Soil-liming effects on the development and nutritional status of the carambola tree and its fruit-yielding capacity

Soil acidity is one of the most important factors limiting agricultural production in the tropics. For this reason, the objective of this research work was to evaluate the effects of soil liming on the performance of carambola (Averrhoa carambola) trees. The experiment took place at the Citrus Experimental Station in Bebedouro, state of São Paulo, Brazil. The soil was a Typic Haplustox (V = 26% at the 0- to 20-cm layer) between August 1999 and July 2003. The following doses of limestone were employed: 0, 1.85, 3.71, 5.56, and 7.41 t ha(-1). During 40 months after the experiment was set up, soil chemical attributes were periodically examined. For a period of 2 years, the trees had their leaves analyzed for micro-and macronutrients; their trunk diameter, height, and crown volume measured; and the production of fruits determined. Liming improved in evaluated chemical attributes of the soil: pH, calcium (Ca), magnesium (Mg), BS, V, and hydrogen and aluminium (H + At) from the upper 60 cm of soil when the samples were taken from both the line and between the lines of plants. In the leaves, the levels of Ca and Mg also increased. The highest fruit yields were observed when soil base saturations reached 45% on the lines and 50% between the lines, as well as when foliar levels of 8.0 g of Ca and 4.7 a of Mg per kilogram of leaves were attained.

Reproductive investment and seedling survival of the mast-fruiting rain forest tree, Microberlinia bisulcata A. chev

In the southern part of Korup National Park, Cameroon, the mast fruiting tree Microberlinia bisulcata occurs as a codominant in groves of ectomycorrhizal Caesalpiniaceae within a mosaic of otherwise species-rich lowland rain forest. To estimate the amount of carbon and nutrients invested in reproduction during a mast fruiting event, and the consequential seed and seedling survival, three related field studies were made in 1995. These provided a complete seed and seedling budget for the cohort. Seed production was estimated by counting woody pods on the forest floor. Trees produced on average 26,000 (range 0-92,000) seeds/tree, with a dry mass of 16.6 kg/tree. Seeds were contained in woody pods of mass 307 kg/tree. Dry mass production of pods and seeds was 1034 kg ha(-1), equivalent to over half (55%) of annual leaf litterfall for this species, and contained 13% of the nitrogen and 21% of the phosphorus in annual leaf litterfall. Seed and young-seedling mortality was investigated with open quadrats and cages to exclude vertebrate predators, at two distances from the parent tree. The proportion of seeds on the forest floor which disappeared in the first 6 wk after dispersal was 84%, of which 26.5% was due to likely vertebrate removal, 36% to rotting, and 21.5% to other causes. Vertebrate predation was greater close to the stem than 5 m beyond the crown (41 vs 12% of seeds disappearing) where the seed shadow was less dense. Previous studies have demonstrated an association between mast years at Korup and high dry-season radiation before flowering, and have shown lower leaf-litterfall phosphorus concentrations following mast fruiting. The emerging hypothesis is that mast fruiting is primarily imposed by energy limitation for fruit production, but phosphorus supply and vertebrate predation are regulating factors. Recording the survival of naturally-regenerating M. bisulcata seedlings (6-wk stage) showed that 21% of seedlings survived to 31 mo. A simple three-stage recruitment model was constructed. Mortality rates were initially high and peaked again in each of the next two dry seasons, with smaller peaks in the two intervening wet seasons, these latter coinciding with annual troughs in radiation. The very poor recruitment of M. bisulcata trees in Korup, demonstrated in previous investigations, appears not to be due to a limitation in seed or young-seedling supply, but rather by factors operating at the established-seedling stage.

