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Littérature scientifique sur le sujet « Near-infrared technology »

Auteur : Grafiati

Publié le 10 mars 2023

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Articles de revues sur le sujet "Near-infrared technology"

McClure, W. Fred. « Near Infrared Technology Moves South ». NIR news 3, n^o 6 (décembre 1992) : 10–11. http://dx.doi.org/10.1255/nirn.157.

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Williams, Phil. « Near Infrared Technology in Canada ». NIR news 6, n^o 4 (août 1995) : 12–13. http://dx.doi.org/10.1255/nirn.317.

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Petersen, Julio Cesar. « Near Infrared Technology in Latin America ». NIR news 8, n^o 2 (avril 1997) : 8–9. http://dx.doi.org/10.1255/nirn.407.

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Hernández-Hierro, J. M., I. González-Martín, V. Villaescusa-García, F. López-González, C. Oiz-Jiménez, I. A. Lobos-Ortega et B. Gordillo. « Control of quality and silo storage of sunflower seeds using near infrared technology ». Grasas y Aceites 64, n^o 1 (4 février 2013) : 30–35. http://dx.doi.org/10.3989/gya.096312.

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Izzetoglu, Meltem, Scott C. Bunce, Kurtulus Izzetoglu, Banu Onaral et and Kambiz Pourrezaei. « Functional brain imaging using near-infrared technology ». IEEE Engineering in Medicine and Biology Magazine 26, n^o 4 (juillet 2007) : 38–46. http://dx.doi.org/10.1109/memb.2007.384094.

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Razuc, M., A. Grafia, L. Gallo, M. V. Ramírez-Rigo et R. J. Romañach. « Near-infrared spectroscopic applications in pharmaceutical particle technology ». Drug Development and Industrial Pharmacy 45, n^o 10 (17 juillet 2019) : 1565–89. http://dx.doi.org/10.1080/03639045.2019.1641510.

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Nishimura, Erin, J. Patrick Stautzenberger, William Robinson, Traci H. Downs et J. Hunter Downs. « A new approach to functional near-infrared technology ». IEEE Engineering in Medicine and Biology Magazine 26, n^o 4 (juillet 2007) : 25–29. http://dx.doi.org/10.1109/memb.2007.384092.

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Siesler, Heinz. « 1992 Tomas Hirschfeld Award in near Infrared Technology ». NIR news 2, n^o 6 (décembre 1991) : 7. http://dx.doi.org/10.1255/nirn.92.

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McClure, W. Fred. « 204 Years of near Infrared Technology : 1800–2003 ». Journal of Near Infrared Spectroscopy 11, n^o 6 (décembre 2003) : 487–518. http://dx.doi.org/10.1255/jnirs.399.

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Tsuji, Miles. « Cerebral Monitoring by Near-Infrared Spectroscopy ». Journal of Intensive Care Medicine 11, n^o 3 (mai 1996) : 162–72. http://dx.doi.org/10.1177/088506669601100303.

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Near-infrared spectroscopy (NIRS) is a noninvasive optical monitoring technology that can provide information on relative cerebral oxyhemoglobin, deoxyhemoglobin, and oxidized cytochrome aa3 concentrations. Unlike other bedside clinical monitoring technologies, NIRS provides direct information on cerebral hemoglobin oxygenation and blood volume changes. NIRS recordings have documented changes in cerebral oxygenation in fetuses during labor, critically ill premature infants, cardiopulmonary bypass patients, and adult surgical patients. This information may improve understanding of the causes of brain injury and allow detection of inadequate oxygen delivery before brain injury occurs. Future developments in NIRS technology are likely to produce practical, quantitative bedside monitors of global and regional cerebral oxygenation.

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Thèses sur le sujet "Near-infrared technology"

Gresham, Christopher Allen 1965. « Near-infrared spectroscopy utilizing array detector technology ». Diss., The University of Arizona, 1998. http://hdl.handle.net/10150/282690.

