Improving Agarwood (Aquilaria malaccensis Lamk.) Plantlet Formation Using Various Types and Concentrations of Auxins

Aquilaria malaccensis Lamk. is one of the most widespread agarwood-producing plants that face extinction due to overexploitation. Agarwood propagation using in vitro culture techniques is capable of producing large quantities of plants in a shorter time and free from pests and diseases. Therefore, this study was conducted to analyze the effect of auxins type and concentration on agarwood plantlet formation using a split-plot design. The main plot was the type of auxin which included IAA, IBA and NAA, while the subplot was the concentration used which consisted of 0; 5; 10; 15 and 20 µM. The variable observed was agarwood plantlet formation with parameters measured including the number of shoots and leaves, plant height, and number of roots. The results showed that the formation of agarwood plantlets was controlled by the type, concentration, and interaction between the type and concentration of auxin. Furthermore, explants cultured on Murashige Skoog (MS) medium supplemented with 10 µM IBA produced the highest number of shoots (3.39 shoots explant-1) and leaves (7.25 leaves explants-1), while the addition of 10 uM NAA resulted in the highest number of roots (2.52 roots explant-1). This is the first time a study is conducted to evaluate the effect of type and concentration of auxins on agarwood plantlet formation. The production of high-quality shoots and plantlets increased agarwood germplasm availability to prevent extinction and support sustainable production

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

Active Vision and Surface Reconstruction for 3D Plant Shoot Modelling

Plant phenotyping is the quantitative description of a plant’s physiological, biochemical and anatomical status which can be used in trait selection and helps to provide mechanisms to link underlying genetics with yield. Here, an active vision- based pipeline is presented which aims to contribute to reducing the bottleneck associated with phenotyping of architectural traits. The pipeline provides a fully automated response to photometric data acquisition and the recovery of three-dimensional (3D) models of plants without the dependency of botanical expertise, whilst ensuring a non-intrusive and non-destructive approach. Access to complete and accurate 3D models of plants supports computation of a wide variety of structural measurements. An Active Vision Cell (AVC) consisting of a camera-mounted robot arm plus combined software interface and a novel surface reconstruction algorithm is proposed. This pipeline provides a robust, flexible and accurate method for automating the 3D reconstruction of plants. The reconstruction algorithm can reduce noise and provides a promising and extendable framework for high throughput phenotyping, improving current state-of-the-art methods. Furthermore, the pipeline can be applied to any plant species or form due to the application of an active vision framework combined with the automatic selection of key parameters for surface reconstruction

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

High throughput procedure utilising chlorophyll fluorescence imaging to phenotype dynamic photosynthesis and photoprotection in leaves under controlled gaseous conditions

© 2019 The Author(s). Background: As yields of major crops such as wheat (T. aestivum) have begun to plateau in recent years, there is growing pressure to efficiently phenotype large populations for traits associated with genetic advancement in yield. Photosynthesis encompasses a range of steady state and dynamic traits that are key targets for raising Radiation Use Efficiency (RUE), biomass production and grain yield in crops. Traditional methodologies to assess the full range of responses of photosynthesis, such a leaf gas exchange, are slow and limited to one leaf (or part of a leaf) per instrument. Due to constraints imposed by time, equipment and plant size, photosynthetic data is often collected at one or two phenological stages and in response to limited environmental conditions. Results: Here we describe a high throughput procedure utilising chlorophyll fluorescence imaging to phenotype dynamic photosynthesis and photoprotection in excised leaves under controlled gaseous conditions. When measured throughout the day, no significant differences (P > 0.081) were observed between the responses of excised and intact leaves. Using excised leaves, the response of three cultivars of T. aestivum to a user - defined dynamic lighting regime was examined. Cultivar specific differences were observed for maximum PSII efficiency (F v′/F m′ - P 130 μmol m-2 s-1 photosynthetic photon flux density (PPFD). Conclusions: Here we demonstrate the development of a high-throughput (> 500 samples day-1) method for phenotyping photosynthetic and photo-protective parameters in a dynamic light environment. The technique exploits chlorophyll fluorescence imaging in a specifically designed chamber, enabling controlled gaseous environment around leaf sections. In addition, we have demonstrated that leaf sections do not different from intact plant material even > 3 h after sampling, thus enabling transportation of material of interest from the field to this laboratory based platform. The methodologies described here allow rapid, custom screening of field material for variation in photosynthetic processes

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

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

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

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