Fresh-cut watermelon is appreciated for its taste, flavor, and juiciness. However, there are challenges in maintaining the freshness since fresh-cut processing of fruits promotes faster deterioration. Our objective was to determine the effectiveness of multilayered antimicrobial edible coating on the shelf-life of fresh-cut watermelon while keeping its original attributes for longer, without affecting its sensory properties. A set of solutions containing sodium alginate (0.5, 1, 2% w/w), beta-cyclodextrin, trans-cinnamaldehyde (antimicrobial agent), pectin, and calcium lactate were used as coating systems for fresh-cut watermelon cylinders. The samples were coated by the layer-by-layer dipping technique and stored at 4 degrees C for 15 days. Results were analyzed individually for each quality attribute evaluated, and the best concentration among the solutions to improve each attribute was found. Watermelon quality was measured in terms of texture, color, juice leakage (weight loss), oBrix, and pH. Microbiological analysis consisted of total coliforms, yeasts and molds, aerobics, and psychrotrophs. A consumer test was carried out (~ 40 panelists) to support the objective quality data. Panelists scored the samples using a 9-point hedonic scale. Uncoated samples served as controls. Quality tests were conducted at days 1, 3, 7, 12, and 15 of storage. Sensory tests showed high acceptance (P < 0.05) of the coated samples when compared to the controls. Quality attributes, particularly texture (firmness) and juice leakage (weight loss) were enhanced (P < 0.05) by the coating. Microbiological analysis demonstrated that alginate-based edible coating has a huge effect against microbial growth. 1% sodium alginate coating provided better preservation in terms of quality parameters, microbiological growth, and sensory acceptance. These results indicate that different ratios between solutions present a significant variation for each quality attribute measured in this study; and the thickness of the coating as well as the amount of antimicrobial are critical for shelf-life extension of fresh-cut watermelon. Hence, application of an alginate based multilayered edible coating has tremendous potential to enhance microbial quality and extend the shelf-life of fresh-cut watermelon.

Diss. (sammanfattning). Uppsala : Sveriges lantbruksuniv., 2003. / Härtill 4 uppsatser.

Evaluating large numbers of genotypes and phenotypes in multi-environment trials is key to crop improvement for biomass performance in sorghum. In this dissertation, we developed an approach that integrates crop growth models with remote-sensing data and genetic information for modeling and predicting sorghum biomass yield. The goal of studies described in Chapter 2 was to parameterize the Agricultural Production Systems sIMulator (APSIM) crop growth models with remote-sensing and ground-reference data to predict variation in phenology and yield-related traits for 18 commercial grain and biomass sorghum hybrids. These studies showed that (i) biomass sorghum hybrids tended to have higher maximum plant height, final dry biomass and radiation use efficiency (RUE) than grain sorghum, (ii) photoperiod-sensitive sorghum hybrids exhibited greater biomass potential in longer growing environments and (iii) the parameterized APSIM models performed well in above-ground biomass simulations across years and locations. Crop growth models that integrate remote-sensing data offer an efficient approach to parameterize models for larger plant breeding populations. Understanding the genetic architecture of biomass productivity and bioenergy-related traits is another key aspect of bioenergy sorghum breeding programs. In Chapter 3, 619 sorghum genotypes from the sorghum diversity panel were individually crossed to ATx623 to create a half-sib population that was planted and evaluated in field trials in three consecutive years. Single-nucleotide polymorphisms (SNPs) were used in a genome-wide association study (GWAS) to identify genetic loci associated with variation in plant architecture and biomass productivity. A few SNPs associated with these traits were located in previously described genes including the sorghum dwarfing genes <i>Dw1</i> and <i>Dw3</i> and stay-green QTLs <i>Stg1</i> and <i>Stg4</i>. Of particular interest were seven genetic loci that were discovered for biomass yield. For three of these loci, the minor or uncommon allele exhibited a favorable effect on productivity suggesting opportunities to further improve the crop for biomass accumulation through plant breeding. Marker-assisted and genomic selection strategies may provide tools to introgress and exploit these genes for bioenergy sorghum development. Since parameterizing biophysical crop models requires extensive time and manual effort, a simple model was developed in Chapter 4 that used time-dependent measurements of RGB canopy cover and daily radiation coupled with end-of-season biomass for estimating seasonal radiation use efficiency (SRUE) in 619 sorghum hybrids. SRUE was shown to be a stable and heritable trait that has a positive relationship with aboveground dry biomass (ADB) over seasons. GWAS identified 11 SNPs associated with SRUE with the favorable effect represented by the minor allele for seven of these SNPs. Increasing the frequency of these favorable alleles may improve the breeding population. These results demonstrated that the simple model for calculating SRUE can be used in genetic studies and for parameterizing biophysical crop models. The studies integrating crop growth models with remote sensing technologies provide an opportunity to evaluate a large number of phenotypes for the target population to understand the underlying genetic variation of bioenergy sorghum.

