Exploring the feasibility of farmers' rights

In many developing countries, there is concern that a conventional system of plant breeders' rights provides no rewards to farmers for their role in the conservation and enhancement of agro-biodiversity. To redress this imbalance, developing countries are incorporating farmers' rights provisions in their plant variety protection legislation. This article examines the feasibility of farmers' rights provisions based on intellectual property rights. It argues that the farmers' rights provisions crafted by some developing countries will involve enormous operational difficulties, while IPR-based farmers' rights are unlikely to provide significant economic returns to farmers or farming communities. At the same time, farmers' rights provisions, as currently conceived, are likely significantly to dilute the incentives for innovation provided to institutional plant breeders.

Plant variety protection, innovation, and transferability: Some empirical evidence

Under the Agreement on Trade-Related Aspects of Intellectual Property Rights, all member-countries of the World Trade Organization are required to provide an "effective" system of plant variety protection within a specific time frame. In many developing countries, this has led to a divisive debate about the fundamental desirability of extending intellectual property rights to agriculture. Empirical studies on the economic impacts of plant variety protection, especially its ability to generate large private sector investments in plant breeding and to facilitate the transfer of technology, have been very limited. This paper examines two aspects of the international experience of plant variety protection: (a) the relationship between legislation, research, and development expenditures and plant variety protection grants, i.e., the innovation effect and (b) the role of plant variety protection in facilitating the flow of varieties across countries, i.e., the transferability effect.

The use of life-cycle assessment to evaluate the environmental impacts of growing genetically modified, nitrogen use-efficient canola

Agriculture, particularly intensive crop production, makes a significant contribution to environmental pollution. A variety of canola (Brassica napus) has been genetically modified to enhance nitrogen use efficiency, effectively reducing the amount of fertilizer required for crop production. A partial life-cycle assessment adapted to crop production was used to assess the potential environmental impacts of growing genetically modified, nitrogen use-efficient (GMNUE) canola in North Dakota and Minnesota compared with a conventionally bred control variety. The analysis took into account the entire production system used to produce 1 tonne of canola. This comprised raw material extraction, processing and transportation, as well as all agricultural field operations. All emissions associated with the production of 1 tonne of canola were listed, aggregated and weighted in order to calculate the level of environmental impact. The findings show that there are a range of potential environmental benefits associated with growing GMNUE canola. These include reduced impacts on global warming, freshwater ecotoxicity, eutrophication and acidification. Given the large areas of canola grown in North America and, in particular, Canada, as well as the wide acceptance of genetically modified varieties in this area, there is the potential for GMNUE canola to reduce pollution from agriculture, with the largest reductions predicted to be in greenhouse gases and diffuse water pollution.

A novel transcriptomic approach to identify candidate genes for grain quality traits in wheat

A novel methodology is described in which transcriptomics is combined with the measurement of bread-making quality and other agronomic traits for wheat genotypes grown in different environments (wet and cool or hot and dry conditions) to identify transcripts associated with these traits. Seven doubled haploid lines from the Spark x Rialto mapping population were selected to be matched for development and known alleles affecting quality. These were grown in polytunnels with different environments applied 14 days post-anthesis, and the whole experiment was repeated over 2 years. Transcriptomics using the wheat Affymetrix chip was carried out on whole caryopsis samples at two stages during grain filling. Transcript abundance was correlated with the traits for approximately 400 transcripts. About 30 of these were selected as being of most interest, and markers were derived from them and mapped using the population. Expression was identified as being under cis control for 11 of these and under trans control for 18. These transcripts are candidates for involvement in the biological processes which underlie genotypic variation in these traits.

A hierarchical Bayesian model for predicting the functional consequences of amino-acid polymorphisms

Genetic polymorphisms in deoxyribonucleic acid coding regions may have a phenotypic effect on the carrier, e.g. by influencing susceptibility to disease. Detection of deleterious mutations via association studies is hampered by the large number of candidate sites; therefore methods are needed to narrow down the search to the most promising sites. For this, a possible approach is to use structural and sequence-based information of the encoded protein to predict whether a mutation at a particular site is likely to disrupt the functionality of the protein itself. We propose a hierarchical Bayesian multivariate adaptive regression spline (BMARS) model for supervised learning in this context and assess its predictive performance by using data from mutagenesis experiments on lac repressor and lysozyme proteins. In these experiments, about 12 amino-acid substitutions were performed at each native amino-acid position and the effect on protein functionality was assessed. The training data thus consist of repeated observations at each position, which the hierarchical framework is needed to account for. The model is trained on the lac repressor data and tested on the lysozyme mutations and vice versa. In particular, we show that the hierarchical BMARS model, by allowing for the clustered nature of the data, yields lower out-of-sample misclassification rates compared with both a BMARS and a frequen-tist MARS model, a support vector machine classifier and an optimally pruned classification tree.

Estimating numbers of infectious units from serial dilution assays

The paper concerns the design and analysis of serial dilution assays to estimate the infectivity of a sample of tissue when it is assumed that the sample contains a finite number of indivisible infectious units such that a subsample will be infectious if it contains one or more of these units. The aim of the study is to estimate the number of infectious units in the original sample. The standard approach to the analysis of data from such a study is based on the assumption of independence of aliquots both at the same dilution level and at different dilution levels, so that the numbers of infectious units in the aliquots follow independent Poisson distributions. An alternative approach is based on calculation of the expected value of the total number of samples tested that are not infectious. We derive the likelihood for the data on the basis of the discrete number of infectious units, enabling calculation of the maximum likelihood estimate and likelihood-based confidence intervals. We use the exact probabilities that are obtained to compare the maximum likelihood estimate with those given by the other methods in terms of bias and standard error and to compare the coverage of the confidence intervals. We show that the methods have very similar properties and conclude that for practical use the method that is based on the Poisson assumption is to be recommended, since it can be implemented by using standard statistical software. Finally we consider the design of serial dilution assays, concluding that it is important that neither the dilution factor nor the number of samples that remain untested should be too large.

