Annual Report 2018/2019

Gedruckt erschienen im Universitätsverlag der TU Berlin, ISBN 978-3-7983-3113-6 (ISSN 2196-338X)Der Jahresbericht informiert über Lehrveranstaltungen, aktuelle Forschungsvorhaben und Projekte am Fachgebiet und gibt einen Überblick über Mitarbeiter, Publikationen und Gremientätigkeiten.The annual report informs about lectures and current research projects at the chair and gives an overview of the colleagues, their publications and committee work

Image appearance modeling

Traditional color appearance modeling has recently matured to the point that available, internationally-recommended models such as CIECAM02 are capable of making a wide range of predictions to within the observer variability in color matching and color scaling of stimuli in somewhat simplified viewing conditions. It is proposed that the next significant advances in the field of color appearance modeling will not come from evolutionary revisions of these models. Instead, a more revolutionary approach will be required to make appearance predictions for more complex stimuli in a wider array of viewing conditions. Such an approach can be considered image appearance modeling since it extends the concepts of color appearance modeling to stimuli and viewing environments that are spatially and temporally at the level of complexity of real natural and man-made scenes. This paper reviews the concepts of image appearance modeling, presents iCAM as one example of such a model, and provides a number of examples of the use of iCAM in still and moving image reproduction

Seeds morpho-colourimetric analysis as complementary method to molecular characterization of melon diversity

[EN] Melon has undergone an intense process of selection and crossbreeding, resulting in many landraces distributed all over Europe, Africa and Asia. Due to this huge variability, the systematic position of this taxon has been reviewed many times in the last two decades. The goal of this article is to compare the phenotypic characterization achieved by seed features with the molecular analysis on melon genotypes. A set of 124 accessions of Cucurnis melo has been selected for molecular and morpho-colourimetric analyses plus an additional selection of accessions of Cucumis sativus, Citrullus lanatus and Citrullus colocynthis used to highlight seed morphology distances among genus and species. Genotyping was performed on the basis of 211 polymorphic SNPs and was executed using the iPLEX (R) Gold MassARRAY Sequenom technology. A total of 137 parameters were specifically designed to evaluate seed colour, size, shape and texture. Both molecular and seed morpho-colourimetrical analyses confirm the existence of two melon subspecies while an intermediate group has also been found. A non random allelic distribution in SNPs located in specific genomic regions suggests that some of these regions may account for a part of the observed variation in seed size. Six major groups of varieties can be discriminated on the basis on seed traits. (C) 2015 Elsevier B.V. All rights reserved.The Italian University and Research Ministry (MIUR) financed the Ph.D. scholarship (Diego Sabato, Univeristy of Cagliari), making this research possible. Molecular analysis was carried out with contributions of the PLANT KKBE project PIM2010PKB-00691 and the complementary grant from the Generalitat Valenciana ACOMP/2013/141.Sabato, D.; Esteras Gómez, C.; Grillo, O.; Picó Sirvent, MB.; Bacchetta, G. (2015). Seeds morpho-colourimetric analysis as complementary method to molecular characterization of melon diversity. Scientia Horticulturae. 192:441-452. https://doi.org/10.1016/j.scienta.2015.06.006S44145219

