Lettuce (Lactuca sativa) productivity influenced by microbial inocula under nitrogen-limited conditions in aquaponics

Abstract

The demand for food will outpace productivity of conventional agriculture due to projected growth of the human population, concomitant with shrinkage of arable land, increasing scarcity of freshwater, and a rapidly changing climate. While aquaponics has potential to sustainably supplement food production with minimal environmental impact, there is a need to better characterize the complex interplay between the various components (fish, plant, microbiome) of these systems to optimize scale up and productivity. Here, we investigated how the commonly-implemented practice of continued microbial community transfer from pre-existing systems might promote or impede productivity of aquaponics. Specifically, we monitored plant growth phenotypes, water chemistry, and microbiome composition of rhizospheres, biofilters, and fish feces over 61-days of lettuce (Lactuca sativa var. crispa) growth in nitrogen-limited aquaponic systems inoculated with bacteria that were either commercially sourced or originating from a pre-existing aquaponic system. Lettuce above- and below-ground growth were significantly reduced across replicates treated with a pre-existing aquaponic system inoculum when compared to replicates treated with a commercial inoculum. Reduced productivity was associated with enrichment in specific bacterial genera in plant roots, including Pseudomonas, following inoculum transfer from pre-existing systems. Increased productivity was associated with enrichment of nitrogen-fixing Rahnella in roots of plants treated with the commercial inoculum. Thus, we show that inoculation from a pre-existing system, rather than from a commercial inoculum, is associated with lower yields. Further work will be necessary to test the putative mechanisms involved.

Gluconacetobacter diazotrophicus Inoculation of Two Lettuce Cultivars Affects Leaf and Root Growth under Hydroponic Conditions

“…Conversely, under nitrogen deprivation conditions where lettuce yields are significantly reduced, bacterial nitrogen fixation may alleviate some of the nutrient deficiency impairing growth, as has been demonstrated in aquaponic lettuce inoculated with N-fixing Rahnella [50]. Endophyte-sourced plant growth-regulating hormones can increase the production of both above ground and below ground biomass as has been shown in carrot leaf and taproot [23] as well as beetroot [24].…”

Produção integrada de tambaqui com hortaliças em residência urbana

“…Com isso, acreditamos que a melhor taxa de estocagem para tambaquis em sistemas de aquaponia, com 1m³ de água seja de 20 animais na fase de recria e engorda. Os parâmetros ligados ao desempenho produtivo de peixes em sistemas de aquaponia é dependente e pode variar de acordo com diferentes fatores, como por exemplo, fase de desenvolvimento que se encontram os animais, estado fisiológico e de saúde dos animais, taxa de estocagem, valore nutricional e quantidade de ração/alimento oferecida, além da garantia das características de qualidade de água e fatores abióticos do ambiente aquático existentes (Facundes Silva et al, 2020;Oliveira et al, 2020;Maucieri et al, 2019;Day et al 2021;Kralik et al, 2022) Analisando o crescimento do tambaqui integrado à hidroponia em um período de 110 dias, Facundo Silva e colaboradores (2020) mostraram que os animais apresentaram peso médio de 67,28, mantidos na densidade de 50 peixes/m³.…”

“…Após isso, foi observado o melhor desenvolvimento das hortaliças dentro do sistema aquaponico. Outros estudos também relataram resultados não satisfatórios quanto ao desenvolvimento de hortaliças em sistemas de aquaponia (Facundes Silva et al, 2020;Maucieri et al, 2019;Pinho et al, 2018;Day et al, 2021).…”

Growth phase estimation for abundant bacterial populations sampled longitudinally from human stool metagenomes

“…We were able to identify signatures of specific growth phases in 20-40% of the abundant bacterial populations in the guts of these four individuals. We describe how our growth phase inference approach can serve to inform more accurate mechanistic modeling of flow-through ecosystems (e.g., community-scale metabolic models, which usually assume exponential growth), which could have broad implications for the gut microbiome and host health [8, 33, 34], flow-through agricultural systems [35, 36], climate change [35, 37, 38], and industrial bioreactor production processes [39, 40].…”

“…We describe how our growth phase inference approach can serve to improve statistical inferences derived from microbiome data and to inform more accurate mechanistic modeling of flow-through ecosystems (e.g., community-scale metabolic models, which usually assume exponential growth), which could have broad implications for human health 8,34,35 , agricultural systems 36,37 , climate change 36,38,39 , and industrial bioreactor production processes 40,41 .…”