红外光谱结合多元线性回归法快速测定木塑复合材料中木粉含量

采用KBr压片法对杉木/聚丙烯(PP)复合材料样品进行了红外光谱分析,确定杉木特征吸收谱带为1740~1730、1610~1590、1270~1260、1060~1050以及1040~1030 cm-1,以PP在1377 cm-1处吸收强度(I)为内标,对木塑复合材料(WPC)中木粉含量和杉木特征峰相对吸收强度进行相关性分析,并采用逐步多元线性回归法建立木粉含量与相对峰强间的多元线性回归方程。结果表明,选取I(1060-1050)/I1377、I(1270-1260)/I1377为回归变量建立的二元线性回归方程和以I(1060-1050)/I1377、I(1040-1030)/I1377及I(1270-1260)/I1377为回归变量建立的三元线性回归方程,具有较高的预测精度。木粉含量的预测值和参照值之间具有强烈的相关性,校正决定系数(R2c)超过0.98,验证决定系数(R2p)超过0.96。外部验证结果表明,线性回归方程预测准确性较高,预测相对偏差范围为0.9%至7.4%,其中三元线性回归方程预测准确性稍好于二元线性回归方程。     

杉木双系种子园无性系开花习性与异交率及其间的关系研究

基于对杉木双系种子园中成对无性系开花习性的多年观察及多年对杉木双系种子园的同工酶实验,运用EM算法估计各无性系的异交率大小,并使用DPS统计软件,详实地研究了异交率与开花习性诸多因素间的关系,其结果为:Y=0.877 7+0.104 4X1-0.615 8X2+0.354 4X3-0.061 8X4。上式中:X1为异系雄球花量,X3为异系开花同步性指数,它们对异交率的影响有正效应;而X2为系内开花同步性指数,X4为X3/X2之比,它们对异交率的影响有负效应。影响力的大小次序为:X2>X4>X3>X1。根据异交率与开花习性的关系研究,可以发现:今后新建杉木双系种子园时,挑选系内开花同步性小,而系间开花同步性大的双亲材料时,其后代异交率较高。     

The loss of large wood affects rocky mountain trout populations

Western U.S. rivers are currently influenced by legacy effects of reduced large wood (LW) loading and retention that has substantially reduced in‐stream habitat complexity. Large wood is typically associated with streams in undisturbed old‐growth forest and in the correct geomorphic context can drastically alter stream and valley habitat complexity. Streams with LW are typically multichannel and depositional, while streams lacking LW, due to relatively recent wildfire or logging (<200 years ago), are usually single channelled and erosional. We compared population biomass and individual growth rates of Brook Trout Salvelinus fontinalis in streams across a gradient of wood volumes. At both the square metre and valley length scales, standing stock biomass of aquatic invertebrates was the best predictor of trout biomass. However, at the valley scale, the number of pools was important in predicting trout biomass in combination with standing stock biomass of aquatic invertebrates. Individual growth rates of age‐1 Brook Trout were negatively affected by increasing density; however, growth rates for the largest and smallest individuals at each site were unaffected by density. Our results suggest the pool habitat created by LW acts synergistically with prey availability to dramatically increase trout populations. However, in streams lacking LW, negative effects of detrimental land use practices have persisted >100 years, suggesting that recovering lost animal production in mountain stream networks will only occur at decadal to century time scales.     

Determination of Principal Components for Characterizing the Drying of Sea Cucumbers (Stichopus japonicus Selenka) Using Far Infrared Radiation Drying and Hot Air Drying

Principal component analysis (PCA) and multiple linear regression (MLR) were conducted to characterize the drying of sea cucumber (SC). Far infrared radiation drying (FIRD) and hot air drying (AD) were used to dehydrate SC. Thirteen variables—including the morphological, color, and textural properties of dried SC—were selected for statistical analysis. The analysis of these 13 variables yielded three principal components showing significant correlations. PCA showed that the first three components represented 86.2% of the total variation. The first principal component was primarily related to the morphological properties of SC. The principal components determined by the PCA were more strongly influenced by the morphological variables than by the drying method. Of the morphological variables, the weight of SC had the strongest influence on the drying time and rehydration ratio of FIRD and AD.     

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.     

