Can genome editing help transitioning to agroecology?

Meeting the challenges of agroecological transition in a context of climate change requires the use of various strategies such as biological regulations, adapted animal and plant genotypes, diversified production systems, and digital technologies. Seeds and plants, through plant breeding, play a crucial role in driving these changes. The emergence of genome editing presents a new opportunity in plant breeding practices.

Seedling emergence and biomass production of soybean cultivars under wheat-soybean relay cropping.

Diversification and intensification of cropping systems can ensure farm profitability while reducing negative environmental impacts of agriculture. Wheat-soybean relay cropping (RC), which consists in planting soybean into standing wheat prior to its harvest, may have this potential although it is poorly adopted by French and European farmers. One of the reasons underlying this lack of adoption could be poor emergence rates and biomass production of soybean, due to a severe competition from the already established primary crop for water, light and nutrients during the co-growth or intercrop phase.

Improving crop yield potential: Underlying biological processes and future prospects.

The growing world population and global increases in the standard of living both result in an increasing demand for food, feed and other plant-derived products. In the coming years, plant-based research will be among the major drivers ensuring food security and the expansion of the bio-based economy. Crop productivity is determined by several factors, including the available physical and agricultural resources, crop management, and the resource use efficiency, quality and intrinsic yield potential of the chosen crop.

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.

Optimized cultivar deployment improves the efficiency and stability of sunflower crop production at national scale.

Crop simulation helps to analyze environmental impacts on crops and provides year-independent context information. This information is of major importance when deciding which cultivar to choose at sowing time. Plant breeding programs design new crop cultivars which, while developed for distinct populations of environments, are nevertheless grown over large areas during their time in the market.

Combining Experimental and Modeling Approaches to Understand Genotype x Sowing Date x Environment Interaction Effects on Emergence Rates and Grain Yield of Soybean.

Soybean emergence and yield may be affected by many factors. A better understanding of the cultivar x sowing date x environment interactions could shed light into the competitiveness of soybean with other crops, notably, to help manage major biotic and abiotic factors that limit soybean production. We conducted a 2-year field experiments to measure emergence dynamics and final rates of three soybean cultivars from different maturity groups, with early and conventional sowing dates and across three locations.

Combining Simple Phenotyping and Photothermal Algorithm for the Prediction of Soybean Phenology: Application to a Range of Common Cultivars Grown in Europe.

Developing new cropping strategies (very early sowing, crop expansion at higher latitudes, double cropping) to improve soybean production in Europe under climate change needs a good prediction of phenology under different temperature and photoperiod conditions. For that purpose, a simple phenology algorithm (SPA) was developed and parameterized for 10 contrasting soybean cultivars (maturity group 000 to II). Two experiments were carried out at INRA Toulouse (France) for parameterization: 1) Phenological monitoring of plants in pots on an outdoor platform with 6 planting dates.

Data describing the eco-physiological responses of twenty-four sunflower genotypes to water deficit.

This article presents experimental data describing the physiology and morphology of sunflower plants subjected to water deficit. Twenty-four sunflower genotypes were selected to represent genetic diversity within cultivated sunflower and included both inbred lines and their hybrids. Drought stress was applied to plants in pots at the vegetative stage using the high-throughput phenotyping platform Heliaphen at INRA Toulouse (France).

Effects of plant growth stage and leaf aging on the response of transpiration and photosynthesis to water deficit in sunflower.

Water deficit influences leaf transpiration rate and photosynthetic activity. The genotype-dependent response of the latter has not been assessed in sunflower (Helianthus annuus L.), particularly during the reproductive period when grain filling and lipogenesis depend greatly on photosynthate availability.

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.

A biomarker based on gene expression indicates plant water status in controlled and natural environments.

Plant or soil water status is required in many scientific fields to understand plant responses to drought. Because the transcriptomic response to abiotic conditions, such as water deficit, reflects plant water status, genomic tools could be used to develop a new type of molecular biomarker. Using the sunflower (Helianthus annuus L.

Quantifying physiological determinants of genetic variation for yield potential in sunflower. SUNFLO: a model-based analysis.

Present work focussed on improving the description of organogenesis, morphogenesis and metabolism in a biophysical plant model (SUNFLO) applied to sunflower (Helianthus annuus L.). This first version of the model is designed for potential growth conditions without any abiotic or biotic stresses.