Application of commercially available, low-cost, miniaturised NIR spectrometers to the assessment of the sugar content of intact fruit

Recent decreases in costs, and improvements in performance, of silicon array detectors open a range of potential applications of relevance to plant physiologists, associated with spectral analysis in the visible and short-wave near infra-red (far-red) spectrum. The performance characteristics of three commercially available ‘miniature’ spectrometers based on silicon array detectors operating in the 650–1050-nm spectral region (MMS1 from Zeiss, S2000 from Ocean Optics, and FICS from Oriel, operated with a Larry detector) were compared with respect to the application of non-invasive prediction of sugar content of fruit using near infra-red spectroscopy (NIRS). The FICS–Larry gave the best wavelength resolution; however, the narrow slit and small pixel size of the charge-coupled device detector resulted in a very low sensitivity, and this instrumentation was not considered further. Wavelength resolution was poor with the MMS1 relative to the S2000 (e.g. full width at half maximum of the 912 nm Hg peak, 13 and 2 nm for the MMS1 and S2000, respectively), but the large pixel height of the array used in the MMS1 gave it sensitivity comparable to the S2000. The signal-to-signal standard error ratio of spectra was greater by an order of magnitude with the MMS1, relative to the S2000, at both near saturation and low light levels. Calibrations were developed using reflectance spectra of filter paper soaked in range of concentrations (0–20% w/v) of sucrose, using a modified partial least squares procedure. Calibrations developed with the MMS1 were superior to those developed using the S2000 (e.g. coefficient of correlation of 0.90 and 0.62, and standard error of cross-validation of 1.9 and 5.4%, respectively), indicating the importance of high signal to noise ratio over wavelength resolution to calibration accuracy. The design of a bench top assembly using the MMS1 for the non-invasive assessment of mesocarp sugar content of (intact) melon fruit is reported in terms of light source and angle between detector and light source, and optimisation of math treatment (derivative condition and smoothing function).

Robustness of NIR calibrations for assessing fruit quality

Predictive models based on near infra-red spectroscopy for the assessment of fruit internal quality attributes must exhibit a degree of robustness across the parameters of variety, district and time to be of practical use in fruit grading. At the time this thesis was initiated, while there were a number of published reports on the development of near infra-red based calibration models for the assessment of internal quality attributes of intact fruit, there were no reports of the reliability ("robustness") of such models across time, cultivars or growing regions. As existing published reports varied in instrumentation employed, a re-analysis of existing data was not possible. An instrument platform, based on partial transmittance optics, a halogen light source and (Zeiss MMS 1) detector operating in the short wavelength near infra-red region was developed for use in the assessment of intact fruit. This platform was used to assess populations of macadamia kernels, melons and mandarin fruit for total soluble solids, dry matter and oil concentration. Calibration procedures were optimised and robustness assessed across growing areas, time of harvest, season and variety. In general, global modified partial least squares regression (MPLS) calibration models based on derivatised absorbance data were better than either multiple linear regression or `local' MPLS models in the prediction of independent validation populations . Robustness was most affected by growing season, relative to the growing district or variety . Various calibration updating procedures were evaluated in terms of calibration robustness. Random selection of samples from the validation population for addition to the calibration population was equivalent to or better than other methods of sample addition (methods based on the Mahalanobis distance of samples from either the centroid of the population or neighbourhood samples). In these exercises the global Mahalanobis distance (GH) was calculated using the scores and loadings from the calibration population on the independent validation population. In practice, it is recommended that model predictive performance be monitored in terms of predicted sample GH, with model updating using as few as 10 samples from the new population undertaken when the average GH value exceeds 1 .0 .

