LS-SVM data mining analysis: how does biochar influence soil net nitrogen mineralization in the field?

Purpose

Biochar has been considered as a stable-carbon source for improving soil quality and long-term sequestration of carbon. However, in view of ecological environmental feedback and the tightly coupled system of carbon-nitrogen cycling, further attention has shifted to the effect of biochar on soil net nitrogen mineralization (SNNM). Recently, ecological evaluations of biochar were mostly based on laboratory incubation or pot experiments, ignoring external and uncontrollable natural factors. Therefore, the essential characteristics of local environments were not accurately described.

Materials and methods

In this paper, a nonlinear stochastic model of SNNM based on least squares support vector machine (LS-SVM) was set up to study the effect of biochar on nitrogen cycling in a field experiment. In order to explore this effect in natural conditions, partial derivative (PaD) sensitivity analysis of LS-SVM was firstly proposed, evaluated by the data from a known equation, and then applied to open the “black-box” stochastic model of SNNM.

Results and discussion

Comparing with the sensitivity analysis of artificial neural networks (ANNs), the RD values of LS-SVM PaD1 algorithm were almost the same as those of ANNs PaD1 algorithm. However, the RSD values of LS-SVM PaD2 algorithm were closer to the given equation. In the SNNM model, RD values of LS-SVM PaD1 algorithm of initial nitrogen, time, and precipitation were 21, 15, and 14 %, and the biochar RD value was only 0.51 %, implying that biochar did not influence SNNM directly. However, the cumulative RSD of the PaD2 algorithm of biochar with the other factors was 15.05 %, the maximum of the interactions, implying that it could greatly enhance the tendency for SNNM by interacting with other factors.

Conclusions

PaD sensitivity analysis of LS-SVM was a stable and reliable data mining method. In the SNNM model, initial nitrogen, time, and precipitation were the main controlling factors of the SNNM model. Biochar did not directly influence SNNM; however, it could greatly enhance the tendency for SNNM by interactions with other factors by decreasing the inhibitory effect of initial nitrogen on SNNM and modifying soil condition to change the effect of other factors on SNNM.

     

Quantifying soil macropore networks in different forest communities using industrial computed tomography in a mountainous area of North China

Purpose

Macropores have important effects on the movement of soil water, air, and chemical substances. However, the quantitative relationship between complex 3D soil macropore networks and forest communities remains unclear in the northern mountainous area in China. The objectives of this study were to (1) use industrial computed tomography (CT) scanning and image analysis to quantitatively analyze macropore networks in intact soil columns and (2) identify characteristics of soil macropore networks in different forest communities.

Materials and methods

Intact soil columns (100-mm diameter, 300 mm long) were taken from six local forest communities with three replicates for a total of 18 samples. Industrial X-ray CT was used to scan soil samples; then, the scanned images were used to obtain the 3D images of rock fragments and macropore structures. Next, the macropore structure was quantified, including volume, diameter, surface area, length, angle, tortuosity, and number of macropores. This technique provided an accurate method to quantify the structure of macropores.

Results and discussion

The analysis and results revealed that different forest communities influence soil macropore 3D structure significantly and in different ways. Macropores in mixed Pinus tabulaeformis, Castanea mollissima, and Ulmus pumila forest had the largest diameter, surface area, network density, and length density of macropores as well as the smallest mean tortuosity of soil macropores. This is caused by the fact that mixed forest soils had more complex root systems, better soil structure, and more biotic activity. Within the soils of a single forest community, macropore porosity, network density, surface area density, and length of macropores decreased with increased soil depth, because more roots and more biological activity were present in the surface soil.

Conclusions

Advanced industrial CT technology can allow an accurate quantification of soil macropore structure. This is important because this type of structure has significant effects on soil water, air, and chemical transport. The results suggest that mixed forest is the best afforestation model in the northern mountainous area in China because of its ability to improve soil structure.

     

云南省沧源县发展竹产业的优势及对策

云南省沧源县发展竹产业具有竹资源丰富、气候条件优越、交通便利和产业基础好等优势,文章提出了沧源发展竹产业的基本思路、重点领域以及具体措施,为该县竹产业实现跨越式发展提供借鉴。     

黄河三角洲盐碱地人工林土壤肥力质量的综合评价

以黄河三角洲滨海盐碱地柽柳、杜梨、盐柳、白蜡人工林为研究对象,未造林荒地为对照,对不同人工林的土壤养分、土壤酶活性进行测定,利用隶属函数分析法对不同人工林的土壤肥力进行综合评价。结果表明:与对照荒地相比,各人工林平均土壤有机质、铵态氮、硝态氮、有效磷、速效钾质量分数,分别提高了177.89%、76.47%、757.74%、32.76%、30.13%;土壤中磷酸酶、过氧化氢酶、脲酶、蔗糖酶活性,比对照荒地分别提高了47.09%,11.52%,41.07%,76.00%;土壤肥力综合评价分值,从大到小依次为白蜡(0.777)、杜梨(0.694)、柽柳(0.572)、盐柳(0.436)、荒地(0.030)。     

黄曲霉毒素B1诱导MEK/ERK/ROS介导的巨噬细胞自噬反应

为研究黄曲霉毒素B1(AFB1)能否诱导细胞自噬,并初步探讨其可能的作用机制。利用免疫荧光、酶标仪检测、免疫印迹等技术检测经AFB1处理过的细胞的自噬水平、相关蛋白的表达量以及活性氧(Reactive oxygen species,ROS)的产生情况。结果表明:AFB1能够引起RAW264.7细胞和Hela细胞的自噬反应,并且该自噬为完全自噬。AFB1诱导的小鼠单核巨噬细胞RAW264.7自噬是依赖细胞外信号调节激酶(Extracellular signal-regulated kinase,ERK)途径发生的,并受ROS的调节。此外,发现AFB1诱导ROS产生呈浓度依赖性,而ROS抑制剂同时抑制了ROS和自噬发生,但自噬抑制剂并没有有效地抑制ROS的产生,表明ROS处于AFB1诱导自噬的上游,对自噬起到调节作用。这表明AFB1诱导的自噬现象在细胞中普遍存在,而自噬作为机体的免疫机制,在抵抗AFB1毒力侵染的过程中发挥重要作用。     

