Transgenic approaches to crop improvement

Transgenic crops are now grown commercially on several million hectares, principally in North America. To date, the predominant crops are maize (corn), soybean, cotton, and potatoes. In addition, there have been field trials of transgenics from at least 52 species including all the major field crops, vegetables, and several herbaceous and woody species. This review summarizes recent data relating to such trials, particularly in terms of the trends away from simple, single gene traits such as herbicide and insect resistance towards more complex agronomic traits such as growth rate and increased photosynthetic efficiency. Much of the recent information is derived from inspection of patent databases, a useful source of information on commercial priorities. The review also discusses the time scale for the introduction of these transgenes into breeding populations and their eventual release as new varieties.

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.

Quantifying the effect of buffer zones, crop areas and spatial aggregation on the externalities of genetically modified crops at landscape level

The development of genetically modified (GM) crops has led the European Union (EU) to put forward the concept of 'coexistence' to give fanners the freedom to plant both conventional and GM varieties. Should a premium for non-GM varieties emerge in the market, 'contamination' by GM pollen would generate a negative externality to conventional growers. It is therefore important to assess the effect of different 'policy variables'on the magnitude of the externality to identify suitable policies to manage coexistence. In this paper, taking GM herbicide tolerant oilseed rape as a model crop, we start from the model developed in Ceddia et al. [Ceddia, M.G., Bartlett, M., Perrings, C., 2007. Landscape gene flow, coexistence and threshold effect: the case of genetically modified herbicide tolerant oilseed rape (Brassica napus). Ecol. Modell. 205, pp. 169-180] use a Monte Carlo experiment to generate data and then estimate the effect of the number of GM and conventional fields, width of buffer areas and the degree of spatial aggregation (i.e. the 'policy variables') on the magnitude of the externality at the landscape level. To represent realistic conditions in agricultural production, we assume that detection of GM material in conventional produce might occur at the field level (no grain mixing occurs) or at the silos level (where grain mixing from different fields in the landscape occurs). In the former case, the magnitude of the externality will depend on the number of conventional fields with average transgenic presence above a certain threshold. In the latter case, the magnitude of the externality will depend on whether the average transgenic presence across all conventional fields exceeds the threshold. In order to quantify the effect of the relevant' policy variables', we compute the marginal effects and the elasticities. Our results show that when relying on marginal effects to assess the impact of the different 'policy variables', spatial aggregation is far more important when transgenic material is detected at field level, corroborating previous research. However, when elasticity is used, the effectiveness of spatial aggregation in reducing the externality is almost identical whether detection occurs at field level or at silos level. Our results show also that the area planted with GM is the most important 'policy variable' in affecting the externality to conventional growers and that buffer areas on conventional fields are more effective than those on GM fields. The implications of the results for the coexistence policies in the EU are discussed. (C) 2008 Elsevier B.V. All rights reserved.

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.

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.

Bias from farmer self-selection in genetically modified crop productivity estimates: Evidence from Indian data

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.

Inter-laboratory variation of in vitro cumulative gas production profiles of feeds using manual and automated methods

A study was conducted to estimate variation among laboratories and between manual and automated techniques of measuring pressure on the resulting gas production profiles (GPP). Eight feeds (molassed sugarbeet feed, grass silage, maize silage, soyabean hulls, maize gluten feed, whole crop wheat silage, wheat, glucose) were milled to pass a I mm screen and sent to three laboratories (ADAS Nutritional Sciences Research Unit, UK; Institute of Grassland and Environmental Research (IGER), UK; Wageningen University, The Netherlands). Each laboratory measured GPP over 144 h using standardised procedures with manual pressure transducers (MPT) and automated pressure systems (APS). The APS at ADAS used a pressure transducer and bottles in a shaking water bath, while the APS at Wageningen and IGER used a pressure sensor and bottles held in a stationary rack. Apparent dry matter degradability (ADDM) was estimated at the end of the incubation. GPP were fitted to a modified Michaelis-Menten model assuming a single phase of gas production, and GPP were described in terms of the asymptotic volume of gas produced (A), the time to half A (B), the time of maximum gas production rate (t(RM) (gas)) and maximum gas production rate (R-M (gas)). There were effects (P<0.001) of substrate on all parameters. However, MPT produced more (P<0.001) gas, but with longer (P<0.001) B and t(RM gas) (P<0.05) and lower (P<0.001) R-M gas compared to APS. There was no difference between apparatus in ADDM estimates. Interactions occurred between substrate and apparatus, substrate and laboratory, and laboratory and apparatus. However, when mean values for MPT were regressed from the individual laboratories, relationships were good (i.e., adjusted R-2 = 0.827 or higher). Good relationships were also observed with APS, although they were weaker than for MPT (i.e., adjusted R-2 = 0.723 or higher). The relationships between mean MPT and mean APS data were also good (i.e., adjusted R 2 = 0. 844 or higher). Data suggest that, although laboratory and method of measuring pressure are sources of variation in GPP estimation, it should be possible using appropriate mathematical models to standardise data among laboratories so that data from one laboratory could be extrapolated to others. This would allow development of a database of GPP data from many diverse feeds. (c) 2005 Published by Elsevier B.V.

