Uncertainty visualization in 3D scalar data

One problem in most three-dimensional (3D) scalar data visualization techniques is that they often overlook to depict uncertainty that comes with the 3D scalar data and thus fail to faithfully present the 3D scalar data and have risks which may mislead users’ interpretations, conclusions or even decisions. Therefore this thesis focuses on the study of uncertainty visualization in 3D scalar data and we seek to create better uncertainty visualization techniques, as well as to find out the advantages/disadvantages of those state-of-the-art uncertainty visualization techniques. To do this, we address three specific hypotheses: (1) the proposed Texture uncertainty visualization technique enables users to better identify scalar/error data, and provides reduced visual overload and more appropriate brightness than four state-of-the-art uncertainty visualization techniques, as demonstrated using a perceptual effectiveness user study. (2) The proposed Linked Views and Interactive Specification (LVIS) uncertainty visualization technique enables users to better search max/min scalar and error data than four state-of-the-art uncertainty visualization techniques, as demonstrated using a perceptual effectiveness user study. (3) The proposed Probabilistic Query uncertainty visualization technique, in comparison to traditional Direct Volume Rendering (DVR) methods, enables radiologists/physicians to better identify possible alternative renderings relevant to a diagnosis and the classification probabilities associated to the materials appeared on these renderings; this leads to improved decision support for diagnosis, as demonstrated in the domain of medical imaging. For each hypothesis, we test it by following/implementing a unified framework that consists of three main steps: the first main step is uncertainty data modeling, which clearly defines and generates certainty types of uncertainty associated to given 3D scalar data. The second main step is uncertainty visualization, which transforms the 3D scalar data and their associated uncertainty generated from the first main step into two-dimensional (2D) images for insight, interpretation or communication. The third main step is evaluation, which transforms the 2D images generated from the second main step into quantitative scores according to specific user tasks, and statistically analyzes the scores. As a result, the quality of each uncertainty visualization technique is determined.

3D vanadium oxide inverse opal growth by electrodeposition

Three-dimensional vanadium pentoxide (V2O5) material architectures in the form of inverse opals (IOs) were fabricated using a simple electrodeposition process into artificial opal templates on stainless steel foil using an aqueous solution of VOSO4.χH2O with added ethanol. The direct deposition of V2O5 IOs was compared with V2O5 planar electrodeposition and confirms a similar progressive nucleation and growth mechanism. An in-depth examination of the chemical and morphological nature of the IO material was performed using X-ray crystallography, X-ray photoelectron spectroscopy, Raman scattering and scanning/transmission electron microscopy. Electrodeposition is demonstrated to be a function of the interstitial void fraction of the artificial opal and ionic diffusivity that leads to high quality, phase pure V2O5 inverse opals is not adversely affected by diffusion pathway tortuosity. Methods to alleviate electrodeposited overlayer formation on the artificial opal templates for the fabrication of the porous 3D structures are also demonstrated. Such a 3D material is ideally suited as a cathode for lithium ion batteries, electrochromic devices, sensors and for applications requiring high surface area electrochemically active metal oxides.

High-Q hybrid 3D-2D slab-3D photonic crystal microcavity.

The radiation loss in the escaping light cone with a two-dimensional (2D) photonic crystal slab microcavity can be suppressed by means of cladding the low-Q slab microcavity by three-dimensional woodpile photonic crystals with the complete bandgap when the resonance frequency is located inside the complete bandgap. It is confirmed that the hybrid microcavity based on a low-Q, single-defect photonic crystal slab microcavity shows improvement of the Q factor without affecting the mode volume and modal frequency. Whereas 2D slab microcavities exhibit Q saturation with an increase in the number of layers, for the analyzed hybrid microcavities with a small gap between the slab and woodpiles, the Q factor does not saturate.

3D refraction correction and extraction of clinical parameters from spectral domain optical coherence tomography of the cornea.

