Rice-Crayfish Farming Increases Soil Organic Carbon Sequestration by Promoting Soil Aggregate Protection and Microbial Necromass Accumulation DOI

Wanyang Zhang,

Jiaqiong Wu,

Mingshuang Xu

и другие.

Опубликована: Янв. 1, 2024

Язык: Английский

Ecosystem sustainability of rice and aquatic animal co-culture systems and a synthesis of its underlying mechanisms DOI
Lei Ge,

Yu Sun,

Yujie Li

и другие.

The Science of The Total Environment, Год журнала: 2023, Номер 880, С. 163314 - 163314

Опубликована: Апрель 6, 2023

Язык: Английский

Процитировано

34

Returned straw reduces nitrogen runoff loss by influencing nitrification process through modulating soil C:N of different paddy systems DOI
Shaopeng Wang,

Limei Zhai,

Shufang Guo

и другие.

Agriculture Ecosystems & Environment, Год журнала: 2023, Номер 354, С. 108438 - 108438

Опубликована: Май 16, 2023

Язык: Английский

Процитировано

19

Integrated rice-crayfish farming system does not mitigate the global warming potential during rice season DOI
Lijin Guo, Wei‐Hung Lin, Cougui Cao

и другие.

The Science of The Total Environment, Год журнала: 2023, Номер 867, С. 161520 - 161520

Опубликована: Янв. 13, 2023

Язык: Английский

Процитировано

18

Rice-crayfish farming system promote subsoil microbial residual carbon accumulation and stabilization by mediating microbial metabolism process DOI

Wanyang Zhang,

Yi Song, Shihao Ma

и другие.

The Science of The Total Environment, Год журнала: 2024, Номер 946, С. 174188 - 174188

Опубликована: Июнь 24, 2024

Язык: Английский

Процитировано

5

Assessing the nutrient removal performance from rice-crayfish paddy fields by an ecological ditch-wetland system DOI Creative Commons
Jun Yang,

Shihao Tang,

Yiqi Li

и другие.

Heliyon, Год журнала: 2024, Номер 10(19), С. e38373 - e38373

Опубликована: Сен. 24, 2024

Язык: Английский

Процитировано

5

Rice-crayfish farming increases soil organic carbon sequestration by promoting aggregate protection and microbial necromass accumulation DOI

Wanyang Zhang,

Jiaqiong Wu,

Mingshuang Xu

и другие.

Agriculture Ecosystems & Environment, Год журнала: 2025, Номер 383, С. 109519 - 109519

Опубликована: Фев. 1, 2025

Язык: Английский

Процитировано

0

Comprehensive assessment of integrated rice-crayfish farming system as a new paradigm to air-water-food nexus sustainability DOI
Qiaoyu Sun, Benyamin Khoshnevisan, Jianqiang Zhu

и другие.

Journal of Cleaner Production, Год журнала: 2022, Номер 377, С. 134247 - 134247

Опубликована: Сен. 23, 2022

Язык: Английский

Процитировано

11

Distribution patterns and influential factors of pathogenic bacteria in freshwater aquaculture sediments DOI
Wenxiang Xi, Xun Zhang, Xianbin Zhu

и другие.

Environmental Science and Pollution Research, Год журнала: 2024, Номер 31(10), С. 16028 - 16047

Опубликована: Фев. 3, 2024

Язык: Английский

Процитировано

2

Methane emissions sources and impact mechanisms altered by the shift from rice-wheat to rice-crayfish rotation DOI
Shaopeng Wang, Yilin Liu, Fulin Zhang

и другие.

Journal of Cleaner Production, Год журнала: 2023, Номер 434, С. 139968 - 139968

Опубликована: Ноя. 29, 2023

Язык: Английский

Процитировано

5

A Bi-Temporal-Feature-Difference- and Object-Based Method for Mapping Rice-Crayfish Fields in Sihong, China DOI Creative Commons
Siqi Ma, Danyang Wang, Haichao Yang

и другие.

Remote Sensing, Год журнала: 2023, Номер 15(3), С. 658 - 658

Опубликована: Янв. 22, 2023

Rice-crayfish field (i.e., RCF) distribution mapping is crucial for the adjustment of local crop cultivation structure and agricultural development. The single-temporal images two phenological periods in year were classified separately, then areas where water disappeared identified as RCFs previous studies. However, due to differences segmentation lakes rivers between images, incorrect extraction unavoidable. To solve this problem, a bi-temporal-feature-difference-coupling object-based (BTFDOB) algorithm was proposed order map Sihong County. We mapped by segmenting bi-temporal simultaneously based on method selecting appropriate feature classification features. evaluate applicability, results years obtained using single-temporal- (STOB) compared with BTFDOB method. suggested that spectral showed high importance, which could effectively distinguish from non-RCFs. Our worked well, an overall accuracy (OA) 96.77%. Compared STOB method, OA improved up 2.18% across three data. concentrated low-lying eastern southern regions, scale expanded Sihong. These findings indicate can accurately identify RCFs, providing scientific support dynamic monitoring rational management pattern.

Язык: Английский

Процитировано

4