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Towards an empirical model to estimate the spatial variability of grapevine phenology at the within field scale

机译:朝着实证规模估算葡萄候空间变异的实证模型

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The aim of this study is to propose an empirical spatial model to estimate the spatial variability of grapevine phenology at the within-field scale. This spatial model allows the characterization of the spatial variability of a given variable of the fields through a single measurement performed in the field (reference site) and a combination of site-specific coefficients calculated through historical information. This approach was compared to classical approaches requiring extensive sampling and phenology models based on climatic data, which do not consider the spatial variability of the field. The study was conducted on two fields of Vitis vinifera, one of cv Cabernet Sauvignon (CS, 1.56 ha) and the other one of cv Chardonnay (CH, 1.66 ha) located in Maule Valley, Chile. Date of occurrence of grapevine phenology (budburst, flowering and veraison) were observed at the within field level following a regular sampling grid during 4 seasons for cv CS and 2 seasons for cv CH. The best results were obtained with the devised spatial model in almost all cases, with a Root Mean Square Errors (RMSE) lower than 3 days. However, if the variability of phenology is low, the traditional method of sampling could lead to better results. This study is the first step towards a modeling of the spatial variability of grapevine phenology at the within-field scale. To be fully operational in commercial vineyards, the calibration process needs simplification, for example, using low cost, inexpensive ancillary information to zone vineyards according to grapevine phenology.
机译:本研究的目的是提出经验性空间模型来估算现场规模的葡萄候空间变异性。该空间模型允许通过在字段(参考站点)中执行的单个测量和通过历史信息计算的站点特定系数的组合来表征字段的给定变量的空间可变性。将这种方法与基于气候数据的广泛采样和苯上模型进行了比较的经典方法,这不考虑该领域的空间可变性。该研究是在血管赤霞珠(CS,1.56 HA)之一的葡萄宿炎的两种领域进行,另一个位于智利Maule Valley的CV Chardonnay(CH,1.66公顷)。在常规采样网格中,在4个赛季的CV CS和CV CH的2个赛季,在现场水平内观察到葡萄候选的发生日期在几乎所有情况下,使用设计的空间模型获得了最佳结果,具有低于3天的根均方误差(RMSE)。但是,如果诸斯的候选性低,传统的采样方法可能会导致更好的结果。本研究是迈向现场规模在现场规模的葡萄候空间变异性的第一步。为了在商业葡萄园中完全运行,校准过程可根据葡萄候选需要简化,例如,使用低成本,低成本,廉价的辅助信息,以区域葡萄园。

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