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Weeds and diseases can reduce peanut (Arachis hypogaea L.) yield or increase cost of production to maintain acceptable yield. While herbicides and fungicides have limited availability in many areas of Ghana and currently are too expensive for resource-poor farmers, control by these pesticides can have a major positive impact on peanut yield. Field experiments were conducted during the rainy seasons of 2009 and 2010 in northern Ghana to determine the effects of herbicide and hand weeding in combination with fungicides on pest management and peanut yield. Peanut pod yield was often more highly correlated with disease severity and canopy defoliation resulting from early leaf spot (caused by Cercospora arachidicola Hori) and late leaf spot (caused by Cercosporidium personatum (Berk. & M.A. Curtis) Deighton) than weed biomass. In some instances, less disease and canopy defoliation were observed when weeds were not controlled effectively compared with increased weed management through hand weeding or herbicide. Two hand weedings or applying pendimethalin preemergence with one hand weeding in combination with 4 applications of triadimefon and chlorothalonil resulted in the lowest weed density and canopy defoliation and often resulted in the highest peanut yield.  相似文献   
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Bacterial (meningococcal) meningitis is a devastating infectious disease with outbreaks occurring annually during the dry season in locations within the ??Meningitis Belt??, a region in sub-Saharan Africa stretching from Ethiopia to Senegal. Meningococcal meningitis occurs from December to May in the Sahel with large epidemics every 5?C10?years and attack rates of up to 1000 infections per 100,000 people. High temperatures coupled with low humidity may favor the conversion of carriage to disease as the meningococcal bacteria in the nose and throat are better able to cross the mucosal membranes into the blood stream. Similarly, respiratory diseases such as influenza and pneumonia might weaken the immune defenses and add to the mucosa damage. Although the transmission dynamics are poorly understood, outbreaks regularly end with the onset of the rainy season and may begin anew with the following dry season. In this paper, we employ a generalized additive modeling approach to assess the association between number of reported meningitis cases and a set of weather variables (relative humidity, rain, wind, sunshine, maximum and minimum temperature). The association is adjusted for air quality (dust, carbon monoxide), as well as varying degrees of unobserved time-varying confounding processes that co-vary with both the disease incidence and weather. We present the analysis of monthly reported meningitis counts in Navrongo, Ghana, from 1998?C2008.  相似文献   
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