scholarly journals Large-scale field phenotyping using backpack LiDAR and GUI-based CropQuant-3D to measure structural responses to different nitrogen treatments in wheat

2021 ◽  
Author(s):  
Yulei Zhu ◽  
Gang Sun ◽  
Guohui Ding ◽  
Jie Zhou ◽  
Mingxing Wen ◽  
...  
Keyword(s):  
Large Scale ◽  
Structural Changes ◽  
Field Experiments ◽  
Computing Time ◽  
Point Clouds ◽  
Combined System ◽  
Wheat Varieties ◽  
Wide Range ◽  
Field Phenotyping ◽  
Nitrogen Treatments

Plant phenomics is widely recognised as a key area to bridge the gap between traits of agricultural importance and genomic information. A wide range of field-based phenotyping solutions have been developed. Nevertheless, disadvantages of these current systems have been identified concerning mobility, affordability, accuracy, scalability, and the ability to analyse big data collected. Here, we present a novel solution that combines a commercial backpack LiDAR device and graphical user interface (GUI) based software called CropQuant-3D, which has been applied to analyse 3D morphological traits in wheat. To our knowledge, this is the first use of backpack LiDAR in field-based plant research, acquiring millions of 3D points to represent spatial features of crops. A key part of the innovation is the GUI-based software that can extract plot-based traits from large and complex point clouds with limited computing time. We describe how we developed and used the combined system to quantify canopy structural changes, impossible to measure previously. Also, we demonstrate the biological relevance of our work through a case study that examined wheat varieties to three different levels of nitrogen fertilisation in field experiments. The results indicate that the solution can differentiate significant genotype and treatment effects on key traits, with strong correlations with manual measurements. Hence, we believe that the solution presented here could consistently and speedily quantify traits at a larger scale, indicating the system could be used as a reliable research tool in large-scale and multi-location field phenotyping to contribute to the resolution of the phenotyping bottleneck.

scholarly journals On the Shoulders of Giants: Continuing the Legacy of Large-Scale Ecosystem Manipulation Experiments in Puerto Rico

Forests ◽  
2019 ◽  
Vol 10 (3) ◽  
pp. 210 ◽  
Author(s):  
Tana Wood ◽  
Grizelle González ◽  
Whendee Silver ◽  
Sasha Reed ◽  
Molly Cavaleri
Keyword(s):  
Puerto Rico ◽  
Tropical Forests ◽  
Large Scale ◽  
Field Experiments ◽  
Management Strategies ◽  
Luquillo Experimental Forest ◽  
Hurricane Disturbance ◽  
Wide Range ◽  
History Of ◽  
Forest Function

There is a long history of experimental research in the Luquillo Experimental Forest in Puerto Rico. These experiments have addressed questions about biotic thresholds, assessed why communities vary along natural gradients, and have explored forest responses to a range of both anthropogenic and non-anthropogenic disturbances. Combined, these studies cover many of the major disturbances that affect tropical forests around the world and span a wide range of topics, including the effects of forest thinning, ionizing radiation, hurricane disturbance, nitrogen deposition, drought, and global warming. These invaluable studies have greatly enhanced our understanding of tropical forest function under different disturbance regimes and informed the development of management strategies. Here we summarize the major field experiments that have occurred within the Luquillo Experimental Forest. Taken together, results from the major experiments conducted in the Luquillo Experimental Forest demonstrate a high resilience of Puerto Rico’s tropical forests to a variety of stressors.

scholarly journals A large-scale forest fragmentation experiment: the Stability of Altered Forest Ecosystems Project

2011 ◽  
Vol 366 (1582) ◽  
pp. 3292-3302 ◽  
Author(s):  
Robert M. Ewers ◽  
Raphael K. Didham ◽  
Lenore Fahrig ◽  
Gonçalo Ferraz ◽  
Andy Hector ◽  
...  
Keyword(s):  
Forest Fragmentation ◽  
Large Scale ◽  
Forest Cover ◽  
Forest Ecosystems ◽  
Field Experiments ◽  
Spatial Scales ◽  
Ecological Impacts ◽  
Data Types ◽  
Wide Range ◽  
The Stability

