Can genetically-modified cotton contribute to sustainable development in Africa?

Genetically modified (GM) crops and sustainable development remain the foci of much media attention, especially given current concerns about a global food crisis. However, whilst the latter is embraced with enthusiasm by almost all groups, GM crops generate very mixed views. Some countries have welcomed GM, but others, notably those in Europe, adopt a cautious stance. This article aims to review the contribution that GM crops can make to agricultural sustainability in the developing world. Following brief reviews of both issues and their linkages, notably the pros and cons of GM cotton as a contributory factor in sustainability, a number of case studies from resourcepoor cotton farmers in Makhathini Flats, South Africa, is presented for a six-year period. Data on expenditure, productivity and income indicate that Bacillus thuringiensis (Bt) cotton is advantageous because it reduces costs, for example, of pesticides, and increases income, and the indications are that those benefits continued over at least the six years covered by the studies. There are repercussions of the additional income in the households; debts are reduced and money is invested in children's education and in the farms. However, in the general GM debate, the results show that GM crops are not miracle products which alleviate poverty at a stroke, but nor is there evidence that they will cause the scale of environmental damage associated with indiscriminate pesticide use. Indeed, for some GM antagonists, perhaps even the majority, such debates are irrelevant – the transfer of genes between species is unnatural and unethical. For them, GM crops will never be acceptable despite the evidence and pressure to increase world food production.

Atmosphere feedbacks during ENSO in a coupled GCM with a modified atmospheric convection scheme

The too diverse representation of ENSO in a coupled GCM limits one’s ability to describe future change of its properties. Several studies pointed to the key role of atmosphere feedbacks in contributing to this diversity. These feedbacks are analyzed here in two simulations of a coupled GCM that differ only by the parameterization of deep atmospheric convection and the associated clouds. Using the Kerry–Emanuel (KE) scheme in the L’Institut Pierre-Simon Laplace Coupled Model, version 4 (IPSL CM4; KE simulation), ENSO has about the right amplitude, whereas it is almost suppressed when using the Tiedke (TI) scheme. Quantifying both the dynamical Bjerknes feedback and the heat flux feedback in KE, TI, and the corresponding Atmospheric Model Intercomparison Project (AMIP) atmosphere-only simulations, it is shown that the suppression of ENSO in TI is due to a doubling of the damping via heat flux feedback. Because the Bjerknes positive feedback is weak in both simulations, the KE simulation exhibits the right ENSO amplitude owing to an error compensation between a too weak heat flux feedback and a too weak Bjerknes feedback. In TI, the heat flux feedback strength is closer to estimates from observations and reanalysis, leading to ENSO suppression. The shortwave heat flux and, to a lesser extent, the latent heat flux feedbacks are the dominant contributors to the change between TI and KE. The shortwave heat flux feedback differences are traced back to a modified distribution of the large-scale regimes of deep convection (negative feedback) and subsidence (positive feedback) in the east Pacific. These are further associated with the model systematic errors. It is argued that a systematic and detailed evaluation of atmosphere feedbacks during ENSO is a necessary step to fully understand its simulation in coupled GCMs.

Generic systolic array for genetic algorithms

The authors present a systolic design for a simple GA mechanism which provides high throughput and unidirectional pipelining by exploiting the inherent parallelism in the genetic operators. The design computes in O(N+G) time steps using O(N2) cells where N is the population size and G is the chromosome length. The area of the device is independent of the chromosome length and so can be easily scaled by replicating the arrays or by employing fine-grain migration. The array is generic in the sense that it does not rely on the fitness function and can be used as an accelerator for any GA application using uniform crossover between pairs of chromosomes. The design can also be used in hybrid systems as an add-on to complement existing designs and methods for fitness function acceleration and island-style population management

The role of satellite image-processing for national-scale estimates of gene flow from genetically modified crops: rapeseed in the UK as a model.

