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| Filter results5 paper(s) found. |
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1. Precisely Monitoring Nitrogen Requirements for Winter Wheat and Spring Barley Based on Crop Yield Predictions, Remote Sensing Imagery and Soil Texture MapsThe timely and precise evaluation of crop nitrogen demand is crucial for maximizing farmers' contribution margin while simultaneously minimizing nitrogen fertilization. Sufficient nitrogen fertilizer has to be provided for adequate crop growth, yet fertilization should not be excessive to ensure its environmental impact is minimized. A variety of factors determine nitrogen demands as well as crop yield, including weather, topography and soil texture. These factors vary spatially, meaning that... N. Hollain, S. Wang, B. Feld Mikkelsen, |
2. Optimization of Electrochemical Device Development: Laser-Induced Graphene Electrode as an Alternative for Agricultural Monitoring.The agroindustrial sector has driven the technological development of electrochemical devices aimed at field applications. In this context, laser-induced graphene (LIG) electrodes stand out for enabling electrode miniaturization, favoring in situ analyses and equipment portability. These devices exhibit high sensitivity, selectivity, rapid response, and low cost, characteristics that expand their application potential in different scenarios. However, the growing demand for these devices highlights... C. Miler, L. Gonçalves, B. Vasconcellos Lopes, B.B. Gallo, A. La Rosa, D. Fruchtenicht, P. Silveira, F. , N. Carreño, L. Machado |
3. Quantifying Prediction Uncertainty in Field-scale Soil Maps Generated by Machine Learning.Field-scale maps of soil properties are a key component of precision agriculture, as they are routinely used as inputs for variable-rate fertilization, zone delineation, and site-specific management. While machine learning models have substantially improved the accuracy of spatial predictions, uncertainty associated with these predictions is often ignored, limiting the reliability of soil maps as decision-support tools. Quantifying prediction uncertainty is essential not only to assess map quality,... F. García Seleme, P. Paccioretti, M. Balzarini, M. Córdoba |
4. Temporal Stability of Management Zones Derived from Vegetation Indices and Yield Data in Contrasting Production SystemsThe delineation of management zones is a central component of site-specific crop management in precision agriculture. However, the temporal stability of zones derived from different data sources remains a key challenge, particularly when vegetation indices and yield data are combined across multiple seasons. This study evaluates the temporal stability of management zones delineated using vegetation indices and yield data derived from long-term commercial field datasets. The proposed methodology... |
5. Statistical Mean Comparisons in Unreplicated Yield Trials with Georeferenced DataPrecision agriculture technologies have enabled the collection of large volumes of georeferenced yield data within experimental fields. In practice, many on-farm experiments (OFE) are implemented as large unreplicated strips or field zones containing numerous observations within each zone. The lack of replication prevents the use of classical statistical models for comparing zone means. Although many yield observations are available per zone, spatial autocorrelation violates independence assumptions... M. Córdoba, P. Paccioretti, M. Balzarini |