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      Emerging Technologies in Algal Biotechnology: Toward the Establishment of a Sustainable, Algae-Based Bioeconomy

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          Abstract

          Mankind has recognized the value of land plants as renewable sources of food, medicine, and materials for millennia. Throughout human history, agricultural methods were continuously modified and improved to meet the changing needs of civilization. Today, our rapidly growing population requires further innovation to address the practical limitations and serious environmental concerns associated with current industrial and agricultural practices. Microalgae are a diverse group of unicellular photosynthetic organisms that are emerging as next-generation resources with the potential to address urgent industrial and agricultural demands. The extensive biological diversity of algae can be leveraged to produce a wealth of valuable bioproducts, either naturally or via genetic manipulation. Microalgae additionally possess a set of intrinsic advantages, such as low production costs, no requirement for arable land, and the capacity to grow rapidly in both large-scale outdoor systems and scalable, fully contained photobioreactors. Here, we review technical advancements, novel fields of application, and products in the field of algal biotechnology to illustrate how algae could present high-tech, low-cost, and environmentally friendly solutions to many current and future needs of our society. We discuss how emerging technologies such as synthetic biology, high-throughput phenomics, and the application of internet of things (IoT) automation to algal manufacturing technology can advance the understanding of algal biology and, ultimately, drive the establishment of an algal-based bioeconomy.

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          Biofuels from microalgae—A review of technologies for production, processing, and extractions of biofuels and co-products

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            Using Deep Learning for Image-Based Plant Disease Detection

            Crop diseases are a major threat to food security, but their rapid identification remains difficult in many parts of the world due to the lack of the necessary infrastructure. The combination of increasing global smartphone penetration and recent advances in computer vision made possible by deep learning has paved the way for smartphone-assisted disease diagnosis. Using a public dataset of 54,306 images of diseased and healthy plant leaves collected under controlled conditions, we train a deep convolutional neural network to identify 14 crop species and 26 diseases (or absence thereof). The trained model achieves an accuracy of 99.35% on a held-out test set, demonstrating the feasibility of this approach. Overall, the approach of training deep learning models on increasingly large and publicly available image datasets presents a clear path toward smartphone-assisted crop disease diagnosis on a massive global scale.
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              A review on emerging contaminants in wastewaters and the environment: current knowledge, understudied areas and recommendations for future monitoring.

              This review identifies understudied areas of emerging contaminant (EC) research in wastewaters and the environment, and recommends direction for future monitoring. Non-regulated trace organic ECs including pharmaceuticals, illicit drugs and personal care products are focused on due to ongoing policy initiatives and the expectant broadening of environmental legislation. These ECs are ubiquitous in the aquatic environment, mainly derived from the discharge of municipal wastewater effluents. Their presence is of concern due to the possible ecological impact (e.g., endocrine disruption) to biota within the environment. To better understand their fate in wastewaters and in the environment, a standardised approach to sampling is needed. This ensures representative data is attained and facilitates a better understanding of spatial and temporal trends of EC occurrence. During wastewater treatment, there is a lack of suspended particulate matter analysis due to further preparation requirements and a lack of good analytical approaches. This results in the under-reporting of several ECs entering wastewater treatment works (WwTWs) and the aquatic environment. Also, sludge can act as a concentrating medium for some chemicals during wastewater treatment. The majority of treated sludge is applied directly to agricultural land without analysis for ECs. As a result there is a paucity of information on the fate of ECs in soils and consequently, there has been no driver to investigate the toxicity to exposed terrestrial organisms. Therefore a more holistic approach to environmental monitoring is required, such that the fate and impact of ECs in all exposed environmental compartments are studied. The traditional analytical approach of applying targeted screening with low resolution mass spectrometry (e.g., triple quadrupoles) results in numerous chemicals such as transformation products going undetected. These can exhibit similar toxicity to the parent EC, demonstrating the necessity of using an integrated analytical approach which compliments targeted and non-targeted screening with biological assays to measure ecological impact. With respect to current toxicity testing protocols, failure to consider the enantiomeric distribution of chiral compounds found in the environment, and the possible toxicological differences between enantiomers is concerning. Such information is essential for the development of more accurate environmental risk assessment.
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                Author and article information

                Contributors
                Journal
                Front Plant Sci
                Front Plant Sci
                Front. Plant Sci.
                Frontiers in Plant Science
                Frontiers Media S.A.
                1664-462X
                17 March 2020
                2020
                : 11
                : 279
                Affiliations
                [1] 1Climate Change Cluster (C3), University of Technology Sydney , Ultimo, NSW, Australia
                [2] 2CSIRO Synthetic Biology Future Science Platform , Brisbane, QLD, Australia
                Author notes

                Edited by: Edward Rybicki, University of Cape Town, South Africa

                Reviewed by: Philip Thomas Pienkos, National Renewable Energy Laboratory (DOE), United States; Maria Stockenreiter, Ludwig Maximilian University of Munich, Germany

                *Correspondence: Michele Fabris, michele.fabris@ 123456uts.edu.au

                This article was submitted to Plant Biotechnology, a section of the journal Frontiers in Plant Science

                Article
                10.3389/fpls.2020.00279
                7090149
                32256509
                75dd28df-39b9-44da-a7cc-e6c394f30795
                Copyright © 2020 Fabris, Abbriano, Pernice, Sutherland, Commault, Hall, Labeeuw, McCauley, Kuzhiuparambil, Ray, Kahlke and Ralph.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 29 November 2019
                : 24 February 2020
                Page count
                Figures: 2, Tables: 0, Equations: 0, References: 305, Pages: 22, Words: 0
                Categories
                Plant Science
                Review

                Plant science & Botany
                microalgae,synthetic biology,phenomics,industry 4.0,bioproducts,food,bioremediation,feedstock

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