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• Functional analysis methods were able to decompose the yearly trend and spatial structure of the vineyards. • Performance of PCA declines if more than three componets are added. • The results are linked to soil characteristics and other key variables, highlighting several phenomena affecting the vineyard. Sentinel-2 satellite imagery offers a wealth of spectral information combined with a weekly temporal resolution. It is seen as a promising tool to extract spatial information about vineyards and link them to agronomic parameters. Usually, only one or a few images are commonly employed at specific stages like veraison in viticulture. Extracting further information from time-series images may be of interest; however, this remains an issue due to the noisy and complex nature of extracted time-series. The functional analysis proposes a robust continuous representation of these time-series, which can then be used with adapted statistical tools. This paper focuses on extracting relevant information at the within-field level on two vineyards in Spain, which can be jointly interpreted with field observations and measurements. More precisely, it discusses the use of popular linear dimensionality reduction techniques, namely Principal Component Analysis (PCA) and Partial Least Square (PLS), adapted to functional data in order to decompose NDVI time-series into a weighted sum of several functional components. The unsupervised methods, like PCA, decomposed the spatial structure within the vineyards using a few components, resulting in a better and more manageable dataset than the one obtained using simple non-constrained methods. The results show significant correlations with ground-truth data showing the added value of considering the whole NDVI temporal series compared to a single NDVI map at veraison. The proposed approach provided helpful information about each component's yearly trend. Moreover, the results are linked to grapevines' seasonal phenology and management practices, highlighting phenomena affecting the vineyard's development. This method is particularly suited for interactions with field experts, who may derive relevant agronomic information from the decomposition maps. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents a real-time, on-farm irrigation scheduling software (RIDECO). The software was been designed for stone fruit orchards in the semiarid conditions of Spain. The characterization of stone fruit crop water requirements for the local conditions and under different irrigation strategies is presented. Meteorological data in the study area is collected daily from the SIAR public network of weather stations in an automated fashion. Subsequently, values of cumulative degree-days are computed to identify the stages of fruit growth and crop development. The software allows performing weekly irrigation schedules under standard, regulated deficit irrigation and water restriction conditions. The irrigation scheduling software stands as a valuable tool for on-farm water resources allocation planning. It can be used to forecast the irrigation water required to meet seasonal meteorological, agronomical and managerial scenarios in stone fruit orchards. RIDECO can also be used to plan deficit irrigation strategies in cases of severe water restrictions. The software can be parameterized to adjust to specific varieties and local farming conditions. A variety of graphs assist irrigation managers in their decisions. [Copyright &y& Elsevier]

Abstract: This paper explains the process followed to generate the model used as a decision support tool for agricultural production planning in the most agrarian areas in Galicia (NW Spain). The model comprises three procedures that use 44 social, environmental and economic indicators developed using both monographic information and field data. The indicators allow for the selection of the most suitable crops and land uses for each agrarian area, and allow decision makers to define key factors for performing a diagnostic analysis and proposing relevant actions regarding agricultural production planning. The potential of the tool for defining a hierarchy of potential crops and land uses according to their degree of suitability has been illustrated by applying the model to one of the 88 Ecological and Economic Units studied (EEUs). The proposed model can be a useful tool for production managers, agricultural associations, governmental agencies and even non-governmental organizations in underdeveloped countries. The most innovative aspects of the model are the feasibility of grouping indicators to perform a diagnostic analysis of different scenarios, and that it can be adapted to any other region in the world, by adjusting the objectives of agricultural production planning and the corresponding indicators. [Copyright &y& Elsevier]

Abstract: In this paper we present a segmentation algorithm, inspired from an image-processing region-merging algorithm, for the delineation of discrete contiguous management zones in agriculture. The algorithm is unique in that it is applicable to high- or low-density irregular data sets, such as yield data. The algorithm is described and a brief example presented using unprocessed sensor-derived grain yield data. A comparison between the segmentation algorithm and a common classification algorithm (k-means clustering) was done using an aerial normalised differences vegetation index (NDVI) image collected on a 200ha vineyard in Olite, Southern Navarre, Spain. Classification was performed as a univariate (NDVI) analysis and a spatially constrained analysis. Segmentation and classification were run to find 2, 4, 6, …, 24 levels and the effectiveness of the outputs determined by how well it explained the variance in vine trunk circumference, a correlated but independent measurement. The results obtained demonstrated that for a given number of manageable (effective) zones the segmentation outputs were equivalent or superior to the classification outputs for partitioning vine circumference variance. The segmentation output also generated more coherent management units that should facilitate differential management. The algorithm presented is a first generation segmentation algorithm and several aspects still need to be developed, in particular methods for eliminating edge effects and converting management zones into management (treatment) classes. The results of the segmentation algorithm presented here would indicate that with further development, segmentation might provide an alternative and possibly preferable approach to delineating management zones. [Copyright &y& Elsevier]

Abstract: In recent years many applications have been proposed for Wireless Sensor Networks (WSN). One of these is precision agriculture, where WSN can play an important part in the handling and management of water resources for irrigation, in understanding the changes in the crops to assess the optimum point for harvesting, in estimating fertilizer requirements and to predict crop performance more accurately. This paper describes our experience during the introduction and deployment of an experimental sensor network at an ecological horticultural enterprise in the semiarid region of Murcia. It presents the topology of the deployed network using four types of nodes (Soil Mote, Environmental Mote, Water Mote and Gateway Mote), some of them connected to different sensors distributed in the field. These sensors can measure various soil characteristics such us temperature, volumetric moisture content and salinity. For each node, the overall architecture, hardware and software components are described. The system also includes a real-time monitoring application operating from a computer placed in the central offices of the farm. The testing of the system was done in two phases: the first in the laboratory, to validate the functional requirements of the developed devices, the networking solution and the mote''s power management; the second on the farm, to asses the functional performance of the devices, such as range, robustness and flexibility. The system was successfully implemented on a crop of ecological cabbage (Brassica oleracea). The result was a low cost, highly reliable and simple infrastructure for the collection of agronomical data over a distributed area in horticultural environments. [Copyright &y& Elsevier]

Abstract: Since 2002, the Galician Administration (NW Spain) has been working in the development of a decision support system for Agricultural Production Planning. To this end, an initial decision tool, Gestop®, was developed. However, the tool had a number of limitations for practical use because of the lack of differentiated data about the real situation of farms. With a view to improving the initial tool, a combinatorial method (CM) was developed. Such a combinatorial method used official census data to classify farms based on the different production processes, sizes and geographical locations of farms, among other factors. The combinatorial method proved very useful as a source of differentiated data for the decision support system. Yet, validating the results using robust statistical methods was considered essential in order to guarantee the suitability of the model for use. This paper uses discriminant analysis (DA) techniques to validate the types of dairy farms obtained from the combinatorial method for Galicia. Results clearly validate the combinatorial method and its use as a data source for decision support systems in Agricultural Production Planning. [Copyright &y& Elsevier]

Abstract: Agricultural subsidies can only be effectively allocated if there is a suitable information system both at the level of subsidy providers – the government – and recipients – agricultural organizations. Governments have to set up complex schemes to control subsidies using techniques such as remote sensing or photogrammetry. If these techniques do not help, technical staff has to visit the plots. This paper explains the development and implementation of a mobile application to make fieldwork easier. The application uses a number of devices in a Smartphone such as a GPS or a camera to collect information and broadcast it to an office in real time. This application, called GeoFoto, computers was tested in real scenarios in the Spanish region of Andalusia. This provided information about its advantages and disadvantages, and the final results are highly encouraging. [Copyright &y& Elsevier]