.94 3370102.79 3.58 <.0001 Tests of Hypotheses Usmg the Type III MS for year(block) as an Error Term Source DF Type HISS Mean Square F Value Pr>F year 1 13904678.7 13904678.7 5.47 0.058 Tests of Hypotheses Usmg the Type III MS for year*cultivar(block) as an Error Term Source DF Type HISS Mean Square F Value Pr>F method 4 42483872.47 10620968.12 3.15 0.0324 year*method 4 28815718.36 7203929.59 2.14 0.1072 39 CO o CM a 00 CO 1 bO ^ CM CO ^4-1 CO O CM fl Ui o I CO 3 I -a CM < CM I o 'bo - 00 CJ a .3& CM C to CM ofli a >-. fl CO CO 00 CO ^ CO 0) c: (1> cs 00 3 fl -^ CO x! (U g "E Xi fl o CS O IO O IO O IO lO > Tf CO CO CM CM T- 40 X) C>4 00 a CM CO I > CO I CM OH CM S fl 3 bO fl CO 00 Q, CO Co -—i CO c 00 3 fl o o u X) XI o o o o o O 00 CO ^ CM O 00 to ^ CM CN o CM T- T- T- T- rn fl ^ bO o 8J3V/sjeqiun|si fe X) 41 V-l a o fl o CO CS 4> Ui CO o 3 o < (L> C r«S bO O fl o •X3 CN ^ 3 CO tX ^ i « I o I 3 11 m > Q (0 > g > c CO fl !-< cd 3 & CL, fl ^ fl ;-! ^ "^^ CO CM 00 CO CM • -i-> i| • I-H (U 3J9V/sjaqiunN fe Xi 42 bO a. o fl CO I 13 ^? o g fl cn O .-, Ui ' eci ccJ fl 3 CO < O c3 :^ 9^ 'co 'O °l ll So fl f^ 3 (U TS X) 0) ^-. f-^ CO "^ bo PH 0 X) c3 C 3 li C4H 8 o > ID X) fl CM CO <0 ' bO u ejov/sjaquinisj fe 43 ^ : 1 fl CM o CS > '' \ 00 a A O fl 0 CM CO a, J CO * CO CO O CM T3 O - O CN •^ !>/ • B^ CM 3 1 CM < •a" I / y - 00 g 13 / ^ CM ,.o'' /)4-( >'§ ' ' ' ' O « .S bO "CL, c .fl ff fl CO ^13 jf\ - CO ^ fl 3 U CO '4-> p "5 o o <» , CO 3 r^ c £ OH S m — O Q. : 00 5 <•> T3 3 to fl bX) S ro p eat i isu a we e 0 m > Q (0 ::> c X) rS 3 < f - 00 1 \ 1 f Ifl X^) O IO O IO O IO IO ^ ^ CO CO CM CM T- ai i^ b^O &fl ejoV/sjaquinN fe CO 44 fl > fl 0) CO izi • ^—' m 00 O •rt O O 0) '^ > SP lf3 c fl S fl CO (D Q, fl CO fl bO 3 0 C ^ e^ 3 fl X3 13 X) CO CM 00 CO ^ CM •SP i fe CO ajov/sjequinisi 45 CHAPTER IV EFFECT OF LYGUS HESPERUS FEEDING ON DEVELOPING COTTON BOLLS Introduction There are nine species of the genus Lygus that are important in North American agriculture. The westem tamished plant bug (WTPB), Lygus hesperus Knight, is widely distributed in the westem regions of the United States (Barlow et al. 1999). Economically, the WTPB is the most important Lygus species in the west (Scott 1977). The majority of research that has been done on Lygus has been conducted on the tamished plant bug (TPB), or Lygus lineolaris (Palisot de Beauvois), the dominant Lygus species in the southeastern U. S. cotton growing region. However, the biology and damage caused by WTPB and TPB are very similar. Adult WTPB reinge from 5.3-6.5 mm in length and 2.3-2.8 mm in width and have a reddish brown abdomen. These adults go into diapause when light durations decrease to less than 12.5 hours per day and overwinter in plant debris and ground trash (Bariola 1969). When the duration of light is greater than 13.5 hours per day, diapause is terminated and reproductive activity begins (Bariola 1969). A WTPB female can produce 500 eggs in a 20-day period of reproductive activity. When eggs are laid, they are inserted into plant tissue and only the oval shaped cap of the egg is visible (Leigh et al. 1996). Tamished plant bugs undergo gradual metamorphosis and have piercing sucking mouthparts (Layton 2000). Nymphs pass through five instars over a time period of between 12 to 20 days before becoming adults (Bariola 1969). Depending on temperature, adults can survive on cotton for 6 to 30 days. Life cycles of these insects usually range from between 20 to 30 days during the summer months. In the San Joaquin Valley where a large amount of WTPB research has been conducted, there can be five to seven generations per year on alfalfa and as many as three on cotton (Leigh et al. 1996). 46 At this time, Lygus spp. is moving up in the hierarchy when economically important cotton pests are discussed. There are key characteristics in distinguishing the WTPB from other Lygus spp, the most important of which are dark spots on the propleura, or several pairs of spots on the pronotum (Mueller et al. 2003). Westem tamished plant bugs can use at least 100 plant species in 24 families as hosts (Scott 1977). The reasons Lygus spp. are such successful pests can be attributed to their ability to utilize such a wide range of host plants (Hedlvmg and Graham 1987). The reason they are able to utilize such a wide range of hosts is related to their very efficient feeding apparatus. As hemipterans, Lygus use a process