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A near-infrared spectrometer incorporating solid-state design applicable for industrial quantitative/qualitative process monitoring analysis is presented. The solid-state near-infrared spectrometer provides inherent wavelength stability necessary for long term calibration accuracy. The spectrometer consists of a 24 volt, 10 watt quartz-halogen-tungsten regulated source with optical feedback. Wavelength dispersion was accomplished using a 50 μm entrance slit, f/4, 0.25 meter spectrograph equipped with astigmatism correcting toroidal mirrors and a 300 gr/mm plane reflectance ruled grating blazed for 2000 nm peak efficiency. A 1024 element backside- illuminated Schottky-barrier PtSi photodiode array detector with wavelength response from 900-5000 nm and peak quantum efficiency of 8% at 1100 nm was operated using cryogenic cooling to reduce dark response. A readout rate of 31.25 kHz produced 41 msec integration time per array read. The readout was digitized to 16 bit resolution for subsequent data storage. This system demonstrated 1.5 nm spectral bandpass, 3 orders linear dynamic range and typical baseline rms noise level of 10⁻⁴ a.u. Using this system, quantitative/qualitative chemical analyses were performed focusing on industrial analytical chemical applications. Simultaneous quantitative multcomponent xylene isomer mixtures analysis was achieved using the solid-state near-infrared spectrometer coupled with partial least squares regression multivariate data treatment. The results demonstrate an absolute accuracy of ± 0.05, ±0.12 and ±0.09% w/v for o-, m- and p-xylene isomers respectively. In a separate chemical study, qualitative classification analysis of specially denatured alcohol mixtures was successfully performed on 53 validation samples using 35 reference samples belonging to 12 classes. The validation set included mixture sample types used for model calibration as well as others composed of compounds not used for model calibration. The multivariate cluster classification method using principal components was employed to correctly classify 100% of the validations samples analyzed. The solid-state near-infrared spectrometer was also applied for direct reaction monitoring of the O-H overtone absorption band at 1411 nm for the reaction between triisopropyl-chlorosilane and methanol. The results illustrated the utility of near-infrared functional group monitoring of reactions at relatively high concentrations for information elucidation concerning reaction initiation and completion.

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Abdel-Nour, Nicolas. « Chicken egg quality assessment from visible/near infrared observations ». Thesis, McGill University, 2009. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=32396.

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Egg is a fragile component within the human diet. Important changes occur in egg during storage. Prediction of these changes is critical in order to grade the eggs upon their quality and freshness. The objectives of this study were to evaluate the application of visible and near infrared spectroscopy as a non-destructive method for the assessment of egg quality and freshness. Therefore, visible and near infrared transmittance spectral data ranging from 350 to 2500 nm was collected with the help of a radiospectrometer on 360 freshly laid eggs. A partial least squares model was built in order to link the spectral data with the most widely used destructive methods, namely Haugh Units and albumen pH in terms of egg quality and the number of storage days in terms of egg freshness. The ability of maximum R2 method to select the relevant wavelengths in order to build a partial least squares (PLS) predictive model was investigated in the first part of the study. The results showed that this method improved the predictive ability of the model. Coefficient of determination (R2) and root mean square error of cross validation (RMSECV) were calculated in order to select sets of wavelengths to build the model with the best predictive ability. The second part of the study was based on building calibration models for predicting egg freshness in terms of number of storage day and egg quality in terms of Haugh Units and albumen pH. The results showed that the models had good predictive ability and R2 for number of storage days, Haugh Units and albumen pH were 0.89, 0.79 and 0.90, respectively. RMSECV for these three parameters were 1.65, 5.05 and 0.06, respectively.
L'oeuf est un composant fragile dans le regime alimentaire humain. Des changements importants arrivent dans loeuf pendant le stockage. La prediction de ces changements eat ctitique pour classer les oeufs selon leur qualité et leur fraîcheur. Les objectifs de cette étude étaient d'évaluer l'application méthode basée sur la spectroscopie visible et infra-rouge proche comme une method non destructive pour l'évaluation de la qualité et la fraîcheur des oeufs. Donc, la transmission visible et infra rouge proche des données spectrales aux limites de 350 à 2500 nm ont été exécutées à l'aide d'un radiosectromètre sur 360 oeufs récemment pondus. Un modèle des moindres carrées partiels (MCP) a été construit afin de lier les données soectrakes avec les méthodes destructives les plus utilisées, à savoir Unité de Haugh at le pH d'albumen en termes de qualité d'oeufs et le nombre de jours de stoclage en termees de fraîcheur d'oeufs. La première étude a traité de la capacité de la méthode maximum R2 à choisir les longueurs d'onde appropriées afin d'établir un modèle des moindres carrés partiels (MCP). Les résultats ont révélé combien cette méthode a été un bon outil dans le choix des longueurs d'onde instructives et dans l'amélioration de la capacité prédictive du modèle. Le coefficient de détermination (R2) et les erreurs de la racine carrée moyenne (ERCM) ont été calculés afin de choisir des ensembles de longueurs d'onde, lesquels aident le mieux à construire le modèle qui possède la meilleure capacité prédictive. La seconde étude a visé l'établissement des modèles prédictifs de la fraîcheur d'oeufs en fonction du n

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Adedipe, Oluwatosin Emmanuel. « Application of process analytical technology to wood a near infrared spectroscopy approach / ». Morgantown, W. Va. : [West Virginia University Libraries], 2008. https://eidr.wvu.edu/etd/documentdata.eTD?documentid=6037.

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Thesis (Ph. D.)--West Virginia University, 2008.
Title from document title page. Document formatted into pages; contains xi, 98 p. : ill. (some col.). Includes abstract. Includes bibliographical references (p. 47-52).

