Evaluation of Transmittance and Reflectance Pulse Oximetry in a Canine Model of Hypotension and Desaturation

Ten, anesthetized dogs were instrumented with three pulse oximeter probes; two lingual transmittance probes and one rectal reflective probe. Arterial oxygen desaturation was produced by decreasing the inspired oxygen concentration. Hypotension was produced with an infusion of nitroprusside. Simultaneous pulse oximeter readings (SpO₂) were compared to co-oximeter measured arterial saturation (SaO₂) collected over a range of SaO₂ (50–100%) and mean arterial pressures (40–100mmHg). Each of the monitors and means of evaluating SpO₂ studied provided accurate SpO₂ measurements over a range of mean arterial pressure from 40–100mmHg. All of the monitors tested tended to overestimate the SaO₂ when the arterial saturation was less than 70%.     

Prediction of chemical composition and peroxide value in unground pet foods by near‐infrared spectroscopy

The massive development of the pet food industry in recent years has lead to the formulation of hundreds of canine and feline complete extruded foods with the objective of meeting both the needs of the animals and numerous demands from pet owners. In the meantime, highly variable raw material compositions and the industry's new production techniques oblige manufacturers to monitor all phases of the extrusion process closely in order to ensure the targeted composition and quality of the products. This study aimed at evaluating the potential of infrared technology (visible and near‐infrared spectrophotometer; 570–1842 nm) in predicting the chemical composition and peroxide value (PV) of unground commercial extruded dog foods. Six hundred and forty‐nine commercial extruded dog foods were collected. For each product, an unground aliquot was analysed by infrared instrument while a second aliquot was sent to a laboratory for proximate analysis and PV quantification. The wide range of extruded dog food typologies included in the study was responsible for the wide variability observed within each nutritional trait, especially crude fibre and ash. The mean value of the 208 pet foods sampled for PV quantification was 17.49 mEq O₂/kg fat (min 2.2 and max 94.10 mEq O₂/kg fat). The coefficients of determination in cross‐validation of NIRS prediction models were 0.77, 0.97, 0.83, 0.86, 0.78 and 0.94 for moisture, crude protein, crude fat, crude fibre, ash and nitrogen‐free extract (NFE) respectively. PV prediction was less precise, as demonstrated by the coefficient of determination in cross‐validation (0.66). The results demonstrated the potential of NIRS in predicting chemical composition in unground samples, with lower accuracy for moisture and ash, while PV prediction models suggest use for screening purposes only.     

半湿润雨养农业区油菜冠层反射光谱与覆盖度的相关分析

以黄土高原甘肃庆阳西峰为半湿润雨养农区典型代表,分析研究油菜营养生长阶段苗期、蕾苔期和生殖生长阶段初期开花始期的冠层反射光谱特征与其覆盖度的相关性.结果表明,这几个时期油菜覆盖度与450、550、650、850、1650nm波段反射率存在明显的相关关系,尤其是蕾苔期,相关关系达到极显著水平.另外,研究了10个常用的植被指数同油菜覆盖度间的相关关系,这10个植被指数同油菜覆盖度存在着极显著的相关关系,相关性高于同单波段反射率间的关系.并且,利用各时期最优的2个植被指数建立了油菜覆盖度线性及非线性回归监测模型,方程的拟合度都较好.苗期,线形和非线性回归模型拟合程度差异不大,蕾苔期,以线性方程拟合精度较其它方程高;开花始期则以指数模型拟合精度高.     

低温胁迫下毛竹叶片色素质量分数与反射光谱的相关性

为了探讨低温处理后毛竹Phyllostachys edulis叶片反射光谱特性与色素质量分数的相互关系,筛选出能够准确监测低温胁迫下毛竹伤害程度的光谱参数。测定了低温处理后毛竹叶片色素质量分数与反射光谱的变化参数,分析叶片光谱反射率、微分光谱及特征参数与色素质量分数的相关性。结果表明:随着温度的降低,叶绿素a和类胡萝卜素质量分数呈下降趋势(P<0.01)。反射光谱参数光谱反射指数、改良红边比、色素比值指数、归一化植被指数、红边归一化指数、改良类胡萝卜素指数和光化学反射指数等均随着温度的降低而降低(P<0.01);红边面积随着胁迫加深不断减小,红边位置向短波方向移动。在绿光区和红光区,叶绿素a和类胡萝卜素质量分数与光谱反射率及微分光谱显著相关(P<0.05),且与大部分光谱参数达到极显著相关(P<0.01),说明反射光谱特征及其参数可用来估算叶片色素质量分数。图4表5参40     

