crop model; STICS; N management; yield prediction; climate variability
Abstract :
[en] At the parcel scale, crop models such as STICS are powerful tools to study the effects of variable inputs such as management practices (e.g. nitrogen (N) fertilisation). In combination with a weather generator, we built up a general methodology that allows studying the yield variability linked to climate uncertainty, in order to assess the best N practice. Our study highlighted that, applying the Belgian farmer current N practice (60-60-60 kg N/ha), the yield distribution was found to be very asymmetric with a skewness of -1.02 and a difference of 5% between the mean (10.5 t/ha) and the median (11.05 t/ha) of the distribution. This implies that, under such practice, the probability for farmers to achieve decent yields, in comparison to the mean of the distribution, was the highest.
Disciplines :
Agriculture & agronomy Computer science
Author, co-author :
Dumont, Benjamin ; Université de Liège > Agronomie, Bio-ingénierie et Chimie (AgroBioChem) > Phytotechnie des régions tempérées
Basso, Bruno
Leemans, Vincent ; Université de Liège > Ingénierie des biosystèmes (Biose) > Agriculture de précision
Bodson, Bernard ; Université de Liège > Agronomie, Bio-ingénierie et Chimie (AgroBioChem) > Phytotechnie des régions tempérées
Destain, Jean-Pierre ; Université de Liège > Agronomie, Bio-ingénierie et Chimie (AgroBioChem) > Phytotechnie des régions tempérées
Destain, Marie-France ; Université de Liège > Ingénierie des biosystèmes (Biose) > Agriculture de précision
Language :
English
Title :
Yield variability linked to climate uncertainty and nitrogen fertilisation