Falling Number Method Research Articles

Sample distribution of observations of the falling number of corn flour

The sample distribution of observations is studied in order to study the variational feature, while the measured value is considered as random. For practical purposes, the empirical distribution of a random variable is estimated by proximity to the theoretical law. The statistical hypothesis of the sample data belonging to the general population is tested using the consent criteria. The object of this study was the observation of the falling number of corn flour, which is a prescription component of bakery products. In world practice, the falling number method for raw materials from corn is used as a reference for establishing reference interval values, detecting a variation of the studied trait. The purpose of this work was to study the sample distribution of observations of the falling number of corn flour to determine the representativeness of the sample of experimental data. Relying on Glivenko's theorem on the expediency of grouping sample data into a variation series in order to replace the distribution function of the general population with a sample distribution function, at the beginning of the research, the sample data were converted into a statistical series. The research material was an industrial sample of fine-ground corn flour that meets the requirements of GOST 14176-69 "Corn flour. Technical conditions". The falling number was studied when implementing the standard method on the PPP-99 device according to GOST ISO 2093-2016 "Grain and its processed products. Determination of the number of falls by the Hagberg-Perten method". The interval variation series was studied according to a wide list of characteristics: distribution center indicators (sample mean, mode, median, quartiles, deciles), variation indicators (span, average linear deviation, variance, unbiased variance estimate, mean square deviation, coefficient of variation, linear coefficient of variation, oscillation coefficient), distribution form indicators (relative quartile variation index, asymmetry coefficient, Pearson structural asymmetry coefficient, kurtosis index), indicators of interval estimation of the center of the general population (confidence intervals for the general average, interval estimation of the general share, i.e. the probability of an event). For the studied random variable of the falling number of corn flour, the hypothesis of a normal distribution was proved using the indicators of asymmetry and kurtosis, as well as using the 3σ sigma rule. As a result of the calculations, the representativeness of the sample data with respect to the variation of the studied trait in the general population was established

Application of the Falling Number Method in the Evaluation of the α-Amylase Activity of Malt Flour

The Falling Number (FN) test is not suitable for the determination of α-amylase activity in malt flour because the amylolytic activity is too high to be determined by the FN instrument. The aim of this study was to modify the FN method to allow quantification of high α-amylase activity in malt flour. The modifications were performed in two ways: using different amounts of malt flour (0.05, 0.1, 0.2, and 0.3 g) or by using malt extracts (0.5, 1, 2, 3, 4, 5, and 6 mL). In both cases, 6 g of standard wheat starch was used as substrate. The results of the modified methods were compared with the α-amylase activity determined by the standard Ceralpha method. Linear and nonlinear exponential regression was used to calculate the predicted amylase activity, and Bland-Altman analysis was used to measure the agreement between standard and modified methods. The modifications of the FN method using 0.1 g of malt flour showed that the modified method was able to accurately measure high levels of α-amylase activity in malt flour, and the results obtained by the modified method were in agreement with the results obtained by the standard Ceralpha method.

Streamlined alpha‐amylase assays for wheat preharvest sprouting and late maturity alpha‐amylase detection

AbstractLate maturity alpha‐amylase (LMA) and preharvest sprouting (PHS) lead to elevated alpha‐amylase in wheat (Triticum aestivum L.) grain. Risk of poor end‐product quality due to elevated alpha‐amylase is detected in the wheat industry using the Hagberg–Perten falling number (FN) method. In breeding programs, selection for PHS and LMA tolerance requires higher throughput methods requiring a smaller sample size than the 7 g required for the FN method. Specifically, LMA can only be screened only using detection of alpha‐amylase activity or protein after cold treatment of individual wheat spikes at a specific stage of grain development resulting in very small samples (≤1 g). This study developed and evaluated a high throughput 96‐well method for the Phadebas alpha‐amylase enzyme assay for small wheat grain samples and compared this method to FN and the Megazyme Alpha‐Amylase SD (Sprout Damage) Assay Kit performed on the automated Awareness Technology ChemWell‐T Analyzer. In parallel, the efficacy of low‐cost small‐scale milling methods was evaluated relative to traditional larger scale mills. The Phadebas enzyme activity was highly reproducible and showed a strong correlation to the SD enzyme assay and FN method regardless of which mill was used to process the grain. The SD assay offers simpler standardization and calculation of enzyme activity, whereas the Phadebas assay offers higher sensitivity and lower expense. Both the 96‐well Phadebas and automated Megazyme SD assays are suitable for alpha‐amylase detection from small samples, and the use of low‐cost coffee grinders to process small samples did not significantly impact assay performance.

