994 resultados para Crop residue


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Many modelling studies examine the impacts of climate change on crop yield, but few explore either the underlying bio-physical processes, or the uncertainty inherent in the parameterisation of crop growth and development. We used a perturbed-parameter crop modelling method together with a regional climate model (PRECIS) driven by the 2071-2100 SRES A2 emissions scenario in order to examine processes and uncertainties in yield simulation. Crop simulations used the groundnut (i.e. peanut; Arachis hypogaea L.) version of the General Large-Area Model for annual crops (GLAM). Two sets of GLAM simulations were carried out: control simulations and fixed-duration simulations, where the impact of mean temperature on crop development rate was removed. Model results were compared to sensitivity tests using two other crop models of differing levels of complexity: CROPGRO, and the groundnut model of Hammer et al. [Hammer, G.L., Sinclair, T.R., Boote, K.J., Wright, G.C., Meinke, H., and Bell, M.J., 1995, A peanut simulation model: I. Model development and testing. Agron. J. 87, 1085-1093]. GLAM simulations were particularly sensitive to two processes. First, elevated vapour pressure deficit (VPD) consistently reduced yield. The same result was seen in some simulations using both other crop models. Second, GLAM crop duration was longer, and yield greater, when the optimal temperature for the rate of development was exceeded. Yield increases were also seen in one other crop model. Overall, the models differed in their response to super-optimal temperatures, and that difference increased with mean temperature; percentage changes in yield between current and future climates were as diverse as -50% and over +30% for the same input data. The first process has been observed in many crop experiments, whilst the second has not. Thus, we conclude that there is a need for: (i) more process-based modelling studies of the impact of VPD on assimilation, and (ii) more experimental studies at super-optimal temperatures. Using the GLAM results, central values and uncertainty ranges were projected for mean 2071-2100 crop yields in India. In the fixed-duration simulations, ensemble mean yields mostly rose by 10-30%. The full ensemble range was greater than this mean change (20-60% over most of India). In the control simulations, yield stimulation by elevated CO2 was more than offset by other processes-principally accelerated crop development rates at elevated, but sub-optimal, mean temperatures. Hence, the quantification of uncertainty can facilitate relatively robust indications of the likely sign of crop yield changes in future climates. (C) 2007 Elsevier B.V. All rights reserved.

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This paper examines to what extent crops and their environment should be viewed as a coupled system. Crop impact assessments currently use climate model output offline to drive process-based crop models. However, in regions where local climate is sensitive to land surface conditions more consistent assessments may be produced with the crop model embedded within the land surface scheme of the climate model. Using a recently developed coupled crop–climate model, the sensitivity of local climate, in particular climate variability, to climatically forced variations in crop growth throughout the tropics is examined by comparing climates simulated with dynamic and prescribed seasonal growth of croplands. Interannual variations in land surface properties associated with variations in crop growth and development were found to have significant impacts on near-surface fluxes and climate; for example, growing season temperature variability was increased by up to 40% by the inclusion of dynamic crops. The impact was greatest in dry years where the response of crop growth to soil moisture deficits enhanced the associated warming via a reduction in evaporation. Parts of the Sahel, India, Brazil, and southern Africa were identified where local climate variability is sensitive to variations in crop growth, and where crop yield is sensitive to variations in surface temperature. Therefore, offline seasonal forecasting methodologies in these regions may underestimate crop yield variability. The inclusion of dynamic crops also altered the mean climate of the humid tropics, highlighting the importance of including dynamical vegetation within climate models.

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The combined use of organic residue and inorganic fertiliser-phosphorus (P) is appropriate in meeting both the short and long-term P requirement of crops. To assess the influence of added inorganic fertiliser-P on the processes of decomposition and P release from the residue and the relationships with quality, prunings of Gliricidia sepium, Leucaena leucocephela, Senna siamea, Acacia mangium and Paraserienthus falcataria were incubated without and with added inorganic fertiliser-P for 56 days. Soil was added only as inoculum. Decomposition rate and amounts of acid extractable-P (P release) were in the same order: G. sepium > S. siamea > L. leucocepheta > P falcataria > A. mangium. Unlike the other residues, A. mangium released no P despite the loss of half its mass during the 8 weeks of incubation. The residue P content correlated with P release. However, decomposition rate did not correlate with residue P content but with the lignin, polyphenol and cellulose content, and ratios to P. These ratios were negatively correlated with P release suggesting that lignin and polyphenol contents influence P release more when the residue-P content is low. Results suggest that rate of decomposition influences the release of P. The critical residue P content for P release was estimated to be 0.12% < P < 0.19%. Added P had no effect on decomposition and P release from the residues.

