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 ran...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 (q) 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 corresponding C, Z and q 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 different 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).展开更多
An electronic method to estimate the moisture content (MC) of dry fruits by measuring the impedance (Z) and phase angle (θ) of a cylindrical parallel-plate capacitor with dry fruit sample between the plates, using a ...An electronic method to estimate the moisture content (MC) of dry fruits by measuring the impedance (Z) and phase angle (θ) of a cylindrical parallel-plate capacitor with dry fruit sample between the plates, using a CI meter (Chari’s Impedance meter) at 1 and 9 MHz is described. Capacitance C was derived from Z and θ, and using the C, θ, and Z values of a set of dried cherries, whose MC values were later determined by the vacuum hot air-oven method, a calibration equation was developed. Using this equation, and their measured C, θ, and Z values, the MC of a group of cherries, not used in the calibration, was predicted. The predicted values were compared with their air-oven values. Similar predictions were done using the same method on dried blueberries. The method worked well with a good R2 value, and showed a low standard error of prediction (SEP) in the measured MC range between 5% and 30% for cherries, and 9% and 22% for blueberries.展开更多
It was found earlier that moisture content (MC) of intact kernels of grain and nuts could be determined by Near Infra Red (NIR) reflectance spectrometry. However, if the MC values can be determined while the nuts are ...It was found earlier that moisture content (MC) of intact kernels of grain and nuts could be determined by Near Infra Red (NIR) reflectance spectrometry. However, if the MC values can be determined while the nuts are in their shells, it would save lot of labor and money spent in shelling and cleaning the nuts. Grain and nuts absorb low levels of NIR, and when NIR radiation is incident on them, a substantial portion of the radiation is reflected back. Thus, studying the NIR reflectance spectra emanating from in-shell peanuts, an attempt is made for the first time to determine the MC of in-shell peanuts. In-shell peanuts of two different market types, Virginia and Valencia, were conditioned to different moisture levels between 6% and 26% (wet basis), and separated into calibration and validation groups. NIR absorption spectral data from 1000 nm to 2500 nm in 1 nm intervals were collected from both groups. Measurements were obtained on 30 replicates within each moisture level. Reference MC values for each moisture level in these groups were obtained using standard air-oven method. Partial Least Square (PLS) analysis was performed on the calibration data, and prediction models were developed. The Standard Error of Calibration (SEC), and R2 of the calibration models were computed to select the best calibration model. The selected models were used to predict the moisture content of peanuts in the validation sets. Predicted MC values of the validation samples were compared with their standard air-oven moisture values. Goodness of fit was determined based on the lowest Standard Error of Prediction (SEP) and highest R2 value obtained for the prediction models. The model, with reflectance plus normalization spectral data with an SEP of 0.74 for Valencia and 1.57 for Virginia type in-shell peanuts was selected as the best model. The corresponding R2 values were 0.98 for both peanut types. This work establishes the possibility of sensing MC of intact in-shell peanuts by NIR reflectance method, and would be useful for the peanut and allied industries.展开更多
文摘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 (q) 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 corresponding C, Z and q 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 different 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).
文摘An electronic method to estimate the moisture content (MC) of dry fruits by measuring the impedance (Z) and phase angle (θ) of a cylindrical parallel-plate capacitor with dry fruit sample between the plates, using a CI meter (Chari’s Impedance meter) at 1 and 9 MHz is described. Capacitance C was derived from Z and θ, and using the C, θ, and Z values of a set of dried cherries, whose MC values were later determined by the vacuum hot air-oven method, a calibration equation was developed. Using this equation, and their measured C, θ, and Z values, the MC of a group of cherries, not used in the calibration, was predicted. The predicted values were compared with their air-oven values. Similar predictions were done using the same method on dried blueberries. The method worked well with a good R2 value, and showed a low standard error of prediction (SEP) in the measured MC range between 5% and 30% for cherries, and 9% and 22% for blueberries.
文摘It was found earlier that moisture content (MC) of intact kernels of grain and nuts could be determined by Near Infra Red (NIR) reflectance spectrometry. However, if the MC values can be determined while the nuts are in their shells, it would save lot of labor and money spent in shelling and cleaning the nuts. Grain and nuts absorb low levels of NIR, and when NIR radiation is incident on them, a substantial portion of the radiation is reflected back. Thus, studying the NIR reflectance spectra emanating from in-shell peanuts, an attempt is made for the first time to determine the MC of in-shell peanuts. In-shell peanuts of two different market types, Virginia and Valencia, were conditioned to different moisture levels between 6% and 26% (wet basis), and separated into calibration and validation groups. NIR absorption spectral data from 1000 nm to 2500 nm in 1 nm intervals were collected from both groups. Measurements were obtained on 30 replicates within each moisture level. Reference MC values for each moisture level in these groups were obtained using standard air-oven method. Partial Least Square (PLS) analysis was performed on the calibration data, and prediction models were developed. The Standard Error of Calibration (SEC), and R2 of the calibration models were computed to select the best calibration model. The selected models were used to predict the moisture content of peanuts in the validation sets. Predicted MC values of the validation samples were compared with their standard air-oven moisture values. Goodness of fit was determined based on the lowest Standard Error of Prediction (SEP) and highest R2 value obtained for the prediction models. The model, with reflectance plus normalization spectral data with an SEP of 0.74 for Valencia and 1.57 for Virginia type in-shell peanuts was selected as the best model. The corresponding R2 values were 0.98 for both peanut types. This work establishes the possibility of sensing MC of intact in-shell peanuts by NIR reflectance method, and would be useful for the peanut and allied industries.
