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  • Authors: Mark A, Wood; Joanna J, Bryson;

    This paper presents an imitation learning system capable of learning tasks in a complex dynamic real-time environment. In this paper, we argue that social learning should be thought of as a special case of general skill learning, and that the biases it presents to the skill learning problem radically simplify learning for species with sufficient innate predisposition to harness this power. We decompose skill learning into four subproblems, then show how a modification of Roy's CELL system can address all these problems simultaneously. Our system is demonstrated working in the domain of a real-time virtual-reality game, Unreal Tournament.

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  • Authors: Suraj Kumar Pandey; Sonia Sonia; Tushar Semwal; Shivashankar B. Nair;

    Child trafficking has emerged as a worldwide concern owing to its clandestine and pervasive nature. The lack of means for a child, to respond or be tracked during such an incident increases the prevalence of such nefarious activities. Existing solutions either put the onus on the child to respond promptly, under such a situation, or are too intricate that they incur additional infrastructural costs and monitoring. Many of these solutions mandate the use of electronic detectors that are often exposed and thus discernible to a trafficker making the user vulnerable. In this paper, we propose a concealable and wearable embedded system based patch to significantly reduce the chances of such incidents. This wearable patch, which can be added to an apparel, leverages the Internet of Things (IoT) to constantly monitor the child’s whereabouts and generate both voluntary and involuntary responses that notify a remotely located guardian in case of an emergency. The guardian is also empowered to remotely modify the area(s) where the child is permitted to be in. The paper describes how such a patch could be concealed and used in a shoe along with experiments and results that validate its effectiveness in preventing child trafficking or kidnapping.

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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Omaira García; Matthias Schneider; Benjamin Ertl; Eliezer Sepúlveda; +11 Authors

    Abstract. This work presents the methane (CH4) and nitrous oxide (N2O) products as generated by the IASI (Infrared Atmospheric Sounding Interferometer) processor developed during the project MUSICA (MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water). The processor retrieves CH4 and N2O with different water vapour and water vapour isotopologues (as well as HNO3) and uses a single a priori data set for all the retrievals (no variation in space and time). Firstly, the characteristics and errors of the products are analytically described. Secondly, the products are comprehensively evaluated by comparisons to the following reference data measured by different techniques and from different platforms as follows: (1) aircraft CH4 and N2O profiles from the five HIAPER Pole-to-Pole Observation (HIPPO) missions; (2) continuous in situ CH4 and N2O observations performed between 2007 and 2017 at subtropical and mid-latitude high-mountain observatories (Izaña Atmospheric Observatory and Jungfraujoch, respectively) in the framework of the WMO–GAW (World Meteorological Organization–Global Atmosphere Watch) programme; (3) ground-based FTIR (Fourier-transform infrared spectrometer) measurements made between 2007 and 2017 in the framework of the NDACC (Network for the Detection of Atmospheric Composition Change) at the subtropical Izaña Atmospheric Observatory, the mid-latitude station of Karlsruhe and the Kiruna polar site.The theoretical estimations and the comparison studies suggest a precision for the N2O and CH4 retrieval products of about 1.5–3 % and systematic errors due to spectroscopic parameters of about 2 %. The MUSICA IASI CH4 data offer a better sensitivity than N2O data. While for the latter the sensitivity is mainly limited to the UTLS (upper troposphere–lower stratosphere) region, for CH4 we are able to prove that at low latitudes the MUSICA IASI processor can detect variations that take place in the free troposphere independently from the variations in the UTLS region. We demonstrate that the MUSICA IASI data qualitatively capture the CH4 gradients between low and high latitudes and between the Southern Hemisphere and Northern Hemisphere; however, we also find an inconsistency between low- and high-latitude CH4 data of up to 5 %. The N2O latitudinal gradients are very weak and cannot be detected. We make comparisons over a 10-year time period and analyse the agreement with the reference data on different timescales. The MUSICA IASI data can detect day-to-day signals (only in the UTLS), seasonal cycles and long-term evolution (in the UTLS and for CH4 also in the free troposphere) similar to the reference data; however, there are also inconsistencies in the long-term evolution connected to inconsistencies in the used atmospheric temperature a priori data.Moreover, we present a method for analytically describing the a posteriori-calculated logarithmic-scale difference of the CH4 and N2O retrieval estimates. By correcting errors that are common in the CH4 and N2O retrieval products, the a posteriori-calculated difference can be used for generating an a posteriori-corrected CH4 product with a theoretically better precision than the original CH4 retrieval products. We discuss and evaluate two different approaches for such a posteriori corrections. It is shown that the correction removes the inconsistencies between low and high latitudes and enables the detection of day-to-day signals also in the free troposphere. Furthermore, they reduce the impact of short-term atmospheric dynamics, which is an advantage, because respective signals are presumably hardly comparable to model data. The approach that affects the correction solely on the scales on which the errors dominate is identified as the most efficient, because it reduces the inconsistencies and errors without removing measurable real atmospheric signals. We give a brief outlook on a possible usage of this a posteriori-corrected MUSICA IASI CH4 product in combination with inverse modelling.

