Institute of New Imaging Technologies, Universitat Jaume I, Av. Vicente Sos Baynat s/n, 12071 Castellón de la Plana, Spain.
IMAC, Mathematics Department, Universitat Jaume I, Av. Vicente Sos Baynat s/n, 12071 Castelló de la Plana, Spain.
Sensors (Basel). 2020 Nov 18;20(22):6597. doi: 10.3390/s20226597.
Temperature, humidity and precipitation have a strong influence on the generation of diseases in different crops, especially in vine. In recent years, advances in different disciplines have enabled the deployment of sensor nodes on agricultural plots. These sensors are characterised by a low cost and so the reliability of the data obtained from them can be compromised, as they are built from low-confidence components. In this research, two studies were carried out to determine the reliability of the data obtained by different nodes installed in vineyards. Two networks of meteorological stations were used to carry out these studies, one official and the other professional. The first study was based on calculating the homogenisation of the data, which was performed using the Climatol tool. The second study proposed a similarity analysis using cross-correlation. The results showed that the low-cost node can be used to monitor climatic conditions in an agricultural area in the central zone of the province of Castelló (Spain) and to obtain reliable observations for use in previously published fungal disease models.
温度、湿度和降水对不同作物疾病的发生有很大影响,尤其是在葡萄藤中。近年来,不同学科的进步使得可以在农业用地上部署传感器节点。这些传感器具有低成本的特点,因此它们所获得的数据的可靠性可能会受到影响,因为它们是由低可信度的组件构建的。在这项研究中,进行了两项研究,以确定不同安装在葡萄园中的节点所获得的数据的可靠性。使用了两个气象站网络来进行这些研究,一个是官方的,另一个是专业的。第一项研究是基于计算数据的均匀性,这是使用 Climatol 工具完成的。第二项研究提出了使用互相关进行相似性分析。结果表明,低成本节点可用于监测西班牙卡斯特利翁省中心地带农业区的气候条件,并获得可靠的观测结果,用于以前发布的真菌病模型。