Abstract
Background and Aims Intercropping systems contain two or more species simultaneously in close proximity. Due to contrasting features of the component crops, quantification of the light environment and photosynthetic productivity is extremely difficult. However it is an essential component of productivity. Here, a low-tech but high-resolution method is presented that can be applied to single- and multi-species cropping systems to facilitate characterization of the light environment. Different row layouts of an intercrop consisting of Bambara groundnut (Vigna subterranea) and proso millet (Panicum miliaceum) have been used as an example and the new opportunities presented by this approach have been analysed.Methods Three-dimensional plant reconstruction, based on stereo cameras, combined with ray tracing was implemented to explore the light environment within the Bambara groundnut–proso millet intercropping system and associated monocrops. Gas exchange data were used to predict the total carbon gain of each component crop.Key Results The shading influence of the tall proso millet on the shorter Bambara groundnut results in a reduction in total canopy light interception and carbon gain. However, the increased leaf area index (LAI) of proso millet, higher photosynthetic potential due to the C4 pathway and sub-optimal photosynthetic acclimation of Bambara groundnut to shade means that increasing the number of rows of millet will lead to greater light interception and carbon gain per unit ground area, despite Bambara groundnut intercepting more light per unit leaf area.Conclusions Three-dimensional reconstruction combined with ray tracing provides a novel, accurate method of exploring the light environment within an intercrop that does not require difficult measurements of light interception and data-intensive manual reconstruction, especially for such systems with inherently high spatial possibilities. It provides new opportunities for calculating potential productivity within multi-species cropping systems, enables the quantification of dynamic physiological differences between crops grown as monoculture and those within intercrops, and enables the prediction of new productive combinations of previously untested crops.
Highlights
Intercropping systems contain two or more species simultaneously and in close proximity for at least part of their growth season
Without difficult and inaccurate manual measurements, we are able to (1) define structural and photosynthetic features throughout the vertical profile of the canopies; (2) separate each component of the intercrop by assigning identification codes to the reconstructions, and combine them when required; (3) use different methods to visualize the shading influence of a tall component crop on a shorter crop; (4) accurately predict total light interception and include gas exchange data as a means to predict productivity within each of the systems; (5) acquire light data with high spatial and temporal resolution that can be used for dynamic photosynthesis measurements rather than integrated averages; and (6) make predictions for multiple different locations and treatments via modelling
We show that any intercropping treatment that favours more rows of proso millet, or a taller component crop/component with higher leaf area, will have a greater total light interception, despite the shading influence and reduced interception by the Bambara groundnut component
Summary
Intercropping systems contain two or more species simultaneously and in close proximity for at least part of their growth season. Willey, 1979, 1990; Vandermeer, 1989; Keating and Carberry, 1993; Dhima et al, 2007; Mucheru-Muna et al, 2010; Lithourgidis et al, 2011) Often, growth resources such as light, water and nutrients can be more efficiently exploited within the intercrop system as a result of differences in the growth and competitive ability of the component crops (Midmore, 1993; Tsubo et al, 2001). Due to contrasting features of the component crops, quantification of the light environment and photosynthetic productivity is extremely difficult. Gas exchange data were used to predict the total carbon gain of each component crop
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