The State of the Art in Root System Architecture Image Analysis Using Artificial Intelligence: A Review

Roots are essential for acquiring water and nutrients to sustain and support plant growth and anchorage. However, they have been studied less than the aboveground traits in phenotyping and plant breeding until recent decades. In modern times, root properties such as morphology and root system architecture (RSA) have been recognized as increasingly important traits for creating more and higher quality food in the “Second Green Revolution”. To address the paucity in RSA and other root research, new technologies are being investigated to fill the increasing demand to improve plants via root traits and overcome currently stagnated genetic progress in stable yields. Artificial intelligence (AI) is now a cutting-edge technology proving to be highly successful in many applications, such as crop science and genetic research to improve crop traits. A burgeoning field in crop science is the application of AI to high-resolution imagery in analyses that aim to answer questions related to crops and to better and more speedily breed desired plant traits such as RSA into new cultivars. This review is a synopsis concerning the origins, applications, challenges, and future directions of RSA research regarding image analyses using AI

The holistic rhizosphere: integrating zones, processes, and semantics in the soil influenced by roots

Despite often being conceptualized as a thin layer of soil around roots, the rhizosphere is actually a dynamic system of interacting processes. Hiltner originally defined the rhizosphere as the soil influenced by plant roots. However, soil physicists, chemists, microbiologists, and plant physiologists have studied the rhizosphere independently, and therefore conceptualized the rhizosphere in different ways and using contrasting terminology. Rather than research-specific conceptions of the rhizosphere, the authors propose a holistic rhizosphere encapsulating the following components: microbial community gradients, macroorganisms, mucigel, volumes of soil structure modification, and depletion or accumulation zones of nutrients, water, root exudates, volatiles, and gases. These rhizosphere components are the result of dynamic processes and understanding the integration of these processes will be necessary for future contributions to rhizosphere science based upon interdisciplinary collaborations. In this review, current knowledge of the rhizosphere is synthesized using this holistic perspective with a focus on integrating traditionally separated rhizosphere studies. The temporal dynamics of rhizosphere activities will also be considered, from annual fine root turnover to diurnal fluctuations of water and nutrient uptake. The latest empirical and computational methods are discussed in the context of rhizosphere integration. Clarification of rhizosphere semantics, a holistic model of the rhizosphere, examples of integration of rhizosphere studies across disciplines, and review of the latest rhizosphere methods will empower rhizosphere scientists from different disciplines to engage in the interdisciplinary collaborations needed to break new ground in truly understanding the rhizosphere and to apply this knowledge for practical guidance

Unlocking biomarker discovery: Large scale application of aptamer proteomic technology for early detection of lung cancer

Lung cancer is the leading cause of cancer deaths, because ~84% of cases are diagnosed at an advanced stage. Worldwide in 2008, ~1.5 million people were diagnosed and ~1.3 million died – a survival rate unchanged since 1960. However, patients diagnosed at an early stage and have surgery experience an 86% overall 5-year survival. New diagnostics are therefore needed to identify lung cancer at this stage. Here we present the first large scale clinical use of aptamers to discover blood protein biomarkers in disease with our breakthrough proteomic technology. This multi-center case-control study was conducted in archived samples from 1,326 subjects from four independent studies of non-small cell lung cancer (NSCLC) in long-term tobacco-exposed populations. We measured >800 proteins in 15uL of serum, identified 44 candidate biomarkers, and developed a 12-protein panel that distinguished NSCLC from controls with 91% sensitivity and 84% specificity in a training set and 89% sensitivity and 83% specificity in a blinded, independent verification set. Performance was similar for early and late stage NSCLC. This is a significant advance in proteomics in an area of high clinical need

Shovelomics root traits assessed on the EURoot maize panel are highly heritable across environments but show low genotype-by-nitrogen interaction

Abstract The need for sustainable intensification of agriculture in the coming decades requires a reduction in nitrogen (N) fertilization. One opportunity to reduce N application rates without major losses in yield is breeding for nutrient efficient crops. A key parameter that influences nutrient uptake efficiency is the root system architecture (RSA). To explore the impact of N availability on RSA and to investigate the impact of the growth environment, a diverse set of 36 inbred dent maize lines crossed to the inbred flint line UH007 as a tester was evaluated for N-response over 2 years on three different sites. RSA was investigated by excavating and imaging of the root crowns followed by image analysis with REST software. Despite strong site and year effects, trait heritability was generally high. Root traits showing the greatest heritability (> 0.7) were the width of the root stock, indicative of the horizontal expansion, and the fill factor, a measure of the density of the root system. Heritabilities were in a similar range under high or low N application. Under N deficiency the root stock size decreased, the horizontal expansion decreased and the root stock became less dense. However, there was little differential response of the genotypes to low N availability. Thus, the assessed root traits were more constitutively expressed rather than showing genotype-specific plasticity to low N. In contrast, strong differences were observed for 'stay green' and silage yield, indicating that these highly heritable traits are good indicators for responsiveness to low N