Tree Species Composition and Harvest Intensity Affect Herbivore Density and Leaf Damage on Beech, Fagus sylvatica, in Different Landscape Contexts

Most forests are exposed to anthropogenic management activities that affect tree species composition and natural ecosystem processes. Changes in ecosystem processes such as herbivory depend on management intensity, and on regional environmental conditions and species pools. Whereas influences of specific forest management measures have already been addressed for different herbivore taxa on a local scale, studies considering effects of different aspects of forest management across different regions are rare. We assessed the influence of tree species composition and intensity of harvesting activities on arthropod herbivores and herbivore-related damage to beech trees, Fagus sylvatica, in 48 forest plots in three regions of Germany. We found that herbivore abundance and damage to beech trees differed between regions and that – despite the regional differences - density of tree-associated arthropod taxa and herbivore damage were consistently affected by tree species composition and harvest intensity. Specifically, overall herbivore damage to beech trees increased with increasing dominance of beech trees – suggesting the action of associational resistance processes – and decreased with harvest intensity. The density of leaf chewers and mines was positively related to leaf damage, and several arthropod groups responded to beech dominance and harvest intensity. The distribution of damage patterns was consistent with a vertical shift of herbivores to higher crown layers during the season and with higher beech dominance. By linking quantitative data on arthropod herbivore abundance and herbivory with tree species composition and harvesting activity in a wide variety of beech forests, our study helps to better understand the influence of forest management on interactions between a naturally dominant deciduous forest tree and arthropod herbivores.

Exploring Growth Variability and Crown Vitality of Sessile Oak (Quercus Petraea) in the Czech Republic

Unraveling climatic effects on growth of oak - Europe’s most ecologically and economically important forest species - has been the subject of many recent studies; however, more insight based on field data is necessary to better understand the relationship between climate and tree growth and to adapt forest management strategies to future climate change. In this report, we explore the influence of temperature, precipitation and drought variability on the productivity and vitality of oak stands in the Czech Highlands. We collected 180 cores from mature oaks (Quercus petraea) at four forest stands in the Czech Drahany Highlands. Standard dendromethods were used for sample preparation, ring width measurements, cross-dating, chronology development, and the assessment of growth-climate response patterns. Crown vitality was also evaluated, using the modified ICP Forests methodology. Late spring precipitation totals between May and June as well as the mean July temperature for the year of ring formation were found to be the most important factors for oak growth, whereas crown condition was significantly affected by spring and summer drought. This study is rep-resentative for similar bio-ecological habitats across Central Europe and can serve as a dendroclima-tological blueprint for earlier periods for which detailed meteorological information is missing .

Stand Structure Governs the Crown Collisions of Lodgepole Pine

We investigated tree sway and crown collision behavior of even-aged lodgepole pine (Pinus contorta Dougl. ex Loud. var. latifolia Engelm.) stands of different structure in Alberta, Canada, to examine how these factors might affect loss of leaf area as stands mature. The Two Creeks stand (TC) had high density and slender trees, while the Chickadee stand (CH) had stout trees. The TC stand was then thinned (TCT) to reduce the stand density. For each stand, simultaneous tree sways of a group of 10 trees were monitored with biaxial clinometers during wind speed of 5 m/s (canopy top). Crown collisions were reconstructed by combining sway displacement of individual trees with their respective crown dimensions. Comparing the sway statistics between stands with contrasting mean bole slenderness (TC and CH) indicated that more slender trees have greater sway displacements, faster sway speeds, and a greater depth of collision. Disturbance by thinning increased sway displacements, sway speeds, and depth of collisions at TCT. Tree sway patterns were circular in shape and not aligned with wind direction, but patterns were elongated after thinning. This demonstrates the high frequency of crown collision experienced by stands with slender trees and supports the notion that crown collisions result in empty space between crowns of trees.

Processing Pipeline for Digitalizing the Lineage Tree of Early Zebrafish Embryogenesis from Multiharmonic Imaging

The reconstruction of the cell lineage tree of early zebrafish embryogenesis requires the use of in-vivo microscopy imaging and image processing strategies. Second (SHG) and third harmonic generation (THG) microscopy observations in unstained zebrafish embryos allows to detect cell divisions and cell membranes from 1-cell to 1K-cell stage. In this article, we present an ad-hoc image processing pipeline for cell tracking and cell membranes segmentation enabling the reconstruction of the early zebrafish cell lineage tree until the 1K-cell stage. This methodology has been used to obtain digital zebrafish embryos allowing to generate a quantitative description of early zebrafish embryogenesis with minute temporal accuracy and μm spatial resolution

