Implementation of Parallel (p,q) Counters for High Speed Digital Multipliers

Both the (5,3) counter and (2,2,3) counter multiplication techniques are investigated for the efficiency of their operation speed and the viability of the architectures when implemented in a fast bipolar ECL technology. The implementation of the counters in series-gated ECL and threshold logic are contrasted for speed, noise immunity and complexity, and are critically compared with the fastest practical design of a full-adder. A novel circuit technique to overcome the problems of needing high fan-in input weights in threshold circuits through the use of negative weighted inputs is presented. The authors conclude that a (2,2,3) counter based array multiplier implemented in series-gated ECL should enable a significant increase in speed over conventional full adder based array multipliers.

Productivity and optimum plant density of pigeonpea in different environments in Tanzania

The objective of the present study was to determine the optimum plant density of four pigeonpea genotypes, representing early, medium and late maturing types, grown in five contrasting environments in Tanzania. ICPL 86005 (early), Kat 50/3 and QP 37 (medium) and Local (late) were grown at four plant densities (40 000-320 000 plants/ha) in irrigated and rainfed conditions at Ilonga and under rainfed conditions at Kibaha, Selian and Ismani. At maturity, total above-ground biomass and seed yield (SY) were measured. The highest yields were obtained in the irrigated experiment at Ilonga, where the medium/late genotypes produced 25 t biomass/ha and 5 center dot 6 t seed/ha. The lowest SY were at Kibaha, 0 58 to 1 center dot 76 t/ha, where a severe drought occurred. In nearly all cases the response to density was linear or asymptotic. The response of ICPL 86005 was significantly different from the other three genotypes. The optimum density for SY varied from 37 000 to 227 000 plants/ha in ICPL 86005, compared with 3000 to 101000 plants/ha in the medium/late genotypes. The highest optimum density was at Selian and Ismani and the lowest at Ilonga and Kibaha, where drought occurred. Optimum densities therefore varied greatly with genotype (duration) and environment, and this variation needs to be considered when planning trials.

Evidence for associations between common polymorphisms of estrogen receptor beta gene with homocysteine and nitric oxide

Background Homocysteine and asymmetric dimethylarginine (ADMA) affect nitric oxide (NO) concentration, thereby contributing to cardiovascular disease (CVD). Both amino acids can be reduced in vivo by estrogen. Variation in the estrogen receptor (ER) may influence homocysteine and ADMA, yet no information is available on associations with single nucleotide polymorphisms in the estrogen receptor genes ER alpha (PvuII and XbaI) and ER beta (1730G -> A and cx+56 G -> A). Objective To find relationships between common polymorphisms associated with cardiovascular disease and cardiovascular risk factors homocysteine and ADMA. Methods In a cross-sectional study with healthy postmenopausal women (n = 89), homocysteine, ADMA, nitric oxide metabolites (NOx), plasma folate and ER alpha and beta polymorphisms ER alpha PvuII, ER alpha XbaI; ER beta 1730G -> A (AluI), ER beta cx+56 G -> A (Tsp5091) were analyzed. Results Women who are homozygotic for ER beta cx+56 G -> A A/A exhibited higher homocysteine (p = 0.012) and NOx (p = 0.056) levels than wildtype or heterozygotes. NOx concentration was also significantly affected by ER beta 1730 G -> A polymorphism (p = 0.025). The ER beta (p < 0.001) and ER alpha (p < 0.001) polymorphisms were in linkage disequilibrium. Conclusions Women who are homozygotic for ER beta cx+S6 G -> A A/A may be at increased risk for cardiovascular disease due to higher homocysteine levels.

Introducing improved cultivars: Understanding farmers' seed drying and storage practices in central Ghana

Improved upland rice cultivars introduced in Volta Region, Ghana, have been perceived to store poorly compared to farmers' traditional cultivars. A survey was conducted in 2003 in the Hohoc district of this region, where a participatory Varietal Selection programme had started in 1997, to gain insight into fanners' seed production and storage practices that are likely to affect seed quality in storage. Farmers rated keeping quality (p < 0.001), tolerance to storage pests (p < 0.001), seed quality (p < 0.001) and establishment of their local cultivars Kawomo, Viono and Wuwulili as much better than the improved cultivar IDSA 85. Initial seed moisture content ranged from 12.8 to 18% and germination from 0 to 82%. There was a significant relationship between seed moisture content and duration of drying prior to storage (p < 0.001) and storage method (p = 0.015). Germination loss in storage was rapid at high moisture content and slow at low moisture content. Between 60 and 80% of seeds germinated after six Months storage at 12.8% moisture content. The viability equation predicted accurately germination of farmer-saved seed stored under ambient temperature in Ghana. Except for the japonica rice cultivar WAB 126-18-HB, the traditional cultivars Kawomo, Viono and Wuwulili survived better in storage than improved cultivars. There is a need to improve seed quality of improved cultivars if farmers are to benefit from their higher yields and grain quality and to improve storage practices.

