Application and verification of simultaneous determination of cellulose δ13C and δ18O in Picea shrenkiana tree rings from northwestern China using the high-temperature pyrolysis method

Stable isotopes in tree-ring cellulose provide important data in ecological, archaeological, and paleoenvironmental researches, thereby, the demand for stable isotope analyses is increasing rapidly. Simultaneous measurement of cellulose δ¹³C and δ¹⁸O values from tree rings would reduce the cost of isotopic commodities and improve the analytical efficiency compared with conventional separate measurement. In this study, we compared the δ¹³C and δ¹⁸O values of tree-ring α-cellulose from Tianshan spruce (Picea schrenkiana) in an arid site in the drainage basin of the Urumqi River in Xinjiang of northwestern China based on separate and simultaneous measurements, using the combustion method (at 1050°C) and the high-temperature pyrolysis method (at 1350°C and 1400°C). We verified the results of simultaneous measurement using the outputs from separate measurement and found that both methods (separate and simultaneous) produced similar δ¹³C values. The two-point calibrated method improved the results (range and variation) of δ¹³C and δ¹⁸O values. The mean values, standard deviations, and trends of the tree-ring δ¹³C obtained by the combustion method were similar to those by the pyrolysis method followed by two-point calibration. The simultaneously measured δ¹⁸O from the pyrolysis method at 1400°C had a nearly constant offset with that the pyrolysis method at 1350°C due to isotopic-dependence on the reaction temperature. However, they showed similar variations in the time series. The climate responses inferred from simultaneously and separately measured δ¹³C and δ¹⁸O did not differ between the two methods. The tree-ring δ¹³C and δ¹⁸O values were negatively correlated with standardized precipitation evapotranspiration index from May to August. In addition, the δ¹⁸O was significantly correlated with temperature (positive), precipitation (negative), and relative humidity (negative) from May to August. The tree-ring δ¹³C and δ¹⁸O values determined simultaneously through the high-temperature pyrolysis method could produce acceptable and reliable stable isotope series. The simultaneous isotopic measurement can greatly reduce the cost and time requirement compared with the separate isotopic measurement. These results are consistent with the previous studies at humid sites, suggesting that the simultaneous determination of δ¹³C and δ¹⁸O in tree-ring α-cellulose can be used in wide regions.     

加米霉素对照品标定方法的建立

建立了加米霉素对照品的标定方法。采用紫外光谱、红外光谱、核磁共振波谱、质谱和X射线单晶衍射进行结构确认,高效液相色谱法进行纯度检查,质量平衡法进行定量分析,并采用定量核磁技术对赋值结果进行验证。结果显示,加米霉素对照品原料纯度为99.9%;质量平衡法赋值结果为98.8%,定量核磁共振法验证结果为98.3%。加米霉素对照品原料定量赋值结果准确、可靠,能够用于加米霉素原料及制剂的鉴别和含量测定。     

New strategies for a reliable assessment of baking quality of wheat – Rethinking the current indicator protein content

New strategies for a reliable assessment of baking quality of wheat are required since the protein content is a widely discussed indicator in this respect. In this study, the indicator value of the protein content for baking quality was evaluated using almost 600 wheat samples representing different quality and varieties. NIRS calibrations were developed to estimate bread volume at different levels of processing. Bread volume increased with increasing protein content in a wide curvilinear relationship with an R² of 0.59. At protein contents above 12% representing the relevant range for trading, the R² dropped to 0.15. Different wheat varieties showed differential responses (i.e. linear and non-linear) in bread volume to increasing protein content. The performance of NIRS calibrations for bread volume were best at the processing level of dough (R² 0.81) and good at the level of whole grains (R² 0.70). Hence, the protein content is not a reliable indicator for baking quality on its own. Bread volume was predicted better by NIRS calibrations than by protein content. A strategy is presented paying attention to the variety specific interplay between baking quality and protein content with implications for the variety registration system, trading, breeding and nitrogen fertilisation.     

