Above and Below Ground Measurements of Greenhouse Gases from Swine Effluent Amended Soil

Abstract

As a means of economic disposal and to reduce need for chemical fertilizer, waste generated from swine production is often applied to agricultural land. However, there remain many environmental concerns about this practice. Two such concerns, contribution to the greenhouse effect and stratospheric ozone depletion by gases emitted from waste‐amended soils, have not been thoroughly investigated. An intact core study at Auburn University (32 36′N, 85 36′W) was conducted to determine the source‐sink relationship of three greenhouse gases in three Alabama soils (Black Belt, Coastal Plain, and Appalachian Plateau regions) amended with swine waste effluent. Soil cores were arranged in a completely random design, and treatments used for each soil type consisted of a control, a swine effluent amendment (112 kg N ha^?1), and an ammonium nitrate (NH₄NO₃) fertilizer amendment (112 kg N ha^?1). During a 2‐year period, a closed‐chamber technique was used to determine rates of emission of nitrous oxide (N₂O)–nitrogen (N), carbon dioxide (CO₂)–carbon (C), and methane (CH₄)–C from the soil surface. Gas probes inserted into the soil cores were used to determine concentrations of N₂O‐N and CO₂‐C from depths of 5, 15, and 25 cm. Soil water was collected from each depth using microlysimeters at the time of gas collection to determine soil‐solution N status. Application of swine effluent had an immediate effect on emissions of N₂O‐N, CO₂‐C, and CH₄‐C from all soil textures. However, greatest cumulative emissions and highest peak rates of emission of all three trace gases, directly following effluent applications, were most commonly observed from sandier textured Coastal Plain and Appalachian Plateau soils, as compared to heavier textured Black Belt soil. When considering greenhouse gas emission potential, soil type should be a determining factor for selection of swine effluent waste disposal sites in Alabama.     

风送喷雾雾滴粒径测量系统设计与影响因素试验

为方便测量不同喷雾条件下雾滴粒径大小,该文设计了喷头位置、喷雾角度、喷雾压力和风速大小等试验条件可精确调节的风送喷雾雾滴粒径测量系统。该系统喷头xyz三维空间位置调节范围分别为0～0.9、0～0.8和0～0.7m,调整精度为±0.04mm;喷雾角度调节范围为0～360°,调整精度为±0.005°;喷雾压力调节范围为0.2～0.5MPa,相对误差不大于1.5%;风速调节范围为0～15m/s,相对误差不大于4.17%。雾滴粒径风速影响特性试验表明,常用的3个粒径统计项D32、D43和DV0.5随风速增加而增大,其平均变化率分别为2.62、3.59和6.83μm·s/m,速度从3m/s增加到15m/s时,三者分别增加46%、26%和71%;雾滴粒径喷雾压力影响特性试验表明,D32、D43和DV0.5随压力增加而减小,其平均变化率分别为90.33、232.3和300.2μm/MPa,喷雾压力从0.2MPa增加到0.5MPa时,三者分别减小31%、36%和56%,表明风速和喷雾压力对雾滴粒径影响较大,在喷雾系统中进行风速和压力选择时需着重考虑其对粒径变化的影响。     

基于智能检测的发酵过程测控系统集成及应用

发酵测控系统是发酵过程参数智能检测与优化调控的基础,直接影响着发酵过程的控制性能。该文针对L-乳酸发酵过程的智能检测,提出了一种基于智能检测的发酵过程测控系统集成方法,给出了系统的体系结构及实现方法,集成了基于虚拟仪器技术的PXI总线发酵过程智能测控系统,给出了系统的软、硬件设计。该系统通过建立软测量模型,有效地实现了发酵过程不易测量参量的在线估计与控制,为发酵过程提供了一种新的测控系统。试验研究表明,将该系统应用到L-乳酸发酵过程中,通过在线估计葡萄糖液消耗量,实现了L-乳酸发酵过程补料优化控制,乳酸产量提高23%,提高了发酵产物得率。     

番茄叶片和果实热容量的热平衡测定方法

为了分析植物器官体温形成机制的需要,即在植物与环境间热平衡分析时,有准确的植物器官热容量参数,该文采用热平衡法测定了番茄叶片和果实的热容量参数。考虑胁迫生态环境植物传热分析问题,也选择了侧柏等生态恢复先锋树种,以及作为参照的肉质植物芦荟的热容量参数。结果表明,番茄叶片热容为3253.7±97.10J/(kg℃),与针叶植物侧柏和肉质叶植物芦荟叶片的热容相近;番茄果实热容为3517.4±68.50J/(kg℃)。热平衡法可以用来测定植物器官的热容量;其热容量均低于水的热容量。对前人用热平衡法测定生物质热物性参数的方法,进行了改进和完善。该文既为其他生物质的热容量测定提供了试验方法,也为植物气候空间研究提供了热物性参数基础数据。     

基于抽样调查地块实测数据的省级水稻单产遥感估算

利用统计局抽样调查地块实割实测标准单位面积产量数据及空间位置信息,在研究水稻种植区MOD09GA、MYD09GA EVI （enhanced vegetation index）数据结合使用可行性分析的基础上,进行湖南省省级水稻单产遥感估算。结果表明：在水稻种植区,水稻生长期间有超过50%、85%、95%的MOD09GA与MYD09GA EVI偏差绝对值分别小于0.03、0.08、0.1。水稻遥感估产模型以二次非线性模型或回归模型精度较高,且时相集中在水稻生长的孕穗期到抽穗期。在省级水平上,与实测值相比,基于统计局统计抽样调查地块实割实测标准单位面积产量数据的水稻单产遥感拟合结果相对误差小于2%,预测结果的相对误差接近5%,且实测值与模拟值集中分布在1∶1线附近,说明预测结果与统计值在空间分布上具有较好的一致性。     

