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Aboveground biomass of sugar beet influences tuber growth and sugar accumulation. Thus, accurate, rapid, and non-destructive technique of biomass estimation is important to optimize the crop management practices to attain the required aboveground biomass to support high tuber yields and optimal sugar content. The current research aimed to evaluate the performance of hyperspectral indices and band depth analysis, to remotely assess the aboveground biomass in sugar beet. The biomass and hyperspectral reflectance were collected at different growth stages in experimental and farmers’ fields. The model development was based on sugar beet plants sampled at various times during the growing period subject to seven nitrogen rates. The results showed that accuracy of biomass estimation was greater when using vegetation indices involving red edge bands (680–740 nm) as compared to that using the red light-based indices. Four types of optimized band depth information (band depth, band depth ratio, normalized band depth index, and band depth normalized to band area) involving the red edge further increased the accuracy of biomass estimation. This study demonstrated as the sugar beet biomass increased towards later growing period, biomass estimation using red light-based vegetation indices were less accurate as compared to that using band depth analysis in the vicinity of the red edge.

Nondestructive method of measuring soluble solids content (SSC) of citrus fruits was developed using Fourier transform near infrared reflectance (FT-NIR) measurements collected through optics fiber. The models describing the relationship between SSC and the NIR spectra of citrus fruits were developed and evaluated. Different spectra correction algorithms (standard normal variate (SNV), multiplicative signal correction (MSC)) were used in this study. The relationship between laboratory SSC and FT-NIR spectra of citrus fruits was analyzed via principle component regression (PCR) and partial least squares (PLS) regression method. Models based on the different spectral ranges were compared in this research. The first derivative and second derivative were applied to all spectra to reduce the effects of sample size, light scattering, instrument noise, etc. Different baseline correction methods were applied to improve the spectral data quality. Among them the second derivative method after baseline correction produced best noise removing capability and yielded optimal calibration models. A total of 170 NIR spectra were acquired; 135 NIR spectra were used to develop the calibration model; the remaining spectra were used to validate the model. The developed PLS model describing the relationship between SSC and NIR reflectance spectra could predict SSC of 35 samples with correlation coefficient of 0.995 and RMSEP of 0.79 degrees Brix.

A low-cost commercially available Visible/Near Infrared (Vis/NIR) spectrometer was fitted with special light source and fiber optics to measure Vis/NIR diffuse transmittance spectra in intact watermelons. With this device the potential of the diffuse transmittance method to determine the Brix value in watermelon was examined. To reduce the fruit size effect which affected the spectra, the 2nd derivative spectra were normalized by being divided by 2nd derivative value at 827nm, which had a high correlation to the volume of the watermelon. 75 “ZaochunHongyu (ZH) ” watermelons which were purchased from the local fruit market were used in the experiment. 50 watermelons were used for calibration and the others for prediction. Partial least squares (PLS) analysis was carried out to relate the Brix value to the normalized 2nd derivative spectra. The correlation coefficient was 0.947 with a root mean square errors of calibration (RMSEC) of 0.313°Brix. The root mean square errors of prediction (RMSEP) was 0.413°Brix. It is concluded that the Vis/NIR transmittance method yields a satisfied estimate of the Brix value in intact watermelons.

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 fo r 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-co st 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 calib ration 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. Keywords : Diffuse transmittance, visible/Near Infrared, Nondestructive detection, Soluble solids content, Watermelon

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.

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.