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Functional Properties and Predicted Glycemic Index of Gluten Free Cereal, Pseudocereal and Legume

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Functional Properties and Predicted Glycemic Index of Gluten Free Cereal, Pseudocereal and Legume View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by AIR Universita degli studi di Milano 1 Functional properties and predicted glycemic index of gluten free cereal, pseudocereal and legume 2 flours 3 Maria Di Cairanoa*, Nicola Condellia, Marisa Carmela Carusoa, Alessandra Martib, Nazarena Celaa, 4 Fernanda Galgano a 5 *corresponding author: Maria Di Cairano - [email protected] 6 aSchool of Agricultural, Forestry, Food and Environmental Sciences (SAFE), University of Basilicata, 7 Viale Dell’Ateneo Lucano 10, 85100, Potenza, Italy 8 b Department of Food, Environmental, and Nutritional Sciences (DeFENS), Università degli Studi di 9 Milano, Via Celoria, 2, 20133 Milan, Italy 10 email addresses: [email protected], [email protected], [email protected], 11 [email protected], [email protected] 12 13 keywords: flours, gluten free, glycemic index, pasting properties, functional properties 14 Declarations of interest: none 1 15 Abstract 16 Most of gluten free (GF) bakery products available on the market are made by a restricted number 17 of grains. Flours and starches from rice and maize are mainly used. For this reason, people 18 affected by celiac disease frequently suffer of nutritional deficiencies and have high intake of some 19 nutrients. The use of a wider range of GF flours, rich in nutrients and phytochemicals, may 20 improve the nutritional quality of GF products. 21 This study aimed at the characterization of twelve GF flours obtained from cereals, pseudocereals 22 and legumes for what concerns their functional properties, starch composition, phenolic and 23 flavonoid content, and their effect on glycemic index (GI), that was estimated in vitro. In 24 particular, starch composition had an influence on predicted glycemic index (pGI). pGI and 25 damaged starch were positively related, whereas flavonoid, amylose and resistant starch (RS) 26 contents were negatively related to pGI. In general, for all the parameters considered, cereals, 27 except for rice flour, showed similar behavior, so as legumes. On the contrary, pseudocereals 28 presented quite different characteristics between each other, due to their different botanical 29 origin. The knowledge of starch composition, its relationship with GI, and functional properties 30 could contribute to the selection of flours for healthier GF bakery products. 31 1. Introduction 32 Around 1% of world population is affected by celiac disease (Fasano and Catassi 2012) and 5% is 33 estimated to be affected by a gluten related disorder (Elli et al. 2015). To the date, the only cure 34 available is the adherence to a strict gluten-free (GF) diet. Besides people who have pathologies 35 related to gluten ingestion, a part of consumers decides to follow a GF diet as lifestyle choice. 36 Hence, a growth of GF market was recorded in recent years and is still expected in years to come. 37 The offer of GF bakery products, such as biscuits, cakes and bread substitutes, is often not very 38 healthy, due to the low protein and high fat content. Many consumers have a rising awareness 2 39 towards the consumption of healthier products. Thus, there is the need for researchers and 40 industries to answer consumers’ demand. Many studies showed that it is possible to offer 41 healthier GF bakery (Pellegrini and Agostoni 2015; Stantiall and Serventi 2017). 42 GF products are mainly based on refined flour or starches (Gallagher, Gormley, and Arendt 43 2004). In example, it has been reported that the Brazilian GF products are mostly made with rice 44 flour and cassava fecula and most of breads are made with refined rice flour and starches (do 45 Nascimento et al. 2013; Santos, Aguiar, and Capriles 2018). GF biscuits present on the Italian 46 market are mainly made of rice and maize flours and starches (Di Cairano et al. 2018). These flours 47 and starches have a neutral taste, can be employed in a variety of formulations but they lack in 48 vitamins, minerals and fibers and they may contribute to a raise of the glycemic index (GI) because 49 of their richness in rapidly digestible starch. Indeed, it has been seen that GF products generally 50 tend to have a higher GI than their gluten containing counterparts (Vici et al. 2016). 51 The selection and the employment of more nutrient dense flours can improve the quality 52 of GF products. Different authors studied the use of cereal, pseudocereal and legume flours in the 53 production of GF pasta and baked products obtaining a positive effect on product quality without 54 affecting sensory properties (Campo et al. 2016; Sharma, Saxena, and Riar 2016). 