Casting light on the architecture of crop yield

Crop canopy architecture is a central component of yield. The arrangement of leaves in three-dimensional space defines the efficiency of absorption of radiation and its conversion into dry matter at the canopy level. The description of architecture is normally associated with light since the optimal distribution of light is associated with that of other essential components such as nitrogen and pigments. However, architecture has been influenced by a number of other unrelated processes through breeding and selection that may have acted independently or even against light use efficiency. This review attempts to provide a broad view and interpretation of canopy architectural properties and the factors affecting crop architecture starting with evolution, domestication, climatic conditions and cultivation patterns, predominantly focusing on field grown agricultural crops. Using examples of modelling with a virtual canopy, we will discuss how architectural traits affect light interception and photosynthesis. Finally, we will discuss the future of architectural research: the concept of the ideal plant type (the ideotype) and which features we can expect to see, as well as the social constraints that may govern future crop architecture

Automated recovery of 3D models of plant shoots from multiple colour images

Increased adoption of the systems approach to biological research has focussed attention on the use of quantitative models of biological objects. This includes a need for realistic 3D representations of plant shoots for quantification and modelling. Previous limitations in single or multi-view stereo algorithms have led to a reliance on volumetric methods or expensive hardware to record plant structure. We present a fully automatic approach to image-based 3D plant reconstruction that can be achieved using a single low-cost camera. The reconstructed plants are represented as a series of small planar sections that together model the more complex architecture of the leaf surfaces. The boundary of each leaf patch is refined using the level set method, optimising the model based on image information, curvature constraints and the position of neighbouring surfaces. The reconstruction process makes few assumptions about the nature of the plant material being reconstructed, and as such is applicable to a wide variety of plant species and topologies, and can be extended to canopy-scale imaging. We demonstrate the effectiveness of our approach on datasets of wheat and rice plants, as well as a novel virtual dataset that allows us to compute quantitative measures of reconstruction accuracy. The output is a 3D mesh structure that is suitable for modelling applications, in a format that can be imported in the majority of 3D graphics and software packages

Image-based 3D canopy reconstruction to determine potential productivity in complex multi-species crop systems

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 characterisation of the light environment. Different row layouts of an intercrop consisting of Bambara groundnut (Vigna subterranea (L.) Verdc.) 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 stereocameras, 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 was 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 multispecies cropping systems; enables the quantification of dynamic physiological differences between crops grown as monoculture and those within intercrops or; enables the prediction of new productive combinations of previously untested crops

A canopy conundrum: can wind-induced movement help to increase crop productivity by relieving photosynthetic limitations?

Wind-induced movement is a ubiquitous occurrence for all plants grown in natural or agricultural settings and in the context of high, damaging wind speeds it has been well studied. However, the impact of lower wind speeds (that do not cause any damage) on mode of movement, light transmission and photosynthetic properties has, surprisingly, not been fully explored. This is likely to be influenced by biomechanical properties and architectural features of the plant and canopy. A limited number of eco-physiological studies have indicated that movement in wind has the potential to alter light distribution within canopies, improving canopy productivity by relieving photosynthetic limitations. Given the current interest in canopy photosynthesis is timely to consider such movement in terms of crop yield progress. This opinion article sets out the background to wind-induced crop movement and argues that plant biomechanical properties may have a role in the optimisation of whole canopy photosynthesis via established physiological processes. We discuss how this could be achieved using canopy models

Does canopy angle influence radiation use efficiency of sugar beet?

Sugar beet varieties differ greatly in their canopy architecture and can be classified into canopy types according to their petiole angle. Leaf angle is one of the key factors which determines the efficiency with which plant canopies utilise incident and absorbed light for photosynthesis. Sugar beet yield is strongly correlated with accumulated intercepted light but the impact of canopy angle on light interception, biomass accumulation and sugar yield has not been explored. This study aims to analyse these relationships and also to determine if varieties can be selected according to their canopy types for high radiation use efficiency (RUE) and yields. Field trials were conducted with four varieties in 2019 (one upright, one prostrate and two intermediate canopy types) and six varieties in 2021 (two each of upright, intermediate, and prostrate) as well as one alternate sowing treatment (upright and prostrate in alternate rows). Varietal differences in petiole angle were stable across the season in 2019 and consistent between canopy closure and final harvest in 2021. The upright canopy type had a lower maximum canopy cover modelled from canopy expansion curves in both years. The upright canopy type was also slower to achieve canopy closure in 2019 and had a lower LAI at canopy closure in both years. There was a linear relationship between accumulated intercepted radiation and total plant biomass across all canopy types. The intermediate canopy types had the highest RUE in 2019 and highest sugar yield in both years. The upright canopy types had the highest RUE when harvested later in 2021, possibly due to the upright canopy type being better suited to intercept and utilise sunlight during the winter months when the sun angle is lower in the sky. The root to shoot ratio was greater in the high yielding intermediate variety suggesting that, in addition to RUE, biomass partitioning is an important determinant of sugar yield. The results from this study will aid in the selection of varieties to improve sugar beet yields. Whilst canopy angle is an important contributing factor to RUE and yield in sugar beet, other factors, such as leaf level photosynthesis and biomass partitioning are also important

Recovering Wind-induced Plant motion in Dense Field Environments via Deep Learning and Multiple Object Tracking