of extra-oral digestion feeding which allows them to feed on a variety of tissue types (Cohen 1990, 1995, 1998). Some of the more common families of weed hosts that are important to WTPB include: Asteraceae, Fabacea, Brassicaceae, Graminae, Chenopodiaceae, Plantaginaceae, and Rosaceae (Scott 1977). In the Texas High Plains during the spring, mustard or flixweed {Descurainea sophia), redstem filaree {Erodium cicutarium), and alfalfa (Medicago sativa) all support Lygus spp. (Parajulee et al. 2003). During the summer, alfalfa, yellow sweetclover (Melilotus officinalis), woolyleaf bursage (Ambrosia grayi), curly dock {Rumex crispus), Russian thistle (Salsola iberica), field bindweed (Convolvulus arvenis), broomweed (Amphiachyris dracunculoides), ragweed (Ambrosia artemisiifolia), and pigweed (Palmer amaranth) all supported Lygus spp. populations (Parajulee et al. 2003). Lygus can invade cotton at any time between early May and September from other crops and weed hosts as the host plants mature or are harvested (Sevacherian and Stem 1975). Tamished plant bugs can cause damage to cotton from emergence of seedlings through the early lint developmental stage of the last harvestable bolls (Layton 2000). Lygus cause damage at different times throughout the growmg season, but most of the economic damage by the TPB occurs from square initiation to early bloom (Tugwell et al. 1976). Feeding by the TPB causes swollen nodes, shortened intemodes, deformed leaves, non-fertile squares, terminal abortion and may induce vegetative growth in the plant which causes delayed maturity and yield loss (Scales and Furr 1968, Wene and Sheets 1964, Tugwell et al. 1976, Hanney et al. 1977). From the fourth to sixth tme leaf 47 stage through early squaring is the period when the cotton plant is most susceptible to yield loss from TPB feeding (Scales and Furr 1968). Other studies have shown that damage consists of the destmction of small squares where the bugs have fed on anthers and ovules, the destmction of meristematic tissue in the plant terminals, and destmction of developing seeds and bolls (Leigh et al. 1988). Anonymous (1969) also observed that the tender terminal grov^h (meristems), squares (flower buds), blooms, and fruits (bolls) that were fed on by WTPB were abnormal, stained, or had seed injury. Feeding by the TPB during fruiting can also cause delayed boll maturity and significant yield loss (Scott et al. 1986). Pack and Tugwell (1976) stated that when older squares are damaged by Lygus that development may continue but the square damage results in damaged bolls. The bottom line is that feeding by Lygus spp. on cotton can have a significant impact on yield. In the past, research on Lygus spp. injury has focused mainly on damage to squares and terminals and not to bolls. Most of this research has focused on TPB, and few studies have been conducted on WTPB feeding and injury to cotton bolls. Few studies have examined the effects of TPB during the flowering and later developmental stages of cotton development (Russell 1999), but Wilson et al. (1984) studied the WTPB and found that about twice as many adults were on bolls as on squares. At the present time, plant bugs are controlled primarily by insecticides. Insecticides are a very useful tool in pest control, but they also have the detriment of reducing beneficial arthropod numbers which can in tum lead to other pest problems. If a time frame could be established to determine when insecticide use can be terminated for WTPB control, it would not only decrease chemical usage, it could also increase yields, both of which result in higher net profit to cotton producers. The objective of the study was to determine when cotton bolls were safe from WTPB feeding injury using heat units as the indicator of boll maturity. Materials and Methods The study was conducted at the Texas Agricultural Experiment Station at Lubbock, TX. The cotton cultivar selected was PM 2379RR, chosen based upon its 48 reputation as a variety with good yield potential. Irrigation was conducted using the furrow irrigation method and row spacing was 40 inches. An optimum planting date of May 12, 2003 was chosen for the study, to insure normal growth and fruit maturity pattems. The study cotton was planted using a John Deere MaxEmerge planter with a seeding rate of 15 pounds per acre. The systemic insecticide Temik was applied at 3.5 pounds per acre to