30 resultados para Spring Wheat
em University of Queensland eSpace - Australia
Resumo:
Systems approaches can help to evaluate and improve the agronomic and economic viability of nitrogen application in the frequently water-limited environments. This requires a sound understanding of crop physiological processes and well tested simulation models. Thus, this experiment on spring wheat aimed to better quantify water x nitrogen effects on wheat by deriving some key crop physiological parameters that have proven useful in simulating crop growth. For spring wheat grown in Northern Australia under four levels of nitrogen (0 to 360 kg N ha(-1)) and either entirely on stored soil moisture or under full irrigation, kernel yields ranged from 343 to 719 g m(-2). Yield increases were strongly associated with increases in kernel number (9150-19950 kernels m(-2)), indicating the sensitivity of this parameter to water and N availability. Total water extraction under a rain shelter was 240 mm with a maximum extraction depth of 1.5 m. A substantial amount of mineral nitrogen available deep in the profile (below 0.9 m) was taken up by the crop. This was the source of nitrogen uptake observed after anthesis. Under dry conditions this late uptake accounted for approximately 50% of total nitrogen uptake and resulted in high (>2%) kernel nitrogen percentages even when no nitrogen was applied,Anthesis LAI values under sub-optimal water supply were reduced by 63% and under sub-optimal nitrogen supply by 50%. Radiation use efficiency (RUE) based on total incident short-wave radiation was 1.34 g MJ(-1) and did not differ among treatments. The conservative nature of RUE was the result of the crop reducing leaf area rather than leaf nitrogen content (which would have affected photosynthetic activity) under these moderate levels of nitrogen limitation. The transpiration efficiency coefficient was also conservative and averaged 4.7 Pa in the dry treatments. Kernel nitrogen percentage varied from 2.08 to 2.42%. The study provides a data set and a basis to consider ways to improve simulation capabilities of water and nitrogen effects on spring wheat. (C) 1997 Elsevier Science B.V.
Resumo:
Improvement of end-use quality in bread wheat depends on a thorough understanding of current wheat quality and the influences of genotype (G), environment (E), and genotype by environment interaction (G x E) on quality traits. Thirty-nine spring-sown spring wheat (SSSW) cultivars and advanced lines from China were grown in four agro-ecological zones comprising seven locations during the 1998 and 1999 cropping seasons. Data on 12 major bread-making quality traits were used to investigate the effect of G, E, and G x E on these traits. Wide range variability for protein quantity and quality, starch quality parameters and milling quality in Chinese SSSW was observed. Genotype and environment were found to significantly influence all quality parameters as major effects. Kernel hardness, flour yield, Zeleny sedimentation value and mixograph properties were mainly influenced by the genetic variance components, while thousand kernel weight, test weight, and falling number were mostly influenced by the environmental variance components. Genotype, environment, and their interaction had important effects on test weight, mixing development time and RVA parameters. Cultivars originating from Zone VI (northeast) generally expressed high kernel hardness, good starch quality, but poor milling and medium to weak mixograph performance; those from Zone VII (north) medium to good gluten and starch quality, but low milling quality; those from Zone VIII (central northwest) medium milling and starch quality, and medium to strong mixograph performance; those from Zone IX (western/southwestern Qinghai-Tibetan Plateau) medium milling quality, but poor gluten strength and starch parameters; and those from Zone X (northwest) high milling quality, strong mixograph properties, but low protein content. Samples from Harbin are characterized by good gluten and starch quality, but medium to poor milling quality; those from Hongxinglong by strong mixograph properties, medium to high milling quality, but medium to poor starch quality and medium to low protein content; those from Hohhot by good gluten but poor milling quality; those from Linhe by weak gluten quality, medium to poor milling quality; those from Lanzhou by poor bread-making and starch quality; those from Yongning by acceptable bread-making and starch quality and good milling quality; and those from Urumqi by good milling quality, medium gluten quality and good starch pasting parameters. Our findings suggest that Chinese SSSW quality could be greatly enhanced through genetic improvement for targeted well-characterized production environments.
