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METHOD, APPARATUS AND SYSTEM FOR DIAGNOSIS OF STRESSES AND DISEASES IN HIGHER PLANTS

机译:诊断高等植物压力和疾病的方法,装置和系统

摘要

The present invention relates to a method, apparatus and a system of fast diagnosis of stresses and diseases in higher plants. The proposed methodology is based on the hypothesis of that when a plant is in imbalance; there are changes in its metabolism that render an alteration of the chemical composition of its organs. This chemical alteration leads to a change in the physical properties, such as the fluorescence of the leaves. Due to the complexity of the material of the leaves, the present method proposes that the signal be treated with statistical methods and that the classification is made through softwares based on machine learning. As an example of the application of the invention, the results are shown for the Greening disease in citrus. Currently, Greening is the most severe citrus disease since there is no treatment available for it and due to its high dissemination rate and the fact that it affects all varieties of orange trees, being the diagnosis performed through visual inspection, which renders high subjectivity, high error percentage and the disease is only diagnosed after the expression of the symptoms (8 months). During the asymptomatic phase, the infected tree is a source of dissemination of the disease. The present invention can perform the asymptomatic diagnosis of Greening disease from the leaf with a percentage of correct diagnosis higher than 80%.
机译:快速诊断高等植物中的压力和疾病的方法,设备和系统技术领域本发明涉及快速诊断高等植物中的压力和疾病的方法,设备和系统。所提出的方法基于以下假设:植物失衡。它的新陈代谢发生了变化,从而改变了其器官的化学组成。这种化学变化导致物理性质发生变化,例如叶片的荧光。由于叶子材料的复杂性,本方法提出用统计方法处理信号,并通过基于机器学习的软件进行分类。作为本发明的应用实例,显示了柑橘中的绿化病的结果。目前,绿化是最严重的柑橘类疾病,因为目前尚无治疗方法,而且由于其传播率高,而且影响到橙树的所有品种,因此通过目视检查进行诊断,因此主观性高,错误百分比,只有在症状表达后(8个月)才能诊断出疾病。在无症状阶段,被感染的树木是该病传播的来源。本发明可以从叶子进行无症状的绿化病诊断,正确诊断的百分比高于80%。

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