35,388 research outputs found
Opportunities and limitations of crop phenotyping in southern european countries
ReviewThe Mediterranean climate is characterized by hot dry summers and frequent droughts.
Mediterranean crops are frequently subjected to high evapotranspiration demands,
soil water deficits, high temperatures, and photo-oxidative stress. These conditions
will become more severe due to global warming which poses major challenges to the
sustainability of the agricultural sector in Mediterranean countries. Selection of crop
varieties adapted to future climatic conditions and more tolerant to extreme climatic events
is urgently required. Plant phenotyping is a crucial approach to address these challenges.
High-throughput plant phenotyping (HTPP) helps to monitor the performance of improved
genotypes and is one of the most effective strategies to improve the sustainability of
agricultural production. In spite of the remarkable progress in basic knowledge and
technology of plant phenotyping, there are still several practical, financial, and political
constraints to implement HTPP approaches in field and controlled conditions across the
Mediterranean. The European panorama of phenotyping is heterogeneous and integration
of phenotyping data across different scales and translation of “phytotron research” to the
field, and from model species to crops, remain major challenges. Moreover, solutions
specifically tailored to Mediterranean agriculture (e.g., crops and environmental stresses)
are in high demand, as the region is vulnerable to climate change and to desertification
processes. The specific phenotyping requirements of Mediterranean crops have not
yet been fully identified. The high cost of HTPP infrastructures is a major limiting factor,
though the limited availability of skilled personnel may also impair its implementation in
Mediterranean countries. We propose that the lack of suitable phenotyping infrastructures
is hindering the development of new Mediterranean agricultural varieties and will negatively
affect future competitiveness of the agricultural sector. We provide an overview of the
heterogeneous panorama of phenotyping within Mediterranean countries, describing the
state of the art of agricultural production, breeding initiatives, and phenotyping capabilities
in five countries: Italy, Greece, Portugal, Spain, and Turkey. We characterize some of the main impediments for development of plant phenotyping in those countries and identify
strategies to overcome barriers and maximize the benefits of phenotyping and modeling
approaches to Mediterranean agriculture and related sustainabilityinfo:eu-repo/semantics/publishedVersio
In the quest of vision-sensors-on-chip: Pre-processing sensors for data reduction
This paper shows that the implementation of vision systems benefits from the usage of sensing front-end chips with embedded pre-processing capabilities - called CVIS. Such embedded pre-processors reduce the number of data to be delivered for ulterior processing. This strategy, which is also adopted by natural vision systems, relaxes system-level requirements regarding data storage and communications and enables highly compact and fast vision systems. The paper includes several proof-o-concept CVIS chips with embedded pre-processing and illustrate their potential advantages. © 2017, Society for Imaging Science and Technology.Office of Naval Research (USA) N00014-14-1-0355Ministerio de Economía y Competitiviad TEC2015-66878-C3-1-R, TEC2015-66878-C3-3-RJunta de Andalucía 2012 TIC 233
The future of laboratory medicine - A 2014 perspective.
Predicting the future is a difficult task. Not surprisingly, there are many examples and assumptions that have proved to be wrong. This review surveys the many predictions, beginning in 1887, about the future of laboratory medicine and its sub-specialties such as clinical chemistry and molecular pathology. It provides a commentary on the accuracy of the predictions and offers opinions on emerging technologies, economic factors and social developments that may play a role in shaping the future of laboratory medicine
Masking Strategies for Image Manifolds
We consider the problem of selecting an optimal mask for an image manifold,
i.e., choosing a subset of the pixels of the image that preserves the
manifold's geometric structure present in the original data. Such masking
implements a form of compressive sensing through emerging imaging sensor
platforms for which the power expense grows with the number of pixels acquired.
Our goal is for the manifold learned from masked images to resemble its full
image counterpart as closely as possible. More precisely, we show that one can
indeed accurately learn an image manifold without having to consider a large
majority of the image pixels. In doing so, we consider two masking methods that
preserve the local and global geometric structure of the manifold,
respectively. In each case, the process of finding the optimal masking pattern
can be cast as a binary integer program, which is computationally expensive but
can be approximated by a fast greedy algorithm. Numerical experiments show that
the relevant manifold structure is preserved through the data-dependent masking
process, even for modest mask sizes
Reflectance Transformation Imaging (RTI) System for Ancient Documentary Artefacts
This tutorial summarises our uses of reflectance transformation imaging in archaeological contexts. It introduces the UK AHRC funded project reflectance Transformation Imaging for Anciant Documentary Artefacts and demonstrates imaging methodologies
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