Association between the Classification of the Genus of Batrachospermaceae (Rhodophyta) and the Environmental Factors Based on Machine Learning
Batrachospermaceae is the largest family of freshwater red algae, widely distributed around the world, and plays an important role in maintaining the balance of spring and creek ecosystems. The deterioration of the current global ecological environment has also destroyed the habitat of Batrachosperm...
| Main Authors: | , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2022-12-01
|
| Series: | Plants |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2223-7747/11/24/3485 |
| _version_ | 1797455671744004096 |
|---|---|
| author | Qiqin Yang Fangru Nan Xudong Liu Qi Liu Junping Lv Jia Feng Fei Wang Shulian Xie |
| author_facet | Qiqin Yang Fangru Nan Xudong Liu Qi Liu Junping Lv Jia Feng Fei Wang Shulian Xie |
| author_sort | Qiqin Yang |
| collection | DOAJ |
| description | Batrachospermaceae is the largest family of freshwater red algae, widely distributed around the world, and plays an important role in maintaining the balance of spring and creek ecosystems. The deterioration of the current global ecological environment has also destroyed the habitat of Batrachospermaceae. The research on the environmental factors of Batrachospermaceae and the accurate classification of the genus is necessary for the protection, restoration, excavation, and utilization of Batrachospermaceae resources. In this paper, the database of geographical distribution and environmental factors of Batrachospermaceae was sorted out, and the relationship between the classification of genus and environmental factors in Batrachospermaceae was analyzed based on two machine learning methods, random forest and XGBoost. The result shows: (1) The models constructed by the two machine learning methods can effectively distinguish the genus of Batrachospermaceae based on environmental factors; (2) The overall AUC score of the random forest model for the classification and prediction of the genus of Batrachospermaceae reached 90.41%, and the overall AUC score of the taxonomic prediction of each genus of Batrachospermaceae reached 85.85%; (3) Combining the two methods, it is believed that the environmental factors that affect the distinction of the genus of Batrachospermaceae are mainly altitude, average relative humidity, average temperature, and minimum temperature, among which altitude has the greatest influence. The results can further clarify the taxonomy of the genus in Batrachospermaceae and enrich the research on the differences in environmental factors of Batrachospermaceae. |
| first_indexed | 2024-03-09T15:56:42Z |
| format | Article |
| id | doaj.art-a4f83847b0264576ad976bee61ef026a |
| institution | Directory Open Access Journal |
| issn | 2223-7747 |
| language | English |
| last_indexed | 2024-03-09T15:56:42Z |
| publishDate | 2022-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Plants |
| spelling | doaj.art-a4f83847b0264576ad976bee61ef026a2023-11-24T17:28:07ZengMDPI AGPlants2223-77472022-12-011124348510.3390/plants11243485Association between the Classification of the Genus of Batrachospermaceae (Rhodophyta) and the Environmental Factors Based on Machine LearningQiqin Yang0Fangru Nan1Xudong Liu2Qi Liu3Junping Lv4Jia Feng5Fei Wang6Shulian Xie7Shanxi Key Laboratory for Research and Development of Regional Plants, School of Life Science, Shanxi University, Taiyuan 030006, ChinaShanxi Key Laboratory for Research and Development of Regional Plants, School of Life Science, Shanxi University, Taiyuan 030006, ChinaShanxi Key Laboratory for Research and Development of Regional Plants, School of Life Science, Shanxi University, Taiyuan 030006, ChinaShanxi Key Laboratory for Research and Development of Regional Plants, School of Life Science, Shanxi University, Taiyuan 030006, ChinaShanxi Key Laboratory for Research and Development of Regional Plants, School of Life Science, Shanxi University, Taiyuan 030006, ChinaShanxi Key Laboratory for Research and Development of Regional Plants, School of Life Science, Shanxi University, Taiyuan 030006, ChinaSchool of Physical Education, Shanxi University, Taiyuan 030006, ChinaShanxi Key Laboratory for Research and Development of Regional Plants, School of Life Science, Shanxi University, Taiyuan 030006, ChinaBatrachospermaceae