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Quantification of nitrogen mineralization at the field scale is necessary to improve current N fertilizer recommendations. The objective of this study was to identify a suitable set of explanatory variables and an appropriate modelling framework to estimate the average daily amount of N mineralized (DANM) during a corn (Zea mays L.) growing season. In six field experiments in Flat Inland Pampas, Argentina, DANM was evaluated in three different homogeneous zones (HZ), which were defined based on terrain elevation. Mixed‐effect generalized linear models were developed that included growing season as random effect as well as HZ, sand, clay, silt, soil organic carbon, and normalized difference vegetation index (NDVI) as fixed effects. Results showed that DANM ranged from 0.19 to 1.25 kg N ha−1 day−1 with a mean of 0.64 kg N ha−1 day−1, which is equivalent to 110 kg N ha−1 for the corn growing season. The best model included HZ, sand, and early NDVI measurements, and predicted DANM with an RMSE of 0.19 kg N ha−1 day−1. Thus, the model should be improved and tested in the Inland Flat Pampas before it could be used to assess N fertilizer application rates. [ABSTRACT FROM AUTHOR]

In this article, a method is presented for automatic scaling of the F-layer from ionograms based on an image processing technique for the extraction of curvilinear structures. The algorithm obtains the ordinary and extraordinary traces and determines the F2 critical frequency. The performance was tested using a wide data set of ionograms recorded by the Advanced Ionospheric Sounder/Istituto Nazionale di Geofisica e Vulcanologia (AIS/INGV) ionosonde located at Universidad Nacional de Tucumán, Tucuman, Argentina, and the results are compared with manual scaling and also with Autoscala method. Results from these tests show that the method is feasible and can be the seed for the development of a robust automated scaling system. [ABSTRACT FROM AUTHOR]