Capable of three-dimensional imaging of the cornea with micrometer-scale resolution, spectral domain-optical coherence tomography (SDOCT) offers potential advantages over Placido ring and Scheimpflug photography based systems for accurate extraction of quantitative keratometric parameters. In this work, an SDOCT scanning protocol and motion correction algorithm were implemented to minimize the effects of patient motion during data acquisition. Procedures are described for correction of image data artifacts resulting from 3D refraction of SDOCT light in the cornea and from non-idealities of the scanning system geometry performed as a pre-requisite for accurate parameter extraction. Zernike polynomial 3D reconstruction and a recursive half searching algorithm (RHSA) were implemented to extract clinical keratometric parameters including anterior and posterior radii of curvature, central cornea optical power, central corneal thickness, and thickness maps of the cornea. Accuracy and repeatability of the extracted parameters obtained using a commercial 859nm SDOCT retinal imaging system with a corneal adapter were assessed using a rigid gas permeable (RGP) contact lens as a phantom target. Extraction of these parameters was performed in vivo in 3 patients and compared to commercial Placido topography and Scheimpflug photography systems. The repeatability of SDOCT central corneal power measured in vivo was 0.18 Diopters, and the difference observed between the systems averaged 0.1 Diopters between SDOCT and Scheimpflug photography, and 0.6 Diopters between SDOCT and Placido topography.

Characterization of Image Quality for 3D Scatter Corrected Breast CT Images.

The goal of this study was to characterize the image quality of our dedicated, quasi-monochromatic spectrum, cone beam breast imaging system under scatter corrected and non-scatter corrected conditions for a variety of breast compositions. CT projections were acquired of a breast phantom containing two concentric sets of acrylic spheres that varied in size (1-8mm) based on their polar position. The breast phantom was filled with 3 different concentrations of methanol and water, simulating a range of breast densities (0.79-1.0g/cc); acrylic yarn was sometimes included to simulate connective tissue of a breast. For each phantom condition, 2D scatter was measured for all projection angles. Scatter-corrected and uncorrected projections were then reconstructed with an iterative ordered subsets convex algorithm. Reconstructed image quality was characterized using SNR and contrast analysis, and followed by a human observer detection task for the spheres in the different concentric rings. Results show that scatter correction effectively reduces the cupping artifact and improves image contrast and SNR. Results from the observer study indicate that there was no statistical difference in the number or sizes of lesions observed in the scatter versus non-scatter corrected images for all densities. Nonetheless, applying scatter correction for differing breast conditions improves overall image quality.

An enteroendocrine cell-enteric glia connection revealed by 3D electron microscopy.

The enteroendocrine cell is the cornerstone of gastrointestinal chemosensation. In the intestine and colon, this cell is stimulated by nutrients, tastants that elicit the perception of flavor, and bacterial by-products; and in response, the cell secretes hormones like cholecystokinin and peptide YY--both potent regulators of appetite. The development of transgenic mice with enteroendocrine cells expressing green fluorescent protein has allowed for the elucidation of the apical nutrient sensing mechanisms of the cell. However, the basal secretory aspects of the enteroendocrine cell remain largely unexplored, particularly because a complete account of the enteroendocrine cell ultrastructure does not exist. Today, the fine ultrastructure of a specific cell can be revealed in the third dimension thanks to the invention of serial block face scanning electron microscopy (SBEM). Here, we bridged confocal microscopy with SBEM to identify the enteroendocrine cell of the mouse and study its ultrastructure in the third dimension. The results demonstrated that 73.5% of the peptide-secreting vesicles in the enteroendocrine cell are contained within an axon-like basal process. We called this process a neuropod. This neuropod contains neurofilaments, which are typical structural proteins of axons. Surprisingly, the SBEM data also demonstrated that the enteroendocrine cell neuropod is escorted by enteric glia--the cells that nurture enteric neurons. We extended these structural findings into an in vitro intestinal organoid system, in which the addition of glial derived neurotrophic factors enhanced the development of neuropods in enteroendocrine cells. These findings open a new avenue of exploration in gastrointestinal chemosensation by unveiling an unforeseen physical relationship between enteric glia and enteroendocrine cells.

Localization of Metal Electrodes in the Intact Rat Brain Using Registration of 3D Microcomputed Tomography Images to a Magnetic Resonance Histology Atlas.

