(rolling) (colliding) (clicking) – [Kristy] Precision technology’s growing in popularity for
monitoring nutrient content in crops and it’s being applied to improve nutrient use efficiency. This video provides an
overview of an NDVI sensor called a GreenSeeker that can be useful for monitoring nitrogen in growing crops. This video will provide
an introduction of NDVI. We’ll discuss NDVI’s
importance to nitrogen. And we’ll describe how to
use a handheld NDVI sensor. NDVI stands for Normalized
Difference Vegetation Index. More simply, NDVI sensors are monitors that are used to detect light
emissions from vegetation. Essentially, they measure
the amount of light that is absorbed by a plant and compare it to the amount that is reflected. Here’s how NDVI works. Plants use chlorophyll to absorb light and create energy during the
process of photosynthesis. As light hits the chlorophyll molecules the plant absorbs red and blue wavelengths of light and it reflects
green light as well as near infrared light. Although our eyes cannot
see the near infrared light, green light is
visible and its reflection is the reason why plants appear green when we look at them. NDVI sensors are designed
to detect near infrared wavelengths and using them is becoming a standardized way to
measure healthy vegetation because healthier,
greener plants will emit more green and near infrared
wavelengths of light than sick or dying leaves that have less chlorophyll and are brown in color. One practical use of NDVI sensors is to monitor nitrogen
content in growing crops. Nitrogen is a main nutrient needed for vegetative growth and
chlorophyll production. We are most familiar with it as a building block of amino acids and protein. However, nitrogen is
also a main structural component in chlorophyll. The center of each chlorophyll molecule has four nitrogen atoms
surrounding a magnesium atom at the center. Because of this structure, nitrogen is an essential nutrient
to help plant convert, absorb sunlight into energy
during photosynthesis. Because of this, NDVI sensors are useful for estimating the amount of nitrogen that spring cover crops will return to the soil at termination. NDVI sensors can be mounted on the field equipment or attached to
Unmanned Aerial Vehicles which are also called UAVs or drones. However, a small handheld NDVI sensor is the most practical
for small plot monitoring or standard field checks. The GreenSeeker handheld
sensor is a portable battery-operated NDVI
sensor that is useful for monitoring nitrogen
in cover crop biomass. It is equipped with a
light-detecting sensor and a finger trigger. Using the GreenSeeker is easy. Simply hold out the device
at about waist level, walk it over the crop
stand you are monitoring. The sensor will detect near infrared light from the biomass and
will present an average reading when you release
your finger from the trigger. Here’s a video demonstrating
how that works. NDVI values range from negative one to positive one, where negative one would indicate pure water. The GreenSeeker is not sensitive enough to detect negative values,
so it begins at zero. Zero would indicate no vegetation as shown by the reading on the black tabletop and also on bare land. And anything approaching positive one indicates green vegetation. High NDVI values indicate green healthy vegetation,
where lower NDVI values indicate little to no vegetation. Because it is detecting greenness the GreenSeeker will detect bare soil and flowers as low NDVI values. In the previous slide
we saw that it read zero with no vegetation, but here it is giving a low reading of 0.31
when soil cover is patchy with lots of bare spots. It is also influenced when cover crops like canola are flowering
since it does not detect the yellow
flowers, giving a similar reading at 0.33. Unhealthy crops or those
deficient in nutrients or those that are starting to lignify and (indistinct) would have
lower readings similar to these. Once an average NDVI number is obtained for a field it can be compared to the nitrogen prediction curves to give an estimate of nitrogen contributions in the form of pounds of N per acre. These calibration curves
are specific to cover crops in Pennsylvania
and therefore can only be used on crops in this specific area. They were developed as part of a long-term cover crop research trial. You’ll also notice that
they differ depending on the different types
of covers that are grown. The types here include
legumes and mixtures, rye, and triticale and wheat. In this example, the
NDVI reading is at 0.84 on a legume cover crop mixture. So first, locate 0.84 on the X axis and go up the solid line curve
for legumes and mixtures. Then follow it across to the Y axis and you will see that this cover crop has approximately 125
pounds of N per acre. However, 125 pounds of N per acre is not what’s available
to the following crop since that cover crop biomass must undergo mineralization to become plant-available. Mineralization is very
difficult to estimate accurately since it is strongly influenced by a combination of variable factors such as the carbon to
nitrogen ratio of the crop, soil type, (indistinct)
days, and soil moisture and temperature. Despite these challenges,
knowing the nitrogen estimate of the cover
crop before termination is very helpful. This information can help
determine when to kill the cover crop and it
can be used in decision tools that help determine
nitrogen mineralization. More videos are coming
that will help examine these details further
to better help estimate nitrogen availability and mineralization. So in summary NDVI is
used to monitor greenness in plants based on its
chlorophyll content. These handheld sensors
are therefore useful for monitoring nitrogen in cover crops which is also related
to chlorophyll content. Cover crop calibration curves exist but they are specific for Pennsylvania and should only be used in this area. Although it provides a good estimate of the amount of nitrogen in a cover crop more information is needed to accurately determine how much
nitrogen is being supplied to the following crop. However, this information is still very valuable to know and can help improve our understanding about nitrogen dynamics and its relationship in agroecosystems.