Drones deployed to assess nitrogen needs of pearsTechnology & Data
By Eileen Perry, Ian Goodwin, David Cornwall
Researchers from Agriculture Victoria are using drones to remotely sense leaf nitrogen of red-blushed pearsto develop nitrogen fertiliser management guidelines that maximise fruit quality and minimise below root-zone leaching of nitrogen.
In a previous article, Nitrogen management in red-blushed pears (Australian Fruitgrower, Apr-May 2016), we introduced a new research program to identify optimal nitrogen management in red-blushed pears to achieve good colour, high quality fruit and minimise below root-zone leaching of nitrogen. Most current nitrogen guidelines for pears were developed for Williams and Packham pears grown using traditional orchard systems. We are interested in understanding the nitrogen requirements of new red-blushed pears, like ANP-0131 (Deliza®) and ANP-0118 (Lanya®), in modern intensive orchard designs. Previous research shows nitrogen plays a role in colour development in apples, but we have yet to determine nitrogen’s role in colour development in pears.
As part of pear nitrogen management, growers need a way to assess their orchard’s nitrogen status. Destructive sampling of leaves for nitrogen analysis is one approach. However, laboratory analysis of leaves is too costly to provide a whole-of-orchard assessment of the nitrogen status, and doesn’t provide immediate results. Being able to accurately, easily and cheaply measure leaf nitrogen across an entire orchard would be ideal. As an alternative to lab analysis of leaf nitrogen, we looked to remote sensing.
From wheat to pears
Previous research shows that remote sensing to estimate nitrogen in wheat canopies is effective, particularly when the measurements are made during critical growth stages such as stem elongation. We are extending this work to pears by collecting remote sensing data from pear orchards and measuring actual leaf nitrogen.
Canopy reflectance is being measured with handheld radiometers, drones and satellites. The reflectance spectra that we measure are used to compute specialised vegetation indices that are ‘tuned’ to measure the chlorophyll and nitrogen content of the canopy. Vegetation indices such as the Canopy Chlorophyll Concentration Index (CCCI) are based on reflectance measurements in the ‘chlorophyll red-edge’ (approximately 700 – 750 nm), which lies just beyond human vision. These indices take advantage of slight changes in the reflectance at these wavelengths, which are linked to differences in actual leaf nitrogen.
In addition to optimum wavelengths, the image’s spatial resolution, which determines the quality of the digital image from the remote sensing, must be sufficient to detect changes in canopy nitrogen. Previous research on apples and pears showed that commercial satellite imagery, with spatial resolutions of two to five metres, was not sufficient to separate the tree canopy from the underlying orchard floor. Drones provide an effective way to improve image resolution.
As recently as 10 years ago, the size of the cameras used for multi-spectral and hyper-spectral remote sensing limited their use to full sized aircraft and satellites. Since then, miniaturised cameras have evolved that can be flown on drones or unmanned aerial vehicles (UAVs). Using drones allows us to measure reflectance at resolutions much greater than satellites.
For this new research, we are using multi-rotor drone platforms to carry the cameras that measure crop reflectance. These versatile drones can hover over research plots within the orchard and fly low and slow over the canopy, which is useful for research. However, future commercial applications may well utilise fixed wing drones that can cover much larger areas.
As cameras become smaller, UAVs required to support them can be smaller too. The Civil Aviation Safety Authority (CASA) has recently authorised the use of drones weighing less than 2 kg to be flown without an Operator’s Certificate — meaning growers and researchers can fly them.
What have we found so far
The primary objective of this research is to assess if we can accurately determine leaf nitrogen status of pears using remote sensing of the CCCI, and other indices.
In the research so far we have taken both canopy reflectance and actual measurements of nitrogen in an experimental red-blush pear block with 18 plots and three nitrogen fertiliser levels of 60 kg N/ha/yr (High); 30 kg N/ha/yr (Medium); and 0 kg N/ha/yr (Low). Preliminary results suggest that we can differentiate between high and low levels of leaf nitrogen. We are evaluating several sets of measurements over two growing seasons to identify how accurate remote sensing is at determining leaf nitrogen status.
What’s left to do
There will be room to improve the accuracy of remote sensing to determine leaf nitrogen status by accounting for other factors and variables that affect remote sensing measurements.
The spatial resolution must be sufficient to separate the tree canopy from the orchard floor and other vegetation. However, there is a trade-off between spatial resolution, and the cost to generate the maps — the higher the resolution the more expensive.
Likewise, we need to confirm the optimal wavelengths to measure reflectance. Commercial providers may only have the ability to measure one red-edge band, so selection of the right band is critical. Nitrogen content changes through the growing season, so timing of the measurements within the season is another important factor we want to understand.
One of the outcomes of our research will be ‘best practice’ guidelines for the collection, computing and delivery of nitrogen status for pears using remote sensing. These guidelines will address issues such as when to best acquire the imagery during the growing season and how to calibrate the imagery as part of the processing.
Other sensors for leaf nitrogen
We are also evaluating the use of an active light sensor system that measures fluorescence from pear leaves — this is light emitted from pigments in the leaf (such as chlorophyll). The instrument we are using pulses light at different wavelengths (ultraviolet, blue, green and red) and measures the light emitted in the yellow, red and near infrared wavelengths.
The various combinations of pulsed light and measured return light are used to estimate the concentration of chlorophyll, flavonol, nitrogen and anthocyanin in the leaves. As an active light sensor, it can be used outdoors under various light conditions. It is a sensing instrument that is used within close proximity to (or touching) the canopy. Ultimately, instruments like these can be mounted on tractors or other ground-based vehicles and used to create maps of the crop health through the orchard.
This project is funded through the Productivity Irrigation Pests and Soils (PIPS) program by Horticulture Innovation Australia Ltd using the apple and pear industry levy from growers, matching funds from the Australian Government and co-investment from the Department of Economic Development, Jobs, Transport and Resources (DEDJTR), Victoria.
About the authors
Eileen Perry is a specialist in remote sensing; Ian Goodwin is a horticultural researcher and David Cornwall is a horticulture technical officer — all from DEDJTR. For more information contact Eileen on email@example.com or 03 5430 4464.