基于MaxEnt模型的可可潜在适宜分布研究

根据野外采样和文献查阅,系统整理了可可的地理分布记录,并利用MaxEnt生态位模型和ArcGIS软件对可可的潜在适宜分布范围进行预测。结果表明:北美洲南部、中南美洲北部、非洲西部、亚洲东南部以及太平洋美拉尼西亚群岛地区均是可可的潜在适宜分布区域。其中,中国海南、台湾南部、云南西双版纳、广东雷州半岛也属于可可的适生范围。经ROC(Receiver operating characteristic)曲线分析法验证,MaxEnt模型的AUC(Area under curve)值为0.977,表明预测结果具有较高的可信度。各环境变量重要性的Jacknife检验表明,极端最低温度、年降雨量、年温度变化范围、最暖季降雨量对可可的潜在分布影响最大。     

基于PCA-SVR-ARMA的狮头鹅养殖禽舍气温组合预测模型

为提高狮头鹅养殖禽舍气温预测精度,提出了基于主成分分析(Principal Component Analysis,PCA)、支持向量回归机(Support Vector Regression,SVR)融合自回归滑动平均(Autoregressive Moving Average,ARMA)模型的狮头鹅养殖禽舍气温组合预测模型。在建模过程中,运用主成分分析法筛选狮头鹅养殖禽舍气温的关键影响因子,消除变量之间冗余信息,约简预测模型结构;采用SVR-ARMA构建狮头鹅禽养殖舍气温组合预测模型,先通过SVR对气温进行预测,再由基于ARMA模型的残差预测值修正气温预测结果。利用该模型对广东省汕尾市2018年7月21日至2018年7月30日期间的狮头鹅养殖禽舍气温进行预测。结果表明,该组合预测模型取得了良好的预测性能,与标准BP神经网络、标准SVR、PCA-BPNN(反向传播神经网络,BackPropagationNeuralNetwork)、PCA-SVR和PCA-BPNN-ARMA等模型对比分析,其评价指标平均绝对误差、均方根误差和平均绝对百分比误差分别为0.183 2℃、0.454 0℃和0.005 9,均表明所提出的组合模型具有更高的预测效果,不仅能够满足狮头鹅养殖禽舍气温实际精准调控的需要,还为狮头鹅健康养殖和种苗繁育环境精细化管理提供决策。     

地理探测器与Tobit模型在粤西地区粮食生产效率及影响因子分析中的比较应用

为明晰粤西地区粮食生产效率及其关键影响因子，实现优化资源配置效率和推进粮食生产转型升级，基于1999—2018年粤西地区茂名、阳江、湛江3市粮食生产数据，采用交叉效率DEA模型测算区域粮食生产效率，揭示近20年粮食生产效率的时空变化特征，并利用Tobit模型和地理探测器模型比较分析粮食生产效率的关键影响因子。结果表明：粤西地区粮食生产效率平均值为0.77，其中，茂名市粮食生产效率最高（0.88），阳江市次之（0.78），湛江市最低（0.65）。Tobit模型和地理探测器测算粤西地区粮食生产效率影响力（贡献力）最大的投入因子是农业机械总动力，分别为-1.082和0.942。Tobit模型测得的7个投入因子仅化肥施用量（0.015）与粮食生产效率呈显著正相关，有效灌溉面积、粮食播种面积、农药使用量3个因子与粮食生产效率相关性不显著，农用塑料薄膜使用量、从业人口、农业机械总动力3个因子呈显著负相关。而地理探测器测得所有因子均对粮食生产效率产生显著影响。阳江市投入因子贡献力与粤西地区大致相同，但化肥施用量贡献力高出有效灌溉面积0.008。湛江市与茂名市化肥和农药投入的贡献力仅次于农业机械总动力，有效灌溉面积贡献力均最低。但茂名市粮食播种面积的贡献力依次大于从业人口和农用塑料薄膜使用量，湛江市则相反。研究表明，20年来粤西地区粮食生产效率不高，整体呈中等效率水平，粮食生产效率先降后升的变化趋势显著；地理探测器测度结果无不显著因子存在，探测因子影响力比Tobit模型所得结果更稳定且偏误小；农业机械总动力是影响粤西3市粮食生产效率的主导因子，但不同城市粮食生产效率的因子贡献力差异较大，湛江和茂名对化肥、农药等污染较大的生产要素依赖性更强。