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I-Corps: Image processing platform to identify photosynthetic pigment density to measure nitrogen content and manage fertilizer (Smart Sustainable Fertilizer Manager)

I-Corps: Image processing platform to identify photosynthetic pigment density to measure nitrogen content and manage fertilizer (Smart Sustainable Fertilizer Manager)
I-Corps:图像处理平台,用于识别光合色素密度,测量氮含量并管理肥料(智能可持续肥料管理器)
批准号:
2227256
负责人:
Amir Khoddamzadeh
金额:
$5.0万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2022
资助国家:
美国
项目状态:
已结题
起止时间:
2022-06-15 至 2024-07-31

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英文摘要
The broader impact/commercial potential of this I-Corps project is the development of a technology to determine the fertilizer needs of potted plants. Large-scale nursery production, a sizable component of the agriculture industry, involves the use of containers to grow plants. An acre of land in nursery production houses up to 300,000 containers, many of which receive excessive fertilizer application. Nitrogen (N) is a macronutrient that affects plant chlorophyll content, which may be used to define the growth status and leaf N content in plants. The proposed technology may enable nursery producers to determine the fertilizer needs of potted plants and help avoid overfertilization and nutrient runoff. In addition, the proposed technology may promote plant health and environmental sustainability as well as enable big data to be collected from fertilizer practices in large and small settings.This I-Corps project is based on the development of a smart, sustainable fertilizer manager platform that uses image processing and machine learning to measure leaf nitrogen content. The proposed technology allows the use of any camera sensor to image and process leaf color to identify the photosynthetic pigment density in a non-destructive way and compare this measurement with the existing cloud data for analysis. Current fertilizer management is typically based on published fertilizer recommendations, which vary among plant species. The proposed design uses a single image taken by a smartphone to give a recommendation on fertilizer needs for potted plants (flowers and ornamentals). The image is scanned and analyzed, and the user receives a message indicating whether a plant is deficient in nutrients. Core machine learning is being used to train a model based on the “green value” provided by completed and ongoing research projects. The technology's Application Programming Interface (API) will be embedded in the application.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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国内基金
海外基金
基于CE-3及IMAGE卫星地球等离子体层EUV探测数据的反演研究
Raw-Image微小物体高精度位姿测量法
  • 批准号:
    61105029
  • 项目类别:
    青年科学基金项目
  • 资助金额:
    22.0万元
  • 批准年份:
    2011
  • 负责人:
    宋薇
  • 依托单位: