New alternatives from sustainable sources to wheat in bakery foods: Science, technology, and challenges.

Ongoing research in the food industry is striving to replace wheat flour with new alternatives from sustainable sources to overcome the disease burden in the existing population. Celiac disease, wheat allergy, gluten sensitivity, or non-celiac gluten sensitivity are some common disorders associated with gluten present in wheat. These scientific findings are crucial to finding appropriate alternatives in introducing new ingredients supporting the consumer's requirements. Among the alternatives, amaranth, barley, coconut, chestnut, maize, millet, teff, oat, rye, sorghum, soy, rice flour, and legumes could be considered appropriate due to their chemical composition, bioactive profile, and alternatives utilization in the baking industry. Furthermore, the enrichment of these alternatives with proper ingredients is considered effective. Literature demonstrated that the flours from these alternative sources significantly enhanced the physicochemical, pasting, and rheological properties of the doughs. These flours boost a significant reduction in gluten proteins associated with food intolerance, in comparison with wheat highlighting a visible market opportunity with nutritional and organoleptic benefits for food producers. PRACTICAL APPLICATIONS: New alternatives from sustainable sources to wheat in bakery foods as an approach that affects human health. Alternatives from sustainable sources are important source of nutrients and bioactive compounds. Alternatives from sustainable sources are rising due to nutritional and consumer demand in bakery industry. New alternatives from sustainable sources improve physicochemical, pasting, and rheological properties of dough. Non-wheat-based foods from non-traditional grains have a potential to increase consumer market acceptance.

Carbohydrate Taste Is Associated with Food Intake and Body Mass in Healthy Australian Adults.

BACKGROUND: The taste of carbohydrates may drive their intake. Sensitivity to carbohydrate taste varies among individuals, thus, it is important to understand how differences in sensitivity influence eating behaviour and body mass. OBJECTIVE: The aims of this study were to assess associations among carbohydrate taste sensitivity, habitual and acute food intake, and body mass; as well as assess the reliability of the carbohydrate detection threshold (DT) test within and across days. METHODS: Carbohydrate DT was assessed six times across three sessions in 36 healthy adult participants (22 female) using a three-alternate forced choice methodology. Moreover, 24 h diet records were completed on the days prior to testing sessions, and food intake at a buffet lunch was collected following each session. Anthropometry was also measured. Linear mixed regression models were fitted. RESULTS: The DT test required at least three measures within a given day for good reliability (ICC = 0.76), but a single measure had good reliability when compared at the same time across days (ICC = 0.54-0.86). Carbohydrate DT was associated with BMI (kg/m2: ß = -0.38, p = 0.014), habitual carbohydrate intake (g: ß = -41.8, p = 0.003) and energy intake (kJ: ß = -1068, p = 0.019) from the 24-h diet records, as well as acute intake of a buffet lunch (food weight (g): ß = -76.1, p = 0.008). CONCLUSIONS: This suggests that individuals who are more sensitive to carbohydrate are more likely to consume greater quantities of carbohydrates and energy, resulting in a greater body mass.

Association between food liking and the dietary quality in Australian young adults.

BACKGROUND AND OBJECTIVES: An individual's liking for food maybe associated with food consumption. This study investigates the association between food liking and dietary quality in Australian young adults. METHODS AND STUDY DESIGN: Food liking and food frequency data were collected via an online Food Liking Questionnaire (FLQ) and Food Frequency Questionnaire (FFQ). Food liking scores were calculated for groupings of foods. FFQ Food intake data was used to calculate diet quality using a 13 item Dietary Guideline Index (DGI). The relationship between food liking and DGI was assessed using linear regression models and the difference was assessed using an independent sample t-test and One-way ANOVA. RESULTS: Data were available from n=2,535 participants (BMI=24 (SD 3.74), age=21.9 (SD 5.05) years, female=77.1%). Liking for grains, vegetables, fruits, dairy, plant-based protein, was weakly positively associated with diet quality. Liking for animal-based protein, fat and oil, sweet food, and salty food, was weakly negatively associated with diet quality. Liking for grains, vegetables, fruits, dairy, plant-based protein and healthy foods increased across increasing DGI tertiles, and liking for animalbased protein, fat and oil, sweet food, salty food and discretionary foods decreased across increasing DGI tertiles. CONCLUSIONS: The results were logical with increased liking for healthy or discretionary foods linked with increased consumption of those foods. The results reinforce the strategy to introduce a variety of healthy food groups early in life to initiate flavour-nutrient learning and increase liking for healthy foods.

The relationship between culture, food liking, and body mass index in Australian and Thai young adults.

BACKGROUND AND OBJECTIVES: An individual's liking of food may be associated with Body Mass Index (BMI) due to its subsequent impact on food consumption. This study investigates the association between food liking and BMI in young adults from Australia and Thailand. METHODS AND STUDY DESIGN: Food liking data were collected via a validated online Food Liking Questionnaire (FLQ). Food liking scores were calculated for overall liking of groupings of foods: grains, vegetables, fruits, dairy, animal protein, plant-based protein, fat and oil, sweet food, salty food, and alcohol. The relationship between food liking and BMI (calculated from self-reported height and weight) was assessed using linear regression models including country and gender, and mean differences were assessed using independent sample t-test. RESULTS: Data were available from n=4,173 participants (BMI=22.25 (SD 4.18), age=20.6 (SD 4.22) years, female=71.6%, Thai=52.5%). There were significant differences of food liking between countries for all of food groups (p<0.01) except for animal-based protein and plantbased protein liking. BMI was positively, but weakly, associated with liking of animal-based protein (ß=0.20 [0.12, 0.28], p<0.001), and alcohol (ß=0.08 [0.02, 0.13], p<0.01) and negatively associated with plant-based protein (ß=-0.09 [-0.18, -0.01], p<0.05). There was significant difference of food liking between weight status for all of food groups. CONCLUSIONS: This study supports only minor associations between food liking and BMI, but cultural and gender variation in liking was evident.

Assessing Food Liking: Comparison of Food Liking Questionnaires and Direct Food Tasting in Two Cultures.

Food liking can be directly measured in specialised sensory testing facilities; however, this method is not feasible for large population samples. The aim of the study was to compare a Food Liking Questionnaire (FLQ) against lab-based sensory testing in two countries. The study was conducted with 70 Australian and Thai participants (35 Australian, 35 Thai, mean (SD) age 19 (3.01) years, 51% men). Participants completed a FLQ (consisting of 73 food items Australia, 89 Thai) and then, after tasting the food, rated their liking of a selection of 10 commercially available food items using a nine-point hedonic scale. Both tasks were completed on the same day and were repeated one week later. The reliability of and a comparison between methods was determined using Intra-Class Correlation Coefficients (ICC), and the difference was assessed using an independent sample t-test. The results indicate that the test-retest reliability of FLQ and the laboratory-based liking assessment range was moderate (0.40⁻0.59) to excellent (0.75⁻1.00). There were significant differences for the FLQ and the laboratory-based liking assessment between countries for three food items: soft drink, instant vegetable soup, and broccoli (p < 0.01). However, the data produced from the FLQ reflects the laboratory-based liking assessment. Therefore, it provides representative liking data in large population-based studies including cross-cultural studies.