农作制度对设施草莓土壤化学性状的影响

为了解长期种植设施草莓土壤化学性状的特点及其与农作制度的关系,在浙江省范围内采集草莓-水稻与草莓-蔬菜2种种植制度下的代表性设施草莓土壤,比较分析了2种种植制度下设施草莓土壤有机质、全氮、有效磷、速效钾、交换性钙、交换性镁及p H值、电导率等化学指标。结果表明:浙江省设施草莓土壤盐分积累不明显,电导率较低,但土壤酸化显著;土壤有机质以中低等水平为主,平均为23.9 g/kg;全氮处于中高水平,平均为1.5 g/kg;土壤有效磷积累显著,平均高达142.1 mg/kg;速效钾处于中等水平,平均为122.9 mg/kg;交换性钙处于较高水平,平均为1235.5 mg/kg;交换性镁处于较低水平,平均为72.0 mg/kg。草莓-水稻与草莓-蔬菜2种种植制度下设施草莓土壤化学性状存在一定的差异,前者土壤电导率、有机质、全氮、有效磷、速效钾分别比后者低106.5μS/m、3.4 g/kg、0.6 g/kg、128.7 mg/kg和137.0 mg/kg;但土壤p H前者比后者高0.1个单位。研究认为,草莓-水稻种植制度下有利于缓解设施草莓土壤因长期过量施用化肥引起的土壤酸化,减免氮、磷等养分的过度积累等问题。     

基于GM(1,1)模型的四川粮食产量预测研究

中国人口众多,粮食安全关系到国计民生,加强粮食产量预测有利于确保粮食安全。根据2001—2015 年四川粮食产量的历史数据,运用灰色系统理论,建立基于弱化缓冲算子的GM(1,1)预测模型,通过残差、级比偏差、关联度、后验差检测、模拟数据检查对模型的合理性和精度进行误差检验,并应用模型预测未来3 年的粮食产量。研究结果表明,灰色系统理论GM(1,1)适用于粮食产量预测且具有较高的精度。预测了2016、2017、2018 年的粮食产量同比增长分别为-2.11%、-0.39%和1.21%,由此得出未来粮食产量将在波动中增长。     

种子处理方式对欧洲垂枝桦发芽率及苗木生长的影响

以引进的俄罗斯欧洲垂枝桦种子为材料,研究了冷藏、沙藏和雪藏3种种子处理对欧洲垂枝桦场圃发芽率及苗木生长的影响。结果表明:不同种子处理的场圃发芽率、苗高、地径、地上生物量、地下生物量和全株生物量存在显著差异,种子雪藏处理的场圃发芽率、苗高、地径、地上生物量、地下生物量和全株生物量等指标均优于其他处理,其场圃发芽率、生长量和生物量最高。     

温室环境温度预测自适应机理模型参数在线识别方法

温室小气候模型具有非线性、强干扰、时变等特性,常用的线性化模型或离线辨识模型无法有效预测温室环境动态变化规律,模型精度不高直接影响温室环境控制性能。针对模型的这种复杂特性,该文以温度模型为例,提出利用连续-离散递推预测误差算法,对非线性模型参数和状态进行在线估计,以提高模型精度。首先,考虑加热和通风2种控制输入,建立了温室温度模型。然后,论述了该算法的原理和优势,算法通过引入并调整增益矩阵,对系统噪声进行在线更新,减少了系统噪声初始化偏差对参数估计收敛性的影响。最后,基于试验温室实测数据,对温室温度模型进行了在线辨识仿真,结果表明,利用连续-离散递推预测误差算法辨识模型拟合度为93.7%,扩展卡尔曼滤波器拟合度为89.5%,该文提出的算法在预测温室温度方面更为有效。     

Impact of an Urban Environment on Trace Element Concentrations in Domestically Produced Lettuce (<Emphasis Type="Italic">Lactuca sativa L.</Emphasis>)

Urban horticulture is gaining more and more attention in the context of sustainable food supply. Yet, cities are exposed to (former) industrial activities and traffic, responsible for emission of contaminants. Trace elements were monitored in soils located in the urban environment of Ghent (Belgium) and 84 samples of Lactuca satica L. lettuce grown on it. The effects of cultivation in soil versus trays, neighbouring traffic and washing of the lettuce before consumption were studied. The 0–30 cm top layer of soils appeared heterogenic in composition and enriched in Co, Cd, Ni and Pb within 10 m from the nearest road. Yet, no similar elevated concentrations could be found in the crops, except for As. Besides uptake from the roots, the presence of trace elements in the plants is also caused by the atmospheric deposition of airborne particulate matter on the leaf surface. Correlation analysis and principal component analysis (PCA) revealed that this latter transport pathway might particularly be the case for Pt, Pd and Rh. Concentrations of Cd did not exceed the 0.2 mg kg^?1 (fresh weight) threshold for Cd in leafy vegetables set by the European Commission. Measurements to reduce the health risks include the washing of lettuce, which effectively reduced the number of samples trespassing the maximum Pb level of 0.3 mg kg^?1 (fresh weight). Also, cultivation in trays resulted in a lower As content in the plants. Taking into account a vigilance on crop selection, cultivation substrate and proper washing before consumption are considered essential steps for safe domestic horticulture in urban environments.