Non-destructive optical characterisation of fruits with time-resolved reflectance spectroscopy.

Increasing attention is being paid to the possible development of non-invasive tests for the assessment of the quality of fruits We propose a novel non-destructive method for the measurement of the internal optical properties of fruits and vegetables by means of time resolved reflectance spectroscopy in the visible and NIR range. A fully automated instrumentation for time-resolved reflectance measurements was developed It is based on mode-locked laser sources and electronics for time-correlated single photon counting, and provides a time-resolution of 120-160 ps The system was used to probe the optical properties of several species and varieties of fruits and vegetables in the red and NIR range (650-1000 nm). In most fruits, the absorption line shape is dominated by the absorption peak of water, centred around 970 nm Generally, the absorption spectra also show the spectral features typical of chlorophyll, with maximum at 675 nm In particular, for what concerns apples, variations in peak intensity are observed depending on the variety, the degree of ripeness as well as the position on the apple. For all the species and varieties considered, the transport scattering coefficient decreases progressively upon increasing the wavelength.

Non-destructive optical characterization of fruits in the red and near infrared.

Increasing attention is being paid to the possible development of non-invasive tests for the assessment of the quality of Fruits. We propose a novel non-destructive method for the measurement of the internal optical properties of fruits and vegetables by means of lime-resolved reflectance spectroscopy in the visible and NIR range. A Fully automated instrumentation for time-resolved reflectance measurements was developed. It is based on mode-locked laser sources and electronics for time-correlated single photon counting, and provides a time-resolution of 120-160 ps. The system was used to probe the optical properties of several species and varieties of Fruits and vegetables in the red and NIR range (650-1000 nm). In most Fruits, the absorption line shape is dominated by the absorption peak of water, centred around 970 nm. Generally, the absorption spectra also show the spectral features typical of chlorophyll, with maximum at 675 nm. In particular, for what concerns apples, variations in peak intensity are observed depending on the variety, the degree of ripeness as well as the position on the apple. For all the species and varieties considered, the transport scattering coefficient decreases progressively upon increasing the wavelength.

Optical detection of mealiness in apples using laser TDRS.

Mealiness is a textural attribute related to an internal fruit disorder that involves quality loss. It is characterised by the combination of abnormal softness of the fruit and absence of free juiciness in the mouth when eaten by the consumer. Recent research concluded with the development of precise instrumental procedure to measure a scale of mealiness based on the combination of several rheological properties and empirical magnitudes. In this line, time-domain laser reflectance spectroscopy (TDRS) is a new medical technology, used to characterise the optical properties of tissues, and to locate affected areas like tumours. Among its advantages compared to more traditional spectroscopic techniques, there is the feasibility to asses simultaneously and independently two optical parameters: the absorption of the light inside the irradiated body, and the scattering of the photons across the tissues, at each wavelength, generating two coefficients (µa, absorption coeff.; and µ's, transport scattering coeff.). If it is assumed that they are related respectively to chemical components and to physical properties of the sample, TDRS can be applied to the quantification of chemicals and the measurement of the rheological properties (i.e. mealiness estimation) at the same time. Using VIS & NIR lasers as light sources, TDRS was applied in this work to Golden Delicious and Cox apples (n=90), conforming several batches of untreated samples and storage-treated (20°C & 95%RH) to promote the development of mealiness. The collected database was clustered into different groups according to their instrumental test values (Barreiro et al, 1998). The optical coefficients were used as explanatory variables when building discriminant analysis functions for mealiness, achieving a classification score above 80% of correctly identified mealy versus fresh apples.

Models for internal quality sorting of fruit, based on time-domain laser reflectance spectroscopy (TDRS).

Non-destructive measurement of fruit quality has been an important objective through recent years (Abbott, 1999). Near infrared spectroscopy (NIR) is applicable to the cuantification of chemicals in foods and NIK "laser spectroscopy" can be used to estimate the firmness of fruits. However, die main limitation of current optical techniques that measure light transmission is that they do not account for the coupling between absorption and scattering inside the tissue, when quantifying the intensity o f reemitted light. The solution o f this l i m i t a t i o n was the goal o f the present work.