As the number falls, alternatives to the Hagberg-Perten falling number method: A review.

This review examines the application, limitations, and potential alternatives to the Hagberg-Perten falling number (FN) method used in the global wheat industry for detecting the risk of poor end-product quality mainly due to starch degradation by the enzyme α-amylase. By viscometry, the FN test indirectly detects the presence of α-amylase, the primary enzyme that digests starch. Elevated α-amylase results in low FN and damages wheat product quality resulting in cakes that fall, and sticky bread and noodles. Low FN can occur from preharvest sprouting (PHS) and late maturity α-amylase (LMA). Moist or rainy conditions before harvest cause PHS on the mother plant. Continuously cool or fluctuating temperatures during the grain filling stage cause LMA. Due to the expression of additional hydrolytic enzymes, PHS has a stronger negative impact than LMA. Wheat grain with low FN/high α-amylase results in serious losses for farmers, traders, millers, and bakers worldwide. Although blending of low FN grain with sound wheat may be used as a means of moving affected grain through the marketplace, care must be taken to avoid grain lots from falling below contract-specified FN. A large amount of sound wheat can be ruined if mixed with a small amount of sprouted wheat. The FN method is widely employed to detect α-amylase after harvest. However, it has several limitations, including sampling variability, high cost, labor intensiveness, the destructive nature of the test, and an inability to differentiate between LMA and PHS. Faster, cheaper, and more accurate alternatives could improve breeding for resistance to PHS and LMA and could preserve the value of wheat grain by avoiding inadvertent mixing of high- and low-FN grain by enabling testing at more stages of the value stream including at harvest, delivery, transport, storage, and milling. Alternatives to the FN method explored here include the Rapid Visco Analyzer, enzyme assays, immunoassays, near-infrared spectroscopy, and hyperspectral imaging.

Application of the factor analytic model to assess wheat falling number performance and stability in multienvironment trials

AbstractA factor analytic model was used to characterize data generated with the Hagberg–Perten falling number (FN) method, a measure of wheat (Triticum aestivum L.) quality influenced by genotype‐by‐environment interactions. The FN method detects starch degradation due to the presence of the enzyme α‐amylase in wheat grain such that a low FN indicates high α‐amylase activity and high risk of poor end‐product quality. Because farmers receive severe discounts for low FN, FN data have been collected over multiple years for the Washington State University multilocation variety trials to help farmers and breeders identify lower risk varieties. Analysis of these data to objectively rank varieties is challenging because the dataset is unbalanced and because FN is subject to complex genotype‐by‐environment interactions. Low FN can result from environmental differences at multiple stages in grain development because there are two major causes of α‐amylase accumulation in grain, late‐maturity α‐amylase (LMA) and preharvest sprouting (PHS). A five‐factor analytic model extracted explicit measures of overall performance and of stability in variable environments from historical FN data from the multilocation trial, providing a basis for breeding and planting decisions. Whereas a linear model explained 70.3% of the variation, the five‐factor analytic model accounted for 92.5% of variation in the data. Examination of factor loadings enabled us to separate environments and genotype response to either PHS or LMA, specifically. This is the first application of a factor analytic model to evaluate the end‐use quality trait FN, providing a method to rank varieties for grower decisions and breeder selections.

Investigation into the use of the amylase SD assay of milled wheat extracts as a predictor of baked bread quality

α-Amylase content in milled wheat is a key quality parameter in the baking industry. This metric is usually determined using the Hagberg Falling Number (FN) method, the results of which can be used to segment grains into a range of quality categories. The authors describe herein an alternative to the traditional FN assay, namely the Amylase SD assay, as a predictor of baked bread quality. 144 Wheat grain samples with known FN values were analysed using the Amylase SD assay and a simple model for the conversion of Amylase SD units into “predicted FN” (PFN) values has been described. To test the usefulness of this approach, 11 separate wheat grain samples were analysed using the FN method, the Amylase SD assay, and also for gluten content. These grain samples were then milled to produce flour which was re-analysed using the Amylase SD assay and then formulated into dough that was subjected to Mixolab analysis, before being baked to produce pan bread. Correlations of baked bread volume and common Mixolab parameters to both FN and PFN values have been investigated for each sample. The Amylase SD assay has been shown to be a potentially promising alternative to the FN method for use as a baked bread quality predictor.

