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

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Factors Associated with Damage % SPVD % SPVD 40 35 30 25 20 15 10 5 0 40 35 30 25 20 15 10 5 0 Experiment 1 (November 1997-April 1998) Experiment 2 (October 1998-March 1999) 1 2 3 4 5 6 Nam-A Nam-B Nam-C Kan-D Kan-E Kan-F practices also were examined by farm surveys and farmer interviews in 1998- 99 (for methods, see Gibson et al., 2000), focusing particularly on localities where SPVD was unusually prevalent, notably Bukoba and Karagwe sub-districts of Kagera District in Tanzania, and Rukungiri and Mpigi Districts in Uganda (Table 2). Months after planing Figure 3. Progress of sweet potato virus disease (SPVD) in initially disease-free sweetpotato planted during the second rains of 1997 (Experiment 1) and the second rains of 1998 (Experiment 2) at farms at Namulonge (Nam-A, Nam-B, Nam-C) and Kanoni (Kan-D, Kan-E, Kan-F). Most farmers, particularly those in Tanzania not exposed as yet to the bitter lessons of the cassava mosaic epidemic (which began in Uganda), did not realize that SPVD involved a virus spread by whiteflies, many considering it to be caused by too much sun. Even so, most farmers attempted to control SPVD, predominantly through the use 93
of plant health management tactics (Table 2). In particular, most farmers carefully selected their planting material from unaffected parent plants. A few also removed (rogued) diseased plants from young crops. However, farmers often planted new crops close to old diseased crops, even though incidence of SPVD and the distance between crops were significantly (P < 0.05) and negatively correlated. Farmers also appeared to make no attempt to remove diseased plants from old and abandoned crops even when they were close to newly planted fields. This is consistent with farmers lacking knowledge that SPVD is caused by an insect-transmitted virus. Although most farmers knew of SPVD-resistant varieties, few ranked resistance as a valuable management practice (Table 2), apparently because most resistant varieties had a poor and/or late yield. Despite this, they ranked new varieties with superior yield characteristics and resistance as their top requirement. 94 Whiteflies and Whitefly-borne Viruses in the Tropics Table 2. Importance to farmers of different measures that they already are using to manage sweetpotato virus disease (SPVD) (adapted from Gibson et al., 2000). Locality Percentage of farmers a giving the rank indicated to a control measure No. of farmers Symptomless Roguing Resistant Controlling Interviewed planting material cultivars SPVD b 1st 2nd 3rd 1st 2nd 3rd 1st 2nd 3rd Tanzania c Bukoba 100 0 0 0 33 0 0 0 0 15 (75) 20 Karagwe Uganda 80 0 0 20 10 0 0 0 0 10 (36) 28 Rukungiri 82 14 0 11 50 7 7 14 18 44 (88) 50 Mpigi 88 10 0 2 10 27 10 54 7 41 (82) 50 Soroti 100 0 0 0 17 17 0 17 0 6 (12) 50 Overall 87 9 0 7 28 13 6 25 9 116 (60) 198 a. Among those claiming to use specific measures to control SPVD. b. Number of farmers (in parentheses, percentage of farmers among those interviews) claiming to use specific control measures for SPVD. c. Farmers in other districts in Tanzania were not questioned on this subject. Conclusions Our results confirm that SPVD varies considerably in incidence among sites and that part of the variation in incidence is associated with differences in the numbers of B. tabaci infesting the crop. Thus, the explanation for the rarity of SPVD in Soroti and Busia seems to be that whiteflies are rare throughout much of the year (Figure 1) but this still leaves unanswered the question of why fewer whiteflies should be present in Soroti and Busia than in Mpigi District. Our investigation was too limited to identify positively the reason(s) for this. However, a major difference between Soroti and Busia Districts and Mpigi District is that the first rains in Soroti and Busia Districts occur later and the second rains earlier than in Mpigi District. This leads to a more prolonged dry season between the second and the first rains in Soroti and Busia, during which time most vegetation dries out, natural bushfires are common and the resulting natural vegetation predominantly consists of low-growing bushes and grasslands. Rainfall being more evenly spread
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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
Page 58 and 59: Cameroon Farmers undertook various
Page 60 and 61: Cameroon Robertson, I. A. D. 1987.
