Whitefly and whitefly-borne viruses in the tropics : Building a ... - cgiar

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Colombia and Ecuador B biotype B. tabaci A and B biotypes B. tabaci and T. vaporariorum B biotype B. tabaci and T. vaporariorum T. vaporariorum A and B biotypes B. tabaci Pacific Ocean Ecuador Caribbean Sea Colombia Figure 1. Survey area and distribution of whitefly species (Bemisia tabaci and Trialeurodes vaporariorum) in Colombia and Ecuador. Uncoloured areas were not sampled. whitefly incidence. Nine areas were chosen to represent the lowlands along the Pacific coast of Ecuador and the Atlantic coast of Colombia where cotton (Gossypium hirsutum L.), soybean (Glycine max [L.] Merr.) and tomato (Lycopersicon esculentum Mill.) are grown on large farms that occupy a significant proportion of the agricultural land. Eleven areas were chosen to represent the highlands of northern Ecuador and the main N agricultural areas along the three mountain ranges in Colombia. Highland areas in both countries are occupied by small-scale farmers who grow common and snap bean (Phaseolus vulgaris L.), tomato, potato (Solanum tuberosum L.) and other horticultural crops for consumption and sale. Between 10 and 20 data sets were collected and processed in each survey area. A complete data set consisted of a producer questionnaire 275
and biological samples of whiteflies and natural enemies from one of that producer’s fields. Three hundred and twenty-five data sets were processed, based on visits and interviews with 274 farmers and 168 extension agents, private technical assistants, insecticide salesmen and government officers in charge of rural development projects. Insecticide resistance was also assessed in whiteflies from 40 sites, as detailed in Chapter 4.3 (this volume). Whiteflies and natural enemies were identified at CIAT and whitefly biotypes determined using esterase banding patterns in polyacrylamide gel electrophoresis (PAGE) and random amplified polymorphic DNA/ polymerase chain reaction (RAPD-PCR) analysis (Quintero et al., 1998). Biological samples for whitefly species and biotype identification were taken at 215 sites; 74 samples for identification of natural enemies were collected. Whitefly populations were sampled in 14 crops. In the tropical highlands, emphasis was placed on common bean (73% of samples taken), tomato (18%) and potato (7%). In mid-altitude valleys, most samples were taken on tomato (58%) and common bean (18%). Cucurbits (38%), tomato (31%), pepper (Capsicum annuum L.) (10%) and eggplant (Solanum melongena L.) (5%) were the crops most intensively surveyed in the tropical lowlands. Yield losses due to the greenhouse whitefly on snap beans were measured. Species 276 Increased Biological Understanding An analysis of whitefly species composition along an altitudinal gradient suggests that T. vaporariorum and B. tabaci occupy well-defined Whiteflies and Whitefly-borne Viruses in the Tropics niches and habitats (Figure 2). In the tropical lowlands, 91.5% of samples collected were identified as B. tabaci, whereas 100% of the whiteflies collected in the tropical highlands were T. vaporariorum. The species co-exist in all mid-altitude valleys where samples were taken, with T. vaporariorum predominating. Thus, in Colombia and Ecuador, T. vaporariorum occurs between 780 and 2830 m above sea level and is the only species present above 1600 m, whereas B. tabaci is the only species present at lower elevations (500 m or less) (Quintero et al., 2001). This distribution of the two major whitefly species may be related to climatic conditions, especially temperature regimes, which are determined in the tropics principally by elevation. As much of the agricultural production in the Andes is concentrated in mid-altitude valleys, our findings clearly show the need for a correct identification of the whitefly species concerned. If it is assumed, for example, that B. tabaci is the major pest in mid-altitude valleys and highlands, IPM packages will be ill targeted. Our findings also dispel the notion, prevalent among technical Whitefly species (%) 100 80 60 40 20 0 8.5 91.5 0 Tropical lowlands (1000 masl) Trialeurodes vaporariorum Figure 2. Composition of whitefly populations in three major ecological zones, as defined by altitude (masl = metres above sea level), in Colombia and Ecuador.
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About the Partners CIAT The Interna
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Centro Internacional de Agricultura
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Chapter 4 Whiteflies and Whitefly-b
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Chapter 6 Whiteflies and Whitefly-b
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Contents Page Foreword vii Introduc
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Contents Chapter SECTION THREE Whit
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Foreword This book is the product o
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Introduction Introduction The Probl
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Introduction In addition to the yie
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Introduction in pesticide use in La
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Introduction annual crops, especial
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Introduction Plant Resistance contr
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Introduction Otim-Nape, G. W.; Bua,
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SECTION ONE Whiteflies as Vectors o
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Introduction CHAPTER 1.1 Introducti
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Introduction diseases than is cassa
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Introduction Sub-project on Whitefl
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Introduction References Aritua, V.;
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Introduction Thresh, J. M.; Otim-Na
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Ghana 1997, on 80 farms. These incl
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Ghana (6.2%), Bakentenma (5%) and K
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Ghana Legg, J. P.; James, B. D. 199
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Benin Northern guinea savannah Sout
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Benin or disease problem, the main
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Nigeria CHAPTER 1.4 Nigeria Introdu
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Nigeria TMS 30572 (18.8%) and TMS 3
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Nigeria FAO (Food and Agriculture O
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Cameroon protocol, to enable valid
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Cameroon Farmers undertook various
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Cameroon Robertson, I. A. D. 1987.
