This review covers developments in non-invasive techniques for quality analysis and inspection of specialty crops, mainly fresh fruits and vegetables, over the past decade up to the year 2010. Presented and discussed in this review are advanced sensing technologies including computer vision, spectroscopy, X-rays, magnetic resonance, mechanical contact, chemical sensing, wireless sensor networks and radio-frequency identification sensors. The current status of different sensing systems is described in the context of commercial application. The review also discusses future research needs and potentials of these sensing technologies. Emphases are placed on those technologies that have been proven effective or have shown great potential for agro-food applications. Despite significant progress in the development of non-invasive techniques for quality assessment of fruits and vegetables, the pace for adoption of these technologies by the specialty crop industry has been slow.

Time-resolved reflectance spectroscopy can be used to assess nondestructively the bulk (rather than the superficial) optical properties of highly diffusive media. A fully automated system for time-resolved reflectance spectroscopy was used to evaluate the absorption and the transport scattering spectra of fruits in the red and the near-infrared regions. In particular, data were collected in the range 650–1000 nm from three varieties of apples and from peaches, kiwifruits, and tomatoes. The absorption spectra were usually dominated by the water peak near 970 nm, whereas chlorophyll was detected at 675 nm. For all species the scattering decreased progressively with increasing wavelength. A best fit to water and chlorophyll absorption line shapes and to Mie theory permitted the estimation of water and chlorophyll content and the average size of scattering centers in the bulk of intact fruits.

Here, we review different methods for non-destructive horticultural produce size determination, focusing on electronic technologies capable of measuring fruit volume. The usefulness of produce size estimation is justified and a comprehensive classification system of the existing electronic techniques to determine dimensional size is proposed. The different systems identified are compared in terms of their versatility, precision and throughput. There is general agreement in considering that online measurement of axes, perimeter and projected area has now been achieved. Nevertheless, rapid and accurate volume determination of irregular-shaped produce, as needed for density sorting, has only become available in the past few years. An important application of density measurement is soluble solids content (SSC) sorting. If the range of SSC in the batch is narrow and a large number of classes are desired, accurate volume determination becomes important. A good alternative for fruit three-dimensional surface reconstruction, from which volume and surface area can be computed, is the combination of height profiles from a range sensor with a two-dimensional object image boundary from a solid-state camera (brightness image) or from the range sensor itself (intensity image). However, one of the most promising technologies in this field is 3-D multispectral scanning, which combines multispectral data with 3-D surface reconstructio

The external appearance of an olive’s skin is the most decisive factor in determining its\ud quality as a fruit. This work tries to establish a hierarchical model based on the features\ud extracted from images of olives reflecting their external defects. Seven commercial\ud categories of olives, established by product experts, were used: undamaged olives,\ud mussel-scale or ‘serpeta’, hail-damaged or ‘granizo’, mill or ‘rehús’, wrinkled olive or\ud ‘agostado’, purple olive and undefined-damage or ‘molestado’. The original images\ud were processed using segmentation, colour parameters and morphological features of\ud the defects and the whole fruits. The application of three consecutive discriminant\ud analyses resulted in the correct classification of 97% and 75% of olives during\ud calibration and validation, respectively. However the correct classification percentages\ud vary greatly depending on the categories, ranging 80–100% during calibration and 38–\ud 100% during validation

Time-resolved reflectance has been used for the nondestructive measurement of optical properties in apples. The technique is based on the detection of the temporal dispersion of a short laser pulse injected into the probed medium. The time distribution of re-emitted photons interpreted with a solution of the diffusion equation yields the mean values of the absorption and reduced scattering coefficients of the medium. The proposed technique proved useful for the measurement of the absorption and scattering spectra of different varieties of apples, revealing the spectral shape of chlorophyll. No major variations were observed in the experimental data when the fruit was peeled, showing that the optical properties measured were those of the pulp. With this technique the change in chlorophyll absorption during storage and ripening could be followed. Finally, a compact prototype working at few selected wavelengths was designed and constructed, demonstrating potentialities of the technique for industrial applications.

Wo multispectral maturity classifications for red soft-flesh peaches (‘Kingcrest’, ‘Rubyrich’ and ‘Richlady’ n = 260) are proposed and compared based on R (red) and R/IR (red divided by infrared) images obtained with a three CCD camera (800 nm, 675 nm and 450 nm). R/IR histograms were able to correct the effect of 3D shape on light reflectance and thus more Gaussian histograms were produced than R images. As fruits ripened, the R/IR histograms showed increasing levels of intensity. Reference measurements such as firmness and visible spectra also varied significantly as the fruit ripens, firmness decreased while reflectance at 680 nm increased (chlorophyll absorption peak)