62-3 Getting Maize Phenology Right.

See more from this Division: ASA Section: Climatology & Modeling
See more from this Session: Symposium--Improving Tools to Assess Climate Change Effects On Crop Response: Modeling Approaches and Applications: I

Monday, November 4, 2013: 8:45 AM
Tampa Convention Center, Room 7

Matthijs Tollenaar, Monsanto Company - USA, Research Triangle Park, NC, Kofikuma Dzotsi, University of Florida, Gainesville, FL, James W. Jones, Ag. and Bio. Engineering, University of Florida, Gainesville, FL and Saratha V. Kumudini, The Climate Corporation, Research Triangle Park, NC
Abstract:
Arguably, the greatest impact of temperature on maize yield is through its impact on phenology. Phenology influences the duration of the life cycle and the timing of important stages of development that are critical in terms of yield formation and climate. Thermal functions have long been used to account for temperature effects on rate of development. The objective of this study was to determine how well current thermal functions quantify maize phenology, and whether this is dependent on (i) the phase of development, (ii) the relative maturity of the hybrid, and (iii) the ambient temperature distribution. Eight thermal functions were evaluated across a number of diverse public and private data sets.  For each function, thermal accumulation was calculated from planting to anthesis (or silking), and from silking to black layer formation.  Results showed that prediction of the planting to anthesis (or silking) period was more precise for thermal functions than for calendar dates, non-linear methods were generally more precise than the linear methods, Crop Heat Units was overall the most precise method, and thermal functions performed similarly among hybrids ranging in Relative Maturity(RM) ratings from RM76 to RM120. Hybrid-locations were predicted generally more precisely in the higher RM groups grown at more Southern locations in the NA Corn Belt data set, whereas predictions were poorest for the late planting dates in the Argentinean data set. The period from silking to physiological maturity was generally poorly quantified by the tested thermal functions and were less precise than calendar days, with the exception of the General Thermal Index.  The impact of photoperiod, temperature and solar radiation on duration of phases as measured in thermal units was evaluated.

See more from this Division: ASA Section: Climatology & Modeling
See more from this Session: Symposium--Improving Tools to Assess Climate Change Effects On Crop Response: Modeling Approaches and Applications: I