Simultaneous neural recordings taken from multiple areas of the rodent brain are garnering growing interest due to the insight they can provide about spatially distributed neural circuitry. The promise of such recordings has inspired great progress in methods for surgically implanting large numbers of metal electrodes into intact rodent brains. However, methods for localizing the precise location of these electrodes have remained severely lacking. Traditional histological techniques that require slicing and staining of physical brain tissue are cumbersome, and become increasingly impractical as the number of implanted electrodes increases. Here we solve these problems by describing a method that registers 3-D computerized tomography (CT) images of intact rat brains implanted with metal electrode bundles to a Magnetic Resonance Imaging Histology (MRH) Atlas. Our method allows accurate visualization of each electrode bundle's trajectory and location without removing the electrodes from the brain or surgically implanting external markers. In addition, unlike physical brain slices, once the 3D images of the electrode bundles and the MRH atlas are registered, it is possible to verify electrode placements from many angles by "re-slicing" the images along different planes of view. Further, our method can be fully automated and easily scaled to applications with large numbers of specimens. Our digital imaging approach to efficiently localizing metal electrodes offers a substantial addition to currently available methods, which, in turn, may help accelerate the rate at which insights are gleaned from rodent network neuroscience.

Investigation and Development of a Fully 3D Tilt Capable Hybrid SPECT - CT System for Dedicated Breast Imaging

X-ray mammography has been the gold standard for breast imaging for decades, despite the significant limitations posed by the two dimensional (2D) image acquisitions. Difficulty in diagnosing lesions close to the chest wall and axilla, high amount of structural overlap and patient discomfort due to compression are only some of these limitations. To overcome these drawbacks, three dimensional (3D) breast imaging modalities have been developed including dual modality single photon emission computed tomography (SPECT) and computed tomography (CT) systems. This thesis focuses on the development and integration of the next generation of such a device for dedicated breast imaging. The goals of this dissertation work are to: [1] understand and characterize any effects of fully 3-D trajectories on reconstructed image scatter correction, absorbed dose and Hounsifeld Unit accuracy, and [2] design, develop and implement the fully flexible, third generation hybrid SPECT-CT system capable of traversing complex 3D orbits about a pendant breast volume, without interference from the other. Such a system would overcome artifacts resulting from incompletely sampled divergent cone beam imaging schemes and allow imaging closer to the chest wall, which other systems currently under research and development elsewhere cannot achieve.

The dependence of x-ray scatter radiation on object shape, size, material composition and the CT acquisition trajectory, was investigated with a well-established beam stop array (BSA) scatter correction method. While the 2D scatter to primary ratio (SPR) was the main metric used to characterize total system scatter, a new metric called ‘normalized scatter contribution’ was developed to compare the results of scatter correction on 3D reconstructed volumes. Scatter estimation studies were undertaken with a sinusoidal saddle (±15° polar tilt) orbit and a traditional circular (AZOR) orbit. Clinical studies to acquire data for scatter correction were used to evaluate the 2D SPR on a small set of patients scanned with the AZOR orbit. Clinical SPR results showed clear dependence of scatter on breast composition and glandular tissue distribution, otherwise consistent with the overall phantom-based size and density measurements. Additionally, SPR dependence was also observed on the acquisition trajectory where 2D scatter increased with an increase in the polar tilt angle of the system.

The dose delivered by any imaging system is of primary importance from the patient’s point of view, and therefore trajectory related differences in the dose distribution in a target volume were evaluated. Monte Carlo simulations as well as physical measurements using radiochromic film were undertaken using saddle and AZOR orbits. Results illustrated that both orbits deliver comparable dose to the target volume, and only slightly differ in distribution within the volume. Simulations and measurements showed similar results, and all measured dose values were within the standard screening mammography-specific, 6 mGy dose limit, which is used as a benchmark for dose comparisons.

Hounsfield Units (HU) are used clinically in differentiating tissue types in a reconstructed CT image, and therefore the HU accuracy of a system is very important, especially when using non-traditional trajectories. Uniform phantoms filled with various uniform density fluids were used to investigate differences in HU accuracy between saddle and AZOR orbits. Results illustrate the considerably better performance of the saddle orbit, especially close to the chest and nipple region of what would clinically be a pedant breast volume. The AZOR orbit causes shading artifacts near the nipple, due to insufficient sampling, rendering a major portion of the scanned phantom unusable, whereas the saddle orbit performs exceptionally well and provides a tighter distribution of HU values in reconstructed volumes.

Finally, the third generation, fully-suspended SPECT-CT system was designed in and developed in our lab. A novel mechanical method using a linear motor was developed for tilting the CT system. A new x-ray source and a custom made 40 x 30 cm2 detector were integrated on to this system. The SPECT system was nested, in the center of the gantry, orthogonal to the CT source-detector pair. The SPECT system tilts on a goniometer, and the newly developed CT tilting mechanism allows ±15° maximum polar tilting of the CT system. The entire gantry is mounted on a rotation stage, allowing complex arbitrary trajectories for each system, without interference from the other, while having a common field of view. This hybrid system shows potential to be used clinically as a diagnostic tool for dedicated breast imaging.

