Prediction of soil organic carbon for Ethiopian highlands using soil spectroscopy

Soil spectroscopy was applied for predicting soil organic carbon (SOC) in the highlands of Ethiopia. Soil samples were acquired from Ethiopia’s National Soil Testing Centre and direct field sampling. The reflectance of samples was measured using a FieldSpec 3 diffuse reflectance spectrometer. Outliers and sample relation were evaluated using principal component analysis (PCA) and models were developed through partial least square regression (PLSR). For nine watersheds sampled, 20% of the samples were set aside to test prediction and 80% were used to develop calibration models. Depending on the number of samples per watershed, cross validation or independent validation were used.The stability of models was evaluated using coefficient of determination (R2), root mean square error (RMSE), and the ratio performance deviation (RPD). The R2 (%), RMSE (%), and RPD, respectively, for validation were Anjeni (88, 0.44, 3.05), Bale (86, 0.52, 2.7), Basketo (89, 0.57, 3.0), Benishangul (91, 0.30, 3.4), Kersa (82, 0.44, 2.4), Kola tembien (75, 0.44, 1.9),Maybar (84. 0.57, 2.5),Megech (85, 0.15, 2.6), andWondoGenet (86, 0.52, 2.7) indicating that themodels were stable. Models performed better for areas with high SOC values than areas with lower SOC values. Overall, soil spectroscopy performance ranged from very good to good.

A Thalamic-Fronto-Parietal Structural Covariance Network Emerging in the Course of Recovery from Hand Paresis after Ischemic Stroke.

AIM To describe structural covariance networks of gray matter volume (GMV) change in 28 patients with first-ever stroke to the primary sensorimotor cortices, and to investigate their relationship to hand function recovery and local GMV change. METHODS Tensor-based morphometry maps derived from high-resolution structural images were subject to principal component analyses to identify the networks. We calculated correlations between network expression and local GMV change, sensorimotor hand function and lesion volume. To verify which of the structural covariance networks of GMV change have a significant relationship to hand function, we performed an additional multivariate regression approach. RESULTS Expression of the second network, explaining 9.1% of variance, correlated with GMV increase in the medio-dorsal (md) thalamus and hand motor skill. Patients with positive expression coefficients were distinguished by significantly higher GMV increase of this structure during stroke recovery. Significant nodes of this network were located in md thalamus, dorsolateral prefrontal cortex, and higher order sensorimotor cortices. Parameter of hand function had a unique relationship to the network and depended on an interaction between network expression and lesion volume. Inversely, network expression is limited in patients with large lesion volumes. CONCLUSION Chronic phase of sensorimotor cortical stroke has been characterized by a large scale co-varying structural network in the ipsilesional hemisphere associated specifically with sensorimotor hand skill. Its expression is related to GMV increase of md thalamus, one constituent of the network, and correlated with the cortico-striato-thalamic loop involved in control of motor execution and higher order sensorimotor cortices. A close relation between expression of this network with degree of recovery might indicate reduced compensatory resources in the impaired subgroup.

Dietary patterns and risk of pancreatic cancer in a hospital-based case-control study

Background. It is important to understand the association between diet and risk of pancreatic cancer in order to better understand the etiology of pancreatic cancer.^ Objectives. Describe the dietary patterns of cases of adenocarcinoma of the pancreas and non-cancer controls and evaluate the odds of having a healthy eating pattern among cases and non-cancer controls.^ Design and Methods. An ongoing hospital-based case-control study was conducted in Houston, Texas from 2000-2008 with 678 pancreatic adenocarcinoma cases and 724 controls. Participants completed a food frequency questionnaire and a risk factor questionnaire. Dietary patterns were derived by principal component analysis and associations between dietary patterns and pancreatic cancer risk were assessed using unconditional logistic regression.^ Results. Two dietary patterns were derived: fruit-vegetable and high fat-meat. There were no statistically significant associations between the fruit-vegetable pattern and pancreatic cancer. An inverse association was seen between the high fat-meat pattern and pancreatic cancer risk when comparing those in the upper intake quintile to those scoring in the lowest quintile after adjusting for demographic and risk factor variables (OR=0.67, p=0.03). In sex-stratified analysis adjusted for demographic and risk factor variables, females scoring in the upper intake quintile of the fruit-vegetable pattern had a 49% lower risk of pancreatic cancer compared to females scoring in the lowest quintile (OR=0.51, p=0.03). An inverse relationship was also seen for the high fat-meat pattern when comparing females in the upper intake quintile to females in the lowest quintile (OR=0.50, p=0.03). In males, neither dietary pattern was significantly associated with pancreatic cancer.^ Conclusions. The current findings for the fruit-vegetable pattern are similar to those of previous studies and support the hypothesis that there is an inverse association between a “healthy” diet (comprised of fruits, vegetables, and whole grains) and risk of having pancreatic cancer (in females only). However, the inverse relationship with the high fat-meat pattern and risk of pancreatic cancer is contrary to other results. Further research on dietary patters and pancreatic cancer risk may lead to better understanding of the etiologic cause of pancreatic cancer.^

