Geographic Variation in Sexual Attraction of Spodoptera frugiperda Corn- and Rice-Strain Males to Pheromone Lures

The corn- and rice-strains of Spodoptera frugiperda exhibit several genetic and behavioral differences and appear to be undergoing ecological speciation in sympatry. Previous studies reported conflicting results when investigating male attraction to pheromone lures in different regions, but this could have been due to inter-strain and/or geographic differences. Therefore, we investigated whether corn- and rice-strain males differed in their response to different synthetic pheromone blends in different regions in North America, the Caribbean and South America. All trapped males were strain typed by two strain-specific mitochondrial DNA markers. In the first experiment, we found a nearly similar response of corn and rice-strain males to two different 4-component blends, resembling the corn- and rice-strain female blend we previously described from females in Florida. This response showed some geographic variation in fields in Canada, North Carolina, Florida, Puerto Rico, and South America (Peru, Argentina). In dose-response experiments with the critical secondary sex pheromone component (Z)-7-dodecenyl acetate (Z7-12:OAc), we found some strain-specific differences in male attraction. While the response to Z7-12:OAc varied geographically in the corn-strain, rice-strain males showed almost no variation. We also found that the minor compound (Z)-11-hexadecenyl acetate (Z11-16:OAc) did not increase attraction of both strains in Florida and of corn-strain males in Peru. In a fourth experiment, where we added the stereo-isomer of the critical sex pheromone component, (E)-7-dodecenyl acetate, to the major pheromone component (Z)-9-tetradecenyl acetate (Z9-14:OAc), we found that this compound was attractive to males in North Carolina, but not to males in Peru. Overall, our results suggest that both strains show rather geographic than strain-specific differences in their response to pheromone lures, and that regional sexual communication differences might cause geographic differentiation between populations.Fil: Unbehend, Melanie. Instituto Max Planck Institut Fur Chemische Okologie; AlemaniaFil: Hänniger, Sabine. Instituto Max Planck Institut Fur Chemische Okologie; AlemaniaFil: Vasquez, Gissella M.. University Of North Carolina; Estados UnidosFil: Juárez, María Laura. Gobierno de Tucumán. Ministerio de Desarrollo Productivo. Estación Experimental Agroindustrial Obispo Colombres; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Tucumán; ArgentinaFil: Reisig, Dominic. University Of North Carolina; Estados UnidosFil: Mcneil, Jeremy N.. University of Western Ontario. Department of Biology; CanadáFil: Meagher, Robert L.. United States Department Of Agriculture; Estados UnidosFil: Jenkins, David A.. United States Department of Agriculture; ArgentinaFil: Heckel, David G.. Instituto Max Planck Institut Fur Chemische Okologie; AlemaniaFil: Groot, Astrid T.. University Of Amsterdam; Países Bajos. Instituto Max Planck Institut Fur Chemische Okologie; Alemani

Examples of Risk Tools for Pests in Peanut (Arachis hypogaea) Developed for Five Countries Using Microsoft Excel

Suppressing pest populations below economically-damaging levels is an important element of sustainable peanut (Arachis hypogaea L.) production. Peanut farmers and their advisors often approach pest management with similar goals regardless of where they are located. Anticipating pest outbreaks using field history and monitoring pest populations are fundamental to protecting yield and financial investment. Microsoft Excel was used to develop individual risk indices for pests, a composite assessment of risk, and costs of risk mitigation practices for peanut in Argentina, Ghana, India, Malawi, and North Carolina (NC) in the United States (US). Depending on pests and resources available to manage pests, risk tools vary considerably, especially in the context of other crops that are grown in sequence with peanut, cultivars, and chemical inputs. In Argentina, India, and the US where more tools (e.g., mechanization and pesticides) are available, risk indices for a wide array of economically important pests were developed with the assumption that reducing risk to those pests likely will impact peanut yield in a positive manner. In Ghana and Malawi where fewer management tools are available, risks to yield and aflatoxin contamination are presented without risk indices for individual pests. The Microsoft Excel platform can be updated as new and additional information on effectiveness of management practices becomes apparent. Tools can be developed using this platform that are appropriate for their geography, environment, cropping systems, and pest complexes and management inputs that are available. In this article we present examples for the risk tool for each country.Instituto de Patología VegetalFil: Jordan, David L. North Carolina State University. Department of Crop and Soil Sciences; Estados UnidosFil: Buol, Greg S. North Carolina State University. Department of Crop and Soil Sciences; Estados UnidosFil: Brandenburg, Rick L. North Carolina State University. Department of Entomology and Plant Pathology; Estados UnidosFil: Reisig, Dominic. North Carolina State University. Department of Entomology and Plant Pathology; Estados UnidosFil: Nboyine, Jerry. Council for Scientific and Industrial Research. Savanna Agricultural Research Institute; GhanaFil: Abudulai, Mumuni. Council for Scientific and Industrial Research. Savanna Agricultural Research Institute; GhanaFil: Oteng-Frimpong, Richard.Council for Scientific and Industrial Research. Savanna Agricultural Research Institute; GhanaFil: Brandford Mochiah, Moses.Council for Scientific and Industrial Research. Crops Research Institute; GhanaFil: Asibuo, James Y. Council for Scientific and Industrial Research. Crops Research Institute; GhanaFil: Arthur, Stephen. Council for Scientific and Industrial Research. Crops Research Institute; GhanaFil: Paredes, Juan Andrés. Consejo Nacional de Investigaciones Científicas y Técnicas. Unidad de Fitopatología y Modelización Agrícola (UFyMA); ArgentinaFil: Paredes, Juan Andrés. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Patología Vegetal; ArgentinaFil: Monguillot, Joaquín Humberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Unidad de Fitopatología y Modelización Agrícola (UFyMA); ArgentinaFil: Monguillot, Joaquín Humberto. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Patología Vegetal; ArgentinaFil: Rhoads, James. University of Georgia. Feed the Future Innovation Lab for Peanut; Estados Unido

