0000000000306351
AUTHOR
Sergio Cubero
Herramienta para la generación de mapas de rendimiento en cítricos usando los datos de una plataforma de asistencia a la recolección con sistema de clasificación
El uso de nuevas tecnologías y la creación de mapas de rendimiento son una herramienta clave para cuantificar la información de un cultivo. La representación espacial de esta información registrada durante la recolección permite una mayor eficiencia en la gestión del cultivo por parte del agricultor, lo que a su vez repercute en una reducción de los costes de producción.Este trabajo presenta una herramienta para la monitorización del rendimiento en cultivos cítricos y la creación de mapas del cultivo en base a la información obtenida durante la recolección. La información es adquirida por una plataforma móvil de asistencia a la recolección de cítricos creada en el IVIA con sistema de inspec…
In-line Sorting of Processed Fruit Using Computer Vision
Nowadays, there is a growing demand for quality fruits and vegetables that are simple to prepare and consume, like minimally processed fruits. These products have to accomplish some particular characteristics to make them more attractive to the consumers, like a similar appearance and the total absence of external defects. Although recent advances in machine vision have allowed for the automatic inspection of fresh fruit and vegetables, there are no commercially available equipments for sorting of minority processed fruits, like arils of pomegranate (Punica granatum L) or segments of Satsuma mandarin (Citrus unshiu) ready to eat. This work describes a complete solution based on machine visi…
Detection of Invisible Damages in ‘Rojo Brillante’ Persimmon Fruit at Different Stages Using Hyperspectral Imaging and Chemometrics
[EN] 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…
Application of deep convolutional neural networks for the detection of anthracnose in olives using VIS/NIR hyperspectral images
Anthracnose is one of the primary diseases that affect olive production before and after harvest, causing severe damage and economic losses. The objective of this work is to detect this disease in the early stages, using hyperspectral images and advanced modelling techniques of Deep Learning (DL) and convolutional neural networks (CNN). The olives were artificially inoculated with the fungus. Hyperspectral images (450–1050 nm) of each olive were acquired until visual symptoms of the disease were observed, in some cases up to 9 days. The olives were classified into two classes: control, inoculated with water, and fungi composed of olives inoculated with the fungus. The ResNet101 architecture…
Application of deep convolutional neural networks for the detection of anthracnose in olives using VIS/NIR hyperspectral images
Abstract Anthracnose is one of the primary diseases that affect olive production before and after harvest, causing severe damage and economic losses. The objective of this work is to detect this disease in the early stages, using hyperspectral images and advanced modelling techniques of Deep Learning (DL) and convolutional neural networks (CNN). The olives were artificially inoculated with the fungus. Hyperspectral images (450–1050 nm) of each olive were acquired until visual symptoms of the disease were observed, in some cases up to 9 days. The olives were classified into two classes: control, inoculated with water, and fungi composed of olives inoculated with the fungus. The ResNet101 arc…
Discrimination of common defects in loquat fruit cv. ‘Algerie’ using hyperspectral imaging and machine learning techniques
Abstract Loquat (Eriobotrya japonica L.) is an important fruit for the economy of some regions of Spain that is very susceptible to mechanical damage and physiological disorders. These problems depreciate its value and prevent it from being exported. Visible (VIS) and near infrared (NIR) hyperspectral imaging was used to discriminate between external and internal common defects of loquat cv. ‘Algerie’. Two classifiers, random forest (RF) and extreme gradient boost (XGBoost), and different spectral pre-processing techniques were evaluated in terms of their capacity to distinguish between sound and defective features according to three approaches. In the first approach the fruit pixels were c…
Encouraging blended learning and ICT use at Universitat de València to improve the learning process with the .LRN platform
The Universitat de Valencia, one of the largest, oldest and most varied in Spain, concerned about the efficiency of the learning processes in the context of the convergence process towards the Higher Education European Space, has conducted educative innovation experiences in several degrees, diversifying learning activities.Interested in enhancing traditional classroom learning by use of ICT (with progressive blended learning introduction) has established a learning management system to enhance the learning and communication processes for the whole university. The overall goal was to build skills in ICT use in order to improve learning process quality and student participation.This paper de…
Early detection of mechanical damage in mango using NIR hyperspectral images and machine learning
Mango fruit are sensitive and can easily develop brown spots after suffering mechanical stress during postharvest handling, transport and marketing. The manual inspection of this fruit used today cannot detect the damage in very early stages of maturity and to date no automatic tool capable of such detection has been developed, since current systems based on machine vision only detect very visible damage. The application of hyperspectral imaging to the postharvest quality inspection of fruit is relatively recent and research is still underway to find a method of estimating internal properties or detecting invisible damage. This work describes a new system to evaluate mechanically induced da…
Visible-NIR reflectance spectroscopy and manifold learning methods applied to the detection of fungal infections on citrus fruit
Abstract The development of systems for automatically detecting decay in citrus fruit during quality control is still a challenge for the citrus industry. The feasibility of reflectance spectroscopy in the visible and near infrared (NIR) regions was evaluated for the automatic detection of the early symptoms of decay caused by Penicillium digitatum fungus in citrus fruit. Reflectance spectra of sound and decaying surface parts of mandarins cv. ‘Clemenvilla’ were acquired in two different spectral regions, from 650 nm to 1050 nm (visible–NIR) and from 1000 nm to 1700 nm (NIR), pointing to significant differences in spectra between sound and decaying skin for both spectral ranges. Three diffe…
Application of near Infrared Spectroscopy to the Quality Control of Citrus Fruits and Mango
NIR spectroscopy is a proved tool to measure the optical properties of the samples, which are related to their chemical and textural properties. This technology can be used for determining the internal and external quality of fruits. Accordingly, many studies have been reported for long time to assess the quality of different fresh fruits by using reflectance measurements acquired with visible-NIR spectroscopy. We have been working on the estimation of the quality of fruits using computer vision for more than twenty years, always focused on problems that affect the local industry. As the region of Valencia (Spain) is one of the main producers and exporters of citrus fruits worldwide, most o…
Discrimination of astringent and deastringed hard ‘Rojo Brillante’ persimmon fruit using a sensory threshold by means of hyperspectral imaging
[EN] Persimmon fruit cv. 'Rojo Brillante' is an astringent cultivar due to its content of soluble tannins, which are insolubilised during the ripening of the fruit. Traditionally, the consumption of this cultivar has only been possible when the fruit is overripe and the texture is soft. Postharvest treatments based on exposing fruits to high CO2 concentrations allow astringency removal while preserving high flesh firmness. However, the effectiveness of this treatment is controlled by means of slow destructive methods. The aim of this work is to study the application of hyperspectral imaging in the spectral range 450-1040 nm to discriminate astringent (A) and deastringed (DA) fruits non-dest…