Effect of baking and fermentation on the stable carbon and nitrogen isotope ratios of grain-based food

Simultaneously Verifying the Original Region of Green and Roasted Coffee Beans by Stable Isotopes and Elements Combined with Random Forest

Simultaneously verifying the original region of green and roasted coffee beans is very important for protecting legal interests of the stakeholder according to the chemical analyzing method. 131 green coffee bean samples are collected from six different original regions and pretreated with three degrees (green, middle, and dark roasted); five stable isotope ratios (δ13C, δ14N, δ18O, δ2H, and δ32S) and twelve elemental contents (Al, Cr, Ni, Zn, Ba, Cu, Na, Mn, Fe, Ca, K, and Mg) of green, middle, and dark roasted coffee bean samples (131×3) were analyzed. Fractionation of stable isotopes and variation of elemental contents were evaluated, only isotope hydrogen (2H) significantly fractionated, and elemental concentrations increased with a certain rate during the roasting process. One-way analysis of variance (ANOVA) was used to compare the stable isotope ratios and elemental concentrations of all coffee bean samples from six different original regions. Random forest (RF) was employed to build a discriminating model for simultaneously verifying the original regions of green and roasted coffee bean samples; this model provided 100% accuracy. Inclusion of this mathematical model for simultaneously verifying the original region of green and roasted coffee beans had powerful distinguishing capability and which will not be influenced by fractionation of hydrogen (2H) and variation of element contents during the roasted process.

Potential application of light element stable isotope ratio in crude fiber for geographical origin verification of raw and cooked kabocha pumpkin (Cucurbita maxima)

In this study, we investigated the possibility of the geographical origin discrimination between Japanese and Mexican kabocha pumpkin using δ¹³C and δ¹⁸O in lyophilized raw flesh. Kabocha harvested in Hokkaido, the major kabocha production area in Japan, could be discriminated against not only that grown in Mexico but also that in New Zealand. However, seasoning after cooking or processing affected the δ¹³C and the δ¹⁸O values. Crude fiber extraction eliminated the effect of seasonings and enabled the adoption of the δ¹³C and δ¹⁸O values in crude fiber for the geographical origin verification of kabocha even after cooking and processing. The usage of δ¹³C and the δ¹⁸O in crude fiber would extend the application possibilities of stable isotope analysis in the geographical origin determination of various cooked and processed vegetables and fruits as well as raw materials.

Complementary use of 1H NMR and multi-element IRMS in association with chemometrics enables effective origin analysis of cocoa beans (Theobroma cacao L.)

Within the cocoa market (Theobroma cacao L.), quality and prices are often determined by geographical origin, making traceability indispensable. Therefore, to investigate possibilities of tracing by analytical methods, 48 carefully selected cocoa samples from 20 countries have been profiled using a combination of stable isotope-ratio mass spectrometry (IRMS) and proton nuclear magnetic resonance (¹H NMR). Chemometric analysis of combined data sets from both, stable isotope data (δ¹³C, δ¹⁵N, δ¹⁸O, δ²H, %C, %N, %O, %H) and ¹H NMR fingerprints, achieved good separation with increased classification rates compared to classification with data of the isolated methods. IRMS contributed primarily to discrimination between countries, while ¹H NMR significantly contributed to separation of varieties, but also the regions within individual countries. This study thus demonstrates that combination of two analytical methods is an effective tool to enhance both, accuracy and precision, in authenticity testing of cocoa.

Carbon and nitrogen isotopic composition of commercial dog food in Brazil

BACKGROUND

Brazil is a low- to medium-income country and has the second largest pet food market in the world with 8% of world pet food consumption. The lowest-income social class spends around 17% of their domestic budget on pet food and other items related to pets. Consumers are frequently misled by advertising as there is no precise information about the main sources of protein, carbohydrates and fat in the labels, and the Brazilian pet food industry can legally claim that their products contain certain items like salmon or beef even if they use just a flavoring compound.

