Improved strategy of screening tolerant genotypes in drought stress based on a new program in R-language: a practical triticale breeding program
Mozafari, Ali Akbar
Rezaei Mirghaed, Elham
Barzegar Marvasti, Fatemeh
AffiliationSchool of Plant Sciences College of Agriculture & Life Sciences, The University of Arizona
MetadataShow full item record
PublisherInforma UK Limited
CitationSaed-Moucheshi, A., Mozafari, A. A., Pessarakli, M., Rezaei Mirghaed, E., Sohrabi, F., Zaheri, S., Barzegar Marvasti, F., & Baniasadi, F. (2022). Improved strategy of screening tolerant genotypes in drought stress based on a new program in R-language: A practical triticale breeding program. Journal of Plant Nutrition.
JournalJournal of Plant Nutrition
Rights© 2022 Taylor & Francis Group, LLC.
Collection InformationThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at email@example.com.
AbstractIn order to improve the efficiency of breeding programs related to abiotic stresses, a new package in R-based-language, “PBTolindex,” was introduced to distinguish tolerant genotypes to drought stress. Accordingly, a dataset of a practical breeding program on 30 triticale genotypes cultivated under drought stress and normal irrigation conditions in six different environments was evaluated. Correlation plot, scatter plot matrix, 3 D plot, and biplot along with indices’ values and their correlation coefficients were automatically produced as output files for considering the tested genotypes. Additionally, heatmap, a novel data mining method, was successfully applied for the first time in tolerance analysis. Our results indicated that no single suitable tolerance index could be suggested as the best one, and for any other study, different indices should be considered. Furthermore, the outputs of testing triticale genotypes indicated no suitable genotypes for both conditions. However, genotype ELTTCL15 for normal condition and genotypes ET-90-7, ELTTCL21, and ELTTCL18 for stress conditions were recommended by the program. Testing and identifying genotypes by heatmap and principal component analyses showed that the output of our program was accurate. Therefore, using this source-code in future plant breeding projects based on stress indices in any plant species is recommended.
Note12 month embargo; published online: 13 July 2022
VersionFinal accepted manuscript