Caractérisation et évaluation de textiles antifongiques

Hypothèse: L’impression sur textile d’une formulation de microparticules lipidiques avec un principe actif (éconazole nitrate) permet de conserver ou d’améliorer son activité pharmaceutique ex vivo et in vitro. Méthode: Une formulation de microparticules d’éconazole nitrate (ECN) a été formulée par homogénéisation à haut cisaillement, puis imprimée sur un textile LayaTM par une méthode de sérigraphie. La taille des microparticules, la température de fusion des microparticules sur textile et la teneur en éconazole du tissu ont été déterminées. La stabilité de la formulation a été suivie pendant 4 mois à 25°C avec 65% humidité résiduelle (RH). L’activité in vitro des textiles pharmaceutiques a été mesurée et comparée à la formulation commerciale 1% éconazole nitrate (w/w) sur plusieurs espèces de champignons dont le C. albicans, C. glabrata, C. kefyr, C. luminisitae, T. mentagrophytes et T. rubrum. La thermosensibilité des formulations a été étudiée par des tests de diffusion in vitro en cellules de Franz. L’absorption cutanée de l’éconazole a été évaluée ex vivo sur la peau de cochon. Résultats: Les microparticules d’éconazole avaient des tailles de 3.5±0.1 μm. La température de fusion était de 34.8°C. La thermosensibilité a été déterminée par un relargage deux fois supérieur à 32°C comparés à 22°C sur 6 heures. Les textiles ont présenté une teneur stable pendant 4 mois. Les textiles d’ECN in vitro ont démontré une activité similaire à la formulation commerciale sur toutes ii espèces de Candida testées, ainsi qu’une bonne activité contre les dermatophytes. La diffusion sur peau de cochon a démontré une accumulation supérieure dans le stratum corneum de la formulation textile par rapport à la formulation Pevaryl® à 1% ECN. La thermo-sensibilité de la formulation a permis un relargage sélectif au contact de la peau, tout en assurant une bonne conservation à température ambiante.

Effects of fertility management strategies on phosphorus bioavailability in four West African soils

Low phosphorus (P) in acid sandy soils of the West African Sudano-Sahelian zone is a major limitation to crop growth. To compare treatment effects on total dry matter (TDM) of crops and plant available P (P-Bray and isotopically exchangeable P), field experiments were carried out for 2 years at four sites where annual rainfall ranged from 560 to 850 mm and topsoil pH varied between 4.2 and 5.6. Main treatments were: (i) crop residue (CR) mulch at 500 and 2000 kg ha^-1, (ii) eight different rates and sources of P and (iii) cereal/legume rotations including millet (Pennisetum glaucum L.), sorhum [Sorghum bicolor (L.) Moench], cowpea (Vigna unguiculata Walp.) and groundnut (Arachis hypogaea L.). For the two Sahelian sites with large CR-induced differences in TDM, mulching did not modify significantly the soils' buffering capacity for phosphate ions but led to large increases in the intensity factor (C_p) and quantity of directly available soil P (E_1min). In the wetter Sudanian zone lacking effects of CR mulching on TDM mirrored a decline of E_1min with CR. Broadcast application of soluble single superphosphate (SSP) at 13 kg P ha^-1 led to large increases in C_p and quantity of E_1min at all sites which translated in respective TDM increases. The high agronomic efficiency of SSP placement (4 kg P ha^-1) across sites could be explained by consistent increases in the quantity factor which confirms the power of the isotopic exchange method in explaining management effects on crop growth across the region.