Optical-CT 3D Dosimetry Using Fresnel Lenses with Minimal Refractive-Index Matching Fluid.

Telecentric optical computed tomography (optical-CT) is a state-of-the-art method for visualizing and quantifying 3-dimensional dose distributions in radiochromic dosimeters. In this work a prototype telecentric system (DFOS-Duke Fresnel Optical-CT Scanner) is evaluated which incorporates two substantial design changes: the use of Fresnel lenses (reducing lens costs from $10-30K t0 $1-3K) and the use of a 'solid tank' (which reduces noise, and the volume of refractively matched fluid from 1 ltr to 10 cc). The efficacy of DFOS was evaluated by direct comparison against commissioned scanners in our lab. Measured dose distributions from all systems were compared against the predicted dose distributions from a commissioned treatment planning system (TPS). Three treatment plans were investigated including a simple four-field box treatment, a multiple small field delivery, and a complex IMRT treatment. Dosimeters were imaged within 2 h post irradiation, using consistent scanning techniques (360 projections acquired at 1 degree intervals, reconstruction at 2mm). DFOS efficacy was evaluated through inspection of dose line-profiles, and 2D and 3D dose and gamma maps. DFOS/TPS gamma pass rates with 3%/3mm dose difference/distance-to-agreement criteria ranged from 89.3% to 92.2%, compared to from 95.6% to 99.0% obtained with the commissioned system. The 3D gamma pass rate between the commissioned system and DFOS was 98.2%. The typical noise rates in DFOS reconstructions were up to 3%, compared to under 2% for the commissioned system. In conclusion, while the introduction of a solid tank proved advantageous with regards to cost and convenience, further work is required to improve the image quality and dose reconstruction accuracy of the new DFOS optical-CT system.

Promedio bayesiano de modelos para la predicción del consumo máximo de oxígeno en deportistas con datos de no-ejercicio

Históricamente, los modelos de no-ejercicio para predecir el consumo máximo de oxígeno (VO2max) han sido construidos mediante regresión lineal frecuentista, usando técnicas estándar de selección de modelos. Sin embargo, existe incertidumbre acerca de la estructura estadística en el proceso de selección del modelo. En este estudio se propuso construir un modelo de no-ejercicio para predecir el VO2max en deportistas orientados al rendimiento, considerando la incertidumbre de modelo a través del Promedio Bayesiano de Modelos (BMA). Un objetivo adicional fue comparar la performance predictiva del BMA con las de los modelos derivados de varias técnicas frecuentistas usuales de selección de variables. Con tal fin, se implementó un submuestreo aleatorio estratificado repetido. Los datos incluyeron observaciones de la variable respuesta (en L·min-1), así como registros de Género, Deporte, Edad, Peso, Talla e Índice de masa corporal (BMI) (Edad = 22.1 ± 4.9 años, media ± SD; n = 272). Se propuso una clasificación de deportes con el objetivo de incluirla dentro del proceso de construcción del modelo: Combate, Juego, Resistencia 1 y Resistencia 2. El enfoque BMA se implementó en base a dos métodos: Occam's window y Composición de Modelo mediante el método de Monte Carlo con Cadenas de Markov (MC²). Se observaron discrepancias en la selección de variables entre los procedimientos frecuentistas. Ambos métodos de BMA produjeron resultados muy similares. Los modelos que incluyeron Género y las variables dummies para Resistencia 1 y Resistencia 2 acumularon virtualmente toda la probabilidad de modelo a posteriori. El Peso fue el predictor continuo con la más alta probabilidad de inclusión a posteriori (menor a 0.8). Las combinaciones de variables que involucraron predictores con un alto nivel de multicolinealidad fueron desacreditadas. Los modelos con sustancial contribución para el BMA presentaron un ajuste apreciable (R² ajustado menor a 0.8). Entre los modelos seleccionados por estrategias frecuentistas, el obtenido mediante el método de regresión por pasos (Stepwise regression method) con alfa igual a 0.05 fue el más respaldado por los datos, en términos de probabilidad de modelo a posteriori. En concordancia con la literatura, el BMA tuvo mejor performance predictiva de los datos fuera de la muestra que los modelos seleccionados por técnicas frecuentistas, medida por la cobertura del intervalo de predicción de 90 por ciento. La clasificación de deportes reveló resultados consistentes.

