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Fluorine pollution in saline-sodic soils has become an important environmental problem, but little is known about the interaction between Al2(SO4)3 and fluorine when Al2(SO4)3 is used to improve saline-sodic soils. In this study, batch adsorption experiments were conducted to investigate the impacts of different saline-sodic soils with Al2(SO4)3 on fluorine adsorption, and the mechanisms of adsorption were characterized by SEM, BET, FTIR, and XPS analysis. The results showed that fluorine adsorption decreased with increasing soil salinity, and the addition of Al2(SO4)3 increased the adsorption of fluorine in soils. Among the three saline-sodic soils, Al2(SO4)3 contributed greatly to fluorine adsorption by mildly saline-sodic soils, with a range of 40.84%-69.70%. Fluorine adsorption isotherms could be properly described by the Langmuir and Freundlich models. At higher fluorine equilibrium concentrations, the adsorption amount of fluorine was greater for soils with Al→F. Both the soil porosity and the number of aggregates of saline-sodic soils were increased after adding Al2(SO4)3 for adsorption. Functional groups such as Si-O-Si, H-O-H, C-H, -OH, and Al-O-H were involved in the reaction process. Fluorine adsorption on saline-sodic soils refers to the ligand exchange and electrostatic adsorption, and F− replaces -OH on the soil surface. This work may provide a theoretical reference for the changes in fluorine chemical behavior when Al2(SO4)3 ameliorates saline-sodic soils.

Returning corn straw to soil improves soil carbon sequestration in the Phaeozem regions of Northeast China. This research was to investigate the changes in soil carbon fractions of Phaeozem derived from loess and laterite PM with corn straw incorporation and quantify the influence of the key factors on soil carbon accumulation in order to improve the soil carbon stabilization efficiency. A simulative laboratory incubation experiment was conducted over 12 months using Phaeozem derived from loess and laterite PM and eight corn straw doses. Results showed that the clay mineral of Phaeozem was dominated by a mixed-mineral illite-smectite layer, illite, vermiculite, kaolinite, and smaller amounts of montmorillonite. Clay mineral species of topsoil were identical with its PM. The LOC and HOC of six soils increase with increase in straw incorporation level. The promoting effectiveness of straw incorporation on C accumulation declined when the C inputs reached a certain level. At 15% straw incorporation levels, the LOC and HOC of six soil increased by 1.86–3.01 g kg−1 and 1.33–2.22 g kg−1 than CK, respectively. The increment of LOC and HOC of six soils followed the trend of LHAp > LLAp > RHAp > RLAp > LC > RC. At 15% straw incorporation levels, the RLOC of RC (419%) and LC (296%) was greater than topsoil (103–254%) and the RHOC of RC (90%) and LC (61%) was much greater than topsoil (9–26%). Further analysis suggested that C input, TSOC, and clay content were the most influential variables on carbon sequestration efficiency. They accounted for about 73% of the variations of RLOC and RHOC. The relative contributions of 2:1 clay to RLOC and RHOC were about 10% and 15%, respectively and that of 1:1 clay were about 4.4% and 3.5%, respectively. In conclusion, both the topsoil and PM of Phaeozem have considerable C-stabilizing capacity and the C sequestration efficiency of topsoil and PM derived from loess was greater than those for topsoil and PM derived from laterite.

