Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Pedigree Analysis01:35

Pedigree Analysis

84.6K
Overview
84.6K
Bioremediation00:46

Bioremediation

19.6K
Bioremediation is the use of prokaryotes, fungi, or plants to remove pollutants from the environment. This process has been used to remove harmful toxins in groundwater as a byproduct of agricultural run-off and also to clean up oil spills.
19.6K
Survival Tree01:19

Survival Tree

129
Survival trees are a non-parametric method used in survival analysis to model the relationship between a set of covariates and the time until an event of interest occurs, often referred to as the "time-to-event" or "survival time." This method is particularly useful when dealing with censored data, where the event has not occurred for some individuals by the end of the study period, or when the exact time of the event is unknown.
 Building a Survival Tree
Constructing a...
129
Bar Graph01:07

Bar Graph

16.9K
A bar graph is also called a bar chart and consists of bars that are separated from each other. It either uses horizontal or vertical bars to show comparisons among categories. The bars can be rectangles, or they can be rectangular boxes (used in three-dimensional plots). One axis of the graph represents the specific categories being compared, and the other axis shows a discrete value. In this graph, the length of the bar for each category is proportional to the number or percent of individuals...
16.9K
Multiple Bar Graph01:07

Multiple Bar Graph

5.4K
As the name suggests, a multiple bar graph is the same as a bar graph but has multiple bars to depict relationships between different data values. One can include as many parameters as possible. However, each parameter must have the same unit of measurement.
Each bar or column in the multiple bar graph represents a data value. These graphs are used primarily in interrelating two or more sets of data. The categories of different kinds of data are listed along the horizontal or x-axis, whereas...
5.4K
pV-Diagrams01:18

pV-Diagrams

4.3K
The pV diagram, which is a graph of pressure versus volume of the gas under study, is helpful in describing certain aspects of the substance. When the substance behaves like an ideal gas, the ideal gas equation describes the relationship between its pressure and volume. On a pV diagram, it is common to plot an isotherm, which is a curve showing p as a function of V with the number of molecules and the temperature fixed. Then, for an ideal gas, the product of the pressure of the gas and its...
4.3K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Turning Motion into Methane: Electromagnetic Induction in Microbial Aggregates Enhances Wastewater Resource Recovery.

Environmental science & technology·2026
Same author

Fulvic acid enhances lettuce stress tolerance: Molecular mechanisms and in situ changes of lignin.

Bioresource technology·2026
Same author

Lipid metabolism and autophagy maintain cellular homeostasis under chloroplast dysfunction in Chlamydomonas reinhardtii.

The New phytologist·2026
Same author

Molecular and toxicological study of the plasticizers exposure-induced metabolic disorders.

Environmental pollution (Barking, Essex : 1987)·2026
Same author

Using machine learning to deeply analyze the critical role of trace element additives in anaerobic digestion and guide the optimization of addition strategies.

Water research·2025
Same author

Co-application of porous biochar and Fe<sub>2</sub>O<sub>3</sub> in cattle manure and wheat straw composting: mechanistic insights into greenhouse gas mitigation and nitrogen transformation.

Journal of environmental management·2025

Related Experiment Video

Updated: Aug 9, 2025

Physical, Chemical and Biological Characterization of Six Biochars Produced for the Remediation of Contaminated Sites
09:39

Physical, Chemical and Biological Characterization of Six Biochars Produced for the Remediation of Contaminated Sites

Published on: November 28, 2014

35.2K

Tree-based machine learning model for visualizing complex relationships between biochar properties and anaerobic

Yi Zhang1, Yijing Feng1, Zhonghao Ren1

  • 1State Key Laboratory of Heavy Oil Processing, Beijing Key Laboratory of Biogas Upgrading Utilization, College of New Energy and Materials, China University of Petroleum Beijing (CUPB), Beijing 102249, PR China.

Bioresource Technology
|February 22, 2023
PubMed
Summary
This summary is machine-generated.

Machine learning models predict optimal biochar properties for enhanced anaerobic digestion. Key factors like particle size and oxygen content maximize methane yield and production rates.

Keywords:
Anaerobic digestionBiocharMachine learningMethane production

More Related Videos

Author Spotlight: Understanding Riverine Nitrogen Impacts and Primary Productivity for Effective Nutrient Management
05:04

Author Spotlight: Understanding Riverine Nitrogen Impacts and Primary Productivity for Effective Nutrient Management

Published on: July 14, 2023

449
Evaluation of Integrated Anaerobic Digestion and Hydrothermal Carbonization for Bioenergy Production
07:34

Evaluation of Integrated Anaerobic Digestion and Hydrothermal Carbonization for Bioenergy Production

Published on: June 15, 2014

25.6K

Related Experiment Videos

Last Updated: Aug 9, 2025

Physical, Chemical and Biological Characterization of Six Biochars Produced for the Remediation of Contaminated Sites
09:39

Physical, Chemical and Biological Characterization of Six Biochars Produced for the Remediation of Contaminated Sites

Published on: November 28, 2014

35.2K
Author Spotlight: Understanding Riverine Nitrogen Impacts and Primary Productivity for Effective Nutrient Management
05:04

Author Spotlight: Understanding Riverine Nitrogen Impacts and Primary Productivity for Effective Nutrient Management

Published on: July 14, 2023

449
Evaluation of Integrated Anaerobic Digestion and Hydrothermal Carbonization for Bioenergy Production
07:34

Evaluation of Integrated Anaerobic Digestion and Hydrothermal Carbonization for Bioenergy Production

Published on: June 15, 2014

25.6K

Area of Science:

  • Environmental Science
  • Biotechnology
  • Chemical Engineering

Background:

  • Optimizing anaerobic digestion (AD) with biochar requires understanding complex interactions.
  • Varied experimental goals hinder comprehensive study of biochar properties in AD.

Purpose of the Study:

  • To develop predictive models for biochar's impact on AD.
  • To identify key biochar properties influencing methane production.

Main Methods:

  • Employed three tree-based machine learning models.
  • Utilized gradient boosting decision trees for prediction.
  • Performed feature analysis to determine influential parameters.

Main Results:

  • Achieved R-squared values of 0.84 for methane yield and 0.69 for maximum methane production rate.
  • Identified digestion time and particle size as significant factors.
  • Determined optimal conditions: 0.3-0.5 mm particle size, ~290 m²/g surface area, >31% O content, >20 g/L biochar addition.

Conclusions:

  • Tree-based machine learning effectively models biochar-AD interactions.
  • Provides insights into optimizing biochar for enhanced anaerobic digestion.
  • Identifies specific biochar characteristics for maximizing methane production.