Output risk aspects of genetically modified crop technology in South Africa

Technology involving genetic modification of crops has the potential to make a contribution to rural poverty reduction in many developing countries. Thus far, insecticide-producing '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 insecticide 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 using a three-year farm-level dataset on smallholder cotton production in Makhathini flats, Kwa-Zulu Natal, South Africa. Stochastic dominance and stochastic production function estimation methods are used to examine the risk properties of the two technologies. Results indicate that Bt technology increases output risk by being most effective when crop growth conditions are good, but being less effective when conditions are less favourable. However, in spite of its risk increasing effect, the mean output performance of Bt cotton is good enough to make it preferable to conventional technology even for risk-averse smallholders.

Tropospheric ozone and winter wheat production in England and Wales: A note

Tropospheric ozone is an air pollutant thought to reduce crop yields across Europe. Much experimental scientific work has been completed or is currently underway to quantify yield effects at ambient ozone levels. In this research, we seek to directly evaluate whether such effects are observed at the farm level. This is done by intersecting a farm level panel dataset for winter wheat farms in England & Wales with information on ambient ozone, and estimating a production function with ozone as a fixed input. Panel data methods, Generalised Method of Moments (GMM) techniques and nested exogeneity tests are employed in the estimation. The results confirm a small, but nevertheless statistically significant negative effect of ambient ozone levels on wheat yields.

The influence of winter oilseed rape (Brassica napus ssp oleifera var. biennis) cultivar and grass genotype on the competitive balance between crop and grass weeds

Three experiments conducted over two years (2002-04) at the Crops Research Unit, University of Reading, investigated competition between autumn sown oilseed rape cultivars (Brassica napus L. ssp. oleifera var. biennis (DC.) Metzg.) and Lolium multiflorum Lam., L. x boucheanum Kunth and Alopecurus myosuroides Huds., sown as indicative grass weeds. Rape cultivar (cv.) had a substantial effect on grass weed seed return. Over the six cultivars tested, L. multiflorum spikelet production ranged from just under 400 spikelets/m(2) in the presence of cv. Winner to nearly 5800 in competition with cv. Lutin. Cultivar competitiveness was associated with high biomass, large dense floral layers and early stem extension. There was some evidence of differential competitive tolerance between rape cultivars. The results suggested that rape cultivars could be screened for competitiveness by measuring floral layer interception of photosynthetic active radiation. L. x boucheanum cultivars varied in ability to compete with rape. In the absence of inter-specific competition, spikelet density was similar for Aberecho and Polly (circa 31000 spikelets/m(2)) but when grown with rape Polly outyielded Aberecho (i.e. 12 090 and 7990 spikelets/m(2) respectively).

The influence of winter oilseed rape (Brassica napus ssp oleifera var. biennis) cultivar and grass genotype on the competitive balance between crop and grass weeds

Three experiments conducted over two years (2002-04) at the Crops Research Unit, University of Reading, investigated competition between autumn sown oilseed rape cultivars (Brassica napus L. ssp. oleifera var. biennis (DC.) Metzg.) and Lolium multiflorum Lam., L. x boucheanum Kunth and Alopecurus myosuroides Huds., sown as indicative grass weeds. Rape cultivar (cv.) had a substantial effect on grass weed seed return. Over the six cultivars tested, L. multiflorum spikelet production ranged from just under 400 spikelets/m(2) in the presence of cv. Winner to nearly 5800 in competition with cv. Lutin. Cultivar competitiveness was associated with high biomass, large dense floral layers and early stem extension. There was some evidence of differential competitive tolerance between rape cultivars. The results suggested that rape cultivars could be screened for competitiveness by measuring floral layer interception of photosynthetic active radiation. L. x boucheanum cultivars varied in ability to compete with rape. In the absence of inter-specific competition, spikelet density was similar for Aberecho and Polly (circa 31000 spikelets/m(2)) but when grown with rape Polly outyielded Aberecho (i.e. 12 090 and 7990 spikelets/m(2) respectively).

Method for the production of cotton somatic embryos. United States Patent Application

The present invention provides Inter alia, a method for the production of cotton somatic embryos comprising (a) isolating a totipotent stomatal cell-containing epidermal explant from leaf material excised from a cotton plant; and (b) culturing said explant in a basal medium which comprises an embryogenic callus-inducing quantity of an auxin and a cytokinin under an embryogenic callus inducing intensity of light until embryogenic callus is formed; and (c) sub-culturing said embryogenic callus onto a somatic embryo differentiation media to produce said somatic embryos. Plants may be regenerated from the somatic embryos and in a particular embodiment of the invention said totipotent stomatal cell is transformed, prior to the inducement of embryogenic callus, with a polynucleotide that provides for a desired agronomic trait.