Estimation of soil total nitrogen (STN) is important for quantifying the spatial distribution of soil N (Nitrogen) stocks, determining the amount absorbed by crops and avoiding yield losses and environmental pollution. The objective of this research was to determine the spatial distribution of STN using a remote sensing approach and to investigate the importance of different predictors under two conditions: the bare soil condition and the vegetated condition. We also investigated whether the Sentinel-2A red-edge bands and relative spectral indices were suitable for STN estimation. Soil data were collected from the topsoil (0–20 cm) at 104 sampling sites on 06/15/2016 from farmland in a black soil region in Northeast China. Two Sentinel-2A Multispectral Instrument (MSI) remote sensing images were acquired on 05/26/2016 and 08/03/2016 to represent the two conditions. Environmental variables included the terrain attributes, temperature and precipitation. Then, 21 predictors, including the original bands (O), normal spectral indices (S), red-edge indices (R) and environmental variables (E), were employed to estimate the spatial distribution of the STN content using a random forest (RF) model. Finally, different predictors were combined to construct RF models, and the prediction model with the best performance was selected to determine the spatial pattern of the STN content. The results showed that the predictors had different levels of importance under the two conditions. However, most environmental variables and normal spectral indices always play a significant role in the estimation of STN. The model with the combination of the original bands, normal spectral indices, red-edge indices and environmental variables (O + S + E + R) under the bare soil condition had the best prediction performance, and the combination of the original bands, normal spectral indices and red-edge indices (O + S + R) model had a performance similar to the O + S + E + R model. Therefore, the selection of suitable predictors is necessary to predict STN. The spatial pattern of STN was related to the crop type and elevation of the study area. The results of this study suggested that the proposed RF-based remote sensing method was able to accurately capture the variation in STN and that the performance of the prediction model can be improved by providing enough types of suitable predictors.

Converting natural vegetation to other types of land utilization is presently the most common land use change around the world. Conversion of grassland plays an important role in estimating the regional nutrients budget and assessing ecological effects. However, few studies have estimated the impacts of grassland conversion on soil nutrients under different soil pedogenic horizons. This study selected three sites, which were covered by grassland, shelterbelt, and cropland. The study evaluated the effects of grassland conversion and soil pedogenic horizon (to a depth of 100 cm) on the soil organic carbon (SOC), soil total nitrogen (STN), and soil total phosphorus (STP) concentrations and stocks in the Chinese Chernozem region. The results revealed that significant (p &lt, 0.05) differences were seen after grassland conversion for concentrations and stocks of SOC, STN, and STP. The transformation from grassland to shelterbelt and cropland plantations caused soil carbon and soil nitrogen losses but caused soil phosphorus accumulations. Moreover, conversion of grassland made SOC, STN, and STP all drop below the Bk-horizon. Changes in the SOC and STP on an area basis were the greatest after conversion of grassland to cropland, for concentrations of −16% and 26% and for stocks of −15% and 32%, respectively. Land use change and soil pedogenic horizon primarily influenced the distribution patterns of nutrients concentrations and stocks. However, grassland conversion effects on nutrients were mainly at surface horizons. Soil properties, such as calcium carbonate (CaCO3) and soil texture, affected the nutrients from the Bk-horizon to the C-horizon. This study indicates that land use management policies should protect natural grasslands to minimize losses of SOC, STN, and STP.

Agricultural tillage practices play an important role in the production and consumption of greenhouse gases (GHGs) that contribute substantially to the global warming. To explore GHG diffusion characteristic and seek for environment-friendly tillage methods, four tillage systems consisting of continuous rotary tillage (CR), continuous no tillage (CN), ploughing-rotary tillage (PR), and ploughing-no tillage (PN) were designed, and vertical variations of GHG concentrations under different tillage systems were investigated. Mean CO2 concentration in the soil profile was increased significantly with the increase of soil depth. Higher soil moisture promoted CO2 production. However, the influence of soil temperature on the content of CO2 was not obvious. The concentrations of CH4 in soil at 0–20-cm depth were greater than that of 20–40 cm, which was mainly affected by fertilization. The trend of N2O concentration variation in soil was consistent with that of CO2. The diffusion flux of CO2 in soil was all positive, and it changes greatly in the whole growth cycle of maize, which had obvious correlation with precipitation. The CH4 diffusion flux decreased with the increase of soil depth, and the change trend of 0–20-cm soil layer diffusion flux was consistent with the gas concentration. The 20–40-cm soil layer fluctuated greatly, which was mainly affected by water content, and the whole value was negative after jointing. The trend of N2O diffusion flux was similar to that of CH4. In the whole maize growth period, except for CH4 in 20–40-cm soil layer, the cumulative diffusion fluxes of greenhouse gases in each treatment were all positive, indicating that the whole farmland soil was the emission source of greenhouse gases. The effect of three greenhouse gases on greenhouse effect was CO2 > N2O > CH4, and the comprehensive warming potential of different tillage methods was CN > CR > PR> PN. So PN is the best tillage mode to reduce GHG emissions in soil profile under the test conditions.