Opportunities to conduct large-scale field experiments are rare, but provide a unique opportunity to reveal the complex processes that operate within natural ecosystems. Here, we review the design of existing, large-scale forest fragmentation experiments. Based on this review, we develop a design for the Stability of Altered Forest Ecosystems (SAFE) Project, a new forest fragmentation experiment to be located in the lowland tropical forests of Borneo (Sabah, Malaysia). The SAFE Project represents an advance on existing experiments in that it: (i) allows discrimination of the effects of landscape-level forest cover from patch-level processes; (ii) is designed to facilitate the unification of a wide range of data types on ecological patterns and processes that operate over a wide range of spatial scales; (iii) has greater replication than existing experiments; (iv) incorporates an experimental manipulation of riparian corridors; and (v) embeds the experimentally fragmented landscape within a wider gradient of land-use intensity than do existing projects. The SAFE Project represents an opportunity for ecologists across disciplines to participate in a large initiative designed to generate a broad understanding of the ecological impacts of tropical forest modification.

scholarly journals SegMap: Segment-based mapping and localization using data-driven descriptors

2019 ◽  
Vol 39 (2-3) ◽  
pp. 339-355 ◽  
Author(s):  
Renaud Dubé ◽  
Andrei Cramariuc ◽  
Daniel Dugas ◽  
Hannes Sommer ◽  
Marcin Dymczyk ◽  
...  
Keyword(s):  
Large Scale ◽  
Structural Changes ◽  
Mobile Robotics ◽  
State Of The Art ◽  
Point Clouds ◽  
Open Loop ◽  
Data Driven ◽  
Global Localization ◽  
3D Point Clouds ◽  
Coarse Information

Precisely estimating a robot’s pose in a prior, global map is a fundamental capability for mobile robotics, e.g., autonomous driving or exploration in disaster zones. This task, however, remains challenging in unstructured, dynamic environments, where local features are not discriminative enough and global scene descriptors only provide coarse information. We therefore present SegMap: a map representation solution for localization and mapping based on the extraction of segments in 3D point clouds. Working at the level of segments offers increased invariance to view-point and local structural changes, and facilitates real-time processing of large-scale 3D data. SegMap exploits a single compact data-driven descriptor for performing multiple tasks: global localization, 3D dense map reconstruction, and semantic information extraction. The performance of SegMap is evaluated in multiple urban driving and search and rescue experiments. We show that the learned SegMap descriptor has superior segment retrieval capabilities, compared with state-of-the-art handcrafted descriptors. As a consequence, we achieve a higher localization accuracy and a 6% increase in recall over state-of-the-art handcrafted descriptors. These segment-based localizations allow us to reduce the open-loop odometry drift by up to 50%. SegMap is open-source available along with easy to run demonstrations.

scholarly journals Sensitivity of pelagic calcification to ocean acidification

2011 ◽  
Vol 8 (2) ◽  
pp. 433-458 ◽  
Author(s):  
R. Gangstø ◽  
F. Joos ◽  
M. Gehlen
Keyword(s):  
Ocean Acidification ◽  
Carbon Emissions ◽  
Large Scale ◽  
Field Experiments ◽  
Emission Scenario ◽  
Atmospheric Co2 ◽  
Soluble Form ◽  
Saturation State ◽  
Biogeochemical Models ◽  
Wide Range