1. There is concern over the possibility of unwanted environmental change following transgene movement from genetically modified (GM) rapeseed Brassica napus to its wild and weedy relatives. 2. The aim of this research was to develop a remote sensing-assisted methodology to help quantify gene flow from crops to their wild relatives over wide areas. Emphasis was placed on locating sites of sympatry, where the frequency of gene flow is likely to be highest, and on measuring the size of rapeseed fields to allow spatially explicit modelling of wind-mediated pollen-dispersal patterns. 3. Remote sensing was used as a tool to locate rapeseed fields, and a variety of image-processing techniques was adopted to facilitate the compilation of a spatially explicit profile of sympatry between the crop and Brassica rapa. 4. Classified satellite images containing rapeseed fields were first used to infer the spatial relationship between donor rapeseed fields and recipient riverside B. rapa populations. Such images also have utility for improving the efficiency of ground surveys by identifying probable sites of sympatry. The same data were then also used for the calculation of mean field size. 5. This paper forms a companion paper to Wilkinson et al. (2003), in which these elements were combined to produce a spatially explicit profile of hybrid formation over the UK. The current paper demonstrates the value of remote sensing and image processing for large-scale studies of gene flow, and describes a generic method that could be applied to a variety of crops in many countries. 6. Synthesis and applications. The decision to approve or prevent the release of a GM cultivar is made at a national rather than regional level. It is highly desirable that data relating to the decision-making process are collected at the same scale, rather than relying on extrapolation from smaller experiments designed at the plot, field or even regional scale. It would be extremely difficult and labour intensive to attempt to carry out such large-scale investigations without the use of remote-sensing technology. This study used rapeseed in the UK as a model to demonstrate the value of remote sensing in assembling empirical information at a national level.

Parallel genetic algorithms for the tuning of a fuzzy AQM controller

This paper presents the results of the application of a parallel Genetic Algorithm (GA) in order to design a Fuzzy Proportional Integral (FPI) controller for active queue management on Internet routers. The Active Queue Management (AQM) policies are those policies of router queue management that allow the detection of network congestion, the notification of such occurrences to the hosts on the network borders, and the adoption of a suitable control policy. Two different parallel implementations of the genetic algorithm are adopted to determine an optimal configuration of the FPI controller parameters. Finally, the results of several experiments carried out on a forty nodes cluster of workstations are presented.

Implementing a generic systolic array for genetic algorithms

We have designed a highly parallel design for a simple genetic algorithm using a pipeline of systolic arrays. The systolic design provides high throughput and unidirectional pipelining by exploiting the implicit parallelism in the genetic operators. The design is significant because, unlike other hardware genetic algorithms, it is independent of both the fitness function and the particular chromosome length used in a problem. We have designed and simulated a version of the mutation array using Xilinix FPGA tools to investigate the feasibility of hardware implementation. A simple 5-chromosome mutation array occupies 195 CLBs and is capable of performing more than one million mutations per second. I. Introduction Genetic algorithms (GAs) are established search and optimization techniques which have been applied to a range of engineering and applied problems with considerable success [1]. They operate by maintaining a population of trial solutions encoded, using a suitable encoding scheme.

Systolic random number generation for genetic algorithms

A parallel hardware random number generator for use with a VLSI genetic algorithm processing device is proposed. The design uses an systolic array of mixed congruential random number generators. The generators are constantly reseeded with the outputs of the proceeding generators to avoid significant biasing of the randomness of the array which would result in longer times for the algorithm to converge to a solution. 1 Introduction In recent years there has been a growing interest in developing hardware genetic algorithm devices [1, 2, 3]. A genetic algorithm (GA) is a stochastic search and optimization technique which attempts to capture the power of natural selection by evolving a population of candidate solutions by a process of selection and reproduction [4]. In keeping with the evolutionary analogy, the solutions are called chromosomes with each chromosome containing a number of genes. Chromosomes are commonly simple binary strings, the bits being the genes.