Growth and development of body fat distribution from skinfold measurements: Longitudinal principal components

Longitudinal principal components analyses on a combination of four subcutaneous skinfolds (biceps, triceps, subscapular and suprailiac) were performed using data from the London Longitudinal Growth Study. The main objectives were to discover at what age during growth sex differences in body fat distribution occur and to see if there is continuity in body fatness and body fat distribution from childhood into the adult status (18 years). The analyses were done for four age sectors (3mon-3yrs, 3yrs-8yrs, 8yrs-18yrs and 3yrs-18yrs). Longitudinal principal component one (LPC1) for each age interval in both sexes represents the population mean fat curve. Component two (LPC2) is a velocity of fatness component. Component three (LPC3) in the 3mon-3yrs age sector represents infant fat wave in both sexes. In the next two age sectors component three in males represents peaks and shifts in fat growth (change in velocity), while in females it represents body fat distribution. Component four (LPC4) in the same two age sectors is a reversal in the sexes of the patterns seen for component three, i.e., in males it is body fat distribution and in females velocity shifts. Components five and above represent more complicated patterns of change (multiple increases and decreases across the age interval). In both sexes there is strong tracking in fatness from middle childhood to adolescence. In males only there is also a low to moderate tracking of infant fat with middle to late childhood fat. These data are strongly supported in the literature. Several factors are known to predict adult fatness among the most important being previous levels of fatness (at earlier ages) and the age at rebound. In addition we found that the velocity of fat change in middle childhood was highly predictive of later fatness (r $\approx -$0.7), even more so than age at rebound (r $\approx -$0.5). In contrast to fatness (LPC1), body fat distribution (LPC3-LPC4) did not track well even though significant components of body fat distribution occur at each age. Tracking of body fat distribution was higher in females than males. Sex differences in body fat distribution are non existent. Some sex differences are evident with the peripheral-to-central ratios after age 14 years. ^

Nonlinear dimension reduction in pathway-based genome-wide association analysis

Pathway based genome wide association study evolves from pathway analysis for microarray gene expression and is under rapid development as a complementary for single-SNP based genome wide association study. However, it faces new challenges, such as the summarization of SNP statistics to pathway statistics. The current study applies the ridge regularized Kernel Sliced Inverse Regression (KSIR) to achieve dimension reduction and compared this method to the other two widely used methods, the minimal-p-value (minP) approach of assigning the best test statistics of all SNPs in each pathway as the statistics of the pathway and the principal component analysis (PCA) method of utilizing PCA to calculate the principal components of each pathway. Comparison of the three methods using simulated datasets consisting of 500 cases, 500 controls and100 SNPs demonstrated that KSIR method outperformed the other two methods in terms of causal pathway ranking and the statistical power. PCA method showed similar performance as the minP method. KSIR method also showed a better performance over the other two methods in analyzing a real dataset, the WTCCC Ulcerative Colitis dataset consisting of 1762 cases, 3773 controls as the discovery cohort and 591 cases, 1639 controls as the replication cohort. Several immune and non-immune pathways relevant to ulcerative colitis were identified by these methods. Results from the current study provided a reference for further methodology development and identified novel pathways that may be of importance to the development of ulcerative colitis.^

Desarrollo de estándares de calidad para uvas Vitis vinifera L. cv. Malbec y Syrah