A rapid, automated method for measuring α-amylase in pre-harvest sprouted (sprout damaged) wheat

The quality of wheat for baking is critically dependent on the level of α-amylase (1,4-α-D-glucan glucanohydrolase, EC 3.2.1.1), which can be present as “late maturity α-amylase” (LMA), or due to pre-harvest sprouting due to high rainfall and humidity at the time of harvesting. The most commonly used method to measure α-amylase in wheat grain is the Hagberg Falling Number method, but values are also influenced by rheological properties of starch in the grain. In this study we describe a simple, rapid, automated method (Amylase SD) for measurement of α-amylase in pre-harvest sprouted (sprout damaged) wheat grain. The method (Amylase SD) measures the release of p-nitrophenol from 4,6-O-ethylidene-α-4-nitrophenyl-maltoheptaoside by α-amylase in the presence of α-glucosidase. The absorbance of p-nitrophenolate measured at 405 nm in a ChemWell®-T auto-analyser is directly related to the level of α-amylase activity present in the milled wheat grain extract. The Amylase SD method generated <6%CV and correlation to the Falling Number method was represented by an inflection point at ∼160 s. The precision, sensitivity and speed of this method provides an ideal alternative to the Falling Number method for measurement of α-amylase (sprout damage) in wheat grain in wheat breeding programmes or at grain receival points.

Novel assay procedures for the measurement of α-amylase in weather-damaged wheat.

The measurement of α-amylase (EC 3.2.1.1) in sprout-damaged grains is a crucial analysis yet a problematic one owing to the typically low α-amylase levels in ground wheat samples. A number of standardised methods such as the Falling Number method and the Ceralpha method exist which are routinely used for the assay of α-amylase. These methods, however, are either highly substrate-dependent or lack the required sensitivity to assess sprout damage. Novel colorimetric and fluorometric reagents have been prepared (Amylase HR, Amylase SD, BzCNPG7 reagent and BzMUG7 reagent) for the direct and specific assay of α-amylase activity in sprout-damaged wheat. Assays employing these reagents have been developed and optimised to include a decolourisation step using activated charcoal. When used in a convenient assay format, Amylase SD--containing EtNPG7 (II) as the colorimetric substrate and α-glucosidase as the ancillary enzyme--was found to be an excellent reagent for the assessment of sprout damage in wheat with incubation times as short as 5 min. The assay using Amylase SD is completely specific for α-amylase. The use of the Amylase SD assay represents a sensitive and valid alternative to the traditionally used Falling Number values for the assessment of sprout damage in wheat samples.

Physicochemical changes and enzymatic activity of pre-harvest sprouting wheat

O trigo na colheita está exposto a danos por chuva, que podem levar à alteração na qualidade e perda de valor comercial. O objetivo desse trabalho foi caracterizar as alterações de diferentes variedades de trigo da região Sul que sofreram danos por chuva, detectado pelo método de falling number. Treze amostras foram avaliadas quanto a peso hectolitro, peso de mil sementes, proteína, açúcares redutores, nitrogênio solúvel, nitrogênio de aminoácidos livres e atividade enzimática (α e β-amilase, β-glucanase e protease). As alterações na fração de gliadina foram avaliadas por eletroforese SDS-PAGE. As variáveis açúcares redutores, nitrogênio solúvel, nitrogênio de aminoácidos livres, atividade de α-amilase, β-glucanase e protease apresentaram correlações significativas com falling number. À medida que houve redução do falling number, as gliadinas apresentaram alterações nas bandas entre 40 e 30 KDa que ficaram mais intensas.

