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.

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.

Detection of somaclonal variation during cocoa somatic embryogenesis characterised using cleaved amplified polymorphic sequence and the new freeware Artbio

The scarcity and stochastic nature of genetic mutations presents a significant challenge for scientists seeking to characterise de novo mutation frequency at specific loci. Such mutations can be particularly numerous during regeneration of plants from in vitro culture and can undermine the value of germplasm conservation efforts. We used cleaved amplified polymorphic sequence (CAPS) analysis to characterise new mutations amongst a clonal population of cocoa plants regenerated via a somatic embryogenesis protocol used previously for cocoa cryopreservation. Efficacy of the CAPS system for mutation detection was greatly improved after an ‘a priori’ in silico screen of reference target sequences for actual and potential restriction enzyme recognition sites using a new freely available software called Artbio. Artbio surveys known sequences for existing restriction enzyme recognition sites but also identifies all single nucleotide polymorphism (SNP) deviations from such motifs. Using this software, we performed an in silico screen of seven loci for restriction sites and their potential mutant SNP variants that were possible from 21 restriction enzymes. The four most informative locus-enzyme combinations were then used to survey the regenerant populations for de novo mutants. We characterised the pattern of point mutations and, using the outputs of Artbio, calculated the ratio of base substitution in 114 somatic embryo-derived cocoa regenerants originating from two explant genotypes. We found 49 polymorphisms, comprising 26.3% of the samples screened, with an inferred rate of 2.8 × 10−3 substitutions/screened base. This elevated rate is of a similar order of magnitude to previous reports of de novo microsatellite length mutations arising in the crop and suggests caution should be exercised when applying somatic embryogenesis for the conservation of plant germplasm.

An improved methodology for the recovery of Zea mays and other large crop pollen, with implications for environmental archaeology in the Neotropics

We present a simple sieving methodology to aid the recovery of large cultigen pollen grains, such as maize (Zea mays L.), manioc (Manihot esculenta Crantz), and sweet potato (Ipomoea batatas L.), among others, for the detection of food production using fossil pollen analysis of lake sediments in the tropical Americas. The new methodology was tested on three large study lakes located next to known and/or excavated pre-Columbian archaeological sites in South and Central America. Five paired samples, one treated by sieving, the other prepared using standard methodology, were compared for each of the three sites. Using the new methodology, chemically digested sediment samples were passed through a 53 µm sieve, and the residue was retained, mounted in silicone oil, and counted for large cultigen pollen grains. The filtrate was mounted and analysed for pollen according to standard palynological procedures. Zea mays (L.) was recovered from the sediments of all three study lakes using the sieving technique, where no cultigen pollen had been previously recorded using the standard methodology. Confidence intervals demonstrate there is no significant difference in pollen assemblages between the sieved versus unsieved samples. Equal numbers of exotic Lycopodium spores added to both the filtrate and residue of the sieved samples allow for direct comparison of cultigen pollen abundance with the standard terrestrial pollen count. Our technique enables the isolation and rapid scanning for maize and other cultigen pollen in lake sediments, which, in conjunction with charcoal and pollen records, is key to determining land-use patterns and the environmental impact of pre-Columbian societies.

Assessing the benefits of crop albedo bio-geoengineering

It has been proposed that growing crop varieties with higher canopy albedo would lower summer-time temperatures over North America and Eurasia and provide a partial mitigation of global warming ('bio-geoengineering') (Ridgwell et al 2009 Curr. Biol. 19 1–5). Here, we use a coupled ocean–atmosphere–vegetation model (HadCM3) with prescribed agricultural regions, to investigate to what extent the regional effectiveness of crop albedo bio-geoengineering might be influenced by a progressively warming climate as well as assessing the impacts on regional hydrological cycling and primary productivity. Consistent with previous analysis, we find that the averted warming due to increasing crop canopy albedo by 0.04 is regionally and seasonally specific, with the largest cooling of ~1 °C for Europe in summer whereas in the low latitude monsoonal SE Asian regions of high density cropland, the greatest cooling is experienced in winter. In this study we identify potentially important positive impacts of increasing crop canopy albedo on soil moisture and primary productivity in European cropland regions, due to seasonal increases in precipitation. We also find that the background climate state has an important influence on the predicted regional effectiveness of bio-geoengineering on societally-relevant timescales (ca 100 years). The degree of natural climate variability and its dependence on greenhouse forcing that are evident in our simulations highlights the difficulties faced in the detection and verification of climate mitigation in geoengineering schemes. However, despite the small global impact, regionally focused schemes such as crop albedo bio-geoengineering have detection advantages.