Toward a combined seasonal weather and crop productivity forecasting system: Determination of the working spatial scale

A methodology is presented for the development of a combined seasonal weather and crop productivity forecasting system. The first stage of the methodology is the determination of the spatial scale(s) on which the system could operate; this determination has been made for the case of groundnut production in India. Rainfall is a dominant climatic determinant of groundnut yield in India. The relationship between yield and rainfall has been explored using data from 1966 to 1995. On the all-India scale, seasonal rainfall explains 52% of the variance in yield. On the subdivisional scale, correlations vary between variance r(2) = 0.62 (significance level p < 10(-4)) and a negative correlation with r(2) = 0.1 (p = 0.13). The spatial structure of the relationship between rainfall and groundnut yield has been explored using empirical orthogonal function (EOF) analysis. A coherent, large-scale pattern emerges for both rainfall and yield. On the subdivisional scale (similar to 300 km), the first principal component (PC) of rainfall is correlated well with the first PC of yield (r(2) = 0.53, p < 10(-4)), demonstrating that the large-scale patterns picked out by the EOFs are related. The physical significance of this result is demonstrated. Use of larger averaging areas for the EOF analysis resulted in lower and (over time) less robust correlations. Because of this loss of detail when using larger spatial scales, the subdivisional scale is suggested as an upper limit on the spatial scale for the proposed forecasting system. Further, district-level EOFs of the yield data demonstrate the validity of upscaling these data to the subdivisional scale. Similar patterns have been produced using data on both of these scales, and the first PCs are very highly correlated (r(2) = 0.96). Hence, a working spatial scale has been identified, typical of that used in seasonal weather forecasting, that can form the basis of crop modeling work for the case of groundnut production in India. Last, the change in correlation between yield and seasonal rainfall during the study period has been examined using seasonal totals and monthly EOFs. A further link between yield and subseasonal variability is demonstrated via analysis of dynamical data.

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.

Simulation of crop yields using ERA-40: Limits to skill and nonstationarity in weather-yield relationships

Reanalysis data provide an excellent test bed for impacts prediction systems. because they represent an upper limit on the skill of climate models. Indian groundnut (Arachis hypogaea L.) yields have been simulated using the General Large-Area Model (GLAM) for annual crops and the European Centre for Medium-Range Weather Forecasts (ECMWF) 40-yr reanalysis (ERA-40). The ability of ERA-40 to represent the Indian summer monsoon has been examined. The ability of GLAM. when driven with daily ERA-40 data, to model both observed yields and observed relationships between subseasonal weather and yield has been assessed. Mean yields "were simulated well across much of India. Correlations between observed and modeled yields, where these are significant. are comparable to correlations between observed yields and ERA-40 rainfall. Uncertainties due to the input planting window, crop duration, and weather data have been examined. A reduction in the root-mean-square error of simulated yields was achieved by applying bias correction techniques to the precipitation. The stability of the relationship between weather and yield over time has been examined. Weather-yield correlations vary on decadal time scales. and this has direct implications for the accuracy of yield simulations. Analysis of the skewness of both detrended yields and precipitation suggest that nonclimatic factors are partly responsible for this nonstationarity. Evidence from other studies, including data on cereal and pulse yields, indicates that this result is not particular to groundnut yield. The detection and modeling of nonstationary weather-yield relationships emerges from this study as an important part of the process of understanding and predicting the impacts of climate variability and change on crop yields.

