- Mathematical and Statistical Methods - Biometris (3)
- Ecosystemen (2)
- IMARES Ecosystemen (2)
- IMARES Onderzoeksformatie (2)
- Onderzoeksformatie (2)
- WIMEK (2)
- Aquatic Ecology and Water Quality Management (1)
- Business Management & Organization (1)
- Crop and Weed Ecology (1)
- Environmental Economics and Natural Resources (1)
- Environmental Economics and Natural Resources Group (1)
- ID Lelystad, Institute for Animal Science and Health (1)
- Laboratory of Virology (1)
- MGS (1)
- Management Studies (1)
- Physical Chemistry and Colloid Science (1)
- Theoretical Production Ecology (1)
- J. Borovicka (1)
- F. Bosch van den (4)
- S. Cleland (1)
- M. Cronin (1)
- Friso Dalm (1)
- A.C. Davies (1)
- A.O. Debrot (6)
- A. Donald (1)
- B. Duim (1)
- A. Dusi (1)
- S. Escher (1)
- A. Fernandez (1)
- J.A. Frost (1)
- S.G.M. Gabbert (1)
- S.C.V. Geelhoed (2)
- F. Giralt (1)
- G. Gort (1)
- H.H. Hendon (1)
- Roberto Hensen (1)
- M. Hewitt (1)
- J. Holt (2)
- M. Hrovat (1)
- W. Hulsink (1)
- M.J. Jeger (4)
- S. Jeram (1)
- D. Kroese (1)
- T.W. Leslie (1)
- J. Ligon (1)
- L.V. Madden (6)
- R.H. Madden (1)
- J. Madden (1)
- H. Madden (6)
- L.A. Madden (1)
- I. Mangelsdorf (1)
- H.B. Meinke (1)
- W.J. Metheringham (1)
- J.Y. Miller (1)
- M. Nendza (1)
- D.G. Newell (1)
- S.L.W. On (1)
- V.N. Paunov (1)
- A. Pielaat (1)
- S. Piontek (2)
- J. Plas van der (1)
- R. Rallo (1)
- A. Reid (1)
- A.C. Rojer (1)
- A. Roncaglioni (1)
- E. Rorije (1)
- S. Savary (1)
- H. Segner (1)
- B. Simon-Hettich (1)
- J. Stapel (2)
- S.D. Stoyanov (1)
- Lara Uphoff (1)
- T. Vemeire (1)
- J.P. Verdaat (2)
- J.A. Wagenaar (1)
- Steffan Walton (1)
- C.D. Walton (1)
- M.C. Wheeler (1)
- S.R. Williams (1)
- K. Wulf (1)
- J.C. Zadoks (1)
- Leonie Zwet van der (1)
|Encouraging results for controlling an Agricultural pest on St. Eustatius
Debrot, A.O. ; Reid, A. ; Leslie, T.W. ; Madden, H. ; Stapel, J. ; Dalm, Friso ; Uphoff, Lara ; Zwet, Leonie van der - \ 2016
BioNews (2016)26. - p. 8 - 8.
In 2013, the invasive Giant African Land Snail, Achatina fulica was found in a small part of urban St. Eustatius. In collaboration with local government agencies and Dutch universities, IMARES* conducted field and laboratory pilot trials of control methods from October 2015 to June 2016.
New bird records for the Island of St. Eustatius, Dutch Caribbean, with notes on other significant sightings
Madden, H. ; Hensen, Roberto ; Piontek, S. ; Walton, Steffan ; Verdaat, J.P. ; Geelhoed, S.C.V. ; Stapel, J. ; Debrot, A.O. - \ 2015
The Journal of Caribbean Ornithology 28 (2015). - ISSN 1544-4953 - p. 28 - 34.
avifauna - Dutch Caribbean - Netherlands Antilles - St. Eustatius
The avifauna of the Dutch Caribbean island of St. Eustatius has been little studied. We document 22 new bird species for the island and update the status of several important species based on our recent observations. The documented avifauna of
the island amounts to 75 published species records. We conclude by pointing out several positive developments in the avifauna and ascribe these to the combined effects of reduced hunting, the legal establishment of protected park areas, and a growing environmental awareness among the island’s inhabitants
Iguana delicatissima (Lesser Antillean Iguana) Reproduction
Debrot, A.O. ; Boman, E. ; Piontek, S. ; Madden, H. - \ 2014
Herpetological Review 45 (2014)1. - ISSN 0018-084X - p. 129 - 130.