Spatial pattern detection modeling of thrips (Thrips tabaci) on onion fields

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Rapid degradation of propanil in rice crop fields

Propanil and its major degradation product, 3,4-dichloroaniline (DCA), were monitored in surface water and soil samples from two rice fields of the Ebre Delta area (Tarragona, Spain) following agricultural application. On-line solid-phase extraction (SPE) (water) and Soxhlet extraction (soil) followed by liquid chromatography/diode array detection (LC/DAD) were used for the trace determination of both compounds. Unequivocal confirmation/identification was conducted by using liquid chromatography/atmospheric pressure chemical ionization-mass spectrometry, LC/APCI/MS (using negative and positive ionization modes). Concentrations of the herbicide propanil in water samples varied from 1.9 to 55.9 mu g/L. Propanil degraded very rapidly to DCA, and high concentrations of this product were found, varying from 16.5 to 470 mu g/L in water and 119 +/- 22 mu g/kg in soil samples. No detectable DCA (<0.001%) was found in the applied pesticide formulation, indicating that DCA formation took place after propanil application. These field results compared favorably with laboratory experiments showing that humic interactions had a strong influence on the pesticide degradation. The half-lifes under real conditions for propanil and DCA, calculated using a first-order decay, were 1.2 and 1.6 days, respectively.

Validation of an immunoassay method for the determination of traces of carbaryl in vegetable and fruit extracts by liquid chromatography with photodiode array and mass spectrometric detection

A competitive enzyme-linked immunosorbent assay (ELISA) method for carbaryl quantitation in crop extracts was validated by liquid chromatography (LC) with diode array detection (DAD). For this purpose, six crops (banana, carrot, green bean, orange, peach and potato) were chosen for recovery and reproducibility studies. The general sample preparation included extraction with methanol followed by liquid-liquid partitioning and clean-up on Celite-charcoal adsorbent column of the vegetable extracts. ELISA samples consisted of a diluted LC extract in assay phosphate buffer (pH 7.5). The potential effect of methanol in these samples was evaluated. It was observed that a maximum content of 10% methanol present in the assay buffer could be tolerated without expressive losses in the ELISA performance. Under these conditions, a IC50 similar to 1.48 mu g l(-1) was obtained. A minimum matrix effect with a 1:50 dilution of the methanolic extracts in assay buffer was noticed, except for green bean samples that inhibited completely the assay. For the vegetable extracts, the ELISA sensitivities varied from 3.9 to 5.7 mu g l(-1), and good recoveries (82-96%) with R.S.D.s ranging from 5.7 to 12.1% were found. An excellent correlation between the LC-DAD and ELISA techniques was obtained. The confirmation of the carbaryl in less concentrated samples was achieved by LC-mass spectrometry interfaced with atmospheric pressure chemical ionisation. The [M + H](+)= 202 and [M + H-57](+)=145 ions, equivalent to the protonated molecular and l-naphthol ions, respectively, were used to carbaryl identification in these samples. (C) 1998 Elsevier B.V. B.V. All rights reserved.

