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首页> 外文会议>Congreso Argentino de Ciencias de la Informatica y Desarrollos de Investigacion >Building honey-based territorial identity for the Formosa Monte through information exploitation using intelligent systems
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Building honey-based territorial identity for the Formosa Monte through information exploitation using intelligent systems

机译：通过使用智能系统的信息开发来构建蜂蜜的领土标识

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The territorial valorization of food products is tightly related to quality attributes and is currently the base of typification processes. In the construction of territorial identity based on honey coming from Apis-melifera bee, studies integrating melissopalinological and sensory analysis, and physical-chemical parameters have a significant weight in the definition of the botanical origin and allow the conformation of groups belonging to an area of provenance. The analysis and identification methodologies utilized by classic statistics are based in multivariate techniques, that find their limitations associated to a great number of attributes in a small set of samples. As an alternative, the aim of this article is to define a procedure that allows to determine groups and their descriptive properties, through the exploitation of information using intelligent systems. For the analysis, 47 samples of honey from the north-east region of the oriental district of the Chaque?o Park in Formosa Province, Argentina, were used. A set of nine physical-chemical parameters, 20 sensory descriptors and 128 botanical species (taxa) were also used on these samples. On the first place, affinity groups were identified through the Kohonen algorithm. Afterwards, induction rules were utilized to determine the properties of the groups. Moreover, properties of single-flower (type of dominating pollen) and multi-flower (with more than one kind of pollen intervening) groups of honey were identified through induction rules. The applied techniques resulted in a simplification of the methods employed for honey identification and valorization.
机译：食品的领海与质量属性紧密相关，目前是类型的基础。在基于蜂蜜的领土身份构建，基于来自Apis-Melifera Bee的蜂蜜，整合蜂鸣和感官分析的研究，以及物理化学参数在植物来源的定义中具有显着的重量，并允许属于某个区域的组的构象来源。经典统计使用的分析和识别方法基于多变量技术，该技术可以找到与一小组样本中大量属性相关的限制。作为替代方案，本文的目的是通过使用智能系统利用信息来定义允许确定组及其描述性质的过程。对于分析，使用了47个来自阿根廷福尔纳省的东方地区的东北地区的47个蜂蜜样品。在这些样品中也使用了一组9个物理学参数，20个感觉描述符和128种植物种（分类群）。首先，通过kohonen算法鉴定亲和力组。然后，利用归纳规则来确定组的性质。此外，通过归纳规则确定单朵花（主导花粉的类型）和多花（具有多种花粉中间）蜂蜜组。所施加的技术导致简化用于蜂蜜鉴定和储度的方法。

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