Journal of Sensor Technology, 2013, 3, 42-46 Published Online September 2013 (
Capacitance Sensor for Nondestructive Determination of
Total Oil Content in Peanut Kernels
Chari V. Kandala1*, Rao C. N. Rachaputi2, Daniel O’Connor2
1Agricultural Research Service, United States Department of Agriculture, Dawson, USA
2Center for Plant Science, University of Queensland, Kingaroy, Australia
Email: *
Received May 24, 2013; revised June 24, 2013; accepted July 2, 2013
Copyright © 2013 Chari V. Kandala et al. This is an open access article distributed under the Creative Commons Attribution License,
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
In this work, attempts were made to estimate the total oil content (TOC) in single peanut kernels, using the CI meter
(Chari’s Impedance meter, described below). Mature peanut kernels of selected varieties with a range of oil contents
from 47% to 61% were placed one at a time, between the parallel-plate electrodes of the CI meter, and the impedance
(Z) and phase angle (
) of the system were measured, and capacitance, C was computed at 1, 5 and 9 MHz. After the
measurements, the TOC of each kernel was determined by Soxhlet method. Using the known TOC values, and the cor-
responding C, Z and
values, initially on a calibration group of kernels, calibration equations were developed. Using
the model coefficients from the calibration, the TOCs of kernel samples of 31 diverse peanut genotypes grown in dif-
ferent environments in Australia were determined. The method predicted the TOC values of peanut kernels of 31 peanut
genotypes, within 2% of the Soxhlet values, with an R2 of 0.87 (P < 0.001).
Keywords: Impedance Analyzer; Parallel-Plate Electrodes; Capacitance; Phase Angle; Total Oil Content (TOC);
1. Introduction
The peanut plant is a small annual herb, belonging to the
family of fabaceae of the genus Arachis, and botanically
named as Arachis hypogaea. Some common names are
groundnut, earthnuts, etc. Peanut varieties with high oil
content are preferred in countries where peanut oil is the
predominant cooking oil. Peanut oil could also be a pre-
ferred substrate for bio-diesel production in future. Pea-
nut varieties with low oil content are used in making
peanut snack foods. Recent studies have identified sig-
nificant genetic variation in fatty acid composition, par-
ticularly, content of oleic acid in peanut varieties [1]. A
diet rich in oleic acid is believed to lower cholesterol
levels and reduce the chance of heart disease by reducing
low-density lipoproteins (LDL), while maintaining high-
density lipoprotein (HDL) that slows down occurrence of
atherosclerosis and may reverse the inhibitory effect of
insulin production [2]. Presently, estimation of oil in
peanut kernels involve Soxhlet or Soxtec1 instruments [3]
for extracting oil from a known weight of peanuts, and
calculating the TOC in the test sample. These methods
are costly, laborious, and more importantly involve de-
structive sampling. NIR spectroscopy was used success-
fully for oil analysis in many crops including soybean [4],
sunflower [5], rape seeds [6], canola [7], flax seeds [8].
NIR has also been used to determine peanut fatty acids
on individual peanut kernels [9]. Determination of mois-
ture, oil and fatty acids composition using Near Infrared
Reflectance Spectroscopy in in-shell peanuts was also
attempted earlier [10]. However, NIR methods involve
costly equipment, not always available to a peanut farmer,
or a medium scale peanut processor.
Presently, there are no tools that would measure the
TOC of peanut kernels rapidly, economically, and non-
destructively. Peanuts have to be shelled and cleaned
before TOC is measured, which takes time and resources.
Earlier a simple, low cost instrument, called the CI meter
(Chari’s Impedance meter), was designed and assembled,
that could estimate the moisture content (MC) of in-shell
peanuts (MC range 9% to 20%) and yellow-dent field
corn (MC range 7% to 18%) [11]. In this method a sam-
ple of in-shell peanuts or corn was placed between two
parallel plate electrodes, and the impedance (Z) and
*Corresponding author.