Resumo:
Understanding the relationships among testing environments is essential for better targeting cultivars to production environments. To identify patterns of cultivar, environment, cultivar-by-environment interactions, and opportunities for indirect selection for grain yield, a set of 25 spring wheat cultivars from China and the International Maize and Wheat Improvement Center (CIMMYT) was evaluated in nine environments in China and four management environments at CIMMYT in Cd. Obregon, Mexico, during two wheat seasons. Genetic background and original environment were the main factors influencing grain yield performance of the cultivars. Baviacora M 92, Xinchun 2 and Xinchun 6 showed relatively more stable and higher grain yields, whereas highly photoperiod sensitive cultivars Xinkehan 9, Kefeng 6 and Longmai 19 proved consistently inferior across environments, except in Harbin and Keshan, the two high latitude environments. Longmai 26, also from high latitude environments in the northeastern Heilongjiang province, was however probably not as photoperiodicly sensitive as other cultivars; from that region, and produced much higher grain yield and expressed a broader adaptation. None of the environments reported major diseases. Pattern analyses revealed that photoperiod response and planting option on beds were the two main factors underlying the observed interactions for grain yield. The production environment of planting on the flat in Mexico grouped together with Huhhot and Urumqi in both wheat seasons, indicating an indirect response to selection for grain yield in this CIMMYT managed environment could benefit the two Chinese environments. Both the environment of planting on the flat with Chinese Hejin and Yongning, and the three CIMMYT enviromnents planting on raised beds with Chinese Yongning grouped together only in one season, showing that repeatability may not be stable in this case.
Resumo:
Improvement of processing quality is a very important objective for Chinese wheat breeding programs. Twenty-five CIMMYT and Chinese spring wheat cultivars were grown at four managed conditions by CIMMYT in Cd. Obregon, Sonora, Mexico and in nine environments in China, over two successive wheat seasons from 2000 to 2002. These trials were used to identify patterns of cultivar, environment and cultivar x environment interactions, and to determine opportunities for indirect selection for protein content and the protein-quality related parameter, SDS sedimentation (SDSS) value. The cultivar Inqalab 91 showed low levels of interaction with environments in the 2000-01 crop cycle for protein content, and expressed intermediate levels for both protein content and SDSS value, across most of the environments in both years. Longmai 26 had consistently high protein content and SDSS value across environments in both years, indicating that it is possible to breed cultivars expressing high yields with good protein properties. Cluster analyses revealed that cultivars grouped differently for protein content and SDSS value. Besides photoperiod, water availability appeared to influence the ranking of cultivars for protein content and SDSS value. Temperature and soil type may underlie the observed interactions for protein content, while temperature may also be a factor associated with interactions for SDSS value. The full irrigation managed environment in Mexico, with the cultivars sown on raised beds two months later than optimum and exposing them to late heat, clustered together with the Chinese environments Huhhot, Yongning, and Hejin in the 2000-01 season for SDSS value. This indicates that there is an opportunity to exploit indirect responses to selection in the CIMMYT management environments for SDSS value with relevance for China's spring wheat regions. However, there seemed little chance for positive indirect selection in CIMMYT's managed environments for China in regard to protein content, as environments clustered distinctly. Pattern analyses permitted a sensible and useful summary for this multi environment experiment, helping in understanding natural relationships and variations in cultivar performance among the various environment groups, and assisting in the structuring of environments.