Effects of seasonal variability on FT-NIR prediction of dry matter content for whole Hass avocado fruit

Fourier Transform (FT)-near infra-red spectroscopy (NIRS) was investigated as a non-invasive technique for estimating percentage (%) dry matter of whole intact 'Hass' avocado fruit. Partial least squares (PLS) calibration models were developed from the diffuse reflectance spectra to predict % dry matter, taking into account effects of seasonal variation. It is found that seasonal variability has a significant effect on model predictive performance for dry matter in avocados. The robustness of the calibration model, which in general limits the application for the technique, was found to increase across years (seasons) when more seasonal variability was included in the calibration set. The R-v(2) and RMSEP for the single season prediction models predicting on an independent season ranged from 0.09 to 0.61 and 2.63 to 5.00, respectively, while for the two season models predicting on the third independent season, they ranged from 0.34 to 0.79 and 2.18 to 2.50, respectively. The bias for single season models predicting an independent season was as high as 4.429 but <= 1.417 for the two season combined models. The calibration model encompassing fruit from three consecutive years yielded predictive statistics of R-v(2) = 0.89, RMSEP = 1.43% dry matter with a bias of -0.021 in the range 16.1-39.7% dry matter for the validation population encompassing independent fruit from the three consecutive years. Relevant spectral information for all calibration models was obtained primarily from oil, carbohydrate and water absorbance bands clustered in the 890-980, 1005-1050, 1330-1380 and 1700-1790 nm regions. These results indicate the potential of FT-NIRS, in diffuse reflectance mode, to non-invasively predict the % dry matter of whole 'Hass' avocado fruit and the importance of the development of a calibration model that incorporates seasonal variation. Crown Copyright (c) 2012 Published by Elsevier B.V. All rights reserved.

Radio-Optical Imaging of ATLBS Survey

We present the radio-optical imaging of ATLBS, a sensitive radio survey (Subrahmanyan et al. 2010). The primary aim of the ATLBS survey is to image low-power radio sources which form the bulk of the radio source population to moderately high red-shifts (z similar to 1.0). The accompanying multiband optical and near infra-red observations provide information about the hosts and environments of the radio sources. We give here details of the imaging of the radio data and optical data for the ATLBS survey.

Linearization and Reconstruction of Non-linear Diffuse Optical Tomographic Image

Diffuse optical tomography (DOT) is one of the ways to probe highly scattering media such as tissue using low-energy near infra-red light (NIR) to reconstruct a map of the optical property distribution. The interaction of the photons in biological tissue is a non-linear process and the phton transport through the tissue is modelled using diffusion theory. The inversion problem is often solved through iterative methods based on nonlinear optimization for the minimization of a data-model misfit function. The solution of the non-linear problem can be improved by modeling and optimizing the cost functional. The cost functional is f(x) = x(T)Ax - b(T)x + c and after minimization, the cost functional reduces to Ax = b. The spatial distribution of optical parameter can be obtained by solving the above equation iteratively for x. As the problem is non-linear, ill-posed and ill-conditioned, there will be an error or correction term for x at each iteration. A linearization strategy is proposed for the solution of the nonlinear ill-posed inverse problem by linear combination of system matrix and error in solution. By propagating the error (e) information (obtained from previous iteration) to the minimization function f(x), we can rewrite the minimization function as f(x; e) = (x + e)(T) A(x + e) - b(T)(x + e) + c. The revised cost functional is f(x; e) = f(x) + e(T)Ae. The self guided spatial weighted prior (e(T)Ae) error (e, error in estimating x) information along the principal nodes facilitates a well resolved dominant solution over the region of interest. The local minimization reduces the spreading of inclusion and removes the side lobes, thereby improving the contrast, localization and resolution of reconstructed image which has not been possible with conventional linear and regularization algorithm.

Green colored nano-pigments derived from Y2BaCuO5: NIR reflective coatings

A green colored nano-pigment Y2BaCuO5 with impressive near infra-red (NIR) reflectance (61% at 1100 nm) was synthesized by a nano-emulsion method. The developed nano-crystalline powders were characterized by X-ray diffraction (XRD), Transmission electron microscopy (TEM), UV-vis-NIR diffuse reflectance spectroscopy and CIE-L*a*b* 1976 color scales. The XRD and Rietveld analyses of the designed pigment powders reveal the orthorhombic crystal structure for Y2BaCuO5, where yttrium is coordinated by seven oxygen atoms with the local symmetry of a distorted trigonal prism, barium is coordinated by eleven oxygen atoms, and the coordination polyhedron of copper is a distorted square pyramid CuO5]. The UV-vis spectrum of the nano-pigment exhibits an intense d-d transition associated with CuO5 chromophore between 2.1 and 2.5 eV in the visible domain. Therefore, a green color has been displayed by the developed nano-pigment. The potential utility of the nano-pigments as ``Cool Pigments'' was demonstrated by coating on to a building roofing material like cement slab and PVC coatings. (C) 2014 Elsevier Ltd. All rights reserved.

