Naturally occurring variability within a study region harbors valuable information on
relationships between biological variables. Yet, spatial patterns within these study areas, eg …

Several spatial methods exist for the adjustment of local trend in one dimension. The aim of
this study was to evaluate and compare the precision of different spatial methods. For this …

Crop improvement efforts have exploited new methods for modeling spatial trends using the
arrangement of the experimental units in the field. These methods have shown improvement …

The YIELDSTAT model for crop yields, an advanced hybrid of traditional non-linear
regression approaches and expert knowledge databases, was developed to predict the …

The advantages of using spatial analysis in annual crop experiments are well documented.
There is much less evidence for perennial crops. For the sequence of measurements in …

With increasing interest in on-farm experiments, there is a pressing need to develop rigorous
statistical methods for analysing these experiments. The adoption of advanced technologies …

An important aim of the analysis of agricultural field trials is to obtain good predictions for
genotypic performance, by correcting for spatial effects. In practice these corrections turn out …

In common bean (Phaseolus vulgaris L.) breeding, several trials are carried out in field
conditions to predict the genotypic values, but experimental designs may not be sufficient to …

Geostatistical methods are important tools for the assessment of site‐specific management
(SSM) approaches in on‐farm research (OFR) on variable rate technology (VRT) based on …

Biophysical models to simulate crop yield are increasingly applied in regional climate impact
assessments. When performing large-area simulations, there is often a paucity of data to …