Abstract. Ocean acidification might reduce the ability of calcifying plankton to produce and maintain their shells of calcite, or of aragonite, the more soluble form of CaCO3. In addition to possibly large biological impacts, reduced CaCO3 production corresponds to a negative feedback on atmospheric CO2. In order to explore the sensitivity of the ocean carbon cycle to increasing concentrations of atmospheric CO2, we use the new biogeochemical Bern3D/PISCES model. The model reproduces the large scale distributions of biogeochemical tracers. With a range of sensitivity studies, we explore the effect of (i) using different parameterizations of CaCO3 production fitted to available laboratory and field experiments, of (ii) letting calcite and aragonite be produced by auto- and heterotrophic plankton groups, and of (iii) using carbon emissions from the range of the most recent IPCC Representative Concentration Pathways (RCP). Under a high-emission scenario, the CaCO3 production of all the model versions decreases from ~1 Pg C yr−1 to between 0.36 and 0.82 Pg C yr−1 by the year 2100. The changes in CaCO3 production and dissolution resulting from ocean acidification provide only a small feedback on atmospheric CO2 of −1 to −11 ppm by the year 2100, despite the wide range of parameterizations, model versions and scenarios included in our study. A potential upper limit of the CO2-calcification/dissolution feedback of −30 ppm by the year 2100 is computed by setting calcification to zero after 2000 in a high 21st century emission scenario. The similarity of feedback estimates yielded by the model version with calcite produced by nanophytoplankton and the one with calcite, respectively aragonite produced by mesozooplankton suggests that expending biogeochemical models to calcifying zooplankton might not be needed to simulate biogeochemical impacts on the marine carbonate cycle. The changes in saturation state confirm previous studies indicating that future anthropogenic CO2 emissions may lead to irreversible changes in ΩA for several centuries. Furthermore, due to the long-term changes in the deep ocean, the ratio of open water CaCO3 dissolution to production stabilizes by the year 2500 at a value that is 30–50% higher than at pre-industrial times when carbon emissions are set to zero after 2100.

scholarly journals SUBMANIFOLD SPARSE CONVOLUTIONAL NETWORKS FOR SEMANTIC SEGMENTATION OF LARGE-SCALE ALS POINT CLOUDS

2019 ◽  
Vol IV-2/W5 ◽  
pp. 77-84 ◽  
Author(s):  
S. Schmohl ◽  
U. Sörgel
Keyword(s):  
Laser Scanning ◽  
Large Scale ◽  
Computing Time ◽  
Semantic Segmentation ◽  
Point Clouds ◽  
Convolutional Networks ◽  
Airborne Laser ◽  
Semantic Labeling ◽  
3D Data ◽  
Automated Processing

<p><strong>Abstract.</strong> Semantic segmentation of point clouds is one of the main steps in automated processing of data from Airborne Laser Scanning (ALS). Established methods usually require expensive calculation of handcrafted, point-wise features. In contrast, Convolutional Neural Networks (CNNs) have been established as powerful classifiers, which at the same time also learn a set of features by themselves. However, their application to ALS data is not trivial. Pure 3D CNNs require a lot of memory and computing time, therefore most related approaches project ALS point clouds into two-dimensional images. Sparse Submanifold Convolutional Networks (SSCNs) address this issue by exploiting the sparsity often inherent in 3D data. In this work, we propose the application of SSCNs for efficient semantic segmentation of voxelized ALS point clouds in an end-to-end encoder-decoder architecture. We evaluate this method on the ISPRS Vaihingen 3D Semantic Labeling benchmark and achieve state-of-the-art 85.0% overall accuracy. Furthermore, we demonstrate its capabilities regarding large-scale ALS data by classifying a 2.5&amp;thinsp;km<sup>2</sup> subset containing 41&amp;thinsp;M points from the Actueel Hoogtebestand Nederland (AHN3) with 95% overall accuracy in just 48&amp;thinsp;s inference time or with 96% in 108&amp;thinsp;s.</p>

scholarly journals Potential Phenotyping Methodologies to Assess Inter- and Intravarietal Variability and to Select Grapevine Genotypes Tolerant to Abiotic Stress

2021 ◽  
Vol 12 ◽  
Author(s):  
Luísa C. Carvalho ◽  
Elsa F. Gonçalves ◽  
Jorge Marques da Silva ◽  
J. Miguel Costa
Keyword(s):  
Abiotic Stress ◽  
Large Scale ◽  
Field Experiments ◽  
Multiple Scales ◽  
Plant Traits ◽  
Data Retrieval ◽  
Plant Phenotyping ◽  
Soil Conditions ◽  
Related Field ◽  
Field Phenotyping

