|YAPTENCO, KEVIN - University Of The Philippines|
|PEARSON, TOM - Amgen, Inc|
Submitted to: Transactions of the ASABE
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 9/25/2016
Publication Date: 12/1/2016
Citation: Armstrong, P.R., Maghirang, E.B., Yaptenco, K.F., Pearson, T.C. 2016. Visible and near-infrared instruments for detection and quantification of individual sprouted wheat kernels. Transactions of the ASABE. 59(6):1517-1527. doi:10.13031/trans.59.11566.
Interpretive Summary: Pre-harvest sprouting of wheat kernels within the grain head is a serious problem that greatly degrades flour produced from the wheat, resulting in poor dough and bread-making quality. Current grading standards use visual methods to determine sprouting levels on single kernels and Falling Number (FN) lab tests on flour slurries are used to determine the effect of sprouting on dough quality. Both methods require considerable time and expense to perform. Two instruments developed by USDA-ARS researchers in Manhattan KS that measure optical properties of individual grain kernels, one that uses visible light (VIS) and one that uses near-infrared (NIR), were examined as a method to replace these tedious methods. Evaluation of samples of sprouted Hard White and Soft Red Winter wheat classes indicate that both instruments can identify samples that have no or minor sprouting or samples that have extensive sprouting. The NIR instrument was also able to predict the FN by averaging multiple kernels. Both instruments can provide measurement alternatives for some applications such as screening breeder samples for sprouting susceptibility and eliminating non-sprouted samples from further screening.
Technical Abstract: Pre-harvest sprouting of wheat kernels within the grain head presents serious problems as it can greatly affect end use quality. Functional properties of wheat flour made from sprouted wheat result in poor dough and bread-making quality. This research examined the ability of two instruments to estimate the level of sprouting in single kernels of wheat. The objective was to provide a quick method to evaluate sprouting resistance for breeders. One instrument, Single Kernel Near-Infrared (SKNIR), uses near infrared reflectance (NIR) spectra spanning 990-1700 nm. The second instrument is the Silicon Light-Emitting Diode (SiLED) sorter which uses a silicon sensor to measure visible reflected light obtained from a kernel using several LEDs at discrete wavelengths. Multiple varieties of Hard White (HW) and Soft Red Winter (SRW) were conditioned to nine sprouting levels, S1 (untreated) to S9 (highly sprouted), using a multi-step soaking protocol with falling number (FN) being obtained from subsamples for each sprouting level. Partial least squares model predictions of FN based on single kernel NIR spectra yielded R2 values of 0.59 to 0.72. This improved when the spectral average from thirty kernels were used to predict FN resulting in R2 of 0.78 to 0.95. Sprout levels that were separated into three levels, sound, intermediate, and severely sprouted, could be classified reasonably well using the NIR instrument. The SiLED sorter was used to sort samples at each of the nine sprout level into two classes, sound and unsound kernels. Sound kernels were re-sorted twice. Sprouted kernels were then visually identified from the three sound streams and quantified by weight. Linear models developed based on these weights were used to predict FN and sprouted kernels. Models were marginal in most cases with R2s ranging from 0.59 to 0.87. Overall both instruments can identify samples with minimal or no sprouting and those with more severe sprouting; kernels with intermediate levels of sprouting are difficult to quantify.