Determination of carbamate residues in crop samples by cholinesterase-based biosensors and chromatographic techniques

An amperometric biosensor based on cholinesterase (ChE) has been used for the determination of selected carbamate insecticides in vegetable samples. The linear range of the biosensor for the N-methylcarbamates (aldicarb, carbaryl, carbofuran, methomyl and propoxur) varied from 5 x 10(-5) to 50 mg kg(-1). Limits of detection were calculated on the basis that the ChE enzymes were 10% inhibited and varied, depending of the combination ChE (as acetyl- or butyrylcholinesterase) vs. inhibitor (pesticide), from 1 x 10(-4) to 3.5 mg kg(-1). The biosensor-based carbamate determination was compared to liquid chromatography/UV methods. Three vegetable samples were spiked with carbofuran and propoxur at 125 mu g kg(-1) followed by conventional procedures. Good correlations were observed for carbofuran in the vegetable extracts (79, 96 and 91% recoveries for potato, carrot and sweet pepper, respectively), whereas for propoxur unsatisfactory results were obtained. Potato and carrot samples were spiked with 10, 50 and 125 mu g kg(-1) carbofuran, followed by direct determination by the amperometric biosensor. The fortified sampler; resulted in very high inhibition values, and recoveries were: 28, 34 and 99% for potato, and 140, 90 and 101% for carrot, respectively, at these three fortification levels. (C) 1998 Elsevier B.V. B.V.

Identification of foliar diseases in cotton crop

The pathogens manifestation in plantations are the largest cause of damage in several cultivars, which may cause increase of prices and loss of crop quality. This paper presents a method for automatic classification of cotton diseases through feature extraction of leaf symptoms from digital images. Wavelet transform energy has been used for feature extraction while Support Vector Machine has been used for classification. Five situations have been diagnosed, namely: Healthy crop, Ramularia disease, Bacterial Blight, Ascochyta Blight, and unspecified disease. © 2012 Taylor & Francis Group.

Bacteriophage- induced reduction in Salmonella Enteritidis counts in the crop of broiler chickens undergoing preslaughter feed withdrawal

Salmonella food poisoning is a public health problem. Feed withdrawal from broiler chickens before slaughter can favor the multiplication of Salmonella in the cecum and crop of contaminated animals and subsequently lead to contamination of carcasses in the processing plant. In the present study, a cocktail of lytic bacteriophages isolated from sewage water was orally administered to 45-d-old broiler chickens 1 h after they received an oral dose of 107 cfu/mL Salmonella enterica subspecies enterica serotype Enteritidis. Immediately after phage administration and 30 min, 1, 3, 6, and 12 h thereafter, groups of chicken were killed. Ceca and crops were analyzed for the presence of Salmonella. At 3 h posttreatment, there were 103 cfu/g and 101 cfu/g of cecal and crop suspension, respectively. At 6 h after treatment, the number of Salmonella was 103 cfu/g in the cecal suspension, but below the detection limit in the crops. our results suggest that bacteriophage therapy may be able to reduce the contamination of chicken carcasses by reducing the preslaughter load of Salmonella in the birds.

QTL detection of yield-related traits of cashew

The identification of quantitative trait loci (QTL) and marker-assisted selection with a view to breeding programs have aroused great interest, including for cashew improvement. This study identified QTL for yield-related traits: nut weight, male and hermaphrodite flowers. The traits were evaluated in 71 F-1 genotypes of the cross CCP 1001 x CP 96. The methods of interval mapping and multiple QTL mapping were applied to identify QTL. Eleven QTL were detected: three for nut weight, four for male flowers and four for hermaphrodite flowers. The QTL accounted for 3.79 to 12.98 % of the total phenotypic variance and had phenotypic effects of -31.81 to 34.25 %. The potential for marker-assisted selection of the QTL hf-2f and hf-3m is great and the phenotypic effects and percentage of phenotypic variation higher than of the others.

Detection and molecular characterization of viruses infecting Actinidia spp.

