Abstract
Proximal sensing represents a growing avenue for precision fertilization and crop growth monitoring. In the last decade, precision agriculture technology has become affordable in many countries; Global Positioning Systems for automatic guidance instruments and proximal sensors can be used to guide the distribution of nutrients such as nitrogen (N) fertilization using real-time applications. A two-year field experiment (2017–2018) was carried out to quantify maize yield in response to variable rate (VR) N distribution, which was determined with a proximal vigour sensor, as an alternative to a fixed rate (FR) in a cereal-livestock farm located in the Po valley (northern Italy). The amount of N distributed for the FR (140 kg N ha−1) was calculated according to the crop requirement and the regional regulation: ±30% of the FR rate was applied in the VR treatment according to the Vigour S-index calculated on-the-go from the CropSpec sensor. The two treatments of N fertilization did not result in a significant difference in yield in both years. The findings suggest that the application of VR is more economically profitable than the FR application rate, especially under the hypothesis of VR application at a farm scale. The outcome of the experiment suggests that VR is a viable and profitable technique that can be easily applied at the farm level by adopting proximal sensors to detect the actual crop N requirement prior to stem elongation. Besides the economic benefits, the VR approach can be regarded as a sustainable practice that meets the current European Common Agricultural Policy.
Highlights
Today, machinery and high technological devices used in agriculture are very heterogeneous throughout the world due to economic and environmental reasons
For each variable considered in the present study, the mean, the standard deviation, and the coefficient of variation were computed (Table 5)
The present study aimed at evaluating the effectiveness of the variable rate approach in reducing the N fertilization rate at topdressing while avoiding maize yield loss in intensive agricultural farming systems
Summary
Machinery and high technological devices used in agriculture are very heterogeneous throughout the world due to economic and environmental reasons. The wide range of environmental conditions, land use, and suitability differences of agricultural fields make possible a wide diversification of the technical ameliorations. Advancements in remote sensing, machinery control systems, crop modelling, weather monitoring, decision making, cloud computing, and big data analysis drive PA to the new revolution in agriculture named smart farming [3]. These advancements enhanced the accuracy of PA applications and made them available for a broader range of farmers, allowing enhanced practices through the possibility to predict the occurrence of water or nutrient stresses and take real-time supported decisions. Delgado et al 2005 [10]
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