Proceedings
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| Filter results5 paper(s) found. |
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1. Embedded Sensing System To Control Variable Rate Agricultural InputsThis paper presents an embedded sensing system for agricultural machines to collect information about plants and also to control the application of fertilizer with variable rate in corn crop. The Crop Circle reflectance sensor was used with the aim to explore the spectral... G.T. Tangerino, R.V. Sousa, A.J. Porto, R. . Inamasu, P. Pinkston |
2. Contour Planting: A Strategy To Reduce Soil Erosion On Steep SlopesPractices that combine GPS-based guidance for terrain contouring and tillage for runoff detention have potential to increase water infiltration and reduce runoff. The objective of this study was to investigate contour planting as a means to reduce soil erosion on steep slopes of the Columbia Plateau dryland wheat region. An exploratory field study was conducted on a Ritzville... D.S. Long, S.B. Wuest, J.D. Williams, M.J. Bailey, |
3. Biological Soil Mapping - Infesttion By Plasmodiophora Brassicae And Soil CharacteristicsClubroot, caused by Plasmodiophora brassicae, is a soilborne pathogen that causes severe yield losses in many Brassica crops. It is a increasing problem in many Brassica growing countries. The spores survive for 15-20 years and might cause significant yield losses (>10%), already when 20% of plant are infected. An infestation with a couple of thousands spores/g soil is considered to have the potential to give such significant losses.... C. Aberger, A. Wallenhammar, A. Jonsson |
4. A Digital Twin for Arable Crops and for GrassThere is an opportunity to use process-based cropping systems models (CSMs) to support tactical farm management decisions, by monitoring the status of the farm, by predicting what will happen in the next few weeks, and by exploring scenarios. In practice, the responses of a CSM will deviate more and more from reality as time progresses because the model is an abstraction of the real system and only approximates the responses of the real system. This limitation may be overcome by using the CSM... F. Van evert, P. Van oort, B. Maestrini, A. Pronk, S. Boersma, M. Kopanja, G. Mimić |
5. Decision Support Tools for Developing Aflatoxin Risk Maps in Peanut FieldsAspergillus flavus and Aspergillus parasiticus hereafter referred to jointly as A. flavus, are soil fungi that infect and contaminate preharvest and postharvest peanuts with the carcinogenic secondary metabolite aflatoxin. A. flavus can cause extensive economic losses to peanut growers and shellers by contaminating peanut kernels with aflatoxins. In the southeastern U.S., contamination from aflatoxin continues to be a major threat to the peanut industry and... G. Vellidis, M. Abney, T. Burlai, J. Fountain, R.C. Kemerait, S. Kukal, L. Lacerda, S. Maktabi, A. Peduzzi, C. Pilcon, M. Sysskind |