El objetivo del trabajo fue desarrollar estándares de calidad de uva basados en atributos físicos y químicos, capaces de predecir la calidad del vino. Se instaló una red de ensayos en Mendoza (Norte, Este y Valle de Uco), San Juan (Valle de Zonda), La Rioja (Chilecito), Catamarca y Salta (Valles Calchaquíes) (Argentina). Se ensayaron niveles de carga de uva (desbrote 30 y 50%, raleo 30 y 50% y testigo) en Malbec y Syrah. En la cosecha, las uvas fueron analizadas (tamaño baya, concentración azucarina, pH, antocianos, catequinas, taninos, fenoles totales) y vinificadas. Los vinos fueron analizados (alcohol, extracto seco, intensidad colorante, matiz, antocianos, catequinas, taninos, fenoles totales, color polimérico) y evaluados por un panel de degustadores. Empleando todos las variables de los vinos, mediante un análisis de componentes principales, se generaron dos índices que resumieron los atributos con mayor peso explicativo de la variabilidad observada (80%); ellos fueron: Riqueza Fenólica (RF, asociado a antocianos, taninos, catequinas, fenoles totales y concentración) y Peligro Oxidativo (PO, asociado a pH, matiz y tonalidad percibida). No existieron diferencias en cuanto a RF entre variedades ni entre niveles de producción de uva. Los vinos con RF mayor y PO menor se consideraron de mayor calidad. Las uvas cultivadas en zonas más frías tuvieron una mayor RF. En Malbec, las zonas frías y los bajos niveles productivos generaron un PO menor. Para cada variedad se desarrollaron predictores para RF y PO del vino. Se usó la regresión múltiple lineal paso a paso, seleccionando las variables de la uva con mayor poder predictivo. Se definieron las funciones de ajuste RFpred (Malbec R2 = 80%; Syrah R2 = 62%) y POpred (Malbec R2 = 80%; Syrah R2 = 62%). Los índices se tradujeron en estándares de calidad que mostraron concordancia entre uvas y vinos. La metodología puede ser válida para otras variedades tintas, pero debe ajustarse para cada caso. Los estándares permitirían asociar un precio a cada calidad y aumentar la transparencia del mercado.

Climate change technology transfer to developing countries: evidence analysis and policy recommendations

Developing countries are experiencing unprecedented levels of economic growth. As a result, they will be responsible for most of the future growth in energy demand and greenhouse gas (GHG) emissions. Curbing GHG emissions in developing countries has become one of the cornerstones of a future international agreement under the United Nations Framework Convention for Climate Change (UNFCCC). However, setting caps for developing countries’ GHG emissions has encountered strong resistance in the current round of negotiations. Continued economic growth that allows poverty eradication is still the main priority for most developing countries, and caps are perceived as a constraint to future growth prospects. The development, transfer and use of low-carbon technologies have more positive connotations, and are seen as the potential path towards low-carbon development. So far, the success of the UNFCCC process in improving the levels of technology transfer (TT) to developing countries has been limited. This thesis analyses the causes for such limited success and seeks to improve on the understanding about what constitutes TT in the field of climate change, establish the factors that enable them in developing countries and determine which policies could be implemented to reinforce these factors. Despite the wide recognition of the importance of technology and knowledge transfer to developing countries in the climate change mitigation policy agenda, this issue has not received sufficient attention in academic research. Current definitions of climate change TT barely take into account the perspective of actors involved in actual climate change TT activities, while respective measurements do not bear in mind the diversity of channels through which these happen and the outputs and effects that they convey. Furthermore, the enabling factors for TT in non-BRIC (Brazil, Russia, India, China) developing countries have been seldom investigated, and policy recommendations to improve the level and quality of TTs to developing countries have not been adapted to the specific needs of highly heterogeneous countries, commonly denominated as “developing countries”. This thesis contributes to enriching the climate change TT debate from the perspective of a smaller emerging economy (Chile) and by undertaking a quantitative analysis of enabling factors for TT in a large sample of developing countries. Two methodological approaches are used to study climate change TT: comparative case study analysis and quantitative analysis. Comparative case studies analyse TT processes in ten cases based in Chile, all of which share the same economic, technological and policy frameworks, thus enabling us to draw conclusions on the enabling factors and obstacles operating in TT processes. The quantitative analysis uses three methodologies – principal component analysis, multiple regression analysis and cluster analysis – to assess the performance of developing countries in a number of enabling factors and the relationship between these factors and indicators of TT, as well as to create groups of developing countries with similar performances. The findings of this thesis are structured to provide responses to four main research questions: What constitutes technology transfer and how does it happen? Is it possible to measure technology transfer, and what are the main challenges in doing so? Which factors enable climate change technology transfer to developing countries? And how do different developing countries perform in these enabling factors, and how can differentiated policy priorities be defined accordingly? vi Resumen Los paises en desarrollo estan experimentando niveles de crecimiento economico sin precedentes. Como consecuencia, se espera que sean responsables de la mayor parte del futuro crecimiento global en demanda energetica y emisiones de Gases de Efecto de Invernadero (GEI). Reducir las emisiones de GEI en los paises en desarrollo es por tanto uno de los pilares de un futuro acuerdo internacional en el marco de la Convencion Marco de las Naciones Unidas para el Cambio Climatico (UNFCCC). La posibilidad de compromisos vinculantes de reduccion de emisiones de GEI ha sido rechazada por los paises en desarrollo, que perciben estos limites como frenos a su desarrollo economico y a su prioridad principal de erradicacion de la pobreza. El desarrollo, transferencia y uso de tecnologias bajas en carbono tiene connotaciones mas positivas y se percibe como la via hacia un crecimiento bajo en carbono. Hasta el momento, la UNFCCC ha tenido un exito limitado en la promocion de transferencias de tecnologia (TT) a paises en desarrollo. Esta tesis analiza las causas de este resultado y busca mejorar la comprension sobre que constituye transferencia de tecnologia en el area de cambio climatico, cuales son los factores que la facilitan en paises en desarrollo y que politicas podrian implementarse para reforzar dichos factores. A pesar del extendido reconocimiento sobre la importancia de la transferencia de tecnologia a paises en desarrollo en la agenda politica de cambio climatico, esta cuestion no ha sido suficientemente atendida por la investigacion existente. Las definiciones actuales de transferencia de tecnologia relacionada con la mitigacion del cambio climatico no tienen en cuenta la diversidad de canales por las que se manifiestan o los efectos que consiguen. Los factores facilitadores de TT en paises en desarrollo no BRIC (Brasil, Rusia, India y China) apenas han sido investigados, y las recomendaciones politicas para aumentar el nivel y la calidad de la TT no se han adaptado a las necesidades especificas de paises muy heterogeneos aglutinados bajo el denominado grupo de "paises en desarrollo". Esta tesis contribuye a enriquecer el debate sobre la TT de cambio climatico con la perspectiva de una economia emergente de pequeno tamano (Chile) y el analisis cuantitativo de factores que facilitan la TT en una amplia muestra de paises en desarrollo. Se utilizan dos metodologias para el estudio de la TT a paises en desarrollo: analisis comparativo de casos de estudio y analisis cuantitativo basado en metodos multivariantes. Los casos de estudio analizan procesos de TT en diez casos basados en Chile, para derivar conclusiones sobre los factores que facilitan u obstaculizan el proceso de transferencia. El analisis cuantitativo multivariante utiliza tres metodologias: regresion multiple, analisis de componentes principales y analisis cluster. Con dichas metodologias se busca analizar el posicionamiento de diversos paises en cuanto a factores que facilitan la TT; las relaciones entre dichos factores e indicadores de transferencia tecnologica; y crear grupos de paises con caracteristicas similares que podrian beneficiarse de politicas similares para la promocion de la transferencia de tecnologia. Los resultados de la tesis se estructuran en torno a cuatro preguntas de investigacion: .Que es la transferencia de tecnologia y como ocurre?; .Es posible medir la transferencia de tecnologias de bajo carbono?; .Que factores facilitan la transferencia de tecnologias de bajo carbono a paises en desarrollo? y .Como se puede agrupar a los paises en desarrollo en funcion de sus necesidades politicas para la promocion de la transferencia de tecnologias de bajo carbono?