Plant phenotyping is an emerging science that combines multiple methodologies and protocols to measure plant traits (e.g., growth, morphology, architecture, function, and composition) at multiple scales of organization. Manual phenotyping remains as a major bottleneck to the advance of plant and crop breeding. Such constraint fostered the development of high throughput plant phenotyping (HTPP), which is largely based on imaging approaches and automatized data retrieval and processing. Field phenotyping still poses major challenges and the progress of HTPP for field conditions can be relevant to support selection and breeding of grapevine. The aim of this review is to discuss potential and current methods to improve field phenotyping of grapevine to support characterization of inter- and intravarietal diversity. Vitis vinifera has a large genetic diversity that needs characterization, and the availability of methods to support selection of plant material (polyclonal or clonal) able to withstand abiotic stress is paramount. Besides being time consuming, complex and expensive, field experiments are also affected by heterogeneous and uncontrolled climate and soil conditions, mostly due to the large areas of the trials and to the high number of traits to be observed in a number of individuals ranging from hundreds to thousands. Therefore, adequate field experimental design and data gathering methodologies are crucial to obtain reliable data. Some of the major challenges posed to grapevine selection programs for tolerance to water and heat stress are described herein. Useful traits for selection and related field phenotyping methodologies are described and their adequacy for large scale screening is discussed.

scholarly journals Martini Coarse-Grained Model of Hyaluronic Acid for the Structural Change of Its Gel in the Presence of Monovalent and Divalent Salts

2020 ◽  
Vol 21 (13) ◽  
pp. 4602 ◽  
Author(s):  
Raj Kumar ◽  
Young Kyu Lee ◽  
Yong Seok Jho
Keyword(s):  
Hyaluronic Acid ◽  
Large Scale ◽  
Structural Changes ◽  
Coarse Grained ◽  
Radius Of Gyration ◽  
Main Role ◽  
Structural Formation ◽  
Wide Range ◽  
Distinct Property ◽  
End Distance

Hyaluronic acid (HA) has a wide range of biomedical applications including the formation of hydrogels, microspheres, sponges, and films. The modeling of HA to understand its behavior and interaction with other biomolecules at the atomic level is of considerable interest. The atomistic representation of long HA polymers for the study of the macroscopic structural formation and its interactions with other polyelectrolytes is computationally demanding. To overcome this limitation, we developed a coarse grained (CG) model for HA adapting the Martini scheme. A very good agreement was observed between the CG model and all-atom simulations for both local (bonded interactions) and global properties (end-to-end distance, a radius of gyration, RMSD). Our CG model successfully demonstrated the formation of HA gel and its structural changes at high salt concentrations. We found that the main role of CaCl2 is screening the electrostatic repulsion between chains. HA gel did not collapse even at high CaCl2 concentrations, and the osmotic pressure decreased, which agrees well with the experimental results. This is a distinct property of HA from other proteins or polynucleic acids which ensures the validity of our CG model. Our HA CG model is compatible with other CG biomolecular models developed under the Martini scheme, which allows for large-scale simulations of various HA-based complex systems.

scholarly journals Biological markets in cooperative breeders: quantifying outside options

2017 ◽  
Vol 284 (1856) ◽  
pp. 20170904 ◽  
Author(s):  
Lena Grinsted ◽  
Jeremy Field
Keyword(s):  
Evolutionary Biology ◽  
Large Scale ◽  
Field Experiments ◽  
Partner Choice ◽  
Market Theory ◽  
Biological Markets ◽  
Wide Range ◽  
Helping Behaviour ◽  
Large Scale Field ◽  
Biological Market Theory

A major aim in evolutionary biology is to understand altruistic help and reproductive partitioning in cooperative societies, where subordinate helpers forego reproduction to rear dominant breeders' offspring. Traditional models of cooperation in these societies typically make a key assumption: that the only alternative to staying and helping is solitary breeding, an often unfeasible task. Using large-scale field experiments on paper wasps ( Polistes dominula ), we show that individuals have high-quality alternative nesting options available that offer fitness payoffs just as high as their actual chosen options, far exceeding payoffs from solitary breeding. Furthermore, joiners could not easily be replaced if they were removed experimentally, suggesting that it may be costly for dominants to reject them. Our results have implications for expected payoff distributions for cooperating individuals, and suggest that biological market theory, which incorporates partner choice and competition for partners, is necessary to understand helping behaviour in societies like that of P. dominula . Traditional models are likely to overestimate the incentive to stay and help, and therefore the amount of help provided, and may underestimate the size of reproductive concession required to retain subordinates. These findings are relevant for a wide range of cooperative breeders where there is dispersal between social groups.