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    Atmospheric Measurement Techniques
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    Atmospheric Measurement Techniques
    Article . 2018 . Peer-reviewed
    License: CC BY
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      Atmospheric Measurement Techniques
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      Atmospheric Measurement Techniques
      Article . 2018 . Peer-reviewed
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    Authors: F. Pacifico; Gerd A. Folberth; C. D. Jones; Sandy P. Harrison; +1 Authors

    We have implemented a process‐based isoprene emission model in the HadGEM2 Earth‐system model with coupled atmospheric chemistry in order to examine the feedback between isoprene emission and climate. Isoprene emissions and their impact on atmospheric chemistry and climate are estimated for preindustrial (1860–1869), present‐day (2000–2009), and future (2100–2109) climate conditions. The estimate of 460 TgC/yr for present‐day global total isoprene emission is consistent with previous estimates. Preindustrial isoprene emissions are estimated to be 26% higher than present‐day. Future isoprene emissions using the RCP8.5 scenario are similar to present‐day because increased emissions resulting from climate warming are countered by CO2 inhibition of isoprene emissions. The impact of biogenic isoprene emissions on the global O3 burden and CH4 lifetime is small but locally significant, and the impact of changes in isoprene emissions on atmospheric chemistry depends strongly on the state of climate and chemistry.

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    Journal of Geophysical Research Atmospheres
    Article . 2012 . Peer-reviewed
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      Journal of Geophysical Research Atmospheres
      Article . 2012 . Peer-reviewed
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    Authors: Qunming Wang; Chengyuan Zhang; Peter M. Atkinson;

    Abstract Remote sensing images contain abundant land cover information. Due to the complex nature of land cover, however, mixed pixels exist widely in remote sensing images. Sub-pixel mapping (SPM) is a technique for predicting the spatial distribution of land cover classes within mixed pixels. As an ill-posed inverse problem, the uncertainty of prediction cannot be eliminated and hinders the production of accurate sub-pixel maps. In contrast to conventional methods that use continuous geospatial information (e.g., images) to enhance SPM, in this paper, a SPM method with point constraints into SPM is proposed. The method of fusing point constraints is implemented based on the pixel swapping algorithm (PSA) and utilizes the auxiliary point information to reduce the uncertainty in the SPM process and increase map accuracy. The point data are incorporated into both the initialization and optimization processes of PSA. Experiments were performed on three images to validate the proposed method. The influences of the performances were also investigated under different numbers of point data, different spatial characters of land cover and different zoom factors. The results show that by using the point data, the proposed SPM method can separate more small-sized targets from aggregated artifacts and the accuracies are increased obviously. The proposed method is also more accurate than the advanced radial basis function interpolation-based method. The advantage of using point data is more evident when the point data size and scale factor are large and the spatial autocorrelation of the land cover is small. As the amount of point data increases, however, the increase in accuracy becomes less noticeable. Furthermore, the SPM accuracy can still be increased even if the point data and coarse proportions contain errors.

