Investment

Falling Number is a global industry standard to quantify detrimental pre-harvest sprouting (PHS), which can lead to significant effects on end-product quality. However, low Falling Number can also be caused by the genetic trait of Late Maturity alpha-Amylase (LMA). Susceptibility to LMA is currently an Australian milling wheat classification criterion. The incidence of LMA in wheat grain is currently assessed using an ELISA assay to detect and quantify high pI alpha-amylase, the product of LMA expression. The test is relatively low-throughput and cannot be easily adapted to assist decision-making by growers or grain receivers.

This project will develop a low-cost test for starch degradation in wheat grains which can also assign the cause of starch damage to either LMA or PHS. A laboratory-based method will be established using sensor-based technology to map the spatial distribution of starch damage caused by alpha-amylase activity across the surface of the grain. The spatial distribution of alpha-amylase activity will be used to distinguish between LMA and PHS, since activity near the embryo is known to be caused by PHS, while that occurring within the endosperm is caused by LMA. Knowledge of the regions of the electromagnetic spectrum detected by the sensor technology that associate with starch damage caused by alpha-amylase activity will be used to inform the development of rapid, mobile and low-cost sensors. These tools will be usable by breeders and researchers to determine the cause of starch damage in breeding materials and research populations in the field. They will also be suitable for growers to aid post-harvest decision making and allow grain receivers to determine starch damage rapidly and reliably.