55 While reformulating baked products with the aim of enhancing their nutritional profile, the 56 functional properties of the flours cannot be neglecting in order to assure the proper behavior 57 during the production and to keep the desired texture/structure in the final product. The 58 knowledge of functional properties of flours, interaction between GI and starch composition and 59 their richness in phytochemicals could help the selection of raw materials for production of 60 healthier GF products. To our knowledge, few studies report this information on such different 61 number of flours. In particular, functional properties, pasting properties, starch fractions and 62 phenolic and flavonoid content were studied. In this context, the aim of this study was to compare 3 63 the nutritional and functional properties of twelve different GF cereal, pseudocereals and legume 64 flours. Moreover, correlations between flour characteristics and pGI were explored to understand 65 the potential impact of these grains of starch quality. 66 2. Material and methods 67 2.1. Flour samples 68 Commercial cereal, pseudocereal and legume flours were analyzed. Whole brown millet (Molino 69 Filippini, Italy), whole oat flakes (THERMAR 63, Lameri SpA, Italy), rice (CareRice TQ, Caremoli SpA, 70 Italy), sorghum (Molino Favero, Italy) and white teff (Molino Favero) flours were analyzed for 71 cereal group; amaranth (Molino Favero), buckwheat (Careflour Buckwheat F, Caremoli) and 72 quinoa (CareFlour Quinoa, Caremoli) flours were studied for pseudocereal group and chickpea 73 (Terre di Altamura, Italy), green lentil (Terre di Altamura, Italy), red lentil (Cereal Veneta, Italy) and 74 yellow pea (CareFlour YP yellow pea CF, Caremoli SpA) flour flours were analyzed for legume 75 group. All analysis were made on raw flours; flours were stored in sealed plastic bags at ambient 76 temperature and in the dark (20°C). 77 2.2. Functional properties 78 2.2.1. Water absorption capacity, oil absorption capacity and water solubility index 79 Water and oil absorption capacity (WAC and OAC) were determined according to Kaur et al. 80 (2015). One gram of flour was mixed with 10 ml of distilled water or refined soybean oil and kept 81 at 20 °C for 30 minutes. Then, the samples were centrifuged at 2000g for 10 minute and the 82 supernatant decanted. WAC and OAC are the weight of the sample after removal of the 83 supernatant per unit weight of original dry solids. 84 To determine water solubility index (WSI), the supernatant of WAC was decanted into an 85 evaporating dish and dried at 105°C until constant weight (Chauhan, Saxena, and Singh 2015). WSI 4 86 is the weight of dry solids expressed as a percentage of the original weight of sample. 87 Measurements were taken in triplicate. 88 2.2.2. Bulk density 89 Bulk density (BD) was determined as reported in Chauhan et al. (2015). Ten grams of flour were 90 placed in a 25 ml graduated cylinder which was gently tapped ten times from a height of 7-8 cm. 91 The final volume of the flour was measured and bulk density was expressed as g/ml. 92 Measurements were taken in triplicate. 93 2.3. Pasting properties 94 Pasting properties of the flours were determined using a Micro Visco-Amylo-Graph, MVAG, 95 (Brabender GmbH., Duisburg, Germany) according to the procedure of Marengo et al. (2017). 96 Twelve grams of flour were dispersed in 100 ml of distilled water, scaling both sample and water 97 weight on a 14% flour moisture basis. The suspensions were subjected to the following 98 temperature profile: heating from 30 up to 95°C, holding at 95°C for 20 minutes and cooling from 99 95 to 30°C with a heat/cooling rate of 3°C/min. The following parameters were considered: 100 beginning of gelatinization (BG) (temperature at which an initial increase in viscosity occurs), 101 maximum viscosity (MAXV) (MAXV reached during the analysis), peak temperature (PT) 102 (temperature at the MAXV), breakdown (BKD) (difference between the MAXV and the viscosity 103 reached at the end of the holding period) and setback (SB) (difference between the final viscosity 104 at 30°C and the viscosity reached at the end of the holding period). BG and PT were expressed in 105 °C, MAXV, BKD and SB were expressed in Brabender Units. Measurements were taken in duplicate. 5 106 2.4. Starch characterization 107 2.4.1. Resistant starch and total starch content 108 RS and total starch (TS) were determined according to AACC method 32-40.01 using the kit, K- 109 RSTAR (Megazyme International Ireland Ltd., Wicklow, Ireland). Measurements were taken in 110 duplicate. 111 2.4.2. Damaged starch 112 Damaged starch (SDAM) content was evaluated according to AACC Method 76-31.01 using K- 113 SDAM assay kit (Megazyme). Measurements were taken in duplicate. 114 2.4.3. Amylose/amylopectin content 115 Amylose content was measured by using K-AMYL assay kit (Megazyme). In brief, starch samples 116 were dispersed by heating in dimethyl sulfoxide and then amylopectin was precipitated with Con A 117 solution.
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