Global adaptation of spring bread and durum wheat lines near-isogenic for major reduced height genes
Resumo:
The effect of major dwarfing genes, Rht-B1 and Rht-D1, in bread (Triticum aestivum L.) and durum (Triticum turgidum L. var. durum) wheats varies with environment. Six reduced-height near-isogenic spring wheat lines, included in the International Adaptation Trial (IAT), were grown in 81 trials around the world. Of the 56 IAT trials yielding > 3 Mg ha(-1), the mean yield of semidwarfs was significantly greater than tails in 54% of trials; in the 27 trials yielding < 3 Mg ha-1, semidwarfs were superior in only 24%. Sixteen pairs of semidwarf-tall near-isolines were grown in six managed drought environment trials (DETs) in northwestern Mexico. In these trials, semidwarfs outyielded talls in all but the most droughted environment (2.5 Mg ha(-1)). The effect of the height alleles varied with genetic background and environment. For both yield and height, variance components for allele and environment by allele interaction were larger than those for genetic background and genetic background by environment. Pattern analysis showed that tall and semidwarf lines had similar adaptation to stressed environments (< 2.8 Mg ha(-1), low rainfall), while semidwarfs yielded more in less stressed environments (> 4.3 Mg ha(-1), high rainfall). The best adapted near-isogenic pair had a Kauz background, where the tall was only 16% taller than the dwarf. In the Kauz-derived pair, the semidwarf outyielded the tall in only 13% of trials with no differences in low yielding trials. This supports the idea that '' short talls '' may be useful in marginal environments (yield < 3 Mg ha(-1)).
Resumo:
To simulate cropping systems, crop models must not only give reliable predictions of yield across a wide range of environmental conditions, they must also quantify water and nutrient use well, so that the status of the soil at maturity is a good representation of the starting conditions for the next cropping sequence. To assess the suitability for this task a range of crop models, currently used in Australia, were tested. The models differed in their design objectives, complexity and structure and were (i) tested on diverse, independent data sets from a wide range of environments and (ii) model components were further evaluated with one detailed data set from a semi-arid environment. All models were coded into the cropping systems shell APSIM, which provides a common soil water and nitrogen balance. Crop development was input, thus differences between simulations were caused entirely by difference in simulating crop growth. Under nitrogen non-limiting conditions between 73 and 85% of the observed kernel yield variation across environments was explained by the models. This ranged from 51 to 77% under varying nitrogen supply. Water and nitrogen effects on leaf area index were predicted poorly by all models resulting in erroneous predictions of dry matter accumulation and water use. When measured light interception was used as input, most models improved in their prediction of dry matter and yield. This test highlighted a range of compensating errors in all modelling approaches. Time course and final amount of water extraction was simulated well by two models, while others left up to 25% of potentially available soil water in the profile. Kernel nitrogen percentage was predicted poorly by all models due to its sensitivity to small dry matter changes. Yield and dry matter could be estimated adequately for a range of environmental conditions using the general concepts of radiation use efficiency and transpiration efficiency. However, leaf area and kernel nitrogen dynamics need to be improved to achieve better estimates of water and nitrogen use if such models are to be use to evaluate cropping systems. (C) 1998 Elsevier Science B.V.
Resumo:
Previous work has identified several short-comings in the ability of four spring wheat and one barley model to simulate crop processes and resource utilization. This can have important implications when such models are used within systems models where final soil water and nitrogen conditions of one crop define the starting conditions of the following crop. In an attempt to overcome these limitations and to reconcile a range of modelling approaches, existing model components that worked demonstrably well were combined with new components for aspects where existing capabilities were inadequate. This resulted in the Integrated Wheat Model (I_WHEAT), which was developed as a module of the cropping systems model APSIM. To increase predictive capability of the model, process detail was reduced, where possible, by replacing groups of processes with conservative, biologically meaningful parameters. I_WHEAT does not contain a soil water or soil nitrogen balance. These are present as other modules of APSIM. In I_WHEAT, yield is simulated using a linear increase in harvest index whereby nitrogen or water limitations can lead to early termination of grainfilling and hence cessation of harvest index increase. Dry matter increase is calculated either from the amount of intercepted radiation and radiation conversion efficiency or from the amount of water transpired and transpiration efficiency, depending on the most limiting resource. Leaf area and tiller formation are calculated from thermal time and a cultivar specific phyllochron interval. Nitrogen limitation first reduces leaf area and then affects radiation conversion efficiency as it becomes more severe. Water or nitrogen limitations result in reduced leaf expansion, accelerated leaf senescence or tiller death. This reduces the radiation load on the crop canopy (i.e. demand for water) and can make nitrogen available for translocation to other organs. Sensitive feedbacks between light interception and dry matter accumulation are avoided by having environmental effects acting directly on leaf area development, rather than via biomass production. This makes the model more stable across environments without losing the interactions between the different external influences. When comparing model output with models tested previously using data from a wide range of agro-climatic conditions, yield and biomass predictions were equal to the best of those models, but improvements could be demonstrated for simulating leaf area dynamics in response to water and nitrogen supply, kernel nitrogen content, and total water and nitrogen use. I_WHEAT does not require calibration for any of the environments tested. Further model improvement should concentrate on improving phenology simulations, a more thorough derivation of coefficients to describe leaf area development and a better quantification of some processes related to nitrogen dynamics. (C) 1998 Elsevier Science B.V.
