University of Ghana http://ugspace.ug.edu.gh SUSCEPTIBILITY OF TWO SPOTTED SPIDER MITE Tetranychus urticae KOCH (ACARI; TETRANYCHIDAE) TO SOME SELECTED INSECTICIDE IN THE GREATER ACCRA REGION OF GHANA BY BALA RUTH BUBA B.AGRIC (HONS) CROP PROTECTION UNIVERSITY OF MAIDUGURI, BORNO STATE, NIGERIA THIS THESIS IS SUBMITTED TO THE UNIVERSITY OF GHANA, LEGON IN PARTIAL FULFILLMENT OF THE REQUIREMENT FOR THE AWARD OF MASTERS OF PHILOSOPHY DEGREE IN ENTOMOLOGY INSECT SCIENCE PROGRAMME UNIVERSITY OF GHANA, LEGON JULY 2015 JOINT INTERFACULTY PROGRAMME FOR THE TRAINING OF ENTOMOLOGIST IN WEST AFRICA. COLLABORATING DEPARTMENTS: ANIMAL BIOLOGY AND CONSERVATION SCIENCE (SCHOOL OF BIOLOGICAL SCIENCES) AND CROP SCIENCE (SCHOOL OF AGRICULTURE) ALL OF THE COLLEGE OF BASIC AND APPLIED SCIENCES University of Ghana http://ugspace.ug.edu.gh DECLARATION I hereby do declare that with the exception of references to other scholars work which have been duly acknowledge, this thesis consist of my original work and has neither in whole nor part been presented to any other institution for the award of any degree. ………………………………….. Bala Ruth Buba (Student) ……………………………………. Dr. Vincent Yao Eziah (Supervisor) …………………………………… Prof. Kwame Afreh-Nuamah (Supervisor) ……………………………........ Dr Rosina Kyerematen (Coordinator) i University of Ghana http://ugspace.ug.edu.gh DEDICATION I dedicate this research work to the memory of my late father Mr Bala Buba and to my mum, Mrs Barmini Bala Buba whose love, enthusiasm and inspirations have brought me this far. ii University of Ghana http://ugspace.ug.edu.gh ACKNOWLEDGEMENTS I am forever grateful to God whose unfailing love and protection has sustained me throughout this programme. I wish to express my gratitude to my supervisors, Dr. Vincent Yao Eziah of the Department of Crop Science and Prof. Kwame Afreh-Nuamah for their technical advice, guidance and constructive criticisms towards the successful completion of this work. My heartfelt gratitude again goes to Dr. Vincent Yao Eziah, for his immense support, especially for supplying me with the synergist for the assays. I wish to express my profound gratitude to the coordinator, Dr. Rosina Kyerematen and all the lecturers (Prof. Kwadwo Ofori, Prof. Ebenezer Owusu, Dr. Maxwell Billah, Dr. Dave Wilson, Dr. Millicent Cobblah, Rev. Dr. S. Gbewonyo, Dr. Timpong Jones, Dr. Wole Fatunbi) of the ARPPIS. They have contributed in shaping my future as an Entomologist. I acknowledge the help of the lab technician of the Department of Crop Science Mr Kurt Martey and the gardener of the Sinna’s garden Mr K. Addo who helped with the cultivation of insecticide-free eggplant in the screen house. I also express my deepest gratitude to Mr. Zakariya Dauda for the encouragement and assistance, especially when I was in search of admission. I sincerely appreciate the prayers and invaluable support of my siblings Mrs. Sarah, Mrs George Shitta, James and Grace. I notably thank and appreciate the co-operation of my colleagues, particularly Lami, Frank, Peter, Comfort, Michelin, Nnenna, Dickson, Shaphan, Dorcas and Sigismund. God bless you all. iii University of Ghana http://ugspace.ug.edu.gh Finally, I am most grateful to DAAD for the sponsorship of this programme and for selecting me among others to pursue this study in the field of Entomology. iv University of Ghana http://ugspace.ug.edu.gh TABLE OF CONTENTS DECLARATION………………………………………………………………………………i DEDICATION………………………………………………………………………………...ii ACKNOWLEDGEMENT……………………………………………………………………iii TABLE OF CONTENTS……………………………………………………………………...v LIST OF FIGURES…………………………………………………………………………viii LIST OF TABLES……………………………………………………………………………ix LIST OF PLATES……………………………………………………………………………..x LIST OF APPENDICES……………………………………………………………………...xi LIST OF ABBREVIATIONS………………………………………………………………..xii ABSTRACT…………………………………………………………………………………xiii CHAPTER ONE.......................................................................................................................1 1.0 INTRODUCTION…………………………………………………………………………1 1.1 Justification………………………………………………………………………………..3 1.2 Objectives………………………………………………………………………………….4 CHAPTER TWO……………………………………………………………………………..5 2.0 LITERATURE REVIEW………………………………………………………………….5 2.1Origin and distribution of two-spotted spider mite………………………………………...5 2.2 Description and Biology of two-spotted spider mite………………………………………5 2.3 Economic importance of two-spotted spider mite…………………………………………8 2.4 Effect of weather on two-spotted spider mite……………………………………………10 2.5 Management of two-spotted spider mite…………………………………………………10 2.5.1 Integrated pest management (IPM)…………………………………………………….10 2.5.1.1Cultural and physical control…………………………………………………………11 2.5.1.2 Host-plant Resistance………………………………………………………………...11 5 University of Ghana http://ugspace.ug.edu.gh 2.5.1.3 Biological control…………………………………………………………………….12 2.5.1.4 Botanical pesticides…………………………………………………………………..13 2.5.1.5 Entomopathogenic fungi……………………………………………………..............14 2.5.2 Chemical control……………………………………………………………………….15 2.5.2.1 Pesticide usage pattern……………………………………………………………….15 2.5.2.2 Effects of chemical control…………………………………………………………...17 2.5.2.2.1 Human health………………………………………………………………………17 2.5.2.2.2 Agricultural systems………………………………………………………………..17 2.6 Resistance Development…………………………………………………………………18 2.6.1 Mechanisms of insecticide resistance…………………………………………………..19 2.6.1.1 Metabolic Detoxification……………………………………………………………..20 2.6.1.2 Target site insensitivity………………………………………………………………22 2.6.1.3 Behavioural resistance………………………………………………………………..23 2.6.2 Forms of resistance……………………………………………………………………..23 2.6.2.1 Cross resistance………………………………………………………………………23 2.6.2.2 Multiple resistance…………………………………………………………………...24 2.6.3 Resistance in two-spotted spider mite………………………………………………….24 2.7 The role of synergists…………………………………………………………………….25 2.8 Resistance management………………………………………………………………….26 CHAPTER THREE………………………………………………………………………...28 3.0 MATERIALS AND METHODS………………………………………………………...28 3.1 Study Area………………………………………………………………………………..28 3.2 Survey…………………………………………………………………………………….28 3.3 Miticides………………………………………………………………………………….29 3.4 Field sampling of spider mites…………………………………………………………...29 3.5Cultivation of miticide-free Eggplant…………………………………………………….30 3.6 Determination of miticide concentrations………………………………………………..30 3.7 Bioassay………………………………………………………………………………….31 6 University of Ghana http://ugspace.ug.edu.gh 3.8 Determination of optimal (non-lethal) Piperonyl butoxide (PBO) and Diethyl Maleate (DEM) concentration…………………………………………………………………………32 3.9 Time series experiment with synergist…………………………………………………...33 3.10 Determination of the effect of PBO and DEM on Karate resistant populations……….33 3.11 Data analysis……………………………………………………………………………34 CHAPTER FOUR.................................................................................................................35 4.0 RESULTS………………………………………………………………………………..35 4.1.1 Agronomic practices……………………………………………………………………35 4.1.2 Pests and pest control practices………………………………………………………...35 4.1.3 Pesticide usage pattern…………………………………………………………………37 4.1.4 Source of information…………………………………………………………………..38 4.1.5 Mode of insecticide application………………………………………………………..39 4.1.6 Insecticide application dosage……………………………………………………….....40 4.1.7 Timing of insecticide application………………………………………………………40 4.1.8 Frequency of insecticide application…………………………………………………...41 4.1.9 Reason for insecticide change by farmers……………………………………………...42 4.1.10 Method of disposal of empty insecticide containers………………………………….43 4.2 Susceptibility of two-spotted spider mite to miticides…………………………………...44 4.3 Determination of the effect of PBO and DEM on Karate resistant populations…………48 CHAPTER FIVE……………………………………………………………………………49 5.0 DISCUSSION……………………………………………………………………………49 CHAPTER SIX.......................................................................................................................57 CONCLUSION AND RECOMMENDATIONS……………………………………………57 REFERENCES……………………………………………………………………………...58 APPENDICES........................................................................................................................80 7 University of Ghana http://ugspace.ug.edu.gh LIST OF FIGURES Fig. 1: Years spent in crop cultivation by farmers…………………………………………...36 Fig. 2: Farmers perception of crops most affected by spider mites………………………….36 Fig.3: Insect pests of crops as reported by farmers…………………………………………..37 Fig.4: Commonly used insecticides and those perceived as effective by farmers…………...38 Fig.5: Source of farmers’ knowledge about insect pest control……………………………...39 Fig. 6: Insecticide dosage application rate by farmers……………………………………….40 Fig.7: Timing of insecticide application by farmers…………………………………………41 Fig.8: Frequency of insecticide application by farmers……………………………………...42 Fig.9: Reasons for insecticide change by farmers……………………………………………43 Fig.10: Methods of insecticide package disposal by farmers………………………………...43 8 University of Ghana http://ugspace.ug.edu.gh LIST OF TABLES Table 1: Response of four Tetranychus urticae populations to five miticide by spray application……………………………………………………………………………………45 Table 2: Optimal concentration of PBO and DEM on Karate resistant population…………46 Table 3: Time-series experiments using karate resistant population………………………...47 Table 4: Response of two Karate resistant populations pre-treated with Synergist………….48 9 University of Ghana http://ugspace.ug.edu.gh LIST OF PLATES Plate 1: Adult two spotted spider mite………………………………………………………6 Plate 2: Life cycle of two spotted spider mite………………………………………………..7 Plate 3: Cluster of spider mites hanging before dispersal from the tip of an eggplant……….9 Plate 4: Sample collection site at Ashaiman…………………………………………………30 Plate 5: Experimental set up………………………………………………………………….32 10 University of Ghana http://ugspace.ug.edu.gh LIST OF APPENDICES Appendix 1.0: EPA Probit Analysis Program used for calculating LC/EC values version 1.5 Appendix 1.1: Susceptibility of T.urticae to Protect Appendix 1.2: Susceptibility of T.urticae to Imidacloprid Appendix 1.3: Susceptibility of T.urticae to Karate Appendix 1.4: Susceptibility of T.urticae to Levo Appendix 1.5: Susceptibility of T.urticae to Sulphur 11 University of Ghana http://ugspace.ug.edu.gh LIST OF ABBREVIATIONS AChE Acetylcholine esterase EC Emulsifiable concentrates GABA γ - Aminobutyric acid GST Glutathione S-transferase IPM Integrated Pest Management IRAC Insecticide Resistance Action Committee LC50 Median lethal concentration of a pesticide expected to kill 50% of a test organism LD50 Median lethal dose of a pesticide expected to kill 50% of a test organism 12 University of Ghana http://ugspace.ug.edu.gh ABSTRACT The two-spotted spider mite Tetranychus urticae is a pest of several plants including vegetables, fruits, ornamentals and field crops. Damage done to the host plant can cause leaf and fruit loss, complete defoliation and death of the host plant. They are mostly managed by the use of acaricides. Acaricides resistance has been reported in several countries, this is due to the fact that T. urticae fully becomes resistant to an insecticide after two to four years of use. The present study was initiated to monitor resistance by T. urticae to some selected insecticide in Accra. A survey carried out in the Accra suburbs revealed pattern and type of insecticide use for the control of pest, diseases and weeds. The survey also revealed that farmers have little knowledge about T. urticae and so do not specifically targets T. urticae in terms of control but that the insecticide used address the complex of pest affecting their crops. These insecticides are used in high dosages and at short intervals, this serves as a main cause of resistance development in mite pest. Susceptibility studies were carried out using five miticides- lambda cyhalothrin, Emamectin benzoate, prosular oxymatrine, imidacloprid and sulphur. Adult T. urticae were collected from four sites in Accra (Opeibea, Ashaiman, University of Ghana farm and Department of Crop Science Sinna’s garden). These populations were used to raise colonies of spider mite in the screen house of the Department of Crop Science. Spray application was used to determine the resistance in T. urticae by application of different rates of acaricides against the different strains of the spider mite. Mortality was recorded 24 h after treatment. The LD50 values and slopes were estimated by probit analysis and resistance factor were calculated by dividing LD50 of field population by LD50 of susceptible strain. All field populations were quite resistant to Karate (up to 21.6- fold), the LD50 values for the susceptible strain was 0.007 ml/L and varied significantly from those of the field population which ranged from 0.084-0.151 ml/L. All field populations were 13 University of Ghana http://ugspace.ug.edu.gh susceptible to Levo®, Protect® and Sulphur®. The University of Ghana farms, Sinna’s garden and Ashaiman populations were susceptible to Imidacloprid except the Opeibea population which showed a low level of resistance (9-fold) to Imidacloprid. Optimal (non- lethal) concentration of the synergists (PBO and DEM) were also determined using the karate resistant population and a time series experiment was carried out to determine the time lapse between synergist and insecticide application. The optimal (non-lethal) PBO and DEM concentrations were 0.4 and 1.0 µl/ml respectively. Time series experiment showed significant difference between mortalities in mites exposed to karate immediately after pre- treatment with synergists and those with the miticide 1 h later. 