Modeling for Metabonomic Fingerprint Assignment in Olive Fruits

Metabonomics has been recently applied to a variety of studies in the agri-food field, mainly focused on adulteration identification and cultivar or geographical origin assessment. One-dimensional HR-NMR spectrum was acquired using a standard 1D pulse sequence (NOESYPRESAT) with water peak suppression. Two-dimension correlation spectroscopy analyses, 1H-1H 2D experiments (COSY90), were performed. ACD/LABS 8.00 software package was used to obtain simulated spectra from main components in olive, and minor components including those responsible for antioxidant characteristic and aromatics. The application of multivariate statistical techniques to a large HR-NMR spectra data base is the next ste

Mealiness assessment in fruits using MRI techniques.

Mealiness is a sensory attribute that cannot be defined by a single parameter but through a combination of variables (multidimensional structure). Previous studies propose the definition of mealiness as the lack of crispiness, of hardness and of juiciness. Current aims are focused on establishing non destructive tests for mealiness assessment. MultiSliceMultiEcho Magnetic resonance images (MRI, 64*64pixels) have been taken corresponding to a 3ms of Echo time. Small samples of Top Red apples stored 6 months at controlled atmosphere (expected to be non mealy) and 2°C (expected to be mealy) have been used for MRI imaging. Three out of four apples corresponding to the sample maintained at controlled atmosphere did not develop mealiness while three out of four fruits corresponding to the sample stored at 2°C became mealy after 6 month of storage. The minimum T2 values/image obtained for the mealy apples shows to be significantly lower when compared with non mealy apples pointing that a more dis-aggregated structure leads to a quicker loss of signal Also, there is a significant linear correlation (r=-0.76) between the number of pixels with a T2 value below 35ms within a fruit image and the deformation parameter registered during the Magness-Taylor firmness test. Finally, all the T2 images of the mealy apples show a regional variation of contrast which is not shown for non mealy apples. This variation of contrast is similar to the MRI images of water-cored apples indicating that in these cases there is a differential water movement that may precede the internal browning

Corrección de desfase en imágenes de Resonancia Magnética

La imagen de Resonancia Magnética (IRM) se ha estudiado para su aplicación en línea. Se han adquirido dos tipos de imágenes FLASH coronales (tiempo de adquisición 279 ms para limones y 703 para naranjas) de muestras estáticas y conducidas a 54 mm/s a través de un espectrómetro de 4.7 Teslas. Los algoritmos desarrollados para la corrección automática del movimiento has mostrado una mejora notoria en la calidad de las imágenes dinámicas. Las imágenes estáticas y dinámicas corregidas fueron comparadas mediante sus histogramas acumulados loscuales mostraron altos coeficientes de determinación (R2 = 0.96 para limones y 0.98 para naranjas). Un análisis de varianza de los parámetros extraídos de las imágenes estáticas y dinámicas corregidas mostró diferencias no significativas

Detection of seeds in citrus using MRI under motion conditions and improvement with motion correction

Magnetic resonance imaging (MRI) is studied under an online strategy. Axial FLASH images (780 ms acquisition time) have been analyzed to identify seed-containing oranges conveyed at 50 and 100 mm/s through a 4.7 Tesla spectrometer. Developed algorithms enable an automated identification of oranges with more than one seed, though axial images under motion conditions suffer from significant blurring artifacts. To overcome this hindrance, coronal FLASH images have been acquired (279 ms acquisition time), developing devoted algorithms for motion correction with encouraging results for quality improvement of dynamic image

A novel R-package graphic user interface for the analysis of metabonomic profiles

Background Analysis of the plethora of metabolites found in the NMR spectra of biological fluids or tissues requires data complexity to be simplified. We present a graphical user interface (GUI) for NMR-based metabonomic analysis. The "Metabonomic Package" has been developed for metabonomics research as open-source software and uses the R statistical libraries. /Results The package offers the following options: Raw 1-dimensional spectra processing: phase, baseline correction and normalization. Importing processed spectra. Including/excluding spectral ranges, optional binning and bucketing, detection and alignment of peaks. Sorting of metabolites based on their ability to discriminate, metabolite selection, and outlier identification. Multivariate unsupervised analysis: principal components analysis (PCA). Multivariate supervised analysis: partial least squares (PLS), linear discriminant analysis (LDA), k-nearest neighbor classification. Neural networks. Visualization and overlapping of spectra. Plot values of the chemical shift position for different samples. Furthermore, the "Metabonomic" GUI includes a console to enable other kinds of analyses and to take advantage of all R statistical tools. /Conclusion We made complex multivariate analysis user-friendly for both experienced and novice users, which could help to expand the use of NMR-based metabonomics

Mealiness assessment in apples and peaches using MRI techniques.