Whole genome comparisons reveal panmixia among fall armyworm (Spodoptera frugiperda) from diverse locations

Background: The fall armyworm (Spodoptera frugiperda (J.E. Smith)) is a highly polyphagous agricultural pest with long-distance migratory behavior threatening food security worldwide. This pest has a host range of > 80 plant species, but two host strains are recognized based on their association with corn (C-strain) or rice and smaller grasses (R-strain). The population genomics of the United States (USA) fall armyworm remains poorly characterized to date despite its agricultural threat. Results: In this study, the population structure and genetic diversity in 55 S. frugiperda samples from Argentina, Brazil, Kenya, Puerto Rico and USA were surveyed to further our understanding of whole genome nuclear diversity. Comparisons at the genomic level suggest a panmictic S. frugiperda population, with only a minor reduction in gene flow between the two overwintering populations in the continental USA, also corresponding to distinct host strains at the mitochondrial level. Two maternal lines were detected from analysis of mitochondrial genomes. We found members from the Eastern Hemisphere interspersed within both continental USA overwintering subpopulations, suggesting multiple individuals were likely introduced to Africa. Conclusions: Our research is the largest diverse collection of United States S. frugiperda whole genome sequences characterized to date, covering eight continental states and a USA territory (Puerto Rico). The genomic resources presented provide foundational information to understand gene flow at the whole genome level among S. frugiperda populations. Based on the genomic similarities found between host strains and laboratory vs. field samples, our findings validate the experimental use of laboratory strains and the host strain differentiation based on mitochondria and sex-linked genetic markers extends to minor genome wide differences with some exceptions showing mixture between host strains is likely occurring in field populations.Fil: Schlum, Katrina A.. University of Tennessee; Estados UnidosFil: Lamour, Kurt. University of Tennessee; Estados UnidosFil: Placidi de Bortoli, Caroline. University of Tennessee; Estados UnidosFil: Banerjee, Rahul. University of Tennessee; Estados UnidosFil: Meagher, Robert. United States Department Of Agriculture. Center For Medical Agric And Vet Entomology; Estados UnidosFil: Pereira, Eliseu. Universidade Federal de Viçosa; BrasilFil: Murúa, María Gabriela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto de Tecnología Agroindustrial del Noroeste Argentino. Provincia de Tucumán. Ministerio de Desarrollo Productivo. Estación Experimental Agroindustrial "Obispo Colombres" (p). Instituto de Tecnología Agroindustrial del Noroeste Argentino; ArgentinaFil: Sword, Gregory A.. Texas A&M University; Estados UnidosFil: Tessnow, Ashley E.. Texas A&M University; Estados UnidosFil: Viteri Dillon, Diego. Universidad de Puerto Rico; Puerto RicoFil: Linares Ramirez, Angela M.. Universidad de Puerto Rico; Puerto RicoFil: Akutse, Komivi S.. International Centre Of Insect Physiology And Ecology; KeniaFil: Schmidt Jeffris, Rebecca. United States Department Of Agriculture. Center For Medical Agric And Vet Entomology; Estados UnidosFil: Huang, Fangneng. State University of Louisiana; Estados UnidosFil: Reisig, Dominic. North Carolina State University; Estados UnidosFil: Emrich, Scott J.. University of Tennessee; Estados UnidosFil: Jurat Fuentes, Juan Luis. University of Tennessee; Estados Unido

