Evidence map›Paper›PMID 36837662›Full record

ArticleMembranes2023

Influence of Molasses Residue on Treatment of Cow Manure in an Anaerobic Filter with Perforated Weed Membrane and a Conventional Reactor: Variations of Organic Loading and a Machine Learning Application.

Khairina Jaman, Syazwani Idrus, Abdul Malek Abdul Wahab, Razif Harun, Nik Norsyahariati Nik Daud, Amimul Ahsan, Shahriar Shams, Md Alhaz Uddin

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Membranes, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.9field-weighted citation impact, top 30% of its field
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

0 citing papers in PubMed, 8 citations in OpenAlex.

No citing paper in PubMed yet.

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

8 authors at 5 institutions in 5 countries.

Khairina JamanDepartment of Civil Engineering, Faculty of Engineering, Universiti Putra Malaysia, Serdang 43400, Malaysia.
Syazwani IdrusDepartment of Civil Engineering, Faculty of Engineering, Universiti Putra Malaysia, Serdang 43400, Malaysia.ORCID 0000-0003-1318-4040
Abdul Malek Abdul WahabSchool of Mechanical Engineering, College of Engineering, Universiti Teknologi MARA, Shah Alam 40450, Malaysia.ORCID 0000-0003-0605-4117
Razif HarunDepartment of Chemical and Environmental Engineering, Faculty of Engineering, Universiti Putra Malaysia, Serdang 43400, Malaysia.
Nik Norsyahariati Nik DaudDepartment of Civil Engineering, Faculty of Engineering, Universiti Putra Malaysia, Serdang 43400, Malaysia.ORCID 0000-0003-0021-3893
Amimul AhsanDepartment of Civil and Environmental Engineering, Islamic University of Technology (IUT), Gazipur 1704, Bangladesh.
Shahriar ShamsFaculty of Engineering, Universiti Teknologi Brunei, Gadong BE1410, Brunei.ORCID 0000-0001-6233-5365
Md Alhaz UddinDepartment of Civil Engineering, College of Engineering, Jouf University, Sakaka 42421, Saudi Arabia.ORCID 0000-0002-1040-6034
Universiti Putra Malaysia · MYJouf University · SASwinburne University of Technology · AUUniversiti Teknologi Brunei · BNUniversiti Teknologi MARA · MY

Funding

Universiti Putra Malaysia 9713000
6 · The paper itself

Abstract

This study highlighted the influence of molasses residue (MR) on the anaerobic treatment of cow manure (CM) at various organic loading and mixing ratios of these two substrates. Further investigation was conducted on a model-fitting comparison between a kinetic study and an artificial neural network (ANN) using biomethane potential (BMP) test data. A continuous stirred tank reactor (CSTR) and an anaerobic filter with a perforated membrane (AF) were fed with similar substrate at the organic loading rates of (OLR) 1 to OLR 7 g/L/day. Following the inhibition signs at OLR 7 (50:50 mixing ratio), 30:70 and 70:30 ratios were applied. Both the CSTR and the AF with the co-digestion substrate (CM + MR) successfully enhanced the performance, where the CSTR resulted in higher biogas production (29 L/d), SMP (1.24 LCH

Indexed as

artificial neural networkbiomethane potential testcarbon/nitrogen ratioelectrical energy yieldkinetic modelssugar content

Identifiers

PMID36837662
PMCPMC9966026
OpenAlexW4318472841

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.