1 h after pre-treatment with PBO gave a 94.8 and 94.7 % mortality in Opeibea and Ashaiman resistant population respectively. The 1 h pre-treatment with DEM also gave 88.2 and 85.05 % mortalities in Opeibea and Ashaiman resistant populations respectively. The synergist ratios obtained for Opeibea population was 4.3 and 2.9-fold for PBO and DEM where as that of Ashaiman is 2.2 and 2.6 for PBO and DEM respectively. The result of the synergist experiment suggests the involvement of glutathione-S-tranferases (GSTs) and cytochrome P450 monoxygenases as the possible mechanisms of resistance. 14 University of Ghana http://ugspace.ug.edu.gh CHAPTER ONE 1.0 GENERAL INTRODUCTION Mites are the most diverse representatives of the phylum Arthropoda. They belong to the subphylum Chelicerata and subclass Acari. Among the arachnids, Acari are the only group that feeds on plants. Around 7,000 species of Phytophagous mites are known worldwide which occur in five families namely Tetranychidae, Tenuipalpidae, Eriophyidae, Tarsonemidae and Tuckerillidae (Chillar et al., 2007). In agriculture, the two main mite families of concern are the Tetranychidae and the Eriophyidae (Hoy, 2011). Tetranychidae, also known as spider mites, is a large family including about 1,200 species belonging to over 70 genera of worldwide distribution (Bolland et al., 1998). Of the more than 1,200 species of spider mites described the two-spotted spider mites Tetranychus urticae (Bolland et al., 1998; Milegeon et al., 2010) is the most injurious to Agriculture. The two–spotted spider mite Tetranychus urticae Koch (Acari: Tetranychidae), is the most economically important plant-feeding mite pest in the world (Van Leeuwen et al., 2012). It is a cosmopolitan and highly polyphagous pest of many fruits, vegetables, ornamentals, and field crops. Tetranychus urticae is a generalist feeder and is among the most polyphagous arthropod herbivores (Agrawal, 2000), feeding on more than 1,100 plant species belonging to more than 140 different plant families, including those that are known to produce toxic compounds (Grbic 2011; Van Leeuwen et al., 2012). Tetranychus urticae threatens greenhouse production and field, vine, and orchard crops, destroying economically important annual and perennial crops worldwide such as tomatoes, peppers, cucumbers, strawberries, 15 University of Ghana http://ugspace.ug.edu.gh corn, apples, grapes, eggplant, almonds, peppermint, pawpaw and citrus (Jeppson et al., 1975). Spider mites damage their host plants while feeding, using specialized piercing- sucking, stylet-like mouthparts to penetrate through the outer epidermal cells and into parenchyma cells (Park and Lee, 2002), and thus removing chlorophyll and other cell contents (Tomczyk and Kropczyńska, 1985). The loss of chlorophyll results in a visibly patchy discoloration of leaf tissue, as well as a reduced photosynthetic rate and production of nutrients (Park and Lee 2002). Economic injury occurs as high populations accumulate and feeding increases, leading to sufficient damage over a period of days. Extreme levels of damage can eventually cause leaf and fruit loss, complete defoliation, and death of the host plant (Van Leeuwen et al., 2012). Acaricide resistance in T. urticae has been reported from over 60 countries (DARP, 2013), easily earning it the title of the world’s top resistant animal pest (Van Leeuwan et al., 2010). Tolerance documented to acaricides can result after a few applications (Sato, 2005). Furthermore, T. urticae can become fully resistant to new acaricides within two to four years, meaning that control of multi-acaricide resistant T. urticae has become increasingly difficult (Grbic, 2011). The development of resistance in T. urticae has been reported for a number of compounds, including organophosphates, clofentezine, hexythiazox bifenthrin, fenpropathrin, bifenazate, fenpyroximate, pyridaben, tebufenpyrab, chlorfenapyr, etoxazole, spirodiclofen, abamectin, and milbemectin (Osakabe et al., 2009; Van Leeuwen et al., 2010). Tetranychus urticae has rapidly developed resistance to almost all types of acaricides due to its short life cycle, high biotic potential and parthenogenesis reproduction (Croft and Van De Baan, 1988). 16 University of Ghana http://ugspace.ug.edu.gh According to Insecticide Resistance Action Committee (IRAC), 424 cases of T. urticae resistance have been reported to 94 active ingredients of acaricides, emphasizing the urgent necessity of efficient resistance management (http://www.pesticideresistance.com/search.php, accessed 15 February 2015). 1.1 Justification Occurrences of pests and diseases have led to increased indiscriminate use of pesticide and other agrochemicals. Not surprisingly, pesticide use has increased over time in Ghana and is particularly elevated in the production of high-value cash crops and vegetables (Gerken et al. 2001). Dinham, (2003) estimated that 87% of Ghanaian farmers in rely heavily on the use of pesticides and these chemical pesticides are used improperly or in dangerous combinations (Obeng-Ofori et al., 2002). The problem is serious in areas where irrigated farming is practiced because of multiple cropping. The misuse of chemical pesticides is of so much concern that promotion of safe use of pesticides on vegetables has been placed on the agenda of Ghana’s Food and Agriculture Sector Development Policy (Ministry of Food and Agriculture 2002). Efforts to manage T. urticae populations in field crops rely on the use of acaricides. Although acaricides have proven to be highly effective in protecting crops under extreme pressure from pest (Cooper and Dobson, 2007), this over reliance on synthetic chemicals in crop cultivation has generally caused mite resistance development and public concerns on their high residues in crop, soils and water (Owusu and Yeboah, 2007) as well as adverse effects on non-targets beneficial organism, and therefore there is a need for monitoring of T. urticae population. No studies have been done on the susceptibility of Ghanaian populations of T. urticae, it is therefore necessary to conduct susceptibility test to know the resistance level of these pest to 17 University of Ghana http://ugspace.ug.edu.gh commonly used insecticides so that potential solutions can be developed before the onset of severe economic losses to growers. The detection of resistance in its early stages aids in better resistance management and in reducing resistance related cost to farmers. 1.2 Main objective The present study sought to investigate the susceptibility of T. urticae populations to commonly used insecticides in some parts of greater Accra region of Ghana. Specific objectives The specific objectives of this work were thus; i. To determine the pattern and types of commonly used insecticides in these areas ii. To assess the susceptibility of field populations of T. urticea to some selected insecticides iii. To determine the possible roles of detoxifying enzymes using synergism assays. 18 University of Ghana http://ugspace.ug.edu.gh CHAPTER TWO 2.0 LITERATURE REVIEW 2.1 Origin and distribution of the two-spotted spider mite The two-spotted spider mite Tetranychus urticae was described from European specimens and is considered to be a tropical species but it is also found in the subtropical regions (Fasulo and Denmark, 2000). Tetranychus urticae occurs in most parts of the world and has been recorded from most countries in Europe, Asia, Africa, Australia, the Pacific and Caribbean islands, North, Central and South America (Turtle and Baker, 1968; Bolland et al., 1998). 2.2 Description and Biology of the two-spotted spider mite The two-spotted spider mite is oval in shape, about 0.6 mm long (Tuttle and Baker, 1968). Colour varies from brown to orange-red and green (Metcalf and Metcalf, 1993). The female body is about 0.4 mm in length bearing 12 pairs of dorsal setae. The colour of the legs varies from pale to yellowish (Magdalena and Meyer, 1996). The large dark spots are accumulation of body wastes, often visible through the transparent body wall but lacking in newly moulted mites (Tuttle and Baker 1968). The male is elliptical with a slender caudal end, longer legs, more mobile and smaller than the female (Coates, 1974). The axis of knob of aedeagus is parallel or forming a small angle with axis of shaft (Boudreaux, 1956). Both male and female undergo the same number of developmental stages but in the males time spent on each stage is shorter. The colour of the exoskeleton may vary according to their diet and environment. In autumn due to short days and poor host quality the diapause females become orange to brick red and creep into protected places such as on 19 University of Ghana http://ugspace.ug.edu.gh the underside of leaves or on soil surfaces to hibernate, at this stage the mite becomes non- feeding and non-reproductive (Annecke and Moran, 1982; Davidson and Raupp, 1988). Plate 1: Adult two spotted spider mite The life cycle of T. urticae progresses through a series of five stages, egg, larva, protonymph, deutonymph, then finally moulting into an adult male or female (Crooker, 1985). Adult females can lay an average of 5 or 6 eggs daily and 100-150 in a lifetime, over a period of 3-4 weeks (Sabelis, 1985). Spider mite females of the genus Tetranychus lay their eggs within or under webbing. Webbing may be used to protect against climatic factors such as wind and rain, and also protects the mites from natural enemies and exposure to chemicals (Gerson, 1985). Eggs are deposited singly on the underside of leaves. The eggs are translucent pearl-like spheres when initially laid but gradually becomes reddish as they develop (Van Leeuwen, 2012). The developmental period of the eggs varies from 3 days at 24ºC to 21 days at 11ºC (Cagle, 1949) until hatching into an orange six-legged larva which 20 University of Ghana http://ugspace.ug.edu.gh turns green as they feed on chlorophyll. The larvae feed for a few days then search for protected areas to rest and moult into the protonymph. The larvae, along with the next two eight legged nymphal stages (protonymph and deutonymph) are all active immature stages that feed on the host plant, that are followed by a period of quiescence. During the period of quiescence a mite attaches itself to the leaf substrate (Crooker, 1985). Time spent developing in each stage depends on temperature and humidity during the specific life stage (Cagle, 1949; Herbert, 1981). Spider mite can develop from egg to adult in 7-8 days at maximum temperatures of about 30-32ºC (Zhang, 2003). Plate 2: Life cycle of two spotted spider mite (http://www.agf.gov.bc.ca/cropprot/tfipm/mites.htm) Males reach maturity first, then search and wait besides female deutonymph in the resting state (Penman and Cone, 1972). Copulation occurs almost immediately after an adult female emerges (Crooker, 1985). 21 University of Ghana http://ugspace.ug.edu.gh Offspring of both sexes is produced by a fertilized adult female with a sex ratio of 3:1 female: male (Overmeer and Harrison, 1969). Arrhenotokous parthenogenesis occurs in unfertilized eggs, resulting in the production of haploid males (Helle, 1985). The haplodiploidy genetic system enables a single female to initiate a new colony and cause a potential outbreak. 2.3 Economic importance of two-spotted spider mite Modern agricultural system provides an ideal environment with high quality host crops for spider mite population growth. Large scale monoculture, constant irrigation, fertilization and continued application of increasing doses of pesticides also increases the food quality of crops for the pest and has reduced the natural enemies of pest (Bhana, 2014). The importance of mite pest worldwide has become prominent as a result of its rapid reproduction rate and development of resistance to acaricides. Tetranychus urticae have a needle like piercing and sucking mouthpart which is used to penetrate plant tissues and feed on cell chloroplasts on the underside of the leaf. As feeding continues the upper surface of the leaf develops whitish or yellowish stippling characteristic, which may join and become brownish (Park and Lee, 2002). 22 University of Ghana http://ugspace.ug.edu.gh Plate 3: Cluster of spider mites hanging before dispersal from the tip of an eggplant. Depending on developmental stage, the stylet length of T. urticae is 132±27 μm but can vary from 103 μm (larvae) to 157 μm (adult females) (Avery and Briggs, 1968; Sances et al., 1979). The degree of leaf damage is a function of its stylet length and leaf thickness (Park and Lee, 2002). Damage done to leaves caused by T. urticae may result in a reduction in overall plant health or death (Park and Lee, 2002). Chhillar et al. (1998) estimated that an adult spider mite consumes about 50 % of its body mass per hour. Hundred photosynthetically active leaf cells are punctured and emptied per mite. Indirect effects of feeding thus include decrease in photosynthesis and transpiration (Park and Lee, 2002) leading to reduction in the amount of harvestable material (Hussey and Parr, 1963). 