Solid state treatment with Lactobacillus paracasei subsp. paracasei BGHN14 and Lactobacillus rhamnosus BGT10 improves nutrient bioavailability in granular fish feed

PLoS One. 2019 Jul 11;14(7):e0219558. doi: 10.1371/journal.pone.0219558. eCollection 2019.

Abstract

The aim of this research was to improve nutritive value of fishmeal-based feed by lactobacilli in order to achieve satisfactory nutrient availability needed to support fish development. Feed was solid-state treated at a laboratory scale with the combination of Lactobacillus paracasei subsp. paracasei BGHN14 and Lactobacillus rhamnosus BGT10 in different experimental settings, which included the variation of strain ratio, total lactobacilli concentration, percentage of moisture and duration of incubation. Short peptides, soluble proteins, phospho-, neutral and unsaturated lipids were quantified. Differences among treated and control feeds were evaluated by Student t-test, while Gaussian process regression (GPR) modeling was employed to simulate the incubation process and define the optimal treatment combination in the context of overall feed nutritional profile. Treatment duration was shown to be the critical determinant of final outcome, either as single factor or via interaction with strain ratio. Optimal nutrient balance was achieved with 12 h incubation period, 260% moisture, 75:25 and 50:50 BGHN14:BGT10 ratios and 200 mg of lactobacilli per g of dry feed. This study should serve as the basis for large-scale tests which would simulate on-farm production of both fishmeal-based and unconventional, lower cost aquafeed with added value.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animal Feed*
  • Animals
  • Biological Availability
  • Fishes / physiology*
  • Lacticaseibacillus paracasei / metabolism*
  • Lacticaseibacillus rhamnosus / metabolism*
  • Nutritive Value
  • Probiotics / metabolism
  • Seafood / microbiology

Grants and funding

This research has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 652831 (AQUAEXCEL2020), https://ec.europa.eu/programmes/horizon2020/, European Regional and Development Fund and the Government of Hungary within the project GINOP-2.3.2-15-2016-00025, http://www.kormany.hu/en, https://ec.europa.eu/regional_policy/en/funding/erdf/, and by the National project No. 173019 of the Ministry of Education, Science and Technological Development of the Republic of Serbia, http://www.mpn.gov.rs/. This output reflects only the author’s view and the funders cannot be held responsible for any use that may be made of the information contained therein. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.