Proceedings
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| Filter results6 paper(s) found. |
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1. Evaluation Of A Controlled Release N-P Fertilizer Using A Modified Drill For Variable Rate FertilizationBase NP or NPK fertilization is a common practice in cereal production in Chile. Usually, a physical NPK blend is band applied with the seed at planting with the drill. Normal fertilizer rates vary from 400 to 500 kg ha-1; however, there is a tendency in the market to move from physical blend towards chemical blends (monogranule) and, more recently, to controlled release fertilizers (CRF). The CRF are usually recommended at very low rates, varying from 70 to 120 kg ha-1, however this rates are... R.A. Ortega, J.F. Reyes, W. Esquivel, J. Orellana |
2. Use Of Active Radiometers To Estimate Biomass, Leaf Area Index, And Plant Height In CottonActive radiometers have been tested extensively as tools to assess in-season nitrogen (N) status of crops like wheat (Triticum aestivum), corn (Zea mays), and cotton (Gossypium hirsutum). Fewer studies target in-season plant growth parameters such as biomass, plant height or leaf area index (LAI). Uses of this plant data include simulation modeling, total N uptake measurements, evapotranspiration (ET) estimates and irrigation... K.R. Thorp, J.W. White, M.M. Conley, J. Mon, K.F. Bronson |
3. Determining the Marginal Value of Extra Precision in Precision Grazing Systems – an Ex Ante Analysis of Impacts on System Productivity, Sustainability and EconomicsThe development of precision livestock farming (PLF) technologies for application in grazing systems is rapidly evolving. PLF technologies that facilitate the spatial and temporal management of variability in landscapes, pastures and animals promise to improve the efficiency, profitability and sustainability of livestock farming. However, such technologies as a complete package do not yet exist in grazing systems and the question of impacts at the farm system level remains unresolved. Other potential... K. Behrendt, T. Takahashi, M.S. Rutter |
4. Predicting Below and Above Ground Peanut Biomass and Maturity Using Multi-target RegressionPeanut growth and maturity prediction can help farmers and breeding programs improving crop management. Remote sensing images collected by satellites and drones make possible and accurate crop monitoring. Today, empirical relations between crop biomass and spectral reflectance could be used for prediction of single variables such as aboveground crop biomass, pod weight (PW), or peanut maturity. Robust algorithms such as multioutput regression (MTR) implemented through multioutput random forest... M.F. Oliveira, F.M. Carneiro, M. Thurmond, M.D. Del val, L.P. Oliveira, B. Ortiz, A. Sanz-saez, D. Tedesco |
5. Coupling Machine Learning Algorithms and GIS for Crop Yield Predictions Based on Remote Sensing Imagery and Topographic IndicesIn-season yield prediction can support crop management decisions helping farmers achieve their yield goals. The use of remote sensing to predict yield it is an alternative for non-destructive yield assessment but coupling auxiliary data such as topography features could help increase the accuracy of yield estimation. Predictive algorithms that can effectively identify, process and predict yield at field scale base on remote sensing and topography still needed. Machine learning could be an alternative... M.F. Oliveira, G.T. Morata, B. Ortiz, R.P. Silva, A. Jimenez |
6. Use of Crop and Drought Spectral Indices to Support Harvest Decisions of Peanut Fields in AlabamaHarvest efficiency expressed in quantity and quality of peanut fields could increase if farmers are provided with tools to support harvest decisions. Peanut farmers still rely on a visual and empiric method to assess the right time of peanut maturity but this method does not account for within-field variability of crop growth and maturity. The integration of spectral vegetation indices to assess drought, soil moisture, and crop growth to predict peanut maturity can help farmers strengthen decisions... M.F. Oliveira, B.V. Ortiz, E. Hanyabui, J.B. Costa souza, A. Sanz-saez, S. Luns hatum de almeida , C. Pilcon, G. Vellidis |