灌溉柑橘园中叶片湿润传感器校准方法研究

叶片湿润时间是植物病害模型的重要输入变量之一,它与许多叶部病原菌的侵染有关,影响病原侵染和发育速率。叶片湿润传感器可以实现对其实时、自动化监测,而由于叶片湿润时间受到环境和植物交互效应的影响,需要在灌溉环境下的柑橘园中进行校准。以生长季的柑橘为试验材料研究校准方法。叶片湿润传感器角度为30°,采用移液枪向传感器滴水和使用灌溉设施向传感器喷灌2种方法来确定传感器的干湿阈值;比较了柑橘冠层不同位置的传感器监测效果,并研究了有雨和无雨条件下对传感器监测效果的影响,最后通过神经网络模型验证阈值的合理性。结果表明：叶片湿润传感器在灌溉环境下干湿阈值为270 mV,此时传感器的监测效果最好,误差在2 h以内,通过与神经网络模型预测结果对比,证实此阈值下传感器监测效果良好;位于柑橘冠层底部位置的传感器监测准确率最高,可达0.95;传感器在无雨条件下监测效果优于有雨条件。该叶片湿润传感器校准方法可以用于灌溉柑橘园叶片湿润时间监测,符合柑橘病害预警系统的要求。     

香蕉秸秆离散元仿真粘结模型参数标定与试验

为提高离散元法对指导香蕉秸秆粉碎还田装备设计与优化的准确性与可靠性,本文利用Hertz-Mindlin with bonding接触模型建立香蕉秸秆离散元粘结模型并进行参数标定。运用高速摄影技术开展碰撞恢复试验、静摩擦及滚动摩擦台架试验,确定了香蕉秸秆碰撞恢复系数、静摩擦因数和滚动摩擦因数等基本离散元模型接触参数。开展香蕉秸秆物理与仿真剪切试验,获得破坏香蕉秸秆外皮的力学特征曲线,确定物理最大剪切力为122.41N;通过中心组合设计（Central composite design, CCD）响应面法确定香蕉秸秆粘结模型的法向接触刚度、切向接触刚度、临界法向应力与临界切向应力的最佳参数组合为5.89×107N/m、2.49×106N/m、1.39×105Pa、1.34×105Pa。以参数标定结果进行仿真验证,结果表明,仿真剪切力结果与物理剪切力相对误差仅为2.34%,验证了该粘结参数标定方法的可行性,可为香蕉秸秆粉碎还田机设计与研究提供理论参考。     

基于非线性耦合的土壤电导率传感器标定方法

针对土壤电导率传感器测量不准确的问题,提出了不考虑含水率θ与考虑θ的非线性耦合标定模型,并开展了土壤电导率传感器的标定与验证试验。标定试验采用新疆维吾尔自治区阿拉尔市十团苹果园沙土,使用去离子水与NaCl设计了9组含水率梯度与6组含盐量梯度共54组土样,分别使用土壤电导率传感器与高精度电导率仪对土样的电导率进行测量;根据耦合模型分别对不考虑θ、考虑θ以及考虑θ细分的3种处理进行拟合分析;最后对同一苹果园设计了大田验证试验。结果表明,土壤电导率传感器测量的电导率EC₀以及电导率仪测量的电导率EC₁与土壤含盐量均呈正相关,EC₀随θ的增加而增加,EC₁随θ的增加而减少;3次拟合结果表明,θ对电导率测量有显著影响,随θ细分,3个处理的残差逐渐减小,拟合决定系数R²均不小于0.839且逐渐增大;验证试验结果表明所提出耦合模型可以有效提高电导率测量精度,该标定方法可为土壤电导率准确测量以及土壤电导率传感器标定校准等相关研究提供依据。     

Estimating vertical vegetation density through a SPOT5 imagery at multiple radiometric correction levels

