Predicting maize pollen production using tassel morphological characteristics

International audience

Inglés. In the European Union, it has been decided that farmers and consumers should be free to choose between conventional, organic, and genetically modified (GM) crops/products. This concept of coexistence implies the necessity of developing coexistence strategies which curb the risk of mixing GM and non-GM material along agricultural supply chains. Among many things, this requires understanding and predicting the process of cross-pollination between the different varieties cultivated on a given landscape. In order to provide a prediction accurate enough to cope with legal thresholds, it is necessary to be able to rank varieties according to their pollen production. However, this parameter is rarely known, partly because it is difficult and expensive to measure. We investigated how easy-to-measure tassel morphological characteristics can be used to predict the quantity of pollen produced by hybrid maize varieties. Thirteen varieties were grown in France on experimental plots during three years with two varieties added the last year. For each variety, we measured the pollen production and variables that describe the tassel architecture. We found that the number of ramifications, the length of the tassel, the length of the emitting section, the number of spikelets and the TAI (the Tassel Area Index which aims at estimating the pollen emitting area) were correlated with pollen production. Using linear models, we identified the number of spikelets as the best architectural variable related to pollen production. In order to evaluate the ability of tassel characteristics to predict pollen production, we analysed how the relationships established in the case of any two years made it possible to predict the pollen production of the third year. The model that combined the total length of the tassel and the total number of spikelets was found to be the best predictive model of the relative pollen production between varieties.