Authors
| Filter results4 paper(s) found. |
|---|
1. Unmanned Aerial System To Determine Nitrogen Status In MaizeMaize field production shows spatial variability during vegetative crop growth that could be used to prescribe nitrogen variable rates. The use of portable sensors mounted on high-clearance applicators is well documented, however new UAS vehicle equipped with high resolution digital cameras could be used to determine crop spatial variability with the advantage of survey extensive field areas. To our knowledge, comparisons between vegetation indices obtained by a modified digital camera and... A.C. Kemerer, S.M. Albarenque, R.J. Melchiori |
2. Should One Phosphorus Extraction Method Be Used for VRT Phosphorus Recommendation in the Southern Great Plains?Winter Wheat has been produced throughout the southern Great Plains for over 100 years. In most cases this continuous production of mono-culture lower value wheat crop has led to the neglect of the soils, one such soil property is soil pH. In an area dominated by eroded soils and short term leases, Land-Grant University wheat breeders have created lines of winter wheat which are aluminum tolerant to increase production in low productive soils. Now the fields in this region can have... D.B. Arnall, S. Phillips, C. Penn, P. Watkins, B. Rutter, J. Warren |
3. Reverse Modelling of Yield-Influencing Soil Variables in Case of Few Soil DataOur hypothesis was that simple models can be applied to predict yield by using only those yield data which spatially coincide with the soil data and the remaining yield data and the models can be used to test different sampling and interpolation approaches commonly applied in precision agriculture and to better predict soil variables at not observed locations. Three strategies for composite sample collection were compared in our study. Point samples were taken 1.) along lines within homogenous... I. Sisák, A. Benő, K. Szabó, M. Kocsis, J. Abonyi |
4. Simultaneously Estimating Crop Biomass and Nutrient Parameters Using UAS Remote Sensing and Multitask LearningRapid and accurate estimation of crop growth status and nutrient levels such as aboveground biomass, nitrogen, phosphorus, and potassium concentrations and uptake is critical with respect to precision agriculture and field-based crop monitoring. Recent developments in Uncrewed Aircraft Systems (UAS) and sensor technologies have enabled the collection of high spatial, spectral, and temporal remote sensing data over large areas at a lower cost. Coupled deep learning-based modeling approaches with... P. Kovacs, M. Maimaitijiang, B. Millett, L. Dorissant, I. Acharya, U.U. Janjua, K. Dilmurat |