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Near-infrared (NIR) spectroscopy was used to measure the moisture content (MC) of in-shell Virginia and Valencia type peanuts. NIR spectral data from 400 to 2500 nm were collected on calibration samples from Virginia type peanuts ranging in moisture from 6% to 22%. Calibration models to estimate MC were developed using raw and derivative data, and an appropriate model was selected based on parameters such as standard error of calibration and prediction. The ability to predict MC in different types of in-shell peanuts with a single calibration model would save time and labor, otherwise needed for multiple calibrations, and could be useful in developing a commercial instrument. [ABSTRACT FROM AUTHOR]

Peanuts are indeterminate crops and do not mature evenly. Thus, it is difficult to decide the optimal time of harvest. Pod maturity is currently determined by the hull scrape method in conjunction with the maturity profile board (MPB) for estimating the "days until digging". The method is based on the known correlation between maturity level and pod mesocarp color, which is a subjective assessment. The objective of this research was to develop visible (Vis; 400 to 750 nm) and/or visible plus shortwave near-infrared (Vis/NIR; 400 to 1100 nm) reflectance models to predict maturity classes on a pod-by-pod basis. This would allow estimation of the optimum days to dig the crop. Peanuts ('Georgia Green') were harvested on five dates in 2008 and analyzed by the hull scrape method and Vis/NIR reflectance spectroscopy. Spectra from the side of the pod basal segment (N = 754) and from the saddle of the dorsal segment (N = 625) of each pod were analyzed in the Vis and Vis/NIR regions. Partial least squares regression was used to regress MPB maturity column numbers on spectra of pods from three sampling dates. Calibration regression error for MPB class column number was higher for saddle spectra. Based on the calibrations, placement of the pods on the profile board could differ by 1.5 columns, which could alter the estimate of days until digging by ±3 days. Validations of all spectroscopic models were equal to and/or 3 to 7 days longer than the corresponding MPB estimates of days until digging. Separation of the maturity classes was primarily due to the broad and increasing absorbance at 640 nm as the pod matures. [ABSTRACT FROM AUTHOR]

NIR spectroscopy was used to measure the moisture content (MC) of Virginia and Valencia type in-shell peanuts. Peanuts were conditioned to various moisture levels between 7% and 26% (wet basis), and the MC was verified using the standard oven method. Sample from the various moisture levels were separated into two groups, as calibration and validation. NIR absorption spectral data from 400 nm to 2500 nm were collected using peanuts within the calibration and validation sample sets. Measurements were obtained on 30 replicates within each moisture level. Partial least squares (PLS) analysis was performed on the calibration set, and models were developed using the raw spectral data and its derivative function data. The standard error of calibration (SEC) and R² of the calibration models were calculated to select the best calibration model for each peanut market type. Both Valencia and Virginia types gave an R² value of 0.99 for the derivative spectral data treatment as well as for the raw data. The selected models were used to predict the moisture content of peanuts in the validation sample set. Predicted and reference moisture contents were compared. Relative percent deviation (RPD) and standard error of prediction (SEP) were calculated to validate the goodness of fit of the prediction model The raw reflectunce spectra model gave an RPD of 5.55 with a corresponding SEP of O.97 for Valencia type peanuts, which is an indicator that the model is good for quality control and analysis. For Virginia type peanuts, the derivative reflectance spectra model gave the highest RPD value of 5. 75 and the lowest SEP of O. 771. Thus, these two models were selected for the respective peanut types as the best models for prediction of moisture content. [ABSTRACT FROM AUTHOR]