An appropriate tillage method must be implemented by maize growers to improve phosphorus dynamics in the soil in order to increase phosphorus uptake by plant. The objective of this study was to investigate the effects of tillage systems on phosphorus and its fractions in rhizosphere and non-rhizosphere soils under maize. An experimental field was established, with phosphate fertilizers applied to four treatment plots: continuous rotary tillage (CR), continuous no-tillage (CN), plowing-rotary tillage (PR), and plowing-no tillage (PN). Under the different tillage methods, the available P was increased in the non-rhizosphere region. However, the concentration of available P was reduced in the rhizosphere soil region. The soil available P decreased with the age of the crop until the maize reached physiological maturity. The non-rhizosphere region had 132.9%, 82.5%, 259.8%, and 148.4% more available P than the rhizosphere region under the CR, PR, CN, and PN treatments, respectively. The continuous no-tillage method (CN) improved the uptake of soil phosphate by maize. The concentrations of Ca2-P, Ca8-P, Fe-P, Al-P and O-P at the maturity stage were significantly lower than other seedling stages. However, there was no significant relationship between total P and the P fractions. Therefore, a continuous no-tillage method (CN) can be used by farmers to improve phosphorus availability for spring maize. Soil management practices minimizing soil disturbance can be used to impove phosphorus availability for maize roots, increase alkaline phosphatase activity in the rhizosphere soil and increase the abundance of different phosphorus fractions.

Soil pH is a dominant soil variable because it influences many physical, chemical, and biological soil properties and plant growth processes. This study aimed at identifying the potential for field hyperspectral reflectance, multispectral satellite imagery and environmental variables to predict soil pH changes for croplands in regional areas located in the black soil region of Dehui in Northeast China. First, hyperspectral reflectance was acquired from a small area of Dehui; then, Landsat images with a 30 m resolution were acquired on 10 Oct 2005 and 22 Oct 2016 for the whole study region. This showed the scope for estimating soil pH with remote sensing derived variables both at the field scale and the regional scale for croplands in black soil regions. We selected 18 spectral variables from hyperspectral reflectance, 17 spectral variables from multispectral imagery and 6 environmental variables, respectively, and found relationships between the controlling variables and the measured soil pH values. Subsequently, 7 spectral indicators from hyperspectral reflectance, 7 spectral indicators from multispectral reflectance and 3 environmental indicators had higher correlations with soil pH among those variables. Finally, we used the partial least squares regression (PLSR) model to build soil pH prediction models for the 7 spectral indicators from hyperspectral reflectance and for the 7 spectral indicators from Landsat image with 3 environmental indicators, then we combined the two models to obtain a soil pH prediction model at the regional scale. The results showed that several thermal reflectance, vegetation indices and environmental variables, including the ratio vegetation index (RVI), the normalized difference vegetation index (NDVI), the normalized difference water index (NDWI), land use, mean annual precipitation and mean annual temperature were strong predictors of soil pH distribution at the regional scale. The combined soil pH prediction model had an R2 of 0.50, a root mean square error (RMSE) of 0.30 and a residual prediction deviation (RPD) of 1.55, indicating reliable precision and average prediction abilities. We estimated that soil pH values showed obvious heterogeneity over the study region, and soil pH mainly changed with crop type. Our results also suggested that the average decrease in soil pH for most of the study area of was approximately 0.50 units during 2005–2016. This study provides new approaches and knowledge for the better investigation of soil properties at a regional scale by using RS technologies.