Models for Internal Quality Fruit Sorting, Based on Time- Domain Laser Reflectance Spectroscopy (TDRS)

Time domain laser reflectance spectroscopy (TDRS) was applied for the first time to evaluate internal fruit quality. This technique, known in medicine-related knowledge areas, has not been used before in agricultural or food research. It allows the simultaneous non-destructive measuring of two optical characteristics of the tissues: light scattering and absorption. Models to measure firmness, sugar & acid contents in kiwifruit, tomato, apple, peach, nectarine and other fruits were built using sequential statistical techniques: principal component analysis, multiple stepwise linear regression, clustering and discriminant analysis. Consistent correlations were established between the two parameters measured with TDRS, i.e. absorption & transport scattering coefficients, with chemical constituents (sugars and acids) and firmness, respectively. Classification models were built to sort fruits into three quality grades, according to their firmness, soluble solids and acidity.

Fruit quality sensing:Post-harvest ripeness

Firmness sensing of selected varieties of apples, pears and avocado fruits has been developed using a nondestructive impact technique. In addition to firmness measurements, postharvest ripeness of apples and pears was monitored by spectrophotometric reflectance measurements, and that of avocadoes by Hunter colour measurements. The data obtained from firmness sensing were analyzed by three analytical procedures: principal component, correlation and regression, and stepwise discriminant analysis. A new software was developed to control the impact test, analyse the data, and sort the fruit into specified classes, based on the criteria obtained from a training procedure. Similar procedures were used to analyse the reflectance and colour data. Both sensing systems were able to classify fruits w i th good accuracy.