266-5 Model-Estimated Photoperiod Sensitivity of Spring Wheat and Barley.

Poster Number 527

See more from this Division: A03 Agroclimatology & Agronomic Modeling
See more from this Session: Agroclimatology & Agronomic Modeling: II
Wednesday, November 3, 2010
Long Beach Convention Center, Exhibit Hall BC, Lower Level
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Andres Berger, Marina Castro and Sergio Ceretta, INIA, Colonia, Uruguay
Photoperiod sensitivity is of primordial importance in setting time to anthesis in most spring wheat and barley varieties, regulating the adaptation to a range of planting dates. Traditional methods utilized in the determination of photoperiod sensitivity include reciprocal transfer experiments, where plants are exposed to long and short day periods. Alternatively to this approach, data from field trials can be assimilated into a model to estimate photoperiod sensitivity. In this study, data collected from field variety trials conducted at two locations (Young, 32°43’ S, 57°39’ W and La Estanzuela, 34°20’ S, 57°41’ W) between 1991 y 2008 was used to fit the model. A total of 3754 records for 145 spring wheat, and 1806 records for 77 spring barley cultivars representative of the germplasm planted in southern Brazil, Uruguay and Argentina were utilized, assuring a minimum of 11 records per cultivar distributed from early planting (May) to late planting (August) dates. The model fits by least squares a three plane surface in the 3D space defined by mean temperature, mean photoperiod and 1/days to flower. Only 11 wheat and 3 barley cultivars showed to be insensitive to photoperiod. The remaining had some degree of photoperiod sensitivity, with a clear predominance of highly sensitive cultivars among those with the largest emergence-flowering period. Cultivars showed a continuum of responses and it was not possible to identify groupings. The present method appears as a high benefit to cost approach to achieve continuous estimates of photoperiod sensitivity for genetic and modeling analyses utilizing ancillary data from field trials.
See more from this Division: A03 Agroclimatology & Agronomic Modeling
See more from this Session: Agroclimatology & Agronomic Modeling: II