Predicting maize phenology: intercomparison of functions for developmental response to temperature

Kumudini, S., Andrade, F. H., Boote, K. J., Brown, G. A., Dzotsi, K. A., Edmeades, G. O., Gocken, T., Goodwin, M., Halter, A. L., Hammer, G. L., Hatfield, J. L., Jones, J. W., Kemanian, A. R., Kim, S.-H., Kiniry, J., Lizaso, J. I., Nendel, C., Nielsen, R. L., Parent, B., Stӧckle, C. O., Tardieu, F., Thomison, P. R., Timlin, D. J., Vyn, T. J., Wallach, D., Yang, H. S. and Tollenaar, M. (2014) Predicting maize phenology: intercomparison of functions for developmental response to temperature. Agronomy Journal, 106 6: 2087-2097. doi:10.2134/agronj14.0200

Author Kumudini, S.
Andrade, F. H.
Boote, K. J.
Brown, G. A.
Dzotsi, K. A.
Edmeades, G. O.
Gocken, T.
Goodwin, M.
Halter, A. L.
Hammer, G. L.
Hatfield, J. L.
Jones, J. W.
Kemanian, A. R.
Kim, S.-H.
Kiniry, J.
Lizaso, J. I.
Nendel, C.
Nielsen, R. L.
Parent, B.
Stӧckle, C. O.
Tardieu, F.
Thomison, P. R.
Timlin, D. J.
Vyn, T. J.
Wallach, D.
Yang, H. S.
Tollenaar, M.
Title Predicting maize phenology: intercomparison of functions for developmental response to temperature
Journal name Agronomy Journal   Check publisher's open access policy
ISSN 1435-0645
Publication date 2014-11-01
Year available 2014
Sub-type Article (original research)
DOI 10.2134/agronj14.0200
Open Access Status
Volume 106
Issue 6
Start page 2087
End page 2097
Total pages 11
Place of publication Madison, WI, United States
Publisher American Society of Agronomy
Collection year 2015
Language eng
Formatted abstract
Accurate prediction of phenological development in maize (Zea mays L.) is fundamental to determining crop adaptation and yield potential. A number of thermal functions are used in crop models, but their relative precision in predicting maize development has not been quantified. The objectives of this study were (i) to evaluate the precision of eight thermal functions, (ii) to assess the effects of source data on the ability to differentiate among thermal functions, and (iii) to attribute the precision of thermal functions to their response across various temperature ranges. Data sets used in this study represent >1000 distinct maize hybrids, >50 geographic locations, and multiple planting dates and years. Thermal functions and calendar days were evaluated and grouped based on their temperature response and derivation as empirical linear, empirical nonlinear, and process-based functions. Precision in predicting phase durations from planting to anthesis or silking and from silking to physiological maturity was evaluated. Large data sets enabled increased differentiation of thermal functions, even when smaller data sets contained orthogonal, multi-location and -year data. At the highest level of differentiation, precision of thermal functions was in the order calendar days < empirical linear < process based < empirical nonlinear. Precision was associated with relatively low temperature sensitivity across the 10 to 26°C range. In contrast to other thermal functions, process-based functions were derived using supra-optimal temperatures, and consequently, they may better represent the developmental response of maize to supra-optimal temperatures. Supra-optimal temperatures could be more prevalent under future climate-change scenarios, but data sets in this study contained few data in that range.
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Queensland Alliance for Agriculture and Food Innovation
Official 2015 Collection
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Citation counts: TR Web of Science Citation Count  Cited 6 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 9 times in Scopus Article | Citations
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