Evidence map›Paper›PMID 37682509›Full record

ArticleApplied biochemistry and biotechnology2024

Improving Biohydrogen Production by Dark Fermentation of Milk Processing Wastewater by Physicochemical and Enzymatic Pretreatments.

Esma Mahfouf Bouchareb, Kerroum Derbal, Rayane Bedri, Khaled Slimani, Souha Menas, Halima Lazreg, Feriel Maaref, Samir Ouabdelkader, Aya Saheb, Rokaya Bouaita and 2 more

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Article in Applied biochemistry and biotechnology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

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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

2 citing papers in PubMed.

  1. Review
  2. Evaluation of hydraulic retention time on hydrogen production from corn industry wastewater by dark fermentation.Water science and technology : a journal of the International Association on Water Pollution Research · 2025
    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

12 authors.

Esma Mahfouf BoucharebDepartment of Environmental Engineering, Process Engineering Faculty, Saleh Boubnider University, 25000, Constantine, Algeria.
Kerroum DerbalLaboratory of Process Engineering for Sustainable Development and Health Products (LGPDDPS), National Polytechnic School of Constantine, 25000, Constantine, Algeria.
Rayane BedriDepartment of Engineering, National High School of Biotechnology, Toufik Khaznadar, Constantine 3, Algeria.
Khaled SlimaniDepartment of Engineering, National High School of Biotechnology, Toufik Khaznadar, Constantine 3, Algeria.
Souha MenasDepartment of Engineering, National High School of Biotechnology, Toufik Khaznadar, Constantine 3, Algeria.
Halima LazregDepartment of Engineering, National High School of Biotechnology, Toufik Khaznadar, Constantine 3, Algeria.
Feriel MaarefDepartment of Engineering, National High School of Biotechnology, Toufik Khaznadar, Constantine 3, Algeria.
Samir OuabdelkaderDepartment of Engineering, National High School of Biotechnology, Toufik Khaznadar, Constantine 3, Algeria.
Aya SahebDepartment of Engineering, National High School of Biotechnology, Toufik Khaznadar, Constantine 3, Algeria.
Rokaya BouaitaDepartment of Process Engineering, National High School of Polytechnic, Malek Bennabi, Constantine 3, Algeria.
Raouf BoucharebDepartment of Environmental Engineering, Process Engineering Faculty, Saleh Boubnider University, 25000, Constantine, Algeria.
Nadir DizgeDepartment of Environmental Engineering, Mersin University, 33343, Mersin, Turkey. nadirdizge@gmail.com.tr.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Biohydrogen is considered an alternative energy reserve. Dark fermentation is one of the important green hydrogen production techniques that utilizes organic waste as raw material. It is a promising bioconversion, easy, not expensive, and cost-effective process. Milk processing wastewater (MPWW) is an organic effluent generated in large volumes on a daily basis and disposed directly into the environment. In this research, the study of biochemical hydrogen potential (BHP) test of MPWW was evaluated and used as substrate (S). A waste sludge was used as an inoculum (I) and source of bacteria. Both substrate and inoculum were analyzed and the study was based mainly on the ratio of volatile solids (VS) of inoculum and substrate subsequently, which was noted as I/S. Different substrate pretreatments were performed: ultrasonic, thermal, chemical, and enzymatic hydrolysis. The I/S ratio impact was investigated and evaluated the hydrogen production improvement. Modified Gompertz and modified Logistic kinetic models were employed for the kinetic modeling of cumulative hydrogen production values. Results show that I/S ratio of 1/4 gVS/gVS resulted from the best hydrogen production of 59.96 mL during 30 days of MPWW fermentation without pretreatment. It was also shown that all the adopted pretreatments enhanced hydrogen production, whereas ultrasonic pretreatment for 5 min increased the production by only 14.84%. Heat pretreatment was more efficient, where the hydrogen production increased from 60 to 162 mL (170% of improvement) using heat shock at 90 °C for 30 min. The impact of chemical pretreatment was different from a reagent to another. Pretreatment using calcium hydroxide resulted in the biggest hydrogen production of 165.3 mL (175.5%) compared to the other chemical pretreatments. However, the best hydrogen production was given by the biological pretreatment using enzymatic hydrolysis (Lactase) resulting in 254 mL of hydrogen production, which is equivalent to 323.62% of production improvement. Modified Gompertz and Logistic kinetic models fitted well with experimental data. Thus, the enzymatic hydrolysis of MPWW proved to be a promising technique for biohydrogen production enhancement.

Indexed as

FermentationHydrogenWastewaterAnimalsHydrolysisKineticsMilkHydrogenWastewaterBHP testBiohydrogenEnzymatic pretreatmentLactasePhysicochemical pretreatment

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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.