There are some commercial instruments available that use near-infrared (NIR) radiation measurements to determine the moisture content (MC) of a variety of grain products, such as wheat and corn, without the need of any sample grinding or preparation. However, to measure the MC of peanuts with these instruments, the peanut kernels have to be chopped into smaller pieces and filled into the measuring cell This is cumbersome, time consuming, and destructive. An NIR reflectance method is presented here by which the average MC of about 100 g of whole kernels could be determined rapidly and nondestructively. The MC range of the peanut kernels tested was between 8% and 26%. Initially, NIR reflectance measurements were made at 1 nm intervals in the wavelength range of 1000 to 1800 nm, and the data were modeled using partial least squares regression (PLSR). The predicted values of the samples tested in the above range were compared with the values determined by the standard air-oven method. The predicted values agreed well with the air-oven values, with an R² value of 0.93 and a standard error of prediction (SEP) of 1.18. Using the PLSR beta coefficients, five key wavelengths were identified, and MC predictions were made using multiple linear regression (MLR). The R² and SEP values of the MLR model were 0.91 and 1.09, respectively. Both methods performed satisfactorily and, being rapid, nondestructive, and noncontact, may be suitable for continuous monitoring of MC of grain and peanuts as they move on conveyor belts during their processing. [ABSTRACT FROM AUTHOR]

Moisture content (MC) in peanuts is an important parameter to be measured and monitored at various stages in the peanut industry. In previous research, peanut MC was estimated by placing a sample between a set of parallel-plate conductors to measure capacitance and phase angle of the system with commercially available, expensive impedance analyzers. In this work, a low-cost impedance analyzer called the CI meter (Chari's impedance meter) was designed and developed to measure impedance and phase angles at frequencies 1, 5, and 9 MHz using the parallel-plate sensor. The average MC values predicted by the CI meter for peanut samples harvested during two different years were compared with the standard air-oven values. In-shell peanut sample MC ranged between 6% and 23%. Over 90% of estimated in-shell MC values were within 1% of the air-oven values. Ability to determine the average MC of in-shell peanuts without shelling and cleaning them can be of considerable use in the peanut industry. [ABSTRACT FROM AUTHOR]

Two methods for rapidly determining the moisture content of single peanut kernels (Arachis hypogaea L.), were compared with a standard forced-air oven method to evaluate their performance. One method was based on estimating the moisture content from the measurement of capacitance and phase angle of a parallel-plate capacitor with a single peanut held between the plates. These measurements were made at two frequencies (1.0 and 4.5 MHz). The other method was a DC conductance measurement on a single peanut as it passed between two crushing-roller electrodes. This method is used in a commercial instrument presently available. Moisture content was determined by these two methods and by the standard overt method on 30 individual peanut kernels randomly selected from each of six sample lots with moisture contents ranging from 6% to 16%, wet basis. Moisture content measurements obtained using the capacitance and the conductance methods were in agreement with the standard oven values to an acceptable accuracy for over 80% of the samples tested. A distinct advantage of the capacitance method is that it is nondestructive. [ABSTRACT FROM AUTHOR]

Measuring the moisture content of peanuts without shelling the peanuts, particularly during buying/selling and drying, would be beneficial to the peanut industry. Previous research has shown that radio frequency (RF) impedance measurements of capacitance (C) and phase angle (0) using a parallel-plate system could be used to estimate the moisture content (MC) of a single in-shell peanut. This method was extended to determine the average MC of a small sample of peanut pods accommodated between the plates. For both single pods and small samples, the predicted MC values were within 1% of the standard air-oven values for over 85% of the samples tested in the moisture range between 5% and 22%. The current research discusses extending the measurement system to predict the average MC of in-shell peanuts in bulk quantities (about 200 g) from similar capacitance and phase angle measurements at 1 and 9 MHz. The parallel-plate system used in previous research was modified and fitted into a non-conducting cylindrical sample holder. [ABSTRACT FROM AUTHOR]

An assessment was made of estimating the moisture content (mc) of single peanut pods (in-shell peanuts) by measuring the complex impedance of a parallel-plate capacitor with a single pod between the plates. Capacitance (C), phase angle (θ) and/or dissipation factor (D) were measured at 1.0 and 5.0 MHz, and the measured values at these two frequencies were used in a derived empirical equation to calculate the mc. Previous research had determined that the mc of single and small samples of shelled peanuts (kernels) could be determined by similar measurements at 1 and 4.5 MHz. In this paper, the mc of the pods tested was between 5% and 25%. The predicted mc of the pods was within 1% of the standard air-oven values for about 85% of the single pods. [ABSTRACT FROM AUTHOR]