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      Raman spectroscopy enables phenotyping and assessment of nutrition values of plants: a review

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          Abstract

          Our civilization has to enhance food production to feed world’s expected population of 9.7 billion by 2050. These food demands can be met by implementation of innovative technologies in agriculture. This transformative agricultural concept, also known as digital farming, aims to maximize the crop yield without an increase in the field footprint while simultaneously minimizing environmental impact of farming. There is a growing body of evidence that Raman spectroscopy, a non-invasive, non-destructive, and laser-based analytical approach, can be used to: (i) detect plant diseases, (ii) abiotic stresses, and (iii) enable label-free phenotyping and digital selection of plants in breeding programs. In this review, we critically discuss the most recent reports on the use of Raman spectroscopy for confirmatory identification of plant species and their varieties, as well as Raman-based analysis of the nutrition value of seeds. We show that high selectivity and specificity of Raman makes this technique ideal for optical surveillance of fields, which can be used to improve agriculture around the world. We also discuss potential advances in synergetic use of RS and already established imaging and molecular techniques. This combinatorial approach can be used to reduce associated time and cost, as well as enhance the accuracy of diagnostics of biotic and abiotic stresses.

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          Crop losses due to diseases and their implications for global food production losses and food security

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            Hyperspectral imaging – an emerging process analytical tool for food quality and safety control

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              Antibacterial cannabinoids from Cannabis sativa: a structure-activity study.

              Marijuana (Cannabis sativa) has long been known to contain antibacterial cannabinoids, whose potential to address antibiotic resistance has not yet been investigated. All five major cannabinoids (cannabidiol (1b), cannabichromene (2), cannabigerol (3b), Delta (9)-tetrahydrocannabinol (4b), and cannabinol (5)) showed potent activity against a variety of methicillin-resistant Staphylococcus aureus (MRSA) strains of current clinical relevance. Activity was remarkably tolerant to the nature of the prenyl moiety, to its relative position compared to the n-pentyl moiety (abnormal cannabinoids), and to carboxylation of the resorcinyl moiety (pre-cannabinoids). Conversely, methylation and acetylation of the phenolic hydroxyls, esterification of the carboxylic group of pre-cannabinoids, and introduction of a second prenyl moiety were all detrimental for antibacterial activity. Taken together, these observations suggest that the prenyl moiety of cannabinoids serves mainly as a modulator of lipid affinity for the olivetol core, a per se poorly active antibacterial pharmacophore, while their high potency definitely suggests a specific, but yet elusive, mechanism of activity.
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                Author and article information

                Contributors
                dkurouski@tamu.edu
                Journal
                Plant Methods
                Plant Methods
                Plant Methods
                BioMed Central (London )
                1746-4811
                15 July 2021
                15 July 2021
                2021
                : 17
                : 78
                Affiliations
                [1 ]GRID grid.264756.4, ISNI 0000 0004 4687 2082, Department of Biochemistry and Biophysics, , Texas A&M University, ; College Station, TX 77843 USA
                [2 ]GRID grid.264756.4, ISNI 0000 0004 4687 2082, Department of Biomedical Engineering, , Texas A&M University, ; College Station, TX 77843 USA
                Author information
                http://orcid.org/0000-0002-6040-4213
                Article
                781
                10.1186/s13007-021-00781-y
                8281483
                34266461
                d42e087f-629e-4c14-bc5c-1b95b30c8a67
                © The Author(s) 2021

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 10 March 2021
                : 11 July 2021
                Funding
                Funded by: Texas A and M University-Central Texas (US)
                Award ID: startup funds
                Award Recipient :
                Categories
                Review
                Custom metadata
                © The Author(s) 2021

                Plant science & Botany
                digital farming,raman spectroscopy,phenotyping,nutrition value identification

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