A stochastic framework to simulate the process of initiation, diameter growth, death and self-pruning of branches in loblolly pine (Pinus taeda L.) trees was developed. A data set was obtained from a destructive sampling of whorl sections from 34 trees growing under different initial spacing. Data from dissected branches were used to develop a model for representing knot shape, which assumed that the live portion of a knot can be modeled by a one-parameter equation and the dead portion by assuming a cylindrical shape. For the developed knot model analytical expressions were derived for estimating the volume of knots (live/dead portions) for three types of branch conditions on simulated trees: (i) live branches, (ii) non-occluded dead branches, and (iii) occluded dead branches. This model was intended to recover information on knots shape and volume during the simulation process of branch dynamics. Three different components were modeled and hierarchically connected: whorl, branches and knots. For each new growing season, whorls and branches are assigned stochastically along and around the stem. Thereafter, branch diameter growth is predicted as function of relative location within the live crown and stem growth. Using a taper equation, the spatial location (X,Y,Z) of both live and dead portion of simulated knots is maintained in order to create a 3D representation of the internal stem structure. At the end of the projection period information on (i) vertical trend of branch diameter and location along and around the stem, (ii) volume of knots, and (iii) spatial location, size and type (live and dead) of knots can be obtained. The proposed branch model was linked to the individual-tree growth and yield model PTAEDA3.1 to evaluate the effect of initial spacing and thinning intensity on branch growth in sawtimber trees. The use of the dynamic branch model permitted generation of additional information on sawlog quality under different management regimes. The arithmetic mean diameter of the largest four branches, one from each radial quadrant of the log (i.e. Branch Index, BI) and the number of whorls per log were considered as indicators of sawlog quality. The developed framework makes it possible to include additional wood properties in the simulation system, allowing linkage with industrial conversion processes (e.g. sawing simulation). This integrated modeling system should promote further research to obtain necessary data on crown and branch dynamics to validate the overall performance of the proposed branch model and to improve its components. / Ph. D.

Esta dissertação flexibiliza a suposição de normalidade, dispondo de distribuições assimétricas em modelos de crescimento. Propõe uma abordagem bayesiana para ajuste de modelos não lineares quando a suposição de normalidade para os erros não é razoável e/ou apresentam heteroscedasticidade. Assim, adota-se as distribuições skew-normal e skew-t para as situações em que é necessário modelar dados com caudas mais pesadas ou mais leves que a normal e assimétricos; sendo que é considerado também a presença de heteroscedasticidade. Diferentes funções são utilizadas na estrutura multiplicativa para modelar a variância. Com esse objetivo, métodos de inferência na abordagem bayesiana são desenvolvidos para estimar os parâmetros dos modelos de regressão não linear com os erros seguindo as distribuições citadas anteriormente. A metodologia visa aplicação à curvas de crescimento para dados de árvores / This paper relaxes the assumption of normality, featuring asymmetric distributions in growth models. Proposes a Bayesian approach to fit nonlinear models when the assumption of normality for the errors is not reasonable and/or exhibit heteroscedasticity. Thus, we adopt the skew-normal and skew-t distributions for situations where it is necessary to model data with tails heavier or lighter than normal and asymmetric, which is considered also the presence of heteroscedasticity. Different functions are used to model the multiplicative structure of variance. With this objective, methods of inference in the Bayesian approach are developed to estimate the parameters of nonlinear regression models with errors following the distributions listed above. The methodology is intended to apply to the growth curves for trees data sets