The F test for comparing two normal variances: correct and incorrect calculation of the two-sided p-value?

This article illustrates that not all statistical software packages are correctly calculating a p-value for the classical F test comparison of two independent Normal variances. This is illustrated with a simple example, and the reasons why are discussed. Eight different software packages are considered.

A jackknife variance estimator for unequal probability sampling

The jackknife method is often used for variance estimation in sample surveys but has only been developed for a limited class of sampling designs.We propose a jackknife variance estimator which is defined for any without-replacement unequal probability sampling design. We demonstrate design consistency of this estimator for a broad class of point estimators. A Monte Carlo study shows how the proposed estimator may improve on existing estimators.

Variance estimation with highly stratified sampling designs with unequal probabilities

It is common practice to design a survey with a large number of strata. However, in this case the usual techniques for variance estimation can be inaccurate. This paper proposes a variance estimator for estimators of totals. The method proposed can be implemented with standard statistical packages without any specific programming, as it involves simple techniques of estimation, such as regression fitting.

Some general comparative points on Chao's and Zelterman's estimators of the population size

Two simple and frequently used capture–recapture estimates of the population size are compared: Chao's lower-bound estimate and Zelterman's estimate allowing for contaminated distributions. In the Poisson case it is shown that if there are only counts of ones and twos, the estimator of Zelterman is always bounded above by Chao's estimator. If counts larger than two exist, the estimator of Zelterman is becoming larger than that of Chao's, if only the ratio of the frequencies of counts of twos and ones is small enough. A similar analysis is provided for the binomial case. For a two-component mixture of Poisson distributions the asymptotic bias of both estimators is derived and it is shown that the Zelterman estimator can experience large overestimation bias. A modified Zelterman estimator is suggested and also the bias-corrected version of Chao's estimator is considered. All four estimators are compared in a simulation study.

Adjusted jackknife for imputation under unequal probability sampling without replacement

Imputation is commonly used to compensate for item non-response in sample surveys. If we treat the imputed values as if they are true values, and then compute the variance estimates by using standard methods, such as the jackknife, we can seriously underestimate the true variances. We propose a modified jackknife variance estimator which is defined for any without-replacement unequal probability sampling design in the presence of imputation and non-negligible sampling fraction. Mean, ratio and random-imputation methods will be considered. The practical advantage of the method proposed is its breadth of applicability.

Review: intellectual property aspects of plant transformation

One of the recurring themes of the debates concerning the application of genetic transformation technology has been the role of Intellectual Property Rights (IPR). This term covers both the content of patents and the confidential expertise usually related to methodology and referred to as 'Trade Secrets'. This review explains the concepts behind patent protection, and discusses the wide-ranging scope of existing patents that cover all aspects of transgenic technology, from selectable markers and novel promoters to methods of gene introduction. Although few of the patents in this area have any real commercial value, there are a small number of key patents that restrict the 'freedom to operate' of new companies seeking to exploit the methods. Over the last 20 years, these restrictions have forced extensive cross-licensing between ag-biotech companies and have been one of the driving forces behind the consolidation of these companies. Although such issues are often considered of little interest to the academic scientist working in the public sector, they are of great importance in any discussion of the role of 'public-good breeding' and of the relationship between the public and private sectors.

Educational participation post-16: a longitudinal analysis of intentions and outcomes

The issue of levels of participation in post-compulsory education has been emphasised by the current policy initiatives to increase the age to which some form of participation is compulsory. One of the acknowledged weaknesses of research in the field of children's intentions with regard to participation is the lack of longitudinal data. This paper offers a longitudinal analysis using the Youth Survey from the British Household Panel Survey. The results show that most children can express intentions with regard to future participation very early in their secondary school careers and that these intentions are good predictors of actual behaviour five years later. Intentions to stay on are more consistent than intentions to leave and most children who finally leave at 16 have at some point said they want to remain in education post-16. The strongest association with participation levels is attainment at GCSE. However, there are also influences of gender and parental background and these remain, even after attainment is held constant. The results show the value of focusing on intentions for participation at a very early stage of children's school careers and also the importance of current attempts to reform curriculum and assessment for the 14-19 age group.

A new theory of educational change - punctuated equilibrium: the case of the internationalisation of Higher Education institutions

This article argues for a new theoretical paradigm for the analysis of change in educational institutions that is able to deal with such issues as readiness for change, transformational change and the failure of change strategies. Punctuated equilibrium (Tushman and Romanelli, 1985) is a theory which has wide application. It envisages long-term change as being made up of a succession of long periods of relative stability interspersed by brief periods of rapid profound change. In the periods of stability only relatively small incremental changes are possible. The periods of transformational change may be triggered by external or internal influences. A recent study of the long-term process of internationalisation in higher education institutions shows evidence to support the theory: long periods of incremental change, events precipitating profound change and the failure of externally imposed attempts to change. Also, as the theory predicts, changes in collegial organisations are slower and more uncertain than changes in managed organisations.