A hyperspectral imaging (HSI) approach for bio-digestate real time monitoring

One of the key issues in developing Good Agricultural Practices (GAP) is represented by the optimal utilisation of fertilisers and herbicidal to reduce the impact of Nitrates in soils and the environment. In traditional agriculture practises, these substances were provided to the soils through the use of chemical products (inorganic/organic fertilizers, soil improvers/conditioners, etc.), usually associated to several major environmental problems, such as: water pollution and contamination, fertilizer dependency, soil acidification, trace mineral depletion, over-fertilization, high energy consumption, contribution to climate change, impacts on mycorrhizas, lack of long-term sustainability, etc. For this reason, the agricultural market is more and more interested in the utilisation of organic fertilisers and soil improvers. Among organic fertilizers, there is an emerging interest for the digestate, a sub-product resulting from anaerobic digestion (AD) processes. Several studies confirm the high properties of digestate if used as organic fertilizer and soil improver/conditioner. Digestate, in fact, is somehow similar to compost: AD converts a major part of organic nitrogen to ammonia, which is then directly available to plants as nitrogen. In this paper, new analytical tools, based on HyperSpectral Imaging (HSI) sensing devices, and related detection architectures, is presented and discussed in order to define and apply simple to use, reliable, robust and low cost strategies finalised to define and implement innovative smart detection engines for digestate characterization and monitoring. This approach is finalized to utilize this “waste product” as a valuable organic fertilizer and soil conditioner, in a reduced impact and an “ad hoc” soil fertilisation perspective. Furthermore, the possibility to contemporary utilize the HSI approach to realize a real time physicalchemical characterisation of agricultural soils (i.e. nitrogen, phosphorus, etc., detection) could allow to set up “real time” selective fertilization strategies in order to obtain a safer culture production