The soil organic carbon accumulation in soda saline-alkaline soil and the humus composition changes with application of aluminum sulfate and rice straw were investigated by the controlled simulative experiments in laboratory. For evaluating the amelioration effect, organic carbon content and humus composition in soda saline-alkaline soil were investigated with different application amounts of rice straw and aluminum sulfate. Potassium dichromate oxidation titration (exogenous heat) method and Kumada method were used to analyze the contents of organic carbon and humus composition, respectively. The transformation of soil organic matter in the saline-alkali soil during the amelioration has been clarified in this paper. The results demonstrated that the contents of soil organic carbon were significantly increased (13-92%) with different application amounts of rice straw and aluminum sulfate. The contents of free fraction and combined fraction of humus and their compositions (humic acid and fulvic acid) were increased with different application amounts of rice straw. The free fraction of humus was increased more dramatically. Due to aluminum sulfate application, free fraction of humus and humic acid (HA) was transformed to combined fraction partially. Free HA was changed to be P type with rice straw application. With aluminum sulfate application, free form of HA was changed from type P to type Rp. For rice straw application, combined HA only was transferred within the area of type A. Aluminum sulfate addition had no significant effect on the type of combined form of HA. With the same amount of rice straw application, the contents of soil organic carbon were increased by increasing the amount of aluminum sulfate application. Both rice straw and aluminum sulfate applications could reduce the humification degree of free and combined fraction of HA. According to the types of HA, it could be concluded that humus became younger and renewed due to the application of rice straw and aluminum sulfate.

Crankshaft is one of the most important parts in diesel engine. The fatigue failure and fracture of crankshaft may lead to damage to the other parts, even some accidents. Recently with the increasing requirement of engine power and engine reliability, the investigation of the crankshaft strength becomes more important. Since during the engine work process, the extremely complicated force are loaded on the crankshaft and different vibration caused by torque, bending, etc., the crankshaft may create the resonance and appended dynamic stress in the working frequency range, which will be easy to bring about the bending and torsion damage after short work period. In this paper, the traditional algorithm on the basis of MATLAB/SIMULINK software is used to carry out the dynamic calculation and analysis for a certain type of diesel engine crankshaft. The crankshaft stress state and its variation are analyzed, and the results of the bending moment, torsion versus crank angle are obtained. Finally, the fatigue strength of crankshaft is checked and the safety factor is calculated to verify the crankshaft reliability.

Recently, many optimized nutrient management strategies have been applied to improve rice yield and nitrogen use efficiency (NUE) in China, most of which achieved higher yield and NUE than farmers’ usual fertilizer practices. The objective of this study was to investigate the aboveground biomass, nitrogen (N) accumulation and contribution of yield factors (i.e., number of effective panicles, number of spikelets per panicle, and grain weight) on rice yield regulated by optimized nitrogen application at different growth stages. Field experiments were conducted in 2009 and 2010 at 7 different sites, and three optimized N treatments (OPT) were compared with local farmers’ fertilizer practices (FFP). Rice yields of the optimized treatments increased 8.2–12.6% over the farmers’ fertilizer practices. Recovery efficiency of N (RE N ), agronomic N use efficiency (AE N ) and partial factor productivity of applied N (PFP N ) for OPT1 and OPT2 were all significantly higher than those obtained using the farmers’ fertilizer practices. The aboveground biomass and nitrogen accumulation of OPTs were lower than FFP at the vegetative and earlier reproductive growth stages, but the accumulation rate became faster than FFP at the later reproductive stage. In our result, grain yield was positively correlated with the panicles per unit area for OPTs, but not for FFP. Spikelets per panicles had negative correlation with panicles per unit area but the slop of OPTs was slower than the slope of FFP. We found that the OPTs treatments could mitigate the contradiction between yield formation factors. According to yield responses to the treatments, we defined two dominant yield-promotion stages: the primary nutrient contribution stage and the advanced nutrient contribution stage. Our results illustrated that at the primary nutrient contribution stage, the main promotion factor for yield was panicle number, which was mainly promoted by high N application at the early vegetative stage, and at the advanced nutrient contribution stage, the yield increase depended upon resolving the contradiction between number of effective panicles and spikelet number per panicle, which resulted from appropriate adjustments to the proportions of added N applied at different growth stages. In conclusion, our results indicated that adjusting the proportion of N application at different growth stages may reform the source–sink contradiction of yield, thus further increasing rice yield.