prevent early season thrips damage. Treatments consisted of cotton bolls of different maturities (150, 250, 350, 450, and 550 heat units). A single unsexed Lygus hesperus adult was caged on each boll in the field for a period of 48 hours. Bolls were then collected, examined for damage and tested using a penetrometer constmcted in-lab to determine pressure required to penetrate the carpel wall. As a control, 60 white blooms were tagged, allowed to mature and were harvested at season's end. To prepare for the test, a total of 800 white blooms were individually caged on August 4, 2003 using 4x6 inch white nylon #280 mesh bags with drawstrings for closure. More blooms were caged than were necessary for the test to allow for any natural fruit shed that would take place. Fmit was caged at the white bloom stage to eliminate damage by other insects and cages remained in place from the white bloom stage until the desired heat unit accumulation was reached. Caging procedures were similar to that of Hom et al. (1999). A total of 100 bolls were allocated for each heat unit accumulation. Daily heat unit accumulation (>60 °F) was determined from the day the bags were placed over the bolls. The crop reached the freatment heat units as follows: August 9 = 150HU, August 16 = 250 HU, August 20 = 350 HU, August 25 = 450 HU, September 29 = 550 HU. Lygus were collected from nearby alfalfa using a conventional 15" sweepnet then fransferred to 1-gallon Ziploc brand plastic storage bags. The bags containing the insects were then placed into an ice chest containing freezer packs and transported to the laboratory. Lygus were immediately separated from plant matter and other insects using a hand held aspirator. Lygus hesperus were separated from other Lygus species at this time 49 and placed into a 6x10 inch round plastic container with a cheese cloth lid. They were observed in the laboratory for a period of 24 hours to isolate bugs injured during the collection process. During this time they were given a diet of fresh green beans, Phaleolus vulgaris (L). The container holding the WTPB was then placed back into the ice chest with the freezer packs and transported to the field for infestation release. Each boll was infested with a single WTPB using a hand held aspirator. The cheese cloth lid covering the 6x10 inch container was carefully lifted exposing the Lygus. The WTPB were then sucked into the aspirator by mouth and gently blovm into the mesh bag that had been placed around the white bloom earlier in the season, and now contained the boll that had received the desired heat units. The infestation period for bolls lasted 48 hours at which time WTPB were removed. Bolls on which the infesting WTPB had died during the 48-hour period were discarded. Only bolls on which the WTPB were still alive after the 48 hour period were used. A total of 60 bolls were infested for each heat unit accumulation period; of those, 20 were used to determine inner injury and outer damage, and 20 were allowed to mature and were harvested. The 20 bolls for the injury and damage examination were removed from the plant the same day the Lygus were removed (after 48 hrs). The bolls were placed into an ice chest with freezer packs, brought to the laboratory and stored in a growth chamber at 15° C for 48 hours. Bolls were removed from the chamber and examined extemally then dissected to identify intemal feeding damage. Dark and sunken lesions on the outer wall were counted and recorded to determine extemal injury. The dissections were performed using a scalpel, and punctures that penefrated the endoderm were recorded (Wene and Sheets 1964). Lint staining and seed damage that occurred due to these punctures were also recorded. The remaining bolls that had been infested were left on the plant until maturity at which time they were harvested by hand to determine lint quality and yield. Bolls were harvested on December 12, 2003 and bolls of each HU accumulation were kept separate by placing them in brown paper sacks designated for the corresponding HU. The mature bolls were taken into the laboratory and weighed. Total weight or bur weight was taken for each individual boll. Each boll was then hand ginned and lint and seed 50 weight was taken for each individual boll. Numbers of seed per boll was also recorded. Lint from all bolls was combined by freatment and taken to the Texas Tech University Intemational