Evaluation of in vitro digestion methods and starch structure components as determinants for predicting the glycemic index of rice
Mainstreaming the low glycemic index (GI) trait in breeding programs is constrained by low-throughput and high-cost clinical GI phenotyping. This study aimed to evaluate the potential of starch fine structure components and simulated digestion parameters in predicting GI in rice. Amylose (AM1 and AM...
| Main Authors: | , , , , , |
|---|---|
| Format: | Journal Article |
| Language: | Inglés |
| Published: |
Elsevier
2022
|
| Subjects: | |
| Online Access: | https://hdl.handle.net/10568/126495 |
| _version_ | 1855518745821184000 |
|---|---|
| author | Pautong, Putlih Adzra Añonuevo, Joanne Jerenice Guzmán, Maria Krishna de Sumayao, Rodolfo Henry, Christiani Jeyakumar Sreenivasulu, Nese |
| author_browse | Añonuevo, Joanne Jerenice Guzmán, Maria Krishna de Henry, Christiani Jeyakumar Pautong, Putlih Adzra Sreenivasulu, Nese Sumayao, Rodolfo |
| author_facet | Pautong, Putlih Adzra Añonuevo, Joanne Jerenice Guzmán, Maria Krishna de Sumayao, Rodolfo Henry, Christiani Jeyakumar Sreenivasulu, Nese |
| author_sort | Pautong, Putlih Adzra |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | Mainstreaming the low glycemic index (GI) trait in breeding programs is constrained by low-throughput and high-cost clinical GI phenotyping. This study aimed to evaluate the potential of starch fine structure components and simulated digestion parameters in predicting GI in rice. Amylose (AM1 and AM2; r = −0.94 and r = −0.80, respectively, p < .05) and amylopectin fine structure (MCAP, SCAP, and SCAP1; r = 0.78-0.86, p < .05) measured through size-exclusion chromatography along with resistant starch (r = −0.81, p < .05) in seven (7) rice accessions showed high correlation with in vivo GI. Meanwhile, starch hydrolysis extent (SH) and the corresponding area under the digestion curve (AUC) obtained through in vitro digestion were found to be of higher correlation with GI, even within shorter digestion periods of 5 min or 30 min (r = 0.96, p < .01). These results highlight the potential use of these parameters as predictors of GI, with improved predictive capacity through a multiple regression model. Higher correlations of simulated digestion AUC with GI may be due to its ability to account for the overall food matrix native macro- and micro-structures, gaining an added advantage over SEC method as a predictive tool in studying rice GI variability. Validation in a larger population is an inevitable next step. |
| format | Journal Article |
| id | CGSpace126495 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2022 |
| publishDateRange | 2022 |
| publishDateSort | 2022 |
| publisher | Elsevier |
| publisherStr | Elsevier |
| record_format | dspace |
| spelling | CGSpace1264952025-12-08T10:11:39Z Evaluation of in vitro digestion methods and starch structure components as determinants for predicting the glycemic index of rice Pautong, Putlih Adzra Añonuevo, Joanne Jerenice Guzmán, Maria Krishna de Sumayao, Rodolfo Henry, Christiani Jeyakumar Sreenivasulu, Nese rice glycine max in vitro digestibility starch food science Mainstreaming the low glycemic index (GI) trait in breeding programs is constrained by low-throughput and high-cost clinical GI phenotyping. This study aimed to evaluate the potential of starch fine structure components and simulated digestion parameters in predicting GI in rice. Amylose (AM1 and AM2; r = −0.94 and r = −0.80, respectively, p < .05) and amylopectin fine structure (MCAP, SCAP, and SCAP1; r = 0.78-0.86, p < .05) measured through size-exclusion chromatography along with resistant starch (r = −0.81, p < .05) in seven (7) rice accessions showed high correlation with in vivo GI. Meanwhile, starch hydrolysis extent (SH) and the corresponding area under the digestion curve (AUC) obtained through in vitro digestion were found to be of higher correlation with GI, even within shorter digestion periods of 5 min or 30 min (r = 0.96, p < .01). These results highlight the potential use of these parameters as predictors of GI, with improved predictive capacity through a multiple regression model. Higher correlations of simulated digestion AUC with GI may be due to its ability to account for the overall food matrix native macro- and micro-structures, gaining an added advantage over SEC method as a predictive tool in studying rice GI variability. Validation in a larger population is an inevitable next step. 2022-10 2023-01-03T12:13:37Z 2023-01-03T12:13:37Z Journal Article https://hdl.handle.net/10568/126495 en Open Access application/pdf Elsevier Pautong, Putlih Adzra, Joanne Jerenice Añonuevo, Maria Krishna de Guzman, Rodolfo Sumayao Jr, Christiani Jeyakumar Henry, and Nese Sreenivasulu. "Evaluation of in vitro digestion methods and starch structure components as determinants for predicting the glycemic index of rice." LWT 168 (2022): 113929. |
| spellingShingle | rice glycine max in vitro digestibility starch food science Pautong, Putlih Adzra Añonuevo, Joanne Jerenice Guzmán, Maria Krishna de Sumayao, Rodolfo Henry, Christiani Jeyakumar Sreenivasulu, Nese Evaluation of in vitro digestion methods and starch structure components as determinants for predicting the glycemic index of rice |
| title | Evaluation of in vitro digestion methods and starch structure components as determinants for predicting the glycemic index of rice |
| title_full | Evaluation of in vitro digestion methods and starch structure components as determinants for predicting the glycemic index of rice |
| title_fullStr | Evaluation of in vitro digestion methods and starch structure components as determinants for predicting the glycemic index of rice |
| title_full_unstemmed | Evaluation of in vitro digestion methods and starch structure components as determinants for predicting the glycemic index of rice |
| title_short | Evaluation of in vitro digestion methods and starch structure components as determinants for predicting the glycemic index of rice |
| title_sort | evaluation of in vitro digestion methods and starch structure components as determinants for predicting the glycemic index of rice |
| topic | rice glycine max in vitro digestibility starch food science |
| url | https://hdl.handle.net/10568/126495 |
| work_keys_str_mv | AT pautongputlihadzra evaluationofinvitrodigestionmethodsandstarchstructurecomponentsasdeterminantsforpredictingtheglycemicindexofrice AT anonuevojoannejerenice evaluationofinvitrodigestionmethodsandstarchstructurecomponentsasdeterminantsforpredictingtheglycemicindexofrice AT guzmanmariakrishnade evaluationofinvitrodigestionmethodsandstarchstructurecomponentsasdeterminantsforpredictingtheglycemicindexofrice AT sumayaorodolfo evaluationofinvitrodigestionmethodsandstarchstructurecomponentsasdeterminantsforpredictingtheglycemicindexofrice AT henrychristianijeyakumar evaluationofinvitrodigestionmethodsandstarchstructurecomponentsasdeterminantsforpredictingtheglycemicindexofrice AT sreenivasulunese evaluationofinvitrodigestionmethodsandstarchstructurecomponentsasdeterminantsforpredictingtheglycemicindexofrice |