Photothermal Colloid Antibodies for Shape-Selective Recognition and Killing of Microorganisms
Borovicka, J. ; Metheringham, W.J. ; Madden, L.A. ; Walton, C.D. ; Stoyanov, S.D. ; Paunov, V.N. - \ 2013
Journal of the American Chemical Society 135 (2013)14. - ISSN 0002-7863 - p. 5282 - 5285.
tobacco-mosaic-virus - gold nanoparticles - pathogenic bacteria - cancer-cells - lysis - challenge - nanorods - therapy
We have developed a class of selective antimicrobial agents based on the recognition of the shape and size of the bacterial cells. These agents are anisotropic colloid particles fabricated as negative replicas of the target cells which involve templating of the cells with shells of inert material followed by their fragmentation. The cell shape recognition by such shell fragments is due to the increased area of surface contact between the cells and their matching shell fragments which resembles antibody-antigen interaction. We produced such "colloid antibodies" with photothermal mechanism for shape-selective killing of matching cells. This was achieved by the subsequent deposition of (i) gold nanoparticles (AuNPs) and (ii) silica shell over yeast cells, which were chosen as model pathogens. We demonstrated that fragments of these composite AuNP/silica shells act as "colloid antibodies" and can bind to yeast cells of the same shape and size and deliver AuNPs directly onto their surface. We showed that after laser irradiation, the localized heating around the AuNPs kills the microbial cells of matching shape. We confirmed the cell shape-specific killing by photothermal colloid antibodies in a mixture of two bacterial cultures of different cell shape and size. This approach opens a number of avenues for building powerful selective biocides based on combinations of colloid antibodies and cell-killing strategies which can be applied in new antibacterial therapies.
|Research of the Month: Butterflies of St. Sustatius, Saba and St. Maarten
Debrot, A.O. ; Madden, H. ; Becking, L.E. ; Rojer, A.C. ; Miller, J.Y. - \ 2013
BioNews 2013 (2013)09. - p. 6 - 7.
The Lesser Antillean Iguana on St. Eustatius: A 2012 Population Status Update and Causes for Concern
Debrot, A.O. ; Boman, E. ; Madden, H. - \ 2013
IRFC Reptiles & Amphibians 20 (2013)2. - p. 44 - 52.
Important Bird Areas in the Caribbean Netherlands
Geelhoed, S.C.V. ; Debrot, A.O. ; Ligon, J. ; Madden, H. ; Verdaat, J.P. ; Williams, S.R. ; Wulf, K. - \ 2013
IMARES (Report / IMARES C054/13)
Data quality assessment for in silico methods: A survey of approaches and needs
Nendza, M. ; Aldenberg, T. ; Benfenati, E. ; Benigni, R. ; Cronin, M. ; Escher, S. ; Fernandez, A. ; Gabbert, S.G.M. ; Giralt, F. ; Hewitt, M. ; Hrovat, M. ; Jeram, S. ; Kroese, D. ; Madden, J. ; Mangelsdorf, I. ; Rallo, R. ; Roncaglioni, A. ; Rorije, E. ; Segner, H. ; Simon-Hettich, B. ; Vemeire, T. - \ 2010
In: In Silico Toxicology: Principles and applications / Cronin, M., Madden, J., Cambridge, UK : Royal Society of Chemistry (Issues of toxicology 7) - ISBN 9781849730044 - p. 59 - 117.
Impacts of the Madden-Julian oscillation on Australian rainfall and circulation
Wheeler, M.C. ; Hendon, H.H. ; Cleland, S. ; Meinke, H.B. ; Donald, A. - \ 2009
Journal of Climate 22 (2009)6. - ISSN 0894-8755 - p. 1482 - 1498.
