Abstract: Variability of crop yields is detrimental for food security. Under climate change its amplitude is likely to increase, thus it is essential to understand the underlying causes and mechanisms. Crop models are the primary tool to project future changes in crop yields under climate change. Asystematic overview of drivers and mechanisms of crop yield variability (YV) can thus inform crop model development and facilitate improved understanding of climate change impacts on crop yields. Yet there is a vast body of literature on crop physiology and YV, which makes a prioritization of mechanisms for implementation in models challenging. Therefore this paper takes on a novel approach to systematically mine and organize existing knowledge from the literature. The aim is to identify important mechanisms lacking in models, which can help to set priorities in model improvement. We structure knowledge from the literature in a semi-quantitative network. This network consists of complex interactions between growing conditions, plant physiology and crop yield. We utilize the resulting network structure to assign relative importance to causes of YV and related plant physiological processes. As expected, our findings confirm existing knowledge, in particular on the dominant role of temperature and precipitation, but also highlight other important drivers of YV. More importantly, our method allows for identifying the relevant physiological processes that transmit variability in growing conditions to variability in yield. We can identify explicit targets for the improvement of crop models. The network can additionally guide model development by outlining complex interactions between processes and by easily retrieving quantitative information for each of the 350 interactions. We show the validity of our network method as a structured, consistent and scalable dictionary of literature. The method can easily be applied to many other research fields.

Abstract: Soil salinization is one of the most critical environmental factors affecting crop yield. It is estimated that 20% of cultivated land and 33% of irrigated agricultural land are affected by salinity. In the last decades, considerable effort to manage saline agro-ecosystems has focused on 1) controlling soil salinity to minimize/reduce the accumulation of salts in the root zone and 2) improving plants ability to cope with osmotic and ionic stress. Less attention has been given to other components of the agro-ecosystem including weed populations, which also react and adapt to soil salinization and indirectly affect plant growth and yield. Weeds represent an increasing challenge for crop systems since they have high genetic resilience and adaptation ability to adverse environmental conditions such as soil salinization. In this review, we assess current knowledge on salinity tolerance of weeds in agricultural contexts and discuss critical components of crop-weed interactions that may increase weeds competitiveness under salinity. Compared to crop species, weeds generally exhibit greater salt tolerance due to high intraspecific variability, associated with diverse physiological adaptation mechanisms (e.g. phenotipic plasticity, seed heteromorphism, allelopathy). Weed competitiveness in saline soils may be enhanced by their earlier emergence, faster growth rates and synergies occurring between soil salts and allelochemicals released by weeds. In the future, a better understanding of crop-weed relationships and molecular, physiological and agronomic stress responses under salinity is essential to design efficient strategies to achieve weed control under altered climatic and environmental conditions.

Abstract: Ectopic cystatin expression has long been used in plant pest management, but the cysteine protease, targets of these inhibitors, might also have important functions in the control of plant lifespan and stress tolerance that remain poorly characterized. We therefore characterized the effects of expression of the rice cystatin, oryzacystatin-I (OCI), on the growth, development and stress tolerance of crop (soybean) and model (Arabidopsis thaliana) plants. Ectopic OCI expression in soybean enhanced shoot branching and leaf chlorophyll accumulation at later stages of vegetative development and enhanced seed protein contents and decreased the abundance of mRNAs encoding strigolactone synthesis enzymes. The OCI-expressing A. thaliana showed a slow-growth phenotype, with increased leaf numbers and enhanced shoot branching at flowering. The OCI-dependent inhibition of cysteine proteases enhanced drought tolerance in soybean and A. thaliana, photosynthetic CO2 assimilation being much less sensitive to drought-induced inhibition in the OCI-expressing soybean lines. Ectopic OCI expression or treatment with the cysteine protease inhibitor E64 increased lateral root densities in A. thaliana. E64 treatment also increased lateral root densities in the max2-1 mutants that are defective in strigolactone signalling, but not in the max3-9 mutants that are defective in strigolactone synthesis. Taken together, these data provide evidence that OCI-inhibited cysteine proteases participate in the control of growth and stress tolerance through effects on strigolactones. We conclude that cysteine proteases are important targets for manipulation of plant growth, development and stress tolerance, and also seed quality traits.