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Management Options and Soil Types Differentially Affect Weeds in Maize Fields of Kakamega, Western Kenya

Journal of Agricultural Science and Technology(A) 2012年第1期2卷 104-114页

作者： Ajebesone Francis Ngome Kelvin Mtei Mtei Frank Mussgnug mathias becker Annual Crops Department Institute of Agricultural Research for Development （IRAD） Yaounde Centre Region B.P. 2123 Yaounde Cameroon Department of Plant Nutrition Institute of Crop Science and Resource Conservation （INRES） University of Bonn Bonn NRW Karlrobert Kreiten Strasse 13 Bonn 53115 Germany Cropping systems Department AfricaRice Africa Rice Centre Cotonou O1 B.P. 2031 Cotonou Benin

Maize production in Kenya is constrained by weed infestation and nutrient deficiencies. Field studies were conducted during the 2008/2009 cropping seasons to investigate weeds in maize fields on three dominant soil types in Western Kenya. Weeds were inventoried and their composition was compared using Jaccard"s index. The economic importance of weed species (potential to reduce yields and the difficulty to control them by manual weeding) was assessed through participatory surveys. Finally, field trials assessed the effects of management options (farmer"s practice, clean weeding, green manure, zero-tillage + cover crop and zero-tillage) on weed biomass and species composition. Across the three soil types, 55 weed species in 21 families were identified. Soil types influenced species composition as confirmed by Jaccard"s similarity indices of 0.50, 0.58 and 0.62 for Nitisol vs. Acrisol, Ferralsol vs. Acrisol and Nitisol vs. Ferralsol, respectively. The economically important weeds were Commelina benghalensis, Cynodon nlemfuensis, Bidens pilosa, Galinsoga parviflora and Leonotis nepetifolia. Management options significantly (P < 0.05) reduced weed biomass, irrespective of soil type and seasons. Maize biomass response was highest (7-16 Mg ha-1) in zero-tillage and zero-tillage + cover crop and lowest (2-8 Mg ha-1) in farmer"s practice. Significantly negative relationships (P < 0.01, r2 = 0.37 - 0.51) were established between leaf area index of maize and weed biomass across the soils. Zero-tillage combined with the use of a cover crop had the lowest weed biomass (< 30% of the farmer practice) and thus appears to be a promising strategy combining soil fertility improvement with weed suppression in smallholder maize farming systems of Western Kenya.

关键词：玉米田杂草土壤类型肯尼亚选项管理西部覆盖作物玉米产量

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Seasonal Vegetation Changes in the Malinda Wetland Using Bi-Temporal, Multi-Sensor, Very High Resolution Remote Sensing Data Sets

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Advances in Remote Sensing 2014年第1期3卷 33-48页

作者： David N. Kuria Gunter Menz Salome Misana Emiliana Mwita Hans-Peter Thamm Miguel Alvarez Neema Mogha mathias becker Helida Oyieke Department of Geography Dar es Salaam University College of Technology Dar es Salaam Tanzania Department of Geography Free University Berlin Malteserstr Germany Department of Geography University of Bonn Meckenheimer Allee Bonn Germany Department of Geography University of Dar es Salaam Dar es Salaam Tanzania Institute of Crop Science and Resource Conservation University of Bonn Katzenburgweg Germany Institute of Geomatics GIS & Remote Sensing Dedan Kimathi University of Technology Nyeri Kenya National Museums of Kenya Nairobi Kenya

Small wetlands in East Africa have grown in prominence driven by the unreliable and diminished rains and the increasing population pressure. Due to their size (less than 500 Ha), these wetlands have not been studied extensively using satellite remote sensing approaches. High spatial resolution remote sensing approaches overcome this limitation allowing detailed inventorying and research on such small wetlands. For understanding the seasonal variations in land cover within the Malinda Wetland in Tanzania (350 Ha), two periods were considered, May 2012 coinciding with the wet period (rainy season) and August 2012 coinciding with a fairly rain depressed period (substantially dry but generally cooler season). The wetland was studied using very high spatial resolution orthophotos derived from Unmanned Aerial Vehicle (UAV) photography fused with TerraSAR-X Spotlight mode dual polarized radar data. Using these fused datasets, five main classes were identified that were used to firstly delineate seasonal changes in land use activities and secondly used in determining phenology changes. Combining fuzzy maximum likelihood classification, knowledge classifier and Change Vector Analysis (CVA), land cover classification was undertaken for both seasons. From the results, manifold anthropogenic activities are taking place between the seasons as evidenced by the high conversion rates (63.01 Ha). The phenological change was also highest within the human influence class due to the growing process of cropped land (26.60 Ha). Much of the changes in both cover and phenology are occurring in the mid upper portion of the wetland, attributed to the presence of springs in this portion of the wetland along the banks of River Mkomazi. There is thus seasonality in the observed anthropogenic influence between the wetland and its periphery.

关键词： Image Fusion Land Cover Classification Unmanned Aerial Vehicle Change Vector Analysis Land Cover Change Vegetation Phenology

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沥青储罐系统的分布式自动化

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现代制造 2015年第47期 78-79页

作者： mathias Stracke WAGO

Westhydraulik-becker的沥青储罐用于为沥青搅拌设备供应沥青，其中应用的自动化组件充分体现了自身的多功能与高性能。

关键词：自动化组件沥青储罐分布式系统设备供应多功能

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