Artificial vision systems are powerful tools for the automatic inspection of fruits and vegetables. Typical target applications of such systems include grading, quality estimation from external ...parameters or internal features, monitoring of fruit processes during storage or evaluation of experimental treatments. The capabilities of an artificial vision system go beyond the limited human capacity to evaluate long-term processes objectively or to appreciate events that take place outside the visible electromagnetic spectrum. Use of the ultraviolet or near-infrared spectra makes it possible to explore defects or features that the human eye is unable to see. Hyperspectral systems provide information about individual components or damage that can be perceived only at particular wavelengths and can be used as a tool to develop new computer vision systems adapted to particular objectives. In-line grading systems allow huge amounts of fruit or vegetables to be inspected individually and provide statistics about the batch. In general, artificial systems not only substitute human inspection but also improve on its capabilities. This work presents the latest developments in the application of this technology to the inspection of the internal and external quality of fruits and vegetables.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Visible–near-infrared (450–1040 nm) hyperspectral reflectance imaging was studied in order to assess the internal physicochemical properties and sensory perception of ‘Big Top’ and ‘Magique’ ...nectarines (Prunus persica L. Batsch var. nucipersica) (yellow and white-flesh cultivar, respectively) during ripening using the Ripening Index (RPI) and the Internal Quality Index (IQI). Hyperspectral images of the intact fruits were acquired during the ripeness under controlled conditions, and their physicochemical properties (flesh firmness, total soluble solids, titratable acidity and flesh colour) were analysed. IQI and RPI were used to relate the spectral information obtained from nectarines with the physicochemical properties and the sensory perception of their maturity using Partial Least Square (PLS) regression with proper variable selection. Optimal results were obtained with R2 values higher than 0.87 for the two indices and the two cultivars. The ripeness of each fruit could be visualised by projecting the PLS models of the IQI on the pixels of the fruits in the images, showing great potential for further monitoring of the evolution of intact nectarine ripeness in industrial setups.
•RPI and IQI are proposed for internal quality assessment of nectarines.•Prediction results indicate that PLS models have excellent prediction accuracy.•Wavelength selection provides good performance in prediction of RPI and IQI.•Hyperspectral imaging has great potential for monitoring nectarines in industrial setups.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
Computer vision systems are becoming a scientific but also a commercial tool for food quality assessment. In the field, these systems can be used to predict yield, as well as for robotic harvesting ...or the early detection of potentially dangerous diseases. In postharvest handling, it is mostly used for the automated inspection of the external quality of the fruits and for sorting them into commercial categories at very high speed. More recently, the use of hyperspectral imaging is allowing the detection of not only defects in the skin of the fruits but also their association to certain diseases of particular importance. In the research works that use this technology, wavelengths that play a significant role in detecting some of these dangerous diseases are found, leading to the development of multispectral imaging systems that can be used in industry. This article reviews recent works that use colour and non-standard computer vision systems for the automated inspection of citrus. It explains the different technologies available to acquire the images and their use for the non-destructive inspection of internal and external features of these fruits. Particular attention is paid to inspection for the early detection of some dangerous diseases like citrus canker, black spot, decay or citrus Huanglongbing.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Early automatic detection of fungal infections in post-harvest citrus fruits is especially important for the citrus industry because only a few infected fruits can spread the infection to a whole ...batch during operations such as storage or exportation, thus causing great economic losses. Nowadays, this detection is carried out manually by trained workers illuminating the fruit with dangerous ultraviolet lighting. The use of hyperspectral imaging systems makes it possible to advance in the development of systems capable of carrying out this detection process automatically. However, these systems present the disadvantage of generating a huge amount of data, which must be selected in order to achieve a result that is useful to the sector. This work proposes a methodology to select features in multi-class classification problems using the receiver operating characteristic curve, in order to detect rottenness in citrus fruits by means of hyperspectral images. The classifier used is a multilayer perceptron, trained with a new learning algorithm called extreme learning machine. The results are obtained using images of mandarins with the pixels labelled in five different classes: two kinds of sound skin, two kinds of decay and scars. This method yields a reduced set of features and a classification success rate of around 89%.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
The use of remote sensing to map the distribution of plant diseases has evolved considerably over the last three decades and can be performed at different scales, depending on the area to be ...monitored, as well as the spatial and spectral resolution required. This work describes the development of a small low-cost field robot (Remotely Operated Vehicle for Infection Monitoring in orchards, XF-ROVIM), which is intended to be a flexible solution for early detection of Xylella fastidiosa (X. fastidiosa) in olive groves at plant to leaf level. The robot is remotely driven and fitted with different sensing equipment to capture thermal, spectral and structural information about the plants. Taking into account the height of the olive trees inspected, the design includes a platform that can raise the cameras to adapt the height of the sensors to a maximum of 200 cm. The robot was tested in an olive grove (4 ha) potentially infected by X. fastidiosa in the region of Apulia, southern Italy. The tests were focused on investigating the reliability of the mechanical and electronic solutions developed as well as the capability of the sensors to obtain accurate data. The four sides of all trees in the crop were inspected by travelling along the rows in both directions, showing that it could be easily adaptable to other crops. XF-ROVIM was capable of inspecting the whole field continuously, capturing geolocated spectral information and the structure of the trees for later comparison with the in situ observations.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
RobHortic is a remote-controlled field robot that has been developed for inspecting the presence of pests and diseases in horticultural crops using proximal sensing. The robot is equipped with ...colour, multispectral, and hyperspectral (400–1000 nm) cameras, located looking at the ground (towards the plants). To prevent the negative influence of direct sunlight, the scene was illuminated by four halogen lamps and protected from natural light using a tarp. A GNSS (Global Navigation Satellite System) was used to geolocate the images of the field. All sensors were connected to an on-board industrial computer. The software developed specifically for this application captured the signal from an encoder, which was connected to the motor, to synchronise the acquisition of the images with the advance of the robot. Upon receiving the signal, the cameras are triggered, and the captured images are stored along with the GNSS data. The robot has been developed and tested over three campaigns in carrot fields for the detection of plants infected with ‘Candidatus Liberibacter solanacearum’. The first two years were spent creating and tuning the robot and sensors, and data capture and geolocation were tested. In the third year, tests were carried out to detect asymptomatic infected plants. As a reference, plants were analysed by molecular analysis using a specific real-time Polymerase Chain Reaction (PCR), to determine the presence of the target bacterium and compare the results with the data obtained by the robot. Both laboratory and field tests were done. The highest match was obtained using Partial Least Squares-Discriminant Analysis PLS-DA, with a 66.4% detection rate for images obtained in the laboratory and 59.8% for images obtained in the field.
