Analysis and modelling of plant interactions

Analysis and modelling of plant interactions, abiotic factor use efficiency and yield performance in species mixtures

By WP2 coordinators: Erik Steen Jensen (Erik.Steen.Jensen@slu.se); Raj Chongtham (Raj.Chongtham@slu.se); Etienne-Pascal Journet (Etienne-Pascal.Journet@inra.fr), TjeerdJan Stomph (tjeerdjan.stomph@wur.nl); Jochem Evers (jochem.evers@wur.nl)

The ‘four Cs’ in action - competition, complementarity, cooperation and compensation

Over the first year of ReMIX partners have been working on producing a knowledge synthesis on the factors that determine yield, yield stability and abiotic resource capture and use efficiency of intercropping as compared to sole cropping. The focus has been on existing knowledge gaps and the research approaches needed to advance the field and pave the way for a wider usage of intercropping in modern sustainable agriculture. A paper will be released shortly covering the main aspects of the knowledge synthesis.  

Field experiments for determining interactions in species mixtures for improved yield and yield stabilisation

A first set of field experiments have been successfully carried out since autumn 2017 at the Aristotle University of Thessaloniki (AUTH, Greece), including pea-wheat mixtures (several varieties of each tested), and with/without irrigation, to further study how species mixtures interact for improved acquisition of light and water under different managements. These experiments also aim genotype behaviour testing in pea-wheat, faba bean-wheat, and bean-maize mixtures, at different densities and for various management conditions (water availability, fertilization). The data generated on a number of crop-relevant variables and those available at INRA and the Chinese Agricultural University from previous experiments will be combined for further analysis. 

Field experiments at the Swedish University of Agricultural Sciences (SLU) and University of Hohenheim (UHOH) have been established during the first year to determine how intercrops and sole crops of pea and oats perform in a field with heterogeneous soil conditions. The sole crops and intercrops were sown in strips along transects with known soil variability (electrical conductivity and elevation) within the field. Soil samples were analysed for pH, texture, nitrogen, carbon, exchangeable potassium, phosphate and water content. These soil parameters will be examined in relation to crop performance (grain yield, biomass, yield stability, nutrient acquisition), biomass and occurrence of weeds, and occurrence of diseases using geo-spatial statistics. Due to long period of draught and warm temperature during late spring in Sweden, some of the crops (specially the peas) in the experiment have been damaged.

WP2_pic1
WP2_pic2

Pictures: Oat-pea intercrop (Photo by Raj C., above) and interpolated map of measured soil phosphate (below) from the field in Sweden (WP2, Task 2.3).

Modelling above- and below-ground plant interactions in species mixtures

Literature synthesis and data coming from ReMIX experiments will be used for simulation of crop mixtures to find optimal trait combinations in WP5 and for practical tools in WP6. A knowledge synthesis on existing models is on the making and a scientific paper will shortly be submitted. Farm-level experiments will assess effects of soil heterogeneity on resource availability, including assessment of biotic stresses (weeds, diseases).

Partners are working on building a functional- structural plant model that can simulate performance of component species in crop mixtures, based on both above and below ground interactions. Significant progress has been made in the coupling of soil, root and shoot modules in order to be able to simulate water dynamics. Steps have been taken to evaluate model performance in terms of prediction of single plant growth.

 Click on the links below to watch videos on above and below ground modelling of maize and wheat intercrops:

Modification date : 31 August 2023 | Publication date : 20 June 2018 | Redactor : INI