Mapping and controlling molecular processes: The application of control theory and system identification algorithms to ASOPS and other fast pulse spectroscopies

Asynchronous Optical Sampling (ASOPS) [1,2] and frequency comb spectrometry [3] based on dual Ti:saphire resonators operated in a master/slave mode have the potential to improve signal to noise ratio in THz transient and IR sperctrometry. The multimode Brownian oscillator time-domain response function described by state-space models is a mathematically robust framework that can be used to describe the dispersive phenomena governed by Lorentzian, Debye and Drude responses. In addition, the optical properties of an arbitrary medium can be expressed as a linear combination of simple multimode Brownian oscillator functions. The suitability of a range of signal processing schemes adopted from the Systems Identification and Control Theory community for further processing the recorded THz transients in the time or frequency domain will be outlined [4,5]. Since a femtosecond duration pulse is capable of persistent excitation of the medium within which it propagates, such approach is perfectly justifiable. Several de-noising routines based on system identification will be shown. Furthermore, specifically developed apodization structures will be discussed. These are necessary because due to dispersion issues, the time-domain background and sample interferograms are non-symmetrical [6-8]. These procedures can lead to a more precise estimation of the complex insertion loss function. The algorithms are applicable to femtosecond spectroscopies across the EM spectrum. Finally, a methodology for femtosecond pulse shaping using genetic algorithms aiming to map and control molecular relaxation processes will be mentioned.

A safety evaluation of genetically modified feedstuffs for livestock production; the fate of transgenic DNA and proteins

dTwo genetic constructs used to confer improved agronomic characteristics, namely herbicide tolerance (HT) in maize and soyabean and insect resistance (Bt) in maize, are considered in respect of feeding to farm livestock, animal performance and the nutritional value and safety of animal products. A review of nucleic acid (DNA) and protein digestion in farm livestock concludes that the frequency of intact transgenic DNA and proteins of GM and non-GM crops being absorbed is minimal/non existent, although there is some evidence of the presence of short fragments of rubisco DNA of non-GM soya in animal tissues. It has been established that feed processing (especially heat) prior to feeding causes significant disruption of plant DNA. Studies with ruminant and non-ruminant farm livestock offered GM feeds demonstrated that animal performance and product composition are unaffected and that there is no evidence of transgenic DNA or proteins of current GM in the products of animals consuming such feeds. On this evidence, current HT and Bt constructs represent no threat to the health of animals, or humans consuming the products of such animals. However as new GM constructs become available it will be necessary to subject these to rigorous evaluation.

Explaining contradictory evidence regarding impacts of genetically modified crops in developing countries. Varietal performance of transgenic cotton in India

A study of the commercial growing of different varieties of Bacillus thuringiensis (Bt) cotton compares the performance of growing official and unofficial hybrid varieties of Bt cotton and conventional (non-Bt) hybrids in Gujarat by 622 farmers. Results suggest that the official Bt varieties (MECH 12 and MECH 162) significantly outperform the unofficial varieties. However, unofficial, locally produced Bt hybrids can also perform significantly better than non-Bt hybrids, although second generation (F-2) Bt seed appears to have no yield advantage compared to non-Bt hybrids but can save on insecticide use. Although hybrid vigour is reduced, or even lost, with F-2 seed the Bt gene still confers some advantage. The F-2 seed is regarded as 'GM' by the farmers (and is sold as such), even though its yield performance is little better than the non-GM hybrids. The results help to explain why there is so much confusion arising from GM cotton release in India.

Farm-level economic performance of genetically modified cotton in Maharashtra, India

A study of the commercial growing of Bacillus flutringiensis (Bt) cotton in India, compares the performance of over 9,000 Bt and non-Bt cotton farm plots in Maharashtra over the 2002 and 2003 seasons. Results show that since their commercial release in 2002, Bt cotton varieties have had a significant positive impact on average yields and on the economic performance of cotton growers. Regional variation showed that, in a very few areas, not all farmers had benefited from increased performance of Bt varieties.

The economic impact of genetically modified cotton on South African smallholders: Yield, profit and health effects

Results of a large-scale survey of resource-poor smallholder cotton farmers in South Africa over three years conclusively show that adopters of Bt cotton have benefited in terms of higher yields, lower pesticide use, less labour for pesticide application and substantially higher gross margins per hectare. These benefits were clearly related to the technology, and not to preferential adoption by farmers who were already highly efficient. The smallest producers are shown to have benefited from adoption of the Bt variety as much as, if not more than, larger producers. Moreover, evidence from hospital records suggests a link between declining pesticide poisonings and adoption of the Bt variety.