期刊
PLANT MOLECULAR BIOLOGY REPORTER
卷 32, 期 5, 页码 1070-1084出版社
SPRINGER
DOI: 10.1007/s11105-014-0711-7
关键词
Grapevine; Genetic phenology; Gene expression; Fertilization; Precision agriculture
资金
- Natural Science Foundation of China (NSFC) [31301759]
- Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD)
- Chinese Postdoctoral Science Foundation [2013M531373]
- Postdoctoral Science Foundation of Jiangsu Province [1301116C]
- Nanjing Agricultural University Youth Science and Technology Innovation Fund [KJ2013013]
- Special Fund for Independent innovation of Agricultural Science and Technology in Jiangsu province [SCX(11)2044]
The development of precision agriculture calls for the emergence of new approaches to more accurately depict plant phenology. Gene expression data can predict and indicate plant growth state and phenological events accurately at the molecular level, and thus could be developed as a novel means of describing crop phenophase. Here, we analyzed the expression profiles of nine genes involved in grapevine flower and berry development, and screened the most informative genes for use in depicting grapevine phenology. Of the genes tested, VvAP1, VvAP3, VvFLC were found to be best suited to depicting grapevine phenology. The feasibility and efficiency of using the genetically depicted grapevine phenology was further tested in fertilization trials. The results showed that fertilization could be used to decrease flower and berry drop ratio and increase berry weight and size to a greater extent when taking into account variations in the activity of specific genes. Thus, phenologies predicted by a knowledge of gene activity can definitely be formed, and can be regarded as genetic phenology. A first grapevine genetic phenology profile was completed, and used to pre-depict grapevine phenophases to accurately guide the timing of grapevine farming activities and in the pre-diagnosis of the influence of some stresses on grapevines. Genetic phenology could be developed into a simple, low-cost and highly effective technology for accurate prediction of traditional crop phenology at the molecular level that is well suited to precision agriculture.
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