Optimization of Tomato Productivity Using Flowering Time Variantsopen access
- Authors
- Rajendran, Sujeevan; Heo, Jung; Kim, Yong Jun; Kim, Dae Heon; Ko, Kisung; Lee, Young Koung; Oh, Seok Kwi; Kim, Chul Min; Bae, Jong Hyang; Park, Soon Ju
- Issue Date
- Feb-2021
- Publisher
- MDPI
- Keywords
- flowering time; genetic variants; optimization; plant growth; tomato yield
- Citation
- AGRONOMY-BASEL, v.11, no.2
- Journal Title
- AGRONOMY-BASEL
- Volume
- 11
- Number
- 2
- URI
- https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/48180
- DOI
- 10.3390/agronomy11020285
- ISSN
- 2073-4395
2073-4395
- Abstract
- Y The control of flowering time is a major contributing factor to the improvement of crop yield by optimizing plant growth in a crop cycle. Genetic variants that determine flowering time can provide insights into optimizing flowering time for higher yields and other beneficial traits in tomato crops. Here, we examined a collection of flowering time variants to assess their effects on biomass and total tomato yields. Five late flowering (lf), thirteen large plant (lp), and seven floral homeotic (fh) mutants were identified as flowering time variants that could be rearranged according to leaf production in the primary shoot meristem (PSM). A flowering time continuum of mutants was translated into a positive continuum of biomass yield with more leaves, branches, and floral organs. The flowering time continuum showed an optimal curve of fruit yield, indicating a certain late flowering time as optimal for fruit yield, with the yield gradually decreasing in both directions with earlier or later flowering times. We isolated lf1, lf10, lp22, and fh13 as high-yielding genotypes with optimal flowering time, showing a new balance between the vegetative and flowering phases of tomato. Additionally, lp8, fh8, and fh15 produced extremely high biomass in leaves, axillary shoots, and floral organs due to late flowering in shoot apices with additional production of floral organs and lateral shoot. Our new late-flowering variants provide new genetic resources that can be used to optimize crop yield by fine-tuning flowering time, and future molecular studies could be conducted by revisiting our yield model.
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