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

• Autores: Jordan, David L.; Buol, Greg S.; Brandenburg, Rick L.; Reisig, Dominic; Nboyine, Jerry; Abudulai, Mumuni; Oteng Frimpong, Richard; Mochiah, Moses Brandford; Asibuo, James Y.; Arthur, Stephen; Akromah, Richard; Mhango, Wezi; Chintu, Justus; Morichetti, Sergio; Paredes, Juan Andres; Monguillot, Joaquín Humberto; Singh Jadon, Kuldeep; Shew, Barbara B.; Jasrotia, Poonam; Thirumalaisamy, P. P.; Harish, G.; Holajjer, Prasanna; Maheshala, Nataraja; MacDonald, Greg; Hoisington, David; Rhoads, James
• Año de publicación: 2022
• Idioma: inglés
• Tipo de recurso: artículo
• Materia: AGRONOMY; CROP ROTATION; CULTIVAR RESISTANCE; DECISION TOOL; IPM-AGRICULTURE; PESTICIDE
• Institución: Consejo Nacional de Investigaciones Científicas y Técnicas

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 Unidos
Fil: Buol, Greg S.. North Carolina State University; Estados Unidos
Fil: Brandenburg, Rick L.. North Carolina State University; Estados Unidos
Fil: Reisig, Dominic. North Carolina State University; Estados Unidos
Fil: Nboyine, Jerry. Council for Scientific and Industrial Research Savanna Agricultural Research Institute; Ghana
Fil: Abudulai, Mumuni. Council for Scientific and Industrial Research Savanna Agricultural Research Institute; Ghana
Fil: Oteng Frimpong, Richard. Council for Scientific and Industrial Research Savanna Agricultural Research Institute; Ghana
Fil: Mochiah, Moses Brandford. Council for Scientific and Industrial Research Crops Research Institute; Ghana
Fil: Asibuo, James Y.. Council for Scientific and Industrial Research Crops Research Institute; Ghana
Fil: Arthur, Stephen. Council for Scientific and Industrial Research Crops Research Institute; Ghana
Fil: Akromah, Richard. Kwame Nkrumah University Of Science And Technology; Ghana
Fil: Mhango, Wezi. Lilongwe University Of Agriculture And Natural Resources; Malaui
Fil: Chintu, Justus. Chitedze Agricultural Research Service, Lilongwe; Malaui
Fil: Morichetti, Sergio. Aceitera General Deheza; Argentina
Fil: 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; Argentina
Fil: Monguillot, Joaquín Humberto. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigaciones Agropecuarias. Instituto de Patología Vegetal; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Singh Jadon, Kuldeep. Central Arid Zone Research Institute, Jodhpur; India
Fil: Shew, Barbara B.. North Carolina State University; Estados Unidos
Fil: Jasrotia, Poonam. Indian Institute Of Wheat And Barley Research, Karnal; India
Fil: Thirumalaisamy, P. P.. India Council of Agricultural Research, National Bureau of Plant Genetic Resources; India
Fil: Harish, G.. Directorate Of Groundnut Research, Junagadh; India
Fil: Holajjer, Prasanna. National Bureau Of Plant Genetic Resources, New Delhi; India
Fil: Maheshala, Nataraja. Directorate Of Groundnut Research, Junagadh; India
Fil: MacDonald, Greg. University of Florida; Estados Unidos
Fil: Hoisington, David. University of Georgia; Estados Unidos
Fil: Rhoads, James. University of Georgia; Estados Unidos