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Sayita, Yusuf. « Classification Of Migraineurs Using Functional Near Infrared Spectroscopy Data ». Master's thesis, METU, 2012. http://etd.lib.metu.edu.tr/upload/12614184/index.pdf.

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Classification of migraineur and healthy subjects using statistical pattern classifiers on functional Near Infrared Spectroscopy (NIRS) data is the main purpose of this study. Also a statistical comparison between trials that have different type of classifiers, classifier settings and feature sets is done. Features are extracted from raw light measurement data acquired with NIRS device, namely Niroxcope, during two separate previous studies, using Modified Beer-Lambert Law. After feature extraction, Naï
ve Bayes classifier and k Nearest Neighbor classifier are utilized with and with-out Principal Component Analysis in separate trials. Results obtained are compared within each other using statistical hypothesis tests namely Mc Nemar and Cochran Q.

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Stevenson, Brady Roos. « Analysis of Near-Infrared Phase Effects on Biometric Iris Data ». BYU ScholarsArchive, 2006. https://scholarsarchive.byu.edu/etd/1299.

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The purpose of this research is to ascertain potential iris scan data variations from near infrared waves derived from fluorescent illumination. Prior studies of iris data variances from infrared wave interference of halogen, incandescent, and sunlight with iris cameras suggest that similar changes may exist under near infrared wavelengths from fluorescent light. The concern is that the fluorescent energy emission may interfere with the near infrared detection of an iris camera. An iris camera is used to measure human eye characteristics known as biometrics. If such infrared emission is statistically significant, then it can alter the validity of the iris scan data. The experiment utilized nine hundred forty-five (945) scans from sixty-three (63) subjects. Measured results showed increased heat from ambient fluorescent illumination does not statistically alter the biometric readings of human eyes. The test results fail to reject that data loss will not occur as heat is increased in the ambient fluorescent light source.

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Naicker, Krishnaveni. « An investigation into the introduction of process analytical technology, using near infrared analysis, to selected pharmaceutical processes ». Thesis, Nelson Mandela Metropolitan University, 2007. http://hdl.handle.net/10948/577.

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Introduction: Process analytical technologies are systems for the analysis and control of manufacturing processes to assure acceptable end-product quality. This is achieved by timely measurements of critical parameters and performance attributes of raw material and in-process material and processes. The introduction of process analytical technology using near infrared analysis was investigated in three areas, namely incoming raw material analysis, blend uniformity analysis and moisture determination in the fluid bed dryer. Methodology: Incoming raw material identification - The FOSS XDS rapid content analyzer was used for the development of a NIR method for the identification and material qualification of starch maize and lactose monohydrate. Blend uniformity analysis – The SP15 Laboratory Blender fitted with near infrared probe was utilized for the study. Two types of blend experiments were designed to monitor the distribution of magnesium stearate (lubricant) in the blend, namely, a powder blend utilizing lactose monohydrate and a granule blend utilizing Ridaq® granule. Software methods were developed to monitor the standard deviation of the absorbance at the wavelengths that were specific for lactose monohydrate, Ridaq® granule and magnesium stearate. To confirm the prediction of end-point using near infrared, results were verified using an atomic absorption method for magnesium stearate. The blends were sampled at the selected time intervals corresponding to three states of the blend, namely, before end-point, at end-point and after end-point using a sampling plan. An additional six blends were conducted for the granule blend and sampled when the standard deviation had reached a value below 3 x 10-6 at the magnesium stearate wavelength at four consecutive data points (standard deviation value extrapolated from blends carried out to predetermined time intervals). Moisture determination in the fluid bed dryer – Moisture values for two products (Product A and Product B) were retrospectively collected from past production batches. A process capability study was conducted on the moisture values to determine if the current process was in a state of control. Results and Discussion: Incoming raw material identification – The algorithms used for the spectral library were able to distinguish between the raw materials selected. The spectral library positively identified the starch maize and lactose monohydrate samples that were not present in the library. The negative challenge with pregelatinised starch and tablettose demonstrated that the spectral library was able to differentiate between closely related compounds. Blend uniformity analysis – Blends sampled at the predetermined time intervals demonstrated a homogeneous state when the standard deviation of the absorbance was low and a non-homogeneous state when the standard deviation of the absorbance was high, thus near infrared prediction on the state of the blend was confirmed by the standard analytical methods. The series of Ridaq® granule and magnesium stearate blends sampled when the standard deviation was below 3 x 10-6 were homogeneous with the exception of one blend that was marginally out of specification. Blend durations were significantly lower than the standard blend durations used in the facility and ranged from 112 to 198 seconds. Moisture determination in the fluid bed dryer – From the process capability study of the two products it was noted that Product A is stable but can still be optimized while Product B is at a desirable state. The statistical evaluation of the moisture values for Product A and Product B demonstrated that the use of the product temperature to monitor the moisture gave consistent results. The current process is stable and capable of producing repeatable results although near infrared provides a means for continuously monitoring the product moisture and allows one to take action to prevent over-drying or under-drying. Conclusion: From the investigations conducted, it can be seen that there is definitely a niche for process analytical technology at this pharmaceutical company. The implementation is a gradual process of change, which may take time, probably several years (Heinze & Hansen 2005).