outgoing longwave radiation - tropical-extratropical interaction - northern winter - climate variability - prediction - monsoon - precipitation - temperature - reanalysis - atmosphere
Impacts of the Madden¿Julian oscillation (MJO) on Australian rainfall and circulation are examined during all four seasons. The authors examine circulation anomalies and a number of different rainfall metrics, each composited contemporaneously for eight MJO phases derived from the real-time multivariate MJO index. Multiple rainfall metrics are examined to allow for greater relevance of the information for applications. The greatest rainfall impact of the MJO occurs in northern Australia in (austral) summer, although in every season rainfall impacts of various magnitude are found in most locations, associated with corresponding circulation anomalies. In northern Australia in all seasons except winter, the rainfall impact is explained by the direct influence of the MJO's tropical convective anomalies, while in winter a weaker and more localized signal in northern Australia appears to result from the modulation of the trade winds as they impinge upon the eastern coasts, especially in the northeast. In extratropical Australia, on the other hand, the occurrence of enhanced (suppressed) rainfall appears to result from induced upward (downward) motion within remotely forced extratropical lows (highs), and from anomalous low-level northerly (southerly) winds that transport moisture from the tropics. Induction of extratropical rainfall anomalies by remotely forced lows and highs appears to operate mostly in winter, whereas anomalous meridional moisture transport appears to operate mainly in the summer, autumn, and to some extent in the spring
|Making markets: telecommunications in Western Europe
Hulsink, W. ; Davies, A.C. - \ 2003
In: World Telecommunications Markets / Madden, G., Londen : Edward Elgar Publishing (World Telecommunications Markets: The International Handbook of Telecommunications Economics 3) - ISBN 1840643412 - p. 413 - 429.
|New developments in the subtyping of Campylobacter species
Newell, D.G. ; Frost, J.A. ; Duim, B. ; Wagenaar, J.A. ; Madden, R.H. ; Plas, J. van der; On, S.L.W. - \ 2000
In: Campylobacter / Nachamkin, Irving, Blaser, Martin J., - p. 27 - 44.
A theoretical assessment of the effects of vector-virus transmission mechanisms on plant virus disease epidemics
Madden, L.V. ; Jeger, M.J. ; Bosch, F. van den - \ 2000
Phytopathology 90 (2000). - ISSN 0031-949X - p. 576 - 594.
A continuous-time and deterministic model was used to characterize plant virus disease epidemics in relation to virus transmission mechanism and population dynamics of the insect vectors. The model can be written as a set of linked differential equations for healthy (virus-free), latently infected, infectious, and removed (postinfectious) plant categories, and virus-free, latent, and infective insects, with parameters based on the transmission classes, vector population dynamics, immigration/emigration rates, and virus-plant interactions. The rate of change in diseased plants is a function of the density of infective insects, the number of plants visited per time, and the probability of transmitting the virus per plant visit. The rate of change in infective insects is a function of the density of infectious plants, the number of plants visited per time by an insect, and the probability of acquiring the virus per plant visit. Numerical solutions of the differential equations were used to determine transitional and steady-state levels of disease incidence (d*); d* was also determined directly from the model parameters. Clear differences were found in disease development among the four transmission classes: nonpersistently transmitted (stylet-borne [NP]); semipersistently transmitted (foregut-borne [SP]); circulative, persistently transmitted (CP); and propagative, persistently transmitted (PP), with the highest disease incidence (d) for the SP and CP classes relative to the others, especially at low insect density when there was no insect migration or when the vector status of emigrating insects was the same as that of immigrating ones. The PP and CP viruses were most affected by changes in vector longevity, rates of acquisition, and inoculation of the virus by vectors, whereas the PP viruses were least affected by changes in insect mobility. When vector migration was explicitly considered, results depended on the fraction of infective insects in the immigration pool and the fraction of dying and emigrating vectors replaced by immigrants. The PP and CP viruses were most sensitive to changes in these factors. Based on model parameters, the basic reproductive number (R(0))--number of new infected plants resulting from an infected plant introduced into a susceptible plant population--was derived for some circumstances and used to determine the steady-state level of disease incidence and an approximate exponential rate of disease increase early in the epidemic. Results can be used to evaluate disease management strategies. Additional keywords: compartmental model, nonlinear model, strategic modeling, theoretical epidemiology.
|A theoretical assessment of vector-virus transmission mechanisms on plant virus disease epidemics
Madden, L.V. ; Jeger, M.J. ; Bosch, F. van den - \ 1999
In: Abstracts VII International Plant Virus Epidemiology Symposium, Aguadulce, Spain, 11-16 April 1999. - [S.l.] : [s.n.], 1999 - p. 93 - 93.
