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Starch Chemical Composition and Molecular Structure in Relation to Physicochemical Characteristics and Resistant Starch Content of Four Thai Commercial Rice Cultivars Differing in Pasting Properties.

Wichian SangwongchaiKanitha TananuwongKuakarun KrusongSupidcha NateeMaysaya Thitisaksakul
Published in: Polymers (2023)
Variations in starch pasting properties, considered an alternative potential quality classification parameter for rice starches, are directly controlled by the diverse starch molecular composition and structural features. Here, the starch characteristics of four rice cultivars (i.e., RD57, RD29, KDML105, and RD6) differing in pasting properties were assessed, and their relationship was determined. The results revealed that protein and moisture contents and their crystalline type were similar among the four rice starches. However, their molecular compositions and structures (i.e., reducing sugar and amylose contents, amylopectin branch chain-length distributions, granule size and size distribution, and degree of crystallinity) significantly varied among different genotypes, which resulted in distinct swelling, solubility, gelatinization, retrogradation, and hydrolytic resistance properties. The swelling power and gelatinization enthalpy (∆H) were positively correlated with C-type granule and relative crystallinity, but were negatively correlated with amylose content, B-type granule and median particle size (d(0.5)). Conversely, the water solubility and resistant starch content negatively correlated with C-type granule, but positively correlated with amylose content, B-type granule, and d(0.5). The gelatinization onset temperature (To(g)), and retrogradation concluding temperatures (Tc(r)), enthalpy (∆H(r)), and percentage (R%) were positively impacted by the amount of protein, amylose, and B1 chains (DP 13-24), while they were negatively correlated with short A chains (DP 6-12). Collectively, the starch physicochemical and functional properties of these Thai rice starches are attributed to an interplay between compositional and structural features. These results provide decisive and crucial information on rice cultivars' suitability for consumption as cooked rice and for specific industrial applications.
Keyphrases
  • machine learning
  • lactic acid
  • deep learning
  • single molecule
  • high resolution
  • wastewater treatment
  • quality improvement
  • health information
  • ionic liquid
  • monte carlo