The growing situation of crops is reflected by their physiological characteristics, and the physiological characteristics determine the changes of light absorption, transmission, and reflection of crops, so that the growth status of crops can be monitored based on the differences in spectra. Plant water, mineral content, chlorophyll concentration and leaf area index, which reflect the main physiological and biochemical parameters of crop growth, are different at different stages of crop growth. The reflectance characteristics of green plants on the spectrum, the visible light band is affected by various pigments such as chlorophyll, and there is a strong absorption band; the near-infrared band is affected by the leaf water status, and has a strong reflection peak. Remote sensing can be used to estimate crop coverage and leaf area index, and vegetation index is linearly related to the crop distribution density. The size of the crop index is determined by crop coverage and leaf area index. Hyperspectral remote sensing can use crop index for crops. Growth monitoring analysis. Jin Xiuliang et al. established a spectral estimation model of cotton biomass and leaf area index. All the selected vegetation indices and cotton leaf area index and biomass correlation reached extremely significant levels. Using the spectral characteristic parameters, the growing trend of the cotton growth period was realized. Effective monitoring. Li Weiguo and others used satellite imagery information combined with ground test data to analyze the relationship between the three population quality indicators and vegetation indices of wheat leaf area index, biomass, and plant nitrogen content at jointing stage, and based on the normalized vegetation index and ratio. The vegetation quality index monitoring model for wheat population quality shows that the model has good monitoring and versatility. Therefore, a leaf area analyzer was developed. Nitrogen fertilizer plays an important role in increasing the total biological and economic output of crops and improving the nutritional value of agricultural products. Chlorophyll is a necessary substance for photosynthesis of plants. Enzymes are the catalysts for the transformation of various substances in plants. Nitrogen is a component of chlorophyll and many enzymes. When nitrogen stress, crop growth will be affected, so the diagnosis of crop nitrogen nutrition Non-destructive testing technology is a key research area in hyperspectral remote sensing applications. Zhu Xicun et al. used the FieldSpec 3 spectrometer developed by American ASD Corporation to determine the hyperspectral reflectivity of 120 apple flower samples at flowering stage and assayed their nitrogen content. The characteristics of the original spectrum and first derivative spectra of apple flowers were analyzed. Based on the above, a nitrogen content prediction model was established to provide theoretical basis for apple's real-time nutrition diagnosis and information management, and a chlorophyll meter was developed. Wang Zhi et al. measured the spectral reflectance and total nitrogen content of peach leaves, and analyzed the correlation of nitrogen content, leaf spectral reflectance, and various variant data, in order to further utilize hyperspectral remote sensing to detect the leaves. Chemical components provide a reference. In addition to the monitoring of crop growth, hyperspectral remote sensing also has important applications in land resource surveys. In wetland research, hyperspectral remote sensing technology is used for fine classification of vegetation communities, extraction of wetland water information, and division of lake boundaries. On the aspect of geological prospecting and mine waste monitoring, on the one hand, different minerals and lithology can be distinguished according to the different electromagnetic reflection spectrum characteristics of different minerals to guide regional ore prospecting; on the other hand, hyperspectral remote sensing images can be fast. Accurately display changes in geological environment, such as mudslides, collapses, and landslides, and provide scientific evidence for the comprehensive investigation of mine resources and environmental monitoring and evaluation.
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Hyperspectral remote sensing techniques monitor the chlorophyll content of the vegetation from the blade level to the canopy level, and the spectral vegetation index needs to be revised. Establishing the relationship between the reflectance spectrum and the chlorophyll content will contribute to the development of the portable spectrometer and the improvement of its performance, and provide a basis for the satellite remote sensing to monitor the change of the chlorophyll content of the vegetation. Li Huan, through laboratory measurements and field observation experiments, measured canopy reflectance spectra of citrus during the phenophases of long-term sprouting, flowering and fruit setting, fruit ripening and flower bud differentiation, and other phenophases using the hand-held field object spectrometer. The spectral reflectance, differential spectrum and chlorophyll content were correlated. Zhang Jinheng et al. compared the absorption, transmission and reflection spectrum curves of rice leaves and the first-order derivative spectral curves. Using regression analysis, it was found that the actual spectral band position of the spectral transmittance linear model for estimating chlorophyll a and chlorophyll b content was found.
The rigidity and toughness of the frame structure are optimized and strengthened, and the weft insertion and beating-up are more stable, offering excellent high-speed performance.
Easy to operate:
This weaving machine fully considers ergonomics, strives to operate comfortably and conveniently, reduces the warp position line, and improves the comfort of the operator. Through the man-machine dialogue interface of the high-definition color touch screen, all settings are basically simplified and excellent operation is achieved.
Computer control system:
Equipped with a human-machine interface keyboard, which can display the operating status of the loom, the cause of failure, the weaving process parameters and the setting conditions of the loom on the display screen. Various data can be input conveniently through the function keys, and various set parameters can be stored for a long time through the memory card or input into the loom at any time.