Management zones can be defined as homogeneous regions for which specific management decisions are to be considered. The delineation of these management units is important because it enables or at least facilitate growers and practitioners performing site specific management. The delineation of management zones has essentially been performed by (i) clustering techniques or (ii) segmentation algorithms arising from the image processing domain. However, the first approach does not take into account the spatial relationships in the data, and is prone to generate a large number of fragmented zones while he second methodology has only been dedicated to regularly-spaced, within-field data. This work proposes a new approach to generate contiguous management zones from irregularly-spaced within-field observations, e.g. within-field yield, soil conductivity, soil samples, which are a very important source of data in precision agriculture studies. A seeded region growing and merging algorithm has been specifically designed for these irregularly-spaced observations. More specifically, a Voronoi tessellation was implemented to define spatial relationships between neighbouring observations. Seeds were automatically placed at specific locations across the fields and management zones were first expanded from these seeds. The merging procedure aimed at generating more manageable and interpretable zones. The merging algorithm was defined in a way that made it possible to incorporate machinery and technical management constraints. Experiments demonstrated that the proposed methodology was able to generate relatively compact and contiguous management zones. Furthermore, machinery and technical constraints were shown to significantly influence the results of the delineation which proved the importance of accounting for these considerations.