A generalização de modelos de crescimento por meio de um parâmetro de controle foi primeiramente proposta por Richards, em 1959. Em nosso trabalho, propomos uma forma alternativa de generalização obtendo uma interpretação emp rica e outra microscopica do parâmetro de controle. Mais especificamente, quando consideramos a proliferacão de c elulas, o parâmetro est a relacionado ao alcance da interação e a dimensão fractal da estrutura celular. Obtemos a solucão anal ítica para esta equação diferencial. Mostramos que, atrav és da escolha apropriada da escala conseguimos o colapso de dados representando a independência em relacão aos parâmetros e as condições iniciais. Al ém disso, ao considerarmos a taxa de esforco como a retirada de indiví duos de uma população, podemos associ á-la ao tratamento visando extinguir uma populacãoo de c élulas cancerosas. Em modelos epidemiol ogicos, propomos modelar a dinâmica de transmissão da dengue utilizando equacões diferenciais ordin árias. Em nosso modelo, levamos em conta tanto a dinâmica do hospedeiro quanto a do vetor, assim temos o controle da dinâmica de ambas as populações. Inclu ímos tamb ém no modelo o efeito \"enhancing\" com intuito de verificar sua influência na dinâmica de disseminacão da doença. O efeito \"enhancing\" é considerado uma das principais hipóteses para explicar a dengue hemorr ágica que pode levar a morte. Fizemos o estudo de um modelo epidemiol ógico da dengue com o objetivo de revelar quais são os fatores que levam a disseminação desse caso mais severo da doenca e, possivelmente, sugerir polí ticas p úblicas de sa úde para evit á-lo. Implementamos tamb ém um modelo de transmissão da tuberculose fazendo uso da modelagem computacional baseada em agentes, que oferece a possibilidade de representar explicitamente heterogeneidades em nível individual. / The generalization of growth models by means of a control parameter was first proposed by Richards in 1959. In our work, we propose an alternative way to obtainin an empirical and microscopic interpretation of control parameter. More specically, when considering the proliferation of cells, the parameter is related to the range of interaction and the fractal dimension of the cell structure. We obtain the analytical solution for this dierential equation. We show that, by appropriate choice of scale we have data collapse, representing the independence on parameters and initial conditions. Furthermore, when considering the e ffort as rate the removal of individuals from a population, we can associate it with the treatment to extinguish cancer cells population. In epidemiological models, we propose to model the dynamics of dengue transmission using ordinary dierential equations. In our model, we take into account both the dynamics of the host and the vector, so we have control of the dynamics of both populations. We also included in the model the effect of enhancing in order to verify their inuence on the dynamics of disease spread. The effect of enhancing is considered one of the main hypotheses to explain the hemorrhagic fever that can lead to death. We study a model of epidemiology of dengue in order to reveal what are the factors that lead to the dissemination of this more severe case of the disease and, possibly suggesting public health policies to prevent it. We also implemented a model of tuberculosis transmission making use of agent-based computational modeling, which o ffers the possibility to explicitly represent heterogeneity at the individual level. This approach allows us to deal with each individual in particular, unlike the model of dierential equations, in which all individuals are in the same compartment interact in a similar way as in a mean field interaction.

Modelos não lineares como o Logístico e o Gompertz são amplamente usados para descrever vários processos biológicos por meio da curva de crescimento dada pela equação do modelo. O objetivo deste trabalho foi ajustar o modelo Chanter, assim como o Logístico e o Gompertz, utilizando um conjunto de dados do fruto do cacaueiro. O modelo Chanter é um híbrido entre o modelo Logístico e o modelo Gompertz cujos parâmetros podem ser interpretados similarmente. A comparação sobre a qualidade do ajuste entre os modelos foi feita utilizando as seguintes medidas estatísticas: o critério de informação de Akaike (AIC), o critério Peso de Akaike, o critério de informação de Bayes (BIC), o desvio padrão residual (DPR) e as medidas de não linearidade vício de Box e curvatura de Bates e Watts além de um estudo de simulação. Verificou-se que o modelo Chanter dentre os modelos estudados neste trabalho é o mais adequado para o ajuste dos dados do fruto do cacaueiro. / Nonlinear models such as Logistic and Gompertz are widely used to describe several biological processes using a growth curve given by the equation of the model. The objective of this work was to adjust the Chanter model, as well as the Logistic and the Gompertz, using a data set of cocoa fruit. The Chanter model is a hybrid between the Logistic model and the Gompertz model whose parameters can be interpreted similarly. A comparison of the quality of fit between the models was made using the following statistical measures: the Akaike information criterion (AIC), the Akaike weight criterion, Bayes information criterion (BIC), residual standard deviation (RSD), and measures of non-linearity Box addiction and Bates and Watts curvature as well as a simulation study. It was verified that the Chanter model is the most suitable one among the studied models for modeling the cocoa data.