1Mention of company or trade names is for the purpose of description
only and does not imply endorsement by the US Department of Agri-
opyright © 2013 SciRes. JST
phase angle (
) of the system were measured at 1 MHz
and 5 MHz. Using the measured values of Z,
, the
computed capacitance (C), and the MC values obtained
by standard methods, semi-empirical equations were de-
veloped to estimate the moisture content in peanuts and
corn. In the present paper, the design and working of this
low- cost radio frequency based meter that can rapidly,
and nondestructively, estimate the TOC in a single pea-
nut kernel is described. Such an instrument would be
very useful in peanut varietal improvement as well as in
processing plants around the world.
2. Materials and Methods
2.1. CI meter Circuit
For a parallel-plate capacitor with plate area A and sepa-
ration D, the difference in dielectric constants at two fre-
quencies can be defined as:
r1 r2120
 
  (1)
εr1 and εr2 are the dielectric constants of the material be-
tween the plates and C1 and C2 are the capacitance of the
parallel-plate system at the two frequencies. ε0 is the per-
mittivity of free space (8.854 × 1012 farad/m). If the
space between the parallel-plates is filled with a dielec-
tric of the same A and D but with different moisture con-
tents, (C1 C2) would give a good estimate of the water
present in the dielectric. In the case of materials such as
grain and nuts, which do not have regular shapes, two
other parameters, impedance, Z and phase angle, θ were
also measured at 1 and 5 MHz [12]. From the values of Z
and θ, the value of C was computed for each frequency,
and the differences (C1 C
2), (θ1 θ2), and (Z1 Z
were used in a semi-empirical equation to predict the MC.
The phase angle change, (
2) accounted for the loss
factor while the dissipation factor difference, (D1 D
represented the quality factor of the material of the pea-
nuts. While measurements of Z and θ at 1 and 5 MHz
enabled the prediction of moisture content, measure-
ments at 9 MHz had to be included along with 1 and 5
MHz for the determination of TOC. The differences in
the values at the three frequencies, (Z1 Z2), (Z1 Z3),
(θ1 θ2) and (θ1 θ3) were incorporated into an empiri-
cal equation, along with (C1 C
2) and (C1 C
3), from
which the TOC of the sample was calculated. Since, wa-
ter content of the peanut has a profound effect on capaci-
tance, to estimate the oil contents, all samples were dried
to bring the moisture contents to less than 8%.
Frequencies 1, 5 and 9 MHz are generated by crystal
oscillators as shown in the block diagram (Figure 1) for
1 MHz. The circuits for the three frequencies are similar.
These signals are applied to the electrode system alter-
nately by switching through a multiplexer. Initially at 1.0
MHz, the current flowing through this system with an
Rectifier e
Attenuator Phase
Detector e
Oscillator Filter
Comparato Filter
Rectifier e
1 MHz
5 MHz
Sample Holder
9 MHz
Figure 1. Block diagram of the CI meter circuit shown for 1
impedance Z, is fed into an op-amp. The same current
would flow through the feed-back resistor Rr. The output
voltage of the op-amp and the original signal from the
oscillator are rectified and measured as em1 and er1 re-
spectively. The current through Z is calculated as em1/Rr
and the magnitude of the impedance of the parallel-plate
system with sample between them is obtained as |Z1| = Rr
The phase angle at 1 MHz is determined by comparing
the signal emerging out of the op-amp with that of the
original signal, using a comparator and phase detector
that give an output voltage ep1, proportional to the phase
angle θ1 between the two. The computer then switches
the multiplexer to the 5 MHz and impedance |Z2| and
phase angle θ2 are measured. Similarly, at 9 MHz also,
the impedance |Z3|, and phase angle θ3 are measured.
From the values of Z and θ, the real and imaginary parts
of the impedance R and X, at each frequency, are calcu-
lated as R = |Z| Cosθ and X = |Z| Sinθ. The value of ca-
pacitance C of the parallel-plate system with a sample
between them is given as C = 1/2πfX, at each fre-
2.2. Parallel-Plate System
The electrode system used in this study consisted of two
circular plane and parallel brass electrodes, 25-mm in
diameter between which the peanut kernel was held. The
kernel was placed on the lower electrode and held in po-
sition by the upper electrode which can be moved up and
down under a light spring pressure (shown in Figure 2).