Nonvolatile holograms in LiNbO3 : Fe : Cu by use of the bleaching effect

We report our observation of a bleaching effect under an ultraviolet exposure in LiNbO3:Fe:Cu crystals. Two three-step recording-transferring-fixing schemes are proposed to record nonvolatile photorefractive holograms in such crystals. In the schemes two red laser beams and an ultraviolet illumination are used selectively to write the charge grating in the shallow-level Fe centers, to develop the charge grating in the deep-level Cu centers by transferring the charge grating in the Fe centers, and to fix only the charge grating in the Cu centers for unerasable read-out. Experimental results, verifications, and an optimal recording scheme are given. A comparison of the lithium niobate crystals of the same double-doping system of Fe:Mn, Ce:Mn, Ce:Cu, and Fe:Cu is outlined. (C) 2002 Optical Society of America.

Controlling Sub-nm Gaps in Plasmonic Dimers using Graphene

Graphene is used as the thinnest possible spacer between gold nanoparticles and a gold substrate. This creates a robust, repeatable, and stable sub-nanometre gap for massive plasmonic field enhancements. White light spectroscopy of single 80 nm gold nanoparticles reveals plasmonic coupling between the particle and its image within the gold substrate. While for a single graphene layer, spectral doublets from coupled dimer modes are observed shifted into the near infra-red, these disappear for increasing numbers of layers. These doublets arise from plasmonic charge transfer, allowing the direct optical measurement of out-of-plane conductivity in such layered systems. Gating the graphene can thus directly produce plasmon tuning.

Synthesis and properties of d6 metal complexes of bidentate and tridentate ‘super donor’ ligands

La polyvalence de la réaction de couplage-croisé C-N a été explorée pour la synthèse de deux nouvelles classes de ligands: (i) des ligands bidentates neutres de type N^N et (ii) des ligands tridentates neutres de type N^N^N. Ces classes de ligands contiennent des N-hétérocycles aromatiques saturés qui sont couplés avec hexahydropyrimidopyrimidine (hpp). Les ligands forment de cycles à six chaînons sur la coordination du centre Ru(II). Ce fait est avantageux pour améliorer les propriétés photophysiques des complexes de polypyridyl de Ru(II). Les complexes de Ru(II) avec des ligands bidentés ont des émissions qui dépendent de la basicité relative des N-hétérocycles. Bien que ces complexes sont électrochimiquement et photophysiquement attrayant, le problème de la stereopurité ne peut être évité. Une conception soigneuse du type de ligand nous permet de synthétiser un ligand bis-bidentate qui est utile pour surmonter le problème de stereopurité. En raison de la spécialité du ligand bis-bidentate, son complexe diruthénium(II,II) présente une grande diastéréosélectivité sans séparation chirale. Alors que l'unité de hpp agit comme un nucléophile dans le mécanisme de C-N réaction de couplage croisé, il peut également agir en tant que groupe partant, lorsqu'il est activé avec un complexe de monoruthenium. Les complexes achiraux de Ru(II) avec les ligands tridentés présentent des meilleures propriétés photophysiques en comparason avec les prototypes [Ru(tpy)2]2+ (tpy = 2,2′: 6′, 2′′-terpyridine). L’introduction de deux unités de hpp dans les ligands tridentates rend le complexe de Ru(II) en tant que ‘absorbeur noir’ et comme ‘NIR émetteur’ (NIR = de l’anglais, Near Infra-Red). Cet effet est une conséquence d'une meilleure géométrie de coordination octaédrique autour de l'ion Ru(II) et de la forte donation sigma des unités hpp. Les complexes du Re(I) avec des ligands tridentates présentent un comportement redox intéressant et ils émettent dans le bleu. L'oxydation quasi-réversible du métal est contrôlée par la donation sigma des fragments hpp, tandis que la réduction du ligand est régie par la nature électronique du motif N-hétérocycle central du ligand lui-même. Cette thèse presente également l'auto-assemblage des métal-chromophores comme ‘métallo-ligands’ pour former des espèces supramoléculaires discretes utilisant des complexes neutres. Les synthèses et propriétés des métaux-chromophores précités et les supramolécules sont discutées.