The measurement of achievement growth raises many challenges, including how to define "growth" and select or develop a growth measure that captures that definition. Despite these complications, current federal educational policies focus on student growth measures for accountability purposes. Student growth percentiles (SGPs) are one metric developed under these policies. They use quantile regression to produce normative growth interpretations: They describe how much a student has grown relative to students with similar past test scores. SGPs are increasingly popular, but there are gaps in the literature concerning their performance for small sample sizes and the number of prior years of test scores included in the model, as well as their invariance to transformations of the test scale. This study proposes an ordinary least squares analog, the percentile rank of residuals (PRRs). PRRs are the percentile rank of the residuals found by regressing the current grade-level assessment score on past grade-level assessment scores. PRRs may be a more robust alternative to SGPs, especially for small samples. They also stem from a wide array of regression based metrics in education and only require estimation of one regression line, as opposed to the 100 regression lines estimated for SGPs. This dissertation first places the growth metrics of interest in a framework anchored by four key contrasts in growth interpretations: (1) absolute versus normative, (2) unconditional normative versus conditional normative, (3) student- versus group-level, and (4) aggregated individual growth versus growth of aggregated-individuals. SGPs and PRRs afford normative conditional growth interpretations. They are investigated at the student level using simulated multivariate normal data and two statewide empirical datasets. These student-level analyses assess the accuracy of SGPs and PRRs by their recovery of benchmark growth percentiles under multivariate normality, or normal conditional growth percentiles (NCGPs), their robustness to scale transformations, their comparability to each other under varying conditions, and their stability over different sample sizes and numbers of prior years included in the models. SGPs and PRRs are also investigated at the group level by aggregating them with the mean and median functions. The robustness of the aggregated growth percentiles to test scale transformations is also assessed. Finally, the aggregated growth percentiles are contrasted against group effects from a simple layered value-added model (VAM). The analyses found that PRRs better recover expected growth percentiles under multivariate normality and are more accurate and stable for small samples, whereas SGPs are substantially more robust to test scale transformations. However, estimation issues with the SGPs can cause students with extreme initial statuses to obtain substantially different SGPs under transformations of the data. At the aggregate level, there is little distinction in how robust SGPs and PRRs are to scale transformations of the test score data. The mean SGPs and mean PRRs are consistently more robust to scale transformations of the test score data then their median counterparts. They are also the most highly correlated and rank order the groups more similarly to the value-added school effects than the median SGPs and PRRs.

The main goal of this thesis was to improve our understanding of the long-term effects of establishment treatments and climate change on lodgepole pine and white spruce growth in the western boreal forests. My dissertation also investigated the combined effects of climate and competition on white spruce and trembling aspen growth in boreal mixtures. In the first part of the thesis I evaluated the effects of site preparation treatments on growth of lodgepole pine and white spruce in north-eastern British Columbia. Results indicate that mechanical site preparation can provide yield gains of up-to 10 percent for pine and spruce at 60 and 80 years, respectively. These stands are showing a Type 1 growth response which implies that the treatment effect will eventually cease 90-100 years after planting. In the second part of the thesis I explored pine and spruce growth in relation to past climate and site preparation. Results indicate that up-to 45% and 37% of the respective variation in spruce and pine growth can be explained by selected climatic variables. Future projections indicated that height growth of young pine plantations in the sub-boreal zone could benefit (in the short term) from longer growing seasons by up-to 12% on untreated stands. Untreated young spruce plantations in the boreal zone may suffer height growth decreases of up-to 10% due to increased drought-stress. Vegetation control and mechanical site preparation treatments appear to mitigate effects of climate change to some extent. In the third part of the thesis I explored the combined effects of climate and trembling aspen competition on spruce and aspen growth using data from a long-term study in the boreal zone. Results indicate that climate variables and initial size of the tree can account for significant portions of the annual growth of spruce. Including an estimate of aspen competition in the equations improved the predictive ability of these models. Evidence of the inter-annual variability in aspen competitiveness on spruce and aspen growth indicates that the stress-gradient hypothesis can be applied in boreal mixedwood forests. / Forest Biology and Management

The central research question is the extent to which gifted programming affects student academic outcomes of gifted as compared to not-gifted students and how this differs by race/ethnicity and/or poverty status. Since the identification of elementary school students as gifted is not random, propensity score matching is used to remove this bias in the estimates of the effects. A matched sample of North Carolina middle school students based on individual level data of both gifted and not-gifted students of varied racial/ethnic groups and income levels is used for this analysis. This enables a comparison of sixth, seventh, and eighth grade student achievement to determine the extent to which participating in gifted programming differentiates effects by race/ethnicity and poverty status. I show the additional test score gain, if any, from being in gifted programming compared to students not participating in gifted programs. Variations in gifted program effects across race/ethnicity and income are assessed. This research adds empirical evidence to the more qualitatively focused gifted debate by analyzing differences in student outcomes between gifted and not-gifted students in North Carolina. Since black and lower income students are less likely to participate in gifted programs, they disproportionately encounter less experienced teachers, lower expectations, and fewer resources. The extent to which these additional learning supports translate to differences in student outcomes are analyzed.