Inferencia bayesiana sobre los parámetros de dispersión genéticos y ambientales en modelos animales con efectos maternos

Los modelos 'modelos animales con efectos maternos' (MAM) son modelos lineales mixtos que se utilizan para ajustar registros de caracteres bajo la influencia de efectos maternos. Uno de los desafíos más importantes en el marco de los MAM es la estimación de los parámetros de dispersión o 'componentes de (co) varianza' (CVC). En esta tesis se introducen desde una perspectiva bayesiana contribuciones teóricas y metodológicas con relación a la estimación de CVC para MAM sujetos a estructuras de covarianza novedosas. En primer lugar, se describe una implementación del análisis bayesiano jerárquico vía el algoritmo del muestreo de Gibbs. Luego, se considera una especificación conjugada diferente para la distribución a priori de la matriz de covarianza genética, basada en la distribución Wishart invertida generalizada, y se presenta una estrategia para determinar los correspondientes hiperparámetros. Esta estrategia fue comparada contra otras especificaciones a priori mediante un estudio de simulación estocástica, y produjo estimaciones precisas de los parámetros genéticos, con menores errores estándares y mejor tasa de convergencia. En segundo lugar, se presenta una formulación alternativa del MAM que incluye un parámetro de correlación ambiental entre pares de observaciones madre-progenie, y se desarrolla un procedimiento de estimación basado en un algoritmo de muestreo por grilla. El procedimiento fue programado y ejecutado exitosamente, y se obtuvo la primera estimación del parámetro de correlación con datos de campo para peso al destete en bovinos de carne. Por último, se considera el problema de la estimación de CVC en una población multirracial, donde en general es necesario especificar una estructura de covarianza heterogénea para los valores de cría. En particular, se demuestra que el modelo basado en la descomposición de la matriz de covarianza genética es equivalente al que deriva de la teoría genética cuantitativa. Además, se extiende el modelo para incluir efectos maternos y se describe la implementación de un análisis bayesiano jerárquico con el objetivo de estimar los CVC. El procedimiento fue implementado con éxito en datos experimentales de peso al destete y se obtuvieron por primera vez estimaciones para el conjunto completo de CVC.

Modelos animales para caracteres con efectos maternos, madres no identificadas e información incompleta

La evaluación genética para caracteres de crecimiento pre - destete requiere ajustar modelos animales con efectos maternos (MAM). Tanto la estimación paramétrica de la variabilidad como la evaluación genética mediante MAM son realizadas empleando datos de campo, muchos de los cuales no poseen información completa para todas las variables explicativas maternas. Es común no contar con la identificación de madres (biológicas y/o receptoras), de abuelas maternas y, consecuentemente, de la edad de la madre (EM). Este problema es bien marcado en razas compuestas como Brangus y Braford que tienen políticas para registrar animales de pedigrí "abierto". Además, no existe un consenso sobre cuál es el mejor modelo de predicción, y existen interrogantes sobre la magnitud de los componentes de (co) varianza genético-aditivos y ambientales del modelo de evaluación. La primera investigación de esta tesis consistió en la estimación, mediante métodos bayesianos de los parámetros de dispersión en MAMs con distintas estructuras de (co) varianza, para datos de peso al destete de animales Angus de pedigrí. El análisis se caracterizó por la originalidad en los muestreos de las distribuciones marginales posteriores de las covarianzas genéticas aditivas y de la correlación entre los efectos ambientales maternos permanentes de una vaca y sus hijas también madres. Con el objeto de especificar correctamente la fracción aditiva de las (co) varianzas cuando se desconocen las madres y/o abuelas maternas de los animales con datos, en otro capítulo se desarrollaron MAMs equivalentes que no requieren alargar los vectores de los valores de cría con madres o abuelas fantasmas. Finalmente, se desarrolló un modelo mixto que atenúa el sesgo por error de medición clásico en el efecto EM, e introduce splines penalizadas y una estructura de (co) variación autoregresiva de orden 1 para suavizar las covarianzas residuales Este modelo es apropiado para ajustar datos de animales nacidos por transplante embrionario con madres receptoras desconocidas