Optimization algorithms in FMRF model-based segmentation for LIDAR data and co-registered bands

In this paper, a fuzzy Markov random field (FMRF) model is used to segment land-objects into free, grass, building, and road regions by fusing remotely, sensed LIDAR data and co-registered color bands, i.e. scanned aerial color (RGB) photo and near infra-red (NIR) photo. An FMRF model is defined as a Markov random field (MRF) model in a fuzzy domain. Three optimization algorithms in the FMRF model, i.e. Lagrange multiplier (LM), iterated conditional mode (ICM), and simulated annealing (SA), are compared with respect to the computational cost and segmentation accuracy. The results have shown that the FMRF model-based ICM algorithm balances the computational cost and segmentation accuracy in land-cover segmentation from LIDAR data and co-registered bands.

NDVI With Artificial Neural Networks For SRTM Elevation Model Improvement – Hydrological Model Application

Digital elevation model (DEM) plays a substantial role in hydrological study, from understanding the catchment characteristics, setting up a hydrological model to mapping the flood risk in the region. Depending on the nature of study and its objectives, high resolution and reliable DEM is often desired to set up a sound hydrological model. However, such source of good DEM is not always available and it is generally high-priced. Obtained through radar based remote sensing, Shuttle Radar Topography Mission (SRTM) is a publicly available DEM with resolution of 92m outside US. It is a great source of DEM where no surveyed DEM is available. However, apart from the coarse resolution, SRTM suffers from inaccuracy especially on area with dense vegetation coverage due to the limitation of radar signals not penetrating through canopy. This will lead to the improper setup of the model as well as the erroneous mapping of flood risk. This paper attempts on improving SRTM dataset, using Normalised Difference Vegetation Index (NDVI), derived from Visible Red and Near Infra-Red band obtained from Landsat with resolution of 30m, and Artificial Neural Networks (ANN). The assessment of the improvement and the applicability of this method in hydrology would be highlighted and discussed.

Avaliação e valorização de recursos agrícolas: avaliação nutricional e mineral de variedades tradicionais de batata-doce (Ipomoea batatas L.) provenientes da Madeira e Açores

Este trabalho foi desenvolvido com o intuito de avaliar nutricionalmente variedades agrícolas regionais madeirenses e açorianas de Ipomoea batatas L. (batata-doce). No total 18 amostras foram analisadas, entre as quais 11 são variedades provindas da Madeira e outras 7 provindas dos Açores. O maior objectivo deste estudo foi comparar a composição nutricional e mineral de um conjunto de variedades de batata-doce, valorizando assim os recursos agrícolas da Madeira e Açores. A caracterização nutricional e mineral dos rizomas, produzidos nestas regiões, proporcionou informação relevante para a valorização destes recursos. Sendo um rizoma tropical consumido habitualmente pela população e disponível todo o ano, torna essencial a sua avaliação. A análise laboratorial dos rizomas permitiu determinar um conjunto de características nutricionais. De um modo geral, os valores nutricionais médios detectados em rizomas de batata-doce destas duas regiões são de 93,64 g/100g de MS para o resíduo seco, 3,01 g/100g de MS para cinzas, 3,19 g/100g de MS para fibra (ADF), 1,21 g/100g de MS para gordura bruta, 3,20 g/100g de MS para proteína, 14,00 g/100g de MS para açúcares solúveis e 59,72 g/100g de MS para o amido. A análise mineral incluiu a determinação de fósforo, potássio, cálcio, magnésio, ferro, cobre, zinco, manganês e boro. Na variedade “De cenoura” (ISOP 1028), foi quantificado o nível de pro-vitamina A pela técnica de HPLC, que foi verificado ser 12,48 mg/100g em MS de β-caroteno. Os dados obtidos na análise nutricional foram usados para construir uma base de dados no NIRS (Near Infra-Red Spectroscopy) de modo a construir um modelo de previsão que possa predizer o valor nutritivo de um grande número de amostras em tempo reduzido, com um mínimo de impacto ambiental. Posteriormente, os dados obtidos através das análises nutricionais e minerais foram introduzidos no software estatístico SPSS 19.0 para determinar correlações e similaridades.

