Surveys were completed in Eritrea, Ethiopia, Kenya, Madagascar, Mozambique, Tanzania, Uganda and Zanzibar to assess the lepidopteran stem borer species diversity on wild host plants. A total of 24,674 larvae belonging to 135 species were collected from 75 species of wild host plants belonging to the Poaceae, Cyperaceae and Typhaceae. Amongst them were 44 noctuid species belonging to at least nine genera, 33 crambids, 15 pyralids, 16 Pyraloidea species not yet identified, 25 tortricids and three cossids. The noctuid larvae represented 73.6% of the total number of larvae collected, with 66.3, 3.5 and 3.8% found on Poaceae, Cyperaceae and Typhaceae, respectively. The Crambidae, Pyralidae, Tortricidae and Cossidae represented 19.8, 1.9, 2.5 and 0.1% of the total larvae collected, respectively, with 90.4% of the Crambidae and Pyralidae collected from Poaceae, and 99.7% of the Tortricidae collected from Cyperaceae. The lepidopteran stem borer species diversity in the wild host plants was far more diverse than previously reported.
A considerable challenge in applied agricultural use of reflection-based spectroscopy is that most analytical approaches are quite sensitive to radiometric noise and/or low radiometric repeatability. In this study, hyperspectral imaging data were acquired from individual maize leaves and the main objective was to evaluate a classification system for detection of drought stress levels and spider mite infestation levels across maize hybrids and vertical position of maize leaves. A second objective was to estimate biomass and biofuel potential (heating value) of growing maize plants. Stepwise discriminant analysis was used to identify the five spectral bands (440, 462, 652, 706, and 784 nm) that contributed most to the classification of three levels of drought stress (moderate, subtle, and none) across hybrids, leaf position, and spider mite infestation. Regarding the five selected spectral bands, average reflectance values and standard variogram parameters ("nugget", "sill", and "range" derived from variogram analysis) were examined as indicators of spider mite and/or drought stress. There was consistent significant effect of drought stress on average reflectance values, while only one spectral band responded significantly to spider mite infestations. Different variogram parameters provided reliable indications of spider mite infestation and drought stress. Based on independent validation, variogram parameters could be used to accurately predict spider mite density but were less effective as indicators of drought stress. In addition, variogram parameters were used as explanatory variables to predict biomass and biofuel potential of individual maize plants. The potential of using variogram analysis as part of hyperspectral imaging analysis is discussed.
Many food products are subjected to quality control analyses for detection of surface residue/contaminants, and there is a trend of requiring more and more documentation and reporting by farmers regarding their use of pesticides. Recent outbreaks of food borne illnesses have been a major contributor to this trend. With a growing need for food safety measures and -smart applications‖ of insecticides, it is important to develop methods for rapid and accurate assessments of surface residues on food and feed items. As a model system, we investigated detection of a miticide applied to maize leaves and its miticidal bioactivity over time, and we compared two types of reflectance data: fourier transformed infrared (FTIR) data and hyperspectral imaging (HI) data. The miticide (bifenazate) was applied at a commercial field rate to maize leaves in the field, with or without application of a surfactant, and with or without application of a simulated -rain event‖. In addition, we collected FTIR and HI from untreated control leaves (total of five treatments). Maize leaf data were collected at seven time intervals from 0 to 48 hours after application. FTIR data were analyzed using conventional analysis of variance of miticide-specific vibration peaks. Two unique FTIR vibration peaks were associated with miticide application (1,700 cm −1 and 763 cm −1 ). The integrated intensities of these two OPEN ACCESSRemote Sensing 2010, 2 909 peaks, miticide application, surfactant, rain event, time between miticide application, and rain event were used as explanatory variables in a linear multi-regression fit to spider mite mortality. The same linear multi-regression approach was applied to variogram parameters derived from HI data in five selected spectral bands (664, 683, 706, 740, and 747 nm). For each spectral band, we conducted a spatial structure analysis, and the three standard variogram parameters (-sill‖, -range‖, and -nugget‖) were examined as possible -indicators‖ of miticide bioactivity. We demonstrated that both FTIR peaks and standard variogram parameters could be used to accurately predict spider mite mortality, but linear multi-regression fits based on standard variogram parameters had the highest accuracy and were successfully validated with independent data. Based on experimental manipulation of HI data, the use of spatial structure analysis in classification of HI data was discussed.
The potato leafhopper, Empoasca fabae (Harris), is a circular migratory pest of many crops in the United States that overwinters in the southern states. Northward migrant population arrival to the northern states occurs earlier in the north central states compared with northeastern states. Migrant leafhopper arrival to the north varies from year to year depending on factors influencing the development of spring migrants in the overwintering areas and on timing of weather systems capable of transporting the migrants northward. An estimate of the potato leafhopper minimum temperature survival, the geographic limits of the potato leafhopper overwintering range, leafhopper spring development in the overwintering areas, and the identification of the spring migration initiation northwards can help to predict the leafhopper arrival time in the northern states. In the current study, geographic information system (GIS) was used to estimate the potato leafhopper minimum temperature survival and premigrant development. The minimum winter temperature was estimated by overlaying minimum temperature isolines with potato leafhopper collection data taken during the winter, The geographic limits of the overwintering range were estimated using the minimum temperature survival to create a condition-based model by using ArcMap-GIS 8.2. The estimated overwintering range was larger and covered areas further north than previously estimated and included Missouri, Kansas, Kentucky, Virginia, and Maryland. The use of degree-day accumulation to estimate days of first adult emergence in the overwintering areas resulted in earliest adult emergence in the south central region. First adult emergence in south central and southeastern areas occurred before the detection of potato leafhoppers in the north central United States. These data suggested that the difference in population arrival between the north central states and the northeastern states was more dependent on factors affecting the migration and weather conditions encountered along the migration pathway.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.