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    Remote Sensing of Environment
    Article . 2020 . Peer-reviewed
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      Remote Sensing of Environment
      Article . 2020 . Peer-reviewed
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    Authors: Ohood Saud Althobaiti; Mischa Dohler;

    The Internet of Things (IoT) is an emerging networking paradigm connecting billions of devices securely to the Internet. Another emerging paradigm is quantum computing which - while opening new compute opportunities - was shown to jeopardise most cybersecurity protocols. In this study, we discuss techniques able to provide security in a post-quantum IoT. Specifically, we examine how the third-generation partnership project (3GPP) IoT security solutions fair in a post-quantum environment. Also, we analyse the security features of fifth-generation (5G) networks, propose improvements and discuss the manner in which a quantum computer can compromise security. Our results prove the existence of multiple vulnerabilities in the current IoT architecture and implementations. With advances in quantum computing having rendered the current security algorithms unsafe, more advanced techniques should be established to mitigate such risks. To this end, we present promising lattice-driven cryptographic techniques which we prove quantum resistance.

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    IEEE Access
    Article . 2020 . Peer-reviewed
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  • Authors: Martin L. Parry; Timothy R. Carter; Nicolaas T. Konijn;

    Previous sections have outlined the drought climatology of the Kirinyaga-Embu-Machakos area and the results of several agroclimatic models that indicate agricultural and livestock potentials in different climatic scenarios. Even using very simple models, it is clear that climate and weather are the primary variables in determining potential productivity (and its temporal and spatial patterns) in the area. The next step is to trace the importance of variability in agricultural and livestock production to smallholder agriculturalists. Over 80% of the population of Kenya resides in the rural areas, and the majority are smallholder farmers. Development policy in Kenya has long recognized the importance of drought in planning agricultural and livestock development. It must also incorporate consideration of the smallholders’ vulnerability to drought and their means of coping with recurrent droughts of various magnitudes and durations.

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    https://doi.org/10.1007/978-94...
    Part of book or chapter of book . 1988 . Peer-reviewed
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      https://doi.org/10.1007/978-94...
      Part of book or chapter of book . 1988 . Peer-reviewed
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    Authors: T. Maharajan; Stanislaus Antony Ceasar; Thumadath Palayullaparambil Ajeesh Krishna; M. Ramakrishnan; +3 Authors

    AbstractPhosphorus (P) is the second most growth limiting macronutrient after nitrogen and plays several important roles in all organisms including plants. In soil, P is available in both organic and inorganic forms. P deficiency reduces the growth and yield of several crop plants. Plants respond to P deficiency by the phenotypic changes especially by the modification of root architecture. Molecular marker‐assisted breeding (MAB) has been proposed as an important tool to identify and develop improved varieties of crop plants with efficient P‐use efficiency (PUE). Identification of quantitative trait loci (QTLs) for traits related to PUE has been considered as the first step in marker‐assisted selection (MAS) and improvement of crop yield programmes. In this review, we describe in detail on architectural changes of roots under P deficiency that are reported in various crops and discuss the efforts made to improve PUE using molecular marker tools. Details on QTLs identified for low P‐stress tolerance in various crop plants are presented. These QTLs can be used to improve PUE in crop plants through MAS and breeding, which may be beneficial to improve the yields under P‐deficient soil. Development of new and improved varieties using MAB will limit the use of non‐renewable fertilizers and improve PUE of key crop plants in low input agriculture.

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    Plant Breeding
    Article . 2017 . Peer-reviewed
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      Plant Breeding
      Article . 2017 . Peer-reviewed
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    Authors: Zheng, Ying; Waldron, Susan; Flowers, Thomas;

    Assessing whether land use, from activities such as wind farm construction and tree-felling, impacts on terrestrial C delivery to rivers has focused on quantifying the loss of dissolved organic carbon (DOC), and not the composition changes. Here we explore how land use influences DOC composition by considering fluvial DOC concentration, [DOC], and spectrophotometric composition of a river draining a peat-rich catchment. We find that in this 5.7km2 catchment differences occur in both the concentration and composition of the DOC in its sub-catchments. This is attributed to differences in how land was used: one tributary (D-WF) drains an area with wind farm construction and forestry in the headwaters, and one tributary (D-FF) drains an area with felled plantation trees. Generally, [DOC] in both streams showed similar seasonal variation, and autumn maxima. However, the felled catchment had greater mean [DOC] than the wind farm catchment. The SUVA254 and E4/E6 indicated DOC in both streams had similar aromaticity and fulvic:humic acid for most of the time, but SUVA410 and E2/E4 indicated less DOC humification in the felled catchment. This may be due to young DOC from the breakdown of residual branches and roots, or more humification in soils in the wind farm area. During the dry months, DOC composition showed more spatial variation: the D-WF DOC had smaller SUVA254 (less total aromatic material) and SUVA410 (fewer humic substances). The decreased E2/E4 in both streams indicated the total aromatic carbon decreased more than humic substances content. Moreover, the larger E4/E6 for D-WF in summer indicated that the humic substances were richer in fulvic acids than humic acids. Soil disturbance associated with forestry-felling likely contributed to the higher [DOC] and release of less-humified material in D-FF. This research indicates drivers of different DOC concentration and composition can exist even in small catchments.