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Medendorp, Joseph Peter. « CHEMOMETRICS, SPECTROMETRY, AND SENSORS FOR INTEGRATED SENSING AND PROCESSING : ADVANCING PROCESS ANALYTICAL TECHNOLOGY ». Lexington, Ky. : [University of Kentucky Libraries], 2006. http://lib.uky.edu/ETD/ukyphsc2006d00464/JPMv4.pdf.

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Thesis (Ph. D.)--University of Kentucky, 2006.
Title from document title page (viewed on August 22, 2006). Document formatted into pages; contains: xvi, 229 p. : ill. (some col.). Includes abstract and vita. Includes bibliographical references (p. 213-227).

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Abdelgawad, Eid Ahmed Rabiea. « Inline optimization of cheese making using a near infrared light backscatter sensor technology ». Doctoral thesis, Universitat Autònoma de Barcelona, 2016. http://hdl.handle.net/10803/400021.

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L’elaboració de formatge es pot considerar un “procés controlat d’eliminació d’aigua de la llet”. Aquest procés concentra la proteïna, el greix i altres nutrients de la llet, augmentant la seva vida útil. La fabricació de formatge consta de diverses etapes d’entre les quals, dues de les més importants, tenen lloc en el tanc de formatgeria: la coagulació de la llet i la sinèresi de la quallada. La monitorització a temps real de la coagulació de la llet i l’enduriment del gel lacti, així com la predicció del temps de tall, són essencials per la producció de formatge ja que aquests factors exerceixen un impacte substancial tant en el rendiment formatger com en la qualitat del formatge final. Hi ha nombrosos factors que afecten el procés de fabricació de formatge mitjançant la modificació de la quantitat, la qualitat i les propietats tecnològiques de la llet. Si bé la majoria d’aquests factors són ben coneguts, alguns no han estat suficientment estudiats. L’objectiu general d’aquesta tesi fou avaluar l’impacte de la mescla de llet (i. e., diferents proporcions de llet de cabra, ovella i vaca) i la llet de baixa qualitat (i. e., llet d’animals amb mastitis subclínica) en la predicció del temps de coagulació, del temps de tall, de la velocitat d’eliminació del sèrum i de diversos altres índexs de producció formatgera, mitjançant la monitorització de la coagulació i la sinèresi amb vàries tecnologies de sensors de dispersió de llum d’infraroig proper: sensor de coagulació de laboratori CoAguLAb; sensor de coagulació CoAguLite i sensor de sinèresi LFV. Els dos darrers, instal·lats en la paret d’un tanc de formatgeria de deu litres a escala de planta pilot. El paràmetre de dispersió tmax i diversos altres paràmetres òptics de temps es correlacionaren significativament amb els temps visual i reològics de coagulació i de tall, així com amb els rendiments de sèrum i formatge i amb el recompte de cèl·lules somàtiques. Es va observar que les mescles de llet i la raça dels animals no tingueren un efecte significatiu (P ≥ 0,05) en els indicadors òptics ni reològics del temps de coagulació, mentre que la concentració d’enzim, la temperatura de coagulació i la infecció subclínica tingueren un efecte significatiu sobre tots els índexs, tant òptics com reològics, relacionats amb el temps de coagulació i la velocitat d’acoblament del gel lacti (i. e., agregació micel·lar i enduriment del gel). La mastitis subclínica, la mescla de llet, la temperatura i la raça tingueren un efecte significatiu sobre la sinèresi de la quallada, mentre que el rendiment formatger es veié afectat per la mastitis subclínica i la raça (cal fer notar que els efectes de la concentració d’enzim, la temperatura i la mescla de llet no foren avaluats directament). S’obtingueren models de predicció pels temps de coagulació i de tall, tant visuals com reològics, l’angle de fase (tgδ) en el moment de tall, la velocitat de sinèresi i diversos indicadors de rendiment formatger. Els nostres resultats confirmen la utilitat de la monitorització a temps real mitjançant dispersió de llum d’infraroig proper tant de la coagulació de llet com de l’eliminació de sèrum de la quallada, amb la finalitat de millorar el control d’aquestes dues etapes crítiques de l’elaboració del formatge. Els resultats obtinguts demostren que l’impacte de factors com la mescla de llets i la mastitis subclínica s’ha de tenir en consideració en les operacions de control de processos de l’elaboració de formatge.
La elaboración de queso puede considerarse como un "proceso controlado de eliminación de agua de la leche". Este proceso concentra la proteína, grasa y otros nutrientes de la leche, aumentando su vida útil. La fabricación de queso consta de varias etapas, de entre las cuales dos de las más importantes tienen lugar en la cuba quesera: la coagulación de la leche y la sinéresis de la cuajada. La monitorización a tiempo real de la coagulación de la leche y el endurecimiento del gel láctico, así como la predicción del tiempo de corte es esencial para la producción de queso ya que dichos factores ejercen un impacto sustancial tanto en el rendimiento quesero como en la calidad del queso final. Existen numerosos factores que afectan al proceso de fabricación de queso mediante la modificación de la cantidad, calidad y propiedades tecnológicas de la leche. Si bien la mayoría de dichos factores son bien conocidos, algunos no han sido suficientemente estudiados. El objetivo general de esta tesis fue evaluar