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Uganda between November 1997 and Ja
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Uganda environment, host plant heal
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Uganda local varieties. Assessments
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Uganda Harrison, B. D. 1987. Proper
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Kenya Recent epidemiological studie
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Kenya respective diseases were reco
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Kenya Bock, K. R. 1983. Epidemiolog
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Tanzania CHAPTER 1.8 Tanzania Intro
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Tanzania Adult whiteflies were more
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Tanzania loss) to assess yield loss
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Tanzania Legg, J. P.; Raya, M. 1998
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Malawi Increased Biological Underst
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Malawi Physiology and Ecology in th
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Madagascar Tanzania Madagascar Moza
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Madagascar surprising, particularly
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Diversity of African Cassava Mosaic
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Sweetpotato Virus Disease in East A
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Factors Associated with Damage CHAP
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Factors Associated with Damage Mean
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Factors Associated with Damage % SP
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Factors Associated with Damage thro
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Factors Associated with Damage Gedd
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Conclusions and Recommendations col
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Conclusions and Recommendations Mal
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Conclusions and Recommendations Mpi
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Conclusions and Recommendations com
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Conclusions and Recommendations con
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Conclusions and Recommendations (2)
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Conclusions and Recommendations Ger
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SECTION TWO Whiteflies as Pests and
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Introduction Czosnek, H.; Navot, N.
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Sudan cotton, leading to the introd
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Sudan Table 1. Reproductive host pl
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Sudan Historically, Sudan has been
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Sudan Only 10% of producers reporte
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Sudan Conclusions The work conducte
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Kenya CHAPTER 2.3 Kenya Introductio
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Kenya Increased Biological Understa
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Kenya Samples of 10 plants per fiel
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Kenya Table 4. Maximum incidence (%
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Kenya Seventy-nine percent of tomat
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Kenya under Phase 2 of the TWF-IPM
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Tanzania CHAPTER 2.4 Tanzania Intro
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Tanzania The reproductive host plan
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Tanzania Geographical range of whit
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Tanzania Local names given to white
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Tanzania Nono-Womdim, R.; Swai, I.
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Malawi levels of infestation by the
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Malawi Table 3. Maximum incidence (
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Malawi (40%) believe that the white
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Tomato Yellow Leaf Curl Virus in E.
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Conclusions and Recommendations CHA
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Conclusions and Recommendations (Fi
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Conclusions and Recommendations Cen
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Conclusions and Recommendations the
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SECTION THREE Whiteflies as Vectors
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Introduction especially for export.
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Mexico CHAPTER 3.2 Mexico Introduct
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Mexico Culiacán, Sinaloa, in north
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Mexico Table 2. Virus survey of tom
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Mexico results of the molecular bio
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Mexico Strengthened Research Capaci
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Mexico López, R. 1996. Experiencia
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Guatemala 1960s, and at this time t
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Guatemala Table 2. Results of white
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Guatemala Table 5. Cropping systems
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Guatemala contemplated in this prel
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El Salvador CHAPTER 3.4 El Salvador
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El Salvador During the course of th
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El Salvador markets: common bean, m
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El Salvador Current Status of White
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Honduras Copan Ocotepeque Santa Bá
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Honduras Table 3. Biotyping of whit
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Honduras References Caballero, R. 1
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Nicaragua Nueva Segovia Madriz Este
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Nicaragua Lowlands of Nicaragua. Th
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Nicaragua Region VI is a main horti
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Costa Rica CHAPTER 3.7 Costa Rica I
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Costa Rica Table 1. Characterizatio
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Costa Rica Castillo, J. 1997. Movim
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Panama Bocas del Toro Chiriquí Ver
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Page 242 and 243: Haiti Grande-Anse Sud Grande-Anse S
Page 244 and 245: Haiti collaborators in this project
Page 246 and 247: Cuba Ciudad de la Habana Pinar del
Page 248 and 249: Cuba Table 3. Comparative homologie
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Page 252 and 253: Dominican Republic CHAPTER 3.11 Dom
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Page 256 and 257: Dominican Republic Strengthened Res
Page 258 and 259: Reproductive Crop Hosts of Bemisia
Page 266 and 267: Biotypes of Bemisia tabaci CHAPTER
Page 268 and 269: Biotypes of Bemisia tabaci For this
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Page 272 and 273: Biotypes of Bemisia tabaci biotype
Page 274 and 275: Biotypes of Bemisia tabaci Table 2.
Page 276 and 277: Biotypes of Bemisia tabaci Already
Page 278 and 279: Conclusions and Recommendations CHA
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Page 282 and 283: SECTION FOUR Whiteflies as Pests of
Page 284 and 285: Introduction CHAPTER 4.1 Introducti
Page 286 and 287: Introduction control, due to resist
Page 288 and 289: Introduction Posada, L. 1976. Lista
Page 292 and 293: Colombia and Ecuador assistants and
Page 294 and 295: Colombia and Ecuador and squash. On
Page 296 and 297: Colombia and Ecuador Table 2. Main
Page 298 and 299: Colombia and Ecuador Table 6. Patte
Page 300 and 301: Insecticide Resistance in Colombia
Page 310 and 311: Conclusions and Recommendations CHA
Page 312 and 313: Conclusions and Recommendations res
Page 314 and 315: Conclusions and Recommendations rot
Page 316 and 317: SECTION FIVE Special Topics on Pest
Page 318 and 319: Sustainable IPM through Host Plant
Page 328 and 329: Biological Control of Whiteflies by
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Progress of Cassava Mosaic Disease
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Management of the Cassava Mosaic Di
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Conclusions Conclusions The Tropica
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Conclusions whitefly pests and thus
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Conclusions developing countries, a
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Acronyms and Abbreviations Acronyms
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Acronyms and Abbreviations FIRA Fid
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Acronyms and Abbreviations PROFRIJO
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Acronyms and Abbreviations PYR pyre
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