Near-infrared spectroscopy for determination of soil organic C,microbial biomass C and C and N fractions in a heterogeneous sample of German arable surface soils

Visual and near-infrared spectroscopy (vis-NIRS) is an established method to estimate soil properties. However, only limited information is available to estimate C and N fractions in a heterogeneous sample. The objectives of our study were to determine estimation accuracies of vis-NIRS using two software for soil organic carbon (SOC), total nitrogen (N_t), pH, texture, and C and N fractions (light (LF), mineral (MF), labile, intermediate and passive fractions) in a heterogeneous sample (consisting of 51 units with different mineralogy) and to compare these results with those obtained by mid-infrared spectroscopy (MIRS). Analyzing vis-NIRS spectra and the mentioned properties showed a possibility to distinguish between high and low values for SOC (residual prediction deviation (RPD) = 1.90) and N_t (RPD = 1.93). Sand and clay could be estimated, whereas pH and silt could not. No useful estimation was possible for N-LF, passive C, intermediate C or intermediate N. C-LF, C-MF and N-MF could be differentiated between high and low values, whereas for passive N the estimation was approximate quantitative. MIRS reached one or two times higher estimation categories than vis-NIRS for SOC, N_t, pH and texture, suggesting that MIRS has a higher potential to estimate soil properties in a heterogeneous sample.     

Identification of low productivity sites for European larch (Larix decidua Miller) in Maine,USA

As silvicultural capital becomes limited, allocation of funds to high quality sites becomes critical and sites with low productivity potential should be avoided. Data collected from 31 plots located in 12 plantations established between 1930 and 1982 throughout central Maine were used to develop a soil-based rule to identify sites having a low productivity potential for European larch in Maine, thereby removing them from consideration for plantation establishment. Stepwise regression and discriminant analyses identified several variables that were associated with site index at an index age of 20 years breast height (SI₂₀): solum thickness, B horizon clay content, and B horizon exchangeable K. Using these variables, a classification rule was developed to classify sites into 2 categories (poor, average SI₂₀=14.7 m; and good, average SI₂₀=17.7 m). Cross-validation demonstrated that the classification functions correctly identified 88% of the poor sites and 81% of the good sites.     

Bayes逐步判别法在绿茶板栗香化学识别上的应用

由经验丰富的感官审评专家对各茶样进行感官审评,依据感官审评结果将茶样分为板栗香型、非板栗香型两大类;应用Bayes逐步筛选过程对具有板栗香茶样的共有成分先进行筛选,再以筛选出的香气成分为变量,建立判别方程。交叉验证和检验样本验证结果显示:用筛选出的顺-茉莉酮和香叶基丙酮建立的判别方程,在训练数据集判别和交叉验证中,判别正确率均达到94.44%;对8个检验样本都做出了正确的判断,正确率为100%,可认为,该判别方程有效,判别结果理想。此外,由顺-茉莉酮和香叶基丙酮的主成分图也可得出,筛选出的变量对板栗香与非板栗香具有很好的区分效果。     

基于GIS空间插值的降水分布模拟方法比较研究

为了获取区域最优插值方案,模拟降水空间分布信息,基于1960-2015年湖南省87个气象站点资料,利用ArcGIS 10.2软件平台,采用克里金法、反距离权重法、样条函数法和趋势面法对研究区近56 a年均降水量进行空间插值,通过比较各插值方法的插值精度获得适合区域的插值方法,并分析了研究区降水空间分布特征.结果表明:湖...     

基于BP神经网络猪咳嗽声识别

咳嗽是猪患呼吸道系统疾病发病早期的主要症状.为解决猪呼吸系统疾病难以被发现和人工监测准确率低的问题,提出利用BP神经网络来检测和识别猪咳嗽声音的方案.基于四麦克风阵列进行猪声音数据的采集,以猪咳嗽声、打呼噜声、尖叫声、哼哼声、咆哮声的声音为研究对象,对得到的声音数据进行滤波、端点检测等预处理,把梅尔频率倒谱系数(MFC...     