Quinoa phenotyping methodologies: An international consensus

Quinoa is a crop originating in the Andes but grown more widely and with the genetic potential for significant further expansion. Due to the phenotypic plasticity of quinoa, varieties need to be assessed across years and multiple locations. To improve comparability among field trials across the globe and to facilitate collaborations, components of the trials need to be kept consistent, including the type and methods of data collected. Here, an internationally open-access framework for phenotyping a wide range of quinoa features is proposed to facilitate the systematic agronomic, physiological and genetic characterization of quinoa for crop adaptation and improvement. Mature plant phenotyping is a central aspect of this paper, including detailed descriptions and the provision of phenotyping cards to facilitate consistency in data collection. High-throughput methods for multi-temporal phenotyping based on remote sensing technologies are described. Tools for higher-throughput post-harvest phenotyping of seeds are presented. A guideline for approaching quinoa field trials including the collection of environmental data and designing layouts with statistical robustness is suggested. To move towards developing resources for quinoa in line with major cereal crops, a database was created. The Quinoa Germinate Platform will serve as a central repository of data for quinoa researchers globally.Fil: Stanschewski, Clara S.. King Abdullah University of Science and Technology; Arabia SauditaFil: Rey, Elodie. King Abdullah University of Science and Technology; Arabia SauditaFil: Fiene, Gabriele. King Abdullah University of Science and Technology; Arabia SauditaFil: Craine, Evan B.. Washington State University; Estados UnidosFil: Wellman, Gordon. King Abdullah University of Science and Technology; Arabia SauditaFil: Melino, Vanessa J.. King Abdullah University of Science and Technology; Arabia SauditaFil: Patiranage, Dilan S. R.. King Abdullah University of Science and Technology; Arabia SauditaFil: Johansen, Kasper. King Abdullah University of Science and Technology; Arabia SauditaFil: Schmöckel, Sandra M.. King Abdullah University of Science and Technology; Arabia SauditaFil: Bertero, Hector Daniel. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Producción Vegetal. Cátedra de Producción Vegetal; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura. Universidad de Buenos Aires. Facultad de Agronomía. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura; ArgentinaFil: Oakey, Helena. University of Adelaide; AustraliaFil: Colque Little, Carla. Universidad de Copenhagen; DinamarcaFil: Afzal, Irfan. University of Agriculture; PakistánFil: Raubach, Sebastian. The James Hutton Institute; Reino UnidoFil: Miller, Nathan. University of Wisconsin; Estados UnidosFil: Streich, Jared. Oak Ridge National Laboratory; Estados UnidosFil: Amby, Daniel Buchvaldt. Universidad de Copenhagen; DinamarcaFil: Emrani, Nazgol. Christian-albrechts-universität Zu Kiel; AlemaniaFil: Warmington, Mark. Agriculture And Food; AustraliaFil: Mousa, Magdi A. A.. Assiut University; Arabia Saudita. King Abdullah University of Science and Technology; Arabia SauditaFil: Wu, David. Shanxi Jiaqi Agri-Tech Co.; ChinaFil: Jacobson, Daniel. Oak Ridge National Laboratory; Estados UnidosFil: Andreasen, Christian. Universidad de Copenhagen; DinamarcaFil: Jung, Christian. Christian-albrechts-universität Zu Kiel; AlemaniaFil: Murphy, Kevin. Washington State University; Estados UnidosFil: Bazile, Didier. Savoirs, Environnement, Sociétés; Francia. Universite Paul-valery Montpellier Iii; FranciaFil: Tester, Mark. King Abdullah University of Science and Technology; Arabia Saudit

Quinoa Phenotyping Methodologies: An International Consensus

Quinoa is a crop originating in the Andes but grown more widely and with the genetic potential for significant further expansion. Due to the phenotypic plasticity of quinoa, varieties need to be assessed across years and multiple locations. To improve comparability among field trials across the globe and to facilitate collaborations, components of the trials need to be kept consistent, including the type and methods of data collected. Here, an internationally open-access framework for phenotyping a wide range of quinoa features is proposed to facilitate the systematic agronomic, physiological and genetic characterization of quinoa for crop adaptation and improvement. Mature plant phenotyping is a central aspect of this paper, including detailed descriptions and the provision of phenotyping cards to facilitate consistency in data collection. High-throughput methods for multi-temporal phenotyping based on remote sensing technologies are described. Tools for higher throughput post-harvest phenotyping of seeds are presented. A guideline for approaching quinoa field trials including the collection of environmental data and designing layouts with statistical robustness is suggested. To move towards developing resources for quinoa in line with major cereal crops, a database was created. The Quinoa Germinate Platform will serve as a central repository of data for quinoa researchers globally