Phenotyping Alfalfa (Medicago sativa L.) Root Structure Architecture via Integrating Confident Machine Learning with ResNet-18

Background: Root system architecture (RSA) is of growing interest in implementing plant improvements with belowground root traits. Modern computing technology applied to images offers new pathways forward to plant trait improvements and selection through RSA analysis (using images to discern/classify root types and traits). However, a major stumbling block to image-based RSA phenotyping is image label noise, which reduces the accuracies of models that take images as direct inputs. To address the label noise problem, this study utilized an artificial intelligence model capable of classifying the RSA of alfalfa (Medicago sativa L.) directly from images and coupled it with downstream label improvement methods. Images were compared with different model outputs with manual root classifications, and confident machine learning (CL) and reactive machine learning (RL) methods were tested to minimize the effects of subjective labeling to improve labeling and prediction accuracies. Results: The CL algorithm modestly improved the Random Forest model’s overall prediction accuracy of the Minnesota dataset (1%) while larger gains in accuracy were observed with the ResNet-18 model results. The ResNet-18 cross-population prediction accuracy was improved (~8% to 13%) with CL compared to the original/preprocessed datasets. Training and testing data combinations with the highest accuracies (86%) resulted from the CL- and/or RL-corrected datasets for predicting taproot RSAs. Similarly, the highest accuracies achieved for the intermediate RSA class resulted from corrected data combinations. The highest overall accuracy (~75%) using the ResNet-18 model involved CL on a pooled dataset containing images from both sample locations. Conclusions: ResNet-18 DNN prediction accuracies of alfalfa RSA image labels are increased when CL and RL are employed. By increasing the dataset to reduce overfitting while concurrently finding and correcting image label errors, it is demonstrated here that accuracy increases by as much as ~11% to 13% can be achieved with semi-automated, computer-assisted preprocessing and data cleaning (CL/RL)

The First Hour of Extra-galactic Data of the Sloan Digital Sky Survey Spectroscopic Commissioning: The Coma Cluster

On 26 May 1999, one of the Sloan Digital Sky Survey (SDSS) fiber-fed spectrographs saw astronomical first light. This was followed by the first spectroscopic commissioning run during the dark period of June 1999. We present here the first hour of extra-galactic spectroscopy taken during these early commissioning stages: an observation of the Coma cluster of galaxies. Our data samples the Southern part of this cluster, out to a radius of 1.5degrees and thus fully covers the NGC 4839 group. We outline in this paper the main characteristics of the SDSS spectroscopic systems and provide redshifts and spectral classifications for 196 Coma galaxies, of which 45 redshifts are new. For the 151 galaxies in common with the literature, we find excellent agreement between our redshift determinations and the published values. As part of our analysis, we have investigated four different spectral classification algorithms: spectral line strengths, a principal component decomposition, a wavelet analysis and the fitting of spectral synthesis models to the data. We find that a significant fraction (25%) of our observed Coma galaxies show signs of recent star-formation activity and that the velocity dispersion of these active galaxies (emission-line and post-starburst galaxies) is 30% larger than the absorption-line galaxies. We also find no active galaxies within the central (projected) 200 h-1 Kpc of the cluster. The spatial distribution of our Coma active galaxies is consistent with that found at higher redshift for the CNOC1 cluster survey. Beyond the core region, the fraction of bright active galaxies appears to rise slowly out to the virial radius and are randomly distributed within the cluster with no apparent correlation with the potential merger of the NGC 4839 group. [ABRIDGED]Comment: Accepted in AJ, 65 pages, 20 figures, 5 table

Observational and Dynamical Characterization of Main-Belt Comet P/2010 R2 (La Sagra)

