Gene flow in commercial alfalfa (Medicago sativa subsp. sativa L.) seed production fields: Distance is the primary but not the sole influence on adventitious presence

In insect-pollinated crops, gene flow is affected by numerous factors including crop characteristics, mating system, life history, pollinators, and planting management practices. Previous studies have concentrated on the impact of distance between genetically engineered (GE) and conventional fields on adventitious presence (AP) which represents the unwanted presence of a GE gene. Variables other than distance, however, may affect AP. In addition, some AP is often present in the parent seed lots used to establish conventional fields. To identify variables that influence the proportion of AP in conventional alfalfa fields, we performed variable selection regression analyses. Analyses based on a sample-level and a field-level analysis gave similar, though not identical results. For the sample-level model, distance from the GE field explained 66% of the variance in AP, confirming its importance in affecting AP. The area of GE fields within the pollinator foraging range explained an additional 30% of the variation in AP in the model. The density of alfalfa leafcutting bee domiciles influenced AP in both models. To minimize AP in conventional alfalfa seed fields, management practices should focus on optimizing isolation distances while also considering the size of the GE pollen pool within the pollinator foraging range, and the foraging behavior of pollinators.

Meeting the Tolerance: How Successful is Coexistence in Commodity Corn Handling Systems?

HighlightsMeeting the 0.9% tolerance level was challenging under most conditions.Non-GM loads in the simulation were able to meet a 1.5% or 3% tolerance level under specific conditions.Field isolation distance plays a large role in a non-GM load meeting the posted tolerance levelAbstract. The open-air growth environment used in maize production makes it nearly impossible to ensure 100% purity of specified genetic traits. One measure of successful coexistence is a low level of unintended material in seed, grain, and feed or food products, termed “adventitious presence” (AP). To allow the coexistence of genetically modified (GM) and non-genetically modified (non-GM) maize, tolerance levels regulate how much AP of genetically modified corn is allowed in each unit of maize. This research sought to model four factors contributing to levels of adventitious presence: seed purity, field isolation distance, combine cleanout, and grain elevator receipt and handling practices. Monte Carlo simulation was used to test nine scenarios to determine the feasibility of successfully meeting three tolerance levels for adventitious presence (0.9%, 1.5%, and 3.0%). After 50,000 iterations for each model, sensitivity analysis was performed to identify factors that play an important role in whether the load meets the posted tolerance level or not. Results suggest that non-GM maize loads would not meet a tolerance level of 0.9% in most cases. Non-GM maize loads were found to meet tolerance levels of 1.5% and 3.0% in certain cases. The most significant factors affecting the probability of the unit of maize meeting the posted tolerance level were field isolation distance, elevator handling practices, and seed purity. Keywords: Adventitious presence, Coexistence, Identity preservation, Monte Carlo simulation, Transgenic grain.

Developing a Graphical User Interface (GUI) to Predict the Contamination of GM Corn in Non-GM Corn

HighlightsA GUI tool was developed to predict the adventitious presence in non-GM produce.The software calculates tolerance and the probability of GM corn in non-GM corn.Predicted probability of contamination ranged from 0.050 to 0.356 at tolerance levels ranging from 0.1% to 5.0%.Abstract. The current rate of population growth necessitates the use of viable technologies like genetic modification to address estimated global food and feed requirements. However, in recent years, there has been an increase in resistance against the diffusion of genetic modification technology around the world. Many countries have adopted coexistence policies to allow a certain percentage of adventitious presence in non-genetically modified crops. However, the tolerance percentage for adventitious presence has been a bottleneck to free trade in some cases. It is a challenging task to fix a tolerance percentage considering the level of permeation of genetic modification technology in agriculture. This article introduces a software developed to serve as a decision-making tool to predict the probability distribution of genetically modified (GM) contamination in non-GM grain lot using user inputs such as final quantity of processed corn, overall tolerance level, and moisture content. The output from the software includes the mass of corn in each processing stage, the tolerance level and the probability distribution of potential GM contamination. The software predicted the probability of contamination with adventitious presence at tolerance levels of 5.0%, 3.0%, 1.0%, 0.9%, 0.5%, and 0.1% as 0.05, 0.07, 0.11, 0.12, 0.16, and 0.36, respectively. The predictions from the model were compared to a similar study wherein the effect of tolerance levels incurred in the costs of segregation was studied. The mean absolute percentage error for the predictions was found to be 3.07%. This software can be used as a tool in testing GM contamination in non-GM grain against a desired threshold levels in a grain elevator. Keywords: Corn, Genetic modification, Graphical User Interface (GUI), Threshold level.

MANAGEMENT OF FOOD ALLERGENS IN THE FOOD INDUSTRY

Ensuring food safety for people suffering fromvarious intolerances faces serious threats posed by allergenswhich have become a challenge for food manufacturers andmass caterers. These businesses are required to developand implement appropriate programs to manage allergenspresent in their sites. The purpose of this paper was to analyzethe actions taken by food manufacturers with respect tosubstances and products causing allergies or food intolerancesin the context of providing consumers with a safe, properlylabeled product. To achieve the objective of this study, a dataanalysis and synthesis method was employed based on requirementsdefined in obligatory and non-obligatory standardsfor food safety assurance and management in the foodproduction sector. In summary, as regards allergen management,the companies must create appropriate conditions andtake adequate measures (including the analysis of risks due tointentional and adventitious presence of allergens in food, andthe implementation of appropriate preventive actions). Solutionsprovided in the mandatory standards, mainly GHP andHACCP, as well as in non-mandatory standards, such as ISO22000, BRC, IFS and SQF, may be helpful in the managementof substances causing allergies or intolerances.