Exploring the dynamics of remotely detected fluorescence transients from basil as a potential feedback for lighting control in greenhouses

Carstensen, Anna-Maria; Wik, Torsten; Bånkestad, Daniel; Pocock, Tessa

doi:10.17660/actahortic.2016.1134.49

Cited by 4 publications

(3 citation statements)

References 7 publications

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“…These two features alone were sufficient to distinguish between healthy and abiotically stressed plants (drought and salt stress investigated), where faster dynamics (shorter peak time) and a higher normalized peak value were found to be indicators of stress. This stress response is also in agreement with the light stress experiments by Carstensen et al [30,31]. Hence, we concluded that abiotic stress (salt and drought) could be distinguished from healthy plants using DFR.…”

Section: Discussionsupporting

confidence: 92%

“…The aim with this study was to test the hypothesis that it is possible to distinguish between healthy and stressed plants from variations in the dynamic fluorescence response (DFR). The DFR method applied here to detect stress is a modification of the method proposed in Carstensen et al to analyse the level of light stress [31]. In that work, transfer function responses were fitted to the step responses, and then the transfer functions were analysed in the frequency domain using Bode plots.…”

Section: Discussionmentioning

confidence: 99%

“…We have previously shown correlation with photosynthesis [26][27][28] and used it for growth tracking [29] and for light stress detection [30][31][32]. In the latter work, the variations in the DFR originating from a weak excitation from a blue LED light were used for light stress detection.…”

Section: Introductionmentioning

confidence: 99%

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Stress Detection Using Proximal Sensing of Chlorophyll Fluorescence on the Canopy Level

et al. 2021

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Chlorophyll fluorescence is interesting for phenotyping applications as it is rich in biological information and can be measured remotely and non-destructively. There are several techniques for measuring and analysing this signal. However, the standard methods use rather extreme conditions, e.g., saturating light and dark adaption, which are difficult to accommodate in the field or in a greenhouse and, hence, limit their use for high-throughput phenotyping. In this article, we use a different approach, extracting plant health information from the dynamics of the chlorophyll fluorescence induced by a weak light excitation and no dark adaption, to classify plants as healthy or unhealthy. To evaluate the method, we scanned over a number of species (lettuce, lemon balm, tomato, basil, and strawberries) exposed to either abiotic stress (drought and salt) or biotic stress factors (root infection using Pythium ultimum and leaf infection using Powdery mildew Podosphaera aphanis). Our conclusions are that, for abiotic stress, the proposed method was very successful, while, for powdery mildew, a method with spatial resolution would be desirable due to the nature of the infection, i.e., point-wise spread. Pythium infection on the roots is not visually detectable in the same way as powdery mildew; however, it affects the whole plant, making the method an interesting option for Pythium detection. However, further research is necessary to determine the limit of infection needed to detect the stress with the proposed method.

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Section: Discussionsupporting

confidence: 92%

Section: Discussionmentioning

confidence: 99%