| In this thesis, based on field experiment and potted trails, The possibility and accuracy of using digital image analysis method for plant growth monitoring and N nutrition status diagnosis was studied, The standard method of digital image acquisition and file format was established as well. The relation between the spectrum parameters of tomato plant canopy and biologic parameters and N nutrition status of plant was analyzed, the characteristics parameters, which can express the canopy color of processing tomato under varied N-status, are abstracted and screened, and a N diagnostic model was built-up. Some most widely used methods for assessing plant nitrogen status (SPAD-502, Hyperspectral Meter) are adopted in the research for proposal of checking the accurance of different methods. Conclusions are as follows:1. While taken digital image of processing tomato canopy in the field, for the sake of quality and accuracy of the analysis, it is best to capture picture at noon in the cloudy or sunny day before irrigated, and to choose a pixel resolution of 2048×1536.2. The trend of dynamic change of leaf area index, biomass and characteristic spectrum parameters PGCV (Percent ground cover of vegetation) was concurrent, Empirical statistical showed that a significant linear and curvilinear correlation between the PGCV and processing tomato biological parameters, The correlative coefficient was higher than 0.9. So PGCV can reliably evaluate the quantity of growth, and the biomass and the leaf area index (LAI) of processing tomato plant through the whole growth seasons.3. Chlorophyll meter SPAD-502 could be used to survey the chlorophyll relatively concentration of leaf, SPAD value and leaves' chlorophyll concentration and leaves' nitrogen concentration was used to a regression analysis, Empirical statistical showed that a significant liner relation between both the parameters. The correlative coefficient was higher than 0.7. Furthermore, most of correlative coefficient between SPAD values of different locative leaves and nitrogen contents was the reciprocal third leaves. Moreover, the results show significant relationships between the DGCI (Dark Green Color Index) and the color characteristic parameters and SPAD values. Therefore, we can use the image processing technique to get the spectrum parameters and evaluate the chlorophyll concentration and N concentration of the processing tomato.4. It was found that there have a stronger reflected peak at the 550nm, and results showed significant difference at this band. It showed a well correlation between the NDVI and N nutrition index, and the correlative coefficient was higher than 0.7 between NDVI, PGCV and DGCI, and a significant correlation between the NDVI and color feature parameters was detected as well, therefore, the image processing technique can used to diagnose the nitrogen concentration of processing tomato.5. Images of processing tomato canopy were analyzed with the image processing technique and the characteristic spectrum parameters were extracted and constructed. Under different N supply in field, it has a better significant correlation between characteristic spectral parameters and PGCV and nitrogen nutrition index in different growth stage. The correlative coefficient was higher than 0.9 between N accumulation and PGCV, results also showed signification relationships between a series of spectrum parameters and N nutrition index. According to the principle of the best relativity, the parameters were filtered and evaluate model was founded, Validation test showed that the diagnosis result is highly reliable. A stepwise regression method was used for screening color feature parameters that had the highest determination index with plant N content and other biological parameters, models for evaluating tomato chllrophyll, and nitrogen content were founded by this method.
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