F. Tardieu: Which information from phenotyping can be used for breeding?

Francois Tardieu is an Ecophysiologist and Research Director at INRA Montpellier (France). His research focuses on the adaptation of genotypes to drought scenarios, including those in 2050, via a combination of phenomics, modelling and genomic prediction. He coordinates the French Phenomic infrastructure and a European project on phenomics. He is invited professor in the Nanjing Agricultural University. He got awards by the French Academy, by the “laurier d’Excellence INRA” and by the Soil Science Society of America.

The plant science community takes for granted that the triplet mechanism (QTL)-phenomics-genomics is the best, perhaps the only way towards efficient breeding in a changing climate. It is healthy to recognise that, for good reasons, most breeding companies have essentially abandoned this view in favour of genomic prediction approaches. Why invest in costly phenotyping platforms that do not represent the field, are more heterogeneous than any field and do not improve heritability?

Field phenotyping is now fashionable but why invest in vectors and sensors whose outputs are well correlated to yield, whereas it is simpler and more accurate to measure yield itself and to predict it for hundreds of genotypes via big data approaches? I firmly believe that phenomics keeps its interest in this context, but with renewed objectives and techniques that makes it complementary to big data. I shall present elements to back this statement, and discuss consequences in terms of modelling the genotype x environment interaction (‘where and when every combination of alleles?’, ‘what happens if?’).