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    The Science of The Total Environment
    Article . 2018 . Peer-reviewed
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      The Science of The Total Environment
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    Authors: Singh, Minerva; Evans, Damian; Chevance, Jean-Baptiste; Tan, Boun Suy; +4 Authors

    This study develops a modelling framework by utilizing multi-sensor imagery for classifying different forest and land use types in the Phnom Kulen National Park (PKNP) in Cambodia. Three remote sensing datasets (Landsat optical data, ALOS L-band data and LiDAR derived Canopy Height Model (CHM)) were used in conjunction with three different machine learning (ML) regression techniques (Support Vector Machines (SVM), Random Forests (RF) and Artificial Neural Networks (ANN)). These ML methods were implemented on (a) Landsat spectral data, (b) Landsat spectral band & ALOS backscatter data, and (c) Landsat spectral band, ALOS backscatter data, & LiDAR CHM data. The Landsat-ALOS combination produced more accurate classification results (95% overall accuracy with SVM) compared to Landsat-only bands for all ML models. Inclusion of LiDAR CHM (which is a proxy for vertical canopy heights) improved the overall accuracy to 98%. The research establishes that majority of PKNP is dominated by cashew plantations and the nearly intact forests are concentrated in the more inaccessible parts of the park. The findings demonstrate how different RS datasets can be used in conjunction with different ML models to map forests that had undergone varying levels of degradation and plantations. International audience

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    Other literature type . Article . 2019 . Peer-reviewed
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  • Authors: Mark A, Wood; Joanna J, Bryson;

    This paper presents an imitation learning system capable of learning tasks in a complex dynamic real-time environment. In this paper, we argue that social learning should be thought of as a special case of general skill learning, and that the biases it presents to the skill learning problem radically simplify learning for species with sufficient innate predisposition to harness this power. We decompose skill learning into four subproblems, then show how a modification of Roy's CELL system can address all these problems simultaneously. Our system is demonstrated working in the domain of a real-time virtual-reality game, Unreal Tournament.

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  • Authors: Suraj Kumar Pandey; Sonia Sonia; Tushar Semwal; Shivashankar B. Nair;

    Child trafficking has emerged as a worldwide concern owing to its clandestine and pervasive nature. The lack of means for a child, to respond or be tracked during such an incident increases the prevalence of such nefarious activities. Existing solutions either put the onus on the child to respond promptly, under such a situation, or are too intricate that they incur additional infrastructural costs and monitoring. Many of these solutions mandate the use of electronic detectors that are often exposed and thus discernible to a trafficker making the user vulnerable. In this paper, we propose a concealable and wearable embedded system based patch to significantly reduce the chances of such incidents. This wearable patch, which can be added to an apparel, leverages the Internet of Things (IoT) to constantly monitor the child’s whereabouts and generate both voluntary and involuntary responses that notify a remotely located guardian in case of an emergency. The guardian is also empowered to remotely modify the area(s) where the child is permitted to be in. The paper describes how such a patch could be concealed and used in a shoe along with experiments and results that validate its effectiveness in preventing child trafficking or kidnapping.