el impacto de la mezcla de leche (i.e., diferentes proporciones de cabra, oveja y vaca) y la leche de baja calidad (i.e., leche de animales con mamitis subclínica) en la predicción del tiempo de coagulación, del tiempo de corte, de la velocidad de desuerado y de varios otros índices de producción quesera, mediante la monitorización de la coagulación y la sinéresis con varias tecnologías de sensores de dispersión de luz de infrarrojo próximo: sensor de coagulación de laboratorio CoAguLAb; sensor de coagulación CoAguLite y sensor de sinéresis LFV. Los dos últimos, instalados en la pared de una cuba de quesería de diez litros a escala de planta piloto. El parámetro de dispersión tmax y varios otros parámetros ópticos de tiempo se correlacionaron significativamente con los tiempos visuales y reológicos de coagulación y de corte así como con los rendimientos de suero y queso; y con el recuento de células somáticas. Se observó que las mezclas de leche y la raza de los animales no tienen un efecto significativo (P ≥ 0,05) ni en los indicadores ópticos ni en los reológicos del tiempo de coagulación, mientras que la concentración de enzima, la temperatura de coagulación, y la infección subclínica tuvieron un efecto significativo sobre todos los índices tanto ópticos como reológicos relacionados con el tiempo de coagulación y la velocidad de ensamblado del gel láctico (i.e., agregación micelar y endurecimiento del gel). La mastitis subclínica, la mezcla de leche, la temperatura y la raza tuvieron un efecto significativo sobre la sinéresis de la cuajada, mientras que el rendimiento quesero se vio afectado por la mastitis subclínica y la raza (nótese que el efecto de la concentración de enzima, la temperatura y la mezcla de leche no fue evaluado directamente). Se obtuvieron modelos de predicción para los tiempos de coagulación y de corte tanto visuales como reológicos, el ángulo de fase (tgδ) en el momento del corte, la velocidad de sinéresis y varios indicadores de rendimiento quesero. Nuestros resultados confirman la utilidad de la monitorización a tiempo real tanto de la coagulación de leche como del desuerado de la cuajada mediante dispersión de luz de infrarrojo próximo, a fin de mejorar el control de esas dos etapas críticas de elaboración de queso. Los resultados obtenidos demuestran que el impacto de factores tales como la mezcla de leches y la mastitis subclínica debe ser tenido en consideración en las operaciones de control de procesos de la elaboración de queso.
Cheese making is the “controlled process of removing water from milk”. This process concentrates the milk protein, fat and other nutrients and increases its shelf life. Cheese manufacture consists of two main steps occurring in the cheese vat, milk coagulation and curd syneresis. Real-time monitoring of milk coagulation, curd firming and syneresis as well as inline prediction of cutting time is essential for cheese making as those factors exert a substantial impact in both cheese yield and quality. Many factors affect the cheese manufacturing process by modifying the quantity, quality, and processing properties of the produced milk. The general objective of this dissertation was to evaluate the impact of milk mixture (i.e., different proportions of goat, sheep and cow milk) and low quality milk (i.e., milk from animals with subclinical mammary infections) in the prediction of clotting time, cutting time, syneresis rate and several other cheese making indexes based on monitoring milk coagulation and syneresis using NIR light backscatter sensor technologies. Several optical devices: a lab-scale coagulation tester (CoAguLab), an inline coagulation sensor and an inline large field of view (LFV) syneresis sensor were used to monitor milk coagulation, cutting time, and whey separation during Manchego cheese manufacture. Optical parameter tmax and several other time-based light backscatter parameters were highly correlated with visually- and rheologically-derived clotting and cutting times as well as cheese yield, yield of whey and SCC. It was observed that milk mixtures and animal breed did not have a significant (P ≥ 0.05) effect on optical and rheological time parameters related to clotting time, while different enzyme concentrations, coagulation temperatures, and subclinical infection had a significant effect on all optical and rheological parameters related to milk clotting time, and gel assembly rate (i.e., aggregation and firming rates). Subclinical mastitis, milk mixtures, temperature, and breed had a significant effect on curd syneresis while cheese yield was affected by subclinical mastitis and breed (note that syneresis effect of enzyme concentration, temperature and milk mixtures was not directly evaluated). Prediction models using light backscatter parameters alone or in combination with protein/solids concentration were successfully obtained for visually determined clotting and cutting times, rheologically derived gelation and cutting times, tanδ at cutting, syneresis rate constant and several cheese yield indicators. Our results confirm the usefulness of light backscatter inline monitoring of milk coagulation and curd syneresis for improved process control of those two critical cheese making steps. The results obtained show that the impact of factors such as milk mixtures and subclinical mastitis in cheese manufacture needs to be considered on cheese making process control operations.

