Investigation of Leaf Diseases and Estimation of Chlorophyll Concentration in Seven Barley Varieties Using Fluorescence and Hyperspectral Indices

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*Title:*	Main Title: Investigation of Leaf Diseases and Estimation of Chlorophyll Concentration in Seven Barley Varieties Using Fluorescence and Hyperspectral Indices
*Description:*	Abstract: Leaf diseases, such as powdery mildew and leaf rust, frequently infect barley plants and severely affect the economic value of malting barley. Early detection of barley diseases would facilitate the timely application of fungicides. In a field experiment, we investigated the performance of fluorescence and reflectance indices on (1) detecting barley disease risks when no fungicide is applied and (2) estimating leaf chlorophyll concentration (LCC). Leaf fluorescence and canopy reflectance were weekly measured by a portable fluorescence sensor and spectroradiometer, respectively. Results showed that vegetation indices recorded at canopy level performed well for the early detection of slightly-diseased plants. The combined reflectance index, MCARI/TCARI, yielded the best discrimination between healthy and diseased plants across seven barley varieties. The blue to far-red fluorescence ratio (BFRR_UV) and OSAVI were the best fluorescence and reflectance indices for estimating LCC, respectively, yielding R2 of 0.72 and 0.79. Partial least squares (PLS) and support vector machines (SVM) regression models further improved the use of fluorescence signals for the estimation of LCC, yielding R2 of 0.81 and 0.84, respectively. Our results demonstrate that non-destructive spectral measurements are able to detect mild disease symptoms before significant losses in LCC due to diseases under natural conditions.
*Identifier:*	10.3390/rs6010064 (DOI)
*Citation Advice:*	Yu K, Leufen G, Hunsche M, Noga G, Chen X, Bareth G. Investigation of Leaf Diseases and Estimation of Chlorophyll Concentration in Seven Barley Varieties Using Fluorescence and Hyperspectral Indices. Remote Sensing. 2014; 6(1):64-86.

Responsible Party

*Creators:*	Kang Yu (Author), Georg Leufen (Author), Mauricio Hunsche (Author), Georg Noga (Author), Xinping Chen (Author), Georg Bareth (Author)
*Publisher:*	MDPI AG, Basel, Switzerland
*Publication Year:*	2014

Topic

*TR32 Topic:*	Remote Sensing
*Related Subproject:*	Z1
*Subjects:*	Keywords: Remote Sensing, Chlorophyll, Fluorescence, Vegetation Index, Winter Barley, Plant Growth

File Details

*Filename:*	Yu_et_al_RS_2014.pdf
*Data Type:*	Text - Article
*Size:*	18 Pages
*File Size:*	719 KB
*Date:*	Issued: 19.12.2013
*Mime Type:*	application/pdf
*Data Format:*	PDF
*Language:*	English
*Status:*	Completed

Constraints

*Download Permission:*	Free
*Download Information:*	Remote Sensing Open Access Option: http://www.mdpi.com/2072-4292/6/1/64
*General Access and Use Conditions:*	no conditions apply
*Access Limitations:*	no limitations
*Licence:*	[TR32DB] Data policy agreement

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Specific Information - Publication

*Publication Status:*	Published
*Review Status:*	Not peer reviewed
*Publication Type:*	Article
*Article Type:*	Journal
*Source:*	Remote Sensing
*Source Website:*	http://www.mdpi.com/2072-4292/6/1/64
*Issue:*	1
*Volume:*	6
*Number of Pages:*	23 (64 - 86)

Metadata Details

*Metadata Creator:*	Georg Bareth
*Metadata Created:*	14.05.2014
*Metadata Last Updated:*	14.05.2014
*Subproject:*	Z1
*Funding Phase:*	2
*Metadata Language:*	English
*Metadata Version:*	V50

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