近红外分析技术在稻米淀粉RVA谱特征值测定中的应用

采用近红外光谱分析技术和化学计量方法建立了稻米淀粉RVA谱3项(BDV、SBV、CSV)与稻米其它品质相关显著的特征值的近红外分析模型,并对模型进行了预测准确性评价。结果显示BDV、SBV和CSV的模型校正决定系数Rc2分别为0.9707,0.9966和0.9943,校正标准差RMSEE分别为4.12,2.41和1.72;内部交叉检验的决定系数Rcv2分别为0.942,0.9942和0.9913;标准差RMSECV分别为5.4,2.87和1.99。验证决定系数除DBV外均达到0.99以上,模型准确性较高,具有实用价值。     

Determining and mapping some soil physico-chemical properties using geostatistical and GIS techniques in the Naqade region,Iran

The distribution variability of soil electrical conductivity (EC), pH, clay, sand, CaCO₃, organic carbon (OC) and available potassium (K) in the Naqade region was investigated using a geostatistical method and Geographical Information System (GIS) technique. Two hundred and eighty-two topsoil (0–30 cm) samples were randomly collected and analyzed. pH and clay followed a normal distribution, whereas sand EC, CaCO₃, OC and K were log-transformed. The highest variation was observed for soil EC, and the lowest for soil pH. In the variography analysis, spherical, exponential and gaussian models were best fit on experimental semivariograms. The minimum effective spatial autocorrelation was 1500 m for OC and the maximum effective spatial autocorrelation was 4000 m for sand and K. Strong spatial correlations were noted with sand and CaCO₃ (<25%), whereas values were moderate for clay, EC, OC and K (25–75%). Ordinary kriging was utilized for the interpolation of estimated variable determinations in unsampled sites. It was found that soil properties in this study area were strongly influenced by both environmental and natural factors. The results can be used as a source of information for the development and implementation of any further land management and soil and water conservation plans.     

Total tree,merchantable stem and branch volume models for miombo woodlands of Malawi

The objective of this study was to develop general (multispecies) models for prediction of total tree, merchantable stem and branch volume including options with diameter at breast height (dbh) only, and with both dbh and total tree height (ht), as independent variables. The modelling data set was based on destructively sampled trees and comprised 74 trees from 33 tree species, collected from four forest reserves located in different ecological zones of Malawi. The dbh and ht ranges for the data set were 5.3–111.2?cm and 3.0–25.0?m, respectively. A number of alternative model forms were tested and the final model selection was based on root mean square error (RMSE) values calculated using a leave-one-out cross-validation procedure. The model performances and the evaluations of the finally selected models (R? 2 range 0.72 to 0.92; RMSE range 38% to 71%; mean prediction errors range ?1.4% to 1.3%) suggest that all models can be used over a wide range of geographical and ecological conditions in Malawi with an appropriate accuracy in predictions. The appropriateness of the developed models was also supported by the fact that the mean prediction errors of these models were much lower than the mean prediction errors (range ?23.6% to 48.9%) of some previously developed models tested on our data.     

晋西黄土区土壤水分时空异质性分析

选择山西吉县蔡家川流域典型坡面,应用同一尺度(20 m×20 m)取样方法机械布设土壤水分监测点(313个),用TDR水分测定仪测定土壤水分(测定时间:2005年,分两个季节:4月和8月;土壤剖面分两个层次:0~30cm和30~60 cm),基于kriging插值的方法生成了研究区土壤水分空间分布图,并结合观测季土壤水分的时空分布状况,研究土壤水分在空间和时间上分布的随机性和结构性特征。研究结果表明:4月份0~30 cm土层土壤平均含水量低于30~60 cm土层,土壤水分变异系数高于30~60 cm土层,而8月份0~30 cm土层土壤平均含水量明显高于30~60 cm土层,土壤水分变异系数高于30~60 cm土层;4月、8月表层土壤水分含量基本相当,而底层土壤水分含量8月明显低于4月;8月土壤水分的空间异质性程度小于4月;4月份0~30 cm3、0~60 cm土壤水分含量多集中于10~15%之间,而8月份0~30 cm土多集中于10~15%之间,而30~60 cm土壤水分均低于10%,生长初期土壤水分能支持植物生长的需要,而生长旺季植被的耗水明显增强,从土壤中吸收的水分明显增加。     

基于Hyperion植被指数的干旱地区稀疏植被覆盖度估测

受稀疏植被与明亮土壤背景影响,干旱地区植被覆盖精确遥感估测难度较大。以Hyperion影像为数据源,选取甘肃省民勤绿洲-荒漠过渡带为研究区,系统比较了利用不同类型高光谱及多光谱植被指数估测干旱地区稀疏植被覆盖度的能力,以期确定干旱地区稀疏植被覆盖度估测的最佳植被指数。不同植被指数估测稀疏植被覆盖度的能力利用线性回归R2及留一交叉验证的均方根误差进行比较,结果表明:高光谱植被指数估测稀疏植被覆盖度的能力显著优于相应的多光谱植被指数,抗大气植被指数(ARVI)及抗土壤和大气植被指数(SARVI)表现明显优于归一化植被指数(NDVI)与土壤调节植被指数(SAVI),其中以基于833.3nm/640.5nm波段组合的ARVI表现最佳,R2可达0.7294,均方根误差(RMSE)仅为5.5488。