To enable a better decision making by the farmer in order to optimize the crop management, it is essential to provide a set of information on basic parameters of the crops. These information are numerous and the image processing is increasingly used for disease detection, weed detection or yield estimation. We will focus initially on assessing the yield of a wheat crop in automatic way. This yield is directly related to the number of ears per square meter for which the counting is currently done manually. To gather more accurate data than these obtained by remote sensing or not accessible by this technic, we developed a proxi-detection system. The advantages of this kind of system in comparison to remote sensing are: a best resolution, temporality and precision but also a simplified access and a lower costs. To go further in the analysis of parameters of an agronomic scene, the contribution of three-dimensional information using 3D acquisition of such a scene is a relevant solution. Indeed, such a system would provide information like a leaf volume or a growth followed automatically. Many techniques exist for 3D reconstruction using multiple cameras to obtain three-dimensional information. However, our application requires a transportable system and must be used independently in the field so we moved towards a 3D acquisition system based on a mono-camera reconstruction technique. With this system, we obtain a depth information of our scene allowing us to complete our previous works and to evaluate the parameters previously inaccessible.