Variation throughout the tree stem in the physical-mechanical properties of the wood of Abies alba Mill. from the Spanish Pyrenees

This study analyses the variation of main physical-mechanical properties of wood along the longitudinal and radial directions of the tree for Abies alba Mill. growing in the Spanish Pyrenees. Small clear specimens were used to study the properties of volumetric shrinkage (VS), density (?), hardness (H), bending strength (MOR), modulus of elasticity (MOE), maximum compressive strength parallel to the grain (MCS) and impact strength (K). Several models of properties variation in the longitudinal and radial directions were analyzed. Main trends of variation of properties throughout the tree stem were identified although none of them could be fitted to predictive statistical models. Along the longitudinal direction, the properties studied followed a downward trend from the base to the crown, which was not significant in all cases, indicating that no differences in quality existed. Throughout the radial direction the trend is upward for the first 40-50 growth rings, after which it slopes downwards, more gently at first until rings 70-75 and then more steeply. This behaviour is related to variation in wood structure from the pith to the bark, depending on whether the wood is juvenile, sapwood or heartwood, and to wood maturity and microfibril angle. Authors encourage carrying further studies on other populations of A. alba in the Spanish Pyrenees to check if the trends found in this study apply to other provenances.

Higher-order regularization and morphological techniques for image segmentation

La segmentación de imágenes es un campo importante de la visión computacional y una de las áreas de investigación más activas, con aplicaciones en comprensión de imágenes, detección de objetos, reconocimiento facial, vigilancia de vídeo o procesamiento de imagen médica. La segmentación de imágenes es un problema difícil en general, pero especialmente en entornos científicos y biomédicos, donde las técnicas de adquisición imagen proporcionan imágenes ruidosas. Además, en muchos de estos casos se necesita una precisión casi perfecta. En esta tesis, revisamos y comparamos primero algunas de las técnicas ampliamente usadas para la segmentación de imágenes médicas. Estas técnicas usan clasificadores a nivel de pixel e introducen regularización sobre pares de píxeles que es normalmente insuficiente. Estudiamos las dificultades que presentan para capturar la información de alto nivel sobre los objetos a segmentar. Esta deficiencia da lugar a detecciones erróneas, bordes irregulares, configuraciones con topología errónea y formas inválidas. Para solucionar estos problemas, proponemos un nuevo método de regularización de alto nivel que aprende información topológica y de forma a partir de los datos de entrenamiento de una forma no paramétrica usando potenciales de orden superior. Los potenciales de orden superior se están popularizando en visión por computador, pero la representación exacta de un potencial de orden superior definido sobre muchas variables es computacionalmente inviable. Usamos una representación compacta de los potenciales basada en un conjunto finito de patrones aprendidos de los datos de entrenamiento que, a su vez, depende de las observaciones. Gracias a esta representación, los potenciales de orden superior pueden ser convertidos a potenciales de orden 2 con algunas variables auxiliares añadidas. Experimentos con imágenes reales y sintéticas confirman que nuestro modelo soluciona los errores de aproximaciones más débiles. Incluso con una regularización de alto nivel, una precisión exacta es inalcanzable, y se requeire de edición manual de los resultados de la segmentación automática. La edición manual es tediosa y pesada, y cualquier herramienta de ayuda es muy apreciada. Estas herramientas necesitan ser precisas, pero también lo suficientemente rápidas para ser usadas de forma interactiva. Los contornos activos son una buena solución: son buenos para detecciones precisas de fronteras y, en lugar de buscar una solución global, proporcionan un ajuste fino a resultados que ya existían previamente. Sin embargo, requieren una representación implícita que les permita trabajar con cambios topológicos del contorno, y esto da lugar a ecuaciones en derivadas parciales (EDP) que son costosas de resolver computacionalmente y pueden presentar problemas de estabilidad numérica. Presentamos una aproximación morfológica a la evolución de contornos basada en un nuevo operador morfológico de curvatura que es válido para superficies de cualquier dimensión. Aproximamos la solución numérica de la EDP de la evolución de contorno mediante la