Textile Center in Lubbock, TX for fiber analysis. Data were analyzed with ANOVA and means were separated using LSD (SAS Institute 2003). The same day, the WTPB were infroduced (the day total heat units equaled the desired accumulation) the bolls that were not infested, but caged, were removed and brought into the laboratory for penetrometer testing. These were bolls of the 100 that were caged for each specific age that were retained by the plant to this point but not infested with WTPB. This was repeated for each heat unit accumulation of 150, 250, 350, 450, and 550. After being brought back to the lab, these bolls were placed into a cradle {V2 inch PVC cap) to hold them firmly in place during penetrometer testing. The penefrometer was built using a 1/16 inch drill bit with the flat end pointed downward and fixed onto a VA" X 18" aluminum rod. The bit was fixed to the rod so that the flat end of the bit was pointing downward and would be the surface used to test boll wall toughness. A drill bit made an ideal probe because ofthe flat end and the fact that the diameter ofthe bit was known, allowing pressure calculations. The aluminum rod was guided in its up/down travel by a 54" x 8" steel pipe. A fiirmel was attached to the top ofthe rod where the weight could be added, and number 6 lead bird-shot was used as the weight. The boll in the cradle was placed directly under the drill bit, and lead shot was slowly dribbled into the fimnel until the weight had forced the tip of the drill bit to puncture the carpel wall. The weight of the shot was placed on a balance and the weight was recorded. The rod, funnel and bit were weighed together. This weight was added to the weight of the shot and ftinnel and the total weight applied was calculated. The known surface area of the drill bit tip allowed calculation ofthe pressure necessary to puncture the boll. Fifteen bolls for each heat unit accumulation were tested. Results and Discussion Percent damage and injury to bolls of different ages. Outer injury refers to the damage caused that is visible on the outside ofthe cotton boll. Inner damage refers to the damage that was caused intemally to the cotton boll by the infestation of WTPB. Feeding 51 injury by WTPB to cotton bolls was greatest on the bolls that had accumulated 150 (HU). There was outer injury on 100 percent of these bolls. Outer injury of bolls dropped slowly as boll age increased to 300 HUs, then dropped sharply at 450 and 550 HU with outer injury at 25 percent on the 550 HU bolls (Figure 4.1). Bolls that had accumulated 150 HU suffered inner damage on 60 percent ofthe bolls that were infested. Bolls that had accumulated 350 and 550 HU suffered inner damage on only 5 percent of the bolls that were infested and bolls that had accumulated 450 HU suffered no intemal damage (Figure 4.1). The total amount of damage associated with these bolls ranged from a total of 209 outer punctures on the 20 bolls that had accumulated 150 HU to a low of 56 on the 550 HU bolls (Table 4.1). The total amount of intemal injury ranged from 48 on the 150 HU bolls to 0 on the bolls that had reached 450 HU (Table 4.1). Results indicate that as boll age increases the amount of outer damage and inner injury decrease, and that after bolls have received 350 HUs they are relatively safe from intemal injury caused by WTPB. Results are from a one-year study therefore, for a sfronger conclusion to be drawn further research needs to be conducted. Effect of heat units on boll size. As heat units increased the boll size increased significantly, with all boll ages significantly different from each other (Table 4.2). The bolls that accumulated 150 HU on the average were 17.6 mm in diameter. The average size for bolls that accumulated 550 HU was significantly higher at 33.7 mm in diameter. Effect of Lygus hesperus on seed and lint. Number of seed per boll decreased with decreasing numbers of heat units the boll had received at time of Lygus infestation (Table 4.3). There were significant differences in mean number of seed per boll when comparing bolls that had been infested at different heat unit accumulations. Average number of seed ranged from 21 seed per boll for the 150 HU freatment to 29.57 seed per boll for the 550 HU treatment (Table 4.3). Bolls of 150 HUs at time of infestation had significantly fewer seed per boll than bolls of 350, 450 and 550 HUs, and uninfested confrol. This indicates that WTPB damage to seed decreases as the number of heat units a boll receives prior to infestation increases. 