An Agro-Climatic Approach to Developing a National Prevention Tool for Deoxynivalenol in French Maize-Growing Areas.

The levels of deoxynivalenol (DON)-a mycotoxin produced by Fusarium graminearum-in maize for food and feed are subject to European Union regulations. Obtaining a compliant harvest requires the identification of agronomic and climatic risk factors related to higher fungal contamination and DON production. A national, multiyear database for maize was created, based on field survey data collected from 2004 to 2020. This database contains information about agricultural practices, climatic sequences and DON content at harvest for a total of 2032 maize fields localized in the French maize-growing regions. A linear mixed-model approach highlighted the presence of borers, late harvest and inadequate crop residue management, normal-to-cold temperatures in March, humidity in August and the absence of a hot end of the maize development cycle with a dry August as creating conditions favoring maize contamination with DON. The various possible associations between these risky climatic conditions and agricultural practices were compared, grouped and ranked as related to very low to high DON concentrations. Some combinations may even exceed the regulatory threshold. The national prevention tool, created for producers and agricultural cooperatives, is informative and easy-to-use to control the sanitary quality of their harvest.

A Fumonisin Prevention Tool for Targeting and Ranking Agroclimatic Conditions Favoring Exposure in French Maize-Growing Areas.

The levels of fumonisins (FUMO)-mycotoxins produced by Fusarium verticillioides-in maize for food and feed are subject to European Union regulations. Compliance with the regulations requires the targeting of, among others, the agroclimatic factors influencing fungal contamination and FUMO production. Arvalis-Institut du végétal has created a national, multiyear database for maize, based on field survey data collected since 2003. This database contains information about agricultural practices, climatic conditions and FUMO concentrations at harvest for 738 maize fields distributed throughout French maize-growing regions. A linear mixed model approach highlights the presence of borers and the use of a late variety, high temperatures in July and October, and a water deficit during the maize cycle as creating conditions favoring maize contamination with Fusarium verticillioides. It is thus possible to target a combination of risk factors, consisting of this climatic sequence associated with agricultural practices of interest. The effects of the various possible agroclimatic combinations can be compared, grouped and classified as promoting very low to high FUMO concentrations, possibly exceeding the regulatory threshold. These findings should facilitate the creation of a national, informative and easy-to-use prevention tool for producers and agricultural cooperatives to manage the sanitary quality of their harvest.

Genetic and Environmental Variation in Starch Content, Starch Granule Distribution and Starch Polymer Molecular Characteristics of French Bread Wheat.

This study investigates genetic and environmental variation in starch content and characteristics of 14 French bread cultivars. Understanding the impact of these factors on wheat quality is important for processors and especially bakers to maintain and meet the requirements of industrial specifications. Different traits were evaluated: starch content, distribution of starch granules, percentage of amylose and amylopectin and their molecular characteristics (weight-average molar mass, number-average molar mass, polydispersity and gyration radius). Genetic, environment and their interaction had significant effects on all parameters. The relative magnitude of variance attributed to growth conditions, for most traits, was substantially higher (21% to 95%) than that attributed to either genotype (2% to 73%) or G × E interaction (2% to 17%). The largest environmental contribution (95%) to total variance was found for starch dispersity. The highest genetic influence was found for the percentage of A-type starch granules. G × E interaction had relatively little influence (≈7%) on total phenotypic variance. All molecular characteristics were much more influenced by environment than the respective percentages of amylose and amylopectin were. This huge difference in variance between factors obviously revealed the importance of the effect of growing conditions on characteristics of cultivars.

Efficient models for predicting durum wheat grain Cd conformity using soil variables and cultivars.

Contamination of durum wheat grain by cadmium (Cd) threatens food safety and is of increasing concern because regulations concerning Cd are becoming stricter due to its toxicity. This work aimed at using soil variables and cultivar types to build models to predict whether durum wheat grain Cd will conform with current and possibly lower regulatory thresholds. We combined multiple Gaussian and logistic regressions and the random forest algorithm to take advantage of their strength. Models tested using cross-validation produced excellent performances including for the lowest regulatory threshold of 0.1 mg Cd/kg, half of the current one: 79-85% of the non-conformity cases were detected and the reliability of predictions was 69-82%. The models enabled identification of a x1.4 variability in grain Cd content between cultivars that do not have the low Cd accumulation allele of the Cdu1 gene. The models confirmed that for the grain Cd content, the between-cultivar variability had much less influence than the phytoavailability of Cd in soil, the critical contexts of which were characterized by the models. For farmers, these models are valuable tools to predict whether durum wheat production will conform with existing and future Cd regulation in foodstuffs.

Predictive statistical modelling of cadmium content in durum wheat grain based on soil parameters.

Regulatory limits on cadmium (Cd) content in food products are tending to become stricter, especially in cereals, which are a major contributor to dietary intake of Cd by humans. This is of particular importance for durum wheat, which accumulates more Cd than bread wheat. The contamination of durum wheat grain by Cd depends not only on the genotype but also to a large extent on soil Cd availability. Assessing the phytoavailability of Cd for durum wheat is thus crucial, and appropriate methods are required. For this purpose, we propose a statistical model to predict Cd accumulation in durum wheat grain based on soil geochemical properties related to Cd availability in French agricultural soils with low Cd contents and neutral to alkaline pH (soils commonly used to grow durum wheat). The best model is based on the concentration of total Cd in the soil solution, the pH of a soil CaCl2 extract, the cation exchange capacity (CEC), and the content of manganese oxides (Tamm's extraction) in the soil. The model variables suggest a major influence of cadmium buffering power of the soil and of Cd speciation in solution. The model successfully explains 88% of Cd variability in grains with, generally, below 0.02 mg Cd kg-1 prediction error in wheat grain. Monte Carlo cross-validation indicated that model accuracy will suffice for the European Community project to reduce the regulatory limit from 0.2 to 0.15 mg Cd kg-1 grain, but not for the intermediate step at 0.175 mg Cd kg-1. The model will help farmers assess the risk that the Cd content of their durum wheat grain will exceed regulatory limits, and help food safety authorities test different regulatory thresholds to find a trade-off between food safety and the negative impact a too strict regulation could have on farmers.