Neonicotinoid seed treatments of soybean provide negligible benefits to US farmers

Neonicotinoids are the most widely used insecticides worldwide and are typically deployed as seed treatments (hereafter NST) in many grain and oilseed crops, including soybeans. However, there is a surprising dearth of information regarding NST effectiveness in increasing soybean seed yield, and most published data suggest weak, or inconsistent yield benefit. The US is the key soybean-producing nation worldwide and this work includes soybean yield data from 194 randomized and replicated field studies conducted specifically to evaluate the effect of NSTs on soybean seed yield at sites within 14 states from 2006 through 2017. Here we show that across the principal soybean-growing region of the country, there are negligible and management-specific yield benefits attributed to NSTs. Across the entire region, the maximum observed yield benefits due to fungicide (FST = fungicide seed treatment) + neonicotinoid use (FST + NST) reached 0.13 Mg/ha. Across the entire region, combinations of management practices affected the effectiveness of FST + N ST to increase yield but benefits were minimal ranging between 0.01 to 0.22 Mg/ha. Despite widespread use, this practice appears to have little benefit for most of soybean producers; across the entire region, a partial economic analysis further showed inconsistent evidence of a break-even cost of FST or FST + N ST. These results demonstrate that the current widespread prophylactic use of NST in the key soybean-producing areas of the US should be re-evaluated by producers and regulators alike

Examples of risk tools for pests in Peanut (Arachis hypogaea) developed for five countries using Microsoft Excel

Suppressing pest populations below economically-damaging levels is an important element of sustainable peanut (Arachis hypogaea L.) production. Peanut farmers and their advisors often approach pest management with similar goals regardless of where they are located. Anticipating pest outbreaks using field history and monitoring pest populations are fundamental to protecting yield and financial investment. Microsoft Excel was used to develop individual risk indices for pests, a composite assessment of risk, and costs of risk mitigation practices for peanut in Argentina, Ghana, India, Malawi, and North Carolina (NC) in the United States (US). Depending on pests and resources available to manage pests, risk tools vary considerably, especially in the context of other crops that are grown in sequence with peanut, cultivars, and chemical inputs. In Argentina, India, and the US where more tools (e.g., mechanization and pesticides) are available, risk indices for a wide array of economically important pests were developed with the assumption that reducing risk to those pests likely will impact peanut yield in a positive manner. In Ghana and Malawi where fewer management tools are available, risks to yield and aflatoxin contamination are presented without risk indices for individual pests. The Microsoft Excel platform can be updated as new and additional information on effectiveness of management practices becomes apparent. Tools can be developed using this platform that are appropriate for their geography, environment, cropping systems, and pest complexes and management inputs that are available. In this article we present examples for the risk tool for each country.Fil: Jordan, David L.. University of Georgia; Estados Unidos. North Carolina State University; Estados UnidosFil: Buol, Greg S.. North Carolina State University; Estados UnidosFil: Brandenburg, Rick L.. North Carolina State University; Estados UnidosFil: Reisig, Dominic. North Carolina State University; Estados UnidosFil: Nboyine, Jerry. Council for Scientific and Industrial Research Savanna Agricultural Research Institute; GhanaFil: Abudulai, Mumuni. Council for Scientific and Industrial Research Savanna Agricultural Research Institute; GhanaFil: Oteng Frimpong, Richard. Council for Scientific and Industrial Research Savanna Agricultural Research Institute; GhanaFil: Mochiah, Moses Brandford. Council for Scientific and Industrial Research Crops Research Institute; GhanaFil: Asibuo, James Y.. Council for Scientific and Industrial Research Crops Research Institute; GhanaFil: Arthur, Stephen. Council for Scientific and Industrial Research Crops Research Institute; GhanaFil: Akromah, Richard. Kwame Nkrumah University Of Science And Technology; GhanaFil: Mhango, Wezi. Lilongwe University Of Agriculture And Natural Resources; MalauiFil: Chintu, Justus. Chitedze Agricultural Research Service, Lilongwe; MalauiFil: Morichetti, Sergio. Aceitera General Deheza; ArgentinaFil: Paredes, Juan Andres. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigaciones Agropecuarias. Instituto de Patología Vegetal; Argentina. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigaciones Agropecuarias. Unidad de Fitopatología y Modelización Agrícola - Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Unidad de Fitopatología y Modelización Agrícola; ArgentinaFil: Monguillot, Joaquín Humberto. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigaciones Agropecuarias. Instituto de Patología Vegetal; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Singh Jadon, Kuldeep. Central Arid Zone Research Institute, Jodhpur; IndiaFil: Shew, Barbara B.. North Carolina State University; Estados UnidosFil: Jasrotia, Poonam. Indian Institute Of Wheat And Barley Research, Karnal; IndiaFil: Thirumalaisamy, P. P.. India Council of Agricultural Research, National Bureau of Plant Genetic Resources; IndiaFil: Harish, G.. Directorate Of Groundnut Research, Junagadh; IndiaFil: Holajjer, Prasanna. National Bureau Of Plant Genetic Resources, New Delhi; IndiaFil: Maheshala, Nataraja. Directorate Of Groundnut Research, Junagadh; IndiaFil: MacDonald, Greg. University of Florida; Estados UnidosFil: Hoisington, David. University of Georgia; Estados UnidosFil: Rhoads, James. University of Georgia; Estados Unido