23 University of Ghana http://ugspace.ug.edu.gh 2.4 Effect of weather on two-spotted spider mite The biology, distribution and abundance of mites are affected by various abiotic factors. Temperature is one of the most important factors responsible for build-up of T.urticae population. Several authors have reported a positive relationship between mite population and high temperature (Singh and Singh, 1993; Dhar et al., 2000; Putatunda and Tagore, 2003; Gulati, 2004; Haque et al., 2011). However Sunita, (1996) reported positive relationship between mite population and low temperature. Spider mites are reported to be most abundant during warm and dry weather which favours its multiplication and spread (Jeppson et al., 1975). Relative humidity is another abiotic factor found to affect mite population build-up. Pande and Yadav, (1976) reported a positive relationship between relative humidity and mite population build-up, non-significant negative relationship was reported by other authors (Singh and Singh, 1993; Dhar et al., 2000). Heavy rains have also been reported to be a major cause of mortality for this pest as it is easily dislodged from plants by rain (Singh and Singh 1993; Gulati, 2004). Qui and Li, (1988) reported that low wind velocity favours the population build-up of tetranychid mites. 2.5 Management of two-spotted spider mite 2.5.1 Integrated pest management (IPM) Integrated Pest Management focuses on environmentally friendly pest management options (Lacey and Brooks, 1997), which has been developed into an alternative approach to the conventional chemical based pest control system, currently used by the agricultural industry. The primary objectives of IPM are to maintain pest damage below economic injury levels and so as to reduce the adverse impact of chemicals in the environment and to maintain long-term 24 University of Ghana http://ugspace.ug.edu.gh sustainable food production system (Thacker, 2002). IPM involves use of selective pesticide and other sustainable practices such as cultural control, physical control, host plant resistance, botanicals etc. Some of these methods are discussed briefly below for use against T. urticae. 2.5.1.1 Cultural control Cultural control is a form of manipulating the environment for pest management (Hajek, 2004). Cultural control can be achieved by regular scouting of crops to identify T. urticae outbreaks to know the level of infestation. Intercropping or establishing barriers with non- host crops, burning of infested plants in the hot dry months help to reduce mite densities. Weeds are common mite hosts and are eliminated to prevent the spread of the two-spotted spider mite. Also, separation of infested and newly planted crops reduces the spread of mites (Magdalena and Meyer, 1996). Irrigation and fertilization increases plant vigor and reduces crop stress. It has been documented that this reduces the susceptibility of plants to T.urticae infestation (Walsch et al., 1998). Other cultural practices such as planting of cover crops, mulching and crop rotation also help to reduce pest establishment (Arancon et al., 2005). Mites are easily dislodged from plants when a steady stream of water is sprayed on the plant (Lester et al., 1997). 2.5.1.2 Host-plant Resistance Breeding and selection of T. urticae resistant plant has been carried out on a several crops, such as Impatiens (Al-Abbasi and Weigle, 1982), soyabean (Mohammad and Rodriguez, 1985), Pelargonium (Chang et al., 1972), cucumber (de Ponti, 1980), Vigna angularis (Aguilar et al., 1996), strawberry (Shanks and Moore, 1995; Easterbrook and Simpson, 1998; Olbricht et al., 2014), watermelon (Lopez et al., 2005; El-Saiedy et al., 2011), maize (Mead 25 University of Ghana http://ugspace.ug.edu.gh et al., 2010), tomato (e.g. Saeidi and Mallik, 2012) and citrus (Agut et al., 2014). However, the resistance may be polygenic in most cases (Easterbrook and Simpson, 1998), and so is difficult to exploit by plant breeders. Agut et al., (2014), attributed the mechanisms of host-plant resistance of T. urticae to flavonoid pathways in citrus. Olbricht et al., (2014), reported that leaf trichomes on Fragaria entraps mites on tomato (Saeidi and Mallik, 2012), increased peroxidase and polyphenol oxidase activity in melon (Shoorooei et al., 2013), antibiosis and antixenosis in bean (Kamelmanesh et al., 2010), phytochemical compounds in watermelon, where El-Saiedy et al. (2011) reported a negative relationship between mite infestation and tannins, and nitrogen and protein content in maize leaves (Mead et al., 2010). 2.5.1.3 Biological control Biological control is defined as the use of a living organism to suppress a specific pest organism, making it either less abundant or less damaging than it would be (Hajek, 2004). In biological control, human intervention by enhancing the numbers of or introducing new natural enemies of target organisms so as to restore the natural balance result in a safer and environmentally friendly alternative of pest control (Burges and Hussey, 1971; Gullan and Cranston, 1994). Bacteria, fungi, nematodes, protozoa and viruses are entomopathogens regarded as key bio control components of IPM (Bidochka et al., 2002; Thacker, 2002) in pest control programmes. Tetranychus urticae has been the subject of some of the most successful examples of biological control by use of the phytoseiid mite Phytoseiulus persimilis. Hussey et al. (1965) were among the first researchers to have used Phytoseiulus persimilis in glasshouses on various crops and since then, it has been successfully used on different crops in a range of protected and unprotected environments. 26 University of Ghana http://ugspace.ug.edu.gh However, P. persimilis is active only under a limited range of conditions (Gorski and Eajfer, 2003), and so other species of phytoseiid mites have also been used against T. urticae. For example, Amblyseius idaeus and Phytoseiulus macropilis have been used on strawberry and cucumber in Brazil (Watanabe et al., 1994). Metwally et al. (2005) investigated life table and prey consumption of the predatory mite Neoseiulus cynodactylon, and concluded that T. urticae was a profitable prey species of this phytoseiid as a facultative predator. Neoseiulus californicus has shown promise as an agent in conservation biological control of T. urticae; the natural control of the mite in strawberries was used as the basis for developing an integrated management plan, using acaricide only when necessary (Greco et al., 2011). Complete eradication of the pest is not the aim since it will disturb the balance between the pest and the biological control agents (Schuster and Murphy, 1991). Thus, the success of biological control depends on the activities of these natural enemies in order to facilitate the reduction of density and distribution of the pest and eventually the potential agricultural damage (Gullan and Cranston, 1994). 2.5.1.4 Botanical pesticides Botanical pesticides such as garlic, chilli, soap extracts have been tested against spider mite in Namibia, Neem and Tephrosia in Zimbabwe, Kenya and Malawi (Keizer and Zuurbier, 1998) and insecticidal soaps containing potassium salts and fatty acids (Recep et al., 2005). Essential oils have also been used in pest control. Besides exerting acute toxicity to insects and mites, essential oils show sub-lethal effect as repellents, anti-feedants and reproduction inhibitors. Essential oils extracted from caraway seeds, eucalyptus, mint, rosemary, basil, oregano, thyme, and other plants have shown a significant acaricidal activity (Aslan et al., 2004; Choi et al., 2004; Miresmailli et al., 2006). These oils could be useful as fumigants in the control of phytophagous mites in greenhouses. Plant oils such as cottonseed oil (Rock & 27 University of Ghana http://ugspace.ug.edu.gh Crabtree, 1987) soybean oil (Lancaster et al., 2002; Moran et al., 2003) and rapeseed oil (Kiss et al., 1996; Marčić et al., 2009) have also proven to be effective in control of mite pest well. 2.5.1.5 Entomopathogenic fungi Studies have shown that entomopathogenic fungi, especially ascomycetes plays a vital role in regulating populations of harmful arthropods if used in biological control (Hajek & Delalibera, 2010), or applied as mycoinsecticides and/or mycoacaricides (Maniania et al., 2008; Jackson et al., 2010). The conidia and blastospores of Beauveria basssiana, Hirsutella thompsonii, Lecanicillium sp., Metharizium anisopliae, Isaria fumosorosea, Neozygites floridana (Chandler et al., 2000; Maniania et al., 2008), are used for formulation of fungal- based biopesticides. The main advantage of fungi as control agents is their ability to infect insects by penetrating the cuticle at any developmental stage. This means that insects of all ages and feeding habits, even sap-suckers, are susceptible to fungal disease (Gullan and Cranston, 1994). At the beginning of the 1980s, only one mycoacaricide was available (Mycar), formulated from conidia of H. thompsoni and intended for supression of citrus rust mite. Quarter of century later, there are some 30 commercial products acting against tetranychid, eriophyoid, and tarsonemid mites, mostly formulated as wettable powder or oil dispersions, and one third of which is made from conidia of B. bassiana (Faria and Wraight, 2007). 2.5.2 Chemical control Despite the hazards of conventional pesticides, some use is unavoidable (Gullan and Cranston, 1994), chemical pesticides are predominantly used in the control of T. urticae because they are readily available, easy to apply, effective, cheap and as a result of the lack of reliable alternative control measures (Sanderson and Zang, 1995). Some examples of chemical control which has been used for the control of T. urticae include, abamectin, 28 University of Ghana http://ugspace.ug.edu.gh bifenazate, bifenthrin, clofentizine, dicofol and methyl bromate (Motoba et al., 2000; Rauch and Nauen, 2003; Simpson et al., 2004; Recep et al., 2005; Fahnbulleh, 2007; Piraneo, 2013). Tetranychus urticae develops resistance to chemical groups after a few years of use which makes its control very difficult (Cranham and Helle, 1985). It has also developed cross- resistance to other chemical groups (Thwaite, 1991; Al-Jboory et al., 2004). Although chemical control play a significant role in the control of the two-spotted spider mite, mites still continue to cause a notable yield loss in field and greenhouse crops (Kim and Seo, 2001). 2.5.2.1 Pesticide usage pattern In order to produce healthy-looking, damage free fruit and vegetable to meet the demand of the growing population, fertilizers and insecticides are used to increase productivity and to control pest. Chemical pesticide use is a common practice in controlling pest and diseases in vegetable cultivation in Ghana (Ntow, 2007) since farmers’ reason that as long as there is no better alternative to pest control, the spraying of pesticides is good investment (Hardy, 1995). Although the use of chemicals gives rapid curative action, effective and economically adaptable in all situations in meeting changing agronomic and ecological conditions (Metcalf, 1975). Not surprisingly pesticide use has increased overtime in Ghana and is particularly elevated in the production of vegetable (Gerken et al., 2001). Chemical pesticides are used improperly and in dangerous combinations (Obeng-Ofori et al., 2002). Mixing of pesticides was encouraged by the farmers’ desire to have rapid knockdown of pests. Studies conducted by other authors (Wintuma, 2009; Kingsley, 2010) revealed similar findings among farmers in Accra. Though farmers claimed the combination was effective in controlling pest, however, combination of two insecticides with the same or different mode of action or mixing of two unrelated insecticides are dangerous (Obeng-Ofori et al., 2002) and results to cross or multiple resistance (IRAC, 2011). Medina, (1987), stated that the idea of mixing chemicals by farmers is questionable because the combinations used are indiscriminate. The 29 University of Ghana http://ugspace.ug.edu.gh practice of using indiscriminate combinations of pesticides, particularly of insecticides, may have contributed to the increase in incidences of insect pest infestation of tomato in Ghana (Biney, 2001) thereby defying some of the basic principles of insecticide management. For instance, Metcalf (1980), in his recommendation of strategies for pesticide management, states that the use of mixtures of insecticides must be avoided, since mixtures of insecticides generally result in the simultaneous development of resistance. Historically mite pests have been controlled by the introduction of acaricidal compound with a novel mode of action. Tetranychus urticae resistance to acaricides is a well-documented event (Grbic et al., 2011). Resistance to acaricides have been reported in over 60 countries to 95 acaricidal/insecticidal active ingredients (Van Leeuwen et al., 2010; DARP, 2013). Acaricides resistance have been reported from Norway (Fahnbulleh, 2007), North pacific (Piraneo, 2013), Turkey (Sokeli et al., 2007) and Australia (Nauen et al., 2001). Factors contributing to the development of resistance in T. urticae include high fecundity, short generation time and changes in agro-ecosystems (Cranham and Helle, 1985). 