Efficient phosphorus application strategies for increased crop production in sub-Saharan West Africa

Comparable data are lacking from the range of environments found in sub-Saharan West Africa to draw more general conclusions about the relative merits of locally available rockphosphate (RockP) in alleviating phosphorus (P) constraints to crop growth. To fill this gap, a multi-factorial field experiment was conducted over 4 years at eight locations in Niger, Burkina Faso and Togo. These ranged in annual rainfall from 510 to 1300 mm. Crops grown were pearl millet (Pennisetum glaucum L.), sorghum (Sorghum bicolor (L.) Moench) and maize (Zea mays L.) either continuously or in rotation with cowpea (Vigna unguiculata Walp.) and groundnut (Arachis hypogaea L.). Crops were subjected to six P fertiliser treatments comprising RockP and soluble P at different rates and combined with 0 and 60 kg N ha^-1. For legumes, time trend analyses showed P-induced total dry matter (TDM) increases between 28 and 72% only with groundnut. Similarly, rotation-induced raises in cereal TDM compared to cereal monoculture were only observed with groundnut. For cereals, at the same rate of application, RockP was comparable to single superphosphate (SSP) only at two millet sites with topsoil pH-KCl <4.2 and annual average rainfall >600 mm. Across the eight sites NPK placement at 0.4 g P per hill raised average cereal yields between 26 and 220%. This was confirmed in 119 on-farm trials revealing P placement as a promising strategy to overcome P deficiency as the regionally most growth limiting nutrient constraint to cereals.

Causes of legume-rotation effects in increasing cereal yields across the Sudanian, Sahelian and Guinean zone of West Africa

On-farm experiments and pot trials were conducted on eight West African soils to explore the mechanisms governing the often reported legume rotation-induced cereal growth increases in this region. Crops comprised pearl millet (Pennisetum glaucum L.), sorghum (Sorghum bicolor Moench), maize (Zea mays L.), cowpea (Vigna unguiculata Walp.) and groundnut (Arachis hypogaea L.). In groundnut trials the observed 26 to 85% increases in total dry matter (TDM) of rotation cereals (RC) compared with continuous cereals (CC) in the 4th year appeared to be triggered by site- and crop-specific early season differences in nematode infestation (up to 6-fold lower in RC than in CC), enhanced Nmin and a 7% increase in mycorrhizal (AM) infection. In cowpea trials yield effects on millet and differences in nematode numbers, Nmin and AM were much smaller. Rhizosphere studies indicated effects on pH and acid phosphatase activity as secondary causes for the observed growth differences between RC and CC. In the study region legume-rotation effects on cereals seemed to depend on the capability of the legume to suppress nematodes and to enhance early N and P availability for the subsequent cereal.

Cereal/legume rotation effects on rhizosphere bacterial community structure in West African soils

The increased use of cereal/legume crop rotation has been advocated as a strategy to increase cereal yields of subsistence farmers in West Africa, and is believed to promote changes in the rhizosphere that enhance early plant growth. In this study we investigated the microbial diversity of the rhizoplane from seedlings grown in two soils previously planted to cereal or legume from experimental plots in Gaya, Niger, and Kaboli, Togo. Soils from these legume rotation and continuous cereal plots were placed into containers and sown in a growth chamber with maize (Zea mays L.), millet (Pennisetum glaucum L.), sorghum (Sorghum bicolor L. Moench.), cowpea (Vigna unguiculata L.) or groundnut (Arachis hypogaea L.). At 7 and 14 days after sowing, 16S rDNA profiles of the eubacterial and ammoniaoxidizing communities from the rhizoplane and bulk soil were generated using denaturing gradient gel electrophoresis (DGGE). Community profiles were subjected to peak fitting analyses to quantify the DNA band position and intensities, after which these data were compared using correspondence and principal components analysis. The data showed that cropping system had a highly significant effect on community structure (p <0.005), irrespective of plant species or sampling time. Continuous cereal-soil grown plants had highly similar rhizoplane communities across crop species and sites, whereas communities from the rotation soil showed greater variability and clustered with respect to plant species. Analyses of the ammonia-oxidizing communities provided no evidence of any effects of plant species or management history on ammonia oxidizers in soil from Kaboli, but there were large shifts with respect to this group of bacteria in soils from Gaya. The results of these analyses show that crop rotation can cause significant shifts in rhizosphere bacterial communities.