aplicación sucesiva de un conjunto de operadores morfológicos aplicados sobre una función de conjuntos de nivel. Estos operadores son muy rápidos, no sufren de problemas de estabilidad numérica y no degradan la función de los conjuntos de nivel, de modo que no hay necesidad de reinicializarlo. Además, su implementación es mucho más sencilla que la de las EDP, ya que no requieren usar sofisticados algoritmos numéricos. Desde un punto de vista teórico, profundizamos en las conexiones entre operadores morfológicos y diferenciales, e introducimos nuevos resultados en este área. Validamos nuestra aproximación proporcionando una implementación morfológica de los contornos geodésicos activos, los contornos activos sin bordes, y los turbopíxeles. En los experimentos realizados, las implementaciones morfológicas convergen a soluciones equivalentes a aquéllas logradas mediante soluciones numéricas tradicionales, pero con ganancias significativas en simplicidad, velocidad y estabilidad. ABSTRACT Image segmentation is an important field in computer vision and one of its most active research areas, with applications in image understanding, object detection, face recognition, video surveillance or medical image processing. Image segmentation is a challenging problem in general, but especially in the biological and medical image fields, where the imaging techniques usually produce cluttered and noisy images and near-perfect accuracy is required in many cases. In this thesis we first review and compare some standard techniques widely used for medical image segmentation. These techniques use pixel-wise classifiers and introduce weak pairwise regularization which is insufficient in many cases. We study their difficulties to capture high-level structural information about the objects to segment. This deficiency leads to many erroneous detections, ragged boundaries, incorrect topological configurations and wrong shapes. To deal with these problems, we propose a new regularization method that learns shape and topological information from training data in a nonparametric way using high-order potentials. High-order potentials are becoming increasingly popular in computer vision. However, the exact representation of a general higher order potential defined over many variables is computationally infeasible. We use a compact representation of the potentials based on a finite set of patterns learned fromtraining data that, in turn, depends on the observations. Thanks to this representation, high-order potentials can be converted into pairwise potentials with some added auxiliary variables and minimized with tree-reweighted message passing (TRW) and belief propagation (BP) techniques. Both synthetic and real experiments confirm that our model fixes the errors of weaker approaches. Even with high-level regularization, perfect accuracy is still unattainable, and human editing of the segmentation results is necessary. The manual edition is tedious and cumbersome, and tools that assist the user are greatly appreciated. These tools need to be precise, but also fast enough to be used in real-time. Active contours are a good solution: they are good for precise boundary detection and, instead of finding a global solution, they provide a fine tuning to previously existing results. However, they require an implicit representation to deal with topological changes of the contour, and this leads to PDEs that are computationally costly to solve and may present numerical stability issues. We present a morphological approach to contour evolution based on a new curvature morphological operator valid for surfaces of any dimension. We approximate the numerical solution of the contour evolution PDE by the successive application of a set of morphological operators defined on a binary level-set. These operators are very fast, do not suffer numerical stability issues, and do not degrade the level set function, so there is no need to reinitialize it. Moreover, their implementation is much easier than their PDE counterpart, since they do not require the use of sophisticated numerical algorithms. From a theoretical point of view, we delve into the connections between differential andmorphological operators, and introduce novel results in this area. We validate the approach providing amorphological implementation of the geodesic active contours, the active contours without borders, and turbopixels. In the experiments conducted, the morphological implementations converge to solutions equivalent to those achieved by traditional numerical solutions, but with significant gains in simplicity, speed, and stability.

Hyperspectral to multispectral imaging for detection of tree nuts and peanut traces in wheat flour