舟山近海域悬浮泥沙浓度遥感反演研究

[目的]采用卫星遥感方法反演舟山海域悬浮泥沙的分布,并进一步探索适合的反演模型,为以后舟山海域悬浮泥沙遥感研究提供参考依据。[方法]利用实测数据、遥感数据和实验室分析的方法,对舟山海域不同水体进行光谱分析,建立水体遥感反射率与悬浮泥沙浓度之间3种不同的反演模型。[结果]遥感参数反演模型的反演效果最好;对数反演模型次之,对数模型下TM4波段的相关系数最大,TM3波段的相关系数最小;线性反演模型最差,线性模型下TM2波段的相关系数最大,TM3波段的相关系数最小。[结论]在舟山海域采用遥感参数模型可以获得较高的反演精度。     

Simple method for extracting the seasonal signals of photochemical reflectance index and normalized difference vegetation index measured using a spectral reflectance sensor

A spectral reflectance sensor(SRS) fixed on the near-surface ground was developed to support the continuous monitoring of vegetation indices such as the normalized difference vegetation index(NDVI) and photochemical reflectance index(PRI). NDVI is useful for indicating crop growth/phenology, whereas PRI was developed for observing physiological conditions. Thus, the seasonal change patterns of NDVI and PRI are two valuable pieces of information in a crop-monitoring system. However, capturing the seasonal patterns is considered challenging because the vegetation index values estimated by the reflection from vegetation are often governed by meteorological conditions, such as solar irradiance and precipitation. Further, unlike growth/phenology, the physiological condition has diurnal changes as well as seasonal characteristics. This study proposed a novel filtering method for extracting the seasonal signals of SRS-based NDVI and PRI in paddy rice, barley, and garlic. First, the measurement accuracy of SRSs was compared with handheld spectrometers, and the R~2 values between the two devices were 0.96 and 0.81 for NDVI and PRI, respectively. Second, the experimental study of threshold criteria with respect to meteorological variables(i.e., insolation, cloudiness, sunshine duration, and precipitation) was conducted, and sunshine duration was the most useful one for excluding distorted values of the vegetation indices. After data processing based on sunshine duration, the R2 values between the measured vegetation indices and the extracted seasonal signals of vegetation indices increased by approximately 0.002–0.004(NDVI) and 0.065–0.298(PRI) on the three crops, and the seasonal signals of vegetation indices became noticeably improved. This method will contribute to an agricultural monitoring system by identifying the seasonal changes in crop growth and physiological conditions.     

Pedotransfer functions to assess adsorbed phosphate using iron oxide content and magnetic susceptibility in an Oxisol

Adsorbed phosphate in soils can be chemically extracted; however, this process is both time‐consuming and not cost‐effective if large numbers of samples have to be analysed. Indirect assessment of adsorbed phosphate by pedotransfer functions (PTFs) can help optimize fertilizer strategies. This study aimed to evaluate the spatial variability of adsorbed phosphate (P_ads), iron oxides and magnetic susceptibility (MS) in oxisols and to calibrate PTFs to predict P_ads. A total of 308 soil samples were collected from Hapludox and Eutrudox soils formed from sandstone in Brazil. The contents of clay (196–607 g/kg), iron oxides (40–165 g/kg), MS (1.2–29 × 10^?6 m³/kg) and P_ads (327–842 mg/kg) were in the range of typical values for these highly weathered soils. This study showed that the attributes studied were spatially dependent. Geomorphic surfaces enabled understanding of spatial variability and helped to develop a more efficient sampling scheme to calibrate PTFs. Moreover, the adsorbed phosphate in these oxisols could be predicted by a PTF using iron oxides and MS as predictors. The MS attribute enabled the most accurate prediction (concordance coefficient = 0.95, root‐mean‐square error = 46 mg/kg and relative improvement in root‐mean‐square error = ?4.12) of spatial variability through PTF compared to other predictors.     