Emprego do método número de queda fúngico na determinação da atividade de alfa-amilase em farinha de trigo

Summary The quantity of fungal alpha-amylase used in wheat flour must be controlled since an excess negatively affects the baking process. Since the classical falling number method does not quantify fungal alpha-amylase, a method must be used that does determine the amount present. The aim of this work was to study the fungal falling number method in the determination of the amylolytic activity of wheat flour, and to evaluate its influence on the functional properties of the loaves. Four wheat flour samples were characterized with respect to their moisture, crude protein and damaged starch contents, and also alveography and falling number. Concentrations of 0, 0.028, 0.056 and 0.084 g.kg –1 of fungal alpha-amylase in the treatments were evaluated, determining the falling number and carrying out baking tests. The results were analyzed by the analysis of variance and the comparison of means by Tukey’s test at the 5% level of significance. The flour characterization results showed that the values for dough deformation energy (W) correlated with the percentage of damaged starch, and there was no relationship between W and the percentage of crude protein. The amylolytic activity proportionally reduced the amount of fungal alpha-amylase added. This method is appropriate to predict the total amount of amylolitc enzymes present in wheat flour, producing better loaf volume yields and crust colours when fungal alpha-amylase concentrations of 0.056 and 0.084 g.kg – ¹ were used.

Study of the relationship between sprouting score and sprout damage in durum wheat (Triticum turgidumL. var.durum)

Sprout damage in durum wheat (Triticum turgidum L. var. durum) is caused by pre-harvest sprouting. It reduces seed quality and causes a loss of starch gel viscosity, which negatively affects the pasta industry. The objectives of this research were to study the relationship between sprouting score and sprout damage in two durum wheat populations grown at Langdon, and Prosper, ND, to test the sensitivity of the stirring number test compared with the falling number test for estimating sprout damage, and to evaluate the effect of cutting date on sprout damage. A negative correlation between sprouting and sprout damage was detected in both populations. The stirring number test was more sensitive than the falling number method, but the two tests were positively correlated when sprouted and sound seeds were used. Cutting date did not significantly affect sprouting score. There was no significant cutting date × genotype interaction. Viscosity loss due to sprouting was complete in the two populations.

Comparison between methods for estimating sprout damage in wheat

Sprouting in wheat is common when rain occurs during harvest. This causes the moisture content of the grain to increase to a level at which germination takes place and α-amylase increases. Various methods can be used to determine α-amylase in cereals. The Falling Number method is currently widely used in the milling and baking industry. As well as being time-tested and reliable, this method is very sensitive to the presence of low levels of enzyme. However, it is often influenced by factors other than α-amylase, such as the nature of the starch, starch damage and environment. In this study various methods to determine preharvest sprouting and α-amylase activity were compared. All the methods evaluated showed significant correlations to each other and any of these methods could therefore be used to determine sprouting. Results indicated that the Stirring Number and Falling Number methods are the most reliable for the determination of preharvest sprouting and α-amylase activity.

The influence of fungal α‐amylase supplementation on amylolytic activity and baking quality of flour

In order to determine the quantity of fungal α‐amylase to be added to flour of low amylolytic activity, it was thought necessary to develop a method suitable for measuring the activity of both cereal and fungal α‐amylase. For determination of fungal α‐amylase activity, thermolability of the enzyme made the classical Falling Number Method not suitable. The Fungal Falling Number (FFN) Method was developed to measure amylolytic activity in flour supplemented with fungal α‐amylase. Reproducibility of Fungal Falling Number measurements on tested flour samples is high (standard deviation was 16.33 s and the variation coefficient 6.19%). The ratio between flour amylolytic activity, after addition of fungal α‐amylase, and the quantity of the added fungal α‐amylase, as well as the initial amylolytic activity of flour was described by the multiple regression non‐linear model. By applying the model, one could account for 88.48% of total deviations of the regression of the measured Fungal Falling Number values, making the model representative. Such a model can be used to determine the required quantity of fungal α‐amylase to achieve the optimal amylolytic activity of flour for the baking industry, provided the starting amylolytic activity in flour is known. The analysis of test baking results has shown that flour with an amylolytic activity range of 100 s &lt;FFNf &lt; 200 s yields bread loaves of the largest volume and excellent sensory properties.

Effect of Kiln Drying on Falling Number of Oats

ABSTRACTThe suitability of the falling number method for oats was studied using samples of oat groats, oat bran, oat endosperm flour, and rolled oats. Sample sizes of 4.5–8 g were tested. The results showed that a standard 7‐g sample falling number determination would be suitable for oats, the falling number of samples varying from 328 to 721 sec. Due to high gelatinization temperature of oat starch, falling number values &lt;300 sec showed greater variation than those &gt;300 sec. Oat groat samples from two separate kiln drying processes showed that kiln drying increased the falling number values by 30–89%. The falling number determination is a potential tool for estimating the adequacy of kiln drying of oats. However, further modifications of the method should be developed to better consider the pasting properties of oat starch.

