Fourier transform near infrared reflectance (FT-NIR) spectroscopy has been used successfully to measure soluble
solids content (SSC) in citrus fruit. However, for practical implementation, the technique needs to be able to compensate
for fruit temperature fluctuations, as it was observed that the sample temperature affects the near infrared reflectance
spectrum in a non-linear way. Temperature fluctuations may occur in practice because of varying weather conditions or
improper conditioning of the fruit immediately after harvest. Two techniques were found well suited to control the
accuracy of the calibration models for soluble solids with respect to temperature fluctuations. The first, and most
practical one, consisted of developing a global robust calibration model to cover the temperature range expected in the
future. The second method involved the development of a range of temperature dedicated calibration models. The
drawback of the latter approach is that the required data collection is very large. The global temperature calibration
model avoids temperature-sensitive wavelengths for the calibration of SSC. Global temperature models are preferred
above dedicated temperature models because of the following shortcomings of the latter. For each temperature, a new
calibration model has to be made, which is time-consuming.
Watermelon is a popular fruit in the world. Soluble solids content (SSC) is major characteristic used for assessing watermelon internal quality. This study was about a method for nondestructive internal quality detection of watermelons by means of visible/Near Infrared (Vis/NIR) diffuse transmittance technique. Vis/NIR transmittance spectra of intact watermelons were acquired using a low-cost commercially available spectrometer when the watermelon was in motion (1.4m/s) and in static state. Spectra data were analyzed by partial least squares (PLS) method. The influences of different data preprocessing and spectra treatments were also investigated. Performance of different models was assessed in terms of root mean square errors of calibration (RMSEC), root mean square errors of prediction (RMSEP) and correlation coefficient (r) between the predicted and measured parameter values. Results showed that spectra data preprocessing influenced the performance of the calibration models and the PLS method can provide good results. The nondestructive Vis/NIR measurements provided good estimates of SSC index of watermelon both in motion and in static state, and the predicted values were highly correlated with destructively measured values. The results indicated the feasibility of Vis/NIR diffuse transmittance spectral analysis for predicting watermelon internal quality in a nondestructive way.
Near-infrared (NIR) spectroscopy has become a very popular technique for the non-invasive assessment of intact fruit. This work presents an application of a low-cost commercially available NIR spectrometer for the estimation of soluble solids content (SSC) of Chinese citrus. The configuration for the spectra acquisition was used (diffuse transmittance), using a custom-designed contact optical fiber probe. Samples of Chinese citrus in deferent orchard, collected over the 2005 harvest seasons, were analyzed for soluble solids content (Brix). Partial least squares calibration models, obtained from several preprocessing techniques (smoothing, multiplicative signal correction, standard normal variate, etc), were compared. Also, the short-wave (SW-NIR) spectral regions were used. Performance of different models was assessed in terms of root mean square of cross-validation, root mean square of prediction (RMSEP) and R for a validation set of samples. RMSEP of 0.538 with R = 0.896 indicate that it is possible to estimate Chinese citrus SSC (Brix value), by using a portable spectrometer.