Adaptive digital tools for nitrogen management: utilising remote sensing data, modelling and sparse ground truthing

Christine Lion1, Ben Jones1, Anastasiia Volkova1

1FluroSat Pty Ltd, 2-4 Cornwallis Street, Eveleigh, NSW, 2015, https://flurosat.com, hello@flurosat.com

Abstract

Remote sensing data can be used in conjunction with crop modelling and data analysis tools to estimate the crop canopy nitrogen status and provide up-to-date information to underpin in-season management decisions. In this study cereal tissue samples were calibrated against indices calculated from satellite imagery and used to generate nitrogen mapping models for wheat and barley at tillering (whole plant) and heading (youngest emerged blade) in South Australia. Crop type was not significant for whole plant samples at tillering (p>0.99) but was for youngest emerged blade at heading (p<0.001). Biomass dilution (related to NDVI/NDRE) was the main component of variation in tissue N% (91% of variance), and (apart from crop type, 75% of variance) the CCCI was the main remote sensing component related to youngest emerged blade N% at heading (17% of variance). The nitrogen maps allowed agronomists to test in some fields rather than all and to use a nitrogen map generated using the remote sensing data as a substitute. In conjunction with tools for management zone creation and nutrient prescription, the nitrogen maps were used to target nutrient application in-season with minimal effort on the agronomist’s behalf.

Host

The Australian Society of Agronomy is the professional body for agronomists in Australia. It has approximately 500 active members drawn from government, universities, research organisations and the private sector.

Photo Credits

David Marland Photography david_marland@hotmail.com Graham Centre for Agricultural Innovation, Charles Sturt University

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