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    Authors: Omaira García; Matthias Schneider; Benjamin Ertl; Eliezer Sepúlveda; +11 Authors

    Abstract. This work presents the methane (CH4) and nitrous oxide (N2O) products as generated by the IASI (Infrared Atmospheric Sounding Interferometer) processor developed during the project MUSICA (MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water). The processor retrieves CH4 and N2O with different water vapour and water vapour isotopologues (as well as HNO3) and uses a single a priori data set for all the retrievals (no variation in space and time). Firstly, the characteristics and errors of the products are analytically described. Secondly, the products are comprehensively evaluated by comparisons to the following reference data measured by different techniques and from different platforms as follows: (1) aircraft CH4 and N2O profiles from the five HIAPER Pole-to-Pole Observation (HIPPO) missions; (2) continuous in situ CH4 and N2O observations performed between 2007 and 2017 at subtropical and mid-latitude high-mountain observatories (Izaña Atmospheric Observatory and Jungfraujoch, respectively) in the framework of the WMO–GAW (World Meteorological Organization–Global Atmosphere Watch) programme; (3) ground-based FTIR (Fourier-transform infrared spectrometer) measurements made between 2007 and 2017 in the framework of the NDACC (Network for the Detection of Atmospheric Composition Change) at the subtropical Izaña Atmospheric Observatory, the mid-latitude station of Karlsruhe and the Kiruna polar site.The theoretical estimations and the comparison studies suggest a precision for the N2O and CH4 retrieval products of about 1.5–3 % and systematic errors due to spectroscopic parameters of about 2 %. The MUSICA IASI CH4 data offer a better sensitivity than N2O data. While for the latter the sensitivity is mainly limited to the UTLS (upper troposphere–lower stratosphere) region, for CH4 we are able to prove that at low latitudes the MUSICA IASI processor can detect variations that take place in the free troposphere independently from the variations in the UTLS region. We demonstrate that the MUSICA IASI data qualitatively capture the CH4 gradients between low and high latitudes and between the Southern Hemisphere and Northern Hemisphere; however, we also find an inconsistency between low- and high-latitude CH4 data of up to 5 %. The N2O latitudinal gradients are very weak and cannot be detected. We make comparisons over a 10-year time period and analyse the agreement with the reference data on different timescales. The MUSICA IASI data can detect day-to-day signals (only in the UTLS), seasonal cycles and long-term evolution (in the UTLS and for CH4 also in the free troposphere) similar to the reference data; however, there are also inconsistencies in the long-term evolution connected to inconsistencies in the used atmospheric temperature a priori data.Moreover, we present a method for analytically describing the a posteriori-calculated logarithmic-scale difference of the CH4 and N2O retrieval estimates. By correcting errors that are common in the CH4 and N2O retrieval products, the a posteriori-calculated difference can be used for generating an a posteriori-corrected CH4 product with a theoretically better precision than the original CH4 retrieval products. We discuss and evaluate two different approaches for such a posteriori corrections. It is shown that the correction removes the inconsistencies between low and high latitudes and enables the detection of day-to-day signals also in the free troposphere. Furthermore, they reduce the impact of short-term atmospheric dynamics, which is an advantage, because respective signals are presumably hardly comparable to model data. The approach that affects the correction solely on the scales on which the errors dominate is identified as the most efficient, because it reduces the inconsistencies and errors without removing measurable real atmospheric signals. We give a brief outlook on a possible usage of this a posteriori-corrected MUSICA IASI CH4 product in combination with inverse modelling.

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    Atmospheric Measurement Techniques
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    Atmospheric Measurement Techniques
    Article . 2018 . Peer-reviewed
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      Atmospheric Measurement Techniques
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      Atmospheric Measurement Techniques
      Article . 2018 . Peer-reviewed
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    Authors: F. Pacifico; Gerd A. Folberth; C. D. Jones; Sandy P. Harrison; +1 Authors

    We have implemented a process‐based isoprene emission model in the HadGEM2 Earth‐system model with coupled atmospheric chemistry in order to examine the feedback between isoprene emission and climate. Isoprene emissions and their impact on atmospheric chemistry and climate are estimated for preindustrial (1860–1869), present‐day (2000–2009), and future (2100–2109) climate conditions. The estimate of 460 TgC/yr for present‐day global total isoprene emission is consistent with previous estimates. Preindustrial isoprene emissions are estimated to be 26% higher than present‐day. Future isoprene emissions using the RCP8.5 scenario are similar to present‐day because increased emissions resulting from climate warming are countered by CO2 inhibition of isoprene emissions. The impact of biogenic isoprene emissions on the global O3 burden and CH4 lifetime is small but locally significant, and the impact of changes in isoprene emissions on atmospheric chemistry depends strongly on the state of climate and chemistry.