2.5.2.2 Effects of chemical control Indiscriminate use of insecticides has hazardous effect on both the human health and the environment. Hazards caused by the prolonged use of pesticides may affect human health directly or indirectly through residues in food and other biotic systems (Metcalf, 1980). 2.5.2.2.1 Human health Insecticides are not only toxic to insects but to humans as well. The World Health Organization (WHO) reported that 20% of pesticides use in the world is concentrated in developing countries posing danger to human health as well as environment (Hurtig et al., 2003). McCauley et al., (2001) noted that families residing in agricultural areas had noticeable levels of pesticide in their body systems. In Benin, endosulfan the most commonly 30 University of Ghana http://ugspace.ug.edu.gh used insecticide in cotton during 1999/2000 growing season contributed to food poisoning deaths of approximately 70 Benin citizens (Vodouhe, 2001). In Ghana, high levels of pesticide residues in foodstuff has led to an outcry over the inappropriate use of pesticides on vegetables cultivated in urban and peri-urban areas (Koteh et al., 2008). In July 2004, several people were admitted to hospital at Tarkwa in the Central Region of Ghana after eating cabbage sprayed with excessive amounts of organophosphate (Ghana News Agency, 2004). 2.5.2.2.2 Agricultural systems Modern agricultural system and over reliance on the use of chemicals disrupts the natural balance between insect pest and their natural enemies. These therefore lead to pest resurgence and introduction of new pest species whose populations were once regulated by natural enemies. The concept of secondary pest outbreak was introduced on spider mite as a nd paradigm. Advances in agricultural production after the 2 world war based on the extensive use of insecticide, fertilizer, irrigation and other cultural practices induced increase in spider mite population far above economic threshold (Hufkar et al., 1970; McMurtry et al., 1970; Jeppson et al., 1975; Metcalf, 1980). The use of acaricides has increased substantially over th the half past 20 century since the first serious and widespread outbreak of spider mites population during the 1950’s earning it the title of world most serious mite pest. 2.6 Resistance Development Resistance to an insecticide may be defined as an inherent ability of an insect population to survive doses of toxicant which would prove harmful to majority of the individuals in a normal population of the same species (Brown and Pal, 1971). According to Sawicki (1987), resistance represents a genetic change in response to assortment by toxicant that may impede control in the field. Generally, pests are known to 31 University of Ghana http://ugspace.ug.edu.gh develop resistance to chemicals due to frequent uncontrolled use and weak effect from common pesticides which are not actually potent against them (Fahnbulleh, 2007); and this resistance, in part, comes from their genetic makeup (Zhang, 2003). According to the Insecticide Resistance Action Committee (IRAC) resistance is the selection of a heritable characteristic in an insect population that results in the repeated failure of an insecticide product to provide the intended level of control when used as recommended, while Gunning, (1991) defined resistance as failure of an insecticide to control a population of insects due to a genetically transmitted capacity to tolerate more insecticide than usual. Resistance can also be considered as a form of self-defense, because pest subjection to the many environmental stresses or dangers such as: humidity, temperature, radiation, predation/parasitism, diseases, and pollutants in the form of pesticides or plants allelochemicals inhibit their activities for survival. It is the apparent expression of pests’ natural response to the above stresses through resistance mechanisms that is regarded as self- defence (Koehn and Bayne, 1989; Scott, 1995). As a result, the chemical is applied more frequently and in large quantities to make up for the decline in effectiveness. Resistant genes are normally present in a population but at a low frequency. They are derived from the initial population by the selective mortality of the more susceptible genotype growing during the application of an insecticide (Crow, 1957; O’Brien, 1967; Sawick, 1979). Development of resistance is rapid when selection pressure exerted by insecticide is widespread and continuous and occurs after the insect has been exposed to chemicals for several generations. Kumar (1984) reported that Heliothis virescens developed resistance to DDT after 15 years of use. Resistance to organochlorine compounds by the boll weevil Anthonomus grandis took 25 generations (Graves et al., 1967). The more rapid the lifecycle of the insect and the more persistent the chemical is in the environment the rapid the development of resistance (Hassal, 1990). 32 University of Ghana http://ugspace.ug.edu.gh 2.6.1 Mechanisms of insecticide resistance According to Brattsten et al., (1985) insecticide resistance is a multi-dimensional phenomenon affected by biochemical, physiological, genetic and ecological nature of the insect. They are metabolic detoxification, target site insensitivity and behavioural resistance. 2.6.1.1 Metabolic Detoxification Metabolic resistance is based on the normal biochemical reactions that occur in insect which enables them to detoxify or prevent the activation of toxic materials. The biochemical reaction responsible for detoxification of xenobiotics in insect includes esterases, monooxygenases and glutathione-S-tranferases (GSTs). These enzyme systems are often enhanced in resistant insect strain enabling them to metabolise or degrade insecticide before they are able to exert a toxic effect (IRAC, 2011) Cytochrome P450 – dependent monooxygenases The cytochrome P450 monooxygenases belong to a very large family of water-repelling, hemecontaining enzymes involved in the detoxification of many identical internally originated elements such as juvenile hormones, ecdysteroids and pheromones, and externally originated substances such as plant allelochemicals, insecticides and promutagenes (Eldefrawi et al., 1960; Nordhus, 2005). As for its association with acaricide resistance, the process of fluvalinate resistance in the Varroa mite is a good example (Hillesheim et al., 1996). Cytochrome P450 oxidizes biochemical change in insecticides through O-, S-, and N- alkyl hydroxylation, aliphatic hydroxylation and pixilation, aromatic hydroxylation, ester oxidation and nitrogen and thioester oxidation (Brogdon and McAllister, 1998). 33 University of Ghana http://ugspace.ug.edu.gh Glutathione- S - transferases (GSTs) Glutathione –S – transferase is another enzymes class that has been found to be involved in metabolic resistance (Scott, 1995). It plays a vital role in detoxification of Organophosphate insecticides (Salinas and Wong, 1999; Nordhus, 2005) thereby accelerating the breakdown of pesticides or their metabolism (Stumpf, 2001) so as to increase water solubility and later the elimination of lipophilic substances (Motoyama and Deuterman, 1975; Stumpf, 2001). They can convert the poisonous substances of pyrethroid, organophosphate (OP), DDT, cyclodiene and carbamate insecticides into harmless substances. An increased GST production has been associated with resistance to all major classes of insecticides (Prapanthadara et al., 1995; Vontas et al., 2001; Hemingway et al., 2004; Nordhus, 2005), but the process involved in this elevated enzyme production is not well known (Enayati et al., 2005; Nordhus, 2005). Enzymatic detoxification has the potential to confer cross resistance to toxins independent of their target site (Stumpf, 2001). Despite the fact that much is known about insect GSTs and their role in the biochemical changes (metabolism) of insecticides, little information is available concerning the enzyme in spider mite (Stumpf, 2001) therefore, resistance mechanisms linked to GST in mites are difficult to elucidate. Nonspecific Esterases One of the most common metabolic resistance mechanisms is that of elevated levels, or activity, of esterases enzymes, which hydrolyse ester bonds or sequester insecticides. These esterases comprise six families of proteins belonging to α/ß hydrolase fold superfamily. Nearly all of the strains of Culex quinquefasciatus which resist a broad range of organophosphate (OP) insecticides have been found to possess multiple copies of a gene for esterases, enabling them to overproduce this type of enzyme. In contrast, strains of malathion resistant Anopheles have been found with non-elevated levels of an altered form of esterase 34 University of Ghana http://ugspace.ug.edu.gh that specifically metabolises the OP malathion at a much faster rate than that in susceptible individuals. In Diptera, they occur as a gene cluster on the same chromosome. Individual members of the gene cluster may be modified in instances of insecticide resistance, for example, by changing a single amino acid that converts the specificity of an esterase to an insecticide hydrolase or by existing as multiple-gene copies that are amplified in resistant insects (Brogdon and McAllister, 1998). 2.6.1.2 Target site insensitivity Target site insensitivity is the second most common resistance mechanism encountered in insects. The site of action has been altered to decrease sensitivity to toxic attack. Alterations of amino acids responsible for insecticide binding at its site of action cause the insecticide to be less effective or even ineffective. Three different target site resistance mechanisms have been found: γ - aminobutyric acid (GABA), Acetylcholine esterase (AchE) and Sodium channel (knockdown resistance, kdr). All of these are well known targets of insecticides, and resistance alleles of each have been found (Scott, 1995). Insecticides act at this site within the insect, typically within the nervous system. The site of action can be modified in resistant strains of insects such that the insecticide no longer binds effectively. This result in the insects being unaffected or less affected, by the insecticide than susceptible insects. For example, the target site for Organophosphorus and carbamate insecticides is acetylcholinesterase (AChE) in the nerve cell synapses and the target of organochlorines (DDT) and synthetic pyrethroids are the sodium channels of the nerve sheath. DDT- pyrethroid cross-resistance may be produced by single amino acid changes (one or both of two known sites) in the axonal sodium channel insecticide-binding site. This cross-resistance 35 University of Ghana http://ugspace.ug.edu.gh appears to produce a shift in the sodium current activation curve and cause low sensitivity to pyrethroids. An unresponsive AChE resulting in OP resistance is found in many different insect species and has also been discovered in T. urticae strains from Germany (Voss and Matsumura, 1964; Smissaert et al., 1970), New Zealand (Ballantyne and Harrison, 1967), and in a few other tetranychid pest species, including the carmine spider mite (Tetranychus cinnabarinus) from Israel (Zahavi and Tahori, 1970), the kanzawa spider mite, Tetranychus kanzawa, from Japan (Kuwahara, 1982) and Caloglyphus berlesei (Blank, 1979). A point mutation in the γ – aminobutyric acid (GABA) receptor can confer an increased resistance to cyclodiene insecticides. This has been found in a range of different insect species (Bloomquist, 1994). 2.6.1.3 Behavioural resistance Behavioural resistance describes any modification in insect behaviour that helps to avoid the lethal effects of insecticides that will otherwise prove lethal. Insecticide resistance in mosquitoes is not always based on biochemical mechanisms such as metabolic detoxification or target site mutations, but may also be conferred by behavioural changes in response to prolonged exposure to an insecticide. For example, a species of Anopheles in Africa was reported to avoid insecticide residues inside houses by remaining outdoors (Brown, 1958). Behavioural resistance is not as important as physiological resistance but might be considered to be a contributing factor, leading to the avoidance of lethal doses of an insecticide (IRAC, 2011). 36 University of Ghana http://ugspace.ug.edu.gh 2.6.2 Forms of resistance 2.6.2.1 Cross resistance Cross resistance occurs when a resistance mechanism, that allows insects to resist one insecticide, also confers resistance to compounds within the same class, and may occur between chemical classes, depending on mechanism. The phenomenon of cross resistance is a relatively frequent one in vector populations (IRAC, 2011). For example, DDT and pyrethroid insecticides are chemically unrelated but both act on the same target site, the voltage gated sodium channel. Earlier use of DDT has resulted in several insect species developing resistance to DDT due to the kdr mutation at the target site. Where these mutations have been retained in the population, the insects have some resistance to all pyrethroids in addition to DDT. Cross resistance can also occur between OP and carbamate insecticides when resistance results from altered ACHe 2.6.2.2 Multiple resistance Multiple resistances are a common phenomenon and occur when several different resistance mechanisms are present simultaneously in resistant insects. The different resistance mechanisms may combine to provide resistance to multiple classes of products. It is also quite common for the contribution of different mechanisms to change over time as selection processes evolve (IRAC, 2011). 