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Wolf, J., Ouattara, K., & Supit, I. (2015). Sowing rules for estimating rainfed yield potential of sorghum and maize in Burkina Faso. Agricultural and Forest Meteorology, 214-215, 208–218.
Abstract: To reduce the dependence on local expert knowledge, which is important for large-scale crop modelling studies, we analyzed sowing dates and rules for maize (Zea mays L.) and sorghum (Sorghum bicolor (L)) at three locations in Burkina Faso with strongly decreasing rainfall amounts from south to north. We tested in total 22 methods to derive optimal sowing dates that result in highest water-limited yields and lowest yield variation in a reproducible and objective way. The WOFOST crop growth simulation model was used. We found that sowing dates that are based on local expert knowledge, may work quite well for Burkina Faso and for West Africa in general. However, when no a priori information is available, maize should be sown between Julian days 160 and 200, with application of the following criteria: (a) cumulative rainfall in the sowing window is >= 3 cm or available soil moisture content is >2 cm in the moderately dry central part of Burkina Faso, (b) cumulative rainfall in this period is >= 2 cm or available soil moisture content is >1 cm in the more humid regions in the southern part of Burkina Faso. Sorghum should also be sown between Julian days 160 and 200 with application of the following criteria: (a) in the dry northern part of Burkina Faso the long duration sorghum variety should be sown when cumulative rainfall is >2 cm in the sowing window, and the short duration sorghum variety should be sown later when cumulative rainfall is >= 3 cm, (b) in central Burkina Faso sowing should start when cumulative rainfall in this period is >= 2 cm or when available soil moisture content is >1 cm. Sowing date rules are shown to be generally crop and location specific and are not generic for West Africa. However, the required precision of the sowing rules appears to rapidly decrease with increasing duration and intensity of the rainy season. Sowing delay as a result of, for example, labour constraints, has a disastrous effect on rainfed maize and sorghum yields, particularly in the northern part of West Africa with low rainfall. Optimization of sowing dates can also be done by simulating crop yields in a time window of two months around a predefined sowing date. Using these optimized dates appears to result in a good estimate of the maximal mean rainfed yield level. (C) 2015 Elsevier B.V. All rights reserved.
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Waterworth, W. M., Bray, C. M., & West, C. E. (2015). The importance of safeguarding genome integrity in germination and seed longevity. J. Experim. Bot., 66(12), 3549–3558.
Abstract: Seeds are important to agriculture and conservation of plant biodiversity. In agriculture, seed germination performance is an important determinant of crop yield, in particular under adverse climatic conditions. Deterioration in seed quality is associated with the accumulation of cellular damage to macromolecules including lipids, protein, and DNA. Mechanisms that mitigate the deleterious cellular damage incurred in the quiescent state and in cycles of desiccation-hydration are crucial for the maintenance of seed viability and germination vigour. In early-imbibing seeds, damage to the embryo genome must be repaired prior to initiation of cell division to minimize growth inhibition and mutation of genetic information. Here we review recent advances that have established molecular links between genome integrity and seed quality. These studies identified that maintenance of genome integrity is particularly important to the seed stage of the plant lifecycle, revealing new insight into the physiological roles of plant DNA repair and recombination mechanisms. The high conservation of DNA repair and recombination factors across plant species underlines their potential as promising targets for the improvement of crop performance and development of molecular markers for prediction of seed vigour.
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Ventrella, D., Charfeddine, M., Giglio, L., & Castellini, M. (2012). Application of DSSAT models for an agronomic adaptation strategy under climate change in Southern of Italy: optimum sowing and transplanting time for winter durum wheat and tomato. Ital. J. Agron., 7(1), 16.
Abstract: Many climate change studies have been carried out in different parts of the world to assess climate change vulnerability and adaptation capacity of agricultural crops for certain environments characterized from climatic, pedological and agronomical point of view. The objective of this study was to analyse the productive response of winter durum wheat and tomato to climate change and sowing/transplanting time in one of the most productive areas of Italy (i.e. Capitanata, Puglia), using CERES-Wheat and CROPGRO cropping system models. Three climatic datasets were used: i) a single dataset (50 km x 50 km) provided by the JRC European centre for the period 1975- 2005; two datasets from HadCM3 for the IPCC A2 GHG scenario for time slices with +2°C (centred over 2030-2060) and +5°C (centred over 2070-2099), respectively. All three datasets were used to generate synthetic climate series using a weather simulator (model LARS-WG). No negative yield effects of climate change were observed for winter durum wheat with delayed sowing (from 330 to 345 DOY) increasing the average dry matter grain yield under forecasted scenarios. Instead, the warmer temperatures were primarily shown to accelerate the phenology, resulting in decreased yield for tomato under the + 5°C future climate scenario. In general, under global temperature increase by 5°C, early transplanting times could minimize the negative impact of climate change on crop productivity but the intensity of this effect was not sufficient to restore the current production levels of tomato cultivated in southern Italy.
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Van Oosten, M. J., Sharkhuu, A., Batelli, G., Bressan, R. A., & Maggio, A. (2013). The Arabidopsis thaliana mutant air1 implicates SOS3 in the regulation of anthocyanins under salt stress. Plant Mol. Biol., 83(4-5), 405–415.
Abstract: The accumulation of anthocyanins in plants exposed to salt stress has been largely documented. However, the functional link and regulatory components underlying the biosynthesis of these molecules during exposure to stress are largely unknown. In a screen of second site suppressors of the salt overly sensitive3-1 (sos3-1) mutant, we isolated the anthocyanin-impaired-response-1 (air1) mutant. air1 is unable to accumulate anthocyanins under salt stress, a key phenotype of sos3-1 under high NaCl levels (120 mM). The air1 mutant showed a defect in anthocyanin production in response to salt stress but not to other stresses such as high light, low phosphorous, high temperature or drought stress. This specificity indicated that air1 mutation did not affect anthocyanin biosynthesis but rather its regulation in response to salt stress. Analysis of this mutant revealed a T-DNA insertion at the first exon of an Arabidopsis thaliana gene encoding for a basic region-leucine zipper transcription factor. air1 mutants displayed higher survival rates compared to wild-type in oxidative stress conditions, and presented an altered expression of anthocyanin biosynthetic genes such as F3H, F3’H and LDOX in salt stress conditions. The results presented here indicate that AIR1 is involved in the regulation of various steps of the flavonoid and anthocyanin accumulation pathways and is itself regulated by the salt-stress response signalling machinery. The discovery and characterization of AIR1 opens avenues to dissect the connections between abiotic stress and accumulation of antioxidants in the form of flavonoids and anthocyanins.
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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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