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Chen, Limei. « Non-destructive measurement of tomato quality using visible and near-infrared reflectance spectroscopy ». Thesis, McGill University, 2009. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=32405.

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Experiments were conducted to assess the feasibility of determining the quality attributes of tomato (Lycopersicon esculentum Mill cv 'DRK 453' and 'Trust') based upon visible/near-infrared reflectance (VIS/NIR) spectroscopy. A partial least squares regression (PLS) method was used to build prediction models. Excellent prediction performance was achieved for lycopene content (LC), colour value a*/b* ratio, tomato colour index (TCI), and firmness. Coefficient of determination (R2) for each of the parameters was respectively 0.96, 0.99, 0.99, and 0.97. All these R2 were significant at 1% level. The root mean square errors of prediction (RMSEP) for all the parameters were low indicating the high quality of the fit of the prediction models. The values were 2.15, 0.06, 1.52, and 1.44 for LC, a*/b* ratio, TCI, and firmness, respectively. However, the models for prediction of titratable acidity, soluble solids content (SSC) and acid-Brix ratio showed relatively poor reliability, with R2 value of 0.49, 0.03 and 0.65, and RMSEP of 0.43, 0.15 and 0.08, respectively. Further, a model built by the PLS2 method showed good performance in simultaneously predicting a*/b* ratio, TCI, firmness, and LC of tomato, with R2 values of 0.99, 0.99, 0.97, and 0.92, and RMSEP of 0.06, 1.75, 1.44, and 3.03, respectively. Once again here all the R2 values were significant at 1% level.
Des essais visant à évaluer la faisabilité d'utiliser la spectroscopie de réflectance dans le visible et le proche infrarouge (VIS/PIR) pour déterminer certaines caractéristiques contribuant à la qualité de la tomate (Lycopersicon esculentum Mill. cv. 'DRK 453' et 'Trust') ont été menés. Une analyse de régression partielle par les moindres carrés a servi à bâtir des modèles de prédiction. D'excellentes prédictions ont été obtenues pour la teneur en lycopène (TL), la valeur chromatique a*/b*, l'indice de couleur de la tomate (ICT), et la fermeté. Les coefficients de détermination (R2) pour chacun de ces paramètres ont été de 0.96, 0.99, 0.99 et 0.97. Tous ces R2 ont été significatifs à un niveau de 1%. L'erreur-type de prédiction (ETP) a été petite pour tous ces paramètres, indiquant un très bon degré d'ajustement des modèles. Des valeurs d'ETP de 2.15, 0.06, 1.52 et 1.44 ont respectivement été obtenues pour le TL, le rapport a*/b*, l'ICT, et la fermeté. Cependant, les modèles visant à prédire l'acidité totale, la teneur en solides solubles et le rapport acide-Brix se sont montrés peu fiables avec des valeurs respectives de R2 de 0.49, 0.03 et 0.65 et de ETP de 0.43, 0.15 et 0.08. De plus, un modèle multivariable bâti par une méthode de régression partielle par des moindres carrés (PLS2) s'est montrée très performant pour la prédiction simultanée du rapport a*/b*, de l'ICT, de la fermeté et de la TL avec des valeurs respectives de R2 de 0.99, 0.99, 0.97 et 0.92 et de ETP de 0.06, 1.75, 1.44 et 3.03. Comme auparavant toutes les valeurs de R2 ont été significatives à un niveau de 1%.

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Machhadani, Houssaine, M. Beeler, S. Sakr, E. Warde, Y. Kotsar, M. Tchernycheva, M. P. Chauvat et al. « Systematic study of near-infrared intersubband absorption of polar and semipolar GaN/AlN quantum well ». Linköpings universitet, Halvledarmaterial, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-93977.