52 There were differences in seed weight per boll depending on stage of bolls at time of infestation with WTPB. Bolls that were mfested at 150 HU had an average seed weight of 2.8 g which was significantly lower than that ofthe 250 and 450 HU bolls (Table 4.4). The weight of seed from the control bolls did not weigh significantiy more when compared to the bolls that had accumulated 150 HU, but the control bolls had a numerically higher seed weight and the difference was substantial. This analysis did not break as cleanly as the number of seed (Table 4.3), but it does suggest a trend that bolls attacked by Lygus at 150 HUs of age are the most susceptible to loss of seed weight in bolls (Table 4.4). There were also differences in the mean lint weight from the bolls that had been infested at different ages. Lint from bolls infested at 150 HU weighed significantly less at 1.78 grams than those infested at 250, 450 and 550 HU with the highest weight at 450 HU (2.13 grams) (Table 4.5). Though there is not a clear trend of more lint linked to less damage to older bolls, with the control falling low in the range, the 150 HU or youngest boll attacked by Lygus had the lowest lint weight, while the bolls receiving the most heat units (450 and 550) or the oldest bolls attacked produced the most lint. Though the pattem is not perfect, it does indicate that older bolls do suffer less lint loss due to Lygus damage, and that bolls of 150 heat units are most susceptible. Effect that age had on the toughness of the carpel wall. Bolls that had accumulated 150 HU requfred the least amount of pressure to puncture the top of the carpel wall (Table 4.6). Bolls that had accumulated 350, 450 and 550 HUs required significantly more force than those of 250 and 150 HUs. The increase from 250 to 350 HUs was almost 250 grams/mm^, indicating a rapid increase in hardness between the two ages. The force required to puncture a boll side or lock also increased with increasing maturity. It required 823.24 grams to puncture a boll that had accumulated 150 HU, the lowest amount of force required to penetrate bolls of any of the freatments. As with boll tops, bolls of 350, 450 and 550 HUs required significantly more force for penetration than bolls of the other two ages (Table 4.6). Plotting pressure required to puncture the 53 carpel wall on the boll side or lock shows clearly that pressure needed increases until the 350 HU age and then begins to level out (Figure 4.2). The trend was similar in the force required to puncture the lower 1/3 or bottom of the boll (Table 4.6). The amount of force required was generally stratified by boll age, with the 550 HU treatment requiring the most pressure. At 150 HU it required 1004.77 grams to puncture a boll, a number significantiy less than that for bolls of all other ages, and less than half the force required to penetrate 550 HU bolls. Again 350, 450 and 550 heat imit means separated from both 150 and 250 HU means. For every heat unit freatment, the side of the boll or lock required the least pressure for penefration, indicating that it is the softest area and therefore the most susceptible to attack by Lygus. A boll hardness sampling method used to determine the point at which bolls are safe from Lygus damage should use the side of the boll or lock, rather than the top or bottom. The increase in force required to penetrate a boll gaining 100 heat units is presented in Figure 4.3. As bolls increased in age from 150-250 HU on average it required 375 more grams for penetration. From 250-350 HU it required 240 more grams to penefrate, from 350-450 HU it required 140 grams more to penetrate, and from 450- 550HU it required only 8 grams more to penefrate (Figure 4.3). As the boll increases in age, the force required to penefrate the bottom significantly increases to a point and then levels off. These data all support the finding that as a boll increases in age it becomes harder and less vuhierable to damage by WTPB. Linear regression analyses were run to correlate damage with the amount of pressure required to puncture the carpel wall of a boll. The regression for outer feeding and pressure was not significant indicating no trend, and a weak R of 0.5014 indicated poor fit ofthe model (Figure 4.4). The lack of any pattem