Growth and yield of groundnut, sesame and roselle in an Acacia senegal agroforestry system in North Kordofan, Sudan

A field experiment was conducted under rainfed conditions in western Sudan at El-Obeid Research Farm and Eldemokeya Forest Reserve, North Kordofan State, during the growing seasons 2004/05 and 2005/06. The main objective was to investigate the soil physical and chemical properties and yield of groundnut (Arachis hypogea), sesame (Sesamum indicum) and roselle (Hibiscus sabdariffa) of an Acacia senegal agroforestry system in comparison with the sole cropping system. Data were recorded for soil physical and chemical properties, soil moisture content, number of pods per plant, fresh weight (kg ha^−1) and crop yield (kg ha^−1). The treatments were arranged in Randomized Complete Block Design (RCBD) and replicated four times. Significant differences (P < 0.05) were obtained for sand and silt content on both sites, while clay content was not significantly different on both sites. The nitrogen (N) and organic carbon were significantly (P < 0.05) higher in the intercropping system in Eldemokeya Forest Reserve compared with sole cropping. Soil organic carbon, N and pH were not significant on El-Obeid site. Yet the level of organic carbon, N, P and pH was higher in the intercropping system. Fresh weight was significantly different on both sites. The highest fresh weight was found in the intercropping system. Dry weights were significantly different for sesame and roselle on both sites, while groundnut was not significantly different. On both sites intercropping systems reduced groundnut, sesame and roselle yields by 26.3, 12 and 20.2%, respectively. The reduction in yield in intercropping plots could be attributed to high tree density, which resulted in water and light competition between trees and the associated crops.

Leguminous cover crops differentially affect maize yields in three contrasting soil types of Kakamega, Western Kenya

Maize production in smallholder farming systems in Kenya is largely limited by low soil fertility. As mineral fertilizer is expensive, green manuring using leguminous cover crops could be an alternative strategy for farmers to enhance farm productivity. However due to variability in soil type and crop management, the effects of green manure are likely to differ with farms. The objectives of this study were to evaluate Mucuna pruriens and Arachis pintoi on (i) biomass and nitrogen fixation (^15N natural abundance), (ii) soil carbon and nitrogen stocks and (iii) their effects on maize yields over two cropping seasons in Kakamega, Western Kenya. Mucuna at 6 weeks accumulated 1–1.3 Mg ha^{-1} of dry matter and 33–56 kg ha^{-1} nitrogen of which 70% was nitrogen derived from the atmosphere (Ndfa). Arachis after 12 months accumulated 2–2.7 Mg ha^{-1} of dry matter and 51–74 kg N ha^{-1} of which 52-63 % was from Ndfa. Soil carbon and nitrogen stocks at 0–15 cm depth were enhanced by 2-4 Mg C ha^{-1} and 0.3–1.0 Mg N ha^{-1} under Mucuna and Arachis fallow, irrespective of soil type. Maize yield increased by 0.5-2 Mg ha^{-1} in Mucuna and 0.5–3 Mg ha^{-1} in Arachis and the response was stronger on Nitisol than on Acrisol or Ferralsol. We concluded that leguminous cover crops seem promising in enhancing soil fertility and maize yields in Kenya, provided soil conditions and rainfall are suitable.

Crop yield reduction in the tropics under climate change: Processes and uncertainties

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.

