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This paper reviews the main applications of geostatistics to the description and modeling of the spatial variability of microbiological and physico-chemical soil properties. First, basic geostatistical tools such as the correlogram and semivariogram are introduced to characterize the spatial variability of each attribute separately as well as their spatial(More)
The use of new, rapid and non-invasive sensors in the field allows the collection of many observations which are necessary to assess the spatial variability of berry composition. The aim of this work was to study the spatial variability in anthocyanin content in grapes and to quantify its relationship with the vigour and yield in a commercial vineyard. The(More)
Cranberry harvesting methods give only one yield value per field making characterization of within-field variation, the usual first step in precision farming, difficult. Time-consuming berry count yield and fruit rot estimations are the best “ground truth” indication of yield variation within fields. Correlations and coincidence of binary classifications(More)
This paper describes a multivariate geostatistical methodology to delineate areas of potential interest for future sedimentary gold exploration, with an application to an abandoned sedimentary gold mining region in Portugal. The main challenge was the existence of only a dozen gold measurements confined to the grounds of the old gold mines, which precluded(More)
This paper presents three multivariate geostatistical algorithms for incorporating a digital elevation model into the spatial prediction of rainfall: simple kriging with varying local means; kriging with an external drift; and colocated cokriging. The techniques are illustrated using annual and monthly rainfall observations measured at 36 climatic stations(More)
1. Abstract This paper presents a geostatistical approach to model uncertainty about the spatial distribution of soil properties and to propagate it through a crop model, allowing for incorporation of uncertainty in the choice of management scenarios (no lime, single-rate liming and site-specific lime applications to acidic field soil). The methodology(More)
Cranberries are grown in sensitive wetland ecosystems and precision farming could be beneficial to reduce agro-chemical pollution and increase production without expanding area. Precision farming requires knowledge of the variation of yield within-fields but cranberry harvesting methods produce only one yield value per field unless an expensive pre-harvest(More)