地理加权回归及其在土壤和环境科学上的应用前景

地理加权回归(GWR)是近些年来出现的一种新的空间局部回归技术。它是将数据的空间位置嵌入线性回归模型中,以此来探测空间关系的非平稳性。在运用于空间数据分析方面,相对于传统的普通最小二乘回归法,具有明显的优势。本文首先介绍了GWR的理论起源并描述了该方法的基本原理、存在的不足以及后来的扩展;然后为了更准确地了解GWR的应用状况和研究进展,进行了一个文献调查;接着回顾了GWR在土壤和环境科学上的初步应用情况;最后对该方法在土壤和环境科学上的应用前景作了展望。目的是为我国土壤和环境科学领域的同行了解和应用GWR提供参考。经过国内外研究者多年的研究和实践,GWR方法已被证明是一个理论上较为成熟,能够应用到实际研究中的优秀空间统计学方法。因此,GWR在土壤和环境科学上将会有着广泛的应用前景。     

Hyperspectral Visible–Near Infrared Determination of Arsenic Concentration in Soil

The development of rapid techniques, such as hyperspectral spectrophotometry, for investigating arsenic (As) soil contamination could be of great value with respect to conventional methods. This study was conducted to detect As concentrations in artificially polluted soils (from 25 to 1045 mg kg^?1) through hyperspectral visible–near infrared spectrophotometry and to compare two multivariate statistical regression analyses: partial least squares and support vector machines. The correlation coefficient r is greater in the partial least squares in both model (0.93%) and test (0.87%) with respect to support vector machines (0.88% for the model and 0.82% for the test). The most important model variables extracted from the variable importance in projection scores resulted the absorption peaks at 580, 660, 715, and 780 nm. Bands in the visible spectra are not directly associated to As, but the metalloid can interact with the main spectrally active components of soil permitting to multivariate statistical models to screen As concentrations.     

Rapid determination of lime requirement by mid‐infrared spectroscopy: A promising approach for precision agriculture

Mid‐infrared spectroscopy (MIRS) has proven to be a cost‐effective, high throughput measurement technique for soil analysis. After multivariate calibration mid‐infrared spectra can be used to predict various soil properties, some of which are related to lime requirement (LR). The objective of this study was to test the performance of MIRS for recommending variable rate liming on typical Central European soils in view of precision agriculture applications. In Germany, LR of arable topsoils is commonly derived from the parameters organic matter content (SOM), clay content, and soil pH (CaCl₂) as recommended by the Association of German Agricultural Analytical and Research Institutes (VDLUFA). We analysed a total of 458 samples from six locations across Germany, which all revealed large within‐field soil heterogeneity. Calcareous topsoils were observed at some positions of three locations (79 samples). To exclude such samples from LR determination, peak height at 2513 cm^?1 of the MIR spectrum was used for identification. Spectra‐based identification was accurate for carbonate contents > 0.5%. Subsequent LR derivation (LR_SPP) from MIRS‐PLSR predictions of SOM, clay, and pH (CaCl₂) for non‐calcareous soil samples using the VDLUFA look‐up tables was successful for all locations (R² = 0.54–0.82; RMSE = 857–1414 kg CaO ha^?1). Alternatively, we tested direct LR prediction (LR_DP) by MIRS‐PLSR and also achieved satisfactory performance (R² = 0.52–0.77; RMSE = 811–1420 kg CaO ha^?1; RPD = 1.44–2.08). Further improvement was achieved by refining the VDLUFA tables towards a stepless algorithm. It can be concluded that MIRS provides a promising approach for precise LR estimation on heterogeneous arable fields. Large sample numbers can be processed with low effort which is an essential prerequisite for variable rate liming in precision agriculture.     

Removing Moisture Effect on Soil Reflectance Properties: A Case Study of Clay Content Prediction

