Development of a food product with pea protein (Pisum sativum L.) and carbohydrates for athletes.

Develop a food product that is rich in pea protein (Pisum sativum), obtained through a pea protein concentrate (PPC), and carbohydrates. The research is guided by the need to replace nutrients in athletes during intense physical activity. Pea is a good alternative source of protein because has a high amount of nutrients and is a product cheaper than the protein from an animal source. The PPC from three different brands were obtained and characterized by physical/chemical measures and after that the nutritional value was determinate. The PPC 3 was selected to develop a food product for athletes because has high protein content and favorable sensory characteristics. After the selection, the physical/chemical composition, nutritional value and the viscosity of the product were determinate. Subsequently the product was tested by a sensory analysis for acceptance and purchase intent, being compared to a commercial gel product with whey protein (from animal source) in its composition. The food product made with pea protein shows an acceptability index over 70% for three of the six sensory attributes tested. The result shows that the product has a good acceptance between the panelists. However the intention of purchase has generated doubt between 50% of the panelists, showing that there are parameters to be enhanced to improve the acceptance of the product. The use of pea to develop a food product for athletes is a good alternative to protein from an animal source. The pea protein is a source cheaper and has high amounts of nutrients in its composition.Desenvolvimento de um produto alimentício com consistência em gel para atletas que seja rico em proteína de ervilha (Pisum sativum), obtida através de um concentrado proteico de ervilha (CPE) e carboidratos. O estudo está pautado na necessidade de reposição de nutrientes em atletas submetidos a esforço físico vigoroso e de longa duração. A ervilha mostrou-se uma fonte de proteína alternativa a proteína animal, por ser rica em nutrientes e ser um produto de menor custo para produção. Foram obtidos 3 CPE de diferentes marcas e caracterizados quanto a composição centesimal e parâmetros físico-químicos. O CPE 3 mostrou-se mais adequado para o desenvolvimento de um produto alimentício para atletas, por ter alta concentração de proteína e características sensoriais favoráveis a obtenção de um produto de qualidade. O produto alimentício desenvolvido foi caracterizado quanto à composição centesimal e valor calórico e quanto à viscosidade aparente, demonstrando a característica pseudoplástica esperada para um gel verdadeiro. Posteriormente o produto foi submetido à análise sensorial para aceitação e intenção de compra, sendo comparado a um produto em gel existente no mercado com proteína de origem animal em sua composição. O produto alimentício com proteína de ervilha apresentou índice de aceitabilidade maior que 70% para 3 dos 6 atributos sensoriais testados, sendo aceitação global o mais importante, indicando que o produto foi bem-aceito pelos provadores. No entanto, a intenção de compra ainda gerou dúvida entre 50% dos provadores, mostrando que existem parâmetros a serem aprimorados para melhorar a aceitação. A utilização de ervilha para o desenvolvimento de um produto alimentício para atletas é viável e inovador, pois a ervilha é uma fonte proteica de fácil obtenção e baixo custo e seu uso pode beneficiar a indústria alimentícia

Basal Metabolic Rate of Adolescent Modern Pentathlon Athletes: Agreement between Indirect Calorimetry and Predictive Equations and the Correlation with Body Parameters

<div><p>Purpose</p><p>The accurate estimative of energy needs is crucial for an optimal physical performance among athletes and the basal metabolic rate (BMR) equations often are not well adjusted for adolescent athletes requiring the use of specific methods, such as the golden standard indirect calorimetry (IC). Therefore, we had the aim to analyse the agreement between the BMR of adolescents pentathletes measured by IC and estimated by commonly used predictive equations.</p><p>Methods</p><p>Twenty-eight athletes (17 males and 11 females) were evaluated for BMR, using IC and the predictive equations Harris and Benedict (HB), Cunningham (CUN), Henry and Rees (HR) and FAO/WHO/UNU (FAO). Body composition was obtained using DXA and sexual maturity data were retrieved through validated questionnaires. The correlations among anthropometric variables an IC were analysed by T-student test and ICC, while the agreement between IC and the predictive equations was analysed according to Bland and Altman and by survival-agreement plotting.</p><p>Results</p><p>The whole sample average BMR measured by IC was significantly different from the estimated by FAO (p<0.05). Adjusting data by gender FAO and HR equations were statistically different from IC (p <0.05) among males, while female differed only for the HR equation (p <0.05).</p><p>Conclusion</p><p>The FAO equation underestimated athletes’ BMR when compared with IC (T Test). When compared to the golden standard IC, using Bland and Altman, ICC and Survival-Agreement, the equations underestimated the energy needs of adolescent pentathlon athletes up to 300kcal/day. Therefore, they should be used with caution when estimating individual energy requirements in such populations.</p></div

Bland and Altman scatter plots for male and female.

<p>(A) FAO; (B) Harris and Benedict; (C) Henry and Rees and (D) Cunningham. The dashed lines represent the mean bias and 95% limits of agreement of the raw data. Filled dots represent males and opened dots represent female individuals.</p

Survival-agreement plot for indirect calorimetry and predictive equations.

<p>Survival-agreement plot for indirect calorimetry and predictive equations.</p

Basal metabolic rate (Kcal.day-1) of the studied sample, measured (IC) and estimated by the equations (FAO, HB, HR and CUN), (n = 28).

<p>Basal metabolic rate (Kcal.day-1) of the studied sample, measured (IC) and estimated by the equations (FAO, HB, HR and CUN), (n = 28).</p

Main Characteristics of Modern Pentathlon athletes, according to the gender (n = 28); X±SD.

<p>Main Characteristics of Modern Pentathlon athletes, according to the gender (n = 28); X±SD.</p

Predictive equations given in their original unit (kcal/day).

<p>BM: Body Mass in kilogram (Kg); H: Height in centimeters (cm); A: Age in years; FFM: Free Fat Mass in kilogram (Kg)</p><p>Predictive equations given in their original unit (kcal/day).</p