Neonicotinoid seed treatments of soybean provide negligible benefits to US farmers

Neonicotinoids are the most widely used insecticides worldwide and are typically deployed as seed treatments (hereafter NST) in many grain and oilseed crops, including soybeans. However, there is a surprising dearth of information regarding NST effectiveness in increasing soybean seed yield, and most published data suggest weak, or inconsistent yield benefit. The US is the key soybean-producing nation worldwide and this work includes soybean yield data from 194 randomized and replicated field studies conducted specifically to evaluate the effect of NSTs on soybean seed yield at sites within 14 states from 2006 through 2017. Here we show that across the principal soybean-growing region of the country, there are negligible and management-specific yield benefits attributed to NSTs. Across the entire region, the maximum observed yield benefits due to fungicide (FST = fungicide seed treatment) + neonicotinoid use (FST + NST) reached 0.13 Mg/ha. Across the entire region, combinations of management practices affected the effectiveness of FST + N ST to increase yield but benefits were minimal ranging between 0.01 to 0.22 Mg/ha. Despite widespread use, this practice appears to have little benefit for most of soybean producers; across the entire region, a partial economic analysis further showed inconsistent evidence of a break-even cost of FST or FST + N ST. These results demonstrate that the current widespread prophylactic use of NST in the key soybean-producing areas of the US should be re-evaluated by producers and regulators alike

Extended Sentinel Monitoring of Helicoverpa zea Resistance to Cry and Vip3Aa Toxins in Bt Sweet Corn: Assessing Changes in Phenotypic and Allele Frequencies of Resistance

Transgenic corn and cotton that produce Cry and Vip3Aa toxins derived from Bacillus thuringiensis (Bt) are widely planted in the United States to control lepidopteran pests. The sustainability of these Bt crops is threatened because the corn earworm/bollworm, Helicoverpa zea (Boddie), is evolving a resistance to these toxins. Using Bt sweet corn as a sentinel plant to monitor the evolution of resistance, collaborators established 146 trials in twenty-five states and five Canadian provinces during 2020–2022. The study evaluated overall changes in the phenotypic frequency of resistance (the ratio of larval densities in Bt ears relative to densities in non-Bt ears) in H. zea populations and the range of resistance allele frequencies for Cry1Ab and Vip3Aa. The results revealed a widespread resistance to Cry1Ab, Cry2Ab2, and Cry1A.105 Cry toxins, with higher numbers of larvae surviving in Bt ears than in non-Bt ears at many trial locations. Depending on assumptions about the inheritance of resistance, allele frequencies for Cry1Ab ranged from 0.465 (dominant resistance) to 0.995 (recessive resistance). Although Vip3Aa provided high control efficacy against H. zea, the results show a notable increase in ear damage and a number of surviving older larvae, particularly at southern locations. Assuming recessive resistance, the estimated resistance allele frequencies for Vip3Aa ranged from 0.115 in the Gulf states to 0.032 at more northern locations. These findings indicate that better resistance management practices are urgently needed to sustain efficacy the of corn and cotton that produce Vip3Aa

