A non-linear model of nondestructive estimation of anthocyanin content in grapevine leaves with visible/red-infrared hyperspectral

Jiang Lin Qin, Donald Rundquist, Anatoly Gitelson, Zongkun Tan, Mark Steele

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Scopus citations

Abstract

The anthocyanin(Anth) content in leaves provides valuable information about the physiologocal status of plant. Thus, there is a need for accurate, efficient, practical methodologies to estimate this biochemical parameter. Hyperspectral measurement is a means of quickly and nondestructively assessing leaf Anth in situ. Wet chemical methods has traditionally been used for this purpose. Recently, NIR(near-infrared)/green, red/green, anthocyanin reflectance index(ARI), and a modified anthocyanin refelctance index(MARI) was been used to estimate the anthocyanin content. In this paper, a an artificial-intelligence technique model was introduced to establish the relationship between the anthocyanin content and reflectance of 400-750nm spectum, variation of species and growth stages. The objective of this study was to test the overall performance and accuracy of this new nondestructive techniques for estimating Anth content in grapevine leaves. Although Anth in validation data set was widely variable, the new methods were capable of accurate predicting Anth content in grapevine leaves with a root mean square error below 1.65 mg/m 2, which is lower than that of MARI or ARI [20]. It documents the facts that such an approach is more suitable for developing simple hand-held field instrumentation for accurate nondestructive Anth estimation and for analyzing digital airborne or satellite imagery to assist in making informed decisions vineyard management.

Original languageEnglish (US)
Title of host publicationComputer and Computing Technologies in Agriculture IV - 4th IFIP TC 12 Conference, CCTA 2010, Selected Papers
PublisherSpringer New York LLC
Pages47-62
Number of pages16
EditionPART 4
ISBN (Print)9783642183683
DOIs
StatePublished - 2011

Publication series

NameIFIP Advances in Information and Communication Technology
NumberPART 4
Volume347 AICT
ISSN (Print)1868-4238

Keywords

  • Anthocyanin
  • Grapes
  • Hyperspectral
  • SVM (Support Vector Machine)

ASJC Scopus subject areas

  • Information Systems
  • Computer Networks and Communications
  • Information Systems and Management

Fingerprint Dive into the research topics of 'A non-linear model of nondestructive estimation of anthocyanin content in grapevine leaves with visible/red-infrared hyperspectral'. Together they form a unique fingerprint.

  • Cite this

    Qin, J. L., Rundquist, D., Gitelson, A., Tan, Z., & Steele, M. (2011). A non-linear model of nondestructive estimation of anthocyanin content in grapevine leaves with visible/red-infrared hyperspectral. In Computer and Computing Technologies in Agriculture IV - 4th IFIP TC 12 Conference, CCTA 2010, Selected Papers (PART 4 ed., pp. 47-62). (IFIP Advances in Information and Communication Technology; Vol. 347 AICT, No. PART 4). Springer New York LLC. https://doi.org/10.1007/978-3-642-18369-0_6