18 research outputs found

    Simulation of growth and development of diverse legume species in APSIM

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    This paper describes the physiological basis and validation of a generic legume model as it applies to 4 species: chickpea (Cicer arietinum L.), mungbean (Vigna radiata (L.) Wilczek), peanut (Arachis hypogaeaL.), and lucerne (Medicago sativa L.). For each species, the key physiological parameters were derived from the literature and our own experimentation. The model was tested on an independent set of experiments, predominantly from the tropics and subtropics of Australia, varying in cultivar, sowing date, water regime (irrigated or dryland), row spacing, and plant population density. The model is an attempt to simulate crop growth and development with satisfactory comprehensiveness, without the necessity of defining a large number of parameters. A generic approach was adopted in recognition of the common underlying physiology and simulation approaches for many legume species. Simulation of grain yield explained 77, 81, and 70% of the variance (RMSD = 31, 98, and 46 g/m2) for mungbean (n = 40, observed mean = 123 g/m2), peanut (n = 30, 421 g/m2), and chickpea (n = 31, 196 g/m2), respectively. Biomass at maturity was simulated less accurately, explaining 64, 76, and 71% of the variance (RMSD = 134, 236, and 125 g/m2) for mungbean, peanut, and chickpea, respectively. RMSD for biomass in lucerne (n = 24) was 85 g/m2 with an R2 of 0.55. Simulation accuracy is similar to that achieved by single-crop models and suggests that the generic approach offers promise for simulating diverse legume species without loss of accuracy or physiological rigour

    Effect of artificial wind shelters on the growth and yield of rainfed crops

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    There is great interest in quantifying and understanding how shelter modifies crop growth and development under Australian conditions. Small constructed enclosures (shelters) can consistently reduce wind speed, allowing experiments to be run with replicated sheltered and unsheltered treatments in close proximity. The aim of this study was to quantify the effect on microclimate of consistently reducing wind speed by 70% and explain the consequences for dryland wheat (Triticum aestivum), lupin (Lupinus angustifolius) and mungbean (Vigna radiata) growth and development, at sites in Queensland, Victoria and Western Australia. Crops were grown inside and outside of artificial shelters, 10 by 10 m and extending 1 m above the crop canopy throughout the growing season. Mean daily air and soil temperatures and atmospheric vapour pressure inside the shelters were largely similar to unsheltered conditions. However, clear diurnal trends were evident; daily maximum temperature and vapour pressure deficit (VPD) were increased in shelter when crops were establishing or senescing. When leaf area index (LAI) was reduced in the shelters, soil temperature was greater than in the open, however when LAI was increased in the shelters, soil temperature was less than in the open. Grain yield in shelters ranged between 78 and 120% of unsheltered yield, depending on seasonal conditions and crop species; the mean yield for all sites, crops and years was 99% of unsheltered yield. In the absence of waterlogging, sheltered crops tended to develop more leaf area than unsheltered crops, with an increase in the ratio of leaf area to above-ground biomass. This greater leaf area did not increase soil water use. While LAI was increased by shelter, only 2 of the 6 sheltered crops that were not waterlogged yielded significantly more grain than the unsheltered crops. This may be because the sheltered crops experienced greater maximum temperatures and VPD during anthesis and grain filling than unsheltered crops. Also, net photosynthesis may not have increased in the shelters after canopy closure (LAI>3–4). Lupins, which developed more leaf area inside shelters, may have experienced strong competition for assimilates between developing branches, flowers and fruit. When rainfall was above average and the soil became waterlogged for part of the growing season, grain yield was reduced inside the shelters. Reduced evaporation inside the shelters may have extended the duration and severity of waterlogging and increased stresses on sheltered plants when potential yield was being set. The reductions in wind speed achieved inside the artificial shelters were greater than those likely in conventional tree windbreak systems. Analysis of crop growth illustrated that microclimate modification at this high level of shelter can be both beneficial and harmful, depending on the crop species and climatic conditions during the growing season