Heat tolerance in groundnut

Tolerance to high soil and air temperature during the reproductive phase is an important component of adaptation to and and semi-arid cropping environments in groundnut. Between 10 and 22 genotypes were screened for tolerance to high air and soil temperature in controlled environments. To assess tolerance to high soil temperature, 10 genotypes were grown from start of podding to harvest at ambient (28 degrees) and high (38 degreesC) soil temperatures, and crop growth rate (CGR), pod growth rate (PGR) and partitioning (ratio PGR:CGR) measured. To assess tolerance to high air temperature during two key stages-microsporogenesis (3-6 days before flowering, DBF) and flowering, fruit-set was measured in two experiments. In the first experiment, 12 genotypes were exposed to short (3-6 days) episodes of high (38 degreesC) day air temperature at 6 DBF and at flowering. In the second experiment, 22 genotypes were exposed to 40 degreesC day air temperature for I day at 6 DBF, 3 DBF or at flowering. Cellular membrane thermostability (relative injury, RI) was also measured in these 22 genotypes. There was considerable variation among genotypes in response to high temperature, whether assessed by growth rates, fruit-set or RI. Pod weight at high soil temperature was associated with variation in CGR rather than partitioning. Flowering was more sensitive to high air temperature than microsporogenesis. Genotypes tolerant to high air temperature at microsporogenesis were not necessarily tolerant at flowering, and nor was tolerance correlated with RI. Six genotypes (796, 55-437, ICG 1236, ICGV 86021, lCGV 87281 and ICGV 92121) were identified as heat tolerant based on their performance in all tests. These experiments have shown that groundnut genotypes can be easily screened for reproductive tolerance to high air and soil temperature and that several sources of heat tolerance are available in groundnut germplasm. (C) 2003 Elsevier Science B.V. All rights reserved.

Drought, pod yield, pre-harvest Aspergillus infection and aflatoxin contamination on peanut in Niger

Soil moisture and soil temperature affect pre-harvest infection with Aspergillus flavus and production of aflatoxin. The objectives of our field research in Niger, West Africa, were to: (i) examine the effects of sowing date and irrigation treatments on pod yield, infection with A. flavus and aflatoxin concentration; and (ii) to quantify relations between infection, aflatoxin concentration and soil moisture stress. Seed of an aflatoxin susceptible peanut cv. JL24 was sown at two to four different sowing dates under four irrigation treatments (rainfed and irrigation at 7, 14 and 21 days intervals) between 1991 and 1994, giving 40 different 'environments'. Average air and soil temperatures of 28-34 degrees C were favourable for aflatoxin contamination. CROPGRO-peanut model was used to simulate the occurrence of moisture stress. The model was able to simulate yields of peanut well over the 40 environments (r(2) = 0.67). In general, early sowing produced greater pod yields, as well as less infection and lower aflatoxin concentration. There were negative linear relations between infection (r(2) = 0.62) and the average simulated fraction of extractable soil water (FESW) between flowering and harvest, and between aflatoxin concentration (r(2) = 0.54) and FESW in the last 25 days of pod-filling. This field study confirms that infection and aflatoxin concentration in peanut can be related to the occurrence of soil moisture stress during pod-filling when soil temperatures are near optimal for A. flavus. These relations could form the basis of a decision-support system to predict the risk of aflatoxin contamination in peanuts in similar environments. (c) 2005 Elsevier B.V. All rights reserved.

Climate change and the flowering time of annual crops

Crop production is inherently sensitive to variability in climate. Temperature is a major determinant of the rate of plant development and, under climate change, warmer temperatures that shorten development stages of determinate crops will most probably reduce the yield of a given variety. Earlier crop flowering and maturity have been observed and documented in recent decades, and these are often associated with warmer (spring) temperatures. However, farm management practices have also changed and the attribution of observed changes in phenology to climate change per se is difficult. Increases in atmospheric [CO2] often advance the time of flowering by a few days, but measurements in FACE (free air CO2 enrichment) field-based experiments suggest that elevated [CO2] has little or no effect on the rate of development other than small advances in development associated with a warmer canopy temperature. The rate of development (inverse of the duration from sowing to flowering) is largely determined by responses to temperature and photoperiod, and the effects of temperature and of photoperiod at optimum and suboptimum temperatures can be quantified and predicted. However, responses to temperature, and more particularly photoperiod, at supraoptimal temperature are not well understood. Analysis of a comprehensive data set of time to tassel initiation in maize (Zea mays) with a wide range of photoperiods above and below the optimum suggests that photoperiod modulates the negative effects of temperature above the optimum. A simulation analysis of the effects of prescribed increases in temperature (0-6 degrees C in + 1 degrees C steps) and temperature variability (0% and + 50%) on days to tassel initiation showed that tassel initiation occurs later, and variability was increased, as the temperature exceeds the optimum in models both with and without photoperiod sensitivity. However, the inclusion of photoperiod sensitivity above the optimum temperature resulted in a higher apparent optimum temperature and less variability in the time of tassel initiation. Given the importance of changes in plant development for crop yield under climate change, the effects of photoperiod and temperature on development rates above the optimum temperature clearly merit further research, and some of the knowledge gaps are identified herein.