不同波长选择方法在土壤有机质含量检测中对比研究

由于近红外光谱数据的多重共线性，特征波长选择一直是近红外光谱分析技术的重要研究内容。以108个土壤样本光谱数据和土壤有机质(SOM)含量为研究对象，以连续投影算法（SPA）、间隔偏最小二乘法（IPLS）、竞争自适应重加权采样法（CARS）三种典型的特征波长选择算法进行近红外光谱波长选择和土壤有机质含量建模。研究结果表明，基于上述三种方法提取的特征波长所建立的模型预测能力均优于全谱模型。其中，基于SPA算法的MLR预测模型精度最优，预测集相关系数（Rp）和均方根误差（RMSEP）分别为0970 2和1.214 4，模型参数只有6个。因此，SPA-MLR可以有效地应用近红外光谱的建模，并且简化模型的复杂度，提高模型的计算效率。     

宁夏玉米营养成分近红外分析模型建立与应用

研究采集宁夏区内各市县(固原、海原、同心、中卫、中宁、永宁、平罗)抽取玉米样品120批,用近红外分析仪扫描定标样品集获得玉米近红外光谱图,利用偏最小二乘法建立模型,并分别经过无预处理、均值中心化、标准正态变量转换、一阶导数、标准正态变量转换结合去趋势校正(SNV+D)预处理光谱,获得水分、粗蛋白、粗脂肪、粗纤维预测模型,分别是经过MC、SNV+D、SNV+D、SNV+D光谱预处理后效果最好。预测决定系数R² _p分别为0.951、0.976、0.728、0.897,相对分析误差RPD除粗脂肪为2.62外,其他均大于3的近红外预测模型,通过预测模型验证集验证后,并对模型预测值与实测值进行U检验,结果为差异不显著(P>0.05)。该近红外预测模型对玉米中水分、粗蛋白、粗纤维具有较佳预测效果,粗脂肪的预测精度有待进一步提高。     

Land surface temperature retrieval for arid regions based on Landsat-8 TIRS data:a case study in Shihezi,Northwest China

Scientific interest in geophysical information about land surface temperature （LST） is ever increasing, as such information provides a base for a large number of applications, including environmental and agricultural monitoring. Therefore, the research of LST retrieval has become a hot topic. Recent availability of Landsat-8 satel- lite imagery provides a new data source for LST retrieval. Hence, exploring an adaptive method with reliable ac- curacy seems to be essential. In this study, basing on features of Landsat-8 TIRS thermal infrared channels, we re-calculated parameters in the atmospheric transmittance empirical models of the existing split-window algorithm, and estimated the ground emissivity with the help of the land cover classification map of the study area. Further- more, a split-window algorithm was rebuilt by virtual of the estimation model of the updated atmospheric transmit- tance and the ground emissivity, and then a remote sensing retrieval for the LST of Shihezi city in Xinjiang Uygur autonomous region of Northwest China was conducted on the basis of this modified algorithm. Finally, precision validation of the new model was implemented by using the MODIS LST products. The results showed that the LST retrieval from Landsat-8 TIRS data based on our algorithm has a higher credibility, and the retrieved LST is more consistent with the MODIS LST products. This indicated that the modified algorithm is suitable for retrieving LST with competitive accuracy. With higher resolutions, Landsat-8 TIRS data may provide more accurate observation for LST retrieval.     

基于无人机成像高光谱影像的冬小麦LAI估测

利用无人机Cubert UHD185 Firefly成像光谱仪和ASD光谱仪获取了冬小麦挑旗期、开花期和灌浆期的成像和非成像高光谱以及LAI数据。首先,对比ASD与UHD185光谱仪数据光谱反射率,评价两者精度;然后,选取7个光谱参数,分析其与冬小麦3个生育期LAI的相关性,并使用线性回归和指数回归挑选出最佳估测参数;最后利用多元线性回归、偏最小二乘、随机森林、人工神经网络和支持向量机构建了冬小麦3个不同生育期LAI的估测模型。结果表明:UHD185光谱仪光谱反射率在红边区域与ASD光谱仪趋势一致性很高,反射率在挑旗期、开花期、灌浆期的R^2分别为0.9959、0.9990和0.9968,UHD185光谱仪数据精度较高;7种光谱参数在挑旗期、开花期、灌浆期与LAI相关性最高的参数分别是NDVI(r=0.738)、SR(r=0.819)、NDVI×SR(r=0.835);LAI-MLR为冬小麦LAI的最佳估测模型,其中开花期拟合性最好,精度最高(建模R^2=0.6788、RMSE为0.69、NRMSE为19.79%,验证R^2=0.8462、RMSE为0.47、NRMSE为16.04%)。     

4种植物油热氧化同步荧光光谱分析

以亚麻籽油、大豆油、菜籽油与葵花籽油为原料,在不同温度条件下氧化并测定其不同时间的同步荧光光谱,分析同步荧光光谱及荧光物质变化情况。结果表明,4种植物油不同温度下的同步荧光光谱峰变化主要集中在300~415 nm内,且随着加热时间的延长存在波动现象;在50℃和150℃加热氧化条件下,300,330,375,415 nm这4个峰都存在明显的波动现象;二维相关分析表明,这4个峰的荧光强度变化速率不同,不同油变化差异较大;同种油在不同温度下,4个峰的波动情况、相互关系、变化速率均有明显差异。这些峰的变化与油脂氧化过程中荧光物质和油脂氧化程度的变化有关,可以利用同步荧光光谱的变化特性作为监控油脂氧化的依据。     

