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A numerical analysis of the micromechanical behaviour of a granular material is described using a new program MASOM based on Cundall's discrete element method. In the analysis the individual grains which make up the material are taken to be deformable 2D polygons of arbitrary size and shape. Contact forces between the grains are calculated according to Mindlin's solution for frictional contact between elastic bodies. The material in each grain is taken to be linear elastic but limited by the fracture strength of the material. Fracture is permitted along any one of a number of candidate fracture planes if an associated compressive load tending to split the gain reaches a critical level. Fragments of fractured grains are carried until they become too small to track using the explicit time integration algorithm used to advance the solution. The MASOM program is able to consider a number of different classes of elements and different types of contact between the various classes. Thus, in addition to the granular material the program can also model containers and loading devices. The program is used to simulate uniaxial and triaxial compression tests for geological materials. The results are shown to give results for stress‐strain and stress difference versus pressure which are in qualitative agreement with test data. The numerical results reveal a very complex micromechanical behaviour in granular materials, including highly variable and rather unstable load paths and a very inhomogeneous load distribution within a representative sample of the material. A video of the response of a typical frictional material to applied loads shows an interesting localized effect near sample boundaries involving crowding together of grains which cannot be observed using conventional static field plots.

As it becomes increasingly evident that skills shortage in many areas of business and commerce is likely to grow, it is clear that knowledge‐based systems can go some way towards replacing human resources. The use of these systems also increases the productivity and effectiveness of already experienced personnel and also brings with it consistent standards of performance and reliability. A better balance is also achievable between the tasks done by employees and those performed by machines.

To describe the function and use of the GreenSeeker™ active remote sensor used to detect crop nitrogen status.

In this paper, the GreenSeeker active remote sensor and its use in irrigated maize production systems will be described. A brief discussion of the science of using remote sensing for studying plants is presented. Additionally, a summary of observations collected from field trials is presented.

The GreenSeeker active sensor has tremendous potential for accurately characterizing crop variability for site‐specific N rate determinations in the Western Great Plains region of the United States.

This paper discusses the GreenSeeker active sensor for detecting crop variability. Data from the GreenSeeker can be used to make site‐specific nitrogen fertilizer applications which may lead to improved nitrogen use efficiency.