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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Food Quality Laboratory » Research » Publications at this Location » Publication #344054

Research Project: Rapid Methods for Quality and Safety Inspection of Small Grain Cereals

Location: Food Quality Laboratory

Title: Falling number of soft wheat wheat by near-infrared spectroscopy: a challenge revisited

item Delwiche, Stephen - Steve
item Steber, Camille

Submitted to: Cereal Chemistry
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 3/20/2018
Publication Date: 3/30/2018
Citation: Delwiche, S.R., Steber, C.M. 2018. Falling number of soft wheat wheat by near-infrared spectroscopy: a challenge revisited. Cereal Chemistry. 95(3):469-477.

Interpretive Summary: A very common analytical procedure known as 'falling number' is used in wheat commerce worldwide to gauge the biochemical integrity of milled flour for use in production of bread, cakes, crackers, and other wheat products. Falling number is based on a physical measurement (viscosity of a heated and hydrated mass) to infer the activity level of enzyme that cleaves the large starch molecules into sugars necessary for plant development. Too high a level means that a wheat lot may not be suitable for use in food production. Although the falling number procedure is relatively accurate, its cost, analysis time and required operator skill usually preclude this test from where it is needed the most, the first point of sale commonly called the country elevator. By contrast, near-infrared (NIR) spectroscopy is a technology that enjoys widespread use at the country elevator for analysis of moisture and protein. Past studies using early NIR instrumentation and statistical algorithms were not successful in producing workable NIR models for falling number. The current study, conducted at the behest of the U.S. Pacific Northwest wheat industry, sought to revisit this challenge using up-to-date equipment and software. Based on a very large collection of soft white wheat breeders' samples grown in multiple locations in Washington State, NIR modeling of falling number was explored by two approaches. The first approach was based on statistical regression modeling to emulate falling number directly, while the second approach was based on providing a pass/fail decision on whether the estimated falling number fell above or below a prescribed threshold. In either approach, the results indicated that NIR spectroscopy is not a suitable replacement to the actual falling number procedure. This knowledge is intended to serve the U.S. wheat commerce industry.

Technical Abstract: Wheat Hagberg falling number is a long-standing quality test that, by means of measuring the viscosity of a heated water-meal or water-flour mixture, characterizes the activity of alpha-amylase, the enzyme primarily responsible for starch hydrolysis. The accuracy, time requirement, and cost of this test have come under heightened scrutiny, particularly in seasons when weather conditions have been favorable to pre-harvest sprouting or late maturity amylase. Near-infrared (NIR) spectroscopy, an analytical approach routinely used in the grain industry to measure contents of protein and moisture, was reexamined as a possible alternative to the falling number procedure. More than 500 samples of Washington grown soft white wheat from state variety performance trials were used to develop and test NIR spectroscopy regression models for falling number. Additionally, linear discriminant analysis models were developed and tested for a falling number cutoff value in order to evaluate the feasibility of using a pass/fail test in lieu of a quantitative value for falling number. The results indicated that partial least squares regression model accuracy was low, with standard errors of performance ranging from 40 to 77s. Qualitative, pass/fail modeling accuracy was also low, with the best model correctly identifying 78% and 59% of the samples above and below a threshold value established as the median value of falling number of the samples in a calibration set of several hundred. Because of these lackluster performances, we conclude that replacement of the falling number test with one based on NIR spectroscopy on either whole grain or ground meal is not recommended.