Monitoring grapevine phenology during the agricultural season is one of the most important tasks within the vine field since this is a key input for the proper planning of agricultural labor management. Traditionally, vine growers make very few phenological observations at the field level, which are extrapolated to an entire production unit, without considering the field natural spatial variability. This situation generates significant loss of agricultural inputs and energy, which makes the vine system less sustainable, because this vineyard natural spatial variability is not usually considered in the field management. In this study, two models were tested using information recollected by a meteorological weather station and a wireless sensor network (WSN) to estimate vineyard phenology in a key period such as flowering. Therefore, the general objective of this proposal is to develop a low-cost wireless sensor network (WSN) for monitoring the spatial variability of vine phenology in a commercial vineyard. Results indicated that both models presented a better estimation of vine phenology during the second season, given that the first season was affected by the ENSO “La Niña” climatic effect. However, it can be noted that the Parker model (GPV) presented better phenological estimation than the Monomolecular equation-based model (ME), when using a low-cost wireless sensor network. Based on the results, we can conclude that it is possible to develop and implement a low-cost electronic device for the monitoring of spatialized phenological events in the vineyard.

在农业季节监测葡萄物候是葡萄田内最重要的任务之一，因为这是正确规划农业劳动力管理的关键输入。传统上，葡萄种植者很少在田间进行物候观察，这些观察被外推到整个生产单元，而没有考虑田间自然空间变异性。这种情况会导致农业投入和能源的大量损失，从而使葡萄树系统的可持续性降低，因为在田间管理中通常不考虑这种葡萄园的自然空间变异性。在这项研究中，使用气象气象站和无线传感器网络 (WSN) 收集的信息测试了两个模型，以估计开花等关键时期的葡萄园物候。所以，该提案的总体目标是开发一种低成本的无线传感器网络 (WSN)，用于监测商业葡萄园中葡萄物候的空间变异性。结果表明，鉴于第一个季节受到 ENSO“拉尼娜”气候效应的影响，两个模型都对第二个季节的葡萄树物候进行了更好的估计。然而，可以注意到，当使用低成本无线传感器网络时，Parker 模型 (GPV) 比基于单分子方程的模型 (ME) 表现出更好的物候估计。基于结果，我们可以得出结论，可以开发和实施一种低成本的电子设备，用于监测葡萄园中的空间物候事件。