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    Journal of Geophysical Research Atmospheres
    Article . 2012 . Peer-reviewed
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      Journal of Geophysical Research Atmospheres
      Article . 2012 . Peer-reviewed
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    Authors: Qunming Wang; Chengyuan Zhang; Peter M. Atkinson;

    Abstract Remote sensing images contain abundant land cover information. Due to the complex nature of land cover, however, mixed pixels exist widely in remote sensing images. Sub-pixel mapping (SPM) is a technique for predicting the spatial distribution of land cover classes within mixed pixels. As an ill-posed inverse problem, the uncertainty of prediction cannot be eliminated and hinders the production of accurate sub-pixel maps. In contrast to conventional methods that use continuous geospatial information (e.g., images) to enhance SPM, in this paper, a SPM method with point constraints into SPM is proposed. The method of fusing point constraints is implemented based on the pixel swapping algorithm (PSA) and utilizes the auxiliary point information to reduce the uncertainty in the SPM process and increase map accuracy. The point data are incorporated into both the initialization and optimization processes of PSA. Experiments were performed on three images to validate the proposed method. The influences of the performances were also investigated under different numbers of point data, different spatial characters of land cover and different zoom factors. The results show that by using the point data, the proposed SPM method can separate more small-sized targets from aggregated artifacts and the accuracies are increased obviously. The proposed method is also more accurate than the advanced radial basis function interpolation-based method. The advantage of using point data is more evident when the point data size and scale factor are large and the spatial autocorrelation of the land cover is small. As the amount of point data increases, however, the increase in accuracy becomes less noticeable. Furthermore, the SPM accuracy can still be increased even if the point data and coarse proportions contain errors.

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    Remote Sensing of Environment
    Article . 2020 . Peer-reviewed
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      Remote Sensing of Environment
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    Authors: Ohood Saud Althobaiti; Mischa Dohler;

    The Internet of Things (IoT) is an emerging networking paradigm connecting billions of devices securely to the Internet. Another emerging paradigm is quantum computing which - while opening new compute opportunities - was shown to jeopardise most cybersecurity protocols. In this study, we discuss techniques able to provide security in a post-quantum IoT. Specifically, we examine how the third-generation partnership project (3GPP) IoT security solutions fair in a post-quantum environment. Also, we analyse the security features of fifth-generation (5G) networks, propose improvements and discuss the manner in which a quantum computer can compromise security. Our results prove the existence of multiple vulnerabilities in the current IoT architecture and implementations. With advances in quantum computing having rendered the current security algorithms unsafe, more advanced techniques should be established to mitigate such risks. To this end, we present promising lattice-driven cryptographic techniques which we prove quantum resistance.

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    IEEE Access
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    IEEE Access
    Article . 2020 . Peer-reviewed
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    Article . 2020
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    IEEE Access
    Article . 2020
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      IEEE Access
      Article . 2020 . Peer-reviewed
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  • Authors: Martin L. Parry; Timothy R. Carter; Nicolaas T. Konijn;

    Previous sections have outlined the drought climatology of the Kirinyaga-Embu-Machakos area and the results of several agroclimatic models that indicate agricultural and livestock potentials in different climatic scenarios. Even using very simple models, it is clear that climate and weather are the primary variables in determining potential productivity (and its temporal and spatial patterns) in the area. The next step is to trace the importance of variability in agricultural and livestock production to smallholder agriculturalists. Over 80% of the population of Kenya resides in the rural areas, and the majority are smallholder farmers. Development policy in Kenya has long recognized the importance of drought in planning agricultural and livestock development. It must also incorporate consideration of the smallholders’ vulnerability to drought and their means of coping with recurrent droughts of various magnitudes and durations.