Beet mosaic virus : epidemiology and damage
Dusi, A. - \ 1999
Agricultural University. Promotor(en): R.W. Goldbach; D. Peters; Wopke van der Werf. - S.l. : Dusi - ISBN 9789058080752 - 137
bietenmozaïekvirus - plantenvirussen - plantenziekteverwekkers - plantenziekten - epidemiologie - oogstschade - simulatiemodellen - Beet mosaic virus - plant viruses - plant pathogens - plant diseases - epidemiology - crop damage - simulation models
<p><strong>Overview:</strong></p><p>The aim of the studies described in this thesis was to obtain a thorough understanding of the main factors determining the spread of a potyvirus in a high plant density crop. The factors studied included the relationships between virus, host and vector, the spread of the virus around an initial virus source consisting of one or more infected plants, the spread of the virus by the prevailing aphid population, and the effect of plant density on the spread of the virus. A time-save sampling technique was developed and the damage caused was estimated. This study was made with the system beet - beet mosaic virus (BtMV), a potyvirus infecting sugar beet, as a model pathosystem. Sugar beet is a herbaceous plant widely cultivated in The Netherlands. The crop, which has a cycle of approximately 8 months, is cultivated in fields at a density of 7 to 10 plants/m <sup>2</SUP>. The disease in this crop is polycyclic, as several infection cycles occur during the growing season.</p><p>The spread of a potyvirus in a crop starts with a primary infection, either introduced by migrating aphids from sources outside the field or by the use of infected seed or propagative plant material. These plants form the sources from which the virus is spread secondarily in the field. The primary infections are in most cases scattered over the field, whereas secondary infections are aggregated around early-infected plants. Studies on the spread of a virus from a known source are few, as primary introductions are difficult to prevent in many crop virus system. Primary infections are frequently introduced at erratic moments and increase in virus incidence, due to plants infected from outside sources is superimposed on the secondary spread ongoing within the field. As BtMV is only rarely encountered in The Netherlands and not seed transmitted, this pathosystem is a good model to analyze secondary spread using a known virus source in the experimental plots. Spread was expected only to occur from these sources and not from outside sources.</p><p><strong>Development of a time saving transect sampling method:</strong></p><p>Spread of BtMV occurred around the virus source in a clustered isotropic pattern with a negative exponential gradient. Such a spread is common for polycyclic epidemics of potyviruses in annual crops (Dahal, 1992; Eckel and Lampert, 1993; Nelson and Campbell, 1993; Perring et al., 1992). The isotropic spatial pattern of spread found in all plots showed that a simple sampling method, called transect sampling method, could be developed and used to monitor the development of the infection. This method consisted of monitoring the plants on two orthogonal transects extending diagonally across the rows from the source plants in the plot. In the analysis of transect data, the uneven representation of the sampled plants at each distance class must be taken into consideration. The temporal and spatial spread of the BtMV disease could be described as reliably using the transect method, as by monitoring the whole plot, provided that a lower precision per repetition is compensated by raising the number of repetitions. This result suggests that by using this less labor intensive and less time consuming sampling method, more sites or more treatments can be studied.</p><p>This sampling method can also be applied to study the spread in other pathosystems such as <em>Papaya</em><em>ringspot</em><em>virus</em> (PRSV) in cucurbits, <em>Potato</em> vi <em>r</em> us <em>Y</em> (PVY) in crops of various solanaceous species, and <em>Soybean mosaic virus</em> (SMV) in soybeans, when the virus source is known or can be found. This sampling method can potentially also be applied to semi-persistently and persistently transmitted viruses such as <em>Beet yellows virus (</em> BYV and <em>Beet mild yellowing virus</em> (BMYV) (van der Werf, personal communication), which form usually clusters with an isotropic spatial pattern around the primarily infected virus source, in a similar fashion as BtMV.</p><p><strong>Modeling spread as a function of migrating aphid flights:</strong></p><p>Under natural conditions, aphids transmit potyviruses in a non-persistent manner. Although the interaction between the virus and the vector is specific (Shukla et al., 1994), apparent specificities in the epidemiological relationships between potyviruses and aphid species have not been elucidated. The role of the individual aphid species in the spread of potyviruses has been analyzed by different analytical methods. The simplest approach is to plot virus incidence and number of aphids counted on plants or collected with traps on a common time axis and to subjectively compare the curves obtained for the spread and the number of aphids obtained for each individual species or the total aphid population. Eckel and Lampert (1993), van Hoof (1977) and Karl et al. (1983) used this approach but could not find any relation between the species and the spread of the potyviruses studied. A pitfall of this approach is that population trends of different aphid species over time may be collinear (Chapter 4). Thus, the role of one species might not be isolated from the other. Correlation and regression analysis also usually fail to relate spread to aphid species or total counts (Madden et al., 1987; Mora-Aguilera et al., 1992; Watson and Healy, 1953).