    Modelling crop growth and yield under the environmental changes induced by windbreaks. 1. Model development and validation

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    Yield advantages of crops grown behind windbreaks have often been reported, but underlying principles responsible for such changes and their long-term consequences on crop productivity and hence farm income have rarely been quantified. Physiologically and physically sound simulation models could help to achieve this quantification. Hence, the APSIM systems model, which is based on physiological principles such as transpiration efficiency and radiation use efficiency (termed here APSIMTE), and the Soil Canopy Atmosphere Model (SCAM), which is based on the Penman–Monteith equation but includes a full surface energy balance, were employed in developing an approach to quantify such windbreak effects. This resulted in a modified APSIM version (APSIMEO), containing the original Penman equation and a calibration factor to account for crop- and site-specific differences, which were tested against field data and simulations from both the standard APSIMTE and SCAM models. The APSIMEO approach was tested against field data for wheat and mungbean grown in artificial enclosures in south-east Queensland and in south-east Western Australia. For these sheltered conditions, daily transpiration demand estimates from APSIMEO compared closely to SCAM. As the APSIMEO approach needed to be calibrated for individual crops and environments, average transpiration demand for open field conditions predicted by APSIMEO for a given site was adjusted to equal that obtained using APSIMTE by modifying a calibration parameter β. For wheat, a β-value of 1.0 resulted in best fits for Queensland, while for Western Australia a value of 0.85 was necessary. For mungbean a value of 0.92 resulted in the best fit (Qld). Biomass and yields simulated by APSIMTE and the calibration APSIMEO for wheat and mungbean grown in artificial enclosures were generally distributed around the 1:1 line, with R2 values ranging from 0.92 to 0.97. Finally, APSIMEO was run at 2 sites using long-term climate data to assess the likely year-to-year variability of windbreak effects on crop yields. Assuming a 70% reduction in wind speed as representing the maximum potential windbreak effect, the average yield improvement for the Queensland site was 13% for wheat and 3% for mungbean. For wheat at the WA site the average yield improvement from reduced wind speed was 5%. In any year, however, effects varied from negative, neutral to positive, highlighting the highly variable nature of the expression of windbreak effects. This study has shown how physical and biological modelling approaches can be combined to aid our understanding of systems processes. Both the environmental physics perspective and the biological perspective have shortcomings when issues that sit at the interface of both approaches need to be addressed. While the physical approach has clear advantages when investigating changes in physical parameters such as wind speed, vapour pressure deficit (VPD), temperature or the energy balance of the soil–plant–atmosphere continuum, it cannot deal with complex, biological systems adequately. Conversely, the crop physiological approach can handle such biological interactions in a scientific and robust way while certain atmospheric processes are not considered. The challenge was not to try and capture all these effects in 1 model, but rather to structure a modelling approach in a way that allowed for inclusion of such processes where necessary

    Modelling crop growth and yield under the environmental changes induced by windbreaks. 2. Simulation of potential benefits at selected sites in Australia