Visible, near-infrared and shortwave-infrared (VNIR-SWIR) spectroscopy is an efficient approach for predicting soil properties because it reduces the time and cost of analyses. However, its advantages are hampered by the presence of soil moisture, which masks the major spectral absorptions of the soil and distorts the overall spectral shape. Hence, developing a procedure that skips the drying process for soil properties assessment directly from wet soil samples could save invaluable time. The goal of this study was twofold:proposing two approaches, partial least squares (PLS) and nearest neighbor spectral correction (NNSC), for dry spectral prediction and utilizing those spectra to demonstrate the ability to predict soil clay content. For these purposes, we measured 830 samples taken from eight common soil types in Israel that were sampled at 66 different locations. The dry spectrum accuracy was measured using the spectral angle mapper (SAM) and the average sum of deviations squared (ASDS), which resulted in low prediction errors of less than 8% and 14%, respectively. Later, our hypothesis was tested using the predicted dry soil spectra to predict the clay content, which resulted in R² of 0.69 and 0.58 in the PLS and NNSC methods, respectively. Finally, our results were compared to those obtained by external parameter orthogonalization (EPO) and direct standardization (DS). This study demonstrates the ability to evaluate the dry spectral fingerprint of a wet soil sample, which can be utilized in various pedological aspects such as soil monitoring, soil classification, and soil properties assessment.     

PLS算法在高光谱估测加工番茄白粉病色素含量中的应用

采用传统光谱特征参数和新建光谱特征参数对色素含量进行多光谱特征参数的偏最小二乘法(PLS)估算,以此来估测加工番茄白粉病病叶色素含量,并进行精度检验。结果表明:色素含量原始光谱与反对数光谱的敏感波长分别为350～718 nm、719～839 nm和350～718 nm、728～857 nm。从传统光谱特征参数和新建光谱特征参数中选取9个光谱特征参数PSNDa、GNDVI、PSSRa、PSSRb、GM、TPMPa、TPMPb、TPMPc和TPMPd,分别构成PGP、PGT、TTT 3组对色素含量进行估测,TTT组为色素含量光谱组合最佳估测模型。     

去早蕾对转基因抗虫棉黄萎病发生及早衰的影响

 以我国黄河流域和长江流域种植面积较大的8个品种为试验材料,研究了去早蕾对棉花黄萎病、生理性早衰及产量的影响。结果表明,去早蕾可显著减轻棉花黄萎病和早衰危害。2005年7月18日、8月19日和2006年8月22日,去早蕾处理黄萎病病情指数显著低于对照;除欣抗4号外,其它7个品种病情指数降低1.6%～15.0%,99B、冀668、豫杂35、中棉所41与对照之间差异达显著水平。2005年8月19、8月24日和2006年8月27日,去早蕾处理早衰指数显著低于对照;除邯109外,其它7个品种早衰指数降低1.3%～19.0%,99B、冀668、豫杂35、中棉所29之间差异达显著水平。去早蕾能显著提高棉花产量,但在不同品种之间存在差异,其中杂交棉品种表现较为明显。     

Friedman检验和定量描述分析法(QDA)在风味酸奶感官评定中的应用

对青橘味(A)、甜橙味(B)、西柚味(C)、柠檬味(D)4种柑橘类酸奶的整体喜好度、感官特性进行评价。其中整体喜好度采用非参数Friedman检验和多重比较中的最小显著差数法(LSD),感官特性选择10个描述风味酸奶的感官描述词进行定量描述分析法(QDA)评价,同时采用偏相关性分析整体喜好度与感官特性关系。结果显示4种产品的整体喜好度评分排序为:C>B>A>D,即评价员最喜欢的是西柚味酸奶,其次是甜橙味酸奶、青橘味酸奶,最不喜欢的是柠檬味酸奶。在5%显著性水平上,C样品明显比A、D样品更受喜欢,B样品明显比D样品更受喜欢。将4种样品分为4组,通过QDA法分析,4种风味酸奶的感官特性各有特色。整体喜好度及感官特性的相关性结果显示,评价员喜欢总香气、奶香气、发酵味、果香气稍强,甜味稍强,稠厚,无苦味的产品,对带有涩感和有颗粒感的样品的喜好度不一致,对香气太强或太弱、稠厚度太强、酸味太弱的产品的喜好度有所下降。     

基于低场核磁的稻谷储藏指标快速测定初探

本研究用国标方法和低场核磁仪器分别检测3种储藏年份和2个品种籼稻的含水量、粗脂肪含量、直链淀粉、发芽率等理化指标和横向弛豫曲线,简单分析弛豫曲线的变化规律,并采用偏最小二乘法将理化指标和核磁数据进行关联.结果表明,稻谷的横向弛豫强度衰减速度很快,弛豫时间段0～300ms为区分稻谷样品的重要特征信号区域;回归模型结果初步表明使用低场核磁能够较好地预测稻谷储藏指标,如含水量、脂肪含量、直链淀粉和发芽率等.