2.6.3 Resistance in two-spotted spider mite Resistance in mites to acaricides was first observed by Compton and Kearns in two-spotted spider mite, T. urticae Koch against ammonium potassium selenosulfide (Selecide) in 1937. It has been found that mites are capable of speedily developing extensive resistance to many acaricides (Cranham and Helle, 1985; Knowles, 1997; Stumpf and Nauen, 2001) after one to 37 University of Ghana http://ugspace.ug.edu.gh four years of use and often induces a high degree of cross-resistance. Factors that contributes to resistance in two-spotted spider mites include great egg laying potential, polyphagous feeding habit, short life-cycle, cross fertilization and high mutation rates coupled with their extremely dispersal behaviour all help to boost resistance development in the species (Croft and Van de Bann, 1988). The continuous exposure of T. urticae to different pesticides in order to contain them below economic threshold has resulted in resistant populations found in more than 40 countries in both greenhouses and field conditions (Georghiou and Lagunes- Tejeda, 1991), and resistance to at least 85 different compounds has been published (http://www.pesticideresistance.org accessed 21 May 2015). 2.7 The role of synergists Synergists are compounds that enhance the toxicity of some insecticides, although they usually have limited toxicity themselves. At non-toxic concentrations, insecticide synergists act by inhibiting certain enzymes naturally present in insects that would otherwise breakdown and detoxify insecticide molecules. The use of synergists has a valuable place in increasing the activity of certain insecticides on insects with specific resistance mechanisms and prolonging the useful life of those insecticides where resistance is developing. Synergists, including piperonyl butoxide (PBO), S,S,S-tributyl phosphoro-trithioate (DEF), and N-Octyl bicycloheptene dicarboximide (MGK-264) and Diethyl maleate (DEM), enhance the effect of several classes of insecticide, including the pyrethroids, organophosphates and carbamates. Synergists act by blocking metabolic pathways that would otherwise break down pesticides, thus restoring susceptibility to the agent. Piperonyl Butoxide (PBO) is co- formulated with insecticides such as carbaryl, methomyl, fenvalerate, permethrin, parathion, malathion and dimethoate; S,S,S-tributyl phosphorotrithioate (DEF) is co-formulated with 38 University of Ghana http://ugspace.ug.edu.gh malathion and permethrin; and Diethyl maleate (DEM) is co-formulated with parathion, malathion and dimethoate (Bernard and Philogene, 1993). Insecticide synergists have also been used to investigate resistance mechanisms and to identify the specific metabolic pathways targeted. Tolerance of honey bees, Apis mellifera, to pyrethroids is largely reversed by PBO and at low levels by DEF, suggesting a significant role of cytochrome P450s and a lesser role of esterases in detoxification of the chemical. However, the metabolic routes blocked by synergists are not yet fully understood and maybe dependent on the species of arthropods (Johnson et al., 2006). For example, although initial evidence in the 1970's suggested that PBO acts as a specific inhibitor of monooxygenases (P450s), recently, esterases of pyrethroid resistant strains of the cotton bollworm, (Helicoverpa armigera) were shown to be inhibited by PBO (Young and Gunning, 2005). In a study conducted with insecticide resistant strain of the German cockroach, Blatella germanica, PBO and DEF were tested as synergists to propoxur (a carbamate insecticide). Both were shown to inhibit cytochrome P450 monooxygenases at different levels (Sanches- Arroyo et al., 2001), thus, suggesting that this enzyme family is primarily responsible for the metabolism of the pesticide. 2.8 Resistance management Effective resistance management depends on early detection of the problem and rapid assimilation of information on the resistant insect population so that rational pesticide choices can be made (WHO, 2006). The ability to use other pesticides in order to avoid or delay the development of resistance in pest populations hinges on the availability of an adequate supply of pesticides with differing modes of action. This method is perhaps not the best solution, but it allows a pest to be controlled until other management strategies can be developed and brought to bear against the pest. These strategies often include the use of pesticides, but used 39 University of Ghana http://ugspace.ug.edu.gh less often and sometimes at reduced application rates (Karaagac, 2010). The goal of resistance management is to delay evolution of resistance in pests. The best way to achieve this is to minimize insecticide use. Thus, resistance management is a component of integrated pest management, which combines chemical and non-chemical controls to seek safe, economical, and sustainable suppression of pest populations. Alternatives to insecticides include biological control by predators, parasitoids, and pathogens. Also valuable are cultural controls (crop rotation, manipulation of planting dates to limit exposure to pests, and use of cultivars that tolerate pest damage) and mechanical controls (exclusion by barriers and trapping). Because large-scale resistance experiments are expensive, time consuming, and might worsen resistance problems, modelling has played a prominent role in devising tactics for resistance management. Although models have identified various strategies with the potential to delay resistance, practical successes in resistance management have relied primarily on reducing the number of insecticide treatments and diversifying the types of insecticide used. For example, programs in Australia, Israel, and the United States have limited the number of times and periods during which any particular insecticide is used against cotton pests. Resistance management requires more effective techniques for detecting resistance in its early stages of development. Pest resistance to a pesticide can be managed by reducing selection pressure by this pesticide on the pest population. In other words, the situation when all the pests except the most resistant ones are killed by a given chemical should be avoided. This can be achieved by avoiding unnecessary pesticide applications, using non-chemical control techniques, and leaving untreated refuges where susceptible pests can survive. Adopting the integrated pest management (IPM) approach usually helps with resistance management. When pesticides are the sole or predominant method of pest control, resistance is commonly managed through 40 University of Ghana http://ugspace.ug.edu.gh pesticide rotation. This involves alternating among pesticide classes with different modes of action to delay the onset of or mitigate existing pest resistance. 41 University of Ghana http://ugspace.ug.edu.gh CHAPTER THREE 3.0 MATERIALS AND METHODS 3.1 Study Area The study was conducted in four localities within Accra metropolis (Ashaiman, Opeibea, Sinna’s garden and University of Ghana farm (Legon). These areas were chosen because of the differences in farming practices, rainfall and pesticide usage pattern. The Accra metropolitan area is located within the greater Accra region in Southern Ghana. It is a coastal savannah ecological zone characterized by dry climatic conditions with two peak rainy seasons from April to June and September to October. The annual rainfall ranges between 740 and 890 mm per annum and a temperature of 26 C and 30 C the relative humidity is 65- 75 % (Dickson and Benneh, 1988). 3.2 Survey A survey was conducted on some selected farmers in the vegetable growing areas of Ashaiman, Opeibea, University of Ghana farm (Legon) and Sinna’s garden (Department of Crop Science) within the Accra metropolis so as to obtain information which will guide in the selection of insecticide to use for the study. A semi structured questionnaire was administered to farmers to obtain information on the practise, types, frequency and use of insecticides. Ten farmers were randomly selected at each of the afore-mentioned areas. Questions were structured to suit farmers understanding. An administrator was present to help translate the questions in the local dialect. 42 University of Ghana http://ugspace.ug.edu.gh 3.3 Miticides Commercial formulations of miticide tested were Karate® (lamda-cyhalothrin 5% EC Syngenta Crop Protection Pty Ltd, Pendle Hill, NSW)), Protect® (Emamectin Benzoate 1.9 % EC Syngenta Crop Protection Pty Ltd, Pendle Hill, NSW), Levo 2.4 SL™ Sineria Industries Ltd. Neosytou Georgiou, The Netherlands), Anty ataa® (Imidacloprid Bayer Australia Ltd, Pymble, NSW) and the synergists PBO (97.5% ultra PBO, Pu-SF-02-008, Endura® Fine Chemicals, Italy) and DEM 97% (Aldrich Chemical Company, Inc., Milwuakee, USA). 3.4 Field Sampling of spider mites Adult T. urticae were collected between November and April 2015, from commercial Eggplants, Okra, Paw paw and Cassava farms established at Ashaiman and Opeibea. Collection of mites was also made at University of Ghana farm and Department of crop science Sinna’s garden. Infested leaves were excised from the plants and carefully placed in a Paper bag and transported to the laboratory for bioassay. The T. urticae for the susceptible population were originally collected from cassava plant grown in the green house of the Department of Crop Science University of Ghana where miticides had not been used for well over three years and reared on eggplant in the greenhouse and kept breeding for about five generations. 43 University of Ghana http://ugspace.ug.edu.gh Plate 4: Sample collection site at Ashaiman. 3.5 Cultivation of miticide-free Egg plant Miticide-free eggplant seeds were grown in the green house of the Department of Crop Science University of Ghana (Legon). The seedlings were used to culture the mites for the synergism assay. New uninfested eggplant seedlings were rotated into the mite colony every ten days. 3.6 Determination of Miticide Concentrations A preliminary experiment was conducted to determine the optimal miticide concentration that will kill 90% of the mites after 24 h. 10 adult mites were exposed to each miticide (serially diluted with distilled water starting from twice the recommended rate for each miticide). The result of this preliminary experiment led to select a concentration of 0.7 ml/L and 1.5 ml/L, 4 44 University of Ghana http://ugspace.ug.edu.gh ml/L, 10 ml/L, 0.66 ml/L and 5 g/L for Protect®, Imidacloprid®, Karate®, Levo® and Sulphur® miticide respectively for use in subsequent bioassays. 3.7 Bioassay Adult T. urticae collected from the field were used upon arrival in the Laboratory. The leaf disc bioassays were used to estimate the LD50 and LD90, (the lethal concentrations that kill 50% and 90% of the population, respectively) of a particular miticide. My bioassay method closely mimics methods described by Piraneo, (2013) to determine the direct efficacy of some selected miticide against T. urticae. Each bioassay consisted of five serial dilutions with three replicates per tested concentration. Each test included a control where the insects were treated with distilled water. Infested leaves were cut into small disc and placed in a 90 mm petri-dish lined with filter paper. The number of T. urticae on each leaf disc was then counted under a microscope and recorded. The leaves were then sprayed with 1 ml of miticide dilutions at the different concentrations with a hand sprayer. All treatments were maintained at room temperature (27.0 ±2.0ºC) with a photoperiod of 12h: 12h (L: D). Mortality was accessed 24 h after treatment by probing each mite with a fine brush under a microscope. Mites unable to move were classified as dead. Mites were also classified as dead if they were twitching or were unable to move a distance equivalent to their body length. 45 University of Ghana http://ugspace.ug.edu.gh Plate 5: Experimental set up. 3.8 Determination of optimal (non-lethal) Piperonyl butoxide (PBO) and Diethyl Maleate (DEM) concentration A preliminary experiment was conducted to determine the optimal (non-lethal) synergist concentration that the mites could tolerate and remain alive for 24 hours. Serial dilutions of the synergist were prepared in distilled water. Adult mites from Opeibea and Ashaiman population (Karate resistant population) were exposed to each synergist as previously described and maintained under same condition (3.6). The result of this preliminary experiment led to select a concentration (0.4 and 1µl/ml respectively) of each synergist for use in subsequent synergism assays. 