Resumo:
Participatory plant breeding (PPB) has been suggested as an effective alternative to formal plant breeding (FPB) as a breeding strategy for achieving productivity gains under low input conditions. With genetic progress through PPB and FPB being determined by the same genetic variables, the likelihood of success of PPB approaches applied in low input target conditions was analyzed using two case studies from FPB that have resulted in significant productivity gains under low input conditions: (1) breeding tropical maize for low input conditions by CIMMYT, and (2) breeding of spring wheat for the highly variable low input rainfed farming systems in Australia. In both cases, genetic improvement was an outcome of long-term investment in a sustained research effort aimed at understanding the detail of the important environmental constraints to productivity and the plant requirements for improved adaptation to the identified constraints, followed up by the design and continued evaluation of efficient breeding strategies. The breeding strategies used differed between the two case studies but were consistent in their attention to the key determinants of response to selection: (1) ensuring adequate sources of genetic variation and high selection pressures for the important traits at all stages of the breeding program, (2) use of experimental procedures to achieve high levels of heritability in the breeding trials, and (3) testing strategies that achieved a high genetic correlation between performance of germplasm in the breeding trials and under on-farm conditions. The implications of the outcomes from these FPB case studies for realizing the positive motivations for adopting PPB strategies are discussed with particular reference for low input target environment conditions.
Resumo:
Pearl millet landraces from Rajasthan, India, yield significantly less than improved cultivars under optimum growing conditions, but not under stressed conditions. To successfully develop a simulation model for pearl millet, capable of capturing such genotype x environment (G x E) interactions for grain yield, we need to understand the causes of the observed yield interaction. The aim of this paper is to quantify the key parameters that determine the accumulation and partitioning of biomass: the,light extinction coefficient, radiation use efficiency (RUE), pattern of dry matter allocation to the leaf blades, the determination of grain number, and the rate and duration of dry matter accumulation into individual grains. We used data on improved cultivars and landraces, obtained from both published and unpublished sources collected at ICRISAT, Patancheru, India. Where possible, the effects of cultivar and axis (main shoot vs. tillers) on these parameters were analysed, as previous research suggested that G x E interactions for grain yield are associated with differences in tillering habit. Our results indicated there were no cultivar differences in extinction coefficient, RUE, and biomass partitioning before anthesis, and differences between axes in biomass partitioning were negligible. This indicates there was no basis for cultivar differences in the potential grain yield. Landraces, however, produced consistently less grain yield for a given rate of dry matter accumulation at anthesis than did improved cultivars. This was caused by a combination of low grain number and small grain size. The latter was predominantly due to a lower grain growth rate, as genotypic differences in the duration of grain filling were relatively small. Main shoot and tillers also had a similar duration of grain filling. The low grain yield of the landraces was associated with profuse nodal tillering, supporting the hypothesis that grain yield was below the potential yield that could be supported by assimilate availability. We hypothesise this is a survival strategy, which enhances the prospects to escape the effects of stress around anthesis. (C) 2002 E.J. van Oosterom. Published by Elsevier Science B.V. All rights reserved.