Sistemas de evaluación de tierras y elaboración de modelos de aptitud de uso agrícola, para distintos escenarios climáticos, en un sector de la subregión pampa arenosa (Provincia de Buenos Aires, Argentina)

La Pampa Arenosa ha sido escenario de cambios en el uso del territorio que respondieron principalmente al aumento de las precipitaciones a partir de la década del 70. La evaluación de las tierras es una etapa crítica en la planificación del uso sustentable. Por este motivo, se analizaron distintos sistemas de evaluación de tierras y se desarrollaron modelos expertos que consideren los factores ambientales heredados y las variaciones climáticas, para el sector de dunas longitudinales de la Pampa Arenosa en la Provincia de Buenos Aires, a escala 1: 50.000, considerando a los partidos de Nueve de Julio, Carlos Casares, Pehuajó y Trenque Lauquen. Las tierras fueron clasificadas por Capacidad de Uso, Indice de Productividad (IP) y se generaron sistemas expertos, utilizando el programa ALES, para los tipos de utilización de las tierras (TUTs) : maíz, soja y trigo. La homogeneidad de las series climáticas de precipitaciones se determinó mediante el test de Rachas. La aplicación del test de Pettitt permitió identificar la existencia de un cambio abrupto en las precipitaciones y el este de Mann Kendall mostró una tendencia creciente en relación a la precipitación anual. Las tierras con severas (clase III) y muy severas limitaciones (clase IV), fueron las más frecuentes ocupando el 42,6 por ciento y 29,8 por ciento respectivamente del área. Se comprobó que el IP de las tierras se incrementó con el aumento de las precipitaciones, alcanzando su máxima expresión climática en el período posterior al cambio abrupto. Las tierras de moderada capacidad productiva con valores de IP entre 65-51 ocuparon la mayor superficie de área de estudio. Los modelos expertos según los TUTs presentaron una aptitud de uso de las tierras variable, condicionada por la capacidad de retención hídrica de los suelos. Los modelos expertos fueron sensibles a las variaciones climáticas y el cambio abrupto en las precipitaciones.

Modelos explicativos y predictivos de la productividad, disponibilidad y calidad de forraje basados en sensores remotos

La productividad primaria neta aérea (PPNA) y la biomasa y la calidad forrajeras son clave en los sistemas pastoriles. Dada su variación espacial y temporal, contar con descripciones de dicha variación y con herramientas de monitorización facilita y perfecciona su manejo. Los sensores remotos permiten estimar frecuente y detalladamente la PPNA pero no la biomasa y la calidad. El objetivo de esta tesis es mejorar el conocimiento sobre la PPNA y las posibilidades de monitorización de los recursos forrajeros en general y los de la Pampa Deprimida en particular. Primero, se presentan patrones de variación de la PPNA de los principales recursos forrajeros y modelos de prospección de la PPNA primaveral para distintas unidades de vegetación. Segundo, se presentan modelos de estimación de la biomasa y calidad forrajera basados en sensores remotos y generados mediante ensayos en condiciones controladas y a campo. La variación espacial de la PPNA fue explicada por la precipitación a escala regional, los suelos a escala subregional y los suelos y el pastoreo a escala local. Entre recursos, las pasturas de loma tuvieron mayor PPNA que los pastizales de bajo; dicha diferencia aumentó con la precipitación media. Entre escalas, la variación espacial fue mayor a escala regional y la temporal fue mayor a escala local. La PPNA primaveral se relacionó con variables ambientales de meses previos diferentes según los pastizales estuvieran dominados por especies invernales o estivales, y según las pasturas fueran de suelos profundos o someros. Las estimaciones de la biomasa y calidad forrajera fueron satisfactorias en general, aunque imprecisas bajo ciertas condiciones experimentales como sequía, fertilización, y presencia de biomasa senescente, que requirieron modelos específicos. La estimación de la biomasa total a campo mediante un modelo basado en estimaciones independientes de la biomasa fotosintética y la no fotosintética resultó precisa a lo largo de un año. Los resultados aportan información acerca de los controles ambientales de la PPNA en pastizales subhúmedos y representan un avance en la estimación de la biomasa y calidad forrajera mediante sensores remotos

Sistema de observaciones fenológicas y fenométricas para la calibración de modelos fisiológicos de rendimiento

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