46 University of Ghana http://ugspace.ug.edu.gh 3.9 Time series experiment with synergists The optimal (non-lethal) PBO and DEM concentration determined from the above experiment were used for these assays. A time series experiment was carried out to determine the optimum time lapse between synergist and miticide application. The infested leaves were cut into leaf disc and the number of mites on each leaf disc were counted and placed in a 90 mm petri-dish lined with filter paper. The optimal PBO and DEM concentration determined from the above experiment was then applied. Karate miticide (0.151 ml/L and 0.140 ml/L) which produced 50 % mortality in the Opeibea and Ashaiman population respectively was then applied to the mites at 0, 1, 2 and 3 h after pre-treatment. All experiments were kept under lab conditions and mortality was recorded as stated earlier (3.6). 1 h pre-treatment period was used for both synergists. 3.10 Determination of the effect of PBO and DEM on Karate resistant populations The optimal PBO and DEM concentrations determined from the above experiments were used for the assays. Infested leaves were cut into leaf disc and placed in a 90 mm petri dish lined with filter paper and pre-treated with 0.4 µl/ml and 1.0 µl/ml PBO and DEM respectively, karate miticide was serially diluted (at least five concentrations) and sprayed on each leaf disc at 1 h after treatment with synergist. For each treatment, there were three replicate Petri dishes each. The experimental conditions were the same as before and mortality was recorded as stated earlier. 47 University of Ghana http://ugspace.ug.edu.gh 3.11 Data analysis Mortality data were subjected to probit analysis (Finney 1971) using a US Environmental Protection Agency probit program version 1.5 to determine the LD50, slope and fiducial limits. Resistance factors (RFs) were determined by dividing the LD50 of the field populations by the LD50 of the susceptible population. Time-series experiments were analysed using analysis of variance (ANOVA) after the percentage mortalities were arcsine transformed. The means were separated using the least significant difference (LSD). The synergist ratio (SR) was determined by dividing the LD50 of the field population without synergists by the LD50 of the field population with synergists. 48 University of Ghana http://ugspace.ug.edu.gh CHAPTER FOUR 4.0 RESULTS 4.1.1 Agronomic practices The survey covered a total of forty (40) farmers in Accra suburbia. The survey showed that (10%) of the farmers had been involved in crop cultivation for a period of 5-10 years, (32.5%) for a period of 11-15 years and (27.5%) for a period of over 20 years (fig 1). 4.1.2 Pests and pest control practices All the farmers indicated that the presence of pests were major reason for pesticide application. The farmers (50%) professed to take the necessary precautions before; during and after insecticide application and others (40%) relied on nose mask, gloves and long sleeves. A few (35%) sometimes took the necessary precautions, while the rest took absolutely no precaution though were aware of the associated health hazard of the pesticide. 49 University of Ghana http://ugspace.ug.edu.gh 35 30 25 20 15 10 5 0 5-10 11-15 16-20 >21 Years Fig. 1: Years spent in crop cultivation by farmers. Several crops were cultivated with garden egg (80%), okra (35%), cowpea (72.5%), pepper (45%), Soya bean (55%) and pawpaw (35%) being host and most affected by spider mite (fig 2). 100 crop cultivated 90 % crop affected by spider mite 80 70 60 50 40 30 20 10 0 Fig. 2: Farmers perception of crops most affected by spider mites. 50 Farmers (%) Farmers (%) University of Ghana http://ugspace.ug.edu.gh Farmers reported pest such as Aphids, Whiteflies, Diamond back moth, Thrips, Spider mites, crickets, grasshoppers and tomato bollworm affecting their crops. Diamond Back Moth and tomato bollworm were reported as the most destructive (fig 3). 100 90 80 70 60 50 40 30 20 10 0 Fig.3: Insect pests of crops as reported by farmers. 4.1.3 Pesticide usage pattern All the farmers interviewed indicated that they use agrochemicals on their crops. The main groups of agrochemicals used included insecticides, fungicides, herbicides and fertilizers (inorganic and organic manure). Of the agrochemical used; 11 types were insecticides, 3 fungicides, and 2 herbicides. The highest proportions and quantities of insecticides used were organophosphates, organochlorines and pyrethroids. These insecticides were applied as either single formulations or mixture (coctails). The neonicotinoid Imidacloprid which had a (30%) use among farmers with (22.5%) of the farmers using the product reported that it was effective. Also, (10%) of farmers surveyed sprayed cocktails of insecticide on their crops. Insecticides were classified as unlabelled if their labelling were either unclear to be read or there was none. Among the groups of fungicides; Mancozeb®, Maneb® and Cuprofix® were 51 Farmers (%) University of Ghana http://ugspace.ug.edu.gh the mostly used products against crop fungi. Glyphosate and Round up®) were the commonly used herbicides (fig 4). 80 widely used 70 effective 60 50 40 30 20 10 0 Fig.4: Commonly used insecticides and those perceived as effective by farmers. 4.1.4 Source of information The study revealed that (65%) of farmers most commonly obtained general information of crop protection and agricultural practices from experience, (30%) claimed to have received advice from Extension officers and (50%) received advice from other farmers. The mass media was another means of educating and disseminating information on pest control strategies but was not fully exploited by farmers and was cited by (12.5%) of the farmers surveyed (fig 5). 52 Farmers (%) University of Ghana http://ugspace.ug.edu.gh 70 60 50 40 30 20 10 0 Fig.5: Source of farmers’ knowledge about insect pest control. 4.1.5 Mode of insecticide application Most of the farmers applied pesticides by use of Knapsack sprayers fitted with different nozzles tips. The farmers were able to give the various application rates of the insecticides used per sprayer. Majority used the lid of the insecticide container as standard measure of dosages. In addition to this, dosages in the farms were difficult to estimate because the application equipment was not calibrated before use. Remnants of pesticides were discarded in the farm by pouring them on the ground or burying. 53 Farmers (%) University of Ghana http://ugspace.ug.edu.gh 4.1.6 Insecticide application dosage The result also showed that most farmers (68%) applied the recommended dose whilst (32%) exceeded the recommended dose but none of the farmers surveyed applied insecticide below the recommended rate (fig 6). 0% 32% 68% below recommended recommended above recommended Fig. 6: Insecticide dosage application rate by farmers. 4.1.7 Timing of insecticide application The timing of pesticides application mostly depended on presence of pests in different crops and their potential damages to the crop as well as farmers’ perception regarding pest management practices. The first application of insecticides was generally carried out two weeks after transplanting of seedlings (fig 7). 54 University of Ghana http://ugspace.ug.edu.gh 60 50 40 30 20 10 0 Presence of insects Degree of pest Date of transplanting infestation Fig.7: Timing of insecticide application by farmers. 4.1.8 Frequency of insecticide application Based on the farmers’ recollection on pesticide type and application frequency, weekly pesticide spraying was the most common, with (47.5%) of the farmers spraying insecticide. (25%) sprayed fortnightly, (12.5%) sprayed four times in a season; some (5%) of the farmers did not take note of the number of times they applied chemical on their crops (fig 8). 55 Farmers % University of Ghana http://ugspace.ug.edu.gh 50 45 40 35 30 25 20 15 10 5 0 weekly fortnightly monthly 4 times a varied season Fig.8: Frequency of insecticide application by farmers. 4.1.9 Reason for insecticide change by farmers When farmers were asked their reason for changing the use of some insecticide, (70%) of the farmers attributed the decline in the usage of those insecticides to ineffectiveness against the target pest while (45%) of the respondents said the insecticides were out of stock compelling them to look for an alternative even though the previous ones had not failed. Of the farmers surveyed, (10%) cited cost as their sole reason for changing insecticide (fig 9). 56 Farmers (%) University of Ghana http://ugspace.ug.edu.gh 80 70 60 50 40 30 20 10 0 cost effectiveness availability Fig.9: Reasons for insecticide change by farmers. 4.1.10 Method of disposal of empty insecticide containers Disposal of the empty pesticide containers was mainly by throwing away in farms and waste (60%), others burnt or buried them in pits (35%), while the rest (12.5%) put them to other uses. 70 60 50 40 30 20 10 0 Throw away Burning/burying in pits Put into other uses Fig.10: Methods of insecticide package disposal by farmers. 57 Farmers (%) Farmers (%) University of Ghana http://ugspace.ug.edu.gh 4.2 Susceptibility of two-spotted spider mite to miticides The response pattern of four population strains of the two-spotted spider mite against five miticides was examined by the spray application method. Susceptibility of the four populations differed in all of the five miticides treatment compared to the susceptible population (table 1). The LD50 values of all field populations were significantly higher than those of the susceptible strain for the five miticides assayed. All field populations were resistant to Karate (ranging from 12.0-21.6-fold) differing significantly from the reference strain but did not differ amongst each other. The field populations showed differences in response with regards to Imidacloprid insecticide. The Opebia area populations recorded the highest LD50 value to Imidacloprid (0.072 ml/L) and differed significantly from Ashaiman and Sinna’s garden population (0.014 and 0.022 ml/L respectively) but not the School farm, which recorded a significantly higher LD50 value for Imidacloprid (0.055) compared to Sinna’s garden population. However, all the field populations were susceptible to Levo® and Sulphur® as there were no significant differences amongst the field population. The slope of regression values obtained from the Probit analysis for all the five miticides were low ranging from 0.567-1.115. This is indicative of the fact that the field populations’ response to the toxicity test was quite heterogeneous. The resistance ratios for Protect ranged from 7-11, 1.8- 9.0 for Imidacloprid, Levo, 2.0-4.0 and Sulphur, 4.3-11.0. Karate recorded the highest resistance ratio ranging from 12.0-21.6 (Table 1). 58 University of Ghana http://ugspace.ug.edu.gh Table 1: Response of Four T. urticae Populations to Five Miticides by spray application. Insecticide/ N LD50 95%CL Slope±SE RF population Protect Susceptible 150 0.001 0.000-0.004 0.749-0.177 - Opeibea 207 0.007 0.002-0.017 0.859±0.159 7.0 Sinna's garden 258 0.007 0.002-0.018 0.772±0.123 7.0 Ashaiman 192 0.011 0.002-0.036 0.587-0.105 11.0 School farm 186 0.008 0.002-0.024 0.567-0.106 8.0 Imidacloprid Susceptible 150 0.008 0.002-0.023 0.766-0.153 - Opeibea 261 0.072 0.011-0.219 0.700-0.146 9.0 Sinna's garden 309 0.022 0.006-0.056 0.660-0.096 2.8 Ashaiman 192 0.014 0.004-0.013 0.857-0.129 1.8 School farm 252 0.055 0.016-0.123 0.754-0.120 6.9 Karate Susceptible 150 0.007 0.001-0.023 0.646-0.143 - Opeibea 273 0.151 0.038-0.375 0.793-0.137 21.6 Sinna's garden 222 0.094 0.025-0.242 0.680-0.118 13.4 Ashaiman 225 0.139 0.036-0.333 0.761-0.131 19.9 School farm 216 0.084 0.034-0.175 0.790-0.119 12.0 Levo Susceptible 150 0.003 0.001-0.009 0.748-0.147 - Opeibea 150 0.012 0.003-0.028 1.115-0.262 4.0 Sinna's garden 183 0.007 0.002-0.021 0.648-0.127 2.3 Ashaiman 282 0.006 0.002-0.013 0.762-0.118 2.0 School farm 213 0.009 0.001-0.005 0.658-0.105 3.0 Sulphur Susceptible 150 0.003 0.000-0.011 0.633-0.141 - Opeibea 150 0.033 0.799-0.123 0.009-0.176 11.0 Sinna's garden 228 0.017 0.002-0.020 0.584-0.097 5.7 Ashaiman 297 0.013 0.005-0.025 0.911-0.128 4.3 School farm 249 0.02 0.006-0.047 0.644-0.108 6.7 N, total number of mites tested; RF, resistance factor. LD50 field population/LD50 susceptible strain. 59 University of Ghana http://ugspace.ug.edu.gh The optimal PBO and DEM concentrations were 0.4 and 1.0 µl/ml for the karate resistant population, respectively. Time series experiment showed significant differences (<0.005) between mortalities in mites exposed immediately to karate after pre-treatment with PBO and DEM and those with the insecticide 1 or 2 h later (Table 2 and 3). Table 2: Optimal concentration of PBO and DEM on Karate resistant population. Synergist concentration Mean + SE %mortality (µl/ml) PBO O p e i b e a Ashaiman 0.4 0 0 2.0 29.44 ± 2.42 25.00 ± 4.81 10 91.16 ± 5.25 86.11 ± 7.35 DEM 1.0 0 0 5.0 21.03 ± 2.41 22.09 ± 2.0 25 92.31 ± 7.69 70.79 ± 7.70 60 University of Ghana http://ugspace.ug.edu.gh Table 3: Time-series experiments using karate resistant population Population Insecticide/synergist Time Mean ± SE % mortality concentration (h) a Opeibea 0.151 ml/L + 0.4 µl/ml 0 48.9±3.22a area b 1 94.8±2.60 bc 2 83.2±4.10 c 3 79.5±3.61 a Opeibea 0.151 ml/L + 1.0 µl/ml 0 48.7±1.28 area b 1 88.2±6.05 bc 2 83.5±3.40 c 3 76.7±3.00 Ashaiman 0.139 ml/L + 0.4 µl/ml 0 a 50.0±1.92 1 bc 94.7±2.68 2 c 81.4±9.44 ac 3 68.5±5.69 a Ashaiman 0.139 ml/L + 1.0 µl/ml 0 48.2±4.30 bc 1 85.05±2.52 a 2 63.34±3.49 a 3 62.74±2.01 Means followed by the same letter do not differ significantly (P<0.005) from one another. 