Discriminating Spectral Signatures Among and
Within Two Closely Related Grapevine Species
Matthew Maimaitiyiming, Allison J. Miller, and Abduwasit Ghulam
Abstract
Several North American Vitis species are used to breed scions
and rootstocks, including V. riparia and V. rupestris. However,
the degree to which Vitis species can be distinguished using
remote sensing is not well known. Here we explore whether
two North American Vitis species and genotypes growing in a
common garden can be discriminated with leaf and canopy
hyperspectral reflectance factor data (350-2500 nm) using in-
dependent t-test and derivative analysis. Foliar properties and
spectral indices of the grapevines were evaluated with analysis
of the variance (ANOVA) and pair-wise Bonferroni adjusted
t-tests. The results showed that V. riparia and V. rupestris can
be distinguished at the leaf level spectra of visible, near- and
infrared spectral regions. At the canopy level, genotypes were
spectrally discriminated with limited success. The Photochemi-
cal Reflectance Index (PRI) demonstrated the highest potential
not only to differentiate two species, but also two genotype
pair groups within V. rupestris. This finding was also true for
the PRI calculated with simulated EO-1 Hyperion data. These
capacities to distinguish Vitis species, and to a lesser extent
genotypes, using spectral signatures have important applica-
tions in remote monitoring of vineyards for plants health and
also for locating wild Vitis populations for future crop improve-
ment efforts.
Introduction
Grapes (
Vitis
spp.) are the most economically important berry
crop in the world. The European grapevine
V. vinifera
is the
primary species used to produce wine and table grapes (Myles
et al
., 2011); however, like many clonally propagated woody
perennials, cultivated grapevines are usually two distinct
genotypes that are grafted to one another. The above-ground
part of the plant (the scion) produces the stem, leaves, flow-
ers, and berries, and the below-ground part (the rootstock)
makes the lower stem and roots. In most regions of the world,
grafting allows grape growers to retain the economically
valuable berry-producing varietal (e.g., Cabernet Sauvignon,
Chardonnay) while introducing resistance to soil-borne pests
and pathogens through rootstocks.
North American
Vitis
species have played a vital role in
the global grape industry both through the generation of root-
stocks as well as through their contributions to hybrid scions.
For example, while approximately 90 percent of US grape
acreage consists of
V. vinifera
cultivars in California, the vast
majority of these are grafted to rootstocks derived from native
North American grape species including
V. berlandieri
,
V. ri-
paria
, and
V. rupestris.
In the Midwestern and Eastern United
States, abiotic and biotic stress preclude most cultivation of
even grafted
V. vinifera
ssp.
vinifera
; instead, in these areas
cultivated grapevines are hybrid scions derived from crosses
between
V. vinifera
ssp.
vinifera
and one of the native North
American
Vitis
species. Today, grape growing is becoming a
more significant component of rural agricultural development
in these areas. For example, in Missouri, grape and wine is
a $1.6 billion industry with a 16 percent annual growth rate
(Stonebridge Research, 2010). Despite the importance of na-
tive North American species for rootstock and scion breeding,
relatively little is known about our capacity to differentiate
different
Vitis
species remotely.
Given the increasing importance of North American
Vitis
species, two ongoing challenges in the grape and wine in-
dustry are to locate wild North American
Vitis
germplasm for
breeding, and to monitor plant health in hybrid vineyards in
an efficient manner. In this study, we use spectral signatures
to determine whether closely related native grape species
could be distinguished from one another remotely. These ap-
proaches and results have potential applications in ongoing
efforts to locate native germplasm for breeding, and also in
vineyard management, where grape growers are looking for
new ways to efficiently monitor plant health.
This study focuses on two native North American grape-
vines (
V. riparia
and
V. rupestris
) both of which are used in
the generation of hybrid scions and rootstocks..
Vitis riparia
and
V. rupestris
present an interesting system for compar-
ing spectral responses of plants because they are likely
each other’s closest relatives (Zecca
et al
., 2012; Miller
et
al
., 2013), but are differentiated morphologically in terms
of leaf shape and leaf ion concentration, which has strong
implications for monitoring crop health using remote sensing
techniques. Natural populations of
V. riparia
and
V. Rupes-
tris
have evolved to inhabit different types of environments:
V. rupestris
occurs on rocky, dry creek beds in Missouri and
surrounding states (Fernald, 1987). Its closest wild relative,
V.
riparia
, is found in moister soils and in forests throughout the
northeastern quarter of the United States (US Forest Service,
1949).
V. riparia
and
V. rupestris
present an ideal system in
which to explore differences in spectral signatures because
they are closely related but have diverged morphologically
in leaf traits; further, they are easily cloned which means that
spectral reflectance factor data can be collected from multiple
replicates of the same genotype, offering a robust statistical
framework for analysis.
We leverage an experimental vineyard of
V. riparia
and
V. rupestris
housed at the Missouri Botanical Garden (
MBG
)
to test the hypothesis that two unique
Vitis
species, as well
as different genotypes within each species, can be detected
remotely. The plants in the
MBG
experimental vineyard are
Matthew Maimaitiyiming and Abduwasit Ghulam are with
the Center for Sustainability, Saint Louis University, Des
Peres Hall, Room 209A, 3694 West Pine Mall, St. Louis, MO
63108 (
).
Allison J. Miller is with the Saint Louis University, Missouri
Botanical Garden, Macelwane Hall, Room 122, 3507 Laclede
Avenue, St. Louis, MO 63103-2010.
Photogrammetric Engineering & Remote Sensing
Vol. 82, No. 2, February 2016, pp. 51–62.
0099-1112/16/51–62
© 2015 American Society for Photogrammetry
and Remote Sensing
doi: 10.14358/PERS.82.2.51
PHOTOGRAMMETRIC ENGINEERING & REMOTE SENSING
January 2016
51
