Experimental crop growing in Jordan to develop methodology for the identification of ancient crop irrigation

Crop irrigation has long been recognized as having been important for the evolution of social complexity in several parts of the world. Structural evidence for water management, as in the form of wells, ditches and dams, is often difficult to interpret and may be a poor indicator of past irrigation that may have had no need for such constructions. It would be of considerable value, therefore, to be able to infer past irrigation directly from archaeo-botanical remains, and especially the type of archaeo-botanical remains that are relatively abundant in the archaeological record, such as phytoliths. Building on the pioneering work of Rosen and Wiener (1994), this paper describes a crop-growing experiment designed to explore the impact of irrigation on the formation of phytoliths within cereals. If it can be shown that a systemic and consistent relationship exists between phytolith size, structure and the intensity of irrigation, and if various taphonomic and palaeoenvironmental processes can be controlled for, then the presence of past irrigation can feasibly be inferred from the phytoliths recovered from the archaeological record.

Factors affecting the adoption of leguminous cover crops in Nigeria and a comparison with the adoption of new crop varieties

This paper presents the results of (a) On-farm trials (eight) over a two-year period designed to test the effectiveness of leguminous cover crops in terms of increasing maize yields in Igalaland, Nigeria. (b) A survey designed to monitor the extent of, and reasons behind, adoption of the leguminous cover crop technology in subsequent years by farmers involved, to varying degrees, in the trial programme. particular emphasis was placed on comparing adoption of leguminous cover crops with that of new crop varieties released by a non-governmental organization in the same area since the mid 1980s. While the leguminous cover crop technology boosted maize grain yields by 127 to 136% above an untreated control yield of between 141 and 171 kg ha(-1), the adoption rate (number of farmers adopting) was only 18%. By way of contrast, new crop varieties had a highly variable benefit in terms of yield advantage over local varieties, with the best average increase of around 20%. Adoption rates for new crop varieties, assessed as both the number of farmers growing the varieties and the number of plots planted to the varieties, were 40% on average. The paper discusses some key factors influencing adoption of the leguminous cover crop technology, including seed availability. Implications of these results for a local non-governmental organization, the Diocesan Development Services, concerned with promoting the leguminous cover crop technology are also discussed.

The development and contribution of surface charge by crop residues in two Malawian acid soils

The effects of maize and soya bean residues on the pH and charge of a loamy sand (Kawalazi) and a sandy clay loam (Naming'omba) from Malawi were measured to determine both the indirect effect of the residues on soil charge through the changes in pH, and the direct contribution of charge carried on the residue surfaces. The soils had pH values (10 mM CaCl2) of 4.3 and 5.0 and organic matter contents were 1.4% and 2.7%, respectively. The clay fractions were dominated by kaolinite and goethite, and mica was present in both samples. The soils were incubated for 28 days with maize (Zea mays) and soya bean (Glycine max) residues. The maximum addition of residue (12.0%) in the Kawalazi and Naming'omba soils increased the pH from 4.3 and 5.0 to 4.8 and 5.3 (maize) and to 9.0 and 8.8 (soya bean), respectively. Negative charge increased from 2.1 and 4.7 cmol(c) kg(-1) to 3.8 and 7.5 (maize) and to 5.3 and 9.3 cmol(c) kg(-1) (soya bean). Positive charge increased from 0.72 and 0.62 to 0.87 and 0.85 cmol(c) kg(-1) (maize) and to 0.75 and 0.68 (soya bean). The charge contribution by the residues was calculated by difference between the charge on a sample incubated with residue and the charge on a soil without residue limed to the same pH value. Up to 100 cmolc negative charge and 10 cmol(c) of positive charge per kg of residue were directly contributed to the soil-residue mixture, the amounts depending on the type of residue, the extent to which the residue was decomposed in the soil and the pH of the mixture. The Anderson and Sposito method [Soil Sci. Soc. Am. J. 55 (1991) 1569] was used to partition the permanent negative charge (holding Cs+) from variable negative charge (holding Li+). In the pH range 3.7-6.5 the maize residue contributed between 3 and 26 cmol(c) of variable charge per kg of residue in the Kawalazi soil and between 6 and 25 cmol(c) per kg of residue in the Naming'omba soil. For soya bean the values were between I and 28 and between 4 and 68 cmolc per kg of residue, respectively. At a given pH value, the charge tended to increase with time of incubation and for a given addition of residue, pH decreased during incubation. Addition of residues contributed no permanent negative charge and the charge on the soil measured by Cs adsorption was independent of pH change caused by the residue showing that the method is valid for soil-residue mixtures. With time there was a decrease in the amount of permanent charge probably due to masking as humic material become adsorbed on mineral surfaces. (C) 2003 Elsevier Science B.V. All rights reserved.

