• Rural Digital Europe

Precision agriculture allows modern producers to manage within fields rather than managing the whole field.By integrating global positioning systems (GPS), variable rate (VR) application equipment, and geographic information systems (GIS), farmers are allowed increased efficiency. However, prior to using VR equipment, accurate maps of yield-limiting factors must be created. Nutrients in any field vary due to topography, soil properties and past management (manure application patterns, crop history, etc.). To account for this variability, farmers will need more than one soil sample in each field. A more intensive sampling scheme must be performed, through either grid or zone sampling. Looking to the future, on-the-go sensors, whether attached to tractors or unmanned aerial vehicles, may also increase accuracy and decrease the cost of soil sampling. University of Maryland Extension

This article belongs to the Special Issue Precision Agriculture Adoption Strategies The purpose of this Special Issue was to publish high-quality research and review papers that cover the definition of strategies that may promote the adoption of PA, assessing the adoption rates, bottlenecks for adoption, adoption promotion, strategic plans, and incentives. The Special Issue covers nine peer-reviewed research papers and one systematic review paper info:eu-repo/semantics/publishedVersion

Dataset 1 represents a collection of NDVI measurements connected to specific N fertilisation levels and management zones. Dataset 2 represents geo- referred soil samples collected at 0-20 cm depth, following a random grid (40 m) spatial survey, collected before sowing and after tillage, used for the delineation of the management zones. The two datasets were used to check the effectiveness of two nitrogen fertilisation management strategies, one based on management zones and one on crop data. The two datasets provide rules for choosing the best strategy based on the dimension of spatial structure of the available information. More details are reported in the paper “Cordero, E., Longchamps, L., Khosla, R., Sacco, D., 2019. Spatial management strategies for nitrogen in maize production based on soil and crop data. Science of the Total Environment 697, 133854. Doi: https://doi.org/10.1016/j.scitotenv.2019.133854”

In this paper, we present an overview of several challenges in arable farming that are well suited for research by the control engineering society. We discuss the global needs that these challenges are related to as well as the relation of these challenges to future applications of arable farming. For each of these opportunities we provide several concrete and detailed research questions. Particular attention is paid to the management of resources and sensors in farms. The objective of writing this paper is to further entice control engineers into the domains of agronomy and agricultural technology.