Artificial neural networks (ANN): prediction of sensory measurements from instrumental data

The objective of this study was to predict by means of Artificial Neural Network (ANN), multilayer perceptrons, the texture attributes of light cheesecurds perceived by trained judges based on instrumental texture measurements. Inputs to the network were the instrumental texture measurements of light cheesecurd (imitative and fundamental parameters). Output variables were the sensory attributes consistency and spreadability. Nine light cheesecurd formulations composed of different combinations of fat and water were evaluated. The measurements obtained by the instrumental and sensory analyses of these formulations constituted the data set used for training and validation of the network. Network training was performed using a back-propagation algorithm. The network architecture selected was composed of 8-3-9-2 neurons in its layers, which quickly and accurately predicted the sensory texture attributes studied, showing a high correlation between the predicted and experimental values for the validation data set and excellent generalization ability, with a validation RMSE of 0.0506.

Okara, a soymilk industry by-product, as a non-meat protein source in reduced fat beef burgers

Okara is a by-product generated during the manufacture of soymilk and tofu. Wet okara was added to beef burgers at 0%, 20%, and 25%. The effects of okara on certain physicochemical, textural, and sensory properties of reduced fat beef burgers were investigated. The beef burgers formulated with okara (104.0-106.0 kcal/100 g) had 60% less calories than commercial beef burgers (268.8 kcal/100 g). The texture profile analysis showed that the addition of wet okara led to a significant increase in hardness (p < 0.05) and a concomitant reduction in the values of chewiness, springiness, and cohesiveness. Lower sensory scores (p < 0.05) of flavour were observed in the beef burgers containing 25% wet okara. However, the sensory evaluation results showed that juiciness, appearance, tenderness, and overall acceptability of beef burgers formulated with okara did not differ statistically from that of the control (0% okara). Wet okara (20%) can be used as a non-meat protein source in the production of reduced-fat beef burgers without changing their sensory quality.

Study of the enthalpy-entropy mechanism from water sorption of orange seeds (C. sinensis cv. Brazilian) for the use of agro-industrial residues as a possible source of vegetable oil production

Orange seeds are a promising agroindustry-waste which can be implemented in the extraction and production of vegetable oil. The relationship between moisture content and water activity provides useful information for the processing and storage of this waste item. The aim of this study was to determine the mechanism of water sorption enthalpy-entropy of orange seeds (C. sinensis cv. Brazilians) according to the moisture content. Therefore, desorption isotherms were determined at five different temperature (30, 40, 50, 60, and 70 ºC) under a wide range of moisture content (0.005-0.057 kg kg-1 d.b.) and water activity (0.02-0.756). Theoretical and empirical models were used for modeling the desorption isotherms. An analytical solution of the Clausius-Clapeyron equation was proposed to compute the isosteric heat of sorption, the differential entropy, and Gibbs free energy using the Oswin model when the effect of temperature on the hygroscopic equilibrium was considered.

Whole and crushed nutlets of chia (Salvia hispanica) from Mexico as a source of functional gums

The objective of this study was to characterize the chemical and functional properties of Mexican chia (Salvia hispanica) gums extracted from defatted whole and crushed nutlets using the Soxhlet and SFE-CO2 methods. Chia gums have interesting chemical and functional properties for the food industry. The oil and gum yields were in the range of 1.98-16.42% and 5.81-12.60%, respectively. The defatting procedure did not affect significantly the oil and gum extraction; the nutlet type (whole or crushed) was the only parameter influencing the yield. The proximate composition and the protein and fiber contents of chia gum were evaluated. Low contents of protein and fiber and high NFE levels were found in whole nutlet gums. The functional properties of chia gum extracted from whole and crushed nutlets with the Soxhlet and SFE-COs methods showed the following ranges of water absorption capacity of 62.64 to 143.66 g/g, water adsorption capacity of 0.69 to 1.35 g/g, and water and oil holding capacity of 100 to 149.28 g/g and19.5 to 40.4 g/g, respectively. The rheological behavior exhibited by the gums was pseudoplastic or shear thinning. From a functional perspective, chia gum is an important food component due its emulsifier and stabilizer potentials.

Brazilian, Chinese, and Indian exports: is the regional market really a source of learning?

In some Latin American countries the exporting activity starts at a regional level, with producers only later venturing into more competitive markets. The implicit risk is that a country might never progress from the regional stage to a more global market. This article compares the experiences of Brazil, China and India. It is shown that Brazil relied on the regional market far more intensely than these Asian countries. There were clear gains accruing to China and India for having exploited more sophisticated markets from the very beginning of their export drive.