Acid-base reactions between an acidic soil and plant residues

The elemental composition of residues of maize (Zea mays), sorghum (S. bicolor), groundnuts (Arachis hypogea), soya beans (Glycine max), leucaena (L. leucocephala), gliricidia (G. sepium), and sesbania (S. sesban) was determined as a basis for examining their alkalinity when incorporated into an acidic Zambian Ferralsol. Potential (ash) alkalinity, available alkalinity by titration to pH 4 and soluble alkalinity (16 It water extract titrated to pH 4) were measured. Potential alkalinity ranged from 3 73 (maize) to 1336 (groundnuts) mmol kg(-1) and was equivalent to the excess of their cation charge over inorganic anion charge. Available alkalinity was about half the potential alkalinity. Cations associated with organic anions are the source of alkalinity. About two thirds of the available alkalinity is soluble. Residue buffer curves were determined by titration with H2SO4 to pH 4. Soil buffer capacity measured by addition of NaOH was 12.9 mmol kg(-1) pH(-1). Soil and residue (10 g:0.25 g) were shaken in solution for 24 h and suspension pH values measured. Soil pH increased from 4.3 to between 4.6 (maize) and 5.2 (soyabean) and the amounts of acidity neutralized (calculated from the rise in pH and the soil buffer capacity) were between 3.9 and 11.5 mmol kg(-1), respectively. The apparent base contributions by the residues (calculated from the buffer curves and the fall in pH) ranged between 105 and 350 mmol kg(-1) of residue, equivalent to 2.6 and 8.8 mmol kg(-1) of soil, respectively. Therefore, in contact with soil acidity, more alkalinity becomes available than when in contact with H2SO4 solution. Available alkalinity (to pH 4) would be more than adequate to supply that which reacts with soil but soluble alkalinity would not. It was concluded that soil Al is able to displace cations associated with organic anions in the residues which are not displaced by H+, or that residue decomposition may have begun in the soil suspension releasing some of the non-available alkalinity. Soil and four of the residues were incubated for 100 days and changes in pH, NH4+ and NO3- concentrations measured. An acidity budget equated neutralized soil acidity with residue alkalinity and base or acid produced by N transformations. Most of the potential alkalinity of soyabean and leucaena had reacted after 14 days, but this only occurred after 100 days for gliricidia, and for maize only the available alkalinity reacted. For gliricidia and leucaena, residue alkalinity was primarily used to react with acidity produced by nitrification. Thus, the ability of residues to ameliorate acidity depends not only on their available and potential alkalinity but also on their potential to release mineral N. (C) 2004 Elsevier B.V. All rights reserved.

Probabilistic simulations of crop yield over western India using the DEMETER seasonal hindcast ensembles

Process-based integrated modelling of weather and crop yield over large areas is becoming an important research topic. The production of the DEMETER ensemble hindcasts of weather allows this work to be carried out in a probabilistic framework. In this study, ensembles of crop yield (groundnut, Arachis hypogaea L.) were produced for 10 2.5 degrees x 2.5 degrees grid cells in western India using the DEMETER ensembles and the general large-area model (GLAM) for annual crops. Four key issues are addressed by this study. First, crop model calibration methods for use with weather ensemble data are assessed. Calibration using yield ensembles was more successful than calibration using reanalysis data (the European Centre for Medium-Range Weather Forecasts 40-yr reanalysis, ERA40). Secondly, the potential for probabilistic forecasting of crop failure is examined. The hindcasts show skill in the prediction of crop failure, with more severe failures being more predictable. Thirdly, the use of yield ensemble means to predict interannual variability in crop yield is examined and their skill assessed relative to baseline simulations using ERA40. The accuracy of multi-model yield ensemble means is equal to or greater than the accuracy using ERA40. Fourthly, the impact of two key uncertainties, sowing window and spatial scale, is briefly examined. The impact of uncertainty in the sowing window is greater with ERA40 than with the multi-model yield ensemble mean. Subgrid heterogeneity affects model accuracy: where correlations are low on the grid scale, they may be significantly positive on the subgrid scale. The implications of the results of this study for yield forecasting on seasonal time-scales are as follows. (i) There is the potential for probabilistic forecasting of crop failure (defined by a threshold yield value); forecasting of yield terciles shows less potential. (ii) Any improvement in the skill of climate models has the potential to translate into improved deterministic yield prediction. (iii) Whilst model input uncertainties are important, uncertainty in the sowing window may not require specific modelling. The implications of the results of this study for yield forecasting on multidecadal (climate change) time-scales are as follows. (i) The skill in the ensemble mean suggests that the perturbation, within uncertainty bounds, of crop and climate parameters, could potentially average out some of the errors associated with mean yield prediction. (ii) For a given technology trend, decadal fluctuations in the yield-gap parameter used by GLAM may be relatively small, implying some predictability on those time-scales.