Detection of internal quality in kiwi with a new optical technique (TDRS)

A compact system based on time-resolved diffuse reflectance spectroscopy (TDRS) has been developed to measure internal fruit quality parameters and has been applied to the non-destructive estimation of firmness, sugar content and acidity of kiwifruits. This new optical technique, developed in medical applications and related areas, provides a complete optical characterisation of a diffusive sample as it estimates at the same time and independently the light absorption inside the tissues and the scattering across them. The working principle of the technique is the analysis of the attenuation and broadening of the time-distribution of the remitted light, and the correct interpretation with a proper theoretical model. This main advantage compared to conventional optical techniques (which are only able to register the global attenuation spectrum) added to the compact, portable prototype developed along a three-year work opens the possibilities of this new measurement method in the food industry.

Clasificación de frutos por su calidad interna mediante espectroscopia láser de reflectancia con resolución temporal (TDRS).

La determinación no destructiva de la calidad interna de la fruta ha sido un objetivo prioritario en las investigaciones recientes (Abbott, 1999). La espectroscopia en el infrarrojo (NIR) es aplicable a la cuantificación de compuestos químicos en alimentos; por otro lado se ha comprobado que el uso de láseres es interesante para la estimación no destructiva de la firmeza de los frutos. Sin embargo estas técnicas ópticas más tradicionales tienen el inconveniente de que miden la intensidad de luz transmitida sin poder diferenciar el efecto de la absorción óptica del efecto de la dispersión espacial que sufre la luz en el interior de los tejidos, lo cual dificulta la estimación independiente de aspectos físicos y químicos. La espectroscopia con resolución temporal es una técnica óptica desarrollada para el diagnóstico en medicina, que permite diferenciar ambos fenómenos (absorción y dispersión), proporcionando una caracterización óptica completa de los tejidos. El objetivo del presente trabajo ha sido la aplicación de esta técnica a frutas y hortalizas, y el desarrollo de modelos matemáticos de estimación no destructiva de su calidad interna para su uso en procesos de clasificación.

Detección óptica de harinosidad en manzana mediante una nueva técnica láser.

Mealiness, a textural disorder that produces quality loss, combines softness and absence of juiciness. The only one (destructive) test to measure it, combines information from a mechanical test on fruit probes to classify the samples according to instrumental mealiness. Time-domain laser reflectance spectroscopy (TDRS) is able to assess simultaneously and independently the absorption of the light inside the irradiated body (µa coefficient) and the scattering of the photons across the tissues (µS, transport scattering coeff.) measured at each wavelength. Using VIS&NIR lasers as light sources, TDRS was applied to Golden Delicious and Cox apples (n=90), conforming batches of untreated samples and storage-treated (20°C&95%RH) to induce mealiness development. The collected database was clustered into different groups according to their instrumental mealiness. Optical variables were used to build discriminant functions, achieving classification scores 75-89% of correctly identified mealy apples.

Dynamic gamma frequency feedback coupling between higher and lower order visual cortices underlies perceptual completion in humans

To perceive a coherent environment, incomplete or overlapping visual forms must be integrated into meaningful coherent percepts, a process referred to as ?Gestalt? formation or perceptual completion. Increasing evidence suggests that this process engages oscillatory neuronal activity in a distributed neuronal assembly. A separate line of evidence suggests that Gestalt formation requires top-down feedback from higher order brain regions to early visual cortex. Here we combine magnetoencephalography (MEG) and effective connectivity analysis in the frequency domain to specifically address the effective coupling between sources of oscillatory brain activity during Gestalt formation. We demonstrate that perceptual completion of two-tone ?Mooney? faces induces increased gamma frequency band power (55?71 Hz) in human early visual, fusiform and parietal cortices. Within this distributed neuronal assembly fusiform and parietal gamma oscillators are coupled by forward and backward connectivity during Mooney face perception, indicating reciprocal influences of gamma activity between these higher order visual brain regions. Critically, gamma band oscillations in early visual cortex are modulated by top-down feedback connectivity from both fusiform and parietal cortices. Thus, we provide a mechanistic account of Gestalt perception in which gamma oscillations in feature sensitive and spatial attention-relevant brain regions reciprocally drive one another and convey global stimulus aspects to local processing units at low levels of the sensory hierarchy by top-down feedback. Our data therefore support the notion of inverse hierarchical processing within the visual system underlying awareness of coherent percepts.

