By Fabian Sanchez
is working to expand knowledge on the modes of action and effectiveness of
biostimulants in agricultural crops. One of the tools we rely on is the
Normalized Differential Vegetative Index (NDVI) to assess live green vegetation
in our BioStimulant product performance trials.
With the advent of numerous innovations, there is more
opportunity than ever to improve our ability to evaluate the health and well-being
of plants in the field. Achieving accurate and useful field assessment data can
be challenging and costly and the data is often fraught with background noise
from human error and subjective variabilities.
NDVI measurements can help us monitor research plots more efficiently.
These measurements can also lead to a larger analysis of vegetative properties to
assess BioStimulant impact including; leaf area index, chlorophyll
concentration, plant productivity, vigor, fractional vegetation cover,
accumulated rainfall, basic nutrient response, crop condition (identify
diseases), yield potential, stress, biomass, herbicide efficiency and the list
could go on.
NDVI uses the photosynthetically
active radiation spectral region of plants in the near-infrared and red
(visible) spectral region. The chlorophyll reflectance value needs to be
determined in order to understand the NDVI readings which are based on the
reflectance values from the plants using the two different wavelengths.
Chlorophyll is known to strongly absorb visible light from 400nm to 700nm for use in photosynthesis therefore, NDVI functionally obtains
the equivalence of simple infrared/red ratio as shown on the figure below.
NDVI is directly related to the photosynthetic capacity
and thus energy absorption of plant canopies. Our instrumentation is the
Greenseeker handheld crop sensor by Trimble (Fig. 2.) and its sensor displays the measured value in terms of an NDVI reading (ranging from 0.00 to 0.99) on
its LCD display screen as described in their website. Therefore, the greener
plant material there is the higher the NDVI reading is which complies with the
principle of having low red-light absorbed by the chlorophyll in the plant and
high near-infrared light reflectance.
Greenseeker is an active light source optical sensor which means it provides
its own light so that the time of the day will not be a factor affecting the
measurement. There are some environmental variables
that can have an impact on data quality.
If wind is blowing plants sufficiently to change which side of the
leaves the sensor is reading, there can be substantial differences, especially
in crops that may have small hairs or different textures on the undersides of
foliage. Naturally, the sensor does not differentiate between weed and crop
species so care must be taken when weeds are present to assure accurate data.
use after calibration and charging consists of holding the device with the sensor
directed at the foliage, pressing the trigger button, and walking at a steady
pace through the target plot areas maintaining a specific height range of 24”
to 48” (60-120 cm) above the crop canopy (depending on the size and type of the
| Above illustrates the sensor’s oval field of view showing how the size is proportional to height and approximates 10” (25cm) wide at 24” (60cm) above the ground and 20” (50cm) wide at 48” (120cm) above the ground, Trimble. An error message will be displayed on the screen if you are too high or too close to the crop.|
sensors on the instrumentation are emitting brief bursts of red and infrared
light and automatically measuring each type of light that is reflected from the
plant to obtain the NDVI reading. The device will display an NDVI value once
per second during operation and reaches a maximum interval of 60 seconds,
therefore, we want to record at least 10 seconds for each plot to collect a
representative data set. After walking the desired area, release the button and
the sensor will display the final average value of all the readings that were
order to establish favorable results, consistency in the plant population and
agronomics are key components to success.
It is important that only the same crop and relative growth stage be compared.
In other words, taking a reading of one plot at 6 leaf and another at 30
leaf is not an accurate comparison. Intuitively,
comparing a wheat reading with a spinach reading does not provide useful
information. The algorithms in these instruments require at least 50% of the
field of view of the sensor to be covered by vegetation for accurate measure of
“Greenness” that equates to productivity.
Bare ground typically reads 0.13, so less than 50% plant coverage of the
soil in our experience is most useful in evaluating weed control if weeds are
dying or breaking through the program.
If we want % ground cover with plants, we are now using imagery and
color thresholding as discussed in RD4AG’s white paper on Canopy Coverage by
Connor Osgood. For plant productivity
evaluations of crops, we tend to wait for the crop to grow a bit larger before
we start the NDVI assessments in our trials.
Since NDVI also depends on the geometry of illumination and anisotropy
of the target we continue to evaluate crops using the same standard procedure
and hence maintain the position of the target of interest within the swath of
the instrument at a specific range so we have consistency that can be relied
upon to tease out subtle differences in crop performance.