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A biomechanical model for maize root lodging

Brune, PhilipF., Baumgarten, Andy, McKay, SteveJ., Technow, Frank, Podhiny, JohnJ.
Plant and soil 2018 v.422 no.1-2 pp. 397-408
Zea mays, biomechanics, corn, corn ears, crop yield, data collection, environmental factors, field experimentation, leaf area, leaves, lodging, lodging resistance, model validation, models, phenotype, plant height, rooting, roots, soil strength, wind speed
BACKGROUND AND AIMS: Root lodging is a structural failure of the root-soil anchorage system in a plant that adversely affects its yield. It is a complex phenomenon that depends strongly on both crop genetics and environmental factors. An accurate biomechanical model to predict root lodging would disentangle the component factors and improve development of lodging resistant plants, thereby reducing the constraint of root lodging on crop yields. METHODS: We developed a biomechanical model that employs an engineering safety factor approach to quantify root lodging resistance as the ratio of anchorage supply and wind demand. We also conducted field experiments to parametrize the model for a sensitivity analysis and validate the model for predictive accuracy. RESULTS: The sensitivity analysis revealed primary, secondary, and tertiary factors for root lodging. The primary factors consisted of root angle, structural rooting depth, soil strength, and wind speed. The secondary factors were plant height, ear height, leaf area, stalk taper, ear mass, and leaf drag. Tertiary factors were stalk diameter and leaf number. The validation analysis found the model predictions compared well with data collected from three natural lodging events, with a goodness-of-fit of 0.58. CONCLUSIONS: The model effectively described a collection of natural lodging events, giving confidence in its predictive accuracy as well as the relative phenotypic and envirotypic influence factors determined in the sensitivity analysis. There are significant opportunities for model improvement, perhaps most significantly in the phenomenological understanding of the physical process.