Detección de azúcares en vinos y mostos mediante espectrofotometría en NIR.

En el proceso de vinificación un aspecto de vital importancia es el control periódico de la concentración de azúcares durante la etapa de fermentación del mosto. Los métodos tradicionales de análisis en laboratorio, si bien son suficientemente precisos, conllevan un importante gasto de material y tiempo, y sólo proporcionan medidas discretas a lo largo del proceso de fermentación. En investigaciones recientes se ha aplicado el NIR espectrofotometría en el infrarrojo cercano a la predicción de los azúcares en distintos productos agrícolas (Bellón, V. l993, en manzanas; Barreiro. P. 1996, en tomates. El objetivo de este trabajo fue el desarrollo de un modelo de estimación del contenido de azúcares disueltos en el mosto, y el establecimiento de un sistema de predicción de la evolución de la fermentación. Mediante un espectrofotómetro con detector en el área del infrarrojo cercano (NIR) y un la medida de la transmisión de luz conducida por fibras ópticas, se adquirieron los datos espectrales de los mostos y vinos en fermentación controlada. Análisis matemáticos y estadísticos posteriores (transformación de los espectros, análisis de componentes principales y regresiones multilineales condujeron al establecimiento del modelo de estimación de los azúcares (con precisión de ±2,5 g/1). Los modelos desarrollados permiten la implantación de un sistema de toma de datos continuo en las cubas de fermentación de una bodega, para el control sistemático en tiempo real del proceso de elaboración del vino.

Claas Lexion 780 Terratrac, el relevo generacional.

El día 25 de junio llevamos a cabo en la Puebla de Montalbán (Toledo) un ensayo de verificación de las prestaciones de una cosechadora Claas Lexion 780 Terratrac, comparándolas con las características de una máquina más antigua, una Claas Lexion 530 Montana que disponía de un cabezal McDon, empleándose además en el primer caso un sistema de auto-guiado. La profusión de datos disponibles no deja lugar a la especulación, todo, o mejor dicho, casi todo puede ser cuantificado.

Navegando a bordo de un New Holland T6 AutoCommand

El pasado día 4 de abril tuvimos la oportunidad de probar un nuevo T6.160 AutoCommand en tierras de Cantalejo, Segovia. Se han realizado dos tipos de tarea con el tractor: preparación del lecho de siembra con una grada rotativa y transporte de un remolque cargado. La parcela tenía una textura fuertemente arenosa típica de la zona y se encontraba en un estado de tempero óptimo. En las distintas pruebas se ha evaluado el modo automático frente al manual. Veamos sus resultados.

Evoluçao e aplicaçao da mecatronica em maquinas agricolas.

Em Ciências Agronómicas, a constante adoção de novas tecnologias, faz com que cada vez mais se alargue o conhecimento em torno de novas áreas técnicas e científicas. Hoje, a incorporação de sistemas mecatrónicos na arquitetura de conceção de tratores e máquinas agrícolas, além de tornar a máquina mais amiga do operador, tem permitido a otimização da sua utilização e rentabilidade de operação. O significado de Mecatrónica e algumas considerações sobre a sua aplicação em máquinas agrícolas são descritas neste artigo.

Usando Kinect como sensor para una pulverización inteligente.

