Λεπτομέρειες βιβλιογραφικής εγγραφής
| Τίτλος: |
Disclosure of Productive and Stable Sugarcane Genotypes for Cane Yield and Quality Traits Using Various Stability Statistics. |
| Συγγραφείς: |
Kumar, Ravinder, Meena, Mintu Ram, Dhansu, Pooja, Chhabra, Manohar Lal, Appunu, Chinnaswamy, Sreenivasa, V., Durai, A. Anna, Mahadeva Swamy, H. K., Amaresh |
| Πηγή: |
Tropical Plant Biology; Mar2025, Vol. 18 Issue 1, p1-16, 16p |
| Περίληψη: |
Sugarcane an important agro-industrial crop, is cultivated under varied environmental regimes of the world. Development of stable and high yielding varieties across multi-environments is major concern to the breeders. The present study was planned to identify most stable sugarcane genotypes combining better cane yield and juice quality among the 52 genotypes developed over the years. Different stability statistics viz., AMMI, GGE and various others were executed on the experimental data recorded during six crop seasons (2015–2021) under subtropical India. The ranking of stable genotypes differed with different stability models. To draw a common consensus of stability, cumulative tend (CT) rank was calculated for each genotype based on the nine stability coefficients of different stability models. Combining cane yield and sucrose% Co 15023 (G48), Co 0238 (G8), Co 06037 (G21), Co 0331 (G12), G 0118 (G4) and Co 06034 (G18) were identified stable genotypes. The AMMI, and GGE analyses also reveals the stability of gazette notified varieties Co 15023, Co 0118 and Co 06034 for both cane yield and sucrose percentage. Their cultivation will sustain the sugarcane and sugar production in Subtropical India and will serves as valuable genetic resources for breeding program utilizing them as the parents in developing cultivars for future sustainable global sugar production. [ABSTRACT FROM AUTHOR] |
|
Copyright of Tropical Plant Biology is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) |
| Βάση Δεδομένων: |
Complementary Index |