The use of the hand-held infrared thermometer as an early detection tool for exertional heat illness in Thoroughbred racehorses: A study at racetracks in eastern Australia

Thoroughbred racehorses perform exercise at maximal intensities and typically display a hyperthermic exercise response, which can drive core body temperature to critical levels. Despite extremely efficient thermoregulatory mechanisms, certain weather conditions may affect the horse’s ability to cool and result in a syndrome referred to as exertional heat illness (EHI). This is characterised by central nervous system dysfunction, as well as cytotoxic effects of heat on cells, which can produce deleterious consequences. Early detection of exertional heat illness (EHI) in Thoroughbred racehorses can be difficult because signs are often vague and the measurement of rectal temperature as an indicator of hyperthermia is not practical. Best practice in the treatment of EHI in horses, as in human subjects, centres on early detection, rapid assessment and aggressive cooling. Research in human subjects has shown that EHI is manageable when recognised early and appropriate treatment provided. The aim of this study was to investigate the measurement of skin surface temperature (SST) by an infrared thermometer as an aid in the early detection of EHI. A skin surface temperature ≥39°C in the immediate postrace period is considered to be hot. It reflects the interaction of exercise-related metabolic heat production, physiological adjustments to the skin surface such as vasodilation and sweating, together with the effect of high ambient temperature. Most importantly, high SST is associated with a reduced core-to-skin temperature difference, which retards heat transfer from the deep body tissues to the skin and can hinder heat dissipation. Identification of horses with high SSTs can prioritise them for rapid cooling and curtail possible progression to EHI.     

Changes in wettability of wood surface using electron beam irradiation

ABSTRACT

This study deals with the influence of electron beam irradiation (EBI) on the wettability of Norway spruce surface samples. To evaluate this possible effect in detail, the changes in chemistry and wood structure were analysed using the methods of IR spectroscopy and Scanning Electron Microscopy (SEM). The surface wettability was determined by the contact angle measurement method. The results of infrared spectra show decreased relative numbers of available hydrophilic groups (e.g. hydroxyl and carbonyl groups) in the wood surfaces due to the electron beam irradiation. This behaviour is consistent with the values from the surface wettability measurements. Structural differences of the wood surfaces after electron beam irradiation were not detectable. Based on these findings pre-treatment of wood surfaces for industrial usages can be a potential field of application of this technology.     

大麦籽粒抗性淀粉含量快速测定方法研究

为探索快速高效测定大麦籽粒中抗性淀粉含量的方法，利用衰减全反射中红外（attenuated total reflection mid-infrared spectroscopy,ATR-MIR）和近红外（near-infrared spectroscopy,NIR）光谱技术，分别用3种不同方法进行预处理，建立大麦样品的抗性淀粉含量快速测定红外模型，通过不同预处理预测模型的校正和内部交叉验证结果的比较，依据决定系数（r）和均方根误差（RMSE）筛选出基于ATR-MIR和NIR光谱的最佳预测模型，再对最佳预测模型进行外部验证。结果表明，经基线位移校正+范围归一化（BOC+RN）预处理后的PLS模型为最佳ATR-MIR预测模型；经标准正态变换+Savitzky-Golay法一阶求导（SNV+1thD）的预处理模型为最佳NIR预测模型。用验证集材料对BOC+RN和SNV+1thD最佳预测模型的预测效果进行外部验证，光谱预测值与化学测定值之间没有显著差异，说明两种方法均可以用于大麦籽粒抗性淀粉含量测定；ATR-MIR光谱比NIR光谱具有更好的预测能力。     

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.     

Growing Degree Day: Noninvasive Remotely Sensed Method to Monitor Diet Crude Protein in Free-Ranging Cattle

The daily nutritional balance of free-ranging cattle is the net result of intake from available forage biomass and nutritive value weighed against the nutritional requirements of the animal. Plant phenology influences nutritive value. Plant phenology is dictated by time of year and an accumulation of photosynthetically active days. Growing degree day (GDD) is a concept that quantifies this relationship and has been used to predict nutritive value in perennial range grasses. GDD could be substituted for chemical analysis to inform grazing animal nutritional monitoring efforts. We hypothesized that in C4 grass-dominated rangelands, a cumulative GDD calculation would correlate with diet crude protein (CP) predictions obtained by fecal near infrared spectroscopy (FNIRS) from free-ranging cattle. Therefore, the objectives of our research were to evaluate the effectiveness of GDD to predict FNIRS-derived determinations of grazing cattle diet CP in 1) two groups of three individual animals grazing a small native pasture and 2) large commercial-scale herds grazing expansive rangelands. For the first objective, cumulative GDD and FNIRS-predicted diet CP were strongly correlated (r² = 0.76; P < 0.01). Relationships between cumulative GDD and FNIRS-predicted diet CP for the second objective varied considerably among ranches, ranging from a low r² of 0.05 (P = 0.871) to a high r² of 0.78 (P < 0.049). Similar values for individual ranch/year combinations were stronger; ranging from a minimum r² of 0.44 (P = 0.556) to a maximum of 0.95 (P = 0.051). The aggregate relationship between GDD and FNIRS-predicted CP for all ranch/year combinations was highly significant (r² = 0.37; P < 0.001), but the standard error was 1.86% CP. The noninvasive remotely sensed grazing animal nutritional monitoring method described here was accurate enough to inform tactical rangeland diet quality assessments but was not accurate enough to inform operational-scale grazing management decisions.