Avaliação de recursos genéticos agrícolas: análise nutricional e anti-nutricional de variedades regionais de feijão (Phaseolus vulgaris L.)

O presente trabalho teve como objectivo proceder à avaliação da qualidade nutricional de 20 variedades regionais de Phaseolus vulgaris L. e à análise comparativa dos parâmetros bioquímicos (nutricionais e anti-nutricionais) obtidos recorrendo às técnicas analíticas convencionais por química molhada e de NIRS (Near Infra-Red Spectroscopy). Uma tipificação das variedades regionais de feijão foi realizada recorrendo a sete parâmetros ou caracteres (traits) nutricionais compreendidos em humidade, proteína bruta, lípidos totais, açúcares solúveis, amido, cinzas e minerais. A faseolamina foi incluída na tipificação do feijão como parâmetro anti-nutricional enquanto inibidor de enzimas digestivas. A variedade que apresentou uma melhor qualidade nutricional foi o feijão vermelho (ISOP 00724), enquanto que o feijão Filipe (ISOP 00478) apresentou uma maior actividade inibitória da PPA (amilase do pâncreas suíno), contribuindo de igual forma como uma característica de qualidade deste feijão. A aplicação de técnicas de quimiometria na quantificação dos vários parâmetros de qualidade nutricional, através da técnica de NIRS, permitiu o desenvolvimento dos modelos PLS globais após a colecção dos valores de referência e obtenção dos respectivos espectros de cada ISOP em análise. A análise comparativa dos parâmetros nutricionais, recorrendo às técnicas analíticas convencionais por química molhada e de NIRS, permitiu relacionar os parâmetros cinzas e proteína bruta como os principais critérios nutricionais para distinção das variedades regionais quanto à sua qualidade, ao diferirem significativamente relativamente aos parâmetros restantes. A partir destas duas técnicas, conclui-se que a espectroscopia NIR associada a técnicas de análise multivariada consegue quantificar os parâmetros em estudo, permitindo distinguir amostras das variedades regionais, quanto às suas características nutricionais, exigindo uma preparação reduzida da amostra, com consequente custo de análise muito reduzido. Este trabalho representou o início de uma base de fenotipagem a partir de caracteres nutricionais, estabelecendo-se um perfil das variedades regionais de feijão e avaliação da importância dos caracteres na sua distinção e tipagem.

Estudo de propriedades físico-químicas de resinas odontológicas: grau de conversão, dureza e expansão térmica

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Dynamic Features for Iris Recognition

The human eye is sensitive to visible light. Increasing illumination on the eye causes the pupil of the eye to contract, while decreasing illumination causes the pupil to dilate. Visible light causes specular reflections inside the iris ring. On the other hand, the human retina is less sensitive to near infra-red (NIR) radiation in the wavelength range from 800 nm to 1400 nm, but iris detail can still be imaged with NIR illumination. In order to measure the dynamic movement of the human pupil and iris while keeping the light-induced reflexes from affecting the quality of the digitalized image, this paper describes a device based on the consensual reflex. This biological phenomenon contracts and dilates the two pupils synchronously when illuminating one of the eyes by visible light. In this paper, we propose to capture images of the pupil of one eye using NIR illumination while illuminating the other eye using a visible-light pulse. This new approach extracts iris features called "dynamic features (DFs)." This innovative methodology proposes the extraction of information about the way the human eye reacts to light, and to use such information for biometric recognition purposes. The results demonstrate that these features are discriminating features, and, even using the Euclidean distance measure, an average accuracy of recognition of 99.1% was obtained. The proposed methodology has the potential to be "fraud-proof," because these DFs can only be extracted from living irises.