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本研究突出了中医理论的指导,将舌诊客观化与中医理论紧密结合,采取“病—证—舌”一体化的研究思路,将舌诊的客观量化与中医证候结合,探求高血压病痰湿壅盛、肝火亢盛证型舌象的差异在光谱上的定量反应,从而阐明“证”的差异是有其客观的基础,并且在一定程度上是可以量化的,为中医证候的客观化研究提供证据。

土壤养分如总氮、有机质、速效钾和速效磷等是农作物生长的主要成分,这些土壤养分参数的检测一直沿用常规化学检测方法,对检测人员要求高,且需要昂贵的检测设备,存在检测成本高、效率低,不能大规模同时检测等问题。近红外光谱和高光谱成像分析技术具有成本低、快速和环保等优点,近年来在土壤养分测定方面提到了越来越广泛的应用。本文主要创新性成果有。

近年来,我国水果产业受到的外来挑战越来越大,提高水果果品的品质成了当前的燃眉之急,这就对我国水果的分级处理能力提出了要求。但是我国目前的分级技术等产后处理技术十分落后,还有不少水果的分级处理工作仍需人工完成。传统方法对水果内部品质检测都需要对样本作破坏性处理,费时费力。因此,亟需一种快速、无损、环保的检测方法对水果的内部品质进行测定。本文通过可见-近红外光谱技术与多光谱图像技术对葡萄可溶性固体含量(SSC)进行了无损检测建模和仪器化研究,主要研究内容如下。

现代农业的发展,得益于化肥与农药的使用。施用化肥能够改善土壤肥力,提高农作物单位产量。然而,人们为了追求高产往往对作物大量盲目施肥。化肥施用量的增加和利用率的下降,不仅在经济上造成巨大损失,还会引起严重的环境污染,致使地表水富营养化,地下水和蔬菜中营养元素含量超标等问题。因此,大面积快速获取土壤养分含量信息,根据土壤养分的丰缺合理适量施肥,对于我国农业可持续发展具有重要意义。应用传统化学分析方法测量土壤养分,分析过程复杂、周期长、成本高、实时性差,很难大规模推广使用。农业生产上迫切需要一种快速,现场原位,连续且无污染的土壤养分检测方法。

利用可见近红外(VIS/NIR)光谱测定技术快速无损地对土壤进行定量分析,是一种被广泛应用的行之有效的方法。大量研究表明土壤有机碳、水分、全氮等属性与光谱之间存在着较强的线性相关性。而野外原位测量受各种环境因素的影响,在一定程度上削弱了这种线性相关性。因此通常在实验室内对经过干燥、磨样处理的土壤进行光谱测量,以消除水分、质地和土壤类型等因素的影响。对于不同粒径导致预测模型精度的影响,目前的研究成果只给出了定性的结果。但是为何会导致差异以及对差异原因的定量解释,还未见诸于相关研究文献。

Green leaf area index (LAI) is an important variable for climate modeling, estimates of primary production, agricultural yield forecasting, and many other diverse applications. Remotely sensed data provide considerable potential for estimating LAI at local, regional, and global scales. The goal of this study was to retrieve green LAI from MODIS 250-m vegetation index (VI) data for irrigated and rainfed maize and soybeans. The performance of both MODIS-derived NDVI and Wide Dynamic Range Vegetation Index (WDRVI) were evaluated across three growing seasons (2002 through 2004) over a wide range of LAI and also compared to the performance of NDVI and WDRVI derived from reflectance data collected at closerange across the same field locations. The NDVI vs. LAI relationship showed asymptotic behavior with a sharp decrease in the sensitivity of the NDVI to LAI exceeding 2 m2/m2 for both crops. WDRVI vs. LAI relation was linear across the entire range of LAI variation with determination coefficients above 0.93. Importantly, the coefficients of the close-range WDRVI vs. LAI equation and the MODISretrieved WDRVI vs. LAI equation were very close. The WDRVI was found to be capable of accurately estimating LAI across a much greater LAI range than the NDVI and can be used for assessing even slight variations in LAI, which are indicative of the early stages of plant stress. These results demonstrate the new possibilities for analyzing the spatio-temporal variation of the LAI of crops using multi-temporal MODIS 250-m imagery.

The Photochemical Reflectance Index (PRI) has been proposed as a tool for the estimation of leaf and canopy light-use efficiency and photosynthesis from remote-sensing data. The application of the index is based on more than fifteen years of spectroscopic studies at the leaf level, which support it with a sound physiological basis. In the present study, the correlation between PRI and instantaneous light-use efficiency was estimated across a range of vegetation types in the San Rossore Regional Park, a CHRIS-Proba core site. The relationship was also tested over an entire season for a pine forest in the Park where carbon fluxes have been monitored by eddy-covariance over the last five years. Seasonal changes in photosynthetic potential were also monitored at the site, in order to test the correlation with PRI reported in the literature. In September 2004, estimates of canopy PRI from CHRIS images were compared with leaf-level measurements from 13 plots corresponding to different vegetation types. The results were used to extrapolate leaf-level information to the entire scene.