in the data may have been due to problems in our design. A caged control should have been included to determine if perceived outer injury spots were tmly Lygus injury or simply age spots. Due to shed of bolls, the initial number caged would have been insufficient to complete the test. A new 54 set of bolls had to be caged at a later date. These bolls were used for the 550 HU freatment, and were of a different age in days than the other bolls tested. Because of these problems it was impossible to predict when a boll is safe from outer injury (Figure 4.4). Further investigation and research will need to be conducted if a strong conclusion is to be drawn. The inner injury data did present a pattem, and a significant linear model was fit to the data using the least squares method (P=0.0092) (Figure 4.4). A relatively strong R^ of 0.9232 indicated a good fit. The regression line crossed the x-axis at about 1500 heat units, indicating that zero WTPB damage can be expected at this boll hardness. These results were obtained using a homemade penetrometer. The fact that WTPB damage and a safety threshold for bolls can be predicted even using data obtained v^th such a cmde insfrument indicate that if an instrument can be found or built that can uniformly and reliably measure boll hardness it can be used to develop a usable threshold to predict when a cotton boll is safe from WTPB injury. Further investigation is needed to develop this tool and refine the threshold. Future researchers should include boll age in days and a confrol to screen age spots as components in their study. WTPB have the ability to cause damage and injury at significant levels up until the boll reaches the 350 HU age at which time the boll is no longer as susceptible to significant injury by this pest. These findings will be useful to producers allowing them to eliminate later season insecticide applications to control WTPB infestations. Infestations late in the season should not cause economic loss therefore treatments are not necessary. The ability to eliminate unnecessary insecticide applications for later season Lygus will increase profit and decrease environmental impact. This study was conducted over a time period of one year. Trends presented here justify further research to verify the results of this study and to further refine the understanding of these pattems before they are incorporated into IPM programs. 55 "OOOOOOOOOOOOOOOOOOO o ^ vo^roTtm—lO-^mvooofs-^Ti-fNmoooo m O o Xi oooooooooooooooooooo fl o o '§ IT) VH '=>'-' "^ 1£ X) CO o T—H cr[ o X3 oo fl m-H^io^rJmino-^oijo-^—"VOTt-^mfS o o o o OCNOOOOOOOOO-HtNlrOOOO-^OO o, CO CM 00 r»1^0>0 — l>0'«d-000-^-^(NOOOOO--i^O ri o in B ch O oNC:c^2^!2f^2;z:i»^'*cn^c^s o - ^ ^ ^ (N o ;-! X5 (Nm-^invor-ooONO D —iCNmTj->/ivot-ooejN o H 56 Table 4.2. Relationship between boll size and boll age Boll age Boll size (mm)' 550 HU 33.7 a 450 HU 32.3 b 350 HU 29.7 c 250 HU 26.7 d 150 HU 17.6 e Table 4.3. Effect of Lygus feeding on seed production in relation to boll age Boll age Number of seed/boll" Control 27.34 ab 550 HU 29.57 a 450 HU 25.27 b 350 HU 25.25 b 250 HU 24.56 be 150 HU 21.78 c Table 4.4. Effect of Lygus feeding on average seed weight in relation to boll age Boll age Seed weight (grams)° Control 3.24 ab 550 HU 3.20 ab 450 HU 3.32 a 350 HU 3.12 ab 250 HU 3.36 a 150 HU 2.82 b Table 4.5. Effect of Lygus feeding on average lint weight in relation to boll age Boll age Lint weight (grams) Control 1.93 ab 550 HU 2.07 a 450 HU 2.13 a 350 HU 2.02 ab 250 HU 2.04 a 150 HU 1.78 b ^Means followed by the same letter within each Table are not significantly different (P>0.05). 57 Table 4.6. Average pressure (grams/mm^) required to penetrate the cotton boll in relation to boll age^ Boll Age Top 1/3 Middle 1/3 (side) Bottom 1/3 550 HU 1683.51 a 1570.59 a 2055.39 a 450 HU 1585.31 b 1564.06 a 1822.04 b 350 HU 1573.81 b 1429.47 b 1761.94 b 250 HU 1332.11 c 1194.73 c 1385.41 c 150 HU 1010.97 d 823.24 d 1004.77 d ^Means followed by the same letter within each column are not significantly different (P>0.05, ANOVA). 