Imaging plants dynamics in heterogenic environments.
ABSTRACT Noninvasive imaging sensors and computer vision approaches are key technologies to quantify plant structure, physiological status, and performance. Today, imaging sensors exploit a wide range of the electromagnetic spectrum, and they can be deployed to measure a growing number of traits, also in heterogenic environments. Recent advances include the possibility to acquire high-resolution spectra by imaging spectroscopy and classify signatures that might be informative of plant development, nutrition, health, and disease. Three-dimensional (3D) reconstruction of surfaces and volume is of particular interest, enabling functional and mechanistic analyses. While taking pictures is relatively easy, quantitative interpretation often remains challenging and requires integrating knowledge of sensor physics, image analysis, and complex traits characterizing plant phenotypes.
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ABSTRACT: PET provides in vivo molecular and functional imaging capability that is crucial to studying the interaction of plant with changing environment at the whole-plant level. We have developed a dedicated plant PET imager that features high spatial resolution, housed in a fully controlled environment provided by a plant growth chamber (PGC). The system currently contains two types of detector modules: 84 microPET R4 block detectors with 2.2 mm crystals to provide a large detecting area; and 32 Inveon block detectors with 1.5 mm crystals to provide higher spatial resolution. Outputs of the four microPET block detectors in a modular housing are concatenated by a custom printed circuit board to match the output characteristics of an Inveon detector. All the detectors are read out by QuickSilver electronics. The detector modules are configured to full rings with a 15 cm diameter trans-axial field of view (FOV) for dynamic tomographic imaging of small plants. Potentially, the Inveon detectors can be reconfigured to quarter-rings to get a 25 cm FOV using step-and-shoot motion. The imager contains 2 linear stages to position detectors at different heights for multi-bed scanning, and 2 rotation stages to collect coincidence events from all angles. The PET system has been built and integrated into the PGC. The system has a typical energy resolution of 15% for Inveon blocks and 24% for R4 blocks; timing resolution of 1.8 ns; and sensitivity of 1.3%,1.4%,3.0% measured at center of FOV, 5 cm off to R4 half-ring and 5 cm off to Inveon half-ring, respectively(with a 350-650 KeV energy and 3.1 ns timing window). System spatial resolution is similar to that of commercial microPET sytems, with 1.25 mm rod sources in the micro-Derenzo phantom resolved using ML-EM algorithm. Preliminary imaging experiments using different plants labeled with 11C-CO2 produced high-quality dynamic PET images.Physics in Medicine and Biology 01/2014; 59(19). · 2.70 Impact Factor
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ABSTRACT: It is over 10 years since the genome sequence of the first crop was published. Since then, the number of crop genomes sequenced each year has increased steadily. The amazing pace at which genome sequences are becoming available is largely due to the improvement in sequencing technologies both in terms of cost and speed. Modern sequencing technologies allow the sequencing of multiple cultivars of smaller crop genomes at a reasonable cost. Though many of the published genomes are considered incomplete, they nevertheless have proved a valuable tool to understand important crop traits such as fruit ripening, grain traits and flowering time adaptation.Current opinion in biotechnology 04/2014; 26C:31-37. · 7.82 Impact Factor
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ABSTRACT: Light curtain arrays (LC), a recently introduced phenotyping method, yield a binary data matrix from which a shoot silhouette is reconstructed. We addressed the accuracy and applicability of LC in assessing leaf area and maximum height (base to the highest leaf tip) in a phenotyping platform. LC were integrated to an automated routine for positioning, allowing in situ measurements. Two dicotyledonous (rapeseed, tomato) and two monocotyledonous (maize, barley) species with contrasting shoot architecture were investigated. To evaluate if averaging multiple view angles helps in resolving self-overlaps, we acquired a data set by rotating plants every 10[degree sign] for 170[degree sign]. To test how rapid these measurements can be without loss of information, we evaluated nine scanning speeds. Leaf area of overlapping plants was also estimated to assess the possibility to scale this method for plant stands. The relation between measured and calculated maximum height was linear and nearly the same for all species. Linear relations were also found between plant leaf area and calculated pixel area. However, the regression slope was different between monocotyledonous and dicotyledonous species. Increasing the scanning speed stepwise from 0.9 to 23.4 m s-1 did not affect the estimation of maximum height. Instead, the calculated pixel area was inversely proportional to scanning speed. The estimation of plant leaf area by means of calculated pixel area became more accurate by averaging consecutive silhouettes and/or increasing the angle between them. Simulations showed that decreasing plant distance gradually from 20 to 0 cm, led to underestimation of plant leaf area owing to overlaps. This underestimation was more important for large plants of dicotyledonous species and for small plants of monocotyledonous ones. LC offer an accurate estimation of plant leaf area and maximum height, while the number of consecutive silhouettes that needs to be averaged is species-dependent. A constant scanning speed is important for leaf area estimations by using LC. Simulations of the effect of varying plant spacing gave promising results for method application in sets of partly overlapping plants, which applies also to field conditions during and after canopy closure for crops sown in rows.Plant Methods 04/2014; 10(1):9. · 2.67 Impact Factor