Kiwifruit (genus Actinidia) is an important horticultural crop grown in the temperate regions. The four world’s largest producers are China, Italy, New Zealand and Chile. More than 50 species are recognized in the genus but the principal species in cultivation are A. deliciosa and A. chinensis. In Italy, as well as in many other countries, the kiwifruit crop has been considered to be relatively disease free and then no certification system for this species has been developed to regulate importation of propagation plant material in the European Union. During the last years a number of fungal and bacterial diseases have been recorded such as Botrytis cinerea and Pseudomonas syringae pv. actinidiae. Since 2003, several viruses and virus-like diseases have been identified and more recent studies demonstrated that Actinidia spp can be infected by a wide range of viral agents. In collaboration with the University of Auckland we have been detected thirteen different viral species on kiwifruit plants. During the three years of my PhD I worked on the characterization of Cucumber mosaic virus (CMV) and Pelargonium zonate spot virus (PZSV). The determination of causal agents has been based on host range, symptom expression in the test plant species and morphological properties of the virus particles using transmission electron microscopy (TEM) and using specific oligonucleotide primers in reverse transcription-polymerase chain reaction (RT-PCR). Both viruses induced several symptoms on kiwifruit plants. Moreover with new technologies such as high-throughput sequencing we detected additional viruses, a new member of the family Closteroviridae and a new member of the family Totiviridae. Taking together all results of my studies it is clear that, in order to minimize the risk of serious viral disease in kiwifruit, it is vital to use virus-free propagation material in order to prevent the spread of these viruses.

Real-time image processing for crop/weed discrimination in maize fields

This paper presents a computer vision system that successfully discriminates between weed patches and crop rows under uncontrolled lighting in real-time. The system consists of two independent subsystems, a fast image processing delivering results in real-time (Fast Image Processing, FIP), and a slower and more accurate processing (Robust Crop Row Detection, RCRD) that is used to correct the first subsystem's mistakes. This combination produces a system that achieves very good results under a wide variety of conditions. Tested on several maize videos taken of different fields and during different years, the system successfully detects an average of 95% of weeds and 80% of crops under different illumination, soil humidity and weed/crop growth conditions. Moreover, the system has been shown to produce acceptable results even under very difficult conditions, such as in the presence of dramatic sowing errors or abrupt camera movements. The computer vision system has been developed for integration into a treatment system because the ideal setup for any weed sprayer system would include a tool that could provide information on the weeds and crops present at each point in real-time, while the tractor mounting the spraying bar is moving

Discriminating Crop, Weeds and Soil Surface with a Terrestrial LIDAR Sensor

In this study, the evaluation of the accuracy and performance of a light detection and ranging (LIDAR) sensor for vegetation using distance and reflection measurements aiming to detect and discriminate maize plants and weeds from soil surface was done. The study continues a previous work carried out in a maize field in Spain with a LIDAR sensor using exclusively one index, the height profile. The current system uses a combination of the two mentioned indexes. The experiment was carried out in a maize field at growth stage 12–14, at 16 different locations selected to represent the widest possible density of three weeds: Echinochloa crus-galli (L.) P.Beauv., Lamium purpureum L., Galium aparine L.and Veronica persica Poir.. A terrestrial LIDAR sensor was mounted on a tripod pointing to the inter-row area, with its horizontal axis and the field of view pointing vertically downwards to the ground, scanning a vertical plane with the potential presence of vegetation. Immediately after the LIDAR data acquisition (distances and reflection measurements), actual heights of plants were estimated using an appropriate methodology. For that purpose, digital images were taken of each sampled area. Data showed a high correlation between LIDAR measured height and actual plant heights (R 2 = 0.75). Binary logistic regression between weed presence/absence and the sensor readings (LIDAR height and reflection values) was used to validate the accuracy of the sensor. This permitted the discrimination of vegetation from the ground with an accuracy of up to 95%. In addition, a Canonical Discrimination Analysis (CDA) was able to discriminate mostly between soil and vegetation and, to a far lesser extent, between crop and weeds. The studied methodology arises as a good system for weed detection, which in combination with other principles, such as vision-based technologies, could improve the efficiency and accuracy of herbicide spraying.