Quantifying uncertainty in the simulation of crop-climate processes

The impacts of climate change on crop productivity are often assessed using simulations from a numerical climate model as an input to a crop simulation model. The precision of these predictions reflects the uncertainty in both models. We examined how uncertainty in a climate (HadAM3) and crop General Large-Area Model (GLAM) for annual crops model affects the mean and standard deviation of crop yield simulations in present and doubled carbon dioxide (CO2) climates by perturbation of parameters in each model. The climate sensitivity parameter (λ, the equilibrium response of global mean surface temperature to doubled CO2) was used to define the control climate. Observed 1966–1989 mean yields of groundnut (Arachis hypogaea L.) in India were simulated well by the crop model using the control climate and climates with values of λ near the control value. The simulations were used to measure the contribution to uncertainty of key crop and climate model parameters. The standard deviation of yield was more affected by perturbation of climate parameters than crop model parameters in both the present-day and doubled CO2 climates. Climate uncertainty was higher in the doubled CO2 climate than in the present-day climate. Crop transpiration efficiency was key to crop model uncertainty in both present-day and doubled CO2 climates. The response of crop development to mean temperature contributed little uncertainty in the present-day simulations but was among the largest contributors under doubled CO2. The ensemble methods used here to quantify physical and biological uncertainty offer a method to improve model estimates of the impacts of climate change.

Use of a crop model ensemble to quantify CO2 stimulation of water-stressed and well-watered crops

Increased atmospheric concentrations of carbon dioxide (CO2) will benefit the yield of most crops. Two free air CO2 enrichment (FACE) meta-analyses have shown increases in yield of between 0 and 73% for C3 crops. Despite this large range, few crop modelling studies quantify the uncertainty inherent in the parameterisation of crop growth and development. We present a novel perturbed-parameter method of crop model simulation, which uses some constraints from observations, that does this. The model used is the groundnut (i.e. peanut; Arachis hypogaea L.) version of the general large-area model for annual crops (GLAM). The conclusions are of relevance to C3 crops in general. The increases in yield simulated by GLAM for doubled CO2 were between 16 and 62%. The difference in mean percentage increase between well-watered and water-stressed simulations was 6.8. These results were compared to FACE and controlled environment studies, and to sensitivity tests on 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., Bell, M.J., 1995. A peanut simulation model. I. Model development and testing. Agron. J. 87, 1085-1093]. The relationship between CO2 and water stress in the experiments and in the models was examined. From a physiological perspective, water-stressed crops are expected to show greater CO2 stimulation than well-watered crops. This expectation has been cited in literature. However, this result is not seen consistently in either the FACE studies or in the crop models. In contrast, leaf-level models of assimilation do consistently show this result. An analysis of the evidence from these models and from the data suggests that scale (canopy versus leaf), model calibration, and model complexity are factors in determining the sign and magnitude of the interaction between CO2 and water stress. We conclude from our study that the statement that 'water-stressed crops show greater CO2 stimulation than well-watered crops' cannot be held to be universally true. We also conclude, preliminarily, that the relationship between water stress and assimilation varies with scale. Accordingly, we provide some suggestions on how studies of a similar nature, using crop models of a range of complexity, could contribute further to understanding the roles of model calibration, model complexity and scale. (C) 2008 Elsevier B.V. All rights reserved.

