Abstract
One of the fields of research in precision agriculture (PA) is the delineation of potential management zones (PMZs, also known as site-specific management zones, or simply management zones). To delineate PMZs, cluster analysis is the main used and recommended methodology. For cluster analysis, mainly yield maps, remote sensing multispectral indices, apparent soil electrical conductivity (ECa), and topography data are used. Nevertheless, there is still no accepted protocol or guidelines for establishing PMZs, and different solutions exist. In addition, the farmer’s expert knowledge is not usually taken into account in the delineation process. The objective of the present work was to propose a methodology to delineate potential management zones for differential crop management that expresses the productive potential of the soil within a field. The Management Zone Analyst (MZA) software, which implements a fuzzy c-means algorithm, was used to create different alternatives of PMZ that were validated with yield data in a maize (Zea mays L.) field. The farmers’ expert knowledge was then taken into account to improve the resulting PMZs that best fitted to the yield spatial variability pattern. This knowledge was considered highly valuable information that could be also very useful for deciding management actions to be taken to reduce within-field variability.
Highlights
Introduction1980s [1] and is experiencing exponential growth, being considered as the one of the top ten revolutions in agriculture [1,2]
Precision agriculture (PA) is a new paradigm in agriculture that dates back to the middle of the1980s [1] and is experiencing exponential growth, being considered as the one of the top ten revolutions in agriculture [1,2]
Since electrical conductivity (ECa) and elevation were not able to clearly distinguish more than two yield classes, we proposed the delineation of a third class to segment the accumulated NDVI (aNDVI) 2C map on the basis of the farmer’s expert knowledge about the soils, environment, and the history of precedent crops in the plot (Figure 4)
Summary
1980s [1] and is experiencing exponential growth, being considered as the one of the top ten revolutions in agriculture [1,2]. In the recent past, the number of research works related to PA has increased enormously. A simple search in Google Academics with the term “precision agriculture”. In terms of farmers as well as food and agricultural companies, progressively more and more users are starting to use some kind of PA-based system [3]. PA is little by little gaining weight in the day-to-day of farms, there is still a big gap between scientific research and real implementation and/or full adoption
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