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Controlled mechanical stimuli reveal novel associations between basil metabolism and sensory quality
School of Science and Technology, Örebro University, Örebro, Sweden. (Man-Technology-Environment Research Centre)
Örebro University, School of Hospitality, Culinary Arts & Meal Science.ORCID iD: 0000-0003-3762-483X
Örebro University, School of Science and Technology. Department of Radiation Sciences, Radiation Physics, Umeå University, Umeå, Sweden. (Centre for Applied Autonomous Sensor Systems)ORCID iD: 0000-0003-4685-379X
School of Science and Technology, Örebro University, Örebro, Sweden; Department of Radiation Sciences, Radiation Physics, Umeå University, Umeå, Sweden. (Centre for Applied Autonomous Sensor Systems)
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2022 (English)In: Food Chemistry, ISSN 0308-8146, E-ISSN 1873-7072, Vol. 404, no Pt A, article id 134545Article in journal (Refereed) Published
Abstract [en]

There is an increasing interest in the use of automation in plant production settings. Here, we employed a robotic platform to induce controlled mechanical stimuli (CMS) aiming to improve basil quality. Semi-targeted UHPLC-qToF-MS analysis of organic acids, amino acids, phenolic acids, and phenylpropanoids revealed changes in basil secondary metabolism under CMS, which appear to be associated with changes in taste, as revealed by different means of sensory evaluation (overall liking, check-all-that-apply, and just-about-right analysis). Further network analysis combining metabolomics and sensory data revealed novel links between plant metabolism and sensory quality. Amino acids and organic acids including maleic acid were negatively associated with basil quality, while increased levels of secondary metabolites, particularly linalool glucoside, were associated with improved basil taste. In summary, by combining metabolomics and sensory analysis we reveal the potential of automated CMS on crop production, while also providing new associations between plant metabolism and sensory quality.

Place, publisher, year, edition, pages
Elsevier, 2022. Vol. 404, no Pt A, article id 134545
Keywords [en]
Agricultural robotics, Linalool glucoside, Network analysis, Plant metabolomics, Sensomics, Sensory analysis
National Category
Robotics
Identifiers
URN: urn:nbn:se:oru:diva-101814DOI: 10.1016/j.foodchem.2022.134545ISI: 000873921900006PubMedID: 36252376Scopus ID: 2-s2.0-85139833699OAI: oai:DiVA.org:oru-101814DiVA, id: diva2:1704400
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Örebro University
Note

Funding agency:

German Academic Exchange Service (Deutscher Akademischer Austauschdienst, DAAD)

Available from: 2022-10-18 Created: 2022-10-18 Last updated: 2022-11-15Bibliographically approved

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Herdenstam, Anders P. F.Kurtser, PolinaCastro Alves, VictorHyötyläinen, TuuliaAndreasson, Henrik

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Herdenstam, Anders P. F.Kurtser, PolinaCastro Alves, VictorHyötyläinen, TuuliaAndreasson, Henrik
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School of Hospitality, Culinary Arts & Meal ScienceSchool of Science and Technology
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Food Chemistry
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