In vitro Starch Digestibility and Estimated Glycemic Index of Indonesian Cowpea Starch (Vigna unguiculata)

Effect of processing and variety on starch digestibility and glycemic index of popular foods made from cassava (Manihot esculenta)

In Sub-Saharan Africa (SSA), the prevalence of diabetes mellitus (DM) is rapidly increasing even in populations with significant undernutrition. The role of energy dense staple crops such as cassava is under query and not yet well understood. In this study, varieties of cassava, made into popular SSA products (fufu and gari dough) were studied for their resistant starch (RS), rapidly digestible starch (RDS) and glycemic index (GI). While the glycemic properties of the varieties studied did not differ significantly, processing any variety into either fufu or gari distinctly impacted RS, RDS and predicted GI (pGI) differently. Specifically, fufu had highest range of RS (1.1-2.1 g/100 g) while gari dough had highest RDS (1.1-1.4 g/100 g) and pGI (54-67). The results from this probe imply that fufu, when consumed, will release glucose in a slower manner than gari, therefore may be better suited in the dietary prevention and management of DM.

Evaluation of Various Starchy Foods: A Systematic Review and Meta-Analysis on Chemical Properties Affecting the Glycemic Index Values Based on In Vitro and In Vivo Experiments

The chemical properties that serve as major determinants for the glycemic index (GI) of starchy food and recommended low-GI, carbohydrate-based foods have remained enigmatic. This present work performed a systematic assessment of linkages between chemical properties of foods and GI, and selected low-GI starchy foods. The data were sourced from literature published in various scientific journals. In total, 57 relevant studies and 936 data points were integrated into a database. Both in vitro and in vivo studies on GI values were included. The database was subsequently subjected to a meta-analysis. Meta-analysis from in vitro studies revealed that the two significant factors responsible for the GI of starchy foods were resistant starch and phenolic content (respectively, standardized mean difference (SMD): -2.52, 95% confidence interval (95%CI): -3.29 to -1.75, p (p-value) < 0.001; SMD: -0.72, 95%CI: -1.26 to -0.17, p = 0.005), while the lowest-GI crop type was legumes. Subgroup analysis restricted to the crop species with significant low GI found two crops, i.e., sorghum (SMD: -0.69, 95%CI: -2.33 to 0.96, p < 0.001) and red kidney bean (SMD: -0.39, 95%CI: -2.37 to 1.59, p = 0.001). Meta-analysis from in vivo studies revealed that the two significant factors responsible for the GI of starchy foods were flavonoid and phenolic content (respectively, SMD: -0.67, 95%CI: -0.87 to -0.47, p < 0.001; SMD: -0.63, 95%CI: -1.15 to -0.11, p = 0.009), while the lowest-GI crop type was fruit (banana). In conclusion, resistant starch and phenolic content may have a desirable impact on the GI of starchy food, while sorghum and red kidney bean are found to have low GI.

Bridging the food security gap: an information-led approach to connect dietary nutrition, food composition and crop production

BACKGROUND

Food security is recognized as a major global challenge, yet human food-chain systems are inherently not geared towards nutrition, with decisions on crop and cultivar choice not informed by dietary composition. Currently, food compositional tables and databases (FCT/FCDB) are the primary information sources for decisions relating to dietary intake. However, these only present single mean values representing major components. Establishment of a systematic controlled vocabulary to fill this gap requires representation of a more complex set of semantic relationships between terms used to describe nutritional composition and dietary function.

RESULTS

We carried out a survey of 11 FCT/FCDB and 177 peer-reviewed papers describing variation in nutritional composition and dietary function for food crops to identify a comprehensive set of terms to construct a controlled vocabulary. We used this information to generate a Crop Dietary Nutrition Data Framework (CDN-DF), which incorporates controlled vocabularies systematically organized into major classes representing nutritional components and dietary functions. We demonstrate the value of the CDN-DF for comparison of equivalent components between crop species or cultivars, for identifying data gaps and potential for formal meta-analysis. The CDN-DF also enabled us to explore relationships between nutritional components and the functional attributes of food.

CONCLUSION

We have generated a structured crop dietary nutrition data framework, which is generally applicable to the collation and comparison of data relevant to crop researchers, breeders, and other stakeholders, and will facilitate dialogue with nutritionists. It is currently guiding the establishment of a more robust formal ontology. © 2019 Society of Chemical Industry.