Development of non-destructive tools for determining mango ripeness would improve the quality of industrial production of the postharvest processes. This study addresses the creation of a new sensor ...that combines the capability of obtaining mechanical and optical properties of the fruit simultaneously. It has been integrated into a robot gripper that can handle the fruit obtaining non-destructive measurements of firmness, incorporating two spectrometer probes to simultaneously obtain reflectance properties in the visible and near-infrared, and two accelerometers attached to the rear side of two fingers. Partial least square regression was applied to different combinations of the spectral data obtained from the different sensors to determine the combination that provides the best results. Best prediction of ripening index was achieved using both spectral measurements and two finger accelerometer signals, with RP2=0.832 and RMSEP of 0.520. These results demonstrate that simultaneous measurement and analysis of the data fusion set improve the robot gripper features, allowing assessment of the quality of the mangoes during pick and place operations.
•The developed gripper is capable of handling mangoes and estimating their ripeness.•Integration of accelerometers and spectrometers in a new non-destructive sensor.•Both sensors work together in the robot gripper without fruit contact.•Assessment of the quality of the mangoes during pick and place processes.•Simultaneous measurement improves ripeness prediction results.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
The main cause of flesh browning in ‘Rojo Brillante’ persimmon fruit is mechanical damage caused during harvesting and packing. Innovation and research on nondestructive techniques to detect this ...phenomenon in the packing lines are necessary because this type of alteration is often only seen when the final consumer peels the fruit. In this work, we have studied the application of hyperspectral imaging in the range of 450–1040 nm to detect mechanical damage without any external symptoms. The fruit was damaged in a controlled manner. Later, images were acquired before and at 0, 1, 2 and 3 days after damage induction. First, the spectral data captured from the images were analysed through an algorithm based on principal component analysis (PCA). The aim was to automatically separate intact and damaged fruit, and to detect the damage in the PC images when present. With this algorithm, 90.0% of intact fruit and 90.8% of damaged fruit were correctly detected. A model based on partial least squares—discriminant analysis (PLS-DA), was later calibrated using the mean spectrum of the pixels detected as damaged, to determine the moment when the fruit was damaged. The model differentiated fruit corresponding correctly to 0, 1, 2 and 3 days after damage induction, achieving a total accuracy of 99.4%.
Wheat flour is a food ingredient used in different processed food products, including pasta, cake, bread, among others. Therefore, the authentication and assurance of good quality are of great ...importance. Traditional techniques used for quality parameters determinations are laborious, destructive, and demand chemical analysis. Hence, it is necessary the development of techniques capable to overcome these disadvantages. Spectral techniques are rapid, non-destructive, and chemical-free. This review approaches the applications of Near Infrared (NIR) Spectroscopy, Fourier Transform Near-Infrared (FT-NIR) Spectroscopy, and Hyperspectral Imaging (HSI) in wheat flour and wheat-based products authentication and assessment of quality parameters, composition, and contamination. Considering the need from the processing industry for a rapid analysis, moving the bench-top analytical system to the production line, future studies can explore in/on-line applications of these techniques for industrial processing lines and compare the use of handheld and benchtop spectrometers in these applications.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Once a new product has been designed, or when creating a new model, most of the times, variations are needed (different configurations) that allow us to study its behavior, feasibility, etc. In the ...way designers traditionally design, models and products are very rigid in the sense that, albeit certain modifications may be applied, they are not flexible enough to obtain the desired new product designs or configurations.This work presents a modeling strategy, which has been implemented by mean of rules using Autodesk Inventor's iLogic tool. This strategy considers the study of the parameters prior to modeling and the implementation of certain rules, which based on a few parameters, allow the complete generation of the new model or product automatically. To illustrate this strategy, a basic explosion engine with a V-cylinder arrangement has been used as an example of a product. With the modification of a minimum number of parameters through a user interface, the new product automatically varies in number of cylinders, their capacity, the stroke ratio and the V angle, what will allow their study through dynamic simulation and FEM of the new desired motor without the need to carry out modifications to the models or to create a new assembly of the product. This strategy has been implemented in the Graphic Engineering department and used for the training of students of the Degree in Engineering in Industrial Technologies.
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