</p><p>Garrett (1988) demonstrated that, in lupine, <em>Clover yellow vein virus</em> was mostly spread by two aphid species ( <em>Aphis craccivora</em> and <em>Myzus persicae</em> ) using multiple regression analysis to relate the rate of spread of this potyvirus to the species that compose the aphid population. In the studies described here, no single species could be associated with the spread applying correlation or regression analyses. A good correlation could be detected between the total daily number of alatae caught and the spread of BtMV.</p><p>Based on the collected data, a deterministic simulation model was developed to study the spread as a function of the migrating aphid population (Chapter 4). This model was based on a logistic population growth applied to plant diseases (van der Plank, 1963). The rate of the disease was, in this model, proportional to the virus sources, healthy plants, latent and incubation periods of the virus in the plant, the total number of aphids caught in a suction trap (not discriminating species) and a parameter ( <em>r</em> ) that represented all aspects of vector activity relevant to virus spread (Jeger et al. 1998). This parameter <em>r</em> , describing the relationship between the daily catches of aphids and the number of newly infected plants, was quite robust among experiments. Remarkably, <em>r</em> appeared to be independent of the moments at which the primary inoculum sources were introduced, confirming that the chosen model and common parameter value give a seasonable mechanistic description of epidemics started at different dates. These results confirm and extend the conclusions of Di Fonzo et al. (1997), Madden et al. (1987), Mora-Aguilera et al. (1992) and Nemecek (1993), that migrating aphids, regardless of the species, play a major role in the spread of non-persistently transmitted viruses.</p><p>The simulation model used in this study only accounted for secondary spread as introductions from external virus sources rarely occur in the Netherlands. The absence of any spread from outside sources allowed inoculating the field at different dates. This simulation model could simulate the final number of plants showing symptoms. A rough approximation, using the averaged obtained value for <em>r</em> and aphid catches showed that the number of infected plants to occur could be predicted two weeks in advance. The use of this model as a predictive tool for the whole crop cycle is premature because it does not model the development of the aphid population. Although <em>r</em> was conserved between the inoculation dates in each experiment, it varied between experiments. The species composition of the aphid population varies each year. Although the total number of aphids caught could be related to virus spread, the rate by which the virus will be spread will differ among years and among locations. In more elaborate models, <em>r</em> must be decomposed into different components representing the behavior of the aphid population such as the acquisition and inoculation rates, the infectious period of the virus in the vector, the vector turn over, the feeding time per vector per day, and the distance hopped by aphids (Jeger et al., 1998).</p><p>The simulation models used by Nemecek (1993) and Sigvald (1992), to predict <em>Potato virus Y</em> spread in potatoes, included some behavioral characteristics and a more detailed description of the aphid species composition. These models could be used to simulate the final disease incidence in crops, which were initially infected with different numbers of virus sources. The studies in <em>Soybean mosaic virus</em> presented by Ruesink and Irwin (1986) also included some behavioral aspects of the vector and could be used to predict yield and level of seed transmission. The complementary information added by the present study was an experimentally demonstration that spread of BtMV is related to the major migrating aphid flight. The calibration studies using a simulation model confirmed that this spread could be described by one absolute rate parameter. It can be concluded that management strategies to control virus spread have to be focused on a delay of virus introductions in the field, or alternatively, to restrain aphid dispersal early in the season.</p><p>The deterministic model developed in Chapter 4 was adapted to include a factor that describes the effect of plant density in the rate equation. This factor could be included on the assumption that plant density would affect the spread by affecting the number of aphids per plant, and the number of available plants, while the other parameters related to spread would remain constant. The spread was indeed inversely proportional to the plant density in the first weeks after the virus started to spread. However, analyzing the incidence for the whole growing season, the model failed to explain the observed spread. Values of <em>r</em> estimated by calibration, to experimental field data, showed that the rate of spread in low-density plots was lower than the rate expected by the hypothesis that spread is proportional to the number of aphids per plant. The factors that lead to the strong aggregation of the infected plants around the primarily infected plant might have affected the rate of spread in these low-density plots.