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

Authors: KUMUDINI, SARATHA - Monsanto Corporation; TOLLENAAR, MATTHIJS - Monsanto Corporation; ANDRADE, FERNANDO - National University Of Mar Del Plata; BOOTE, KENNETH - University Of Florida; BROWN, G - Breaking Ground; DZOTSI, K - University Of Florida; EDMEADES, G - Retired Non ARS Employee; GOCKEN, T - Monsanto Corporation; GOODWIN, M - Monsanto Corporation; HALTER, A - Dupont Pioneer Hi-Bred; Hatfield, Jerry; JONES, JAMES - University Of Florida; KEMANIAN, ARMEN - Pennsylvania State University; NENDEL, CLAUS - Institute Of Landscape Systems Analysis, Leibniz Centre For Agricultural Landscape Research; NIELSEN, ROBERT - Purdue University; PARENT, B - Inland Northwest Research Alliance, Inra; STOCKLE, CLAUDIO - Washington State University; TARDIEU, F - Inland Northwest Research Alliance, Inra; THOMISON, PETER - The Ohio State University; Timlin, Dennis; WALLACH, DANIEL - Inland Northwest Research Alliance, Inra; YANG, HAISHUN - University Of Nebraska

Submitted to: Agronomy Journal
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 6/18/2014
Publication Date: 10/29/2014
Citation: Kumudini, S., Tollenaar, M., Andrade, F., Boote, K., Brown, G.A., Dzotsi, K.A., Edmeades, G.O., Gocken, T., Goodwin, M., Halter, A.L., Hatfield, J.L., Jones, J.W., Kemanian, A.R., Nendel, C., Nielsen, R.L., Parent, B., Stockle, C.O., Tardieu, F., Thomison, P., Timlin, D.J., Wallach, D., Yang, H. 2014. Predicting maize phenology: Intercomparison of functions for developmental response to temperature. Agronomy Journal. 106(6):2087-2097.

Interpretive Summary: Crop development is described by its progression through the different phenological stages. The rate at which a crop progresses through these stages is defined by its response and sensitivity to the environment and in particular, temperature. Phenological development has been related to different expressions of temperature throughout the growing season; however, there has been no comparisons of the different descriptions of thermal time or calendar time on phenological development in corn. We undertook this study to compare different temperature indices using a data set compiled from a wide range of locations throughout the world. Temperature effects on phenological development of corn revealed that the most precise relationship was one which the effect of high temperatures showed a decrease in growth rate showing that as the temperature increases the rate of development could decrease. Improving our ability to estimate how quickly a plant will grow under warm temperatures will help us cope with climate change. This information will be of value to scientists and especially corn breeders trying to develop new varieties in a warm environment.

Technical Abstract: Accurate prediction of phenological development in maize 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 to evaluate the precision of thermal functions and to assess the effects of the quantity and quality of datasets on the ability to differentiate among thermal functions. Datasets used in this study represent >1000 distinct maize hybrids and >50 unique geographies, including datasets with multiple planting dates. Eight thermal functions and calendar days were evaluated and thermal functions were classified according to their temperature response and derivation as empirical linear, empirical non-linear, and process-based functions. The precision in predicting phase durations from planting to anthesis/silking and from silking to physiological maturity was evaluated. Large datasets enabled increased differentiation of thermal functions, even when smaller datasets contained orthogonal, multi-location/year data. At the highest level of differentiation, precision of thermal functions was in the order calendar days < empirical linear < process-based < empirical non-linear. Precision of thermal functions was associated with relatively low temperature sensitivity across the 10-26oC range. Neither the datasets used to derive empirical functions, nor the evaluation datasets reported herein, contained data in the supra-optimal temperature range. Considering the increased likelihood of supra-optimal temperatures under future climate change, it is put forward that thermal functions should be informed by process-based response functions when quantifying the thermal response of maize to future climate change.