January 2022 - 37

Figure 2. Tuber shapes from different areas of the field are different.
bands (~ 3-10 nm), which can capture fine
absorption features of crop nutrients.
So far many studies have indicated that
remote sensing can be effectively applied
to predicting crop parameters/variables,
such as leaf area index, biomass, foliar N
concentration, etc.
The methods used to predict/model
crop traits mainly focus on building
predicting algorithms between spectral
signals and field measurements. A
typical model predictor is vegetation
indices (VI), which are mathematical
combinations of reflectance at two
or more spectral bands. For example,
normalized difference vegetation index
(NDVI) has been widely used in previous
studies due to its simple application
to monitoring vegetation dynamic at
regional and global scales.
We have studied on three machine
learning models (decision tree (DT),
support vector machine (SVM) and
random forest (RF)) that used NDVI
to predict the N status and final yield
of four potato cultivars (two russets
including Silverton and Lakeview
Russet, two chippers including
Snowden and Hodag) over two growing
seasons in 2018 and 2019.
Our preliminary results indicated that
NDVI has great potential of predicting
the potato N status indicated by petiole
NO3
-N, whole leaf total N, or whole
vine total N as well as the end-of-season
total yield. We used R2
that ranges from
0 to 1 to measure goodness-of-fit for
the models. The higher the R2
, the
better the prediction. It is considered to
be a very good prediction if R2
is higher
than 0.75.
Under both VRI systems, tubers from
the wettest area had lower specific
gravity compared to those from the
driest and average areas, and the
difference under the nozzle control
system was significant (Table 1).
Figure 2 showed that tubers from
the wettest area of each field had
significantly higher length to width
ratio. Correspondingly, there was higher
STORAGE
PACKAGING
PROCESSING
R
POTATO
-
HANSEN-RICE, INC. leverages an integrated design-build approach by providing
value to construction projects through a full range of Program Management,
Design & Engineering, Pre-Construction and Construction solutions.
(208) 465-0200
www.hansen-rice.com
Spudman * January 2022
35
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http://www.hansen-rice.com

January 2022

Table of Contents for the Digital Edition of January 2022

January 2022 - 1
January 2022 - 2
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