METHODS

The stable isotope methodology compares the stable isotope ratios of carbon (13C/12C) and nitrogen (15N/14N) between source and product. The 13C/12C ratio of a specific product (e.g., dog food) reveals the proportions of C4 (maize) and C3 (soybean, rice and wheat) plants in that product and the 15N/14N ratio reveals the proportion of the compounds derived from animals. With this isotopic data, we used MixSIAR, a Bayesian stable isotope-mixing model, to estimate the proportion of maize, grains, poultry and beef in dog food.

RESULTS

The δ13C values of dry dog food ranged from -24.2‰ to -12.8‰, with an average (± standard-deviation) of -17.1‰ ± 2.8‰. The δ13C values of wet pet food ranged from -25.4‰ to -16.9‰, with an average (± standard-deviation) of -21.2‰ ± 2.4‰, which was significantly lower (p < 0.01). The δ15N values of the dry and wet food ranged from 1.7‰ to 4.2‰, and from 0.5‰ to 5.5‰, respectively. The average δ15N values of dry food (2.9‰ ± 0.5‰) was not higher than the wet food (2.6‰ ± 1.3‰) (p > 0.01). The output of the MixSIAR showed a low proportion of bovine products in dry dog food samples. On the other hand, poultry was obviously the dominant ingredient present in most of the samples. Maize was the second dominant ingredient. Wet and dry dog food showed similar isotopic analysis results. The only difference was a lower proportion of maize and higher proportion of grains in wet dog food.

DISCUSSION

The main finding is that dog food in Brazil is mostly made of approximately 60% (ranging from 32% to 86%) animal-based and 40% (ranging from 14% to 67%) plant-based products. Poultry and maize are the main ingredients. Poultry is added as a by-product or meal, which avoids competition between dogs and humans for meat products, while they can compete for maize. On the other hand, a large proportion of plant-based products in dog food decreases the energy and environmental footprint, since plant-based food products tend to be less harmful compared to animal-based products. Labels can mislead consumers by showing pictures of items that are not necessarily part of the product composition and by not showing the detailed information on the proportion of each ingredient. This information would allow customers to make their own choices considering their pet's nutrition, the competition between animals and humans for resources and environmental sustainability.

Geographical traceability of wheat and its products using multielement light stable isotopes coupled with chemometrics

The present study was aimed to investigate the variation of stable isotopic ratios of carbon, nitrogen, hydrogen, and oxygen in wheat kernel along with different processed fractions from three geographical origins across 5 years using isotope ratio mass spectrometry (IRMS). Multiway ANOVA revealed significant differences among region, harvest year, processing, and their interactions for all isotopes. The region contributed the major variability in the δ¹³ C ‰, δ² H ‰, δ¹⁵ N ‰, and δ¹⁸ O‰ values of wheat. Variation of δ¹³ C ‰, δ¹⁵ N ‰, and δ¹⁸ O ‰ between wheat whole kernel and its products (break, reduction, noodles, and cooked noodles) were ˂0.7‰, and no significant difference was observed, suggesting the reliability of these isotope fingerprints in geographical traceability of wheat-processed fractions and foods. A significant influence of wheat processing was observed for δ² H values. By applying linear discriminant analysis (LDA) to the whole dataset, the generated model correctly classified over 91% of the samples according to the geographical origin. The application of these parameters will assist in the development of an analytical control procedure that can be utilized to control the mislabeling regarding geographical origin of wheat kernel and its products.

Multi-isotopic signatures of organic and conventional Italian pasta along the production chain

The variability of stable isotope ratios (δ(2) H, δ(13) C, δ(15) N, δ(18) O and δ(34) S) along the production chain of pasta (durum wheat, flour and pasta) produced by using both conventional and organic farming systems in four Italian regions in 2 years was investigated. The aim was to evaluate if and how the farming system and geographical origin affect stable isotope ratios determined along the production chain. Irrespective of the processing technology, 65% of the samples were correctly classified according to the farming system and 98% were correctly classified regarding the geographical region. When considering both farming system and geographical region simultaneously, 80% of the samples were correctly classified. The measured isotope parameters were thus primarily affected by the geographical origin. In conclusion, it is expected that the use of these parameters will allow the development of analytical control procedures that can be used to check the geographical origin of Italian organic and conventional pasta and its raw materials. Copyright © 2016 John Wiley & Sons, Ltd.