61 University of Ghana http://ugspace.ug.edu.gh 4.3 Determination of the effect of PBO and DEM on Karate resistant populations The optimal PBO and DEM concentrations determined from the above experiment were 0.4 and 1.0 µl/ml respectively. Time lapse between pre-treatment with synergist and application of miticide was 1 h. Both PBO and DEM synergised effectively with karate insecticide. The synergist ratios for PBO and DEM were 4.3 and 2.9 respectively for the Opeibea population and 2.2 and 2.6 for Ashaiman population (Table 4). Table 4: Response of two T. urticae Karate resistant populations pre-treated with Synergist Population N LD50 95% CL Slope±SE RF Opeibea 273 0.151 0.038-0.375 0.793±0.137 21.6 Opeibea + PBO 150 0.035 0.007-0.105 0.748±0.127 4.3¶ Opeibea+ DEM 150 0.053 0.018-0.107 0.601±0.107 2.9¶ Ashaiman 225 0.139 0.036-0.333 0.761±0.131 19.9 Ashaiman+PBO 150 0.062 0.012-0.121 0.436±0.238 2.2¶ Ashaiman+DEM 150 0.053 0.007-0.209 0.704±0.089 2.6¶ N= total number of larvae tested, RF, resistance factor. LD50 field population/LD50 susceptible strain population. ¶Synergist ratio. LD50 of field population without synergist/LD50 of field population with synergist. PBO, piperonyl butoxide; DEM, diethyl maleate. 62 University of Ghana http://ugspace.ug.edu.gh CHAPTER FIVE 5.0 DISCUSSION Pest and disease are important constraints to crop production. The present study revealed that intensive small scale irrigated farming was common on small pieces of land with 2 to 6 cropping seasons per year. Pest and disease infestation varied with season. According to the survey, most farmers sprayed in the dry season than the rainy season because they claimed occurrence of pest and disease were more prevalent during the dry season than rainy season and most farmers grew vegetables during the dry season than the rainy season. For example mites’ population were reported to be most abundant during warm and dry weather which favoured their multiplication and spread (Jeppson et al., 1975). The damage caused by this pest had led to increase in use of chemicals (Sanderson and Zang, 1995). The practice of monoculture of different crops on small portions of the farmland was very common among the farms surveyed. Crops such as cowpea, soya bean, pepper, garden egg and okra were cultivated during a single cropping season. This practice create conducive environment by enhancing pest infestation and reducing the natural enemies of mites (Gulan and Cranston, 1994). The present study revealed the use of chemicals such as herbicide, insecticide and fungicides. These chemicals were used extensively from inception of crop cultivation suggesting an erroneous symphony of crop cultivation and insecticides. Dinham, (2003) estimated that 87 % of Ghanaian farmers relied heavily on the use of pesticide to control pest and diseases. This practice is the same in many African countries such as Botswana where about 98% of vegetable farmers rely on the use of chemicals to control pest (Obopile et al., 2008). 63 University of Ghana http://ugspace.ug.edu.gh Most farmers did not have specific insecticide for spider mite control; they expected the insecticides they used to address the pest complex affecting their crops. Insecticides such as lamda cyhalothrin, imidacloprid, ememactin benzoate were used to control pest on tomato, garden egg, pepper and cabbage while fungicides like maneb and mancozeb are used to control pest on cabbage. Farmers also used herbicides such as glyphosate to control growth of unwanted weeds in the farms. The choice of these pesticides was guided by effectiveness in controlling pest. The range of chemicals listed reflected the seriousness of pest problems and difficulties in control which prompted farmers to try different formulations; it could also be the indication that farmers were not using appropriate pesticides (Ntow, 2007). None of the farmers applied pesticide below recommended rate, which was laudable as sub lethal dose have been found to cause pest resurgence and development of resistance. Application of insecticides commenced 2 weeks after transplanting of seedlings subsequently followed by weekly or fortnightly application. Weekly application of insecticide was a common practice amongst the farmers interviewed, the frequency of application coupled with insecticide dosage may exert selection pressure on the insect population thereby selecting for more resistant individuals. Decision to pesticide spray by farmers was guided by the presence of pest, this was borne out of farmers awareness of the threat that pest posed in limiting the yield of their crops as well as the farmers intolerance to the presence of pests and damage level rather than being informed on the basis of economic threshold. General information on crop protection and agricultural practices mainly came from experience through years of cultivation, Agricultural Extension Officers and/or pesticide labels. To a more limited extent, information was also obtained from pesticide dealers or mass media. 64 University of Ghana http://ugspace.ug.edu.gh Farmers interviewed used mixtures (cocktail) of two or more insecticides and this usually resulted in the efficacy of one insecticide masking the inefficacy of others in the mixture. Mixing of pesticides was encouraged by the farmers’ desire to have rapid knockdown of pests. Studies conducted by other authors (Wintuma, 2009; Kingsley, 2010) revealed similar findings among farmers in Accra. Though farmers claim the combination was effective in controlling pest but combination of two insecticides with the same or different mode of action or mixing of two unrelated insecticides are dangerous (Obeng-Ofori et al., 2002) and results to cross or multiple resistance (IRAC, 2011). Medina, (1987), stated that the idea of mixing chemicals by farmers was questionable because the combinations used were indiscriminate. The practice of using indiscriminate combinations of pesticides, particularly of insecticides, may have contributed to the increase in incidences of insect pest infestation of tomato in Ghana (Biney, 2001) thereby defying some of the basic principles of insecticide management. For instance, Metcalf (1980), in his recommendation of strategies for pesticide management, stated that the use of mixtures of insecticides must be avoided, since mixtures of insecticides generally result in the simultaneous development of resistance. Most farmers do not take necessary precaution before, during and after spraying. Rubber boots, long sleeves shirts, gloves and a piece of cloth to cover the mouth serves as protective cover for most of the farmers during spraying. Most of the farmers surveyed had become ill at one point from exposure to pesticide. The most frequent symptoms reported were weakness, headache and/or dizziness (Ntow et al., 2006). With regard to pesticide application procedures, the knapsack was the most popular spraying equipment used. The commonest way of disposing pesticide remnants and sprayer wash water among the farmers interviewed was by throwing them on the field. Empty pesticide containers were thrown away, burnt or put to other use. Pesticide containers were seen lying 65 University of Ghana http://ugspace.ug.edu.gh about at the edges of farms. Majority of respondents interviewed indicated they were unaware of the effects of pesticides to the environment. It was envisaged that poor disposal of pesticide remnants and containers together with indiscriminate use of pesticides in farms presented a potential pollution problem to the environment and public health. In addition, putting the pesticide empty containers into other uses as was reported by the respondents could also be dangerous to human health. The level of resistance observed in all field populations to Karate showed the extent to which this product had been used to control pest in these areas. The commercial farms in this study (Opeibea area and Ashaiman) recorded the highest LD50 values of 0.151 and 0.139 ml/L corresponding to a 21.6-fold and 19.9-fold resistance, respectively. Yang et al. (2002) reported 9.5 and 51.8-fold resistance to bifenthrin and lambda cyhalothrin respectively in Kansas populations of T.urticae. The authors stated that there was a risk of cross resistance between bifenthrin and lambda cyhalothrin and also between bifenthrin and dimethoate as selection with dimethoate led to 15.9-fold cross resistance to bifenthrin. Selection with lambda cyhalothrin also led to a 2.8-fold cross resistance to bifenthrin. Wintuma (2009) and Kingsley (2010) reported an LD50 value of 0.323 ml/L and 1.56 µg ai/larva in Opeibea and Ashaiman population of whiteflies and DBM respectively. High LD50 values were also recorded in the University of Ghana farm and Sinna’s garden population of spider mite. LD50 values were 0.094 and 0.084 ml/L, respectively. Though the susceptibility level of mite pest to this insecticide appeared to be low, some farmers claimed the product was effective in the control of pest. This was significant considering that these fields had continually been exposed to this product for the past 6 years. Therefore, there was a need to discourage the use of synthetic pyrethroids in pest control in these areas so as not to aggravate the resistance problem (Hama 1991). It should be noted that T. urticae develops resistance to chemical 66 University of Ghana http://ugspace.ug.edu.gh groups after two to four years of use which makes its control very difficult (Cranham and Helle, 1985). Presence of abamectin and emamectin benzoate reservoirs in parenchyma tissue accounts for their long residual activity on certain crops under field conditions, and their ability to control several Dipteran and Lepidopteran leafminers (Jansson & Dybas 1996). The result of this studies shows that all the population were susceptible to Emamectin benzoate. The LD50 values ranged from 0.007-0.011 ml/L and resistance ratios ranged from 7.0-11.0 fold. Dybas, (1989) reported about 15-fold resistance ratios to Emamectin benzoate in populations of the spider mites. Compos et al., (1995) first reported a decreased activity of abamectin in T. urticae while monitoring ornamental nurseries in California. Resistance ratios at the LC95 level ranged from 1-658 and it was documented that increased resistance ratios were correlated with the number of abamectin applications per year along with the total no of application of abamectin. Beers et al., (1998) reported a decrease T. urticae susceptibility to abamectin from population collected from pear orchards in Washington. Vassilious and Kitsin (2013) reported LC50 values to abamectin in greenhouse from Cyprus; their highest LC50 value record to abamectin indicated a 1356-fold increase over the susceptible population. Tetranychus urticae have been found to develop cross-resistance to other chemical groups (Thwaite, 1991; Al-Jboory et al., 2004). Sato et al., (2005) reported that T. urticae developed 342-fold resistance to abamectin after 5 selections and that in the resistant population the cross resistance was determined against milbemectin 16.3-fold and chlorfenapyr 2.3-fold. In the Pacific Northwest, Piraneo (2013) reported 86.29-fold resistance in 2012 and 107.64-fold resistance in 2013 after 12 selections with abamectin. However, Fahnbulleh (2007) reported toxicity to abamectin in Norwegian populations of T. urticae, resistance ratios ranged from 1.10 to 1.31- fold. Sokeli et al., (2007) reported high toxicity of abamectin to T.urticae in Isparta province resistance ratios ranged from <1 to 1.6-fold. 67 University of Ghana http://ugspace.ug.edu.gh Except from Opeibea area, Tetranychus urticae populations from Ashaiman, School farm and Sinna’s garden were susceptible to imidacloprid. The LD50 values were 0.014, 0.022 and 0.055 ml/L respectively whilst that of Opeibea was 0.072 ml/L. Owusu-Boateng and Amuzu (2013) reported that farmers in Opeibea area used mixtures of insecticide so that they could have a rapid knock down effect against pest. This practice could be the reason for insecticide resistance in this area. Elbert et al., (1991) reported that at normal field rates Imidacloprid was not toxic to phytophagous mites. James and Price (2002) reported an increase in egg production of female T.urticae by 26% after 12 days of adult life by spray application with Imidacloprid. Oxymatrine and oxymatrine based products have shown considerable toxic and anti-feedant activity against several pest species in laboratory bioassays (Mao and Henderson, 2007; Asghari-Tabali et al., 2009). Spider mite populations from all the four farms were highly susceptible to levo. The LD50 values ranged from 0.006 to 0.012. Wang et al., (2009) found the combination of oxymatrine/prosuler to have an LC50 of 150µg/L for carmine spider mites T. cinnabarinus. Marcic and Medo (2014) reported the LC50 value to be 14.8 µl/L after 96 h. The authors also stated that 