We present observations of comet-like main-belt object P/2010 R2 (La Sagra) obtained by Pan-STARRS 1 and the Faulkes Telescope-North on Haleakala in Hawaii, the University of Hawaii 2.2 m, Gemini-North, and Keck I telescopes on Mauna Kea, the Danish 1.54 m telescope at La Silla, and the Isaac Newton Telescope on La Palma. An antisolar dust tail is observed from August 2010 through February 2011, while a dust trail aligned with the object's orbit plane is also observed from December 2010 through August 2011. Assuming typical phase darkening behavior, P/La Sagra is seen to increase in brightness by >1 mag between August 2010 and December 2010, suggesting that dust production is ongoing over this period. These results strongly suggest that the observed activity is cometary in nature (i.e., driven by the sublimation of volatile material), and that P/La Sagra is therefore the most recent main-belt comet to be discovered. We find an approximate absolute magnitude for the nucleus of H_R=17.9+/-0.2 mag, corresponding to a nucleus radius of ~0.7 km, assuming an albedo of p=0.05. Using optical spectroscopy, we find no evidence of sublimation products (i.e., gas emission), finding an upper limit CN production rate of Q_CN<6x10^23 mol/s, from which we infer an H2O production rate of Q_H2O<10^26 mol/s. Numerical simulations indicate that P/La Sagra is dynamically stable for >100 Myr, suggesting that it is likely native to its current location and that its composition is likely representative of other objects in the same region of the main belt, though the relatively close proximity of the 13:6 mean-motion resonance with Jupiter and the (3,-2,-1) three-body mean-motion resonance with Jupiter and Saturn mean that dynamical instability on larger timescales cannot be ruled out.Comment: 23 pages, 13 figures, accepted for publication in A

The Wide-field Infrared Survey Explorer (WISE): Mission Description and Initial On-orbit Performance

The all sky surveys done by the Palomar Observatory Schmidt, the European Southern Observatory Schmidt, and the United Kingdom Schmidt, the InfraRed Astronomical Satellite and the 2 Micron All Sky Survey have proven to be extremely useful tools for astronomy with value that lasts for decades. The Wide-field Infrared Survey Explorer is mapping the whole sky following its launch on 14 December 2009. WISE began surveying the sky on 14 Jan 2010 and completed its first full coverage of the sky on July 17. The survey will continue to cover the sky a second time until the cryogen is exhausted (anticipated in November 2010). WISE is achieving 5 sigma point source sensitivities better than 0.08, 0.11, 1 and 6 mJy in unconfused regions on the ecliptic in bands centered at wavelengths of 3.4, 4.6, 12 and 22 microns. Sensitivity improves toward the ecliptic poles due to denser coverage and lower zodiacal background. The angular resolution is 6.1, 6.4, 6.5 and 12.0 arc-seconds at 3.4, 4.6, 12 and 22 microns, and the astrometric precision for high SNR sources is better than 0.15 arc-seconds.Comment: 22 pages with 19 included figures. Updated to better match the accepted version in the A

The Sloan Digital Sky Survey Quasar Catalog I. Early Data Release

We present the first edition of the Sloan Digital Sky Survey (SDSS) Quasar Catalog. The catalog consists of the 3814 objects (3000 discovered by the SDSS) in the initial SDSS public data release that have at least one emission line with a full width at half maximum larger than 1000 km/s, luminosities brighter than M_i^* = -23, and highly reliable redshifts. The area covered by the catalog is 494 square degrees; the majority of the objects were found in SDSS commissioning data using a multicolor selection technique. The quasar redshifts range from 0.15 to 5.03. For each object the catalog presents positions accurate to better than 0.2" rms per coordinate, five band (ugriz) CCD-based photometry with typical accuracy of 0.05 mag, radio and X-ray emission properties, and information on the morphology and selection method. Calibrated spectra of all objects in the catalog, covering the wavelength region 3800 to 9200 Angstroms at a spectral resolution of 1800-2100, are also available. Since the quasars were selected during the commissioning period, a time when the quasar selection algorithm was undergoing frequent revisions, the sample is not homogeneous and is not intended for statistical analysis.Comment: 27 pages, 4 figures, 4 tables, accepted by A

Colors of 2625 Quasars at 0<z<5 Measured in the Sloan Digital Sky Survey Photometric System

We present an empirical investigation of the colors of quasars in the Sloan Digital Sky Survey (SDSS) photometric system. The sample studied includes 2625 quasars with SDSS photometry. The quasars are distributed in a 2.5 degree wide stripe centered on the Celestial Equator covering $\sim529$ square degrees. Positions and SDSS magnitudes are given for the 898 quasars known prior to SDSS spectroscopic commissioning. New SDSS quasars represent an increase of over 200% in the number of known quasars in this area of the sky. The ensemble average of the observed colors of quasars in the SDSS passbands are well represented by a power-law continuum with $\alpha_{\nu} = -0.5$ ($f_{\nu} \propto \nu^{\alpha}$). However, the contributions of the $3000 {\rm \AA}$ bump and other strong emission lines have a significant effect upon the colors. The color-redshift relation exhibits considerable structure, which may be of use in determining photometric redshifts for quasars. The range of colors can be accounted for by a range in the optical spectral index with a distribution $\alpha_{\nu}=-0.5\pm0.65$ (95% confidence), but there is a red tail in the distribution. This tail may be a sign of internal reddening. Finally, we show that there is a continuum of properties between quasars and Seyfert galaxies and we test the validity of the traditional division between the two classes of AGN.Comment: 66 pages, 15 figures (3 color), accepted by A