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iPASTIC: An online toolkit to estimate plant abiotic stress indices

PREMISE: In crop breeding programs, breeders use yield performance in both optimal and stressful environments as a key indicator for screening the most tolerant genotypes. During the past four decades, several yield‐based indices have been suggested for evaluating stress tolerance in crops. Despite...

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Detalles Bibliográficos
Autores principales: Pour‐Aboughadareh, Alireza, Yousefian, Mohsen, Moradkhani, Hoda, Moghaddam Vahed, Mohammad, Poczai, Peter, Siddique, Kadambot H. M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6636621/
https://www.ncbi.nlm.nih.gov/pubmed/31346510
http://dx.doi.org/10.1002/aps3.11278
Descripción
Sumario:PREMISE: In crop breeding programs, breeders use yield performance in both optimal and stressful environments as a key indicator for screening the most tolerant genotypes. During the past four decades, several yield‐based indices have been suggested for evaluating stress tolerance in crops. Despite the well‐established use of these indices in agronomy and plant breeding, a user‐friendly software that would provide access to these methods is still lacking. METHODS AND RESULTS: The Plant Abiotic Stress Index Calculator (iPASTIC) is an online program based on JavaScript and R that calculates common stress tolerance and susceptibility indices for various crop traits including the tolerance index (TOL), relative stress index (RSI), mean productivity (MP), harmonic mean (HM), yield stability index (YSI), geometric mean productivity (GMP), stress susceptibility index (SSI), stress tolerance index (STI), and yield index (YI). Along with these indices, this easily accessible tool can also calculate their ranking patterns, estimate the relative frequency for each index, and create heat maps based on Pearsonʼs and Spearmanʼs rank‐order correlation analyses. In addition, it can also render three‐dimensional plots based on both yield performances and each index to separate entry genotypes into Fernandezʼs groups (A, B, C, and D), and perform principal component analysis. The accuracy of the results calculated from our software was tested using two different data sets obtained from previous experiments testing the salinity and drought stress in wheat genotypes, respectively. CONCLUSIONS: iPASTIC can be widely used in agronomy and plant breeding programs as a user‐friendly interface for agronomists and breeders dealing with large volumes of data. The software is available at https://mohsenyousefian.com/ipastic/.