Use of near infrared spectroscopy for estimating moisture content in Brazilian cherry ( Eugenia uniflora L.) seeds submitted to dehydration

Background: The determination of seed moisture content is of utmost importance for the evaluation of its quality. Near-infrared (NIR) spectroscopy has been successfully applied to estimate properties of biological materials. However, studies using this technique on forest seeds are still scarce. Thus, the aim of this study was to explore the potential of NIR spectroscopy for estimating the moisture content of E. uniflora seeds. NIR spectra were obtained using optical fiber from 100 individual seeds that were dehydrated in silica gel for 2, 7, 14, and 21 days. Subsequently, the seeds were subjected to the moisture test by the oven method, and had moisture contents of 52.4%, 41.7%, 33.1%, 21.8%, and 18.1%, respectively. Results: Principal component analysis (PCA) of the spectral signatures explained 100% of the data variability. The moisture content was associated with the spectra by partial least squares regression (PLS-R) and the predictive model presented a coefficient of determination in cross-validation (R2cv) 2 cv) of 0.88 and the root mean square error of cross-validation (RMSEcv) was 5.43%. Conclusion: The statistics associated with the models indicate that NIR spectroscopy has potential for estimating the moisture content of E. uniflora seeds.