The CI meter measured the capacitance, phase angle and
dissipation factor of the parallel-plate system, with a pea-
nut kernel between them, at each of the frequencies 1, 5,
and 9 MHz. A computer program was used to control,
and collect data from the CI meter. The data was logged
on to an excel sheet for further analysis.
Copyright © 2013 SciRes. JST
Figure 2. Parallel-Plate Electrode System. The dial gauze is
used to provide light spring pressure. A single peanut ker-
nel is placed between the plates for the measurement of oil
2.3. Peanut Samples
The peanut varieties used for the study were drawn from
the Australian peanut breeding program based at Kinga-
roy, Queensland. The genotypes were grown using the
recommended practices at the Queensland Department of
Agriculture, Fisheries and Forestry (QDAFF) research
facility at Kingaroy, Queensland, Australia, during No-
vember 2011-May 2012 growing season. At harvest,
fully mature pods were hand-picked for the study. For
calibration of the CI meter, a set of five peanut genotypes,
APB1, APB 2, APB3, APB4 and APB5 were selected
considering the notable variations of TOC among them.
For validation, a total of 31 samples from two inde-
pendent breeding trials (17 entries in set 1 and 14 in set 2)
were used. The two sets of validation samples comprised
of advanced breeding lines including some peanut germ-
plasm used as parents. These entries were grown in the
field during the 2011-12 growing season on diverse soil
types under rain-fed or irrigated environments in the
Wide Bay region of Queensland, Australia.
After harvesting, mature pods were separated from
plant and dried at 35˚C for 3 days to bring the pod mois-
ture content to about 11%. The pods were kept in cold
storage (4˚C) at the QDAFF laboratories, Kingaroy until
further study. Two replicate samples of mature pods were
drawn from each entry and shelled. Single kernels from
each replicate were used for the measurements. After the
measurements were made on the CI meter, each kernel
was processed for determination of Total Oil Content
(TOC) using Soxhlet method [13].
2.4. Measurement
A single peanut kernel of each entry was placed between
the parallel plates of the capacitance sensor shown in
Figure 2. The parallel-plate sensor was connected to the
CI meter, from which the RF signals, applied through
one of the plates, go through the sample, and return
through the second plate into the CI meter. The CI meter
measured the impedance, Z, and phase angle, θ of the
returning signal, first at 1 MHz, as an analog signal. An
A-D (analog to digital) convertor converted these signals
into digital signals, fed them into a lap top programmed
to compute the capacitance, C of the parallel-plate sys-
tem, from the measured values of phase angle and im-
pedance, and store all three values, Z, θ, and C for this
kernel, at 1 MHz. The computer then switched the multi-
plexer to allow 5 MHz signal to go through the parallel-
plates, and the values of Z, θ, and C were measured and
recorded at this frequency. The procedure was repeated
for 9 MHz, also. Five separate measurements were made
on each kernel, to represent five replications. After the
measurements were completed on the CI meter, each ker-
nel was processed for oil analysis, using Soxhlet extrac-
tion method, to determine its total oil content (TOC).
Thus, for each kernel, the average values from the five
repeats were calculated for C, θ and Z, along with the
TOC values, for further analysis.
2.5. Data Analysis
In the samples used for calibration the TOC values ran-
ged from 47% to 61%, representing a significant geno-
typic variation for the TOC. From the capacitance, phase
angle and impedance values, measured at 1, 5, and 9
MHz, and the earlier determined TOC values for the
samples, a regression equation was developed, using the
multiple linear regression (MLR) statistical method [14].
The MLR equation had the following form:
0112213 312
4135 126 13
71 2813
91 2101 3
 
  
  
 
The constants A0 to A10 of Equation (2) were deter-
mined by using the SAS procedures for regression analy-
The values of C, θ and Z at 1, 5 and 9 MHz were
measured for the single kernels of 31 entries used for
validation (i.e. 17 entries in set 1 and 14 in set 2), fol-
lowing similar procedure as described for calibration
samples. With these constants in Equation (2), the TOC
of the validation samples were computed and compared
with the TOC values determined by the standard Soxhlet
3. Results and Discussion
The TOC of the calibration samples varied from 47% to
Copyright © 2013 SciRes. JST
61% representing significant variability for TOC in pea-
nuts. The values obtained for the constants A0….A 10 in
Equation (2) determined by using SAS procedures for
regression analysis of the impedance measurements on
the calibration kernels with the CI meter were:
A6788829, A4531, A0192,
A3035347, A2463551, A546441,
A753 028,A0 00386,A0099,
A157 592,A187 951
.. .
