1 NSW Department of Primary Industries, Wagga Wagga Agricultural Institute, Wagga Wagga, NSW 2650, Australia
2CSIRO Plant Industry, Canberra, ACT 2601, Australia
Late maturity alpha-amylase (LMAA) was recognised in Australia in the late 1980’s. It was found to affect many varieties and lines grown within Australia, particularly in the southern regions of the country (Mares and Mrva, 1992). Growing conditions play a major role in the development of LMAA, in particular cool, moist conditions (Mares and Mrva, 1992). Varietal response to the environment and susceptibility to LMAA can be quite different; some susceptible varieties produce LMAA under a wide range of conditions (Gale and Lenton, 1987; Mares and Gale, 1990). Growing conditions on irrigation seem to be conducive to susceptible varieties developing high levels of LMAA and readily sprouting if there is any rainfall after the crop has ripened.
A GRDC funded project was conducted to evaluate wheat genotype and management practices associated with producing consistent high yield on irrigation in southern NSW. At Benerembah there were three experiments sown at one site, and from these a set of Chara samples were selected. This site and the three trials provided a unique set of Chara samples with a large variation in Falling Numbers. Detailed analyses were conducted to determine the cause of the variation.
Falling Numbers below 350 seconds are considered unacceptable for processing and this is the case with weather damaged grain that has low Falling Numbers. However, grain that has a low Falling Number due to LMAA, which is presumably only α-amylase and not the other enzymes associated with weather damage, were tested to determine acceptability for processing.
Materials and methods
A single trial site was used, located at Benerembah in the southern NSW irrigation area. The site consisted of a single bay with flood irrigation and no undulations in the paddock. Three different trials were conducted using the same management techniques, including watering. The trials were CSIRO Core trial; NSW DPI irrigated wheat trial and Farm Plots with different levels of fertiliser from 20-211kg/plot. There were some differences in the sowing and harvest dates of the trials. The sowing dates for the CSIRO Core Trial, NSW DPI trial and Farm Plots were May 29th, May 5th and May 10th respectively. The Core Trial was harvest on December 10th and both the DPI trial and Farm plots were harvested on the 16th December.
A chrondrometer designed at Wagga Wagga Agricultural Institute, was used to determine test weight. Thousand kernel weight was determined by weighing 1000 grains counted by a Pfeuffer Contador Type KZG ‘E’ seed counter. Falling Number was determined by using the ICC Standard No.107 Perten Falling Number machine Type 1700 (Perten Instruments, Huddinge, Sweden). Grain moisture was determined using electrical conductance (Marconi moisture meter model TF933B). Hardness was determined by using an NIR Technicon Infra-alyzer 250 (Technicon Instruments Corporation, Tarytown, USA) calibrated with a PSI scale and protein was determined by NIR Technicon Infra-alyzer 250 (Technicon Instruments Corporation, Tarytown, USA).
LMAA was tested using a single-grain technique, where a grain is split into ‘embryo’ and ‘endosperm’ portions. This method was used to try and discriminate between sprouting and LMAA (Pleming et al, 1996). In sprouted grain, the α-amylase is concentrated in the embryo end, whereas in LMAA grains, the amount of enzyme in the endosperm equals or exceeds that in the embryo.
Wheat (3kg) was conditioned to 14.6% moisture level for 24 hours. An extra 0.4% moisture was added 0.5 hr before milling in a Buhler MLU202 test mill (Buhler-Miag, Uzwil, Switzerland). Flour extraction was calculated on a total recovered products basis.
Flour colour was measured as L*, a*, b* using a Minolta Chroma meter model CR-200 (Oliver et al. 1993). Flour paste colour was determined using the Minolta Chroma meter model CR-200 and preparing the paste according to the method AACC 14:30.
Physical Dough Measurements
The Farinograph was used to measure water absorption, dough development time, dough stability and breakdown at 5 mins, using the method described by RACI, (1988). Extensograph height and extensibility were determined using the Extensograph method RACI, (1988).
Enzyme Activity Measurements
Flour pasting properties were determined by the Rapid Visco Analyser, Model 3D (Newport Scientific, Australia) using the method described by Allen et al (1998). Alpha amylase levels were determined using AACC Method 22-05, 2000. Flour Swelling Volume (FSV) was determined using the method of Crosbie et al (1991). Polyphenol oxidase (PPO) was determined based on the method described by Demeke et al (2001) using L-tyrosine as the substrate. Falling number (FN) was determined according to the method RACI CCD 05:08.
