Mariann Rakszegi, László Láng, Zoltán Bedő
Agricultural Research Institute of the HAS, Martonvásár, Hungary
Importance of starch properties in quality oriented wheat breeding
Starch in practice
• Inert filler (?)
• Need of the processing industry
- Japanese noodle
- increase of water absorption (meat and paper industry)
- source of carbohydrates
- Resistance starch
• Starch is 65-70% of the dry weight of the kernel
• 20-30% of starch is amylose
citoplazmaszacharózszacharóz
szacharózADPGPP
citoplazma
amiloplaszt
szaharóz
G1P
ADP-glükóz
G1P ADPG SSI SSIISSIII
GBSS
BEIBEII DBE
75% amilopektin
25% amilóz
ADPGPP
ADPGPP
7A, 7D, 4A
citoplazmaszacharózszacharóz
szacharózADPGPP
citoplazma
amiloplaszt
szaharóz
G1P
ADP-glükóz
G1P ADPG SSI SSIISSIII
GBSS
BEIBEII DBE
75% amilopektin
25% amilóz
ADPGPP
ADPGPP
7A, 7D, 4A
Biosynthetic enzymes of starchBiosynthetic enzymes of starch
LokuszLokusz KromoszómaKromoszóma
Wx-A1Wx-A1 7A7A
Wx-D1Wx-D1 7D7D
Wx-B1Wx-B1 4A4AAmilose/amilopectin ratio determines the end use of flour
Aims
Studying diversity of starch propeties in 20 normal winter wheat genotypes (MV)
Starch content (Polarimetric method)
Amilose/amilopectin ratio (Megazyme)
Starch damage (Chopin SDmatic)
Starch viscosity (Rapid Visco Analyser)
Starch content
50
55
60
65
70
75
80
85
90M
V-M
AZ
UR
KA
MV
-SU
VE
GE
S
MV
-RE
GIM
EN
T
BA
NK
UT
I-1
20
1
MV
-KO
DM
ON
MV
-SU
BA
MV
-EM
ES
E
MV
-HO
MB
AR
MV
-MA
RS
AL
L
MV
-MA
GV
AS
MV
-MA
MB
O
MV
-PIR
OS
KA
MV
-MA
GD
AL
EN
A
BE
ZO
ST
AJ
A-1
MV
-MA
TY
O
MV
-PA
LO
TA
S
JU
BIL
EJ
NA
JA
-50
MV
-BE
RE
S
MV
-MA
RT
INA
MV
-PA
LM
A
wa
xy
SD 5% = 7,2
Frequency distribution of amylose content
02468
101214161820222426
20 22 24 26 28 30 32
Amylose [%]
Fre
qu
ency
[%
]
Amylose content of the varieties
0
5
10
15
20
25
30
35
waxy
MV-M
AZURKA
MV-R
EGIM
ENT
MV-P
ALOTAS
MV-H
OM
BAR
MV-M
AMBO
MV-M
AGDALENA
MV-E
MESE
MV-S
UBA
MV-B
ERES
MV-S
UVEGES
MV-K
ODM
ON
MV-M
ARTINA
MV-M
AGVAS
JUBIL
EJNAJA
-50
MV-M
ATYO
MV-P
ALMA
BANKUTI-120
1
MV-M
ARSALL
BEZOST
AJA-1
MV-P
IROSKA
amyl
ose
%
SD 5% = 5,4
40
50
60
70
80
90
100
0 2 4 6 8 10 12 14 16 18 20
Viscosity (RVU)
Time (min)Tem
per
atu
re (
C)
RVA curve
- Water absorption
- Final product quality
- ability to form a gel - sample quality
- ability to withstand heating- factor for processes
RVA pasting profiles of the varieties for flour and starch
RVA-derived pasting properties and starch damage of the varieties
StarchStarch FlourFlourMin.-Min.-Max.Max.
MeanMean SDSD Min.-Max.Min.-Max. MeanMean SDSD
Viscosity at peak [cP]Viscosity at peak [cP] 3236-49323236-4932 40584058 467467 2496-34362496-3436 30323032 293293
Viscosity at hold [cP]Viscosity at hold [cP] 2420-39232420-3923 31673167 427427 1540-18421540-1842 16531653 9090
Viscosity final [cP]Viscosity final [cP] 4706-63104706-6310 55625562 526526 3019-37763019-3776 33533353 212212
Breakdown [cP]Breakdown [cP] 659-1364659-1364 891891 218218 850-1870850-1870 13801380 315315
Pasting Temp. [ºC]Pasting Temp. [ºC] 79.8-87.9579.8-87.95 84.584.5 1.871.87 75.6-86.775.6-86.7 8484 2.92.9
Peak Time [min] Peak Time [min] 9.5-10.59.5-10.5 10.110.1 0.320.32 9-9.69-9.6 9.39.3 0.160.16
Setback [cP]Setback [cP] 1897-27671897-2767 23952395 220220 1479-19731479-1973 17001700 139139
Starch damage (UCDc)Starch damage (UCDc) -- -- -- 10.5-20.510.5-20.5 16.1716.17 2.32.3
Frequency distribution of final viscosity
0
5
10
15
20
25
1900 4700 5000 5300 5600 5900 6200
Final Viscosity (cP)
Fre
quen
cy (%
)
Starch damage
0
5
10
15
20
25
UC
Dc
MV-M
ATYOM
V-REG
IMENT
MV-H
OMBAR
BANKUTI-1
201
MV-M
AZURKAM
V-BERES
BEZOST
AJA-1
MV-P
ALOTAS
JUBIL
EJNAJA
-50
MV-M
AGDALENA
MV-M
ARTINA
MV-S
UBAM
V-KODM
ON
MV-S
UVEGES
MV-M
ARSALL
MV-M
AMBO
MV-E
MESE
MV-P
ALMA
MV-P
IROSKA
MV-M
AGVAS
Water absorption - starch damage
y = 0,4966x + 52,138R2 = 0,1033
15
25
35
45
55
65
75
0 20 40
Farinograph water absorption %
UC
Dc
Hardness-Starch damagey = 0,1002x + 11,138
R2 = 0,6642
0
5
10
15
20
25
0 20 40 60 80 100
Hardness Index
UC
Dc
SD 5% = 2,3
Hierarchical Cluster Analysis for starch
properties
middle
high
low
Starch damage
Summary
• Great variability of starch properties were found in case of winter wheat varieties
• There was a difference in variability of RVA results when flour or starch was measured, as proteins can influence results
• As differences in starch properties can be important for the processing industry, further studies will be carried out
This work is supported by the János Bolyai Fellowship
EU FP-6 Healthgrain project
Thanks for your attention