Improving yield prediction accuracy using energy balance trial, on-the-go and remote sensing procedure

Kulmány, IstvánZsebő, SándorNyéki, AnikóMilics, GáborKovács, Attila JózsefNeményi, Miklós2019-04-262019-04-26http://hdl.handle.net/2437/266261Our long term experience in the ~23.5 ha research field since 2001 shows that decision support requires complex databases from each management zone within that field (eg. soil physical and chemical parameters, technological, phenological and meteorological data). In the absence of PA sustainable biomass production cannot be achieved. The size of management zones will bw ever smaller. Consequently, the on the go and remote sensing data collection should be preferred. The paper presents the results of ECa and near-surface hyperspectral measurements. For the increase in accuracy of yield prediction of DS models the energy input-output analysis in the management zones can also be used.1-9enEnergy input-output in management zonesaccuracy of maize yield predictionincreasing of databaseImproving yield prediction accuracy using energy balance trial, on-the-go and remote sensing procedureproceedingstudományterületek::növénytudományok