便携式猪肉阻抗谱检测系统研制

基于生物阻抗谱检测原理,设计并实现了一个非破坏性的便携式肉品阻抗谱检测系统,主要包括信号发生单元和检测单元,信号源能够在0.1～250 kHz范围内自动扫频,检测单元由检测电极和增益、相位检测器构成。探讨了检测电极设计方案,比较分析了六钢针电极和四针石墨电极的性能,同时通过试验证明了系统的稳定性,1 kHz以上系统的变异系数CV＜6%;以组内相关系数ICC来评定在不同温度下系统的可靠性,系统模型中Ri、Re、C的ICC均大于65%,系统稳定可靠。选取猪肉样品进行了新鲜度指标与阻抗谱关系的初步研究,结果表明随着猪肉新鲜程度改变,猪肉复阻抗值、复阻抗实部值、复阻抗虚部值以及特征频率都表现出减小的趋势。     

棉花叶片厚度的高光谱测试方法

植物叶片厚度的变化能够指示植物生长状态的改变,为了实时、活体、无损地获取叶片厚度,该研究以棉花叶片为研究对象,利用DPS、Origin统计分析软件分析84组光谱数据与叶片厚度的相关性。研究表明,光谱反射率与叶片厚度在可见光350～369 nm及664～689 nm 2个较窄区域达到了极显著正相关关系,在红外917～1 884、2 048～2 380 nm 2个区域呈极显著负相关关系,总体相关程度红外波段高于可见光波段。红边参数与叶片厚度的相关性不高,24个形状参数与厚度达到了极显著相关水平,其中,中心为980 nm的吸收谷面积与叶片厚度相关度最高,相关系数为0.848。分别用反射率、植被指数、光谱形状参数建立并测试3个估算模型,相对误差最高为7.4%,均方根差最高为0.051 mm。结果表明利用高光谱分析技术,可以实现叶片厚度的快速、活体测量。     

A comparison of linear and exponential regression for estimating diffusive CH4 fluxes by closed-chambers in peatlands

The closed-chamber method is the most common approach to determine CH₄ fluxes in peatlands. The concentration change in the chamber is monitored over time, and the flux is usually calculated by the slope of a linear regression function. Theoretically, the gas exchange cannot be constant over time but has to decrease, when the concentration gradient between chamber headspace and soil air decreases. In this study, we test whether we can detect this non-linearity in the concentration change during the chamber closure with six air samples. We expect generally a low concentration gradient on dry sites (hummocks) and thus the occurrence of exponential concentration changes in the chamber due to a quick equilibrium of gas concentrations between peat and chamber headspace. On wet (flarks) and sedge-covered sites (lawns), we expect a high gradient and near-linear concentration changes in the chamber. To evaluate these model assumptions, we calculate both linear and exponential regressions for a test data set (n = 597) from a Finnish mire. We use the Akaike Information Criterion with small sample second order bias correction to select the best-fitted model. 13.6%, 19.2% and 9.8% of measurements on hummocks, lawns and flarks, respectively, were best fitted with an exponential regression model. A flux estimation derived from the slope of the exponential function at the beginning of the chamber closure can be significantly higher than using the slope of the linear regression function. Non-linear concentration-over-time curves occurred mostly during periods of changing water table. This could be due to either natural processes or chamber artefacts, e.g. initial pressure fluctuations during chamber deployment. To be able to exclude either natural processes or artefacts as cause of non-linearity, further information, e.g. CH₄ concentration profile measurements in the peat, would be needed. If this is not available, the range of uncertainty can be substantial. We suggest to use the range between the slopes of the exponential regression at the beginning and at the end of the closure time as an estimate of the overall uncertainty.     

番茄辣椒微型根系形态原位采集系统设计与实现

为实时获取浅根系作物的根系生长形态,设计了一种可用于多点测量的微型根系形态实时原位采集系统。系统主要由微型摄像头和光学放大元件等组成(体积1.5cm3),采集的图像通过无线模块发送至终端。采用基于区域生长的根系图像分析方法,以腐蚀图像为出发点,膨胀图像为终止点,结合相似性准则进行区域生长、区域标记和区域保留,来滤除土壤孔隙和杂质等对图像产生的干扰,从而提取根系轮廓,并通过图像形态学计算得到根长密度、根系平均直径等形态参数。以此系统采集樱桃番茄、辣椒根系形态参数,试验结果表明,根系长度测定值的绝对误差不超过1.5 mm,相对误差不超过5.3%;根系平均直径绝对误差不超过0.09 mm,相对误差不超过6.7%。与土壤采样法测定值相比,在0～10、10～20、20～30和30～40 cm 4个土壤层内2种测定方法根系平均直径决定系数R20.87(P0.01),根长密度在30 cm深度以内的土壤层决定系数R20.81(P0.01)。证明本文设计的微型根系形态实时原位采集系统具有较高的准确性,可用于浅根系作物形态的多点观测。     

The form of the calibration curve of a neutron moisture meter near the soil surface

Abstract

A considerable increase in accuracy of soil moisture determinations near the soil surface was possible with the depth probe of a neutron moisture meter when quadratic calibration curves were used