Indicators of weed competition on Organic Winter Wheat

Organic winter wheat production is limited by climatic and agronomic factors, including weed competition. The incidence of weeds on yield limitation can be characterized through various early indicators to predict weed occurrence and competition. A network of 10 fields of organic winter wheat was implemented in the South East of France in 2005-2006. Results showed that weed density, dynamics and diversity are good indicators for weed occurrence and competition

Improvement of the soil-crop model AZODYN under conventional, low-input and organic conditions

The use of mechanistic crop modelling, simulating the dynamics of crop N requirements and nitrogen supply from the soil and fertilizers, can provide sound advice to users. This paper describes a methodological way to improve soil-crop modeling used for N management of conventional and organic wheat

Wheat/forage legume intercropping in organic grain system: an answer to both weed and nitrogen deficiency issues

Organic grain system managers have to find solutions to nitrogen deficiency and weed infestation. It is especially true when no animals are present on the farm to justify the use of forage legumes despite their interests in the crop succession. Our study focused on the role of four legume cover crop species inserted in a succession of winter wheat and maize on both problems. This insertion consisted in relay-intercropping the legumes under the canopy of wheat. Cover crops were maintained on the field after the harvest of the cereal until the sowing of the subsequent maize crop. The performance of the three crops of the succession was monitored as well as weed development and nitrogen dynamic in the soil-plant system. On the one hand, our results showed that black medic and red clover, that supported the best the competition of wheat, were likely to decrease its grain protein content at harvest (-0.3 to -0.4 %). On the other hand, the four species did not decrease intercropped wheat grain yield. They were able to control weed infestation during the intercropping period and between the two cash crops. Finally, nitrogen restitution to the subsequent maize crop was efficient and allowed a significant 30 % increase of maize grain yield

Ambitious environmental and economic goals for the future of agriculture are unequally achieved by innovative cropping systems

International audienceAgriculture has to face huge challenges in the decades ahead. Four innovative cropping systems were assessed ina “cropping system experiment” in the Ile-de-France region (France) from 2009 to 2014. Three were designed tomeet ambitious goals: the total elimination of pesticides (No-Pest), reducing fossil energy consumption by 50%(L-EN), or decreasing greenhouse gas (GHG) emissions by 50% (L-GHG). They were also required to satisfy awide range of environmental criteria and to maximize yields whilst respecting the major constraint on the systemand the environmental targets set. A fourth system (PHEP), in which the environmental and yield targets wereachieved with no major constraint, was also assessed. After completion of the first full crop sequence for theseinnovative systems, the results obtained indicated that it was possible to design and implement innovativesystems achieving multiple goals. In our field trial conditions, the pesticide and energy constraints were almostsatisfied, whereas the GHG target was missed by a considerable margin. All four innovative systems satisfiedenvironmental criteria in terms of N management, pesticide use, energy consumption and crop diversity.However, herbicide treatment frequency index (TFIH) was higher than expected in the two systems with no-plowpractices, L-EN and L-GHG. In the pesticide-free system, soil organic matter content was lower than expected,due to frequent plowing (every 2 years) and low residue levels as a result of the lower yields obtained. Yieldswere lower for the L-EN system than for the reference system, and yield was variable in the L-GHG system. Theseinnovative systems had better environmental performances than the systems currently used in the Ile-de-Franceregion, with no decrease in gross margins

Editorial

National audienceL'éditorial explique comment ce numéro de la revue cherche à éclairer la manière dont l’agronomie, seule ou avec d’autres disciplines, peut être mise à contribution pour faire face aux multiples enjeux concernant la raréfaction des ressources naturelles qui concernent l’agriculture

Economic Analysis of Summer Fallow Management to Reduce Take-All and N-Leaching in a Wheat Crop Rotation

This paper addresses the question of summer cover crop adoption by farmers in presence of a risk of yield loss due to take-all disease and climate variability. To analyse the public incentives needed to encourage farmers to adopt summer cover crops as a means of reducing N leaching, we combine outputs from an economic, an epidemiological and an agronomic model. The economic model is a simple model of choice under uncertainty. The farmer is assumed to choose among a range of summer fallow managements and input uses on the basis of the expected utility criterion (HARA assumption) in presence of both climate and take all risks. The epidemiological model proposed by Ennaïfar et al. (2007) is used to determine the impact of take all on yields and N-uptake. The crop-soil model (STICS) is used to\ud compute yield developments and N-leaching under various management options and climatic conditions. These models are calibrated to match the conditions prevailing in Grignon, located in the main wheatgrowing\ud area in France. Eight management systems are examined: 4 summer fallow managements: 'wheat volunteers' (WV), 'bare soil' (BS), 'early mustard' (EM), 'late mustard' (LM), and 2 input intensities. We show that the optimal systems are BS (WV) when the take-all risk is (not) taken into account by agents. We then compute the minimum payment to each system such that it emerges in the optimum. We thus derive the required amounts of transfer needed to trigger catch crop adoption. The results of the Monte Carlo sensitivity analysis show that the ranking of management systems is robust over a wide range of input parameters