Mapping QTL for cotton fiber quality traits using simple sequence repeat markers, conserved intron-scanning primers, and transcript-derived fragments

Euphytica ◽  
2014 ◽  
Vol 201 (2) ◽  
pp. 215-230 ◽  
Author(s):  
Xinlei Yang ◽  
Xiaodong Zhou ◽  
Xingfen Wang ◽  
Zhikun Li ◽  
Yan Zhang ◽  
...  
2017 ◽  
Vol 5 (2) ◽  
pp. 86
Author(s):  
Vasileios Greveniotis ◽  
Evangelia Sioki

The objective of this study was to evaluate cotton fiber quality traits across diverse environments. This could lead to the selection of the best environment for cotton cultivations and the best adapted commercial cultivars. For this reason four main cotton regions were chosen as different environments: Thessaly, Thrace, Macedonia and Sterea Ellas. Five of the most commercial upland cotton cultivars (DP332, DP377, ST402, CELIA and ELSA) were used for evaluation of their fiber quality traits. Each cultivar was sown in 10 different fields (in order to exploit and evaluate different soil types) in each of the above mentioned regions and (in total) 200 fields were used in total. Four samples from each field were collected in order to analyze fiber quality traits: micronaire, maturity index (%), fiber length as the upper half mean length (mm), fiber strength (gram/tex), uniformity index (%), fiber elongation, short fiber index, yellowness (+b), reflectance index (Rd).Cultivation regions must also be selected in a way that they could promote fiber traits, in order to ensure the highest fiber quality. Cotton fiber quality traits were affected differently from environmental fluctuations, showing that the ranking of cultivars according to environmental fluctuations is important, if proper breeding methods should be applied. Each trait is affected differently by environmental fluctuations and requires precise knowledge of the degree of inheritance i.e., as to how much qualitative or quantitative is the trait, in order to choose and apply the proper breeding method.


Euphytica ◽  
2017 ◽  
Vol 213 (3) ◽  
Author(s):  
Jeevan Adhikari ◽  
Sayan Das ◽  
Zining Wang ◽  
Sameer Khanal ◽  
Rahul Chandnani ◽  
...  

Genomics ◽  
2020 ◽  
Vol 112 (2) ◽  
pp. 1554-1564 ◽  
Author(s):  
Vandana Jaiswal ◽  
Abdul Rawoof ◽  
Meenakshi Dubey ◽  
Sushil Satish Chhapekar ◽  
Vineet Sharma ◽  
...  

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