A Large-Scale Dataset of Conservation and Deep Tillage in Mollisols, Northeast Plain, China

Fahui Jiang (), Shangshu Huang, Yan Wu, Mahbub Ul Islam, Fangjin Dong, Zhen Cao, Guohui Chen and Yuming Guo
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Fahui Jiang: College of Land Resources and Environment, Jiangxi Agricultural University, Nanchang 330045, China
Shangshu Huang: College of Land Resources and Environment, Jiangxi Agricultural University, Nanchang 330045, China
Yan Wu: Jiangxi Institute of Red Soil, Nanchang 330046, China
Mahbub Ul Islam: Bangladesh Agricultural Research Institute, Gazipur 1701, Bangladesh
Fangjin Dong: Northeast Institute of Geography and Agroeocology, Chinese Academy of Sciences, Harbin 150081, China
Zhen Cao: Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China
Guohui Chen: Jiujiang Academy of Agricultural Sciences, Jiujiang 332000, China
Yuming Guo: Cultivated Land Quality Monitoring and Protection Center, Ministry of Agriculture and Rural Affairs, Beijing 100125, China

Data, 2022, vol. 8, issue 1, 1-15

Abstract: One of the primary challenges of our time is to feed a growing and more demanding world population with degraded soil environments under more variable and extreme climate conditions. Conservation tillage (CS) and deep tillage (DT) have received strong international support to help address these challenges but are less used in major global food production in China. Hence, we conducted a large-scale literature search of English and Chinese publications to synthesize the current scientific evidence to evaluate the effects of CS and DT on soil protection and yield maintenance in the Northeast China Plain, which has the most fertile black soil (Mollisols) and is the main agricultural production area of China. As a result, we found that CS had higher soil bulk density, strong soil penetration resistance, greater water contents, and lower soil temperature, and was well-suited for dry and wind erosion-sensitive regions i.e., the southwest areas of the Northeast. Conversely, DT had better performance in the middle belt of the Northeast China Plain, which contained a lower soil temperature and humid areas. Finally, we created an original dataset from papers [dataset 1, including soil physio-chemical parameters, such as soil water, bulk density, organic carbon, sand, silt, clay, pH, total and available nitrogen (N), phosphorus (P), and potassium (K), etc., on crop biomass and yield], by collecting data directly from publications, and two predicted datasets (dataset 2 and dataset 3) of crop yield changes by developing random forest models based on our data.

Keywords: conservation tillage; deep tillage; conventional tillage; random forest; meta-analysis; subsoiling; no-tillage; straw mulching; crop yield (search for similar items in EconPapers)
JEL-codes: C8 C80 C81 C82 C83 (search for similar items in EconPapers)
Date: 2022
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