Machine Learning and FTIR for Predicting Yield in Agro-Industrial Waste Substrates of Pleurotus pulmonarius

First public release of the EB% prediction models in Pleurotus pulmonarius (Random Forest, Decision Trees, Bland-Altman)

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-09-24
DOI
https://doi.org/10.5281/zenodo.17194171
Primary Topic
Geochemistry and Geologic Mapping
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Machine Learning and FTIR for Predicting Yield in Agro-Industrial Waste Substrates of Pleurotus pulmonarius

Zenodo (CERN European Organization for Nuclear Research)
Geochemistry and Geologic Mapping
article

Machine Learning and FTIR for Predicting Yield in Agro-Industrial Waste Substrates of Pleurotus pulmonarius

article en

Abstract

First public release of the EB% prediction models in Pleurotus pulmonarius (Random Forest, Decision Trees, Bland-Altman)

Zenodo (CERN European Organization for Nuclear Research)
Industry, innovation and infrastructure, Responsible consumption and production
Openalex Percentile: Top 28%
Geochemistry and Geologic Mapping
DOIOpen Access PDFOpenAlex
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Machine Learning and FTIR for Predicting Yield in Agro-Industrial Waste Substrates of Pleurotus pulmonarius · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS