Falling Number: Cereal Alpha-Amylase Assessment
The falling number test reports the time in seconds required for a viscometer stirrer to fall through a heated flour–water slurry after gelatinisation. The longer the time, the higher the slurry viscosity and the lower the alpha-amylase activity. Conversely, short times indicate elevated enzyme action caused by pre-harvest sprouting or malt addition. Pair this article with the drip irrigation water usage calculator to plan field moisture strategies that preserve target falling numbers.
Millers, grain traders, and bakers rely on falling number (FN) to predict dough handling, loaf volume, and crumb structure. Values are typically expressed without units (seconds) but trace back to the SI base unit of time as defined in ISO 3093 and AACCI Method 56-81.01.
Definition and Test Workflow
The Hagberg-Perten method mixes 7 grams of flour (corrected to 14% moisture) with 25 millilitres of distilled water in a viscometer tube. The slurry is shaken to disperse starch, then heated in a boiling water bath while a plunger is stirred. After 60 seconds, the stirrer is released, and the time until it reaches a fixed mark is recorded as the falling number. Higher viscosity slurries (low enzyme activity) delay the plunger descent, producing higher FN values.
Laboratories correct sample weights for actual moisture using factors referenced to volumetric water content. Consistent water temperature, tube diameter, and stirrer mass are essential for reproducible results.
Historical Development
Swedish cereal chemist Harald Hagberg introduced the falling number test in the 1960s to quantify sprout damage in wheat. Later, Carl-Henric Perten commercialised the apparatus, enabling rapid field and laboratory measurements. National grain boards in Scandinavia adopted the test as a standard grading tool, and its success led to global acceptance.
Subsequent refinements introduced automated timers, digital temperature control, and dual-sample instruments. International harmonisation via ISO 3093 ensures that results from different continents remain comparable—critical for export contracts and milling consistency.
Conceptual Foundations
Enzyme Activity and Viscosity
Alpha-amylase hydrolyses starch chains, reducing paste viscosity. The falling number therefore inversely reflects enzyme activity. Sprouted grain delivers excessive enzyme action, yielding FN below 200 seconds, while sound grain typically ranges between 250 and 350 seconds.
Moisture and Temperature Effects
Grain moisture and starch gelatinisation temperature influence the test. High moisture accelerates enzyme action and reduces FN. Laboratories equilibrate flour and water temperatures to 20 °C before testing to stabilise gelatinisation behaviour.
Relationship to Baking Performance
Optimal bread quality requires balanced enzyme activity. Too little (FN > 400) yields dense loaves and poor fermentation, whereas too much (FN < 200) causes sticky dough and gummy crumb. Bakers adjust malt or fungal amylase additions based on FN data to maintain target loaf volume.
Applications
Grain Procurement
Elevator managers screen incoming loads and apply discounts when FN falls below contract thresholds. Integrating FN with drip irrigation planning supports agronomists in mitigating future sprout damage.
Milling Optimisation
Millers segregate wheat streams by FN to balance enzyme activity in flour blends. Combining FN data with specific surface area insights helps tune grinding settings for consistent dough rheology.
Baking and Product Development
Artisan and industrial bakers adjust proofing times and enzyme additions according to FN results. Linking FN with water activity informs shelf-life predictions for breads, cakes, and tortillas.
Importance and Future Outlook
Climate variability increases the incidence of pre-harvest sprouting, heightening dependence on falling number screening. Rapid viscometric and near-infrared instruments are emerging, yet they continue to reference the Hagberg-Perten falling number for calibration.
Integrating FN data into digital grain management systems enables real-time contract enforcement and supports traceability for premium baking programs. Mastery of the seconds-based index ensures transparent communication between growers, traders, and bakers.