There is growing concern about remote sensing of vertical vegetation density in rapidly expanding peri-urban interfaces.A widely used parameter for such density,i.e.,leaf area index (LAI),was measured in situ in Nanjing,China and then correlated with two vegetation indices (VI) derived from multiple radiometric correction levels of a SPOT5 imagery.The VIs were a normalized difference vegetation index (NDVI) and a ratio vegetation index (RVI),while the four radiometric correction levels were i) post atmospheric correction reflectance (PAC),ii) top of atmosphere reflectance (TOA),iii) satellite radiance (SR) and iv) digital number (DN).A total of 157 LAI-VI relationship models were established.The results showed that LAI is positively correlated with VI (r varies from 0.303 to 0.927,p < 0.001).The R 2 values of "pure" vegetation were generally higher than those of mixed vegetation.The average R 2 values of about 40 models based on DN data (0.688) were higher than that of the routinely used PAC (0.648).Independent variables of the optimal models for different vegetation quadrats included two vegetation indices at three radiometric correction levels,indicating the potential of vegetation indices at multiple radiometric correction levels in LAI inversion.The study demonstrates that taking heterogeneities of vegetation structures and uncertainties of radiometric corrections into account may help full mining of valuable information from remote sensing images,thus improving accuracies of LAI estimation.     

Prediction of calibration interval for a measuring instrument using rolling grey bootstrap fusion model

A rolling grey bootstrap fusion model (RGBFM(1,1)) is proposed to predict calibration interval of a measuring instrument under small sample. The model combines GM(1,1) model with bootstrap method. Bootstrap re-sampling is used in the process of modeling the grey differential coefficient function to mine more information about systems. Both the instantaneous value and interval assessment values can be predicted using RGBFM(1,1), which can reduce prediction risk of calibration interval. In contrast, other prediction models only predict the instantaneous value. Experiments show that the RGBFM(1,1) can exactly describe the random wave of original sample data in prediction of instantaneous value, interval upper limit and lower limit, and has higher prediction reliability. Therefore, the RGBFM(1,1) is suitable for the prediction of calibration interval for a measuring instrument.     

玉米果穗离散元模型构建与脱粒仿真验证

针对玉米脱粒离散元仿真中果穗模型难以表征籽粒分离和芯轴破碎的问题，该研究构建了玉米果穗聚合体离散元模型并进行脱粒仿真验证。基于玉米芯轴3层结构采用分层建模与网格划分方法建立玉米芯轴离散元模型，结合Plackett-Burman试验、最陡爬坡试验、Box-Behnken试验和仿真弯曲试验标定粘结参数；以马齿型玉米籽粒为原型，采用五球粘结的籽粒-芯轴连接方式建立玉米果穗聚合体离散元模型，仿真标定籽粒与芯轴的连接力；最后模拟梯形杆齿、圆头钉齿和纹杆块3种脱粒分离机构的玉米脱粒进程。结果表明：玉米芯轴弯曲破坏力和弯曲刚度仿真结果与实测平均值的相对误差分别为-0.12%和-0.14%，籽粒果柄轴向压缩力和径向压缩力仿真结果与实测平均值的偏差分别为-1.8和2.46 N，3种脱粒分离机构脱粒段仿真区域内籽粒平均法向接触力依次为12.50、12.32和8.03 N，3种脱粒元件对籽粒平均法向接触力的递减趋势与台架试验的籽粒破碎率变化一致，根据籽粒与脱粒元件接触合力的累积频率曲线确定籽粒破碎率的临界接触合力为550 N，仿真未脱净率依次为0.15%、0.37%、0.35%，较台架试验结果分别偏小0.07、偏高0.04和偏小0.25个百分点，沿滚筒轴向籽粒质量分布百分比曲线均表现为正偏态单峰分布，脱粒仿真试验的曲线峰值分别比台架试验高1.03、1.86和0.85个百分点，两者脱粒质量相近。该玉米果穗聚合体离散元模型参数标定准确，能够准确反映籽粒和芯轴的力学特性差异，可还原玉米脱粒分离过程，为后续脱粒分离机构的优化提供参考依据。