Since Januarv 1946 a wade EC Project entitled "Mealiness in fruits Consumers perception and means for detection is being carried out. Mealiness is a sensory attribute that cannot be defined by a single parameter but through a combination of variables (multidimensional structure) Previous studies propose the definition of mealiness as the lack of crispiness of hardness and of juiciness. A destructive instrumental procedure combined with a integration technique has been already developed enabling to identify mealy fruits by destructive instrumental means use other contributions of Barreiro and Ortiz to this Ag Eng 98. Current aims .are focused on establishing non destructive tests for mealiness assessment. Magnetic resonance Imaging (MRI) makes use of the magnetic properties that some atomic nuclei have. especially hidrogen nuclei from water molecules to obtain high quality images in the field of internal quality evaluation the MRI has been used to assess internal injury due to conservation as o treatments as chilling injury un Persimmons Clark&Forbes (1994) and water-core in apples (Wang et al. 1998. In the case of persimmons the chilling injury is described as an initial tissue breakdown and lack of cohesion between cells followed by formation of a firm gel and by a lack of juiciness without changes in the total amount ol water content. Also a browning of the flesh is indicated (Clark&Forhes 1994). This definition fits into the previous description of mealiness

MRI texture analysis as means for addressing rehydration and milk diffusion in cereals

Cereals microstructure is one of the primary quality attributes of cereals. Cereals rehydration and milk diffusion depends on such microstructure and thus, the crispiness and the texture, which will make it more palatable for the final consumer. Magnetic Resonance Imaging (MRI) is a very powerful tomographic tool since acquisition parameter leads to a wide possibility for identifying textures, structures and liquids mobility. It is suited for noninvasive imaging of water and fats. Rehydration and diffusion cereals processes were measured by MRI at different times and using two different kinds of milk, varying their fat level. Several images were obtained. A combination of textural analysis (based on the analysis of histograms) and segmentation methods (in order to understand the rehydration level of each variety of cereals) were performed. According to the rehydration level, no advisable clustering behaviour was found. Nevertheless, some differences were noticeable between the coating, the type of milk and the variety of cereals

Detección no destructiva de semillas en mandarina con imágenes de Resonancia Magnética ultrarrápidas: comparativa entre métodos de segmentación automática

La Imagen de Resonancia Magnetica (IRM) se ha propuesto para adquirir imagenes de la estrcretura interna de mandarinas para la identificacion no destructive de semi Has. Se han investigado dos tipos de secuencias rapidas de IRM: una de tipo eco de gradiente y otra de tlpo espiral-radial, con tiempo de adquisicion de 484 ms para la primera y 240 ms para la segunda. La opcion espiral-radial permite un sobremuestreo del area central del espacic-k en la que esta contenida la information sobre el conlraste en las imagenes de RM y con ello la posibilidad de segmentation de las semillas. Se aplican tres tecnicas de segmentacion para el post-procesado de las imagenes: una basada en regiones, una basada en la varianza del bistograma unidimensional y una basada en !a varianza del histograma bidimensional, siendo la ultima la que ha proporcionado los resultados mas prometedores. Parametros como el perimetro, la compacidad, la distancia maxima al centro de gravedad y la relacidn entre altura y ancho se utilizan en una funcion lineal discriminante mediante la que la identificacion de mandarinas con semilla se puede conseguir con el 100% de exactitud cuando se utilizan secuencias espiral- radial y con el 98,7% cuando se obtienen imagenes de eco de gradiente

Computer assisted enhanced volumetric segmentation magnetic imaging data using a mixture of artificial neural networks

An accurate computer-assisted method able to perform regional segmentation on 3D single modality images and measure its volume is designed using a mixture of unsupervised and supervised artificial neural networks. Firstly, an unsupervised artificial neural network is used to estimate representative textures that appear in the images. The region of interest of the resultant images is selected by means of a multi-layer perceptron after a training using a single sample slice, which contains a central portion of the 3D region of interest. The method was applied to magnetic resonance imaging data collected from an experimental acute inflammatory model (T(2) weighted) and from a clinical study of human Alzheimer's disease (T(1) weighted) to evaluate the proposed method. In the first case, a high correlation and parallelism was registered between the volumetric measurements, of the injured and healthy tissue, by the proposed method with respect to the manual measurements (r = 0.82 and p < 0.05) and to the histopathological studies (r = 0.87 and p < 0.05). The method was also applied to the clinical studies, and similar results were derived of the manual and semi-automatic volumetric measurement of both hippocampus and the corpus callosum (0.95 and 0.88

Non destructive assessment of watercore in apples using MRI. Disorder Detection with HR-MAS

This work was carried out in the frame of the European project InsideFood (Integrated sensing and imaging devices for designing, monitoring and controlling microstructure of foods). The aim of this project is to provide technological solutions for exploring the microstructure of foods, by the development, combination and application of different non destructive techniques: X-ray CT, OCT, MRI, NMR, TRS and SRS. Nuclear magnetic resonance (NMR) was used in order to detect watercore in three different varieties of apples: Ascara2, Rebellón and Tempera. Magnetic resonance imaging (MRI) was used under several sequences: 2D T2- weighed sequences, and 3D sequences, proton density and T2- weighed, such as Fast Low Angle SHot (FLASH) and COMSPIRA 3D, all of them with varying acquisition times. A methabonomic study was made to some of these apples, to obtain a metabolic profile of apples affected by watercore, as an indication of the metabolic pathway involved in the disorder. Keywords: Non-destructive measurement, fruit, quality, tomography