Regional yield forecasts of malting barley (Hordeum vulgare L.) by NOAA-AVHRR remote sensing data and ancillary data

Abstract

Yield forecasts are of major interest to the malting and brewing industry in order to allow the most convenient organization of the respective policy of raw materials. As malting barley is predominantly cultivated in a limited set of growing regions because of its special requirements, yield predictions can be limited to these regions of interest. Within this investigation, malting barley yield forecasts (Hordeum vulgare L.) are performed for typical growing regions in southwestern Germany. Multitemporal remote sensing data on the one hand and ancillary data such as meteorological, phenological, pedological, agro statistical and administrative data on the other hand are used as input data for two versions of prediction models, which are both based on an empirical-statistical modelling approach. The basic version of the yield estimation model is conducted by means of linear correlation of remote sensing data [national oceanic and atmospheric administration-advanced very high resolution radiometer (NOAA-AUHRR) normalized difference vegetation index (NDVI) maximum value composites], CORINE land cover data and agro statistical data. In an extended version, meteorological data (temperature and evapotranspiration) and soil data are incorporated. Yield predictions are significantly influenced by the selected time span for NDVI integration. For NDVI time-integration across the grain-filling period, the mean deviation of reported and simulated yield is 7.0 and 6.4 %, respectively, for the basic and extended yield estimation model. © 2005 Blackwell Verlag.