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We report on the observation of intersubband absorption in GaN/AlN quantum well superlattices grown on (11

2)-oriented GaN. The absorption is tuned in the 1.5–4.5 μm wavelength range by adjusting the well thickness. The semipolar samples are compared with polar samples with identical well thickness grown during the same run. The intersubband absorption of semipolar samples shows a significant red shift with respect to the polar ones due to the reduction of the internal electric field in the quantum wells. The experimental results are compared with simulations and confirm the reduction of the polarization discontinuity along the growth axis in the semipolar case. The absorption spectral shape depends on the sample growth direction: for polar quantum wells the intersubband spectrum is a sum of Lorentzian resonances, whereas a Gaussian shape is observed in the semipolar case. This dissimilarity is explained by different carrier localization in these two cases.

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Livres sur le sujet "Near-infrared technology"

Siegfried, Dähne, Resch-Genger Ute, Wolfbeis Otto S, North Atlantic Treaty Organization. Scientific Affairs Division. et NATO Advanced Research Workshop on Syntheses, Optical Properties and Applications of Near-Infrared (NIR) Dyes in High Technology Fields (1997 : Třešt̕, Czechoslovakia), dir. Near-infrared dyes for high technology applications. Dordrecht : Kluwer, 1998.

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Daehne, Siegfried, Ute Resch-Genger et Otto S. Wolfbeis, dir. Near-Infrared Dyes for High Technology Applications. Dordrecht : Springer Netherlands, 1998. http://dx.doi.org/10.1007/978-94-011-5102-3.

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1929-, Burns Donald A., et Ciurczak Emil W. 1945-, dir. Handbook of near-infrared analysis. 2^e éd. New York : Marcel Dekker, 2001.

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Ozaki, Yukihiro, W. Fred McClure et Alfred A. Christy, dir. Near-Infrared Spectroscopy in Food Science and Technology. Hoboken, NJ, USA : John Wiley & Sons, Inc., 2006. http://dx.doi.org/10.1002/0470047704.

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Ozaki, Yukihiro. Near Infrared Spectroscopy in Food Science and Technology. Hoboken : John Wiley & Sons, Inc., 2006.

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Y, Ozaki, McClure W. F et Christy Alfred A, dir. Near-infrared spectroscopy in food science and technology. Hoboken, N.J : Wiley-Interscience, 2007.

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Phil, Williams, Norris K. H et American Association of Cereal Chemists., dir. Near-infrared technology in the agricultural and food industries. St. Paul, Minn., USA : American Association of Cereal Chemists, 1987.

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Phil, Williams, Norris K. H et American Association of Cereal Chemists., dir. Near-infrared technology : In the agricultural and food industries. 2^e éd. St. Paul, Minn : American Association of Cereal Chemists, 2001.

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K, Drennen James, dir. Pharmaceutical and medical applications of near-infrared spectroscopy. New York : Marcel Dekker, 2002.

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Daehne, S. Near-Infrared Dyes for High Technology Applications. Ingramcontent, 2012.

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Chapitres de livres sur le sujet "Near-infrared technology"

Taira, Eizo. « Information and Communication Technology in Agriculture ». Dans Near-Infrared Spectroscopy, 381–89. Singapore : Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-8648-4_17.

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McNulty, John, Michael Born et Robert S. Pozos. « Near-Infrared Spectroscopy (NIRS) ». Dans Springer Handbook of Medical Technology, 423–38. Berlin, Heidelberg : Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-540-74658-4_22.

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Kessler, Rudolf W., et Waltraud Kessler. « Inline and Online Process Analytical Technology with an Outlook for the Petrochemical Industry ». Dans Near-Infrared Spectroscopy, 553–93. Singapore : Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-8648-4_23.

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Reich, Gabriele. « Mid and Near Infrared Spectroscopy ». Dans Advances in Delivery Science and Technology, 61–138. New York, NY : Springer New York, 2016. http://dx.doi.org/10.1007/978-1-4939-4029-5_3.

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Chen, Quansheng, Hao Lin et Jiewen Zhao. « Near-Infrared Spectroscopy Technology in Food ». Dans Advanced Nondestructive Detection Technologies in Food, 23–58. Singapore : Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-3360-7_2.

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Middendorf, Lyle, Jim Amen, Robert Bruce, Dan Draney, Darryl DeGraff, John Gewecke, Dan Grone et al. « Near-Infrared Fluorescence Instrumentation for DNA Analysis ». Dans Near-Infrared Dyes for High Technology Applications, 21–53. Dordrecht : Springer Netherlands, 1998. http://dx.doi.org/10.1007/978-94-011-5102-3_2.

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Lewis, E. Neil, Joseph W. Schoppelrei, Lisa Makein, Linda H. Kidder et Eunah Lee. « Near-Infrared Chemical Imaging for Product and Process Understanding ». Dans Process Analytical Technology, 245–79. Chichester, UK : John Wiley & Sons, Ltd, 2010. http://dx.doi.org/10.1002/9780470689592.ch8.

