Proceedings
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| Filter results4 paper(s) found. |
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1. NDVI 'Depression' In Pastures Following GrazingPasture biomass estimation from normalized difference vegetation index (NDVI) using ground, air or space borne sensors is becoming more widely used in precision agriculture. Proximal active optical sensors (AOS) have the potential to eliminate the confounding effects of path radiance and target illumination conditions typically encountered using passive sensors. Any algorithm that infers the green fraction of pasture from NDVI must factor in plant morphology and live/dead plant ratio, irrespective... J.S. Stanley, D.W. Lamb, M.G. Trotter, M.M. Rahman |
2. Response of Soybean Cultivars According to Management Zones in Southern BrazilThe positioning of soybean cultivars on fields according your environmental response is new strategy to obtain high soybean yields. The aim of this study was to investigate the agronomic response of six soybean cultivars according management zones in Southern Brazil. The study was conducted in 2013/2014 and in two fields located in Boa Vista das Missões, Rio Grande do Sul, Brazil. The experimental design was a randomized complete block in a factorial arrangement (3x6), with three management... T.J. Amado, A.L. Santi, G.M. Corassa, M.B. Bisognin, R. Gaviraghi, J.L. Pires |
3. Challenges and Successes when Generating In-season Multi-temporal Calibrated Aerial ImageryDigital aerial imagery (DAI) of the crop canopy collected by aircraft and unmanned aerial vehicles is the yardstick of precision agriculture. However, the quantitative use of this imagery is often limited by its variable characteristics, low quality, and lack of radiometric calibration. To increase the quality and utility of using DAI in crop management, it is important to evaluate and address these limitations of DAI. Even though there have been improvements in spatial resolution... P.M. Kyveryga, J. Pritsolas, J. Connor, R. Pearson |
4. Within-field Profitability Assessment: Impact of Weather, Field Management and SoilsProfitability in crop production is largely driven by crop yield, production costs and commodity prices. The objective of this study was to quantify the often substantial yet somewhat illusive impact of weather, management, and soil spatial variability on within-field profitability in corn and soybean crop production using profitability indices for profit (net return) and return-on-investment (ROI) to produce estimates. We analyzed yield and cropping system data provided by 42 farmers within Central... P.M. Kyveryga, S. Fey, J. Connor, A. Kiel, D. Muth |