Quinoa Phenotyping Methodologies: An International Consensus

Quinoa is a crop originating in the Andes but grown more widely and with the genetic potential for significant further expansion. Due to the phenotypic plasticity of quinoa, varieties need to be assessed across years and multiple locations. To improve comparability among field trials across the globe and to facilitate collaborations, components of the trials need to be kept consistent, including the type and methods of data collected. Here, an internationally open-access framework for phenotyping a wide range of quinoa features is proposed to facilitate the systematic agronomic, physiological and genetic characterization of quinoa for crop adaptation and improvement. Mature plant phenotyping is a central aspect of this paper, including detailed descriptions and the provision of phenotyping cards to facilitate consistency in data collection. High-throughput methods for multi-temporal phenotyping based on remote sensing technologies are described. Tools for higher-throughput post-harvest phenotyping of seeds are presented. A guideline for approaching quinoa field trials including the collection of environmental data and designing layouts with statistical robustness is suggested. To move towards developing resources for quinoa in line with major cereal crops, a database was created. The Quinoa Germinate Platform will serve as a central repository of data for quinoa researchers globally.EEA FamailláFil: Stanschewski, Clara S. King Abdullah University of Science and Technology. Center for Desert Agriculture, Biological and Environmental Sciences and Engineering Division; Arabia SauditaFil: Rey, Elodie. King Abdullah University of Science and Technology. Center for Desert Agriculture, Biological and Environmental Sciences and Engineering Division; Arabia SauditaFil: Fiene, Gabriele. King Abdullah University of Science and Technology. Center for Desert Agriculture, Biological and Environmental Sciences and Engineering Division; Arabia SauditaFil: Craine, Evan B. Washington State University. Department of Crop and Soil Sciences; Estados UnidosFil: Wellman, Gordon. King Abdullah University of Science and Technology. Center for Desert Agriculture, Biological and Environmental Sciences and Engineering Division; Arabia SauditaFil: Melino, Vanessa J. King Abdullah University of Science and Technology. Center for Desert Agriculture, Biological and Environmental Sciences and Engineering Division; Arabia SauditaFil: Patiranage, Dilan S.R. King Abdullah University of Science and Technology. Center for Desert Agriculture, Biological and Environmental Sciences and Engineering Division; Arabia SauditaFil: Patiranage, Dilan S.R. Christian-Albrechts-University of Kiel. Plant Breeding Institute; AlemaniaFil: Johansen, Kasper. King Abdullah University of Science and Technology. Water Desalination and Reuse Center; Arabia SauditaFil: Schmöckel, Sandra M. University of Hohenheim. Institute of Crop Science. Department Physiology of Yield Stability; AlemaniaFil: Erazzu, Luis Ernesto. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Famaillá; Argentina.Fil: Tester, Mark. King Abdullah University of Science and Technology. Center for Desert Agriculture, Biological and Environmental Sciences and Engineering Division; Arabia Saudit

LABRAD : Vol 46, Issue 4 - October 2021

Role of Barcoding in a Clinical Laboratory to Reduce Pre-Analytical Errors Congenital Dyserythropoietic Anemia: The Morphological Diagnosis Digital Imaging in Hematology: A New Beginning Metabolomics: Identification of Fatty Acid Oxidation (FAO) Disorders Next-Generation Sequencing for HLA Genotyping Urine Metabolomics to identify Organic Academia Next-Generation Sequencing (NGS) of Solid Tumor Importance of using Genomic Tool in Microbial Identification Radiology Practice in 21st Century: Role of Artificial Intelligence Case Quiz Best of the Recent Past Polaroidhttps://ecommons.aku.edu/labrad/1036/thumbnail.jp

Biosensors for Diagnosis and Monitoring

Biosensor technologies have received a great amount of interest in recent decades, and this has especially been the case in recent years due to the health alert caused by the COVID-19 pandemic. The sensor platform market has grown in recent decades, and the COVID-19 outbreak has led to an increase in the demand for home diagnostics and point-of-care systems. With the evolution of biosensor technology towards portable platforms with a lower cost on-site analysis and a rapid selective and sensitive response, a larger market has opened up for this technology. The evolution of biosensor systems has the opportunity to change classic analysis towards real-time and in situ detection systems, with platforms such as point-of-care and wearables as well as implantable sensors to decentralize chemical and biological analysis, thus reducing industrial and medical costs. This book is dedicated to all the research related to biosensor technologies. Reviews, perspective articles, and research articles in different biosensing areas such as wearable sensors, point-of-care platforms, and pathogen detection for biomedical applications as well as environmental monitoring will introduce the reader to these relevant topics. This book is aimed at scientists and professionals working in the field of biosensors and also provides essential knowledge for students who want to enter the field