Este trabajo esta orientado a resolver el problema de la caracterización de la copa de arboles frutales para la aplicacion localizada de fitosanitarios. Esta propuesta utiliza un mapa de profundidad (Depth image) y una imagen RGB combinadas (RGB-D), proporcionados por el sensor Kinect de Microsoft, para aplicar pesticidas de forma localizada. A través del mapa de profundidad se puede estimar la densidad de la copa y a partir de esta información determinar qué boquillas se deben abrir en cada momento. Se desarrollaron algoritmos implementados en Matlab que permiten además de la adquisición de las imágenes RGB-D, aplicar plaguicidas sólo a hojas y/o frutos según se desee. Estos algoritmos fueron implementados en un software que se comunica con el entorno de desarrollo "Kinect Windows SDK", encargado de extraer las imágenes desde el sensor Kinect. Por otra parte, para identificar hojas, se implementaron algoritmos de clasificación e identificación. Los algoritmos de clasificación utilizados fueron "Fuzzy C-Means con Gustafson Kessel" (FCM-GK) y "K-Means". Los centroides o prototipos de cada clase generados por FCM-GK fueron usados como semilla para K-Means, para acelerar la convergencia del algoritmo y mantener la coherencia temporal en los grupos generados por K-Means. Los algoritmos de clasificación fueron aplicados sobre las imágenes transformadas al espacio de color L*a*b*; específicamente se emplearon los canales a*, b* (canales cromáticos) con el fin de reducir el efecto de la luz sobre los colores. Los algoritmos de clasificación fueron configurados para buscar cuatro grupos: hojas, porosidad, frutas y tronco. Una vez que el clasificador genera los prototipos de los grupos, un clasificador denominado Máquina de Soporte Vectorial, que utiliza como núcleo una función Gaussiana base radial, identifica la clase de interés (hojas). La combinación de estos algoritmos ha mostrado bajos errores de clasificación, rendimiento del 4% de error en la identificación de hojas. Además, estos algoritmos de procesamiento de hasta 8.4 imágenes por segundo, lo que permite su aplicación en tiempo real. Los resultados demuestran la viabilidad de utilizar el sensor "Kinect" para determinar dónde y cuándo aplicar pesticidas. Por otra parte, también muestran que existen limitaciones en su uso, impuesta por las condiciones de luz. En otras palabras, es posible usar "Kinect" en exteriores, pero durante días nublados, temprano en la mañana o en la noche con iluminación artificial, o añadiendo un parasol en condiciones de luz intensa.

Spatial variability of seed depth placement of maize under no tillage.

Among the various factors that contribute towards producing a successful maize crop, seed depth placement is a key determinant, especially in a no-tillage system. The main objective of this work was to evaluate the spatial variability of seed depth placement and crop establishment in a maize crop under no-tillage conditions, using precision farming technologies. The obtained results indicate that seed depth placement was significantly affected by soil moisture content, while a very high coefficient of variation of 39% was found for seed depth. Seeding depth had a significant impact on mean emergence time and percentage of emerged plants. Shallow average depth values and the high coefficient of variation suggest a need for improvement in controlling the seeder sowing depth.

Active Optical Sensors for Tree Stem Detection and Classification in Nurseries.

Active optical sensing (LIDAR and light curtain transmission) devices mounted on a mobile platform can correctly detect, localize, and classify trees. To conduct an evaluation and comparison of the different sensors, an optical encoder wheel was used for vehicle odometry and provided a measurement of the linear displacement of the prototype vehicle along a row of tree seedlings as a reference for each recorded sensor measurement. The field trials were conducted in a juvenile tree nursery with one-year-old grafted almond trees at Sierra Gold Nurseries, Yuba City, CA, United States. Through these tests and subsequent data processing, each sensor was individually evaluated to characterize their reliability, as well as their advantages and disadvantages for the proposed task. Test results indicated that 95.7% and 99.48% of the trees were successfully detected with the LIDAR and light curtain sensors, respectively. LIDAR correctly classified, between alive or dead tree states at a 93.75% success rate compared to 94.16% for the light curtain sensor. These results can help system designers select the most reliable sensor for the accurate detection and localization of each tree in a nursery, which might allow labor-intensive tasks, such as weeding, to be automated without damaging crops.