is the largest family of freshwater red algae, widely distributed around the world, and plays an important role in maintaining the balance of spring and creek ecosystems. The deterioration of the current global ecological environment has also destroyed the habitat of Batrachospermaceae. The research on the environmental factors of Batrachospermaceae and the accurate classification of the genus is necessary for the protection, restoration, excavation, and utilization of Batrachospermaceae resources. In this paper, the database of geographical distribution and environmental factors of Batrachospermaceae was sorted out, and the relationship between the classification of genus and environmental factors in Batrachospermaceae was analyzed based on two machine learning methods, random forest and XGBoost. The result shows: (1) The models constructed by the two machine learning methods can effectively distinguish the genus of Batrachospermaceae based on environmental factors; (2) The overall AUC score of the random forest model for the classification and prediction of the genus of Batrachospermaceae reached 90.41%, and the overall AUC score of the taxonomic prediction of each genus of Batrachospermaceae reached 85.85%; (3) Combining the two methods, it is believed that the environmental factors that affect the distinction of the genus of Batrachospermaceae are mainly altitude, average relative humidity, average temperature, and minimum temperature, among which altitude has the greatest influence. The results can further clarify the taxonomy of the genus in Batrachospermaceae and enrich the research on the differences in environmental factors of Batrachospermaceae.https://www.mdpi.com/2223-7747/11/24/3485Batrachospermaceaeenvironmental factorsmachine learningrandom forestXGBoost |
| spellingShingle | Qiqin Yang Fangru Nan Xudong Liu Qi Liu Junping Lv Jia Feng Fei Wang Shulian Xie Association between the Classification of the Genus of Batrachospermaceae (Rhodophyta) and the Environmental Factors Based on Machine Learning Plants Batrachospermaceae environmental factors machine learning random forest XGBoost |
| title | Association between the Classification of the Genus of Batrachospermaceae (Rhodophyta) and the Environmental Factors Based on Machine Learning |
| title_full | Association between the Classification of the Genus of Batrachospermaceae (Rhodophyta) and the Environmental Factors Based on Machine Learning |
| title_fullStr | Association between the Classification of the Genus of Batrachospermaceae (Rhodophyta) and the Environmental Factors Based on Machine Learning |
| title_full_unstemmed | Association between the Classification of the Genus of Batrachospermaceae (Rhodophyta) and the Environmental Factors Based on Machine Learning |
| title_short | Association between the Classification of the Genus of Batrachospermaceae (Rhodophyta) and the Environmental Factors Based on Machine Learning |
| title_sort | association between the classification of the genus of batrachospermaceae rhodophyta and the environmental factors based on machine learning |
| topic | Batrachospermaceae environmental factors machine learning random forest XGBoost |
| url | https://www.mdpi.com/2223-7747/11/24/3485 |
| work_keys_str_mv | AT qiqinyang associationbetweentheclassificationofthegenusofbatrachospermaceaerhodophytaandtheenvironmentalfactorsbasedonmachinelearning AT fangrunan associationbetweentheclassificationofthegenusofbatrachospermaceaerhodophytaandtheenvironmentalfactorsbasedonmachinelearning AT xudongliu associationbetweentheclassificationofthegenusofbatrachospermaceaerhodophytaandtheenvironmentalfactorsbasedonmachinelearning AT qiliu associationbetweentheclassificationofthegenusofbatrachospermaceaerhodophytaandtheenvironmentalfactorsbasedonmachinelearning AT junpinglv associationbetweentheclassificationofthegenusofbatrachospermaceaerhodophytaandtheenvironmentalfactorsbasedonmachinelearning AT jiafeng associationbetweentheclassificationofthegenusofbatrachospermaceaerhodophytaandtheenvironmentalfactorsbasedonmachinelearning AT feiwang associationbetweentheclassificationofthegenusofbatrachospermaceaerhodophytaandtheenvironmentalfactorsbasedonmachinelearning AT shulianxie associationbetweentheclassificationofthegenusofbatrachospermaceaerhodophytaandtheenvironmentalfactorsbasedonmachinelearning |