A Model to Predict Diurnal Pollen Shed in Maize

Abstract

We have developed a mathematical model to predict the diurnal pattern of maize (Zea mays L.) pollen shed on the basis of local meteorological conditions. Our goal is to improve simulations of maize pollen dispersion that have typically released pollen at a constant rate in contrast with measurements of pollen shed that show diurnal variation in the rate of shed. Measurements coupling pollen shed and local meteorological variables were made during controlled experiments and a 2004 fi eld experiment to examine the infl uence of meteorological conditions on pollen shed. From these data, a model was developed to predict the diurnal pattern of pollen shed as a function of vapor pressure defi cit, solar radiation, temperature, and the amount of pollen remaining to be shed. The model was validated by predicting the rate of pollen shed, normalized by the daily total of pollen shed, that occurred hourly for days during a 2003 fi eld study (RMSE = 0.061 h -1 ) and results from van Hout et al. (2008; RMSE = 0.089 h -1 ). The model captured the general trend of pollen shed and predicted the time of peak shed within an hour of the measured peak on most days. The model, however, tended to underpredict the magnitude of the normalized peak rate of shed and did not account for secondary peaks in pollen shed that were occasionally observed. Thus, future model refi nements will depend on identifying additional biological or environmental factors that impact the instantaneous rate of pollen shed.Abbreviations: FoD, fraction of drying; LDT, local daylight time; LoR, length of recruitment time; RoS, rate of shed; VPD, vapor pressure defi cit; VPDT, accumulated vapor pressure defi cit over time.

Maize pollen deposition in relation to distance from the nearest pollen source under common cultivation - results of 10 years of monitoring (2001 to 2010)

“…As described before, the results of the regression analysis show a relatively wide confidence interval for individual values (see Figure 3, Table 3). This can be expected, as our data include variability in pollen production, release, and dispersal resulting from different relative positions of the traps to the main wind direction, and other factors such as field size, plant density, maize variety, growing conditions, agricultural management, and weather conditions [29,45].…”

“…In Germany, maize flowers in summer (July to August) and pollen release is favored by warm and windy (i.e., drying and turbulent) weather conditions during the daytime [29,45,59,79,80]. In turbulent wind conditions, pollen grains are transported higher above the ground and are dispersed over further distances than they are under nonturbulent conditions [29,32,39,40,42,44,59,80].…”

“…For example, turbulence, heat-induced up-drifts, and the stronger winds that typically occur during the maize flowering period in summer can enhance the release and dispersal of maize pollen. These factors correlate with the warm, windy, dry weather conditions during the daytime that trigger the maize pollen release [29,31,32,39,40,44,45].…”

Updated Empirical Model of Genetically Modified Maize Grain Production Practices to Achieve European Union Labeling Thresholds

“…Among all available approaches, physical-based models are arguably the most accurate, as they use a theoretical model of aerial particle dispersal, which is the main process implied in PMGF (Dupont et al, 2006;Jarosz et al, 2004). However, they are also extremely laborious to develop, due to the need to model each biological and physical process (Marceau et al, , 2012Viner et al, 2010;Chamecki et al, 2011). Recently, the biophysical approach was validated with success on individual experimental fields by Dietiker et al (2011) and Astini et al (2009) for hybrid and seed production fields, respectively.…”

Seasonal variation in diurnal atmospheric grass pollen concentration profiles

“…The time of day that pollen concentrations peak may thus be of greater importance to the allergy sufferer than the daily average concentrations typically made available to the public (Käpylä, 1981). A better understanding of what drives variation in diurnal grass pollen profiles may lead to improved advice on how allergy sufferers may best avoid exposure, and would furthermore help to improve the accuracy of pollen dispersion models (Viner et al, 2010).…”