</p><p>The contrast between bare soil and plants will be larger in low-density plots than in plots with standard density. By the middle of July, when most of the aphid migration occurred in both years, the canopy was closed in the standard density plots while bare soil was still visible in the low-density plots. An attraction exerted on the aphids by the contrast between plants and bare soil might have affected the mobility of the aphids within the plot, reducing the distance hopped between plants and, consequently, the spread of the disease as the infected plants might be re-inoculated frequently. A factor considering this distance and/or the spatial pattern of the spread must be included to improve the model. Improvements of this model must, therefore, concentrate on the inclusion of a set of equations representing the vector behavioral components and the spatial pattern of spread.</p><p><strong>BtMV and damage in sugar beet:</strong></p><p>Experiments to determine damage due to virus infections are laborious. It is assumed that yield will depend on date of inoculation, initial inoculum levels, rate at which the virus spreads, disease incidence at the moment of harvest, and others. Since many factors will affect the yield, it will be difficult to estimate the crop losses caused by a pathogen. The use of a crop growth model can overcome these difficulties, assuming that the parameters related to damage can be determined and incorporated in the model. Information on damage caused by BtMV is rare in the literature, but it is generally accepted that this disease has little impact on yield of sugar beet (Watson and Watson, 1953).</p><p>The effect of BtMV infections on the yield of the sugar beet crop was evaluated by simulation using a crop growth model (SUCROS). This analysis was experimentally grounded by determination of the light response curve, light absorption and transmission, and other parameters on healthy and BtMV infected leaves showing mosaic symptoms. The model dynamically simulates the carbon budget and growth of the crop by integrating leaf photosynthesis over time and leaf area, taking into account incident light, leaf area index, proportion of mosaic-affected leaf area, and optical characteristics of the leaves and the canopy. The damage simulated for early-infected crops was estimated to be, under the most extreme situation, approximately 20%. However, as the infection usually starts to spread in the second half of the growing season, the estimated damage in a fully infected crop after July was less than 3%. This value can be neglected considering the damage due to other diseases, harvesting and processing of the roots. Injury component analyses indicated that the direct effect due to both reduction in maximum rate of photosynthesis ( <em>P</em><sub>m</sub> ) and increase in dark respiration ( <em>R</em><sub>d</sub> ) were the major causes of the simulated damage (Chapter 6).</p><p>The simulation studies demonstrated that the usually observed negligible damaging effect of BtMV is due to the late occurrence of the spread of the disease under field conditions (Chapters 3 and 4). When infection takes place, the crop has already a large enough area of healthy leaves to sustain the yield, even if all plants in the field were infected after the middle of the growing season (Chapter 6). This study is probably the first which simulates crop damage caused by a potyvirus, and it is certainly the first simulation study of the damage caused by BtMV in sugar beet.</p><p><strong>Concluding remarks:</strong></p><p>As a model is a simplification of reality, perfection is not expected (Ruesink and Irvin, 1986). Several improvements can be made to the simulation model presented in this study to describe the disease incidence. The present version allowed to test the raised hypothesis that spread was a function of the migrating aphid population, for every date at which the inoculum source was introduced. The results of the analysis of the rate of spread of the field experiments, together with the modeling studies, could indicate the model has to be improved by including an aphid population sub-model that describes vector behavior. It suggested also that the spatial characteristics of spread must be taken in account.</p>
|A model for analyzing plant-virus transmission characteristics and epidemic development.
Jeger, M.J. ; Bosch, F. van den; Madden, L.V. ; Holt, J. - \ 1998
IMA Journal of Mathematics Applied in Medicine and Biology 15 (1998). - ISSN 0265-0746 - p. 1 - 18.
Spores splashing under different environmental conditions: a modeling approach.
Pielaat, A. ; Madden, L.V. ; Gort, G. - \ 1998
Phytopathology 88 (1998). - ISSN 0031-949X - p. 1131 - 1140.
|Analysis of the dynamics of virus transmission by vectors.
Jeger, M.J. ; Bosch, F. van den; Holt, J. ; Madden, L.V. - \ 1996
In: Proc. 20th Int. Congr. of Entomology, Firenze, Italy - p. 456 - 456.
|Use of categorical information and correspondence analysis in plant disease epidmiology.
Savary, S. ; Madden, L.V. ; Zadoks, J.C. - \ 1995
Advances in Botanical Research 21 (1995). - ISSN 0065-2296 - p. 213 - 240.