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Lettuce ( Lactuca sativa L.) Cultures and the Bioactivity of Their Root Microflora Are Affected by Amended Soil.

Konstantina MitsigiorgiGeorgia C NtroumpogianniEfstathios A KatsifasDimitris G HatzinikolaouKonstantinos ChassapisElisavet SkampaAikaterina L StefiNikolaos S Christodoulakis
Published in: Plants (Basel, Switzerland) (2024)
This study aimed to highlight the positive effects of various recycled organic substrates on lettuce plants ( Lactuca sativa L.) and to promote sustainable waste management practices, contributing to the concept of a circular economy. Over a two-month period, the growth potential and rhizosphere microflora of lettuce plants grown in soil amended with different recycled substrates were investigated. All data were compared, and the effects of the culture substrates were evaluated. All groups containing soil improvers offered a significant increase in the number of leaves per plant and, in two cases, an increase in dry biomass as well as an increase in the concentration of all leaf pigments. Both MDA and H 2 O 2 concentrations were the lowest in two groups containing soil improvers (VG 5% and PLUS 10%). At the end of the culture period, isolation and culture of bacteria from the plant rhizosphere were performed. Different bacterial strains were isolated and tested for the production of antimicrobial agents against six microbial indicators ( B. subtilis , E. coli , S. aureus , S. cerevisiae , C. albicans , and P. aeruginosa ). The greater percentage of the isolated strains showed an ability to inhibit the growth of the B. subtilis index. Most of the strains with antimicrobial activity were isolated from the soil samples of the plain soil group and the soil amended with the commercial fertilizer. Three of the isolated strains originating from the Ginagro 5% group are multiproducers as they inhibit the growth of three microbial indicators or more.
Keyphrases
  • plant growth
  • escherichia coli
  • microbial community
  • sewage sludge
  • primary care
  • staphylococcus aureus
  • risk assessment
  • candida albicans
  • cell death
  • high resolution
  • artificial intelligence