Evidence map›Paper›PMID 20003250›Full record

ArticlePlant methods2009

Computer aided data acquisition tool for high-throughput phenotyping of plant populations.

Raju Naik Vankadavath, Appibhai Jakir Hussain, Reddaiah Bodanapu, Eros Kharshiing, Pinjari Osman Basha, Soni Gupta, Yellamaraju Sreelakshmi, Rameshwar Sharma

Abstract read
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Article in Plant methods, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Raju Naik VankadavathSchool of Life Sciences, University of Hyderabad, Hyderabad 500 046, India. rameshwar.sharma@gmail.com.
Appibhai Jakir Hussain
Reddaiah Bodanapu
Eros Kharshiing
Pinjari Osman Basha
Soni Gupta
Yellamaraju Sreelakshmi
Rameshwar Sharma

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe data generated during a course of a biological experiment/study can be sometimes be massive and its management becomes quite critical for the success of the investigation undertaken. The accumulation and analysis of such large datasets often becomes tedious for biologists and lab technicians. Most of the current phenotype data acquisition management systems do not cater to the specialized needs of large-scale data analysis. The successful application of genomic tools/strategies to introduce desired traits in plants requires extensive and precise phenotyping of plant populations or gene bank material, thus necessitating an efficient data acquisition system.

resultsHere we describe newly developed software "PHENOME" for high-throughput phenotyping, which allows researchers to accumulate, categorize, and manage large volume of phenotypic data. In this study, a large number of individual tomato plants were phenotyped with the "PHENOME" application using a Personal Digital Assistant (PDA) with built-in barcode scanner in concert with customized database specific for handling large populations.

conclusionThe phenotyping of large population of plants both in the laboratory and in the field is very efficiently managed using PDA. The data is transferred to a specialized database(s) where it can be further analyzed and catalogued. The "PHENOME" aids collection and analysis of data obtained in large-scale mutagenesis, assessing quantitative trait loci (QTLs), raising mapping population, sampling of several individuals in one or more ecological niches etc.

Identifiers

PMID20003250
PMCPMC2796657

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.