Application of NIR reflectance spectroscopy on determination of moisture content of in-shell peanuts: a non-destructive analysis.

摘要

NIR spectroscopy was used to measure the moisture content (MC) of Virginia and Valencia type in-shell groundnuts. Groundnuts were conditioned to various moisture levels between 7 and 26% (wet basis) and the MC was verified using the standard oven method. Samples from the various moisture levels were separated into 2 groups, as calibration and validation. NIR absorption spectral data from 400 to 2500 nm were collected using groundnuts within the calibration and validation sample sets. Measurements were obtained on 30 replicates within each moisture level. Partial least squares 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 and R2 of the calibration models were calculated to select the best calibration model for each groundnut 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 groundnuts 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 reflectance spectra model gave an RPD of 5.55 with a corresponding SEP of 0.97 for Valencia type groundnuts, which was an indicator that the model was good for quality control and analysis. For Virginia type groundnuts, the derivative reflectance spectra model gave the highest RPD value of 5.75 and the lowest SEP of 0.771. Thus, these 2 models were selected for the respective groundnut types as the best models for prediction of moisture content.