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Cirillo, V., Masin, R., Maggio, A., & Zanin, G. (2018). Crop-weed interactions in saline environments. Europ. J. Agron., 99, 51–61.
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.
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Höglind, M., Van Oijen, M., Cameron, D., & Persson, T. (2016). Process-based simulation of growth and overwintering of grassland using the BASGRA model. Ecol. Model., 335, 1–15.
Abstract: Process-based models (PBM) for simulation of weather dependent grass growth can assist farmers and plant breeders in addressing the challenges of climate change by simulating alternative roads of adaptation. They can also provide management decision support under current conditions. A drawback of existing grass models is that they do not take into account the effect of winter stresses, limiting their use for full-year simulations in areas where winter survival is a key factor for yield security. Here, we present a novel full-year PBM for grassland named BASGRA. It was developed by combining the LINGRA grassland model (Van Oijen et al., 2005a) with models for cold hardening and soil physical winter processes. We present the model and show how it was parameterized for timothy (Phleum pratense L.), the most important forage grass in Scandinavia and parts of North America and Asia. Uniquely, BASGRA simulates the processes taking place in the sward during the transition from summer to winter, including growth cessation and gradual cold hardening, and functions for simulating plant injury due to low temperatures, snow and ice affecting regrowth in spring. For the calibration, we used detailed data from five different locations in Norway, covering a wide range of agroclimatic regions, day lengths (latitudes from 59 degrees to 70 degrees N) and soil conditions. The total dataset included 11 variables, notably above-ground dry matter, leaf area index, tiller density, content of C reserves, and frost tolerance. All data were used in the calibration. When BASGRA was run with the maximum a-posteriori (MAP) parameter vector from the single, Bayesian calibration, nearly all measured variables were simulated to an overall normalized root mean squared error (NRMSE) <0.5. For many site x experiment combinations, NRMSE was <0.3. The temporal dynamics were captured well for most variables, as evaluated by comparing simulated time courses versus data for the individual sites. The results may suggest that BASGRA is a reasonably robust model, allowing for simulation of growth and several important underlying processes with acceptable accuracy for a range of agroclimatic conditions. However, the robustness of the model needs to be tested further using independent data from a wide range of growing conditions. Finally we show an example of application of the model, comparing overwintering risks in two climatically different sites, and discuss future model applications. Further development work should include improved simulation of the dynamics of C reserves, and validation of winter tiller dynamics against independent data. (C) 2016 Elsevier B.V. All rights reserved.
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Van Oijen, M., & Höglind, M. (2016). Toward a Bayesian procedure for using process-based models in plant breeding, with application to ideotype design. Euphytica, 207(3), 627–643.
Abstract: Process-based grassland models (PBMs) simulate growth and development of vegetation over time. The models tend to have a large number of parameters that represent properties of the plants. To simulate different cultivars of the same species, different parameter values are required. Parameter differences may be interpreted as genetic variation for plant traits. Despite this natural connection between PBMs and plant genetics, there are only few examples of successful use of PBMs in plant breeding. Here we present a new procedure by which PBMs can help design ideotypes, i.e. virtual cultivars that optimally combine properties of existing cultivars. Ideotypes constitute selection targets for breeding. The procedure consists of four steps: (1) Bayesian calibration of model parameters using data from cultivar trials, (2) Estimating genetic variation for parameters from the combination of cultivar-specific calibrated parameter distributions, (3) Identifying parameter combinations that meet breeding objectives, (4) Translating model results to practice, i.e. interpreting parameters in terms of practical selection criteria. We show an application of the procedure to timothy (Phleum pratense L.) as grown in different regions of Norway.
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Kunert, K. J., van Wyk, S. G., Cullis, C. A., Vorster, B. J., & Foyer, C. H. (2015). Potential use of phytocystatins in crop improvement, with a particular focus on legumes. J. Experim. Bot., 66(12), 3559–3570.
Abstract: Phytocystatins are a well-characterized class of naturally occurring protease inhibitors that function by preventing the catalysis of papain-like cysteine proteases. The action of cystatins in biotic stress resistance has been studied intensively, but relatively little is known about their functions in plant growth and defence responses to abiotic stresses, such as drought. Extreme weather events, such as drought and flooding, will have negative impacts on the yields of crop plants, particularly grain legumes. The concepts that changes in cellular protein content and composition are required for acclimation to different abiotic stresses, and that these adjustments are achieved through regulation of proteolysis, are widely accepted. However, the nature and regulation of the protein turnover machinery that underpins essential stress-induced cellular restructuring remain poorly characterized. Cysteine proteases are intrinsic to the genetic programmes that underpin plant development and senescence, but their functions in stress-induced senescence are not well defined. Transgenic plants including soybean that have been engineered to constitutively express phytocystatins show enhanced tolerance to a range of different abiotic stresses including drought, suggesting that manipulation of cysteine protease activities by altered phytocystatin expression in crop plants might be used to improve resilience and quality in the face of climate change.
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Bressan, R. A., Park, H. C., Orsini, F., Oh, D. -ha, Dassanayake, M., Inan, G., et al. (2013). Biotechnology for mechanisms that counteract salt stress in extremophile species: a genome-based view. Plant Biotechnol. Rep., 7(1), 27–37.
Abstract: Molecular genetics has confirmed older research and generated new insights into the ways how plants deal with adverse conditions. This body of research is now being used to interpret stress behavior of plants in new ways, and to add results from most recent genomics-based studies. The new knowledge now includes genome sequences of species that show extreme abiotic stress tolerances, which enables new strategies for applications through either molecular breeding or transgenic engineering. We will highlight some physiological features of the extremophile lifestyle, outline emerging features about halophytism based on genomics, and discuss conclusions about underlying mechanisms.
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