{"title":"Development of low-cost leaf spectroscopy based on featured wavelength extraction by fix-bandwidth Gaussian mixture model","authors":"Xingming Long, Ruoshuang Zhang, Jing Zhou","doi":"10.1049/smt2.12139","DOIUrl":null,"url":null,"abstract":"<p>Light spectrum analysis of leaves plays an essential role in measuring the contents of carbohydrates and other important compound like proteins. And it is also useful in evaluating the status of vegetation by remote sensing. Here, an approximation method considering the optical response characteristics of multispectral silicon (Si) sensor for the reflection or absorption spectra of leaves is proposed. The light spectrum is analysed by Gaussian mixture models (GMM) with fixed bandwidth firstly, and then the optimal model parameters are derived and validated to balance the complexity of Si sensor and the 2-norm deviation of spectra, and next a low-cost framework for the leaf spectroscopy with wireless node is illustrated according to the specific centre-wavelengths and bandwidths of the GMM, and finally, an experimental prototype with 18-channel Si sensor node and the developed mobile APP is demonstrated. The simplified strategy and its realization for leaf spectroscopy cast light on large-scale applications in future agriculture.</p>","PeriodicalId":54999,"journal":{"name":"Iet Science Measurement & Technology","volume":null,"pages":null},"PeriodicalIF":1.4000,"publicationDate":"2023-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/smt2.12139","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Iet Science Measurement & Technology","FirstCategoryId":"5","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1049/smt2.12139","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0
Abstract
Light spectrum analysis of leaves plays an essential role in measuring the contents of carbohydrates and other important compound like proteins. And it is also useful in evaluating the status of vegetation by remote sensing. Here, an approximation method considering the optical response characteristics of multispectral silicon (Si) sensor for the reflection or absorption spectra of leaves is proposed. The light spectrum is analysed by Gaussian mixture models (GMM) with fixed bandwidth firstly, and then the optimal model parameters are derived and validated to balance the complexity of Si sensor and the 2-norm deviation of spectra, and next a low-cost framework for the leaf spectroscopy with wireless node is illustrated according to the specific centre-wavelengths and bandwidths of the GMM, and finally, an experimental prototype with 18-channel Si sensor node and the developed mobile APP is demonstrated. The simplified strategy and its realization for leaf spectroscopy cast light on large-scale applications in future agriculture.
期刊介绍:
IET Science, Measurement & Technology publishes papers in science, engineering and technology underpinning electronic and electrical engineering, nanotechnology and medical instrumentation.The emphasis of the journal is on theory, simulation methodologies and measurement techniques.
The major themes of the journal are:
- electromagnetism including electromagnetic theory, computational electromagnetics and EMC
- properties and applications of dielectric, magnetic, magneto-optic, piezoelectric materials down to the nanometre scale
- measurement and instrumentation including sensors, actuators, medical instrumentation, fundamentals of measurement including measurement standards, uncertainty, dissemination and calibration
Applications are welcome for illustrative purposes but the novelty and originality should focus on the proposed new methods.