Adaptation of crops to climate change through genotypic responses to mean and extreme temperatures

The importance of temperature in the determination of the yield of an annual crop (groundnut; Arachis hypogaea L. in India) was assessed. Simulations from a regional climate model (PRECIS) were used with a crop model (GLAM) to examine crop growth under simulated current (1961-1990) and future (2071-2100) climates. Two processes were examined: the response of crop duration to mean temperature and the response of seed-set to extremes of temperature. The relative importance of, and interaction between, these two processes was examined for a number of genotypic characteristics, which were represented by using different values of crop model parameters derived from experiments. The impact of mean and extreme temperatures varied geographically, and depended upon the simulated genotypic properties. High temperature stress was not a major determinant of simulated yields in the current climate, but affected the mean and variability of yield under climate change in two regions which had contrasting statistics of daily maximum temperature. Changes in mean temperature had a similar impact on mean yield to that of high temperature stress in some locations and its effects were more widespread. Where the optimal temperature for development was exceeded, the resulting increase in duration in some simulations fully mitigated the negative impacts of extreme temperatures when sufficient water was available for the extended growing period. For some simulations the reduction in mean yield between the current and future climates was as large as 70%, indicating the importance of genotypic adaptation to changes in both means and extremes of temperature under climate change. (c) 2006 Elsevier B.V. All rights reserved.

Simulation of the impact of high temperature stress on annual crop yields

Brief periods of high temperature which occur near flowering can severely reduce the yield of annual crops such as wheat and groundnut. A parameterisation of this well-documented effect is presented for groundnut (i.e. peanut; Arachis hypogaeaL.). This parameterisation was combined with an existing crop model, allowing the impact of season-mean temperature, and of brief high-temperature episodes at various times near flowering, to be both independently and jointly examined. The extended crop model was tested with independent data from controlled environment experiments and field experiments. The impact of total crop duration was captured, with simulated duration being within 5% of observations for the range of season-mean temperatures used (20-28 degrees C). In simulations across nine differently timed high temperature events, eight of the absolute differences between observed and simulated yield were less than 10% of the control (no-stress) yield. The parameterisation of high temperature stress also allows the simulation of heat tolerance across different genotypes. Three parameter sets, representing tolerant, moderately sensitive and sensitive genotypes were developed and assessed. The new parameterisation can be used in climate change studies to estimate the impact of heat stress on yield. It can also be used to assess the potential for adaptation of cropping systems to increased temperature threshold exceedance via the choice of genotype characteristics. (c) 2005 Elsevier B.V. All rights reserved.

Design and optimisation of a large-area process-based model for annual crops

The formulation of a new process-based crop model, the general large-area model (GLAM) for annual crops is presented. The model has been designed to operate on spatial scales commensurate with those of global and regional climate models. It aims to simulate the impact of climate on crop yield. Procedures for model parameter determination and optimisation are described, and demonstrated for the prediction of groundnut (i.e. peanut; Arachis hypogaea L.) yields across India for the period 1966-1989. Optimal parameters (e.g. extinction coefficient, transpiration efficiency, rate of change of harvest index) were stable over space and time, provided the estimate of the yield technology trend was based on the full 24-year period. The model has two location-specific parameters, the planting date, and the yield gap parameter. The latter varies spatially and is determined by calibration. The optimal value varies slightly when different input data are used. The model was tested using a historical data set on a 2.5degrees x 2.5degrees grid to simulate yields. Three sites are examined in detail-grid cells from Gujarat in the west, Andhra Pradesh towards the south, and Uttar Pradesh in the north. Agreement between observed and modelled yield was variable, with correlation coefficients of 0.74, 0.42 and 0, respectively. Skill was highest where the climate signal was greatest, and correlations were comparable to or greater than correlations with seasonal mean rainfall. Yields from all 35 cells were aggregated to simulate all-India yield. The correlation coefficient between observed and simulated yields was 0.76, and the root mean square error was 8.4% of the mean yield. The model can be easily extended to any annual crop for the investigation of the impacts of climate variability (or change) on crop yield over large areas. (C) 2004 Elsevier B.V. All rights reserved.