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    Recent reports in Australia and elsewhere have attributed enhanced crop yields to the presence of tree windbreaks on farms. One hypothesis for this observation is that, by reducing wind speed, windbreaks influence crop water and energy balances resulting in lower evaporative demand and increased yield. This paper is the second in a series aimed at developing and using crop and micrometeorological modelling capabilities to explore this hypothesis. Specifically, the objectives of this paper are to assist the interpretation of recent field experimentation on windbreak impacts and to quantify the potential benefits and the likelihood of windbreak effects on crop production through an economic analysis of crop yields predicted for the historical climate record at selected sites in Australia. The APSIM systems model was specified to simulate crop growth under the environmental changes induced by windbreaks and subsequently used to simulate the potential benefits on crop production at 2 actual windbreak sites and 17 hypothetical sites around Australia. With the actual windbreak sites, APSIM closely simulated measured crop growth and yield in open-field conditions. However, neither site demonstrated measurable windbreak impacts and APSIM simulations confirmed that such effects would have been either non-existent or masked by experimental variability in the years under study. For each year of the long-term climate record at 17 sites, APSIM simulated yields of relevant crops for transects behind hypothetical windbreaks that provided protection against all wind. When wind protection from all directions is assumed, average simulated yield increases at 5 H (height of windbreak) ranged from 0.2% for maize at Atherton to 24.6% for wheat grown at Dalby, resulting in gross margin changes of ¿14.79/ha.cropand14.79/ha.crop and 24.13/ha.crop, respectively, for a 10 m high windbreak and 100 ha paddock and assuming a 20% yield loss due to tree competition in the 1.0¿3.5 H section. Averaged across all sites and crops, the simulations predicted a yield advantage of 8.6% at 5 H for protection from wind in any direction, resulting in an average gross margin loss of ¿0.60/ha.crop.Atthe8siteswithavailabledataforwinddirection,andassumingprotectiononlyfromwindoriginatingwithina90°arcperpendiculartoahypotheticalwindbreakwhichwasoptimallyorientatedateachsite,averagesimulatedyieldincreasesat5Hrangedfrom1.00.60/ha.crop. At the 8 sites with available data for wind direction, and assuming protection only from wind originating within a 90° arc perpendicular to a hypothetical windbreak which was optimally orientated at each site, average simulated yield increases at 5 H ranged from 1.0% for wheat at Orange to 8.6% for wheat grown at Geraldton. For a 10 m high windbreak, 100 ha paddock and an assumed 20% yield loss in the 1.0¿3.5 H section, the average result across all sites and crops was a 4.7% yield advantage at 5 H and an average gross margin loss of ¿2.49/ha.crop. In conclusion, APSIM simulation and economic analyses indicated that yield benefits from microclimate changes can at least partly offset the opportunity costs of positioning tree windbreaks on farms

    High-resolution carbon isotope records of the Toarcian Oceanic Anoxic Event (Early Jurassic) from North America and implications for the global drivers of the Toarcian carbon cycle

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    The Mesozoic Era experienced several instances of abrupt environmental change that are associated with instabilities in the climate, reorganizations of the global carbon cycle, and elevated extinction rates. Often during these perturbations, oxygen-deficient conditions developed in the oceans resulting in the widespread deposition of organic-rich sediments — these events are referred to as Oceanic Anoxic Events or OAEs. Such events have been linked to massive injections of greenhouse gases into the ocean–atmosphere system by transient episodes of voluminous volcanism and the destabilization of methane clathrates within marine environments. Nevertheless, uncertainty surrounds the specific environmental drivers and feedbacks that occurred during the OAEs that caused perturbations in the carbon cycle; this is particularly true of the Early Jurassic Toarcian OAE (∼183.1 Ma). Here, we present biostratigraphically constrained carbon isotope data from western North America (Alberta and British Columbia, Canada) to better assess the global extent of the carbon cycle perturbations. We identify the large negative carbon isotope excursion associated with the OAE along with high-frequency oscillations and steps within the onset of this excursion. We propose that these high-frequency carbon isotope excursions reflect changes to the global carbon cycle and also that they are related to the production and release of greenhouse gases from terrestrial environments on astronomical timescales. Furthermore, increased terrestrial methanogenesis should be considered an important climatic feedback during Ocean Anoxic Events and other similar events in Earth history after the proliferation of land plants

    Simulating the effects of saline and sodic subsoils on wheat crops growing on Vertosols

