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A HyperSpectral Imaging (HSI) approach for bio-digestate real time monitoring

机译：用于生物消化物实时监控的高光谱成像（HSI）方法

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摘要

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 physical-chemical 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.
机译：制定良好农业规范（GAP）的关键问题之一是最佳利用肥料和除草剂，以减少硝酸盐对土壤和环境的影响。在传统的农业实践中，这些物质是通过使用化学产品（无机/有机肥料，土壤改良剂/调节剂等）提供给土壤的，通常与几个主要的环境问题相关，例如：水污染和污染，肥料依赖性，土壤酸化，微量矿物质消耗，过度施肥，高能耗，对气候变化的贡献，对菌根的影响，缺乏长期可持续性等。因此，农业市场对利用越来越感兴趣有机肥料和土壤改良剂。在有机肥料中，对消化物的兴趣正在兴起，其是厌氧消化（AD）过程产生的副产品。多项研究证实，如果将消化液用作有机肥料和土壤改良剂/改良剂，则具有很高的消化性能。实际上，Digestate在某种程度上类似于堆肥：AD将有机氮的主要部分转化为氨，然后将其作为氮直接提供给植物。在本文中，将介绍和讨论基于高光谱成像（HSI）传感设备和相关检测架构的新分析工具，以定义和应用易于使用，可靠，健壮和低成本的策略，最终确定并实施创新智能检测引擎，用于摘要表征和监控。该方法已最终确定下来，可以在减少影响和“临时”施肥的情况下，将这种“废物”用作有价值的有机肥料和土壤改良剂。此外，当代利用HSI方法实现农业土壤的实时物理化学表征（即氮，磷等，检测）的可能性可以允许建立“实时”选择性施肥策略，以获得土壤肥力。更安全的文化生产。

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