Potato absorption and phytoavailability of Cd,Ni, Cu,Zn and Pb in sierozem soils amended with municipal sludge compost

Effects of sludge utilization on the mobility and phytoavailability of heavy metals in soil-plant systems have attracted broad attention in recent years. In this study, we analyzed the effects of municipal sludge compost(MSC) on the solubility and plant uptake of Cd, Ni, Cu, Zn and Pb in a soil-potato system to explore the mobility, potato plant uptake and enrichment of these five heavy metals in sierozem soils amended with MSC through a potato cultivation trial in Lanzhou University of China in 2014. Ridge regression analysis was conducted to investigate the phytoavailability of heavy metals in amended soils. Furthermore, CaCl_2, CH_3 COONH_4, CH_3COOH, diethylene triamine pentacetic acid(DTPA) and ethylene diamine tetraacetic acid(EDTA) were used to extract the labile fraction of heavy metals from the amended soils. The results show that the MSC could not only improve the fertility but also increase the dissolved organic carbon(DOC) content of sierozem soils. The total concentrations and labile fraction proportions of heavy metals increase with increasing MSC percentage in sierozem soils. In amended soils, Cd has the highest solubility and mobility while Ni has the lowest solubility and mobility among the five heavy metals. The MSC increases the concentrations of heavy metals in the root, stem, peel and tuber of the potato plant, with the concentrations being much higher in the stem and root than in the peel and tuber. Among the five heavy metals, the bioconcentration factor value of Cd is the highest, while that of Ni is the lowest. The complexing agent(DTPA and EDTA) extractable fractions of heavy metals are the highest in terms of phytoavailability. Soil properties(including organic matter, p H and DOC) have important impacts on the phytoavailability of heavy metals. Our results suggest that in soil-potato systems, although the MSC may improve soil fertility, it can also increase the risk of soils exposed to heavy metals.     

大白菜花青素含量及色差指标相关性研究

为了探寻大白菜花青素含量快速测定的方法,本文利用pH差计法和色差仪分别测定了‘城阳青’(普通大白菜)、‘秋宝黄’(黄心白菜)和‘彩凤’3个不同叶色大白菜品种花青素含量以及色差指标,并对6个色泽参数与花青素含量进行了相关和回归分析。结果表明:6个色泽参数均能反映白菜叶片间叶色的细微变化,‘城阳青’和‘秋宝黄’不含花青素,紫色白菜‘彩凤’的花青素主要分布于由外向内的第1～4层叶片。色泽参数L,b,h和C分别与花青素含量呈极显著或显著负相关关系(相关系数分别为-0.85**,-0.58**,-0.49*,-0.58**)。以色泽参数值L、a、h与花青素含量建立了多元回归方程:y=90.24-1.07x1+5.65x2-142.71x3(x1为L值,x2为a值,x3为h值,y为花青素含量),该回归方程相关系数为0.9629。通过色差计依据建立的回归方程可快速测定紫色大白菜花青素的含量。     

Cause and Consequence in Maize Planting Dates in Germany

An important part of agricultural adaptation is the timing of crop sowing dates, affecting yields and the level of risk incurred during a particular season. Cold stress is especially relevant in maize, Zea mays L., so that the timing of planting in the spring is a tactical response to short‐term weather, but is also subject to strategic planning with regard to longer‐term climate. Both factors compare the potential implications of cold stress to the additional yield obtainable through earlier planting. New cultivars suited to growing conditions in Europe and generally increasing spring temperatures have enabled earlier planting, but it is still dependent on short‐term weather during the planting period. In the context of field‐level decision‐making, a panel regression is used to estimate the relationship between weekly local temperature and precipitation and planting dates at specific sites throughout Germany. Next, localised weather data and planting behaviour are linked to yields at the district (Landkreis) level to show the effects of planting date on yield. Based on these relationships optimal planting dates are explored with some associated costs and benefits. Results show a trend towards earlier planting that follows observed increasing spring temperatures and the availability of more cold‐tolerant cultivars but this advance is buffered by the increasing severity of minimum temperatures during a critical period. Earlier planting potentially increases yield but this is offset by additional management costs and risk. A robust and simple depiction of farmer behaviour in climatic, technological and economic context can help to understand trends in crop management and productivity that effect agricultural landscapes.     

不同燕麦基因型源库关系对穗粒数形成过程的影响

为了解燕麦穗粒数形成过程与源、库特征之间的关系，连续两年以10个不同来源、熟期、穗型、株型、小穗数的燕麦品种为试验材料，测定三叶期至拔节期的幼穗分化阶段及抽穗期源库特征，采用方差分析、聚类分析、逐步回归分析等方法，分析不同燕麦基因型源库特征及对穗粒数形成过程的影响。结果表明，燕麦穗粒数形成过程存在基因型差异，幼穗分化较好品种的穗粒数较全部品种平均值高11.22%~65.43%；幼穗分化较好品种的光合势、干物质量、粒数叶比、收获指数显著高于幼穗分化较差品种，其中粒数叶比和收获指数是影响穗粒数形成的主要因素，粒数叶比和收获指数较全部品种平均值分别高0.99%~68.74%和0.85%~13.80%。综上所述，源库协调是燕麦幼穗分化良好的生理基础，可通过提高光合势和干物质量达到增源的目的，进而提高穗粒数。     

Turbidity‐induced changes in emergent effects of multiple predators with different foraging strategies

Abstract – In natural systems, prey frequently interact with multiple predators and the outcome often cannot be predicted by summing the effects of individual predator species. Multiple predator interactions can create emergent effects for prey, but how those change across environmental gradients is poorly understood. Turbidity is an environmental factor in aquatic systems that may influence multiple predator effects on prey. Interactions between a cruising predator (largemouth bass Micropterus salmoides) and an ambush predator (muskellunge Esox masquinongy) and their combination foraging on a shared prey (bluegill Lepomis macrochirus) were examined across a turbidity gradient. Turbidity modified multiple predator effects on prey. In clear water, combined predators consumed in total more prey than expected from individual predator treatments, suggesting risk enhancement for prey. In moderately turbid water, the predators consumed fewer prey together than expected, suggesting a risk reduction for prey. At high turbidity, there were no apparent emergent effects; however, the cruising predator consumed more prey than the ambush predator, suggesting an advantage for this predator. Understanding multiple predator traits across a gradient of turbidity increases our understanding of how complex natural systems function.     