Resumo:
The Agricultural Production Systems slMulator, APSIM, is a cropping system modelling environment that simulates the dynamics of soil-plant-management interactions within a single crop or a cropping system. Adaptation of previously developed crop models has resulted in multiple crop modules in APSIM, which have low scientific transparency and code efficiency. A generic crop model template (GCROP) has been developed to capture unifying physiological principles across crops (plant types) and to provide modular and efficient code for crop modelling. It comprises a standard crop interface to the APSIM engine, a generic crop model structure, a crop process library, and well-structured crop parameter files. The process library contains the major science underpinning the crop models and incorporates generic routines based on physiological principles for growth and development processes that are common across crops. It allows APSIM to simulate different crops using the same set of computer code. The generic model structure and parameter files provide an easy way to test, modify, exchange and compare modelling approaches at process level without necessitating changes in the code. The standard interface generalises the model inputs and outputs, and utilises a standard protocol to communicate with other APSIM modules through the APSIM engine. The crop template serves as a convenient means to test new insights and compare approaches to component modelling, while maintaining a focus on predictive capability. This paper describes and discusses the scientific basis, the design, implementation and future development of the crop template in APSIM. On this basis, we argue that the combination of good software engineering with sound crop science can enhance the rate of advance in crop modelling. Crown Copyright (C) 2002 Published by Elsevier Science B.V. All rights reserved.
Resumo:
Eight milling quality and protein properties of autumn-sown Chinese wheats were investigated using 59 cultivars and advanced lines grown in 14 locations in China from 1995 to 1998. Wide ranges of variability for all traits were observed across genotypes and locations. Genotype, location, year, and their interactions all significantly influenced most of the quality parameters. Kernel hardness, Zeleny sedimentation value, and mixograph development time were predominantly influenced by the effects of genotype. Genotype, location and genotype x location interaction were all important sources of variation for thousand kernel weight, test weight, protein content, and falling number, whereas genotype x location interaction had the largest effect on flour yield. Most of the genotypes were characterized by weak gluten strength with Zeleny sedimentation values less than 40 ml and mixograph development time shorter than 3 min. Eight groups of genotypes were recognized based on the average quality performance, grain hardness and gluten strength were the two parameters that determined the grouping, with contributions from protein content. Genotypes such as Zhongyou 16 and Annong 8903 displayed good milling quality, high grain hardness, protein content and strong gluten strength with high sedimentation value and long mixograph development time. Genotypes such as Lumai 15 and Yumai 18 were characterized by low grain hardness, protein content and weak gluten strength. Genotypes such as Yannong 15 and Chuanmai 24 were characterized by strong gluten strength with high sedimentation value and long mixograph development time, but low grain hardness and protein content lower than 12.3%. Genotypes such as Jingdong 6 and Xi'an 8 had weak gluten strength, but with high grain hardness and protein content higher than 12.2%. Five groups of locations were identified, and protein content and gluten strength were the two parameters that determined the grouping. Beijing, Shijiazhuang, Nanyang, Zhumadian and Nanjing produced wheats with medium to strong gluten strength and medium protein content, although there was still a large variation for most of the traits investigated between the locations. Wheat produced in Yantai was characterized by strong gluten strength, but with low protein content. Jinan, Anyang and Linfen locations produced wheats with medium to weak gluten strength and medium to high protein content. Wheats produced in Yangling, Zhenzhou, and Chengdu were characterized by weak gluten strength with medium to low protein content, whereas wheats produced in Xuzhou and Wuhan were characterized by weak gluten strength with low protein content. Industrial grain quality could be substantially improved through integrating knowledge of geographic genotype distribution with key location variables that affected end-use quality.
