Optical properties of developing pip and stone fruit reveal underlying structural changes.

Analyzing the optical properties of fruits represents a powerful approach for non-destructive observations of fruit development. With classical spectroscopy in the visible and near-infrared wavelength ranges, the apparent attenuation of light results from its absorption or scattering. In horticultural applications, frequently, the normalized difference vegetation index (NDVI) is employed to reduce the effects of varying scattering properties on the apparent signal. However, this simple approach appears to be limited. In the laboratory, with time-resolved reflectance spectroscopy, the absorption coefficient, µa , and the reduced scattering coefficient, µs ', can be analyzed separately. In this study, these differentiated optical properties were recorded (540-940 nm), probing fruit tissue from the skin up to 2 cm depth in apple (Malus × domestica 'Elstar') and plum (Prunus domestica 'Tophit plus') harvested four times (65-145 days after full bloom). The µa spectra showed typical peak at 670 nm of the chlorophyll absorption. The µs ' at 670 nm in apple changed by 14.7% (18.2-15.5 cm(-1) ), while in plum differences of 41.5% (8.5-5.0 cm(-1) ) were found. The scattering power, the relative change of µs ', was zero in apple, but enhanced in plum over the fruit development period. This mirrors more isotropic and constant structures in apple compared with plum. For horticultural applications, the larger variability in scattering properties of plum explains the discrepancy between commercially assessed NDVI values or similar indices and the absolute µa values in plum (R < 0.05), while the NDVI approach appeared reasonable in apple (R ≥ 0.80).

A computational model for path loss in wireless sensor networks in orchard environments.

A computational model for radio wave propagation through tree orchards is presented. Trees are modeled as collections of branches, geometrically approximated by cylinders, whose dimensions are determined on the basis of measurements in a cherry orchard. Tree canopies are modeled as dielectric spheres of appropriate size. A single row of trees was modeled by creating copies of a representative tree model positioned on top of a rectangular, lossy dielectric slab that simulated the ground. The complete scattering model, including soil and trees, enhanced by periodicity conditions corresponding to the array, was characterized via a commercial computational software tool for simulating the wave propagation by means of the Finite Element Method. The attenuation of the simulated signal was compared to measurements taken in the cherry orchard, using two ZigBee receiver-transmitter modules. Near the top of the tree canopies (at 3 m), the predicted attenuation was close to the measured one-just slightly underestimated. However, at 1.5 m the solver underestimated the measured attenuation significantly, especially when leaves were present and, as distances grew longer. This suggests that the effects of scattering from neighboring tree rows need to be incorporated into the model. However, complex geometries result in ill conditioned linear systems that affect the solver's convergence.

Spectrophotometric analyses of chlorophyll and single carotenoids during fruit development of tomato (Solanum lycopersicum L.) by means of iterative multiple linear regression analysis.

When using spectrophotometric transmittance readings of fruit extracts, the analysis of single carotenoids is difficult because of coinciding absorption bands of the various carotenoids and chlorophylls present in the solution. Aimed at the separate analyses of pigments, an iteratively applied linear regression was developed based on spectral profiles of pigment standards. The iterative approach was validated by dilution series of pigments and compared with commonly applied equation systems. High coefficients of determination and low measuring uncertainties were found for chlorophyll a and b (R(2) > or = 0.99, root mean square error RMSE < or = 10%). Carotenoids were separately analyzed with R(2) = 0.99, R(2) = 0.96, and R(2) = 0.98 for lycopene, beta-carotene, and lutein, respectively. The approach based on the spectral profiles provided low measuring uncertainties even if lutein was additionally present in the solutions, which was not possible with common data analyses. Subjecting tomato tissues (Solanum lycopersicum L.) to the iterative approach, contents of in vivo measured pigments were calculated with R(2) = 0.82, R(2) = 0.84, R(2) = 0.67, and R(2) = 0.03 for chlorophyll a and b, lycopene, and beta-carotene, respectively.

[Improving apple fruit quality predictions by effective correction of Vis-NIR laser diffuse reflecting images].