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Harthun, Sven, Kathrin Matischak et Peter Friedl. « Process Control of Antithrombin III Production by Near-Infrared Spectroscopy ». Dans Animal Cell Technology, 417–21. Dordrecht : Springer Netherlands, 1997. http://dx.doi.org/10.1007/978-94-011-5404-8_66.

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Lakowicz, Joseph R., Zakir Murtaza, Ignacy Gryczynski, Xiang-Qun Guo, Henryk Szmacinski, Li Li, Henryk Malak, Harriet Lin, Felix N. Castellano et Jonathan D. Dattelbaum. « Recent Developments in Fluorescence Spectroscopy ». Dans Near-Infrared Dyes for High Technology Applications, 3–19. Dordrecht : Springer Netherlands, 1998. http://dx.doi.org/10.1007/978-94-011-5102-3_1.

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Rurack, K., J. L. Bricks, J. L. Slominskii et U. Reschgenger. « Long Wavelength Emitting Fluorescence Probes for Metal Ions ». Dans Near-Infrared Dyes for High Technology Applications, 191–200. Dordrecht : Springer Netherlands, 1998. http://dx.doi.org/10.1007/978-94-011-5102-3_10.

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Actes de conférences sur le sujet "Near-infrared technology"

Evans III, Lawrence, Guillermo A. Casay, Dong Dai et Gabor Patonay. « Near-infrared fluorescence sensor technology ». Dans European Symposium on Optics for Environmental and Public Safety, sous la direction de Tuan Vo-Dinh. SPIE, 1995. http://dx.doi.org/10.1117/12.224115.

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Alismail, Ayman, Haochuan Wang, Gaia Barbiero, Syed Ali Hussain, Wolfgang Schweinberger, Ferenc Krausz et Hanieh Fattahi. « Near-Infrared Molecular Fieldoscopy ». Dans CLEO : Applications and Technology. Washington, D.C. : OSA, 2019. http://dx.doi.org/10.1364/cleo_at.2019.af3k.5.

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Goldstein, Dennis H., David B. Chenault, Michael G. Gulley et Kevin D. Spradley. « Near-infrared imaging polarimetry ». Dans International Symposium on Optical Science and Technology, sous la direction de Dennis H. Goldstein, David B. Chenault, Walter G. Egan et Michael J. Duggin. SPIE, 2002. http://dx.doi.org/10.1117/12.452878.

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Kobayashi, Hisataka. « Near Infrared Photoimmunotherapy of Cancer ». Dans CLEO : Applications and Technology. Washington, D.C. : OSA, 2021. http://dx.doi.org/10.1364/cleo_at.2021.aw2t.2.

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Kobayashi, Hisataka. « Near Infrared Photoimmunotherapy for Cancer ». Dans CLEO : Applications and Technology. Washington, D.C. : OSA, 2019. http://dx.doi.org/10.1364/cleo_at.2019.am1i.2.

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Joseph, G. B., B. J. Biddies, R. A. D'Silva, A. J. Picot, M. J. Ackerman et C. F. W. Harmer. « A Multi-Channel Near Infrared Spectroradiometer ». Dans Applications of Infrared Technology, sous la direction de Thomas L. Williams. SPIE, 1988. http://dx.doi.org/10.1117/12.945604.

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Dutta, A., D. Y. Wan, B. X. Yan, V. M. Shalaev, T. Venkatesan et A. Boltasseva. « Strontium Niobate for Near Infrared Plasmonics ». Dans CLEO : Applications and Technology. Washington, D.C. : OSA, 2019. http://dx.doi.org/10.1364/cleo_at.2019.jw2a.63.

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Hu, Changyu, Huixu Deng, Daniel Rosenmann, David A. Czaplewski, Xiaodong Yang et Jie Gao. « Experimental Demonstration of Near-Infrared Epsilon-Near-Zero Multilayer Metamaterial Slabs ». Dans CLEO : Applications and Technology. Washington, D.C. : OSA, 2014. http://dx.doi.org/10.1364/cleo_at.2014.jw2a.120.

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Cesetti, M., L. Placentino, G. Pinese, M. Libralato et P. Nicolosi. « Near infrared technology for material identification and selection ». Dans 2015 Fotonica AEIT Italian Conference on Photonics Technologies. Institution of Engineering and Technology, 2015. http://dx.doi.org/10.1049/cp.2015.0158.

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Huang, Wei, Yunhai Zhang, Xin Miao, Xiaojun Xue et Yun Xiao. « Near-infrared hyperspectral reflective confocal microscopy ». Dans International Symposium on Optoelectronic Technology and Application 2016. SPIE, 2016. http://dx.doi.org/10.1117/12.2243835.

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Rapports d'organisations sur le sujet "Near-infrared technology"

Near-infrared spectroscopy. Innovative technology summary report. Office of Scientific and Technical Information (OSTI), juillet 1999. http://dx.doi.org/10.2172/10143951.

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