Optimizing the Nutritional Composition of a Meat Substitute Intended to Replace Meat in Observed Diet Results in Marked Improvement of the Diet Quality of French Adults

Objectives While consumers’ demand is growing, meat substitutes have much varied composition, raising questions about their nutritional interest. We aimed to identify the composition of a meat substitute that would best improve diet quality, and analyze the impact on nutrient adequacy. Methods We aimed at maximizing the overall diet quality of an average individual representing the nutrient intake of the French adult population (INCA3, n = 1125) by modeling the composition of a meat substitute intended to replace meat, using non-linear optimization (using SAS, proc optmodel). The diet quality was assessed using the PANDiet scoring system, which assesses the probability of adequate nutrient intake. Nutritional constraints were applied in order to not increase the risk of overt deficiency for 12 nutrients. A list of 159 ingredients was used to compose the meat replacer and technological constraints were defined so as to take into account the feasibility of the formulation. The impacts on diet quality of the modelled meat substitute were analyzed and compared with those of 43 meat substitutes on the market. Results The optimized meat substitute was composed of 13 ingredients (such as coco bean, yellow sweet pepper, rapeseed oil, dried shiitake mushroom, wheat bran and thyme) and this formulation proved to be relatively robust to variations in the model constraints, as shown by a sensitivity analysis. Meat substitution with this optimized meat substitute largely increased the PANDiet, by 5.5 points above its initial value before substitution (73.7/100). In particular, it led to better adequacies for nutrients that are currently insufficiently consumed (e.g., alpha-linolenic acid, fiber, linoleic acid). It also allowed to compensate for loss of some nutrients partly provided by meat (e.g., vitamin B6, potassium and, to a certain extent, bioavailable iron), but was not sufficient to compensate for bioavailable zinc and vitamin B12. The optimized meat substitute proved to be dramatically more nutritionally efficient than the available meat substitutes, whose individual impact on the PANDiet ranged from −3.1 to +1.5 points. Conclusions We proved that it is possible to select appropriate ingredients resulting in a meat substitute that could be a fairly good nutritional lever when substituting meat. Funding Sources Partly funded by a PhD fellowship from Terres Univia.

The Feasibility of Using Near Infrared Spectroscopy for Rapid Discrimination of Aged Shiitake Mushroom (Lentinula edodes) after Long-Term Storage

Long-term storage can largely degrade the taste and quality of dried shiitake mushroom (Lentinula edodes). This paper aimed at developing a rapid method for discrimination of the regular and aged shiitake by near infrared (NIR) spectroscopic analysis and chemometrics. Regular (n=197) and aged (n=133) samples of shiitake were collected from six main producing areas in two successive years (2013 and 2014). NIR reflectance spectra (4000–12000 cm−1) were measured with finely ground powders. Different data preprocessing method including smoothing, taking second-order derivatives (D2), and standard normal variate (SNV) were investigated to reduce the unwanted spectral variations. Partial least squares discriminant analysis (PLSDA) and least squares support vector machine (LS-SVM) were used to develop classification models. The results indicate that SNV and D2 can largely enhance the classification accuracy. The best sensitivity, specificity, and accuracy of classification were 0.967, 0.953, and 0.961 obtained by SNV-LS-SVM and 0.933, 0.930, and 0.932 obtained by SNV-PLSDA, respectively. Moreover, the low model complexity and the high accuracy in predicting objects produced in different years demonstrate that the classification models had a good generalization performance.