基于广告、技术、奖励的二级供应链效益最大化研究

基于技术进步视角，构建服务业FDI影响产业安全的理论模型，并采用1996-2013年的时序数据和分位数回归方法进行检验。实证结果表明，服务业FDI对技术进步的总效应为正；分位数回归进一步揭示，服务业FDI对技术进步的直接效应为正、间接效应为负，并在技术进步的低中分位点上，服务业FDI的直接效应大于间接效应，而在技术进步的高分位点上，服务业FDI的直接效应小于间接效应。研究证实，在技术进步的初期，服务业FDI会对产业安全发展产生直接的正向推动作用，但随着时间的推移，服务业FDI会威胁其产业安全。     

Predicting the degree of phosphorus saturation using the ammonium acetate–EDTA soil test

As a result of the important role played by phosphorus (P) in surface water eutrophication, the susceptibility of soils to release P requires evaluation. The degree of phosphorus saturation, assessed by oxalate extraction (DPS_ox), has been used as an indicator. However, most laboratories do not include DPS_ox in routine soil tests because of cost and time. This study evaluates the suitability of the ammonium acetate extraction in the presence of EDTA (AAEDTA), the standard soil test P (STP) in Wallonia (Southern Belgium), to predict DPS_ox; we also compared it with the Mehlich 3 extraction. Ninety‐three topsoil samples were collected in agricultural soils throughout Wallonia. Good correlations were found between the AAEDTA and the Mehlich 3 methods for P, Fe and Al (r = 0.85, 0.77 and 0.86, respectively). An exponential relationship was found between P_AAEDTA and DPS_ox. Results of principal component analysis and regression demonstrated that STP can be used to predict DPS_ox (r = 0.93) after logarithmic transformation. Soil test Al was also a good indicator of the P sorption capacity (PSC_ox) of soils (r = 0.86). Including the clay fraction in regression equations only slightly improved the prediction of PSC_ox (r = 0.90), while other readily available data (such as pH or organic carbon) did not significantly improve either DPS_ox or PSC_ox predictions.     

Relationship between corn yield and chemical composition of the ear leaf measured with different regression models

Abstract

Corn yields and leaf samples were obtained from experimental plots receiving varying rates of N, P and K. Yields were regressed on leaf levels of N, P, K, Ca, Mg, B, Cu, Fe, Mn and Zn as independent variables. Various polynomial regressions were fitted to the yields and “goodness of fit”; of particular mathematical models was used as a basis for evaluating particular biological and statistical concepts.

It was found that no regression, where chemical elements were used as ratios, fit the observations as well as a quadratic polynomial or its square root transformation. This suggests that within the set of data used, emphasis on particular cation or anion ratios does not necessarily result in the “best”; explanation of variation in yield.

“Classical”; growth equations were fitted to corn yields, but were not as precise in predicting yields as the polynomials. A modified stagewise regression procedure was used for fitting one mathematical model, but results were less satisfactory than those obtained with usual least squares procedures.     

基于社会燃烧理论的耕地非农化驱动因素分析

中国耕地非农化现象日益明显。基于社会燃烧理论分析了耕地非农化的驱动原理,建立了耕地非农化影响机制模型,并运用SPSS 19.0软件对分类驱动因素进行了主成分及回归分析。结果表明,人均GDP和固定资产投资所占GDP比重等经济发展变量对耕地非农化水平的正向影响最大;粮食单产、总产等农业技术变量对耕地非农化水平具有最大的逆向影响。最后在模型拟合的基础上提出了相应的对策与建议,旨在为合理有效保护耕地提供参考。     

Influence of Soil Particle Size on the Measurement of Sodium by Near-Infrared Reflectance Spectroscopy

This study evaluates the effect of soil particle size (SPS) on the measurement of exchangeable sodium (Na) (EXC-Na) by near-infrared reflectance (NIR) spectroscopy. Three hundred thirty-two (n = 332) top soil samples (0–10 cm) were taken from different locations across Uruguay, analyzed by EXC-Na using emission spectrometry, and scanned in reflectance using a NIR spectrophotometer (1100–2500 nm). Partial least squares (PLS) and principal component regression (PCR) models between reference chemical data and NIR data were developed using cross validation (leaving one out). The coefficient of determination in calibration (R²) and the root mean square of the standard error of cross validation (RMSECV) for EXC-Na concentration were 0.44 (RMSECV: 0.12 mg kg^–1) for soil with small particle size (SPS-0.053) and 0.77 (RMSECV: 0.09 mg kg^–1) for soils with particle sizes greater than 0.212 mm (SPS-0.212), using the NIR region after second derivative as mathematical transformation. The R² and RMSECV for EXC-Na concentration using PCR were 0.54 (RMSECV: 0.07 mg kg^–1) and 0.80 (RMSECV: 0.03 mg kg^–1) for SPS-0.053 and SPS-0.212 samples, respectively.