Effect of amylase treatment on the consistency of cooked, fermented oat bran porridge.

Oat bran porridges were cooked and fermented at 5, 10, 15, and 20% solids (as is basis). Cooking was carried out on gas stove and viscograph. Supplementation with malt flour at 0.1, 0.25, 0.5, 0.75, and 1%. Cooked oat bran porridge was inoculated with fresh yoghurt and fermented 18 h overnight in an incubator at 42 degrees C. Falling number values were made to estimate the effects of amylase treatments by addition of malt flour on oat bran slurry when heated in an aqueous suspension. Pasting properties were observed with the viscograph and consistency measurements were made with Bostwick consistometer. The falling number method was not suitable for consistency measurements due to wide variations in values obtained. Enzymatic additions reduced the consistency of porridge with an increase in flowability during measurements. The peak heights obtained from the viscograms reduced proportionally with an increase in malt flour supplementation. The desirability of a product with higher energy values and a sufficiently low consistency that is spoonable was possible with cooked, fermented oat bran porridge.

THE GRL PASTE VISCOSITY INDICATOR FOR RAPID DETERMINATION OF α-AMYLASE IN CANADIAN RED SPRING WHEAT

An instrument called the paste viscosity indicator (PVI) has been developed at the Grain Research laboratory (GRL) for measuring the paste viscosity of a heated ground grain-water slurry. Increased resistance offered to the stirring device upon heating a ground grain-water slurry is reflected in a voltage signal representing the current requirements of a small DC motor. Paste viscosity decreases with increasing α-amylase levels in the ground grain. The viscosity is measured by a digital panel meter which retains its reading after a testing period of 3 or 3.5 min. The machine is portable (8.8 kg) and does not require a running water source. Operation is in simple steps and sample containers are low cost and disposable. The method correlates well with Falling Number method over the range of 65 – 425 s for Canadian Western Red Spring wheat. As such, it may be well-suited for implementation into a carlot or cargo monitoring program for assessment of preharvest sprout-damage.Key words: Amylase, wheat, control, sprout-damage

ABILITY OF THE CANADIAN GRADING SYSTEM TO SEGREGATE CANADIAN WHEAT BY ALPHA-AMYLASE LEVELS

A survey of falling number values in carlots of most classes of wheat (Triticum aestivum L.) was undertaken between October 1985 and February 1986. The purpose was to assess the effectiveness of the present visual grading system for segregating wheat by α-amylase levels as indicated by the falling number method. In addition, the survey was used to pinpoint areas of the western Canadian prairies from which sprout-damaged wheat originated. CWRS wheat had increasing amounts of α-amylase (lower falling number values) with lower grade. The values obtained for a given grade remained relatively constant over the entire testing period. Furthermore, the interdecile range in falling number values for the samples in a particular grade was only around 110 s. Other classes of wheat (CPS, CWSWS, CWRW) exhibited lower falling number values than CWRS wheat, reflecting increased susceptibility to preharvest sprouting and/or different tolerances for maximum percentage of sprouted kernels. Over the testing period, certain grades of some classes also varied more than CWRS wheats in falling number values. The interdecile range in values for these classes was very large and there was considerable overlap in falling number between grades. This suggests that some form of α-amylase testing could be used to advantage for these classes of wheat to ensure more consistent and uniform quality.Key words: Wheat, alpha-amylase, grading, falling number

COMPARISON OF THE HAGBERG FALLING NUMBER AND MODIFIED GRAIN AMYLASE ANALYZER METHODS FOR ESTIMATING SPROUT DAMAGE IN RYE

The Hagberg falling number method and a recently developed turbidometric method using the Perkin Elmer Model 191 Grain Amylase Analyzer were evaluated for measuring the levels of α-amylase activity in rye samples with varying sprout damage. Poor correlations were obtained between the a-amylase methods and percent visual sprout damage, although the two α-amylase methods correlated fairly well with each other. Differences between levels of α-amylase activity and levels of sprout damage may be explained by: (a) the difficulty in assessing sprout damage levels due to the presence of degermed or skinned kernels; (b) the association of higher levels of α-amylase activity with other types of damaged kernels; and (c) the severity of sprouting of individual rye kernels.

Literature Abstracts

Literature Abstracts