Theoretical and Natural Science

- The Open Access Proceedings Series for Conferences


Theoretical and Natural Science

Vol. 6, 03 August 2023


Open Access | Article

Research on the types of environmental-friendly vegetables

Yilin Jiang 1 , Yijiang Tian * 2 , Yanxi Yu 3
1 The University of California Davis
2 The University of California Santa Barbara
3 The Barstow School Ningbo Campus

* Author to whom correspondence should be addressed.

Theoretical and Natural Science, Vol. 6, 484-491
Published 03 August 2023. © 2023 The Author(s). Published by EWA Publishing
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Citation Yilin Jiang, Yijiang Tian, Yanxi Yu. Research on the types of environmental-friendly vegetables. TNS (2023) Vol. 6: 484-491. DOI: 10.54254/2753-8818/6/20230214.

Abstract

Food production is an important factor in causing environmental pollution, and the processing of food contamination information data, classification, and ultimately rating of the degree of food contamination is an important way to recognize food contamination. Rating the environmental friendliness of food can help people to choose more environmentally friendly food in their daily life and allow companies, scholars, and research organizations to recognize which food can be reduced by technological advances. This study focuses on the contamination rating of foods that are most referenced to help scholars and people understand the environmental contamination capabilities of different foods. This study focuses on the different foods in the Kaggle data, and their contamination aspects of the data were processed. The study began with the classification of foods. This study uses data from Kaggle on various environmental pollutants of food. It uses the linear regression model in the R Studio to select the most suitable pollution objects for evaluation. Finally, this study scored different foods according to different contamination aspects and obtained the following results: 1) detailed food scoring graphs, 2) animal-based food has a greater total contamination capacity than plant-based food.

Keywords

environmental pollution, food production, linear regression.

References

1. Gaoming Jiang. Do you know how to produce the food you eat? China Academy of Sciences, 2021.

2. Xuxia Wang, Hongmei Shang. Pollution problems and preventive measures in apple production. Agricultural Planting Network, 2021.

3. Sandra Quijas, Patricia Balvanera. Biodiversity and ecosystem services. Science Direct, 2013.

4. Puja Mondal. Types of Environmental Impacts: Direct, Indirect, Cumulative, Induced Impact. Moi University, 2012.

5. Christina Hartmann, GiannA Lazzarini, Angela Funk, Michael Siegrist. Measuring consumers’ knowledge of the environmental impact of foods. 2021.

6. Palaniappa Krishnan. Environmental Impact of Food Production and Consumption. Bioresources Engineering Department, University of Delaware, 2018.

7. Hannah Ritchie, Max Roser. Environmental impact of food production. Oxford Martin School, University of Oxford, 2022.

8. Jiawen Dan. Scientific and technologies progress is an important means to solve ecological and environmental problems. Hunan Polytechnic of Environment and Biology, 2019.

9. Wanming Hu. Research on environmental pollution control technology in food production. Food Safety Guide, 2020.

10. UN News. Food systems account for over one-third of global greenhouse has emissions. United Nations, 2021.

Data Availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. Authors who publish this series agree to the following terms:

1. Authors retain copyright and grant the series right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this series.

2. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the series's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this series.

3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See Open Access Instruction).

Volume Title
Proceedings of the International Conference on Modern Medicine and Global Health (ICMMGH 2023)
ISBN (Print)
978-1-915371-65-2
ISBN (Online)
978-1-915371-66-9
Published Date
03 August 2023
Series
Theoretical and Natural Science
ISSN (Print)
2753-8818
ISSN (Online)
2753-8826
DOI
10.54254/2753-8818/6/20230214
Copyright
03 August 2023
Open Access
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited

Copyright © 2023 EWA Publishing. Unless Otherwise Stated