Agriculture Reference
In-Depth Information
Ara h 1 (Krause et al. 2010). The absence of Ara h 1 did not reduce
allergenicity as judged by mediator release from rat basophilic leukemia
cells. A variant of Ara h 3, Ara h 3im, was determined to have potentially
altered glycosylation sites and one less epitope than other Ara h 3
isoforms, structural differences that could reduce allergenicity (Kang
and Gallo 2007). Given that natural genetic variation is rare, inducing
variation may become the most expedient approach for altering allergen
composition (see Section VII C). The prevalence of allergic reactivity, the
IgE epitopes, and the genetic variation in the other peanut allergens
(Ara h 5
-
Ara h 11), which are not classi
ed as major allergens, need
further research.
IV. PREDICTING SEED QUALITY AND ALLERGENS
A. Oil and Oil Quality
Traditionally, gas chromatography (GC), capillary electrophoresis (CE),
and nuclear magnetic resonance (NMR) have been used to accurately
determine the oil and fatty acid composition in peanut seeds (Metcalfe
et al. 1966; Rubel 1994; Bannore et al. 2008; Chamberlin et al. 2011). In
recent years, near-infrared re
ectance spectroscopy (NIRS) has found
wide application in estimating various chemical components in seed,
plant, and food in many crops. It covers the range of the electromagnetic
spectrum from 780 to 2500 nm. Essentially, the product (including seed)
is exposed to NIR irradiation, and the re
ected or transmitted radiation is
measured. While the radiation penetrates the product, its spectral
characteristics change through wavelength-dependent scattering and
absorption. This change depends on the chemical composition of the
product, as well as on its light scattering properties, which are related to
the plant microstructure. Multivariate statistical techniques such as
partial least-squares regression are then applied to extract the required
information from the usually convoluted spectra (Lee et al. 2011).
Tillman et al. (2006) were probably the
rst to demonstrate that NIRS
prediction of oleic acid and linoleic acid, using intact peanut seeds, is
accurate and rapid and could be used for discarding early-generation
segregants in breeding programs. This method accurately identi
ed 90%
of the seeds with elevated oleic acid and reduced linoleic acid contents
in their research. The NIRS calibration equations were highly predictive
of oleic and linoleic acids measured with GC. Further investigation on
use of NIRS con
rmed that it is a reliable method to predict the oleic and
linoleic fatty acids, and could be used to discard segregants with
