Soil tillage, a major agricultural management, could effectively alter soil structure and plant growth, particularly under groundnut plantations. To understand effects of different tillage measures on nitrogen(N), phosphorus(P) and potassium(K) absorptions and use efficiencies for peanut (Arachis hypogaea L.), four tillage treatments: no tillage (NT), deep loosing (DL), deep plow (DP), and shallow plow (SP), were examined for two growing years at three typical peanut-producing sites of Qishan, Wangcheng, and Xiadian in Shandong, China. Results showed that average soil bulk density under DL, DP, and SP at the three sites was decreased by 7.1–19.5% compared with NT treatment for the 2 years. Significantly higher average total N accumulations in underground peanut part patterned as DP (163 kg/ha) > SP (149 kg/ha) > DL (144 kg/ha) > NT (117 kg/ha), while total N in aboveground peanut part was 8.7–22.1% higher under DP than other treatments. Absorptions of N, P, and K in underground parts were extremely significantly contributed to high peanut yields (P < 0.01), whereas increase of N and P absorptions in aboveground parts did not promote peanut yields. Soil bulk density was significantly negatively correlated with plant macronutrient amounts in underground peanut parts and peanut yields (P < 0.01). Moreover, N:P, N:K, and P:K ratios were similar between NT and noncompaction stress treatments of DL, DP, and SP. These results indicate that DP is a rational tillage practice for promoting nutrient uptake amount, efficiency, and peanut yields by alleviating soil compaction stress in peanut-producing fields. 相似文献
Journal of Soils and Sediments - The present study was conducted to understand the pedogenesis of soils developed on basalts and reveal the impact of Asian dust on soils in subtropical China. Soils... 相似文献
Characterizations of soil aggregates and soil organic carbon (SOC) losses affected by different water erosion patterns at the hillslope scale are poorly understood. Therefore, the objective of this study was to quantify how sheet and rill erosion affect soil aggregates and soil organic carbon losses for a Mollisol hillslope in Northeast China under indoor simulated rainfall.
Materials and methods
The soil used in this study was a Mollisol (USDA Taxonomy), collected from a maize field (0–20 cm depth) in Northeast China. A soil pan with dimensions 8 m long, 1.5 m wide and 0.6 m deep was subjected to rainfall intensities of 50 and 100 mm h?1. The experimental treatments included sheet erosion dominated (SED) and rill erosion dominated (RED) treatments. Runoff with sediment samples was collected during each experimental run, and then the samples were separated into six aggregate fractions (0–0.25, 0.25–0.5, 0.5–1, 1–2, 2–5, >?5 mm) to determine the soil aggregate and SOC losses.
Results and discussion
At rainfall intensities of 50 and 100 mm h?1, soil losses from the RED treatment were 1.4 and 3.5 times higher than those from the SED treatment, and SOC losses were 1.7 and 3.8 times greater than those from the SED treatment, respectively. However, the SOC enrichment ratio in sediment from the SED treatment was 1.15 on average and higher than that from the RED treatment. Furthermore, the loss of <?0.25 mm aggregates occupied 41.1 to 73.1% of the total sediment aggregates for the SED treatment, whereas the loss of >?0.25 mm aggregates occupied 53.2 to 67.3% of the total sediment aggregates for the RED treatment. For the organic carbon loss among the six aggregate fractions, the loss of 0–0.25 mm aggregate organic carbon dominated for both treatments. When rainfall intensity increased from 50 to 100 mm h?1, aggregate organic carbon loss increased from 1.04 to 5.87 times for six aggregate fractions under the SED treatment, whereas the loss increased from 3.82 to 27.84 times for six aggregate fractions under the RED treatment.
Conclusions
This study highlights the effects of sheet and rill erosion on soil and carbon losses at the hillslope scale, and further study should quantify the effects of erosion patterns on SOC loss at a larger scale to accurately estimate agricultural ecosystem carbon flux.