Publications by authors named "Liang-Yun Liu"

Sirtuins (SIRTs) are a class of lysine deacylases that regulate cellular metabolism and energy homeostasis. Although sirtuins have been proposed to function in nutrient sensing and signaling, the underlying mechanism remains elusive. SIRT7, a histone H3K18-specific deacetylase, epigenetically controls mitochondria biogenesis, ribosomal biosynthesis, and DNA repair.

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Flux tower method can effectively monitor the vegetation seasonal and phenological variation processes. At present, the differences in the detection and quantitative evaluation of various phenology extraction methods were not well validated and quantified. Based on the gross primary productivity (GPP) and net ecosystem productivity (NEP) data of temperate forests from 9 forest FLUXNET sites in North America, and by using the start dates (SOS) and end dates (EOS) of the temperate forest growth seasons extracted by different phenology threshold extraction methods, in combining with the forest ecosystem carbon source/sink functions, this paper analyzed the effects of different threshold standards on the extraction results of the vegetations phenology.

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The present study focused on variation of vegetation types and canopy spectra along the altitudinal gradients in south-facing slope of Dangxiong valley in Tibet. Spectral extraction methods including red edge analysis and vegetation indices were used for vegetation spectral characteristics analysis. Through the hierarchical clustering analysis based on the vegetation spectral features, the feasibility of remote sensing classification of vegetation types along the elevation gradients in the experimental area was evaluated.

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By using the Landsat images in 1979, 1988, 1999, 2005, and 2009, and the linear unmixed model at pixel scale, this paper analyzed the spatiotemporal variation of vegetation coverage in Beijing mountainous area. After detecting the areas of vegetation degradation or restoration, the impacts of elevation, slope, and soil type on vegetation restoration were studied. From 1979 to 1988, the vegetation coverage in the study area had no obvious change, but in the following 12 years, the vegetation coverage was seriously destroyed due to the fast development of social economy.

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Precision agriculture technology is defined as an information-and technology-based agriculture management system to identify, analyze and manage crop spatial and temporal variation within fields for optimum profitability, sustainability and protection of the environment. In the present study, push-broom hyperspectral image sensor (PHI) image was used to investigate the spatial variance of winter wheat growth. The variable-rate fertilization contrast experiment was carried out on the National Experimental Station for Precision Agriculture of China during 2001-2002.

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Chinese-Brazil Earth Resources Satellite No. 2 (CBERS-02) has good spatial resolution and abundant spectral information, and a strong ability in detecting vegetation. Based on five CBERS-02 images in winter wheat growth season, the spectral distance between winter wheat and other ground targets was calculated, and then, winter wheat was classified from each individual image or their combinations by using supervised classification.

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Improving the efficiency of fertilization is an effective method of enhancing income for farmers, but it depends on measuring the soil nutrients accurately and rapidly. Near infrared reflectance spectroscopy (NIRS) is a fast method to detect the soil nutrients. In order to evaluate the feasibility of using NIRS to determine the soil N and P contents, the soil samples were collected from different LULC (land use and land cover) types in Daxing district, Beijing, and their biochemical parameters were determined by traditional chemical method.

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Investigations have been made on identification of erective and horizontal varieties by bidirectional canopy reflected spectrum and semi-empirical bidirectional reflectance distribution function (BRDF) models. The qualitative effect of leaf area index (LAI) and average leaf angle (ALA) on crop canopy reflected spectrum was studied. The structure parameter sensitive index (SPEI) based on the weight for the volumetric kernel (fvol), the weight for the geometric kernel (fgeo), and the weight for constant corresponding to isotropic reflectance (fiso), was defined in the present study for crop geometry identification.

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With the widespread application of remote sensing (RS) in agriculture, monitoring and prediction of crop nutrition condition attracts attention of many scientists. Foliar nitrogen content (N) is one of the most important nutrients for plant growth, and vertical leaf N gradient is an important indicator of crop nutrition situation. Investigations have been made on N vertical distribution to describe the growth status of winter wheat.

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