6) PlantScreen NIR成像采用多濾波器技術，不僅測量水分吸收峰值1450nm，還可進行reference測量如植物對1000nm反射，從而得到高反差水分分布信息。而其它產品近紅外成像只有一個濾波器得到1400nm的反射影像，沒有reference測量（對照參考測量），得到的數據很大程度上缺乏量化、信噪比非常低
7) PSI不僅是FluorCam葉綠素熒光成像技術的研發生產者，應用于PlantScreen的傳感器（包括高光譜、近紅外、紅外熱成像等）、智能LED光控技術、FytoScope生長室等都由自己生產，從而保障了產品技術的穩定性、可靠性、兼容性及性能指標和價格的實在性，有效避免了維護費用高、兼容性差、容易出問題、性價比低等缺陷
8) PlantScreen所測量的所有數據都是透明的、可以追溯的，而不像其它同類產品只是一個“黑箱”，缺乏原數據的透明性等
9) PSI的表型大數據軟件功能全面先進，具備強大的分析能力、可視化、數據庫等，如對葉片跟蹤監測功能（leaf tracking），可以持續跟蹤監測葉片的生長、變化等等，這是其它同類產品所不具備的
10) PlantScreen不僅可以通過高分辨率RGB鏡頭 或激光掃描構建3D模型，而且還可以通過投射技術，將與其它傳感器所得數據如葉綠素熒光、紅外熱成像溫度數據、近紅外數據、高光譜數據等投射在3D模型上一起進行對比分析等，其它同類產品完全不具備，甚至不能創建真正的3D模型
11) PSI公司建有植物表型分析研究中心，中心有首席科學家帶隊的技術團隊，并發表多篇學術論文，與中國易科泰生態技術公司有著長達10年的合作，設有技術支持中心和EcoLab實驗室，售后服務和技術支持有著充分的保障
上圖為RGB二維形態成像分析；下圖為不同表型成像分析技術（2D RGB成像、FluorCam葉綠素熒光成像、高光譜成像）同步分析，結果表明，Rfd最為敏感，實驗一小時后就可以檢測到實驗組（干旱脅迫）與對照組的明顯差別（左圖為RGB彩色成像分析（葉面積），中圖為FluorCam葉綠素熒光成像分析（熒光衰減指數），右圖為高光譜成像分析（植被歸一化指數））
根窗技術高通量根系表型分析
近期部分參考文獻：
1) Celine Rousseau etc. High throughput quantitative phenotyping of plant resistance using chlorophyll fluorescence image analysis. Plant Methods 2013
2) Anna Rusaczonek etc. Role of phytochromes A and B in the regulation of cell death and acclamatory responses to UV stress in Arabidopsis thaliana. Journal of Experimental Botany 2015
3) Celine Rousseau etc. Phenoplant: a web resource for the exploration of large chlorophyll fluorescence image datasets. Plant Methods 2015
4) Fildas Bourdais etc. Large-scale Phenomics identifies primary and fine-tuning roles for CRKs in responses related to oxidative stress. PLOS Genetics 2015
5) Katarzyna Mozdzen etc. Effect of drought stress induced by mannitol on physiological parameters of Maize(Zea mays L.) seedlings and plants. Journal of Microbiology, Biotechnology and Food Sciences 2015
6) Jan F Humplik etc. Automated integrative high-throughput phenotyping of plant shoots: a case study of the cold-tolerance of pea. Plant Methods 2015
7) Jan F Humplik etc. Automated phenotyping of plant shoots using imaging methods for analysis of plant stress responses – a review. Plant Methods 2015
8) Maria L. Perez-bueno etc. Multicolor fluorescence imaging as a candidate for disease detection in plant phenotyping. Frontiers in Plant Science 2016.
9) Mariam Awlia etc. High-throughput non-destructive phenotyping of traits that contribute to salinity tolerance in Arabidopsis thaliana. Frontiers in Plant Science 2016
10) Tepsuda Rungrat etc. Using phenomic analysis of photosynthetic function for abiotic stress response of gene discovery. BioOne 2016
11) Matthew Jacobs etc. Photonic multilayer structure of Begonia chloroplasts enhances photosynthetic efficiency. Nature Plants 2016
12) Carmen M. Ortiz-Bustos etc. Fluorescence imaging in the red and far-red region during growth of Sunflower Plantlets diagnosis of the early infection by the parasite Orobanche Cumana. Frontiers in Plant Science 2016
13) Henning Tschiersch etc. Establishment of integrated protocols for automated high throughput kinetic chlorophyll fluorescence analyses. Plant Methods 2017.
14) Joao Serodio etc. A chlorophyll fluorescence-based method for the integrated characterization of the photophysiological response to light stress. Journal of Experimental Botany 2017
15) Monica Pineda etc. Use of multicolour fluorescence imaging for diagnosis of bacterial and fungal infection on zucchini by implementing machine learning. Functional Plant Biology 2017
