Mechanized fertilization: Individual application of nitrogen, phosphorus and potassium in sugarcane

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Carneiro, Franciele Morlin [UNESP]
Furlani, Carlos Eduardo Angeli [UNESP]
Ormond, Antonio Tassio Santana [UNESP]
Kazama, Elizabeth Haruna [UNESP]
da Silva, Rouverson Pereira [UNESP]

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With the expansion of areas of sugarcane cultivation, mechanised fertilisation is essential for providing improved operational performance, optimising the supply of nutrients and increasing productivity. However, this type of fertilisation may present deficiencies in the area of distribution, such as fluidity, separation, and particle size, among others. A new concept in fertilisation is therefore being developed, capable of carrying out the individual application of nitrogen, phosphorus and potassium, distributing these in various doses, with greater efficiency of application, employing precision farming and variable rates. The aim of this study was to evaluate the quality of the individual mechanised fertilisation of NPK in ratoon cane by means of Statistical Quality Control - SQC. The experiment was carried out in the city of Matão, in the State of São Paulo, with the experimental area making up part of the Cascavel Farm. The experimental design was based on the basic premise of spatial SQC, monitoring the individual mechanised fertilisation of NPK at 30 sampling points. For this treatment, the lots were composed of six rows of sugarcane, spaced 1.5 m apart, with an effective area of 1,571 m2. There was a sampling point every 30 m, where fertiliser was collected for 5 seconds. The helical metering system especially affected operational quality, as this was inefficient in its distribution. It was concluded that, due to adjustment of the helical metering system, individual application resulted in doses above those recommended for all fertilisers. Nitrogen (protected urea) showed the greatest variability in distribution, whereas phosphorus (MAP) displayed the highest operating quality due to the lower recommended volume.



Mechanised agriculture, Saccharum spp, Statistical process control

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Revista Ciencia Agronomica, v. 48, n. 2, p. 278-287, 2017.