Evidence map›Paper›PMID 37447788›Full record

ArticleSensors (Basel, Switzerland)2023

Determining the Nutrient Content of Hydroponically-Cultivated Microgreens with Immersible Silicon Photonic Sensors: A Preliminary Feasibility Study.

Aristi Christofi, Georgia Margariti, Alexandros Salapatas, George Papageorgiou, Panagiotis Zervas, Pythagoras Karampiperis, Antonis Koukourikos, Petros A Tarantilis, Eleftheria H Kaparakou, Konstantinos Misiakos and 1 more

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Aristi ChristofiInstitute of Nanoscience and Nanotechnology, NCSR "Demokritos", 153 41 Athens, Greece.
Georgia MargaritiInstitute of Nanoscience and Nanotechnology, NCSR "Demokritos", 153 41 Athens, Greece.
Alexandros SalapatasInstitute of Nanoscience and Nanotechnology, NCSR "Demokritos", 153 41 Athens, Greece.
George PapageorgiouInstitute of Nanoscience and Nanotechnology, NCSR "Demokritos", 153 41 Athens, Greece.
Panagiotis ZervasSCiO P.C., 153 10 Agia Paraskevi, Greece.ORCID 0000-0002-6531-4022
Pythagoras KarampiperisSCiO P.C., 153 10 Agia Paraskevi, Greece.
Antonis KoukourikosSCiO P.C., 153 10 Agia Paraskevi, Greece.
Petros A TarantilisLaboratory of Chemistry, Department of Food Science and Human Nutrition, School of Food and Nutritional Sciences, Agricultural University of Athens, 118 55 Athens, Greece.ORCID 0000-0002-5853-4780
Eleftheria H KaparakouLaboratory of Chemistry, Department of Food Science and Human Nutrition, School of Food and Nutritional Sciences, Agricultural University of Athens, 118 55 Athens, Greece.ORCID 0000-0002-9266-348X
Konstantinos MisiakosInstitute of Nanoscience and Nanotechnology, NCSR "Demokritos", 153 41 Athens, Greece.
Eleni MakaronaInstitute of Nanoscience and Nanotechnology, NCSR "Demokritos", 153 41 Athens, Greece.ORCID 0000-0002-5115-5518

Funding

EU Horizon 2020, ERA-NET Co-fund ICT-AGRI-FOOD 86266
6 · The paper itself

Abstract

Microgreens have gained attention for their exceptional culinary characteristics and high nutritional value. The present study focused on a novel approach for investigating the easy extraction of plant samples and the utilization of immersible silicon photonic sensors to determine, on the spot, the nutrient content of microgreens and their optimum time of harvest. For the first time, it was examined how these novel sensors can capture time-shifting spectra caused by the molecules' dynamic adhesion onto the sensor surface. The experiment involved four types of microgreens (three types of basil and broccoli) grown in a do-it-yourself hydroponic installation. The sensors successfully distinguished between different plant types, showcasing their discriminative capabilities. To determine the optimum harvest time, this study compared the sensor data with results obtained through standard analytical methods. Specifically, the total phenolic content and antioxidant activity of two basil varieties were juxtaposed with the sensor data, and this study concluded that the ideal harvest time for basil microgreens was 14 days after planting. This finding highlights the potential of the immersible silicon photonic sensors for potentially replacing time-consuming analytical techniques. By concentrating on obtaining plant extracts, capturing time-shifting spectra, and assessing sensor reusability, this research paves the way for future advancements in urban farming.

Indexed as

BrassicaSiliconAntioxidantsFeasibility StudiesNutrientsAntioxidantsNutrientsSiliconantioxidant activitybasilhydroponicsmicrogreensoptical biosensorsphotonic circuitsreal-time spectral analysistotal phenolic contenturban farming

Identifiers

PMID37447788
PMCPMC10346951

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.