63 research outputs found

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

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    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

    Performance of aquatic plant species for phytoremediation of arsenic-contaminated water

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    This study investigates the effectiveness of aquatic macrophyte and microphyte for phytoremediation of water bodies contaminated with high arsenic concentration. Water hyacinth (Eichhornia crassipes) and two algae (Chlorodesmis sp. and Cladophora sp.) found near arsenic-enriched water bodies were used to determine their tolerance toward arsenic and their effectiveness to uptake arsenic thereby reducing organic pollution in arsenic-enriched wastewater of different concentrations. Parameters like pH, chemical oxygen demand (COD), and arsenic concentration were monitored. The pH of wastewater during the course of phytoremediation remained constant in the range of 7.3–8.4, whereas COD reduced by 50–65 % in a period of 15 days. Cladophora sp. was found to survive up to an arsenic concentration of 6 mg/L, whereas water hyacinth and Chlorodesmis sp. could survive up to arsenic concentrations of 2 and 4 mg/L, respectively. It was also found that during a retention period of 10 days under ambient temperature conditions, Cladophora sp. could bring down arsenic concentration from 6 to <0.1 mg/L, Chlorodesmis sp. was able to reduce arsenic by 40−50 %; whereas, water hyacinth could reduce arsenic by only 20 %. Cladophora sp. is thus suitable for co-treatment of sewage and arsenic-enriched brine in an algal pond having a retention time of 10 days. The identified plant species provides a simple and cost-effective method for application in rural areas affected with arsenic problem. The treated water can be used for irrigation

    A knowledge-driven GIS modeling technique for groundwater potential mapping at the Upper Langat Basin, Malaysia.

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    The aim of this paper is to use a knowledge-driven expert-based geographical information system (GIS) model coupling with remote-sensing-derived parameters for groundwater potential mapping in an area of the Upper Langat Basin, Malaysia. In this study, nine groundwater storage controlling parameters that affect groundwater occurrences are derived from remotely sensed imagery, available maps, and associated databases. Those parameters are: lithology, slope, lineament, land use, soil, rainfall, drainage density, elevation, and geomorphology. Then the parameter layers were integrated and modeled using a knowledge-driven GIS of weighted linear combination. The weightage and score for each parameter and their classes are based on the Malaysian groundwater expert opinion survey. The predicted groundwater potential map was classified into four distinct zones based on the classification scheme designed by Department of Minerals and Geoscience Malaysia (JMG). The results showed that about 17% of the study area falls under low-potential zone, with 66% on moderate-potential zone, 15% with high-potential zone, and only 0.45% falls under very-high-potential zone. The results obtained in this study were validated with the groundwater borehole wells data compiled by the JMG and showed 76% of prediction accuracy. In addition statistical analysis indicated that hard rock dominant of the study area is controlled by secondary porosity such as distance from lineament and density of lineament. There are high correlations between area percentage of predicted groundwater potential zones and groundwater well yield. Results obtained from this study can be useful for future planning of groundwater exploration, planning and development by related agencies in Malaysia which provide a rapid method and reduce cost as well as less time consuming. The results may be also transferable to other areas of similar hydrological characteristics

    Bruchid - A Major Stoarage Pest of Groundnut-Gujarati

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    Bruchid - A Major Stoarage Pest of Groundnut-Hindi

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    Not AvailablePost-Green Revolution period, wheat (Triticum aestivum) is still the most grown staple food grain crop in the world, after rice. Worldwide, it is grown in a range of different environments over an area of 221.6 million hectares (M ha) with an annual production likely to reach more than 750.4 million metric tons in 2016-17 (Foreign Agricultural Service, USDA, 2018). Despite of this significant growth, the world population in some parts is still facing hunger crisis due to insufficient availability of food grains. To meet the future food demands imposed by overwhelming increasing population which is expected to reach nine billions in 2050, the world wheat production must continue to increase by two per cent annually. This challenge of increasing wheat production is daunting as the wheat cropping system at present is constrained by climatic fluctuations, poor soil health and has increased risk of epidemic outbreak of diseases and insect-pests. To address these challenges, innovative technologies with a potential of increasing the sustainability of the present day cropping systems are required to be introduced in modern agriculture. Among these technological advancements, nanotechnology is gathering significant contemplations due to its wide spectrum applications in agriculture and allied sectors and is recognized as the sixth most revolutionary technology in the modern era. It has a wider application in the field of crop production, food security, sustainability and climate change and is being utilized for developing several precise tool sets like nanofertilizer, nanopesticide, nanoherbicide, nanosensor and smart delivery systems for controlled an sustained release of agrochemicals. Recent research evidences indicated that intervention of nanotechnology in wheat farming is still in its early stages, although have bright prospects for efficient nutrient utilization through nanoformulations of fertilizers, breaching yield barriers through bionanotechnology, surveillance and management of pests and diseases and development of new-generation pesticides etc.Not Availabl

    IPM in Groundnut

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