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ARS Home » Plains Area » Manhattan, Kansas » Center for Grain and Animal Health Research » Grain Quality and Structure Research » Research » Publications at this Location » Publication #178621


item Chung, Okkyung
item Park, Seok Ho
item Bean, Scott
item Xiao, Zhihua - Susan

Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: 6/24/2005
Publication Date: 9/11/2005
Citation: Chung, O.K., Park, S., Bean, S., Xiao, Z.S. 2005. Relationships between cooked alkaline noodle texture and solvent retention capacity (SRS), SDS-sedimentation, mixograph, and protein composition. Abstract No. 227 in: 2005 AACC Annual Meeting Program Book. p.141. Meeting Abstract.

Interpretive Summary:

Technical Abstract: Due to increasing uses of hard winter wheat (HWW) in other than bread products, the HWWQL included Asian alkaline noodle-making in the quality evaluation of breeding program. Since the textural measurement of cooked noodle quality is too labor-intensive for thousands of breeding lines, we investigated relationships of texture profile analysis (TPA) values of cooked alkaline noodles of 34 HWW with quick tests generally used for bread quality estimation, i.e. SRC, SDS-sedimentation (Sed), computerized-mixograph (C-M), and protein content (PC) and composition. Some typical TPA values of cooked noodles included hardness, resilience, adhesiveness, and cohesiveness. The hardness values were negatively correlated with SDS-Sedimentation, 5% lactic acid (LA)-SRC, and insoluble polymeric protein content (IPP) (r=-0.53 to -0.75), and with PC (r=-0.38, n=34, P<0.05). Cohesiveness and resilience were positively correlated with SDS-Sed, 5% LA-SRC, and IPP (r=0.61 to 0.74 and 0.46 to 0.72). Both flour PC and IPP were positively correlated with resilience and adhesiveness (r=0.44 to 0.58). Of many C-M parameters, the height at 8 and 6 min values of C-M showed similar correlations, shown by SDS-Sed. Cooking loss was negatively correlated to resilience and cohesiveness (r=-0.78 and r=-0.80, respectively). Prediction equations were developed by stepwise multiple regression using PC and C-M parameters, resulting in R-square values of 0.67, 0.54, and 0.71 for cooked noodle hardness, resilience, and cohesiveness. The addition of SRC, SDS-Sed, and/or IPP data, the prediction improved the R-square from 0.54 to 0.62 for only resilience, but for others marginally, indicating the potential use of flour PC and CM-height values for predicting cooked noodle textures for the HWW breeding program.