Production of haploids and doubled haploids in oil palm

Background: Oil palm is the world’s most productive oil-food crop despite yielding well below its theoretical maximum. This maximum could be approached with the introduction of elite F1 varieties. The development of such elite lines has thus far been prevented by difficulties in generating homozygous parental types for F1 generation. Results: Here we present the first high-throughput screen to identify spontaneously-formed haploid (H) and doubled haploid (DH) palms. We secured over 1,000 Hs and one DH from genetically diverse material and derived further DH/mixoploid palms from Hs using colchicine. We demonstrated viability of pollen from H plants and expect to generate 100% homogeneous F1 seed from intercrosses between DH/mixoploids once they develop female inflorescences. Conclusions: This study has generated genetically diverse H/DH palms from which parental clones can be selected in sufficient numbers to enable the commercial-scale breeding of F1 varieties. The anticipated step increase in productivity may help to relieve pressure to extend palm cultivation, and limit further expansion into biodiverse rainforest.

Effects of reduced height (Rht) and photoperiod insensitivity (Ppd) alleles on yield of wheat in contrasting production systems

Near isogenic lines (NILs) varying for reduced height (Rht) and photoperiod insensitivity (Ppd-D1) alleles in a cv. Mercia background (rht (tall), Rht-B1b, Rht-D1b, Rht-B1c, Rht8c+Ppd-D1a, Rht-D1c, Rht12) were compared for interception of photosynthetically active radiation (PAR), radiation use efficiency (RUE), above-ground biomass (AGB), harvest index (HI), height, weed prevalence, lodging and grain yield, at one field site but within contrasting (‘organic’ v ‘conventional’) rotational and agronomic contexts, in each of three years. In the final year, further NILs (rht (tall), Rht-B1b, Rht-D1b, Rht-B1c, Rht-B1b+Rht-D1b, Rht-D1b+Rht-B1c) in Maris Huntsman and Maris Widgeon backgrounds were added together with 64 lines of a doubled haploid (DH) population [Savannah (Rht-D1b) × Renesansa (Rht-8c+Ppd-D1a)]. There were highly significant genotype × system interactions for grain yield, mostly because differences were greater in the conventional system than in the organic system. Quadratic fits of NIL grain yield against height were appropriate for both systems when all NILs and years were included. Extreme dwarfing was associated with reduced PAR, RUE, AGB, HI, and increased weed prevalence. Intermediate dwarfing was often associated with improved HI in the conventional system, but not in the organic system. Heights in excess of the optimum for yield were associated particularly with reduced HI and, in the conventional system, lodging. There was no statistical evidence that optimum height for grain yield varied with system although fits peaked at 85cm and 96cm in the conventional and organic systems, respectively. Amongst the DH lines, the marker for Ppd-D1a was associated with earlier flowering, and just in the conventional system also with reduced PAR, AGB and grain yield. The marker for Rht-D1b was associated with reduced height, and again just in the conventional system, with increased HI and grain yield. The marker for Rht8c reduced height, and in the conventional system only, increased HI. When using the System × DH line means as observations grain yield was associated with height and early vegetative growth in the organic system, but not in the conventional system. In the conventional system, PAR interception after anthesis correlated with yield. Savannah was the highest yielding line in the conventional system, producing significantly more grain than several lines that out yielded it in the organic system.

Ecosystem services and food production

By 2030, the world’s human population could rise to 8 billion people and world food demand may increase by 50%. Although food production outpaced population growth in the 20th century, it is clear that the environmental costs of these increases cannot be sustained into the future. This challenges us to re-think the way we produce food. We argue that viewing food production systems within an ecosystems context provides the basis for 21st century food production. An ecosystems view recognises that food production systems depend on ecosystem services but also have ecosystem impacts. These dependencies and impacts are often poorly understood by many people and frequently overlooked. We provide an overview of the key ecosystem services involved in different food production systems, including crop and livestock production, aquaculture and the harvesting of wild nature. We highlight the important ecosystem impacts of food production systems, including habitat loss and degradation, changes to water and nutrient cycles across a range of scales, and biodiversity loss. These impacts often undermine the very ecosystem services on which food production systems depend, as well as other ecosystem services unrelated to food. We argue that addressing these impacts requires us to re-design food production systems to recognise and manage the limitations on production imposed by the ecosystems within which they are embedded, and increasingly embrace a more multifunctional view of food production systems and associated ecosystems. In this way, we should be able to produce food more sustainably whilst inflicting less damage on other important ecosystem services.