{"id":167593,"date":"2015-01-01T00:00:00","date_gmt":"2015-01-01T00:00:00","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/msr-research-item\/is-peak-n-key-to-understanding-the-timing-of-flowering-in-annual-plants\/"},"modified":"2018-10-16T22:20:28","modified_gmt":"2018-10-17T05:20:28","slug":"is-peak-n-key-to-understanding-the-timing-of-flowering-in-annual-plants","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/is-peak-n-key-to-understanding-the-timing-of-flowering-in-annual-plants\/","title":{"rendered":"Is &#8216;peak N&#8217; key to understanding the timing of flowering in annual plants?"},"content":{"rendered":"<div class=\"asset-content\">\n<ul>\n<li>Flowering time in annual plants has large fitness consequences and has been the focus of theoretical and empirical study. Previous theory has concluded that flowering time has evolved over evolutionary time to maximize fitness over a particular season length.<\/li>\n<li>We introduce a new model where flowering is cued by a growth-rate rule (peak nitrogen (N)). Flowering is therefore sensitive to physiological parameters and to current environmental conditions, including N availability and the presence of competitors.<\/li>\n<li>The model predicts that, when overall conditions are suitable for flowering, plants should never flower after \u2018peak N\u2019, the point during development when the whole-plant N uptake rate reaches its maximum. Our model further predicts correlations between flowering time and vegetative growth rates, and that the response to increased N depends heavily on how this extra N is made available. We compare our predictions to observations in the literature.<\/li>\n<li>We suggest that annual plants may have evolved to use growth-rate rules as part of the cue for flowering, allowing them to smoothly and optimally adjust their flowering time to a wide range of local conditions. If so, there are widespread implications for the study of the molecular biology behind flowering pathways.<\/li>\n<\/ul>\n<\/div>\n<p><!-- .asset-content --><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Flowering time in annual plants has large fitness consequences and has been the focus of theoretical and empirical study. Previous theory has concluded that flowering time has evolved over evolutionary time to maximize fitness over a particular season length. We introduce a new model where flowering is cued by a growth-rate rule (peak nitrogen (N)). 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We continue to actively explore the exciting intersection of computing and life sciences, with other projects located on\u00a0www.microsoft.com\/research. Building a platform for programming biology The ability to program biology could enable fundamental breakthroughs across a broad range of industries, including medicine, agriculture, food, construction, textiles, materials and chemicals. It could also help lay the foundation for a future bioeconomy based on sustainable technology. 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