Experimental determination and modelling of the soil water extraction capacities of crops of maize,sunflower, soya bean,sorghum and wheat

The estimation of soil water reserves is essential for irrigation management. The usual way of calculating these reserves, held between the soil moisture content at field capacity and the classical limit of –1.5 MPa considered as the lower limit of available water, over the rooting depth of the crop, does not correspond with the real behaviour of crops as regards their ability to extract soil water and should be only considered as the apparent available water (AAW). Measurements of moisture profiles made using a neutron probe soil moisture meter from 1970 until 1991 on unirrigated crops at the INRA Agronomy Station at Toulouse-Auzeville, France, on a deep silty clay soil with a high water holding capacity have enabled us to define the water extraction capacities of maize ( Zea mays L.), sunflower (Helianthus annuus L.), sorghum (Sorghum bicolor L. Moench), soya bean (Glycine max L. Merr.), and winter wheat (Triticum aestivum L.). The results show, not only that all the crops can extract soil water from beyond –1.5 MPa in the surface layers to varying degrees and depths, depending on the crop, but also that deeper down, AAW is not fully used, as the moisture profile gradually returns to field capacity. Of the five crops studied, maize extracts the most water from the top 0.5 m, removing 150% of AAW. This amount falls rapidly lower down, reaching nil at 1.6 m. Conversely sunflower extracts less near the surface, but uses all AAW up to 1.2 m, and still extracts 85% of AAW at 1.6 m. Sorghum is somewhat comparable to sunflower, but with a lower use over the entire profile. Soya bean exhibits strong extraction to 1.0 m, and then much less at depth. As to wheat, its extraction capability is quite high near the surface, and then falls steadily with depth where it is still 30% of AAW at 1.6 m. Soil moisture measurements realised on a bare soil during several successive years were used to fix the maximum soil evaporation and to suggest the contribution of crops in soil water depletion from uppermost layers.The water extraction capacities have been modelled and introduced into the model EPICphase, a modified version of the model EPIC, adapted for irrigation management. Four parameters have been introduced to simulate: (1) the rooting pattern of the crop (parameter ), (2) the degree of involvement of deep layers (parameter p), (3) the fraction of AAW beyond which crop transpiration is affected (parameter t) and (4) the intensity of extraction beyond the limit of –1.5 MPa as a function of soil depth (parameter d). Calibrated on the basis of the driest year since 1970 for each crop, the model was then validated under unirrigated conditions, and then tested on irrigated maize plots. Under unirrigated conditions, the simulations correctly reproduced the water extraction by the five crops, both in an extremely dry year and in a wet year. The observed differences between simulations and observations were found mostly at about 0.1 m depth, and were due to lack of precision of moisture measurements with the neutron probe. From 0.2 to 0.6 m the simulations have a tendency to overestimate the extraction. These differences are explained by water fluxes which are especially high in these layers because of the processes of evaporation from the soil and plant transpiration, which are difficult to simulate with precision. Below 0.6 m, a more stable zone where water movements are of minor importance, the simulations are very precise. For irrigated maize, the results show a very good fit between simulation and measurement, indicating that these water extraction capacity figures could be used for irrigation management provided that the rules for exploitation of the water reserves are well established.     

Injury Profile SIMulator,a Qualitative Aggregative Modelling Framework to Predict Injury Profile as a Function of Cropping Practices,and Abiotic and Biotic Environment. II. Proof of Concept: Design of IPSIM-Wheat-Eyespot

IPSIM (Injury Profile SIMulator) is a generic modelling framework presented in a companion paper. It aims at predicting a crop injury profile as a function of cropping practices and abiotic and biotic environment. IPSIM''s modelling approach consists of designing a model with an aggregative hierarchical tree of attributes. In order to provide a proof of concept, a model, named IPSIM-Wheat-Eyespot, has been developed with the software DEXi according to the conceptual framework of IPSIM to represent final incidence of eyespot on wheat. This paper briefly presents the pathosystem, the method used to develop IPSIM-Wheat-Eyespot using IPSIM''s modelling framework, simulation examples, an evaluation of the predictive quality of the model with a large dataset (526 observed site-years) and a discussion on the benefits and limitations of the approach. IPSIM-Wheat-Eyespot proved to successfully represent the annual variability of the disease, as well as the effects of cropping practices (Efficiency = 0.51, Root Mean Square Error of Prediction = 24%; bias = 5.0%). IPSIM-Wheat-Eyespot does not aim to precisely predict the incidence of eyespot on wheat. It rather aims to rank cropping systems with regard to the risk of eyespot on wheat in a given production situation through ex ante evaluations. IPSIM-Wheat-Eyespot can also help perform diagnoses of commercial fields. Its structure is simple and permits to combine available knowledge in the scientific literature (data, models) and expertise. IPSIM-Wheat-Eyespot is now available to help design cropping systems with a low risk of eyespot on wheat in a wide range of production situations, and can help perform diagnoses of commercial fields. In addition, it provides a proof of concept with regard to the modelling approach of IPSIM. IPSIM-Wheat-Eyespot will be a sub-model of IPSIM-Wheat, a model that will predict injury profile on wheat as a function of cropping practices and the production situation.     

Future area expansion outweighs increasing drought risk for soybean in Europe

The European Union is highly dependent on soybean imports from overseas to meet its protein demands. Individual Member States have been quick to declare self-sufficiency targets for plant-based proteins, but detailed strategies are still lacking. Rising global temperatures have painted an image of a bright future for soybean production in Europe, but emerging climatic risks such as drought have so far not been included in any of those outlooks. Here, we present simulations of future soybean production and the most prominent risk factors across Europe using an ensemble of climate and soybean growth models. Projections suggest a substantial increase in potential soybean production area and productivity in Central Europe, while southern European production would become increasingly dependent on supplementary irrigation. Average productivity would rise by 8.3% (RCP 4.5) to 8.7% (RCP 8.5) as a result of improved growing conditions (plant physiology benefiting from rising temperature and CO₂ levels) and farmers adapting to them by using cultivars with longer phenological cycles. Suitable production area would rise by 31.4% (RCP 4.5) to 37.7% (RCP 8.5) by the mid-century, contributing considerably more than productivity increase to the production potential for closing the protein gap in Europe. While wet conditions at harvest and incidental cold spells are the current key challenges for extending soybean production, the models and climate data analysis anticipate that drought and heat will become the dominant limitations in the future. Breeding for heat-tolerant and water-efficient genotypes is needed to further improve soybean adaptation to changing climatic conditions.