 
The calibration model had an R2 value of 0.95 (Figure
3), and all the terms used in Equation (2) had a probabil-
ity of a greater absolute t value (Pr > |t|) under the null
hypothesis for the variables, less than 0.0001. These con-
stants along with the pooled values of impedance, phase
angle and capacitance were used in Equation (2) to cal-
culate the TOC of each of the 5 entries for calibration of
CI meter. The calculated values were averaged over the
five measurements for each kernel, and were compared
with their respective Soxhlet TOC values and are shown
in Table 1, along with their standard deviations, and dif-
ferences. It could be seen that the differences between
the Soxhlet, and CI meter calculated (average) TOC val-
ues were less than 0.5%. The standard deviations were
Figure 3. Comparison of TOC values determined by the
Soxhlet and CI meter methods for calibration group of pea-
nut varieties.
Table 1. TOC of Calibration samples calculated by Equa-
tion (2) (Average of five measurements for each kernel).
TOC (%) Determined by
S. No.
Soxhlet CI Meter
1 47.13 47.41 0.28 2.05
2 52.32 52.64 0.32 0.66
3 54.85 54.74 0.11 0.94
4 55.84 55.63 0.21 0.53
5 61.04 60.78 0.26 1.18
slightly higher for the lowest and highest TOC values.
The standard error of calibration (SEC)2 was 1.26. The
model coefficients developed from the calibration were
used to predict TOC values for 31 independent samples
drawn from a combination of diverse genotypes and
production environments, The TOCs of the validation
samples were predicted using coefficients in Equation (2)
and averaged over five measurements for each kernel. It
is known that, oil and fatty acids influence genotypic
variability, and genotype by environmental interactions
[15]. It can be seen from Figure 4 that the CI meter is
able to predict the TOCs of single kernels from a diverse
set of peanut genotypes and environments with a rea-
sonable accuracy (R2 = 0.87, P > 0.001). The TOC values
predicted by the CI meter were all within 2% of the Sox-
hlet values, except for one kernel. The difference was
2.15 for that kernel, and this measurement was deleted as
an outlier for the purpose of calculating the standard er-
ror of performance (SEP)3. The SEP was 1.1, comparable
with the SEC of 1.2 for the 30 validation kernels. An R2
of 0.87, and a SEP of 1.1 indicate that the CI meter can
be effectively used to predict the TOC of peanut kernels
rapidly, and non-destructively. Such a tool could be use-
ful for the preliminary screening to estimate the oil con-
tent in peanuts, in peanut breeding programs, or peanut
processing plants. The sensitivity of the method can be
Figure 4. Comparison of TOC values determined by the
Soxtec and CI meter methods for two sets of peanut varie-
2SEC =
n is the number of observations, p
is the number of variables in the regression equation with which the
calibration is performed, and eiis the difference between the observed
and reference value for the ith observation.
3SEP =
where n is the number of observations,
ei is the difference in the moisture content predicted and that deter-
mined by the reference method for the ith sample, and eis the mean
of ei for all of the samples.
Copyright © 2013 SciRes. JST
Copyright © 2013 SciRes. JST
improved by fine tuning the scanning frequencies, opti-
mizing the area of parallel-plates, and also by improving
the accuracy of the Soxhlet method.
4. Conclusion
This nondestructive and rapid method would be useful to
the peanut breeders and the industry, for initial screening
of the newly developed varieties in detecting the TOC
levels. This is a physical method, and involves no chemi-
cal process that is cumbersome and time consuming. The
CI meter is a relatively low-cost instrument within the
reach of the peanut farmer and industry. This informa-
tion could be useful in categorizing the peanut varieties
for appropriate usage. Knowing the TOC of the different
breeds would help the breeders to quickly determine the
suitability of the varieties for large scale plantation.
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