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    Soils with high levels of chloride and/or sodium in their subsurface layers are often referred to as having subsoil constraints (SSCs). There is growing evidence that SSCs affect wheat yields by increasing the lower limit of a crop's available soil water (CLL) and thus reducing the soil's plant-available water capacity (PAWC). This proposal was tested by simulation of 33 farmers' paddocks in south-western Queensland and north-western New South Wales. The simulated results accounted for 79% of observed variation in grain yield, with a root mean squared deviation (RMSD) of 0.50 t/ha. This result was as close as any achieved from sites without SSCs, thus providing strong support for the proposed mechanism that SSCs affect wheat yields by increasing the CLL and thus reducing the soil's PAWC. In order to reduce the need to measure CLL of every paddock or management zone, two additional approaches to simulating the effects of SSCs were tested. In the first approach the CLL of soils was predicted from the 0.3-0.5 m soil layer, which was taken as the reference CLL of a soil regardless of its level of SSCs, while the CLL values of soil layers below 0.5 m depth were calculated as a function of these soils' 0.3-0.5 m CLL values as well as of soil depth plus one of the SSC indices EC, Cl, ESP, or Na. The best estimates of subsoil CLL values were obtained when the effects of SSCs were described by an ESP-dependent function. In the second approach, depth-dependent CLL values were also derived from the CLL values of the 0.3-0.5 m soil layer. However, instead of using SSC indices to further modify CLL, the default values of the water-extraction coefficient (kl) of each depth layer were modified as a function of the SSC indices. The strength of this approach was evaluated on the basis of correlation of observed and simulated grain yields. In this approach the best estimates were obtained when the default kl values were multiplied by a Cl-determined function. The kl approach was also evaluated with respect to simulated soil moisture at anthesis and at grain maturity. Results using this approach were highly correlated with soil moisture results obtained from simulations based on the measured CLL values. This research provides strong evidence that the effects of SSCs on wheat yields are accounted for by the effects of these constraints on wheat CLL values. The study also produced two satisfactory methods for simulating the effects of SSCs on CLL and on grain yield. While Cl and ESP proved to be effective indices of SSCs, EC was not effective due to the confounding effect of the presence of gypsum in some of these soils. This study provides the tools necessary for investigating the effects of SSCs on wheat crop yields and natural resource management (NRM) issues such as runoff, recharge, and nutrient loss through simulation studies. It also facilitates investigation of suggested agronomic adaptations to SSCs

    Expression of Anthocyanins in Callus Cultures of Cranberry (\u3ci\u3eVaccinium macrocarpon Ait\u3c/i\u3e)

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    Expression of anthocyanins and other flavonoids in callus cultures established from different parts of cranberry plant was investigated and the effect of explant source on the in vitro product was determined. Callus cultures were initiated from different parts of the plant in a modified Gamborg\u27s medium with 5.37 μM α-naphthaleneacetic acid, 0.45 μM 2,4-dichlorophenoxyacetic acid, and 2.32 μM kinetin in the dark at 25°C. Callus cultures accumulated anthocyanins only on exposure to light and maximum concentration was observed by day 12. The cultures had lower levels of anthocyanins and only cyanidin 3-galactoside, cyanidin 3-glucoside, and cyanidin 3-arabinoside were identified in all cultures regardless of source of explant. Proanthocyanidin accumulation in cultures was independent of light, and levels were higher than in mature fruit. Exposure to light induced accumulation of flavonols and enhanced activity of phenylalanine ammonia-lyase in the cultures

    Evaluation of the APSIM modeling cropping systems of Asia

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    Not AvailableResource shortages, driven by climatic, institutional and social changes in many regions of Asia, combined with growing imperatives to increase food production whilst ensuring environmental sustainability, are driving research into modified agricultural practices. Well-tested cropping systems Models that capture interactions between soil water and nutrient dynamics, crop growth, climate and farmer management can assist in the evaluation of such new agricultural practices. One such cropping systems model is the Agricultural Production Systems Simulator (APSIM). We evaluated APSIM’s ability to simulate the performance of cropping systems in Asia from several perspectives: crop phenology, production, water use, soil dynamics (water and organic carbon) and crop CO2 response, as well as its ability to simulate cropping sequences without reset of soil variables. The evaluation was conducted over a diverse range of environments (12 countries, numerous soils), crops and management practices throughout the region. APSIM’s performance was statisticallyNot Availabl
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