31 research outputs found
Hydrologic behaviour of Tapi river catchment using morphometric analysis
The study area Tapi River catchment covers 63,922.91 Sq.Km comprising of 5 five Sub-catchments: Purna river catchment (18,473.6 sq.km) Upper Tapi catchment (10,530.3 sq. km), Middle Tapi catchment (4,997.3 sq km), Girna river catchment (10,176.9 sq.km) and lower Tapi catchment (19,282.5 sq.km.). The drainage network of 5 Sub-catchments was delineated using remote sensing data. The morphometric analysis of 5 Sub-catchments has been carried out using GIS softwares – ArcMap. The drainage network showed that the terrain exhibits dendritic to sub-dendritic drainage pattern. Stream orders ranged from sixth to seventh order. Drainage density varied between 0.39 and 0.43km/ km2and had very coarse to coarse drainage texture. The relief ratio ranged from 0.003 to 0.007. The mean bifurcation ratio varied from 4.24 to 6.10 and falls under normal basin category. The elongation ratio showed that all catchment elongated pattern. Thus, the remote sensing techniques proved to be a competent tool in morphometric analysis
Phenotypic and genetic dissection of water stress adaptations in pearl millet (Pennisetum glaucum)
Pearl millet is an important staple food for farming communities
across semi-arid tropical systems of South Asia and
Sub-Saharan Africa where production suffers uncertain precipitation.
This work is undertaken under the premise that maximizing
grain yield under water-limited conditions depends
on both maximizing water use and ensuring water availability
for the grain filling period. Here we discuss the phenotyping
methods targeting the variability in plant water use strategies
which determine the crop production success in water-limited
environments. A fine-mapping population of pearl millet,
segregating within the previously identified drought tolerance
quantitative trait locus (QTL) on chromosome 2 (LG02), was
tested across different experimental environments (pot culture,
high-throughput phenotyping platform (LeasyScan), Lysimeter,
and Field). Recombinants were then analyzed for traits
at different levels of plant organization, ranging from water-use
traits (transpiration rate, leaf area, plant organ dry weights,
etc.) to crop production and agronomic traits (grain yield, tiller
number, harvest index, etc.) The linkages between traits
across the experimental systems were analyzed, using principal
component analysis (PCA) and QTL co-localization approach.
The functional relevance of the phenotyping systems was traced
by PCA analysis. Furthermore, we found four regions within the
LG02-QTL underlying substantial co-mapping of water-use related
and agronomic traits. These regions were identified across
the experimental systems and justified linkages between water-
use traits were phenotyped at lower level of plant organization
to the agronomic traits assessed in the field. Therefore, the
phenotyping systems at ICRISAT are validated and well set to
accelerate crop breeding for drought adaptations
Quantitative trait loci (QTLs) for water use and crop production traits co-locate with major QTL for tolerance to water deficit in a fine-mapping population of pearl millet (Pennisetum glaucum L. R.Br.)
Key message
Four genetic regions associated with water use traits, measured at different levels of plant organization, and with agronomic traits were identified within a previously reported region for terminal water deficit adaptation on linkage group 2. Close linkages between these traits showed the value of phenotyping both for agronomic and secondary traits to better understand plant productive processes.
Abstract
Water saving traits are critical for water stress adaptation of pearl millet, whereas maximizing water use is key to the absence of stress. This research aimed at demonstrating the close relationship between traits measured at different levels of plant organization, some putatively involved in water stress adaptation, and those responsible for agronomic performance. A fine-mapping population of pearl millet, segregating for a previously identified quantitative trait locus (QTL) for adaptation to terminal drought stress on LG02, was phenotyped for traits at different levels of plant organization in different experimental environments (pot culture, high-throughput phenotyping platform, lysimeters, and field). The linkages among traits across the experimental systems were analysed using principal component analysis and QTL co-localization approach. Four regions within the LG02-QTL were found and revealed substantial co-mapping of water use and agronomic traits. These regions, identified across experimental systems, provided genetic evidence of the tight linkages between traits phenotyped at a lower level of plant organization and agronomic traits assessed in the field, therefore deepening our understanding of complex traits and then benefiting both geneticists and breeders. In short: (1) under no/mild stress conditions, increasing biomass and tiller production increased water use and eventually yield; (2) under severe stress conditions, water savings at vegetative stage, from lower plant vigour and fewer tillers in that population, led to more water available during grain filling, expression of stay-green phenotypes, and higher yield
GeantV: Results from the prototype of concurrent vector particle transport simulation in HEP
Full detector simulation was among the largest CPU consumer in all CERN
experiment software stacks for the first two runs of the Large Hadron Collider
(LHC). In the early 2010's, the projections were that simulation demands would
scale linearly with luminosity increase, compensated only partially by an
increase of computing resources. The extension of fast simulation approaches to
more use cases, covering a larger fraction of the simulation budget, is only
part of the solution due to intrinsic precision limitations. The remainder
corresponds to speeding-up the simulation software by several factors, which is
out of reach using simple optimizations on the current code base. In this
context, the GeantV R&D project was launched, aiming to redesign the legacy
particle transport codes in order to make them benefit from fine-grained
parallelism features such as vectorization, but also from increased code and
data locality. This paper presents extensively the results and achievements of
this R&D, as well as the conclusions and lessons learnt from the beta
prototype.Comment: 34 pages, 26 figures, 24 table
Targeting tumorigenesis: development and use of mTOR inhibitors in cancer therapy
The mammalian target of rapamycin (mTOR) is an intracellular serine/threonine protein kinase positioned at a central point in a variety of cellular signaling cascades. The established involvement of mTOR activity in the cellular processes that contribute to the development and progression of cancer has identified mTOR as a major link in tumorigenesis. Consequently, inhibitors of mTOR, including temsirolimus, everolimus, and ridaforolimus (formerly deforolimus) have been developed and assessed for their safety and efficacy in patients with cancer. Temsirolimus is an intravenously administered agent approved by the US Food and Drug Administration (FDA) and the European Medicines Agency (EMEA) for the treatment of advanced renal cell carcinoma (RCC). Everolimus is an oral agent that has recently obtained US FDA and EMEA approval for the treatment of advanced RCC after failure of treatment with sunitinib or sorafenib. Ridaforolimus is not yet approved for any indication. The use of mTOR inhibitors, either alone or in combination with other anticancer agents, has the potential to provide anticancer activity in numerous tumor types. Cancer types in which these agents are under evaluation include neuroendocrine tumors, breast cancer, leukemia, lymphoma, hepatocellular carcinoma, gastric cancer, pancreatic cancer, sarcoma, endometrial cancer, and non-small-cell lung cancer. The results of ongoing clinical trials with mTOR inhibitors, as single agents and in combination regimens, will better define their activity in cancer