Determination of a plant population density threshold for optimizing cotton lint yield: A synthesis
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© 2018 Elsevier B.V. Technology fees associated with modern cotton cultivars have increased seed costs considerably, giving producers the impetus to reduce plant population density, where possible. Most recent studies on cotton population density, conducted across diverse environments, report similar patterns of crop response: decreases in lint yield only at very low densities, with generally consistent yield across all higher densities. But no work had been done to bring the literature together, quantitively synthesizing the yield data collectively, to better pinpoint a population density threshold. And, notably, little had been reported on the effects of population density in lower-yielding dryland environments. Quantitatively synthesizing population density datasets from the literature, including our own dryland data, was the objective of this research. The dryland data showed that lint yield and biomass partitioning were not affected by population density, similar to higher-yielding environments over the same range in density. Following normalization of all lint yield data (literature and dryland datasets), a breakpoint in population density at 35,000 plants ha−1 was identified, which can be interpreted as the minimum plant density at which yield may be optimized. This rate is lower than the common density recommendation of 81,000 plants ha−1 and substantially lower than the risk-averse rates at which many producers plant (129,000 seeds ha−1 or greater). The analysis showed that yield will decline precipitously below 35,000 plants ha−1, exposing the enormous risk to cotton producers in approaching this low density, particularly if significant seed or plant loss is expected. However, the analysis suggests that excessive over-seeding may be occurring in many cases, resulting in economic losses to producers. The analysis also provides guidance on a threshold for producers facing replanting decisions.
author list (cited authors)
Adams, C., Thapa, S., & Kimura, E.