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A dual isotopic technique was used to assess the effects of soil type, and residues of Gliricidia sepium, without and with added fertiliser-P on the utilisation of P. Upland rice (Oryza sativa) was grown for 70 days in two tropical acid soils of different P sorbing capacity and P status. Uniformly P-32-labelled soils were treated with inorganic fertiliser-P tagged with P-33, Gliricidia sepium residue applied at planting and 3 weeks earlier, and in a combination of fertiliser-P and Gliricidia applied at and 3 weeks before planting. There were significant responses of shoot and root weights, and total P uptake to Gliricidia- and/or fertiliser-P addition in the Ultisol (low P status) but not the Oxisol (high P status), suggesting that P in the latter soil was not yield limiting, despite the high standard P requirement. Similarly, incorporation of Gliricidia three weeks before planting further increased shoot weight only in the Ultisol. There were generally higher proportions, quantities and percent utilisations of the Gliricidia- P and fertiliser-P in the Ultisol than in the Oxisol. Gliricidia significantly increased the utilisation of fertiliser-P only in the Ultisol. However, early application of Gliricidia increased Gliricidia- P but not fertiliser-P utilisation in the Ultisol. Added fertiliser-P did not influence Gliricidia- P utilisation.

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In the continuing debate over the impact of genetically modified (GM) crops on farmers of developing countries, it is important to accurately measure magnitudes such as farm-level yield gains from GM crop adoption. Yet most farm-level studies in the literature do not control for farmer self-selection, a potentially important source of bias in such estimates. We use farm-level panel data from Indian cotton farmers to investigate the yield effect of GM insect-resistant cotton. We explicitly take into account the fact that the choice of crop variety is an endogenous variable which might lead to bias from self-selection. A production function is estimated using a fixed-effects model to control for selection bias. Our results show that efficient farmers adopt Bacillus thuringiensis (Bt) cotton at a higher rate than their less efficient peers. This suggests that cross-sectional estimates of the yield effect of Bt cotton, which do not control for self-selection effects, are likely to be biased upwards. However, after controlling for selection bias, we still find that there is a significant positive yield effect from adoption of Bt cotton that more than offsets the additional cost of Bt seed.

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RothC and Century are two of the most widely used soil organic matter (SOM) models. However there are few examples of specific parameterisation of these models for environmental conditions in East Africa. The aim of this study was therefore, to evaluate the ability of RothC and the Century to estimate changes in soil organic carbon (SOC) resulting from varying land use/management practices for the climate and soil conditions found in Kenya. The study used climate, soils and crop data from a long term experiment (1976-2001) carried out at The Kabete site at The Kenya National Agricultural Research Laboratories (NARL, located in a semi-humid region) and data from a 13 year experiment carried out in Machang'a (Embu District, located in a semi-arid region). The NARL experiment included various fertiliser (0, 60 and 120 kg of N and P2O5 ha(-1)), farmyard manure (FYM - 5 and 10 t ha(-1)) and plant residue treatments, in a variety of combinations. The Machang'a experiment involved a fertiliser (51 kg N ha(-1)) and a FYM (0, 5 and 10 t ha(-1)) treatment with both monocropping and intercropping. At Kabete both models showed a fair to good fit to measured data, although Century simulations for treatments with high levels of FYM were better than those without. At the Machang'a site with monocrops, both models showed a fair to good fit to measured data for all treatments. However, the fit of both models (especially RothC) to measured data for intercropping treatments at Machang'a was much poorer. Further model development for intercrop systems is recommended. Both models can be useful tools in soil C Predictions, provided time series of measured soil C and crop production data are available for validating model performance against local or regional agricultural crops. (C) 2007 Elsevier B.V. All rights reserved.

