Non-invasive soil property measurement for precision farming
This work investigates the application of new sensors to enable agronomists and farm managers to make decisions for variable treatment strategies at key crop growth stages. This is needed to improve the efficiency of crop production in the context of precision farming. Two non-invasive sensors were selected for investigation. These were: 1) The MGD-1 ion mobility gas detector made by Environics OY, Finland. 2) The EM38 electromagnetic induction (EMI) sensor made by Geonics Inc., Canada. The gas detector was used to determine residual nitrogen and to measure carbon dioxide gas as a surrogate indicator of soil quality. In the latter, increased microbial carbon dioxide production was expected on soils with high organic matter content. Overall, the results of gas detection were disappointing. The main problems inherent in the system were; lack of control of the gas sampling, insufficient machine resolution and cross contamination. This led to the decision to discontinue the gas detection research. Instead, the application of electromagnetic induction (EMI) to measure soil variation was investigated. There were two principle advances in the research. Firstly the application of EMI to the rapid assessment of soil textural class. Secondly the mapping of available water content in the soil profile. These were achieved through the development of a new calibration procedure based on EMI survey of the sites at field capacity, working with field experiments from five sites over two years. Maps of total available water holding capacity were produced. These were correlated with yield maps from wet and dry seasons and used to explain some of the seasonal influences on the spatial variation in yield. A product development strategy for a new EMI sensor was considered which produced a recommendation to design a new EMI sensor specifically for available water content and soil texture mapping, that could be mounted on a tractor. For the first time, this procedure enables routine monitoring of the spatial variation in available water content. This enables the effects of seasonal and spatial variation to be included in crop models, targeted irrigation and to aid decisions for the variable application of inputs.