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      Unmanned Aerial Vehicle Remote Sensing for Field-Based Crop Phenotyping: Current Status and Perspectives

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          Abstract

          Phenotyping plays an important role in crop science research; the accurate and rapid acquisition of phenotypic information of plants or cells in different environments is helpful for exploring the inheritance and expression patterns of the genome to determine the association of genomic and phenotypic information to increase the crop yield. Traditional methods for acquiring crop traits, such as plant height, leaf color, leaf area index (LAI), chlorophyll content, biomass and yield, rely on manual sampling, which is time-consuming and laborious. Unmanned aerial vehicle remote sensing platforms (UAV-RSPs) equipped with different sensors have recently become an important approach for fast and non-destructive high throughput phenotyping and have the advantage of flexible and convenient operation, on-demand access to data and high spatial resolution. UAV-RSPs are a powerful tool for studying phenomics and genomics. As the methods and applications for field phenotyping using UAVs to users who willing to derive phenotypic parameters from large fields and tests with the minimum effort on field work and getting highly reliable results are necessary, the current status and perspectives on the topic of UAV-RSPs for field-based phenotyping were reviewed based on the literature survey of crop phenotyping using UAV-RSPs in the Web of Science™ Core Collection database and cases study by NERCITA. The reference for the selection of UAV platforms and remote sensing sensors, the commonly adopted methods and typical applications for analyzing phenotypic traits by UAV-RSPs, and the challenge for crop phenotyping by UAV-RSPs were considered. The review can provide theoretical and technical support to promote the applications of UAV-RSPs for crop phenotyping.

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          Most cited references142

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          Yield Trends Are Insufficient to Double Global Crop Production by 2050

          Several studies have shown that global crop production needs to double by 2050 to meet the projected demands from rising population, diet shifts, and increasing biofuels consumption. Boosting crop yields to meet these rising demands, rather than clearing more land for agriculture has been highlighted as a preferred solution to meet this goal. However, we first need to understand how crop yields are changing globally, and whether we are on track to double production by 2050. Using ∼2.5 million agricultural statistics, collected for ∼13,500 political units across the world, we track four key global crops—maize, rice, wheat, and soybean—that currently produce nearly two-thirds of global agricultural calories. We find that yields in these top four crops are increasing at 1.6%, 1.0%, 0.9%, and 1.3% per year, non-compounding rates, respectively, which is less than the 2.4% per year rate required to double global production by 2050. At these rates global production in these crops would increase by ∼67%, ∼42%, ∼38%, and ∼55%, respectively, which is far below what is needed to meet projected demands in 2050. We present detailed maps to identify where rates must be increased to boost crop production and meet rising demands.
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            Plant responses to drought, salinity and extreme temperatures: towards genetic engineering for stress tolerance.

            Abiotic stresses, such as drought, salinity, extreme temperatures, chemical toxicity and oxidative stress are serious threats to agriculture and the natural status of the environment. Increased salinization of arable land is expected to have devastating global effects, resulting in 30% land loss within the next 25 years, and up to 50% by the year 2050. Therefore, breeding for drought and salinity stress tolerance in crop plants (for food supply) and in forest trees (a central component of the global ecosystem) should be given high research priority in plant biotechnology programs. Molecular control mechanisms for abiotic stress tolerance are based on the activation and regulation of specific stress-related genes. These genes are involved in the whole sequence of stress responses, such as signaling, transcriptional control, protection of membranes and proteins, and free-radical and toxic-compound scavenging. Recently, research into the molecular mechanisms of stress responses has started to bear fruit and, in parallel, genetic modification of stress tolerance has also shown promising results that may ultimately apply to agriculturally and ecologically important plants. The present review summarizes the recent advances in elucidating stress-response mechanisms and their biotechnological applications. Emphasis is placed on transgenic plants that have been engineered based on different stress-response mechanisms. The review examines the following aspects: regulatory controls, metabolite engineering, ion transport, antioxidants and detoxification, late embryogenesis abundant (LEA) and heat-shock proteins.
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              Unmanned aerial systems for photogrammetry and remote sensing: A review

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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
                30 June 2017
                2017
                : 8
                : 1111
                Affiliations
                [1] 1Key Laboratory of Quantitative Remote Sensing in Agriculture of Ministry of Agriculture P. R. China, Beijing Research Center for Information Technology in Agriculture Beijing, China
                [2] 2National Engineering Research Center for Information Technology in Agriculture Beijing, China
                [3] 3Key Laboratory of Agri-informatics, Ministry of Agriculture Beijing, China
                [4] 4School of Civil Engineering and Geosciences, Newcastle University Newcastle upon Tyne, United Kingdom
                [5] 5Crop Reduction Systems Research Unit, United States Department of Agriculture-Agricultural Research Service Stoneville, NC, United States
                [6] 6Wheat Breeding Department, Institute of Agricultural Sciences for Lixiahe Region Jiangsu, China
                [7] 7National Center for Soybean Improvement, Nanjing Agricultural University Nanjing, China
                [8] 8Maize Research Center, Beijing Academy of Agriculture and Forestry Sciences Beijing, China
                Author notes

                Edited by: Marcello Mastrorilli, Consiglio per la Ricerca in agricoltura e l'analisi dell' Economia Agriaria (CREA), Italy

                Reviewed by: Bangyou Zheng, Commonwealth Scientific and Industrial Research Organisation (CSIRO), Australia; Wei Guo, University of Tokyo, Japan

                *Correspondence: Chunjiang Zhao zhaocj@ 123456nercita.org.cn

                This article was submitted to Crop Science and Horticulture, a section of the journal Frontiers in Plant Science

                †These authors have contributed equally to this work.

                ‡Co-first authors.

                Article
                10.3389/fpls.2017.01111
                5492853
                28713402
                559d25d3-ae11-49c2-b33e-40a1b5669512
                Copyright © 2017 Yang, Liu, Zhao, Li, Huang, Yu, Xu, Yang, Zhu, Zhang, Zhang, Feng, Zhao, Li, Li and Yang.

                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) or licensor 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
                : 09 April 2017
                : 08 June 2017
                Page count
                Figures: 9, Tables: 5, Equations: 0, References: 156, Pages: 26, Words: 19759
                Funding
                Funded by: National Natural Science Foundation of China 10.13039/501100001809
                Award ID: 61661136003
                Award ID: 41471285
                Award ID: 41471351
                Funded by: Ministry of Science and Technology of the People's Republic of China 10.13039/501100002855
                Award ID: 2016YFD0300602
                Funded by: Beijing Academy of Agricultural and Forestry Sciences 10.13039/501100007934
                Award ID: KJCX20170423
                Categories
                Plant Science
                Review

                Plant science & Botany
                uav,remote sensing,high-throughput,field phenotyping,crop breeding
                Plant science & Botany
                uav, remote sensing, high-throughput, field phenotyping, crop breeding

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