In current industrial environments there is an increasing need for practical and inexpensive quality control systems to detect the foreign food materials in powder food processing lines. This demand is especially important for the detection of product adulteration with traces of highly allergenic products, such as peanuts and tree nuts. Manufacturing industries dealing with the processing of multiple powder food products present a substantial risk for the contamination of powder foods with traces of tree nuts and other adulterants, which might result in unintentional ingestion of nuts by the sensitised population. Hence, the need for an in-line system to detect nut traces at the early stages of food manufacturing is of crucial importance. In this present work, a feasibility study of a spectral index for revealing adulteration of tree nut and peanut traces in wheat flour samples with hyperspectral images is reported. The main nuts responsible for allergenic reactions considered in this work were peanut, hazelnut and walnut. Enhanced contrast between nuts and wheat flour was obtained after the application of the index. Furthermore, the segmentation of these images by selecting different thresholds for different nut and flour mixtures allowed the identification of nut traces in the samples. Pixels identified as nuts were counted and compared with the actual percentage of peanut adulteration. As a result, the multispectral system was able to detect and provide good visualisation of tree nut and peanut trace levels down to 0.01% by weight. In this context, multispectral imaging could operate in conjuction with chemical procedures, such as Real Time Polymerase Chain Reaction and Enzyme-Linked Immunosorbent Assay to save time, money and skilled labour on product quality control. This approach could enable not only a few selected samples to be assessed but also to extensively incorporate quality control surveyance on product processing lines.

Hyperspectral to multispectral imaging for detection of tree nuts and peanut traces in wheat flour.

In current industrial environments there is an increasing need for practical and inexpensive quality control systems to detect the foreign food materials in powder food processing lines. This demand is especially important for the detection of product adulteration with traces of highly allergenic products, such as peanuts and tree nuts. Manufacturing industries dealing with the processing of multiple powder food products present a substantial risk for the contamination of powder foods with traces of tree nuts and other adulterants, which might result in unintentional ingestion of nuts by the sensitised population. Hence, the need for an in-line system to detect nut traces at the early stages of food manufacturing is of crucial importance. In this present work, a feasibility study of a spectral index for revealing adulteration of tree nut and peanut traces in wheat flour samples with hyperspectral images is reported. The main nuts responsible for allergenic reactions considered in this work were peanut, hazelnut and walnut. Enhanced contrast between nuts and wheat flour was obtained after the application of the index. Furthermore, the segmentation of these images by selecting different thresholds for different nut and flour mixtures allowed the identification of nut traces in the samples. Pixels identified as nuts were counted and with the actual percentage of peanut adulteration. As a result, the multispectral system was able to detect and provide good visualisation of tree nut and peanut trace levels down to 0.01% by weight. In this context, multispectral imaging could operate in conjuction with chemical procedures, such as Real Time Polymerase Chain Reaction and Enzyme-Linked Immunosorbent Assay to save time, money and skilled labour on product quality control. This approach could enable not only a few selected samples to be assessed but also to extensively incorporate quality control surveyance on product processing lines.

Speeding up the EM algorithm for mixture model-based segmentation of magnetic resonance images

Mixture models implemented via the expectation-maximization (EM) algorithm are being increasingly used in a wide range of problems in pattern recognition such as image segmentation. However, the EM algorithm requires considerable computational time in its application to huge data sets such as a three-dimensional magnetic resonance (MR) image of over 10 million voxels. Recently, it was shown that a sparse, incremental version of the EM algorithm could improve its rate of convergence. In this paper, we show how this modified EM algorithm can be speeded up further by adopting a multiresolution kd-tree structure in performing the E-step. The proposed algorithm outperforms some other variants of the EM algorithm for segmenting MR images of the human brain. (C) 2004 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.

Stem and crown dimensions as predictors of thinning responses in a crowded tropical rainforest plantation of Flindersia brayleyana F. Muell.

A 67-year-old plantation of Flindersia brayleyana F. Muell. in the wet tropics of north-cast Queensland had developed with minimal management. Before thinning, the stand had a canopy stem density of 770 stems ha(-1) of which 564 were F brayleyana, a stand basal area of 78 m(2) ha(-1), a mean stem diameter at breast height (dbh) of 36 cm, and a mean dbh increment of 5.2 mm year(-1) over the life of the plantation and 0.5 mm year I at the time of thinning. Sixty-three percent of the trees had crown ratios (crown diameter determined from foliage projected area: dbh) of less than 12. Thinning treatments removed 57% of the canopy stems and 45% of the stand basal area. Mean dbh increment over 2.5 years after thinning on basaltic soil was 5.8 +/- 0.3 mm year(-1), but for trees with crown ratio