Estimation of litchi (Litchi chinensis Sonn.) leaf nitrogen content at different growth stages using canopy reflectance spectra

The estimation of crop nitrogen status in fresh vegetation leaf using field spectroscopy is challenging due to the weak responses on leaf/canopy reflectance and the overlapping with the absorption features of other compounds. Although the spectral indices were proposed in the literature to predict leaf nitrogen content (LNC), the performance of selected spectral indices to estimate the LNC is often inconsistent. Moreover, the models for nitrogen content estimation changed with the growth stage. The goal of this study was to evaluate the performance of published indices, ratio of data difference index (RDDI) and ratio of data index (RDI) developed by band iterative-optimization algorithm in LNC estimation. The correlation analysis, linear regression and cross validation were used to analyze the relationship between spectral data and LNC and construct the best performed estimation model. The study was conducted by the data of five growing seasons of litchi from the orchards in Guangdong Province of China. Results showed that the relationship between chlorophyll (Chl) related spectral indices and LNC varied with the growth stage. Even in flower bud morphological differentiation stage and autumn shoot maturation stage, there were not significant correlations between the proposed spectral indices and LNC. Besides it is difficult to estimate the LNC by the general model across the growth stages due to the integrated effects of cultivar, biochemical, canopy structure, etc. The band iterative-optimization algorithm can improve the sensitivity of spectral data to LNC to some extent. The optimal RDDI performed better than other indices for the synthetic dataset and the dataset in each growth stage. And the sensitive bands selected in the optimal indices at each growth stage are not consistent, which are not only related to the Chl absorption but also other biochemical components, such as starch, lignin, cellulose, protein, etc. In general, the LNC can be estimated by the optimized CR-based RDDI indices in autumn shoot maturation stage, flower spike stage, fruit maturation stage, and flowering stage with the R² > 0.50 and RMSE < 0.14. Although there were the significant relationship between RDIs and RDDIs in flower bud morphological differentiation stage, the highest R²s of the model developed by RDDIs and RDIs were less than 0.50 in cross validation. This study indicated that the applicability of canopy reflectance to estimate litchi LNC was closely related to the growth stage of litchi. Growth stage-specific models will be preferred for estimating litchi LNC estimation.     

Influence of Soil Particle Size on the Measurement of Sodium by Near-Infrared Reflectance Spectroscopy

This study evaluates the effect of soil particle size (SPS) on the measurement of exchangeable sodium (Na) (EXC-Na) by near-infrared reflectance (NIR) spectroscopy. Three hundred thirty-two (n = 332) top soil samples (0–10 cm) were taken from different locations across Uruguay, analyzed by EXC-Na using emission spectrometry, and scanned in reflectance using a NIR spectrophotometer (1100–2500 nm). Partial least squares (PLS) and principal component regression (PCR) models between reference chemical data and NIR data were developed using cross validation (leaving one out). The coefficient of determination in calibration (R²) and the root mean square of the standard error of cross validation (RMSECV) for EXC-Na concentration were 0.44 (RMSECV: 0.12 mg kg^–1) for soil with small particle size (SPS-0.053) and 0.77 (RMSECV: 0.09 mg kg^–1) for soils with particle sizes greater than 0.212 mm (SPS-0.212), using the NIR region after second derivative as mathematical transformation. The R² and RMSECV for EXC-Na concentration using PCR were 0.54 (RMSECV: 0.07 mg kg^–1) and 0.80 (RMSECV: 0.03 mg kg^–1) for SPS-0.053 and SPS-0.212 samples, respectively.     

干旱胁迫对3种冷季型草坪草光谱反射率及生理特征的影响

为探讨高光谱分析技术在草坪草水分监测上的应用,以草地早熟禾、高羊茅、多年生黑麦草为试验材料,测定了干旱胁迫下3种冷季型草坪草生理指标及光谱反射率。结果表明:随着干旱胁迫程度的加深,供试草坪草叶片相对含水量和叶绿素含量显著下降(P0.05),丙二醛含量、脯氨酸含量及敏感波段的(550和760 nm)的光谱反射率显著上升(P0.05),3种草坪草抗旱性能的强弱顺序为:高羊茅多年生黑麦草草地早熟禾。3种草坪草敏感波段光谱反射率(R_(550 nm),R_(760 nm))及高光谱参数(Rg,R0,GNDVI)与生理指标间呈显著或极显著相关,以R_(550 nm)与生理指标间的相关系数绝对值最大。同时R_(550 nm)构建了供试草坪草生理指标的估测模型,经检验,模型估测值与实测值相关性达显著或极显著水平。