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José Blasco

Other affiliations: University of Seville
Bio: José Blasco is an academic researcher from University of Valencia. The author has contributed to research in topics: Hyperspectral imaging & Machine vision. The author has an hindex of 39, co-authored 123 publications receiving 4889 citations. Previous affiliations of José Blasco include University of Seville.


Papers
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Journal ArticleDOI
TL;DR: The different technologies available to acquire the images and their use for the non-destructive inspection of the internal and external features of these products are explained, with details of the statistical techniques most commonly used for this task.
Abstract: Hyperspectral imaging systems are starting to be used as a scientific tool for food quality assessment. A typical hyperspectral image is composed of a set of a relatively wide range of monochromatic images corresponding to continuous wavelengths that normally contain redundant information or may exhibit a high degree of correlation. In addition, computation of the classifiers used to deal with the data obtained from the images can become excessively complex and time-consuming for such high-dimensional datasets, and this makes it difficult to incorporate such systems into an industry that demands standard protocols or high-speed processes. Therefore, recent works have focused on the development of new systems based on this technology that are capable of analysing quality features that cannot be inspected using visible imaging. Many of those studies have also centred on finding new statistical techniques to reduce the hyperspectral images to multispectral ones, which are easier to implement in automatic, non-destructive systems. This article reviews recent works that use hyperspectral imaging for the inspection of fruit and vegetables. It explains the different technologies available to acquire the images and their use for the non-destructive inspection of the internal and external features of these products. Particular attention is paid to the works aimed at reducing the dimensionality of the images, with details of the statistical techniques most commonly used for this task.

444 citations

Journal ArticleDOI
Serkan Akkoyun1, A. Algora2, B. Alikhani3, F. Ameil  +375 moreInstitutions (40)
TL;DR: The Advanced GAmma Tracking Array (AGATA) as discussed by the authors is a European project to develop and operate the next generation gamma-ray spectrometer, which is based on the technique of energy tracking in electrically segmented high-purity germanium crystals.
Abstract: The Advanced GAmma Tracking Array (AGATA) is a European project to develop and operate the next generation gamma-ray spectrometer. AGATA is based on the technique of gamma-ray energy tracking in electrically segmented high-purity germanium crystals. This technique requires the accurate determination of the energy, time and position of every interaction as a gamma ray deposits its energy within the detector volume. Reconstruction of the full interaction path results in a detector with very high efficiency and excellent spectral response. The realisation of gamma-ray tracking and AGATA is a result of many technical advances. These include the development of encapsulated highly segmented germanium detectors assembled in a triple cluster detector cryostat, an electronics system with fast digital sampling and a data acquisition system to process the data at a high rate. The full characterisation of the crystals was measured and compared with detector-response simulations. This enabled pulse-shape analysis algorithms, to extract energy, time and position, to be employed. In addition, tracking algorithms for event reconstruction were developed. The first phase of AGATA is now complete and operational in its first physics campaign. In the future AGATA will be moved between laboratories in Europe and operated in a series of campaigns to take advantage of the different beams and facilities available to maximise its science output. The paper reviews all the achievements made in the AGATA project including all the necessary infrastructure to operate and support the spectrometer.

351 citations

Journal ArticleDOI
TL;DR: This work presents the latest developments in the application of Hyperspectral technology to the inspection of the internal and external quality of fruits and vegetables.
Abstract: 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.

317 citations

Journal ArticleDOI
TL;DR: In this article, the authors report on the machine vision techniques developed at the Instituto Valenciano de Investigaciones Agrarias for the on-line estimation of the quality of oranges, peaches and apples, and evaluate the efficiency of these techniques regarding the following quality attributes: size, colour, stem location and detection of external blemishes.

287 citations

Journal ArticleDOI
TL;DR: The experiments demonstrated that the software is able to single the fruit before estimating the size, which is calculated with an error less than 2 mm, and the system is capable of correctly classifying lemons and mandarins, attending to the external defects in 93 and 94% of the cases, following the Spanish citrus standards.

214 citations


Cited by
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Journal Article
TL;DR: This book by a teacher of statistics (as well as a consultant for "experimenters") is a comprehensive study of the philosophical background for the statistical design of experiment.
Abstract: THE DESIGN AND ANALYSIS OF EXPERIMENTS. By Oscar Kempthorne. New York, John Wiley and Sons, Inc., 1952. 631 pp. $8.50. This book by a teacher of statistics (as well as a consultant for \"experimenters\") is a comprehensive study of the philosophical background for the statistical design of experiment. It is necessary to have some facility with algebraic notation and manipulation to be able to use the volume intelligently. The problems are presented from the theoretical point of view, without such practical examples as would be helpful for those not acquainted with mathematics. The mathematical justification for the techniques is given. As a somewhat advanced treatment of the design and analysis of experiments, this volume will be interesting and helpful for many who approach statistics theoretically as well as practically. With emphasis on the \"why,\" and with description given broadly, the author relates the subject matter to the general theory of statistics and to the general problem of experimental inference. MARGARET J. ROBERTSON

13,333 citations

Journal ArticleDOI
TL;DR: An overview of NIR spectroscopy for measuring quality attributes of horticultural produce is given in this article, where the problem of calibration transfer from one spectrophotometer to another is introduced as well as techniques for calibration transfer.

1,780 citations

Journal ArticleDOI
TL;DR: This review discusses the techniques and procedures for the measurement and analysis of colour in food and other biomaterial materials, focusing on the instrumental and visual measurements for quantifying colour attributes and highlights the range of primary and derived objective colour indices used to characterise the maturity and quality of a wide range of food products and beverages.
Abstract: Colour is an important quality attribute in the food and bioprocess industries, and it influences consumer’s choice and preferences. Food colour is governed by the chemical, biochemical, microbial and physical changes which occur during growth, maturation, postharvest handling and processing. Colour measurement of food products has been used as an indirect measure of other quality attributes such as flavour and contents of pigments because it is simpler, faster and correlates well with other physicochemical properties. This review discusses the techniques and procedures for the measurement and analysis of colour in food and other biomaterial materials. It focuses on the instrumental (objective) and visual (subjective) measurements for quantifying colour attributes and highlights the range of primary and derived objective colour indices used to characterise the maturity and quality of a wide range of food products and beverages. Different approaches applied to model food colour are described, including reaction mechanisms, response surface methodology and others based on probabilistic and non-isothermal kinetics. Colour is one of the most widely measured product quality attributes in postharvest handling and in the food processing research and industry. Apart from differences in instrumentation, colour measurements are often reported based on different colour indices even for the same product, making it difficult to compare results in the literature. There is a need for standardisation to improve the traceability and transferability of measurements. The correlation between colour and other sensory quality attributes is well established, but future prospects exist in the application of objective non-destructive colour measurement in predictive modelling of the nutritional quality of fresh and processed food products.

1,232 citations

Journal ArticleDOI
TL;DR: In this article, the authors present a review of the currently used technologies that can be used for developing a ground-based sensor system to assist in monitoring health and diseases in plants under field conditions.

965 citations