Resumo:
There is evidence that high-tillering, small-panicled pearl millet landraces are better adapted to the severe, unpredictable drought stress of the and zones of NW India than are low-tillering, large-panicled modern varieties, which significantly outyield the landraces under favourable conditions. In this paper, we analyse the relationship of and zone adaptation with the expression, under optimum conditions, of yield components that determine either the potential sink size or the ability to realise this potential. The objective is to test whether selection under optimal conditions for yield components can identify germplasm with adaptation to and zones in NW India, as this could potentially improve the efficiency of pearl millet improvement programs targeting and zones. We use data from an evaluation of over 100 landraces from NW India, conducted for two seasons under both severely drought-stressed and favourable conditions in northwest and south India. Trial average grain yields ranged from 14 g m(-2) to 182 g m(-2). The landraces were grouped into clusters, based on their phenology and yield components as measured under well-watered conditions in south India. In environments without pre-flowering drought stress, tillering type had no effect on potential sink size, but low-tillering, large-panicled landraces yielded significantly more grain, as they were better able to realise their potential sink size. By contrast, in two low-yielding and zone environments which experienced pre-anthesis drought stress, low-fillering, large-panicled landraces yielded significantly less grain than high-tillering ones with comparable phenology, because of both a reduced potential sink size and a reduced ability to realise this potential. The results indicate that the high grain yield of low-tillering, large-panicled landraces under favourable conditions is due to improved partitioning, rather than resource capture. However, under severe stress with restricted assimilate supply, high-tillering, small-panicled landraces are better able to produce a reproductive sink than are large-panicled ones. Selection under optimum conditions for yield components representing a resource allocation pattern favouring high yield under severe drought stress, combined with a capability to increase grain yield if assimilates are available, was more effective than direct selection for grain yield in identifying germplasm adapted to and zones. Incorporating such selection in early generations of variety testing could reduce the reliance on random stress environments. This should improve the efficiency of millet breeding programs targeting and zones. (c) 2005 Elsevier B.V. All rights reserved.
Resumo:
Serious infestations of Helicoverpa punctigera are experienced yearly in the eastern cropping regions of Australia. Regression analysis was used to determine whether the size of the first generation in spring (G(1)), which is comprised mostly of immigrants from inland Australia, was related to monthly rainfall in inland winter breeding areas. Data from two long series of light-trap catches at Narrabri in New South Wales (NSW) and Turretfield in South Australia (SA) were used in the analyses. The size of G1 at Narrabri in each year was significantly regressed on the amount of rainfall in western Queensland and NSW in May and June. The size of G1 at Turretfield each year was significantly regressed on the amount of rain in May, June and July in western Queensland and NSW and also in the desert of central Western Australia. Low r(2) values of the regressions suggest that rainfall data for more sites, as well as biological and other physical factors, such as temperature, evaporation, and prevailing wind systems, may need to be included to improve forecasts of the potential magnitude of the infestations in coastal cropping regions.
Resumo:
Under certain soil conditions, e.g. hardsetting clay B-horizons of South-Eastern Australia, wheat plants do not perform as well as would be expected given measurements of bulk soil attributes. In such soils, measurement indicates that a large proportion (80%) of roots are preferentially located in the soil within 1 mm of macropores. This paper addresses the question of whether there are biological and soil chemical effects concomitant with this observed spatial relationship. The properties of soil manually dissected from the 1-3 mm wide region surrounding macropores, the macropore sheath, were compared to those that are measured in a conventional manner on the bulk soil. Field specimens of two different soil materials were dissected to examine biological differentiation. To ascertain whether the macropore sheath soil differs from rhizosphere soil, wheat was grown in structured and repacked cores under laboratory conditions. The macropore sheath soil contained more microbial biomass per unit mass than both the bulk soil and the rhizosphere. The bacterial population in the macropore sheath was able to utilise a wider range of carbon substrates and to a greater extent than the bacterial population in the corresponding bulk soil. These differences between the macropore sheath and bulk soil were almost non-existent in the repacked cores. Evidence for larger numbers of propagules of the broad host range fungus Pythium in the macropore sheath soil were also obtained.
Resumo:
A model of Australian wheat grower supply response was specified under the constraints of price and yield uncertainty, risk aversion, partial adjustment, and quadratic costs. The model was solved to obtain area planted. The results of estimation indicate that risk arising from prices and climate have had a significant influence on producer decision making. The coefficient of relative risk aversion and short-run and long-run elasticities of supply with respect to price were calculated. Wheat growers' risk premium, expected at the start of the season for exposed price and yield risk, was 2.8 percent of revenue or 10.4 percent of profit as measured by producer surplus. (C) 2000 John Wiley & Sons, Inc.