The test baking formula was: flour 110g, yeast 2.5g, sodium chloride 2g, ammonium chloride 0.1g, malt extract 0.6g. The amount of water added was determined from the farinograph water absorption. Doughs were mixed in the National pin mixer (National MGF Co, Lincoln, Nebraska, USA) for various times. After mixing, doughs were fermented for 1 hr at 280C in décor polyethylene screw-top containers, and then lightly hand knocked and run through rollers (5/32”gap setting). Doughs were then proofed for 15 minutes at 280C, moulded in a Mono Universal moulder (Automatic Bakery Machinery, Swansea, England) at pressure 32 and gauge setting 1, and tin-proofed for 45 minutes at 330C and high humidity. Baking was done in a Rotell II rotary oven model RBSR2D STD (APV Baker Pty Ltd) at 215 0C for 20 minutes. Loaf volume and bake scores were determined the next day (AACC, 2000).
Yellow Alkaline Noodle
Noodle sheet colour was measured by the method described by Allen et al, (1999).
Wholemeal Falling Number (FN) was found to be significantly correlated with flour FN (R2= 0.89, p=0.05). In this study, FN low in wholemeal were also low in the flour; indicating milling did not remove α-amylase activity. This is consistent with work conducted by Oliver et al (1996), which showed the milling process was not effective in reducing the alpha-amylase from LMAA affected grain. This may also suggest that the enzyme activity may not be confined to the aleurone layer, although some of the aleurone alpha-amylase may have ended up in the flour due to milling. Unlike weather damage, LMAA affected lines that do not have all the other germination enzymes and any effect on quality was due to α-amylase alone. All other measurements of starch quality such as RVA and FSV showed a similar relationship with enzyme activity as the FN. Flour paste viscosity was significantly correlated with wholemeal FN (r2 = 0.75, p= 0.05). There was no correlation between alpha-amylase activity and polyphenol oxidase (PPO) (r2 = 0.056)
Figure 2: The relationship between FN and alpha-amylase. This same relationship was found by Barnes and Blakeney (1974)
Scatter plots of falling number, wheat proteins and loaf volume show no effect of FN on baking quality; the weather damaged samples did produce loaves with thick cell walls, but not the LMAA samples. Yellow alkaline noodle colour L* at 0.5 hours and 24 hours showed the biggest influence was by protein. Protein also had the biggest influence on both loaf volume and noodle brightness.
Figure 1: FN, WP and Loaf volume
Figure 2: FN, WP and Noodle L* 0.5 hour and 24 hour
The correlations for noodle sheet colour are as follows:
PPO vs 0.5 L* r2 = 0.54 (ns)
PPO vs 24 hour L* r2= 0.66 (significant) (p=0.05)
WP vs 0.5 L* r2 = 0.88 (significant) (p=0.05)
WP vs 24 hour L* r2 = 0.88 (significant) (p=0.05)
FN vs 0.5 L* r2 = 0.07 (ns)
FN vs 24 hour L* r2 = 0.23 (ns)
These results show that PPO (24 hours) and wheat protein content had the major influence on the noodle sheet brightness and there was no correlation between the FN and noodle sheet brightness.
Milling the Chara samples with LMAA was not effective in removing the alpha-amylase, as FN remained low in the flour. LMAA did not appear to have any detrimental effect on the quality parameters measured on Chara. Only weather damaged samples had quality defects, as quality parameters were not affected by the low FN in the LMAA samples. However, if a FN were measured at receivals, the mean FN for all the Chara samples in the paddock was 305 seconds. At this level, the result would be low for Australian Hard or Australian Prime Hard classes.
Given these results, careful thought needs to be given to LMAA testing because of the extreme variability. Environmental conditions are said to play a major role, even on the same variety grown in the same paddock in different replications or plots, as this data shows. This variability can be found down to a single plant level. Therefore, careful research needs to be conducted to address some of the discrepancies in the test results from screening; because of the high costs involved in developing new wheat varieties, decisions to reject a variety should have sound scientific evidence. An important question is “Does the controlled testing relate well to field conditions”?
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