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Giunta, F.

Publications and source records attributed to Giunta, F..

2 recordsLinked to original sources

Tillering structures the genetic variability of wheat vegetative growth and its plasticity under water deficit

Leaf expansion under drought drives the trade-off between water saving for later grain production and canopy photosynthesis. Fine-tuning leaf expansion could therefore become a target of genetic progress for drought-prone environments. However, its components (branching, leaf production and elongation) may have their own genetic variability and plasticity under drought, making hard to calibrate crop simulation models and specify breeding targets. In this study, we focused on the genetic diversity of bread wheat and durum wheat to determine the links and trade-offs between the underlying processes of leaf growth under drought and how it translates to leaf expansion at the whole plant and canopy level. For that, we used non-destructive imaging both in the field and controlled condition platforms to determine the dynamics of the components of shoot expansion and analyze their relative contribution to the genetic variability of whole-plant shoot expansion under drought. Results show that leaf expansion measured at plant level in controlled environment was associated with that measured at canopy level in the field, indicating that controlled phenotyping platforms can capture the genetic variability of growth in the field. Both whole-plant and canopy expansion were associated with tillering rate. In addition, the sensitivity of shoot growth and tillering to soil water deficit were correlated, indicating that both tillering ability and sensitivity to water deficit drive the genetic variability of shoot expansion. Overall, dissecting leaf expansion dynamics allowed determining the links between shoot expansion traits under drought, and provides key targets in phenotyping, modelling and breeding for drought environments.

plant biology↗

Dissecting durum wheat time to anthesis into physiological traits using a QTL-based model

Fine tuning crop development is a major breeding avenue to increase crop yield and for adaptation to climate change. In this study, we used a model that integrates our current understanding of the physiology of wheat phenology to predict the development and anthesis date of a RILs population of durum wheat with genotypic parameters controlling vernalization requirement, photoperiod sensitivity, and earliness per se estimated using leaf stage, final leaf number, anthesis date data from a pot experiment with vernalized and nonvernalized treatments combined with short- and long-day length. Predictions of final leaf number and anthesis date of the QTL-based model was evaluated for the whole population of RILs in a set of independent field trials and for the two parents, which were not used to estimate the parameter values. Our novel approach reduces the number of environments, experimental costs, and the time required to obtain the required data sets to develop a QTL-based prediction of model parameters. Moreover, the use of a physiologically based model of phenology gives new insight into genotype-phenology relations for wheat. We discuss the approach we used to estimate the parameters of the model and their association with QTL and major phenology genes that collocate at QTL. HighlightWe used a modeling framework integrating our current understanding of the physiology of wheat phenology to dissect durum wheat time to anthesis into physiological traits and link them to QTL.

plant biology↗