349
xLanted at
:ions and
months late
lonirrigated
.5 June to 15
. the corn
:ion at 200
luction.
conducted at
k3 long.
;rtic
die North
)°W) on a
stolls. Both
Lants/ha in
lurth was
Ly planted
ition of a
i the rate of
lead-sized
300 plant/ha
if mepiquat
and 25 g/ha
and at first
Lning densely
the
aintained as
nations of
. 1983 at the
L in rows
nieved two
3 197
), and
66 m apart.
s/m 2 .
D) plots each
Twelve
hat the
significant
. Rainfall
y 100 mm all
each term in
three
segments of
4 x 0.6 m)
tentative
of corn were
lite per
ted in Table
d frcm
1982)
(Table 1)
J., 1981)
he 630 to 690
! infrared
igth interval.
: view and was
centered over
>nses plus
>servations
r for each of
luced by the
¡1).
the
'9) and
Richardson
these
based on the
ndville clay
PVI = 0.628(RIR) - 0.778(RED) - 2.537 based on the
soil line
RED = -3.26 + 0.807(RIR) for the Hidalgo sandy
clay loam.
Photosynthetically active radiation (PAR) incident
on (Io)' transmitted (T) through, reflected (R)
from the composite canopy-soil backgrounds, and from
the bare soil (R s ) provided the data for absorbed
PAR, termed APAR, and defined as (I 0 -'P-R+R S T)/I 0 =
d-T’-R'+Rs'T') (Hipps et al., 1983; Gallo
et al., 1985) wherein
I D = the downward PAR flux density at the top of
the canopy
T = the downward PAR flux density at the bottom
of the canopy
R = the upward PAR flux density at the top of the
canopy (the PAR reflectance of the composite
plant and soil background scene)
Rg = the reflectance of the soil beneath the
canopy, and the primes indicate that all
values are normalized to I Q .
For the field measurgments T, R, and Rs were
measured with LI-COR ^ line quantum
sensors (LI 191SB) and I Q was measured with a
quantum sensor (LI 190SB). A line quantum sensor
was inserted below the canopies perpendicular to the
rows (wheat, cotton) and obliquely middle-to-middle
(corn) for the T measurements while the sensor for
measuring R frcm the canopy plus soil was inverted
30 cm above the canopies and parallel to the sensor
below the canopies. The Rs term was measured by a
line quantum sensor inverted 30 cm above a small
area in the plots where the plants had been removed
soon after emergence. The LI 190SB sensor was moved
frcm plot to plot on a 2-m tall stand that was
leveled at each stop. The sensor outputs for T, R,
and I D and the time of the observations were all
electronically logged simultaneously. Care was
taken to keep all sensors level and to avoid shading
the sensor measuring T by the one measuring R.
The data were fit to the ccmmonly used exponential
relation, ^^2 = (1-Ae“ BIAI /cosZ 2)
wherein A is an arbitrary coefficient, B is the
extinction coefficient, and cos Z 2 adjusts LAI for
the path length through the canopy at the time of
the APAR observations.
At the time of each sampling, up to twto days was
required to determine LAI, one day to make the PAR
sensor observations, and about 1 hour to make the
reflectance factor observations. Thus it was
impossible to make all the necessary observations on
the same day. Table 1 summarizes the dates on which
the various measurements were made for each
experiment. When data frcm the various sensors were
merged, the sample date was considered to be that of
the PAR absorption data and they were used as
measured. For pairing observations, the VI and LAI
data were plotted versus time and the VI and LAI
estimates interpolated to the dates of the PAR
measurements.
The LAI samples provided information on the
aboveground biomass by plant parts for those
sampling dates, while yield canponents were
determined on the harvest samples.
Solar zenith angle was calculated frcm latitude
and longitude of the experimental sites using day
of year and time of day of the observations in
ephimeris equations. t
Equations [1 ] and [2 ] were used in analyzing
the data. That is, VI and APAR data taken at
different times of day were accomodated by the solar
zenith angle adjustment to LAI incorporated into the
terms of these equations.
■^Mention of trade names does not infer
preferential treatment nor endorsement by the U.S.
Department of Agriculture over similar products
available frcm other sources.
6 RESULTS
Data presented are paired wath the PAR observations
since they were available on the fewest number of
dates (Table 1).
Solar zenith angles were small on all dates for
corn—because measurements were made near solar noon
in June and July and our latitude, 26.2°N, is close
to the Tropic of Cancer—moderate for cotton, and
wide-ranging for wheat. However, the solar zenith
angle adjustments in LAI were made for all crops on
all dates for uniformity of analysis.
Expressions for each of the three terms of
equation [1 ] are summarized in Table 3 for each
of the three crops. Results for two vegetation
indices, the normalized difference (ND) and the
perpendicular vegetation index (PVI) are given as
exponential, power, or linear expressions. For the
first term on the left, the coefficients of
determination for the dependence of LAI on PVI are
0.92 or greater for all three crops, compared with
0.77 to 0.96 when expressed in terms of ND. The
results demonstrate that there is a close
association between LAI and the vegetation indices
as calculated from reflectance factor measurements
in the visible and reflective infrared wavelengths,
for all crops. f
The second term on the left in equation [1 ]
estimates absorbed photosynthetically active
radiation (APAR) frcm leaf area indices adjusted for
solar zenith angle, LAI/cosZ2* Results are
presented for both the widely accepted
(Charles-Edwards, 1982; Pearson, 1984) exponential
form and a power expression. Again, r 2 ^ 0.93 for
the exponential form and 0.89 for the power form
for all crops. The extinction coefficients are
0.514, 0.540, and 0.347 for cotton, wheat, and corn,
respectively. Corn had a more open canopy than the
other crops and consistently transmitted more PAR at
a given LAI. Pooling the observations for Aim and
Nadadores cultivars of wheat may have lowered the
r 2 because we found in unreported analyses that
their extinction coefficients differ significantly.
■Jhe results for the right hand side of equation
[1 ] in Table 3 demonstrate that APAR was
estimated almost as well for cotton and corn from
the vegetation indices (r 2 = 0.75 to 0.99) as frcm
the LAI. For wheat, the r 2 were lower, 0.48 to
0.83. PVI gave a closer relation in every case than
did ND. For wheat ND increased rapidly frcm its
value of 0.2 for bare soil to 0.83 by the time LAI
was 1. Consequently it was insensitive to increases
in LAI beyond 1.0 where most of the APAR
observations were taken and APAR was still
increasing as LAI increased. In contrast, PVI
increased at a diminishing rate as LAI increased.
Figures 1, 2, and 3 display the data by crop for
each term in equation [1']. In Figure 1 (1st term)
and Figure 3 (right side term) the data are
presented in terms of PVI. For all Figures the best
fit curves for the equations given in Table 2 are
superimposed on the data displays. The data are
restricted, as in Table 2 to the dates when the data
for all three variables LAI, VI, and APAR were
available for pairing. The data for PVI (Figure 1)
and APAR (Figure 2) are both asymptotic to the LAI
axis. The result is that the APAR vs PVI data in
Figure 3 appear to be nearly linear; coefficients of
determination for a linear fit in Figure 3 were
0.924, 0.825, and 0.969 for cotton, wheat, and corn
compared wath 0.969, .835, and .986 for the power
form. Asrar, et al. (1984) reported a linear
relation between APAR and the normalized difference
vegetation index whereas Gallo et al. (1985) related
APAR to the RIR/RED ratio, ND, and greenness (GR)
vegetation indices by quadratic expressions.
7 SUMMARY
The plant physiological, agroncmic, and