In the present study, improved laser-induced light backscattering imaging was studied regarding its potential for analyzing apple SSC and fruit flesh firmness. Images of the diffuse reflection of light on the fruit surface were obtained from Fuji apples using laser diodes emitting at five wavelength bands (680, 780, 880, 940 and 980 nm). Image processing algorithms were tested to correct for dissimilar equator and shape of fruit, and partial least squares (PLS) regression analysis was applied to calibrate on the fruit quality parameter. In comparison to the calibration based on corrected frequency with the models built by raw data, the former improved r from 0. 78 to 0.80 and from 0.87 to 0.89 for predicting SSC and firmness, respectively. Comparing models based on mean value of intensities with results obtained by frequency of intensities, the latter gave higher performance for predicting Fuji SSC and firmness. Comparing calibration for predicting SSC based on the corrected frequency of intensities and the results obtained from raw data set, the former improved root mean of standard error of prediction (RMSEP) from 1.28 degrees to 0.84 degrees Brix. On the other hand, in comparison to models for analyzing flesh firmness built by means of corrected frequency of intensities with the calibrations based on raw data, the former gave the improvement in RMSEP from 8.23 to 6.17 N x cm(-2).

Approach for non-destructive pigment analysis in model liquids and carrots by means of time-of-flight and multi-wavelength remittance readings.

Non-destructive spectroscopy in the visible and near infrared wavelength range has been introduced for analyzing absorbing compounds in fruit and vegetables. A drawback of the method appears due to the measuring principle, where photons detected in the diffusive tissue are influenced by the sample absorption but also scattering properties leading to variation in the photon pathlength. In the present work, distribution of time-of-flight reading was used to calculate the effective pathlength between source and detector. Using this information in addition to the spectral intensities obtained with common continuous wave spectroscopy, Lambert-Beer law was applied for analyzing absolute pigment contents. The method was tested for liquid phantoms mimicking the optical properties of fresh fruit and vegetables. Lambert-Beer law using a constant pathlength as well as combined application of the intensity at a specific wavelength and the effective pathlength resulted in low calibration errors with r(2)>0.98. Applying the two calibrations on phantoms mimicking changes in the scattering properties resulted in validation results of r(2)=0.47 and 0.64, respectively. Improved results by using the effective pathlength were confirmed on real-world samples. The carrot carotenoids analysis resulted in validation results of r(2)=0.66 and 0.74, respectively, while the measuring uncertainty was reduced from 18.10 to 9.62%. Multivariate calibrations using the entire carrot spectra and data pre-processing aiming the reduction of scattering effects resulted in slightly lower measuring uncertainty by comparison. In the sensor fusion approach proposed, however, no expensive spectrophotometer is required and the phenomenon of varying optical properties of the sample is characterized.

Fluorescence spectroscopy for monitoring deterioration of extra virgin olive oil during heating.

The potential of fluorescence spectroscopy for characterizing the deterioration of extra virgin olive oil (EVOO) during heating was investigated. Two commercial EVOO were analysed by HPLC to determine changes in EVOO vitamin E and polyphenols as a result of heating at 170 degrees C for 3 h. This thermal oxidation of EVOO caused an exponential decrease in hydroxytyrosol and vitamin E (R(2)=0.90 and 0.93, respectively) whereas the tyrosol content was relatively stable. At the same time, amounts of preformed hydroperoxides (ROOH), analysed by an indirect colorimetric method, decreased exponentially during the heating process (R(2)=0.94), as a result of their degradation into secondary peroxidation products. Fluorescence excitation spectra with emission at 330 and 450 nm were recorded to monitor polyphenols and vitamin E evolution and ROOH degradation, respectively. Partial least-squares calibration models were built to predict these indicators of EVOO quality from oil fluorescence spectra. A global approach was then proposed to monitor the heat charge from the overall fluorescence fingerprint. Different data pretreatment methods were tested. This study indicates that fluorescence spectroscopy is a promising, rapid, and cost-effective approach for evaluating the quality of heat-treated EVOO, and is an alternative to time-consuming conventional analyses. In future work, calibration models will be developed using a wide range of EVOO samples.