58 flCO O 3 o o u XJ t3 Si, ly >« I X) (U o X) o )-O( (U fe Xjnfui §Uip99^ ;U93J9J bfl fe 59 GO 0) bO cd I O o X3 fl o % o fl o -^ -^ fl o fl CS o x> u 13 fl u o, B u ;-D( CO CO CN bO fe ^UIUI/SUIKJ^ 60 CM o bO cS o X) fl o ti o o cd C+H O o o fl 13 ;-! •fl Si 0) CO CO ;- o fl u C4H XI piU/SUIBJ0 cd XI fe --I 61 a o ct3 cS cd CO o IO > o o •I—( II M Q^ D) 3 C 00 o • ••• c X) •D o00 o fl o •4-o» ^" c ti a> 3 o 4a-> reL. dII o b. -•J Q. a cd 0) fl •4-o * XI 3 0c ) CM bO O Q. E .c o • £ o .1—1 T3 (U )-l E OH xn §-3 .B § •^^- Si^r o O o o o o bO ^ IO CM IO CM fe •^ sejn^ound ^o jeqiunfyj 62 VITA Andy Marshal Cranmer was bom on October 15, 1977 in Hale Center, Texas. His parents are Lee and Linda Cranmer. He has one brother, Kyle Cranmer, and a sister, Emily Cranmer. He was raised on a farm and graduated from Plainview High School in 1996 and then moved to Lubbock to attend Texas Tech University. Mr. Cranmer graduated with a B. S. degree in Integrated Pest Management in 2001 and continued at TTU in pursuit of a Masters of Science in Entomology. He conducted his M.S. thesis research at the Texas Agricultural Experiment Station in Lubbock. While attending TTU from 1996-2001 he worked as an intem and as a demonstration technician for the Lubbock County IPM Agent and the Texas Cooperative Extension. He was awarded the West Texas Agricultural Chemicals Institute Scholarship, and was a member ofthe TTU Plant and Soil Sciences Graduate Advisory Committee from 2002-2004. Upon the completion of his M.S. program at Texas Tech University, he and his wife, Leigh, will reside in Seminole where he is the Extension Agent - Integrated Pest Management for Gaines County, Texas. 63 REFERENCES Almand, L.K., W.L. Sterling, and CL. Green. 1976. Seasonal abundance and dispersal of the cotton fleahopper as related to host plant phenology. TX Agric. Exper. Stn. Bull. 1170.15 pp. Anonymous. 1969. Lygus bugs on cotton, how to confrol them. U.S. Dep. Agric. Leafl. 503. 8 pp. Anonymous. 2002. Cotton pest loss data base. In Proc. Beltwide Cotton Conferences, National Cotton Council. Memphis, TN. Bariola, L. A. 1969. The biology ofthe tamished plant bug, Lygus lineolaris (Palisot de Beauvois), and its nature of damage and control on cotton. Ph.D. Dissertation, Texas A&M Univ. 102 pp. Barlow, V. M., L. D. Godfrey, and R. F. Norris. 1999. Population dynamics of Lygus hesperus (Heteroptera: Miridae) on selected weeds in comparison with alfalfa. J. Econ. Entomol. 92: 846-852. Benedict, J. H., T. F. Leigh, and A. H. Hyer. 1983. Lygus hesperus (Heteroptera: Miridae) oviposition behavior, growth, and survival in relation to cotton trichome density. Envfron Entomol. 12: 331-335. Benedict, J. H., and W. R. Cothran. 1975. A faunistic survey of Hemiptera-Heteroptera foxmd in Northem Califomia hay alfalfa. Ann. Entomol. Soc. Amer. 68: 897-900. Burris, E., J. H. Pankey, B. R. Leonard, and J. B. Graves. 1997. Tamished plant bugs, Lygus lineolaris (Palisot de Beauvois), in cotton. Louisiana Agric. Exp. Stn. Report 101. 1-6. Byerly, K. F., A. P. Gutierrez, R. E. Jones, and R. F. Luck. 1978. A comparison of sampling methods for some arthropod populations in cotton. Hilgardia 46: 257-281. Cochran, W. G. 1977. Sampling Techniques. John Wiley & Sons, New York. 427 pp. Cohen, A. C. 1990. 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B. 2000. Biology and damage ofthe tamished plant bug, Lygus lineolaris, in cotton. Southwest. Entomol. Suppl. 23: 7- 20. Layton, M. B. 1999. Cotton insect control guide. Mississippi State Univ. Ext. Serv. Pub 343. Leigh, T. F., T. A. Kerby, and P. F. Wynholds. 1988. Cotton square damage by the plant bug, Lygus hesperus (Hemiptera: Heteroptera: Miridae), and abscission rates. J. Econ. Entomol. 81: 1328-1337. Leigh, T. F., S. H. Roach, and T. F. Watson. 1996. Biology and ecology of important insects and mite pests ofcotton, pp. 17-85. In E. G. King, J. R. Phillips, and R. J. Coleman [eds.]. Cotton insects and mites: Characterization and management. The Cotton Foundation. Memphis, TN. Leser, J. F. 1999. The boll weevil problem on the High Plains of Texas and eastem New Mexico. Proc. Beltwide Cotton Conf. 2: 828-832. Lukefahr, M. J., C. B. Cowan, T. R. Pfiimmer, and L. W. Noble. 1966. Resistance of experimental cotton sfrain 1514 to the bollworm and cotton fleahopper. J. Econ. 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Parasites of Heliothis spp. (Lepidoptera: Noctuidae): parasitism and seasonal occurrence for host crops in the Texas Rolling Plains. Environ. Entomol. 14: 441-446. Race, S. R. 1960. A comparison of two sampling techniques for Lygus bugs and stink bugs on cotton. J. Econ. Entomol. 53: 689-690. Reinhard, H.J. 1926. The cotton fleahopper. TX Agric. Exp. Stn. Bull., 39 pp. Ruberson, J. R., G. A. Herzog, W. R. Lambert, and W. J. Lewis. 