Understanding the relationships between local environmental conditions and plant structure and function is critical for both fundamental science and for improving the performance of crops in field settings. Wind-induced plant motion is important in most agricultural systems, yet the complexity of the field environment means that it remained understudied. Despite the ready availability of image sequences showing plant motion, the cultivation of crop plants in dense field stands makes it difficult to detect features and characterize their general movement traits. Here, we present a robust method for characterizing motion in field-grown wheat plants (Triticum aestivum) from time-ordered sequences of red, green and blue (RGB) images. A series of crops and augmentations was applied to a dataset of 290 collected and annotated images of ear tips to increase variation and resolution when training a convolutional neural network. This approach enables wheat ears to be detected in the field without the need for camera calibration or a fixed imaging position. Videos of wheat plants moving in the wind were also collected and split into their component frames. Ear tips were detected using the trained network, then tracked between frames using a probabilistic tracking algorithm to approximate movement. These data can be used to characterize key movement traits, such as periodicity, and obtain more detailed static plant properties to assess plant structure and function in the field. Automated data extraction may be possible for informing lodging models, breeding programmes and linking movement properties to canopy light distributions and dynamic light fluctuation

Water use efficiency responses to fluctuating soil water availability in contrasting commercial sugar beet varieties

Many areas of sugar beet production will face hotter and drier summers as the climate changes. There has been much research on drought tolerance in sugar beet but water use ef!ciency (WUE) has been less of a focus. An experiment was undertaken to examine how "uctuating soil water de!cits effect WUE from the leaf to the crop level and identify if sugar beet acclimates to water de!cits to increase WUE in the longer term. Two commercial sugar beet varieties with contrasting upright and prostrate canopies were examined to identify if WUE differs due to contrasting canopy architecture. The sugar beet were grown under four different irrigation regimes (fully irrigated, single drought, double drought and continually water limited) in large 610 L soil boxes in an open ended polytunnel. Measurements of leaf gas exchange, chlorophyll "uorescence and relative water content (RWC) were regularly undertaken and stomatal density, sugar and biomass yields and the associated WUE, SLW and D13C were assessed. The results showed that water de!cits generally increase intrinsic (WUE) and dry matter (WUE ) water use i D Mef!ciency but reduce yield. Sugar beet recovered fully after severe water de!cits, as assessed by leaf gas exchange and chlorophyll "uorescence parameters and, except for reducing canopy size, showed no other acclimation to drought, and therefore no changes in WUE or drought avoidance. Spot measurements of WUEi, showed no differences between the two varieties but the prostrate variety showed lower D13C values, and traits associated with more water conservative phenotypes of a lower stomatal density and greater leaf RWC. Leaf chlorophyll content was affected by water de!cit but the relationship with WUE was unclear. The difference in D13C values between the two varieties suggests traits associated with greater WUEimay be linked to canopy architecture

A canopy conundrum: can wind-induced movement help to increase crop productivity by relieving photosynthetic limitations?

Wind-induced movement is a ubiquitous occurrence for all plants grown in natural or agricultural settings and in the context of high, damaging wind speeds it has been well studied. However, the impact of lower wind speeds (that do not cause any damage) on mode of movement, light transmission and photosynthetic properties has, surprisingly, not been fully explored. This is likely to be influenced by biomechanical properties and architectural features of the plant and canopy. A limited number of eco-physiological studies have indicated that movement in wind has the potential to alter light distribution within canopies, improving canopy productivity by relieving photosynthetic limitations. Given the current interest in canopy photosynthesis is timely to consider such movement in terms of crop yield progress. This opinion article sets out the background to wind-induced crop movement and argues that plant biomechanical properties may have a role in the optimisation of whole canopy photosynthesis via established physiological processes. We discuss how this could be achieved using canopy models

Approaches to three-dimensional reconstruction of plant shoot topology and geometry

There are currently 805 million people classified as chronically undernourished, and yet the World’s population is still increasing. At the same time, global warming is causing more frequent and severe flooding and drought, thus destroying crops and reducing the amount of land available for agriculture. Recent studies show that without crop climate adaption, crop productivity will deteriorate. With access to 3D models of real plants it is possible to acquire detailed morphological and gross developmental data that can be used to study their ecophysiology, leading to an increase in crop yield and stability across hostile and changing environments. Here we review approaches to the reconstruction of 3D models of plant shoots from image data, consider current applications in plant and crop science, and identify remaining challenges. We conclude that although phenotyping is receiving an increasing amount of attention – particularly from computer vision researchers – and numerous vision approaches have been proposed, it still remains a highly interactive process. An automated system capable of producing 3D models of plants would significantly aid phenotyping practice, increasing accuracy and repeatability of measurements

A patch-based approach to 3D plant shoot phenotyping

The emerging discipline of plant phenomics aims to measure key plant characteristics, or traits, though as yet the set of plant traits that should be measured by automated systems is not well defined. Methods capable of recovering generic representations of the 3D structure of plant shoots from images would provide a key technology underpinning quantification of a wide range of current and future physiological and morphological traits. We present a fully automatic approach to image-based 3D plant reconstruction which represents plants as series of small planar sections that together model the complex architecture of leaf surfaces. The initial boundary of each leaf patch is refined using a level set method, optimising the model based on image information, curvature constraints and the position of neighbouring surfaces. The reconstruction process makes few assumptions about the nature of the plant material being reconstructed. As such it is applicable to a wide variety of plant species and topologies, and can be extended to canopy-scale imaging. We demonstrate the effectiveness of our approach on real images of wheat and rice plants, an artificial plant with challenging architecture, as well as a novel virtual dataset that allows us to compute distance measures of reconstruction accuracy. We also illustrate the method’s potential to support the identification of individual leaves, and so the phenotyping of plant shoots, using a spectral clustering approach