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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: T. Maharajan; Stanislaus Antony Ceasar; Thumadath Palayullaparambil Ajeesh Krishna; M. Ramakrishnan; +3 Authors

    AbstractPhosphorus (P) is the second most growth limiting macronutrient after nitrogen and plays several important roles in all organisms including plants. In soil, P is available in both organic and inorganic forms. P deficiency reduces the growth and yield of several crop plants. Plants respond to P deficiency by the phenotypic changes especially by the modification of root architecture. Molecular marker‐assisted breeding (MAB) has been proposed as an important tool to identify and develop improved varieties of crop plants with efficient P‐use efficiency (PUE). Identification of quantitative trait loci (QTLs) for traits related to PUE has been considered as the first step in marker‐assisted selection (MAS) and improvement of crop yield programmes. In this review, we describe in detail on architectural changes of roots under P deficiency that are reported in various crops and discuss the efforts made to improve PUE using molecular marker tools. Details on QTLs identified for low P‐stress tolerance in various crop plants are presented. These QTLs can be used to improve PUE in crop plants through MAS and breeding, which may be beneficial to improve the yields under P‐deficient soil. Development of new and improved varieties using MAB will limit the use of non‐renewable fertilizers and improve PUE of key crop plants in low input agriculture.

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    Plant Breeding
    Article . 2017 . Peer-reviewed
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      Plant Breeding
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Zheng, Ying; Waldron, Susan; Flowers, Thomas;

    Assessing whether land use, from activities such as wind farm construction and tree-felling, impacts on terrestrial C delivery to rivers has focused on quantifying the loss of dissolved organic carbon (DOC), and not the composition changes. Here we explore how land use influences DOC composition by considering fluvial DOC concentration, [DOC], and spectrophotometric composition of a river draining a peat-rich catchment. We find that in this 5.7km2 catchment differences occur in both the concentration and composition of the DOC in its sub-catchments. This is attributed to differences in how land was used: one tributary (D-WF) drains an area with wind farm construction and forestry in the headwaters, and one tributary (D-FF) drains an area with felled plantation trees. Generally, [DOC] in both streams showed similar seasonal variation, and autumn maxima. However, the felled catchment had greater mean [DOC] than the wind farm catchment. The SUVA254 and E4/E6 indicated DOC in both streams had similar aromaticity and fulvic:humic acid for most of the time, but SUVA410 and E2/E4 indicated less DOC humification in the felled catchment. This may be due to young DOC from the breakdown of residual branches and roots, or more humification in soils in the wind farm area. During the dry months, DOC composition showed more spatial variation: the D-WF DOC had smaller SUVA254 (less total aromatic material) and SUVA410 (fewer humic substances). The decreased E2/E4 in both streams indicated the total aromatic carbon decreased more than humic substances content. Moreover, the larger E4/E6 for D-WF in summer indicated that the humic substances were richer in fulvic acids than humic acids. Soil disturbance associated with forestry-felling likely contributed to the higher [DOC] and release of less-humified material in D-FF. This research indicates drivers of different DOC concentration and composition can exist even in small catchments.

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    The Science of The Total Environment
    Article . 2018 . Peer-reviewed
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      The Science of The Total Environment
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Singh, Minerva; Evans, Damian; Chevance, Jean-Baptiste; Tan, Boun Suy; +4 Authors

    This study develops a modelling framework by utilizing multi-sensor imagery for classifying different forest and land use types in the Phnom Kulen National Park (PKNP) in Cambodia. Three remote sensing datasets (Landsat optical data, ALOS L-band data and LiDAR derived Canopy Height Model (CHM)) were used in conjunction with three different machine learning (ML) regression techniques (Support Vector Machines (SVM), Random Forests (RF) and Artificial Neural Networks (ANN)). These ML methods were implemented on (a) Landsat spectral data, (b) Landsat spectral band & ALOS backscatter data, and (c) Landsat spectral band, ALOS backscatter data, & LiDAR CHM data. The Landsat-ALOS combination produced more accurate classification results (95% overall accuracy with SVM) compared to Landsat-only bands for all ML models. Inclusion of LiDAR CHM (which is a proxy for vertical canopy heights) improved the overall accuracy to 98%. The research establishes that majority of PKNP is dominated by cashew plantations and the nearly intact forests are concentrated in the more inaccessible parts of the park. The findings demonstrate how different RS datasets can be used in conjunction with different ML models to map forests that had undergone varying levels of degradation and plantations. International audience

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    PeerJ
    Other literature type . Article . 2019 . Peer-reviewed
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    Article . 2019
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ HAL Descartes; Mémoi...arrow_drop_down
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      This Research product is the result of merged Research products in OpenAIRE.

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