1994. Management of the beet armyworm in cotton: role of natural enemies. Fla. Entomol. 77: 440-453. Ruesink, W. G., and M. Kogan. 1975. The quant basis of pest management: Sampling and meaning. In R. L. Metcalf and W. H. Luckman, Infroduction to Insect Pest Management. John Wiley & Sons, New York. 351. 67 Russell, J. S. 1999. Effects of tamished plant bug, Lygus lineolaris (Palisot de Beauvios), feeding on cotton boll abscission and yield. M.S. Thesis, Louisiana State Univ. Dept. of Entomology. 39 pp. SAS Instittite. 2003. SAS user's guide: Statistics. SAS Institute, Gary, NC. Saugastad, E. S., R. A. Bram, and W. E. Nyquist. 1967. Factors influencing sweep-net sampling of alfalfa. J. Econ. Entomol. 60: 421-426. Scales, A. L., and R. E. Furr. 1968. Relationships between the tamished plant bug and deformed cotton plants. J. Econ. Entomol. 61: 114-118. Schotzko, D. J., and L. E. O'Keeffe. 1986. Comparison of sweepnet, D-Vac, and absolute sampling for Lygus hesperus (Heteroptera: Miridae) in lentils. J. Econ. Entomol. 79: 224-228. Schuster, M. F., and J. L. Frazier. 1976. Mechanisms of resistance to Lygus spp. in Gossypium hirsutum L., pp. 129-135. In EUCARPIA/OILB Host Plant Resistance Proc. Wageningen, The Netherlands. Scott, D. R. 1977. An annotated listing of host plants of Lygus hesperus Knight. Bull. Entomol. Soc. Am. 23: 19-22. Scott, W. P., J. W. Smith, and G. L. Snodgrass. 1986. Impact of early season use of selected insecticides on cotton arthropod populations and yield. J. Econ. Entomol. 79: 797-804. Sevacherian, V., and V. M. Stem. 1975. Movement of Lygus bugs between alfalfa and cotton. Environ. Entomol. 4: 163-165. Shepard, M., G. R. Camer, and S. G. Tumipseed. 1974. A comparison of three sampling methods for arthropods in soybeans. Environ. Entomol. 3:227-232. Simonet, D. E., R. L. Pienkowski, D. G. Martinez, and R. D. Blakeslee. 1978. Laboratory and field evaluation of sampling techniques for nymphal stages ofthe potato leafhopper on alfalfa. Environ. Entomol. 71: 840-842. Simonet, D. E., R. L. Pienkowski, D. G. Martinez, and R. D. Blakeslee. 1979. Evaluation of sampling techniques and development of a sampling program for potato leafhopper adults on alfalfa. Environ. Entomol. 8: 397-399. Slosser, J. E. 1993. Influence of planting date and insecticide treatment on insect pest abundance and damage in dryland cotton. J. Econ. Entomol. 86: 1213-1222. 68 Smith, J. W., E. A. Stadelbacher, and C. W. Gautt. 1976. A comparison of techniques for sampling beneficial arthropod populations associated with cotton. Environ. Entomol. 5: 435-444. Smith, J. D., and S. D. Stewart. 1999. Comparison between drop cloth and suction sampling in cotton during 1998. In 1999 Proc. Beltwide Cotton Prod. Res. Conf., National Cotton Council, Memphis, TN. Southwood, T. R. E. 1978. Ecological Methods. Chapman and Hall, New York. Tingey, W. M., T. F. Leigh, and A. B. Hyer. 1973. Three methods for screening cotton for ovipositional nonpreference by Lygus bugs. J. Econ. Entomol. 66: 1312-1314. Tingey, W. M., T. F. Leigh and A. B. Hyer. 1975. Lygus hesperus: Growth, survival, and egg laying resistance ofcotton genotypes. J. Econ. Entomol. 68: 28-30. Tingey, W. M., and E. A. Pillemer. 1977. Lygus bugs: Crop resistance and physiological nature of feeding injury. Bull. Entomol. Soc. Amer. 23: 277-287. Tugwell, P., S. C. Young, Jr., B. A. Dumas, and J. R. Phillips. 1976. Plant bugs in cotton: Importance of infestation time, types ofcotton injury, and significance of wild hosts near cotton. Ark. Agric. Exp. Stn. Report Series 227. 24 pp. Wene, G. P., and L. W. Sheets. 1964. Lygus bug injury to pre-squaring cotton. Ariz. Agric. Exp. Stn. Tech. Bull. 166. 28 pp. Williams, M. R. 1984 to 2003. Cotton insect losses. Armual reports In Proc. Beltwide Cotton Conf., National Cotton Council, Memphis, TN. Wilson, L. T., T. F. Leigh, D. Gonzalez and C. Foristiere. 1984. Disfribution of Lygus hesperus Knight (Hemiptera: Miridae) on cotton. J. Econ. Entomol. 77: 1313-1319. Wilson, L. T., and A. P. Gutierrez. 1980. Within-plant disfribution of predators on cotton: Comments on sampling and predator efficiencies. Hilgardia 48: 3-11. Young, S. C, and P. Tugwell. 1975. Different methods of sampling for clouded and tamished plant bugs in Arkansas cotton fields. Ark. Agric. Exp. Stn. Rep. 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