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Multi and hyperspectral digital imaging based techniques for agricultural soil characterization

机译:基于多和高光谱数字成像的农业土壤特征技术

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Soil characterization and monitoring in agriculture represent the primary key-factors influencing its productivity and the quality of the produced products. A correct and continuous knowledge of agricultural soil characteristics can help to optimize its use and its degree of exploitation both in absolute terms and with reference to specific cultivations. Soil characterization is conventionally performed adopting integrated physical-chemical analyses based on soil portion (samples), properly sampled, classified and then delivered to specialized laboratories. Such an approach obviously requires a chain of actions and it is time consuming. In this work it is examined the possibility offered by multi and hyperspectral digital imaging based spectrophotometric techniques in order to perform fast, reliable and low cost "in situ" analyses to identify and quantify specific soil attributes, of primary importance in agriculture, as: water, basic nutrients and organic matter content. The proposed hardware and software (HW&SW) integrated architecture have been specifically developed, and their response investigated, with the specific aim to contribute to study a set of "flexible", and very simple, procedures to apply in order to be utilized to operate, not only in agricultural soil characterization, but also in other fields as the environmental monitoring and polluted soils reclamation.
机译:土壤表征和农业监测代表了影响其生产率和生产产品质量的主要关键因素。对农业土壤特性的正确和持续知识可以帮助优化其使用及其绝对术语的利用程度,并参考特定的培养。土壤表征通常是采用基于土壤部分(样品)的综合物理化学分析进行,适当取样,分类,然后送到专门的实验室。这种方法显然需要一系列行动,这是耗时的。在这项工作中,检查了基于多和高光谱数字成像的分光光度技术提供的可能性,以便进行快速,可靠和低成本的“原位”分析,以识别和量化特定的土壤属性,对农业的主要重要性,如:水,基本营养素和有机物质含量。拟议的硬件和软件(HW和SW)集成架构已经专门开发,并调查了他们的回应,具体旨在为研究一组“灵活性”以及申请的程序来进行贡献,以便用于运行,不仅在农业土壤表征中,而且还在其他领域作为环境监测和污染的土壤填海。

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