Pest population dynamics are related to a continental overwintering gradient

Overwintering success is an important determinant of arthropod populations that must be considered as climate change continues to influence the spatiotemporal population dynamics of agricultural pests. Using a long-term monitoring database and biologically relevant overwintering zones, we modeled the annual and seasonal population dynamics of a common pest, Helicoverpa zea (Boddie), based on three overwintering suitability zones throughout North America using four decades of soil temperatures: the southern range (able to persist through winter), transitional zone (uncertain overwintering survivorship), and northern limits (unable to survive winter). Our model indicates H. zea population dynamics are hierarchically structured with continental-level effects that are partitioned into three geographic zones. Seasonal populations were initially detected in the southern range, where they experienced multiple large population peaks. All three zones experienced a final peak between late July (southern range) and mid-August to mid-September (transitional zone and northern limits). The southern range expanded by 3% since 1981 and is projected to increase by twofold by 2099 but the areas of other zones are expected to decrease in the future. These changes suggest larger populations may persist at higher latitudes in the future due to reduced low-temperature lethal events during winter. Because H. zea is a highly migratory pest, predicting when populations accumulate in one region can inform synchronous or lagged population development in other regions. We show the value of combining long-term datasets, remotely sensed data, and laboratory findings to inform forecasting of insect pests

IPM of thrips in timothy and a density-independent effect on wing diphenism of grass thrips (Anaphothrips obscurus Müller)

Timothy (Phleum pratense L.) is an important cool season forage crop in Western states, primarily purchased on aesthetic appearance. Thrips (Anaphothrips obscurus Müller) have been implicated in quality reduction of this forage, but integrated pest management (IPM) is minimal. This dissertation addressed several IPM tenets: reliance on sampling, thresholds, alternative management tactics, and an ecological understanding of the system. Several sampling methods were compared for statistical consistency across time of day and season in Chapter 1. Rapping timothy tillers inside a plastic cup was the most consistent and fastest sampling method. Thrips densities were higher in the upper portion of the plant. Macropterous phenotypes were produced in late spring and throughout the summer; they dispersed as the summer progressed. In Chapter 2, differential thrips populations were created with disruptive insecticides. Thrips reduced hay quality and economic thresholds were established. Tetranychid mite populations were flared when cyfluthrin was used, but populations were not always present. Both thrips and mites affected yield, but quality degradation was a more consistent and common problem in these studies. Spring burning was investigated as an alternative physical management tactic in Chapter 3. Burning reduced populations in the short-term, although long-term management potential is questionable. In Chapter 4, the importance of density-independent effects on wing diphenism was tested by enclosing populations of thrips on timothy without and with nitrogen. Six weeks after fertilization, nitrogen had a direct effect on wing diphenism and a higher proportion of macropterous thrips were produced. This result was also obtained eight weeks after fertilization, but at this point in the study the differences in diphenism could have resulted from either a direct effect of nitrogen or an indirect effect of nitrogen, because there were more conspecifics in the nitrogen-treated timothy. Finally, the appendices detail a study on the precision of two sampling methods, a study on the effect of cyfluthrin calendar sprays on thrips, and several pilot growth chamber studies which investigated the effect of maternal wing diphenism, conspecific density, and nitrogen on offspring wing diphenism

How can policymakers and researchers develop effective insect resistance management guidelines? A quantitative and qualitative study of Brazilian farmers' perspectives and attitudes

Societal Impact Statement Today, over 80% of the US and Brazil row crop acreage has plants expressing insecticidal proteins to prevent the damage caused by caterpillars. These plants (crops expressing Bacillus thuringiensis, Bt, toxins) have brought several benefits to farmers, the environment, and society. However, these can be eroded when insects develop resistance to these toxins. Researchers and regulatory agencies have developed tactics that should be followed by farmers to avoid resistance but with limited efficacy. Our research provides recommendations for researchers and policymakers that are based on farmers' perspectives, thereby offering changes for current guidelines to successfully manage insect resistance and protect Bt crops' efficacy. Summary Genetically engineered crops expressing insecticidal proteins produced by Bacillus thuringiensis (Bt) have brought numerous benefits; however, pest resistance evolution poses a threat to the sustainability of this technology. Insect resistance management (IRM) for Bt crops has been defined as a wicked problem as it involves sociobiological complexities. A main challenge in IRM is the adoption of non‐Bt refuge, which is one out of the few strategies amenable to human intervention. This study investigated farmers' perspectives on information sources and IRM practices in Brazil using quantitative and qualitative data collection. A total of 145 farmers responded to online Qualtrics surveys, and 13 farmers participated in person to open‐ended interviews. This study demonstrates that farmers rely on strong social networks for information exchange and that sources with expertise based on local field experience are the most reliable channels of communication. We identified new challenges for refuge adoption such as the need to spray insecticides for pests not targeted by Bt and the intangible aspect of resistance evolution. Based on results of sources of information and perspectives on IRM practices, we discuss strategies that may be successful in delaying insecticide resistance evolution based on local contexts. This is the first study to investigate Brazilian farmers' perceptions on information sources and IRM strategies using qualitative data. Our results provide important elements to orient research development and decision‐making in biotechnology policies for the agricultural sector in Brazil and other similar contexts