Intelligent image analysis for retrieval of leaf chlorophyll content of rice from digital images of smartphone under natural light
出版年份 2019 全文链接
标题
Intelligent image analysis for retrieval of leaf chlorophyll content of rice from digital images of smartphone under natural light
作者
关键词
-
出版物
PHOTOSYNTHETICA
Volume -, Issue -, Pages -
出版商
Institute of Experimental Botany
发表日期
2019-02-13
DOI
10.32615/ps.2019.046
参考文献
相关参考文献
注意:仅列出部分参考文献,下载原文获取全部文献信息。- Assessment of spinach seedling health status and chlorophyll content by multivariate data analysis and multiple linear regression of leaf image features
- (2018) Avinash Agarwal et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
- Relationships between reflectance and absorbance chlorophyll indices with RGB (Red, Green, Blue) image components in seedlings of tropical tree species at nursery stage
- (2018) Elizabeth Santos do Amaral et al. NEW FORESTS
- Use of a chlorophyll meter to assess nitrogen nutrition index during the growth cycle in winter wheat
- (2017) Clémence Ravier et al. FIELD CROPS RESEARCH
- SmartFluo: A Method and Affordable Adapter to Measure Chlorophyll a Fluorescence with Smartphones
- (2017) Anna Friedrichs et al. SENSORS
- Indicators for diagnosing nitrogen status of rice based on chlorophyll meter readings
- (2016) Zhaofeng Yuan et al. FIELD CROPS RESEARCH
- Feasibility of using smart phones to estimate chlorophyll content in corn plants
- (2016) F. Vesali et al. PHOTOSYNTHETICA
- A novel method for the estimation of soybean chlorophyll content using a smartphone and image analysis
- (2016) J. P. G. Rigon et al. PHOTOSYNTHETICA
- Development of an android app to estimate chlorophyll content of corn leaves based on contact imaging
- (2015) Farshad Vesali et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
- Use of the atLEAF+ chlorophyll meter for a nondestructive estimate of chlorophyll content
- (2015) E. V. Novichonok et al. PHOTOSYNTHETICA
- Colorimetric analyzer based on mobile phone camera for determination of available phosphorus in soil
- (2015) Nuntaporn Moonrungsee et al. TALANTA
- Applications of Smartphone-Based Sensors in Agriculture: A Systematic Review of Research
- (2015) Suporn Pongnumkul et al. Journal of Sensors
- Non-destructive evaluation of chlorophyll content in quinoa and amaranth leaves by simple and multiple regression analysis of RGB image components
- (2014) M. Riccardi et al. PHOTOSYNTHESIS RESEARCH
- Estimating rice chlorophyll content and leaf nitrogen concentration with a digital still color camera under natural light
- (2014) Yuan Wang et al. Plant Methods
- Citrus yield estimation based on images processed by an Android mobile phone
- (2013) Aiping Gong et al. BIOSYSTEMS ENGINEERING
- Estimation of leaf chlorophyll content of rice using image color analysis
- (2013) Hao Hu et al. CANADIAN JOURNAL OF REMOTE SENSING
- Using the mobile phone as Munsell soil-colour sensor: An experiment under controlled illumination conditions
- (2013) Luis Gómez-Robledo et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
- Development of an app for estimating leaf area index using a smartphone. Trueness and precision determination and comparison with other indirect methods
- (2013) R. Confalonieri et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
- Estimation of rice growth and nitrogen nutrition status using color digital camera image analysis
- (2013) Kyu-Jong Lee et al. EUROPEAN JOURNAL OF AGRONOMY
- Reflectance estimation of canopy nitrogen content in winter wheat using optimised hyperspectral spectral indices and partial least squares regression
- (2013) Fei Li et al. EUROPEAN JOURNAL OF AGRONOMY
- Estimating nitrogen status of rice using the image segmentation of G-R thresholding method
- (2013) Yuan Wang et al. FIELD CROPS RESEARCH
- A Review of Methods for Sensing the Nitrogen Status in Plants: Advantages, Disadvantages and Recent Advances
- (2013) Rafael Muñoz-Huerta et al. SENSORS
- Leaf nitrogen concentration and chlorophyll meter readings as predictors of tall fescue nitrogen nutrition status
- (2012) Pedro M. Errecart et al. FIELD CROPS RESEARCH
- Development of a digital image analysis method for real-time estimation of chlorophyll content in micropropagated potato plants
- (2012) S. Dutta Gupta et al. Plant Biotechnology Reports
- Using a chlorophyll meter to estimate tea leaf chlorophyll and nitrogen contents
- (2012) Z.A Liu et al. Journal of Soil Science and Plant Nutrition
- The Assessment of Leaf Nitrogen in Corn from Digital Images
- (2011) Robert L. Rorie et al. CROP SCIENCE
- Chlorophyll meter-based nitrogen management of rice grown under alternate wetting and drying irrigation
- (2011) R.J. Cabangon et al. FIELD CROPS RESEARCH
- Neural-network model for estimating leaf chlorophyll concentration in rice under stress from heavy metals using four spectral indices
- (2010) Meiling Liu et al. BIOSYSTEMS ENGINEERING
- Digital image analysis and chlorophyll metering for phenotyping the effects of nodulation in soybean
- (2010) J. Vollmann et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
- Use of a SPAD-502 meter to measure leaf chlorophyll concentration in Arabidopsis thaliana
- (2010) Qihua Ling et al. PHOTOSYNTHESIS RESEARCH
- Investigation of SPAD meter-based indices for estimating rice nitrogen status
- (2009) Fen Fang Lin et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
- Estimation of the chlorophyll content of micropropagated potato plants using RGB based image analysis
- (2009) Satya Prakash Yadav et al. PLANT CELL TISSUE AND ORGAN CULTURE
- New method to assess barley nitrogen nutrition status based on image colour analysis
- (2008) Miguel Pagola et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
- What are artificial neural networks?
- (2008) Anders Krogh NATURE BIOTECHNOLOGY
- An evaluation of non-destructive methods to estimate total chlorophyll content
- (2008) D. Cassol et al. PHOTOSYNTHETICA
Find Funding. Review Successful Grants.
Explore over 25,000 new funding opportunities and over 6,000,000 successful grants.
ExploreAsk a Question. Answer a Question.
Quickly pose questions to the entire community. Debate answers and get clarity on the most important issues facing researchers.
Get Started