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The sustainability of cereal/legume intercropping was assessed by monitoring trends in grain yield, soil organic C (SOC) and soil extractable P (Olsen method) measured over 13 years at a long-term field trial on a P-deficient soil in semi-arid Kenya. Goat manure was applied annually for 13 years at 0, 5 and 10 t ha(-1) and trends in grain yield were not identifiable because of season-to-season variations. SOC and Olsen P increased for the first seven years of manure application and then remained constant. The residual effect of manure applied for four years only lasted another seven to eight years when assessed by yield, SOC and Olsen P. Mineral fertilizers provided the same annual rates of N and P as in 5 t ha(-1) manure and initially ,gave the same yield as manure, declining after nine years to about 80%. Therefore, manure applications could be made intermittently and nutrient requirements topped-up with fertilizers. Grain yields for sorghum with continuous manure were described well by correlations with rainfall and manure input only, if data were excluded for seasons with over 500 mm rainfall. A comprehensive simulation model should correctly describe crop losses caused by excess water.

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This review evaluates evidence of the impact of uncomposted plant residues, composts, manures, and liquid preparations made from composts (compost extracts and teas) on pest and disease incidence and severity in agricultural and horticultural crop production. Most reports on pest control using such organic amendments relate to tropical or and climates. The majority of recent work on the use of organic amendments for prevention and control of diseases relates to container-produced plants, particularly ornamentals. However, there is growing interest in the potential for using composts to prevent and control diseases in temperate agricultural and horticultural field crops and information concerning their use and effectiveness is slowly increasing. The impact of uncomposted plant residues, composts, manures, and compost extracts/teas on pests and diseases is discussed in relation to sustainable temperate field and protected cropping systems. The factors affecting efficacy or such organic amendments in preventing and controlling pests and disease are examined and the mechanisms through which control is achieved are described.

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Crop irrigation has long been recognized as having been important for the evolution of social complexity in several parts of the world. Structural evidence for water management, as in the form of wells, ditches and dams, is often difficult to interpret and may be a poor indicator of past irrigation that may have had no need for such constructions. It would be of considerable value, therefore, to be able to infer past irrigation directly from archaeo-botanical remains, and especially the type of archaeo-botanical remains that are relatively abundant in the archaeological record, such as phytoliths. Building on the pioneering work of Rosen and Wiener (1994), this paper describes a crop-growing experiment designed to explore the impact of irrigation on the formation of phytoliths within cereals. If it can be shown that a systemic and consistent relationship exists between phytolith size, structure and the intensity of irrigation, and if various taphonomic and palaeoenvironmental processes can be controlled for, then the presence of past irrigation can feasibly be inferred from the phytoliths recovered from the archaeological record.

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This paper presents the results of (a) On-farm trials (eight) over a two-year period designed to test the effectiveness of leguminous cover crops in terms of increasing maize yields in Igalaland, Nigeria. (b) A survey designed to monitor the extent of, and reasons behind, adoption of the leguminous cover crop technology in subsequent years by farmers involved, to varying degrees, in the trial programme. particular emphasis was placed on comparing adoption of leguminous cover crops with that of new crop varieties released by a non-governmental organization in the same area since the mid 1980s. While the leguminous cover crop technology boosted maize grain yields by 127 to 136% above an untreated control yield of between 141 and 171 kg ha(-1), the adoption rate (number of farmers adopting) was only 18%. By way of contrast, new crop varieties had a highly variable benefit in terms of yield advantage over local varieties, with the best average increase of around 20%. Adoption rates for new crop varieties, assessed as both the number of farmers growing the varieties and the number of plots planted to the varieties, were 40% on average. The paper discusses some key factors influencing adoption of the leguminous cover crop technology, including seed availability. Implications of these results for a local non-governmental organization, the Diocesan Development Services, concerned with promoting the leguminous cover crop technology are also discussed.

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Technology involving genetic modification of crops has the potential to make a contribution to rural poverty reduction in many developing countries. Thus far, pesticide-producing Bacillus thuringensis (Bt) varieties of cotton have been the main GM crops under cultivation in developing nations. Several studies have evaluated the farm-level performance of Bt varieties in comparison to conventional ones by estimating production technology, and have mostly found Bt technology to be very successful in raising output and/or reducing pesticide input. However, the production risk properties of this technology have not been studied, although they are likely to be important to risk-averse smallholders. This study investigates the output risk aspects of Bt technology by estimating two 'flexible risk' production function models allowing technology to independently affect the mean and higher moments of output. The first is the popular Just-Pope model and the second is a more general 'damage control' flexible risk model. The models are applied to cross-sectional data on South African smallholders, some of whom used Bt varieties. The results show no evidence that a 'risk-reduction' claim can be made for Bt technology. Indeed, there is some evidence to support the notion that the technology increases output risk, implying that simple (expected) profit computations used in past evaluations may overstate true benefits.