Page 62 and 63: Uganda between November 1997 and Ja
Page 64 and 65: Uganda environment, host plant heal
Page 66 and 67: Uganda local varieties. Assessments
Page 68 and 69: Uganda Harrison, B. D. 1987. Proper
Page 70 and 71: Kenya Recent epidemiological studie
Page 72 and 73: Kenya respective diseases were reco
Page 74 and 75: Kenya Bock, K. R. 1983. Epidemiolog
Page 76 and 77: Tanzania CHAPTER 1.8 Tanzania Intro
Page 78 and 79: Tanzania Adult whiteflies were more
Page 80 and 81: Tanzania loss) to assess yield loss
Page 82 and 83: Tanzania Legg, J. P.; Raya, M. 1998
Page 84 and 85: Malawi Increased Biological Underst
Page 86 and 87: Malawi Physiology and Ecology in th
Page 88 and 89: Madagascar Tanzania Madagascar Moza
Page 90 and 91: Madagascar surprising, particularly
Page 92 and 93: Diversity of African Cassava Mosaic
Page 98 and 99: Sweetpotato Virus Disease in East A
Page 104 and 105: Factors Associated with Damage CHAP
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Page 112 and 113: Factors Associated with Damage Gedd
Page 114 and 115: Conclusions and Recommendations col
Page 116 and 117: Conclusions and Recommendations Mal
Page 118 and 119: Conclusions and Recommendations Mpi
Page 120 and 121: Conclusions and Recommendations com
Page 122 and 123: Conclusions and Recommendations con
Page 124 and 125: Conclusions and Recommendations (2)
Page 126 and 127: Conclusions and Recommendations Ger
Page 128 and 129: SECTION TWO Whiteflies as Pests and
Page 130 and 131: Introduction CHAPTER 2.1 Introducti
Page 132 and 133: Introduction Czosnek, H.; Navot, N.
Page 134 and 135: Sudan cotton, leading to the introd
Page 136 and 137: Sudan Table 1. Reproductive host pl
Page 138 and 139: Sudan Historically, Sudan has been
Page 140 and 141: Sudan Only 10% of producers reporte
Page 142 and 143: Sudan Conclusions The work conducte
Page 144 and 145: Kenya CHAPTER 2.3 Kenya Introductio
Page 146 and 147: Kenya Increased Biological Understa
Page 148 and 149: Kenya Samples of 10 plants per fiel
Page 150 and 151: Kenya Table 4. Maximum incidence (%
Page 152 and 153: Kenya Seventy-nine percent of tomat
Page 154 and 155: Kenya under Phase 2 of the TWF-IPM
Page 156 and 157: 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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Panama Gámez, R. 1970. Los virus d
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Haiti Grande-Anse Sud Grande-Anse S
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Haiti collaborators in this project
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Cuba Ciudad de la Habana Pinar del
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Cuba Table 3. Comparative homologie
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Cuba project provided three keynote
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Dominican Republic CHAPTER 3.11 Dom
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Dominican Republic monoclonal antib
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Dominican Republic Strengthened Res
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Reproductive Crop Hosts of Bemisia
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Biotypes of Bemisia tabaci CHAPTER
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Biotypes of Bemisia tabaci For this
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Biotypes of Bemisia tabaci 100 99 B
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Biotypes of Bemisia tabaci biotype
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Biotypes of Bemisia tabaci Table 2.
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Biotypes of Bemisia tabaci Already
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Conclusions and Recommendations gre
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SECTION FOUR Whiteflies as Pests of
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Introduction control, due to resist
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Introduction Posada, L. 1976. Lista
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Colombia and Ecuador B biotype B. t
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Colombia and Ecuador assistants and
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Colombia and Ecuador and squash. On
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Colombia and Ecuador Table 2. Main
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Colombia and Ecuador Table 6. Patte
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Insecticide Resistance in Colombia
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Conclusions and Recommendations res
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Conclusions and Recommendations rot
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SECTION FIVE Special Topics on Pest
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Sustainable IPM through Host Plant
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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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Whitefly and whitefly-borne viruses in the tropics : Building a ... - cgiar

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