scholarly journals Sensitivity of the marine carbonate cycle to atmospheric CO<sub>2</sub>

2010 ◽  
Vol 7 (5) ◽  
pp. 7029-7090
Author(s):  
R. Gangstø ◽  
F. Joos ◽  
M. Gehlen
Keyword(s):  
Ocean Acidification ◽  
Carbon Emissions ◽  
Large Scale ◽  
Field Experiments ◽  
Open Water ◽  
Atmospheric Co2 ◽  
Soluble Form ◽  
Wide Range ◽  
High Emission ◽  
Ocean Carbon

Abstract. Ocean acidification might reduce the ability of calcifying plankton to produce and maintain their shells of calcite, or of aragonite, the more soluble form of CaCO3. In addition to possibly large biological impacts, reduced CaCO3 production corresponds to a negative feedback on atmospheric CO2. In order to explore the sensitivity of the ocean carbon cycle to increasing concentrations of atmospheric CO2, we use the new biogeochemical Bern3D/PISCES model. The model reproduces the large scale distributions of biogeochemical tracers. With a range of sensitivity studies, we explore the effect of (i) using different parameterizations of CaCO3 production fitted to available laboratory and field experiments, of (ii) letting calcite and aragonite be produced by auto- and heterotrophic plankton groups, and of (iii) using carbon emissions from the range of the most recent IPCC Representative Concentration Pathways (RCP). Under a high-emission scenario, the CaCO3 production of all the model versions decreases from ~1 Pg C yr−1 to between 0.36 and 0.82 Pg C yr−1 by the year 2100. By the year 2500, the ratio of open water CaCO3 dissolution to production stabilizes at a value that is 30–50% higher than at pre-industrial times when carbon emissions are set to zero after 2100. Despite the wide range of parameterizations, model versions and scenarios included in our study, the changes in CaCO3 production and dissolution resulting from ocean acidification provide only a small feedback on atmospheric CO2 of 1–11 ppm by the year 2100.

Residual effect of zinc applied to rice on zinc nutrition of succeeding wheat crop inoculated with zinc solubilizing microbial consortium

2019 ◽  
Vol 66 (3-4) ◽  
pp. 227-237
Author(s):  
Sachin Kumar Vaid ◽  
Prakash Chandra Srivastava ◽  
Satya Pratap Pachauri ◽  
Anita Sharma ◽  
Deepa Rawat ◽  
...  
Keyword(s):  
Crop Production ◽  
Large Scale ◽  
Field Experiments ◽  
Residual Effect ◽  
Wheat Crop ◽  
Bacterial Strains ◽  
Wheat Varieties ◽  
Seed Inoculation ◽  
Zn Uptake ◽  
Zn Concentration

Large scale deficiency of Zn results in low crops yields and the problem of Zn malnutrition in humans and livestock. To economize crop production on Zn deficient soils, two-year field experiments were undertaken with two wheat varieties to evaluate the performance of seed inoculation with a consortium of three bacterial strains in combination with varying doses of Zn fertilizer applied to 1 year rice crop on yields, Zn concentration and Zn uptake of wheat. Seed coating of wheat with bacterial consortium significantly increased grain yields, Zn concentration and uptake in grains and straw and total Zn uptake over the control. It also helped to increase the apparent recoveries of soil applied Zn fertilizer to 1 year rice by succeeding wheat crops and DTPA extractable Zn in soil after 2 year wheat in comparison to the control. Seed inoculation in combination with low dosage of Zn also significantly decreased phytic acid: Zn ratio but increased methionine concentration in wheat grains.

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