Production risk, pesticide use and GM 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, pesticide-producing Bacillus thuringensis (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 pesticide 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 by estimating two 'flexible risk' production function models allowing technology to independently affect the mean and higher moments of output. The first is the popular Just-Pope model and the second is a more general 'damage control' flexible risk model. The models are applied to cross-sectional data on South African smallholders, some of whom used Bt varieties. The results show no evidence that a 'risk-reduction' claim can be made for Bt technology. Indeed, there is some evidence to support the notion that the technology increases output risk, implying that simple (expected) profit computations used in past evaluations may overstate true benefits.

Transcriptome analysis and crop improvement (a review)

The identification and characterization of differential gene expression from tissues subjected to stress has gained much attention in plant research. The recognition of elements involved in the response to a particular stress enhances the possibility of promoting crop improvement through direct genetic modification. However, the performance of some of the 'first generation' of transgenic plants with the incorporation of a single gene has not always been as expected. These results have stimulated the development of new transgenic constructions introducing more than one gene and capable of modifying complex pathways. Several techniques are available to conduct the analysis of gene regulation, with such information providing the basis for novel constructs specifically designed to modify metabolism. This review deals with techniques that allow the identification and characterization of differentially-expressed genes and the use of molecular pathway information to produce transgenic plants.

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.

Landscape gene flow, coexistence and threshold effect: The case of genetically modified herbicide tolerant oilseed rape (Brassica napus)

Globally there have been a number of concerns about the development of genetically modified crops many of which relate to the implications of gene flow at various levels. In Europe these concerns have led the European Union (EU) to promote the concept of 'coexistence' to allow the freedom to plant conventional and genetically modified (GM) varieties but to minimise the presence of transgenic material within conventional crops. Should a premium for non-GM varieties emerge on the market, the presence of transgenes would generate a 'negative externality' to conventional growers. The establishment of maximum tolerance level for the adventitious presence of GM material in conventional crops produces a threshold effect in the external costs. The existing literature suggests that apart from the biological characteristics of the plant under consideration (e.g. self-pollination rates, entomophilous species, anemophilous species, etc.), gene flow at the landscape level is affected by the relative size of the source and sink populations and the spatial arrangement of the fields in the landscape. In this paper, we take genetically modified herbicide tolerant oilseed rape (GM HT OSR) as a model crop. Starting from an individual pollen dispersal function, we develop a spatially explicit numerical model in order to assess the effect of the size of the source/sink populations and the degree of spatial aggregation on the extent of gene flow into conventional OSR varieties under two alternative settings. We find that when the transgene presence in conventional produce is detected at the field level, the external cost will increase with the size of the source area and with the level of spatial disaggregation. on the other hand when the transgene presence is averaged among all conventional fields in the landscape (e.g. because of grain mixing before detection), the external cost will only depend on the relative size of the source area. The model could readily be incorporated into an economic evaluation of policies to regulate adoption of GM HT OSR. (c) 2007 Elsevier B.V. All rights reserved.

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.

Assessing the vulnerability of food crop systems in Africa to climate change

Africa is thought to be the region most vulnerable to the impacts of climate variability and change. Agriculture plays a dominant role in supporting rural livelihoods and economic growth over most of Africa. Three aspects of the vulnerability of food crop systems to climate change in Africa are discussed: the assessment of the sensitivity of crops to variability in climate, the adaptive capacity of farmers, and the role of institutions in adapting to climate change. The magnitude of projected impacts of climate change on food crops in Africa varies widely among different studies. These differences arise from the variety of climate and crop models used, and the different techniques used to match the scale of climate model output to that needed by crop models. Most studies show a negative impact of climate change on crop productivity in Africa. Farmers have proved highly adaptable in the past to short- and long-term variations in climate and in their environment. Key to the ability of farmers to adapt to climate variability and change will be access to relevant knowledge and information. It is important that governments put in place institutional and macro-economic conditions that support and facilitate adaptation and resilience to climate change at local, national and transnational level.

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.