Methods for chlorosis detection and physiological condition monitoring in Vitis vinifera L, through accurate chlorophyll a and b content (Cab) estimation at lead and canopy levels are presented in this manuscript. A total of 24 vineyards were identified for field and airborne data collection with the Compact Airborne Spectrographic Imager (CASI), the Reflective Optics System Imaging Spectrometer (ROSIS) and the Digital Airborne Imaging Spectrometer (DAIS-7915) hyperspectral sensors in 2002 and 2003 in northem Spain, comprising 103 study areas of 10 * 10 m in size, with a total of 1467 leaves collected for determination of pigment concentration. A subsample of 605 leaves was used for measuring the optical properties of reflectance and tranmittance with a Li-Cor 1800-12 Integrating Sphere coupled by a 200um diameter single mode fiber to an Ocean Optics model USB2000 spectrometer. Several narrow-band vegetation indices were calculated from lead reflectance spectra, and the PROSPECT leaf optical model was used for inversion using the extensive database od lead optical properties. Results showed that the best indicators for chlorophyll content estimation in V. vinifera L. leaves were narrow-band hyperspectral indices calculated in the 700-750 nm spectral region (r2 ranging between 0.8 and 0.9), with poor performance of traditional indices such as the Normalized Difference Vegetation Index (NDVI). Results for other biochemicals indicated that the Structure Insensitive Pigment Index (SIPI) and the Photochemical Reflectance Index (PRI) were more sensitice to carotenoids C x+c and chlorophyll-carotenoid ratios Cab/Cx+c than to chlorophyll content Cab. Chlorophyll a and b estimation by inversion of the PROSPECT leaf model on V. vinifera L. spectra was successful, yielding a determination coefficient of r2=0.95, with an RMSE=5.3ug/cm2. The validity of leaf-level indices for chlorophyll content estimation at the canopy level in V. vinifera L. was studied using the scaling-up approach that links PROSPECT and rowMCRM canpy reflectance simulation to account for the effects of vineyard structure, vine dimensions, row orientation and soil and shadow effects on the canopy reflectance. The index calculated as a combination of the Transformed Chlorophyll Absorption in Reflectance Index (TCARI), and the Optimized Soil-Adjusted Vegetation Index (OSAVI) in the form RCARI/OSAVI was the most consistent index for estimating Cab on aggregated and pure vine pixels extracted from 1 m CASI and ROSIS hyperspectral imagery. Predictive relationships were developed with PROSPECT-rowMCRM model between Cab and TCARI/OSAVI as function of LAI, using field-measured vine dimensions and image-extracted siul background, row-orientation and viewing geometry values. Prediction relationships for Cab content with TCARI/OSAVI were successfuly applied to the 103 study sites imaged on 24 fields by ROSIS and CASI airborne sensors, yielding r2=0.67 and RMSE-11.5ug/cm2.

In this study, we investigated the potential of the photochemical resistance index (PRI) to track photosynthetic activity under water stress conditions by measuring PRI, leaf fluorescence, the xanthophyll cycle and photosynthetic activity in different forest tree species subjected to progressive drought. The PRI declined with pre-dawn water potential and a significant relationship between PRI and the xanthophyll de-epoxidation state (DEPS) was observed, although with large interspecific variability in the sensitivity of PRI to changes in DEPS. For single tree species, a strong relationship was observed on either PRI light saturated photosynthesis or PRI maximum photochemical efficiency of PSII (DF/Fm 0); a larger variability in both relationships was apparent when data from different species were pooled together. However, an improved correlation was shown only in the former relationship by plotting the DPRI (dawn PRI minus the midday PRI values). Thus, we conclude that PRI is able to provide a good estimate of maximum CO2 assimilation at saturating light and DF/Fm 0 for single tree species, despite the severe drought conditions applied. PRI should be applied more cautiously when dealing with multispecific forests because of confounding factors such as the strong interspecific differences in the initial value of PRI and in the sensitivity of PRI to changes in DEPS in response to drought.

The fraction of absorbed photosynthetically active radiation, fAPAR, is an important biophysical characteristic in models of gas exchange between the terrestrial boundary layer and the atmosphere, as well as in the analysis of vegetation productivity. Synoptic estimation of fAPAR has been performed by using NDVI as a linear proxy of fAPAR, despite the saturation of NDVI at fAPAR beyond 0.7. This paper analyzes the NDVI/fAPAR relationship in row crops (i.e. maize and soybean), and evaluates alternative vegetation indices to overcome the loss of sensitivity of NDVI at moderate-to-high vegetation biomass. Red-edge NDVI, which uses NIR and a band around 700 nm and the recently proposed Wide Dynamic Range Vegetation Index, which uses red and NIR bands only, were found to be sensitive to fAPAR variation along its entire range and exhibited significant increase in sensitivity to fAPAR.

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