Yan Wu

Dr. Yan Wu


Research Focus & Metrics

Academic Career Length

5Years (2022-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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4 August 2023 in Water
Verified
Journal Article
Open access
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ZCZhen Cao
Zhen Cao
GCGuohui Chen
Guohui Chen
SZSong Zhang
Song Zhang
SHshangshu huang
shangshu huang
YWYan Wu
Yan Wu
JFjiang fahui
jiang fahui
Soil erosion poses a global threat to arable land and its sustainability, particularly in China, where the most severe soil erosion exists worldwide. No-tillage (NT) and mulching (NTS) are considered the most effective soil management techniques for reducing erosion, but only 10% of the global area utilizes them. Therefore, in comparison to conventional tillage (CT), we conducted a comprehensive national assessment of NT and NTS to evaluate their impact on water erosion across China’s croplands for the period spanning 2000 to 2018, through using Revised Universal Soil Loss Equation (RUSLE); subsequently, we projected the temporal and spatial erosion distribution, and examined their effects of various underlying driving factors by using a random-forest model. Nationally, the average soil loss rates were 1085, 564, and 396 t km−2 a−1 for the CT, NT, and NTS, respectively, across the entire arable land over a span of 18 years. This represents a reduction of 48% and 64% in the NT and NTS, respectively, compared to CT. From 2000 to 2018, water erosion-induced soil loss exhibited a slightly increasing trend with a wavelike pattern in CT, NT, and NTS. The spatial distribution of water erosion in China’s arable land was primarily influenced by local precipitation, accounting for 45% to 52% of the total impact on CT, NT, and NTS. Additionally, the soil slope degree played a role, contributing 29% to 36% of the erosion patterns. Overall, NT and NTS demonstrated superior performance in mitigating the soil erosion in the southern regions of China, including the Central South, Southwest, and East China, owing to the substantial local rainfall and steep terrain. In contrast, NT and NTS exhibited a lower but still significant reduction in soil loss in the northern regions of China due to the flat topography and limited rainfall. However, considering the trade-off between economic losses (yield) and ecosystem benefits (erosion control), we recommend implementing NT and NTS primarily in the northern parts of China, such as the Northeast, North China, and Northwest.

19 February 2025 in Agronomy
Verified
Journal Article
Open access
PDF file
XHXiaolin He
Xiaolin He
YWYan Wu
Yan Wu
Kailou LIUKailou LIU
Kailou LIU
JJJianhua Ji
Jianhua Ji
CWChunhong Wu
Chunhong Wu
CZChunhuo Zhou
Chunhuo Zhou
This study investigates the effects of various treatments on soil pH, SOC, and crop yield in red soil with a pH of 4.25 through a two-year field experiment, using a rapeseed and sesame cropping system. The treatments included the control (CK); lime (CaO) (L); fully fermented pig manure (M); a calcium–magnesium–phosphate fertilizer (P); lime and fully fermented pig manure (LM); lime and the calcium–magnesium–phosphate fertilizer (LP); fully fermented pig manure and the calcium–magnesium–phosphate fertilizer (MP); and lime, fully fermented pig manure, and the calcium–magnesium–phosphate fertilizer (LMP). Then, the changes in yield, soil pH, and SOC were analyzed. The results showed that, among all treatments, the LMP treatment produced the highest yields for both rapeseed (93.62%) and sesame (45.10%); they increased by 93.62% and 45.10% compared with that for CK. Furthermore, these treatments with lime application increased the soil pH. During the rapeseed season, compared with CK, the soil pH values increased by 0.87, 0.75, 0.90, 1.03, 1.24, 1.18, and 1.45 units in the L, M, P, LM, LP, MP, and LMP treatments, respectively. Moreover, they increased by 0.66, 0.34, 0.51, 0.95, 0.82, 0.72, and 1.03 units, respectively, in the sesame season. Similarly, in terms of yield, the highest pH was observed in the LMP treatment for both the rapeseed and sesame seasons. In contrast to soil pH, the effects of these treatments on SOC were less pronounced. Furthermore, the relationship between soil pH and crop yields was significant (R2, p < 0.05). In addition, fitted equations indicated a higher yield response (5.17%) in rapeseed compared with that in sesame (2.32%), while soil pH increased by 0.1 unit. Therefore, the combined application of lime, composted pig manure, and calcium–magnesium–phosphate is an effective strategy to reduce soil acidification and improve crop yield in highly acidified red soils, with the increase in soil pH having a more substantial impact on crop yield than the increase in SOC.

24 December 2022 in Data
Verified
Journal Article
Open access
PDF file
JFjiang fahui
jiang fahui
SHShangshu Huang
Shangshu Huang
YWYan Wu
Yan Wu
MIMAHBUB UL ISLAM
MAHBUB UL ISLAM
FDFangjin Dong
Fangjin Dong
YGYuming Guo
Yuming Guo
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.