24 h exposure to prosular oxymatrine at the concentration of 34.3 µl/L caused a corrected mortality of 60% and reduced net fertility of the surviving females by 90%. The use of this insecticide was not widespread thus the high susceptibility levels. Therefore there is a need to monitor its use to avoid resistance development in the future. Sulphur is one of the oldest known insecticides used for the control or prevention of black spot, rust, leaf rust and powdery mildew on roses, other ornamentals, fruits and vegetables. It is also less frequently used as miticide. In the present study low LD50 values were recorded for all the populations this may probably be due to the fact that Sulphur® was less frequently 68 University of Ghana http://ugspace.ug.edu.gh recommended for spider mite control. The LD50 values ranged from 0.013-0.02 ml/L and resistance ratios ranged from 4.3-11-fold. Kovach and Gorsuch (1986) recorded 60% mortality in South Carolina population of spider mites 48 h after treatment. The authors also reported low toxicity of sulphur to predatory mites since some phytoseid mites have developed resistance to sulphur (Jeppson et al., 1975), the use of sulphur in pest management system may help keep mites below economic injury level. Synergism of karate by PBO and DEM resulted in increase in toxicity of karate in Opeibea and Ashaiman populations respectively and required 1 hour pre-treatment period. Resistance ratios fell from 21.6 to between 2.9 and 4.3 for DEM and PBO respectively in the Opeibea area population whilst that of Ashaiman fell from 19-fold to about 2-fold following the application of the synergist. Pasay et al., (2009) have shown in a laboratory experiment that application of PBO/permethrin drastically reduced the median survival time of permethrin resistant Sarcoptes scabiei variety Canis from 15 to 4 hours. Gunning et al., (1991) reported that PBO was likely to facilitate pyrethroid penetration through the cuticle. Eziah et al., (2008) also showed that a 30-fold and 1.9-fold synergist ratio using PBO and DEM in Esfenveralate-resistant populations of DBM with a 300 and 490-fold resistance respectively. These results were consistent with those obtained in the current study and suggest the involvement of glutathione-S- tranferases and cytochrome P450 monoxygenases in the observed resistance to Karate® in these locations. The development of resistance is a major constraint to effective control of pest with pesticides. Early monitoring of resistance should be encouraged as it will provide pest control practitioners the option to develop a long term strategy to arrest further development and institute a sound integrated approach to solving pest problems (Obeng-Ofori et al., 2002). 69 University of Ghana http://ugspace.ug.edu.gh CHAPTER SIX 6.0 Conclusion The present study revealed that farmers in Accra relied heavily on the use of chemicals to control pest, disease and weeds on their farms. Farmers used different types of insecticide with different modes of actions. Use of insecticide mixtures, spraying on weekly basis were improper pest management practices and should be discouraged. There was also a need to sensitize farmers on the threats posed by spider mites since most farmers were unaware of them. The amount of pesticide used in crop cultivation could be reduced if the correct information about suitable insecticides and control method to use against crop pest was provided to the farmer. The results of this study revealed that all field populations of spider mites were susceptible to Levo® and Protect® miticide but resistant to karate. Resistance to karate had been reported in other insects at Opeibea area, Ashaiman and University of Ghana farm but not Sinna’s garden (Wintuma, 2009; Kingsley, 2010). These provide the basis for resistance monitoring in spider mite in the future. The study also showed that both Piperonyl butoxide, (PBO) and Diethyl maleate DEM might be helpful in the management of resistance of spider mite to Karate® insecticide in Accra. 6.1 Recommendation It is then recommended that further studies should focus on creating awareness to farmers through extension workers about the benefits of; 1. Use of synergists 2. Targeted application of pesticides and strategies for resistance management 3. The use of cocktails of pesticides 70 University of Ghana http://ugspace.ug.edu.gh REFERENCES Agrawal, A.A. (2000). 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Sensitivity of Acetylcholinesterase in Spider Mites to Organophosphorus Compounds. Biochemical Pharmacology. 19: 219-225. Zhang Z.Q. (2003). Mites of Greenhouses: Identification, Biology, and Control. CABI. pp240. 92 University of Ghana http://ugspace.ug.edu.gh APPENDICES Appendix 1.0: EPA Probit Analysis Program used for calculating LC/EC values version 1.5 Appendix 1.1: susceptibility of T.urticae to Protect Site: susceptible Chi - Square for Heterogeneity (calculated) = 1.861 Parameter Estimate Std. Err. 95% Confidence Limits --------------------------------------------------------------------- Intercept 7.211835 0.512633 ( 6.207075, 8.216596) Slope 0.749151 0.177089 ( 0.402057, 1.096245) Spontaneous 0.198904 0.063805 ( 0.073846, 0.323963) Response Rate Estimated LC/EC Values and Confidence Limits Exposure 95% Confidence Limits Point Conc. Lower Upper LC/EC 1.00 0.000 0.000 0.000 LC/EC 5.00 0.000 0.000 0.000 LC/EC 10.00 0.000 0.000 0.000 LC/EC 15.00 0.000 0.000 0.000 LC/EC 50.00 0.001 0.000 0.004 LC/EC 85.00 0.027 0.008 0.220 LC/EC 90.00 0.057 0.016 0.779 LC/EC 95.00 0.175 0.039 5.480 LC/EC 99.00 1.422 0.186 239.481 93 University of Ghana http://ugspace.ug.edu.gh Site: Opeibea Chi - Square for Heterogeneity (calculated) = 6.039 Parameter Estimate Std. Err. 95% Confidence Limits --------------------------------------------------------------------- Intercept 6.841657 0.313075 ( 6.228030, 7.455285) Slope 0.859309 0.159006 ( 0.547658, 1.170960) Spontaneous 0.174952 0.058531 ( 0.060232, 0.289673) Response Rate Estimated LC/EC Values and Confidence Limits Exposure 95% Confidence Limits Point Conc. Lower Upper LC/EC 1.00 0.000 0.000 0.000 LC/EC 5.00 0.000 0.000 0.001 LC/EC 10.00 0.000 0.000 0.001 LC/EC 15.00 0.000 0.000 0.002 LC/EC 50.00 0.007 0.002 0.017 LC/EC 85.00 0.116 0.050 0.363 LC/EC 90.00 0.223 0.093 0.897 LC/EC 95.00 0.590 0.213 3.672 LC/EC 99.00 3.664 0.908 57.65 94 University of Ghana http://ugspace.ug.edu.gh Site: Sinna’s garden Chi - Square for Heterogeneity (calculated) = 4.456 Parameter Estimate Std. Err. 95% Confidence Limits --------------------------------------------------------------------- Intercept 6.657091 0.242052 ( 6.182668, 7.131514) Slope 0.772901 0.123393 ( 0.531050, 1.014752) Spontaneous 0.159486 0.062087 ( 0.037796, 0.281176) Response rate Estimated LC/EC Values and Confidence Limits Exposure 95% Confidence Limits Point Conc. Lower Upper LC/EC 1.00 0.000 0.000 0.000 LC/EC 5.00 0.000 0.000 0.000 LC/EC 10.00 0.000 0.000 0.001 LC/EC 15.00 0.000 0.000 0.001 LC/EC 50.00 0.007 0.002 0.018 LC/EC 85.00 0.157 0.070 0.435 LC/EC 90.00 0.327 0.140 1.101 LC/EC 95.00 0.964 0.361 4.692 LC/EC 99.00 7.342 1.908 80.021 95 University of Ghana http://ugspace.ug.edu.gh Site: Ashaiman Chi - Square for Heterogeneity (calculated) = 2.295 Parameter Estimate Std. Err. 95% Confidence Limits --------------------------------------------------------------------- Intercept 6.161765 0.208009 ( 5.754066, 6.569463) Slope 0.587969 0.105086 ( 0.382001, 0.793937) Spontaneous 0.148889 0.063017 ( 0.025375, 0.272403) Response Rate Estimated LC/EC Values and Confidence Limits Exposure 95% Confidence Limits Point Conc. Lower Upper LC/EC 1.00 0.000 0.000 0.000 LC/EC 5.00 0.000 0.000 0.000 LC/EC 10.00 0.000 0.000 0.001 LC/EC 15.00 0.000 0.000 0.001 LC/EC 50.00 0.011 0.002 0.036 LC/EC 85.00 0.612 0.192 3.078 LC/EC 90.00 1.599 0.462 11.408 LC/EC 95.00 6.633 1.547 87.293 96 University of Ghana http://ugspace.ug.edu.gh LC/EC 99.00 95.633 12.932 4578.905 Site: school farm Chi - Square for Heterogeneity (calculated) = 1.575 Parameter Estimate Std. Err. 95% Confidence Limits --------------------------------------------------------------------- Intercept 6.186069 0.234657 ( 5.726142, 6.645997) Slope 0.567341 0.106441 ( 0.358717, 0.775964) Spontaneous 0.134056 0.048543 ( 0.038912, 0.229200) Response Rate Estimated LC/EC Values and Confidence Limits Exposure 95% Confidence Limits Point Conc. Lower Upper LC/EC 1.00 0.000 0.000 0.000 LC/EC 5.00 0.000 0.000 0.000 LC/EC 10.00 0.000 0.000 0.000 LC/EC 15.00 0.000 0.000 0.001 LC/EC 50.00 0.008 0.002 0.024 LC/EC 85.00 0.545 0.155 4.809 LC/EC 90.00 1.474 0.352 21.100 97 University of Ghana http://ugspace.ug.edu.gh LC/EC 95.00 6.438 1.131 198.678 LC/EC 99.00 102.278 9.351 14400.345 Appendix 1.2: susceptibility of T.urticae to imidacloprid Site: Susceptible Chi - Square for Heterogeneity (calculated) = 2.786 Parameter Estimate Std. Err. 95% Confidence Limits --------------------------------------------------------------------- Intercept 6.618414 0.320424 ( 5.990383, 7.246445) Slope 0.776357 0.153197 ( 0.476091, 1.076622) Spontaneous 0.159430 0.052531 ( 0.056469, 0.262391) Response Rate Estimated LC/EC Values and Confidence Limits Exposure 95% Confidence Limits Point Conc. Lower Upper LC/EC 1.00 0.000 0.000 0.000 LC/EC 5.00 0.000 0.000 0.000 LC/EC 10.00 0.000 0.000 0.001 LC/EC 15.00 0.000 0.000 0.002 LC/EC 50.00 0.008 0.002 0.023 LC/EC 85.00 0.178 0.063 0.849 LC/EC 90.00 0.368 0.122 2.443 LC/EC 95.00 1.082 0.300 12.532 LC/EC 99.00 8.162 1.453 299.797 98 University of Ghana http://ugspace.ug.edu.gh Site: Opeibea Chi - Square for Heterogeneity (calculated) = 3.902 Parameter Estimate Std. Err. 95% Confidence Limits --------------------------------------------------------------------- Intercept 5.801442 0.224949 ( 5.360541, 6.242342) Slope 0.700189 0.146269 ( 0.413502, 0.986876) Spontaneous 0.266044 0.069621 ( 0.129588, 0.402500) Response Rate Estimated LC/EC Values and Confidence Limits Exposure 95% Confidence Limits Point Conc. Lower Upper LC/EC 1.00 0.000 0.000 0.001 LC/EC 5.00 0.000 0.000 0.003 LC/EC 10.00 0.001 0.000 0.008 LC/EC 15.00 0.002 0.000 0.014 LC/EC 50.00 0.072 0.011 0.219 LC/EC 85.00 2.166 0.732 11.742 LC/EC 90.00 4.850 1.508 39.585 LC/EC 95.00 16.018 4.031 261.382 LC/EC 99.00 150.585 22.448 10229.071 99 University of Ghana http://ugspace.ug.edu.gh Site: Sinna’s garden Chi - Square for Heterogeneity (calculated) = 3.244 Parameter Estimate Std. Err. 95% Confidence Limits --------------------------------------------------------------------- Intercept 6.090998 0.174063 ( 5.749834, 6.432161) Slope 0.660362 0.096884 ( 0.470469, 0.850255) Spontaneous 0.140044 0.060457 ( 0.021547, 0.258540) Response Rate Estimated LC/EC Values and Confidence Limits Exposure 95% Confidence Limits Point Conc. Lower Upper LC/EC 1.00 0.000 0.000 0.000 LC/EC 5.00 0.000 0.000 0.000 LC/EC 10.00 0.000 0.000 0.001 LC/EC 15.00 0.001 0.000 0.003 LC/EC 50.00 0.022 0.006 0.056 LC/EC 85.00 0.827 0.346 2.591 LC/EC 90.00 1.944 0.756 7.642 LC/EC 95.00 6.899 2.259 40.473 LC/EC 99.00 74.241 15.921 1020.510 100 University of Ghana http://ugspace.ug.edu.gh Site: Ashaiman Chi - Square for Heterogeneity (calculated) = 4.281 Parameter Estimate Std. Err. 95% Confidence Limits --------------------------------------------------------------------- Intercept 6.584781 0.227790 ( 6.138312, 7.031250) Slope 0.857498 0.129803 ( 0.603083, 1.111912) Spontaneous 0.168703 0.062725 ( 0.045763, 0.291644) Response Rate Estimated LC/EC Values and Confidence Limits Exposure 95% Confidence Limits Point Conc. Lower Upper LC/EC 1.00 0.000 0.000 0.000 LC/EC 5.00 0.000 0.000 0.001 LC/EC 10.00 0.000 0.000 0.002 LC/EC 15.00 0.001 0.000 0.003 LC/EC 50.00 0.014 0.004 0.033 LC/EC 85.00 0.229 0.107 0.568 LC/EC 90.00 0.443 0.202 1.272 LC/EC 95.00 1.175 0.486 4.491 101 University of Ghana http://ugspace.ug.edu.gh LC/EC 99.00 7.324 2.254 53.549 Site: school farm Chi - Square for Heterogeneity (calculated) = 1.402 Parameter Estimate Std. Err. 95% Confidence Limits --------------------------------------------------------------------- Intercept 5.952070 0.150260 ( 5.657560, 6.246579) Slope 0.754126 0.120732 ( 0.517491, 0.990761) Spontaneous 0.125421 0.044182 ( 0.038824, 0.212018) Response Rate Estimated LC/EC Values and Confidence Limits Exposure 95% Confidence Limits Point Conc. Lower Upper LC/EC 1.00 0.000 0.000 0.000 LC/EC 5.00 0.000 0.000 0.002 LC/EC 10.00 0.001 0.000 0.005 LC/EC 15.00 0.002 0.000 0.009 LC/EC 50.00 0.055 0.016 0.123 LC/EC 85.00 1.294 0.607 3.652 LC/EC 90.00 2.735 1.194 9.783 LC/EC 95.00 8.293 3.054 44.797 LC/EC 99.00 66.417 16.256 850.250 102 University of Ghana http://ugspace.ug.edu.gh Appendix 1.3: susceptibility of T.urticae to karate Site: Susceptible Chi - Square for Heterogeneity (calculated) = 1.976 Parameter Estimate Std. Err. 95% Confidence Limits --------------------------------------------------------------------- Intercept 6.404239 0.338725 ( 5.740338, 7.068141) Slope 0.646367 0.143398 ( 0.365306, 0.927428) Spontaneous 0.143990 0.059823 ( 0.026738, 0.261243) Response Rate Estimated LC/EC Values and Confidence Limits Exposure 95% Confidence Limits Point Conc. Lower Upper LC/EC 1.00 0.000 0.000 0.000 LC/EC 5.00 0.000 0.000 0.000 LC/EC 10.00 0.000 0.000 0.001 LC/EC 15.00 0.000 0.000 0.001 LC/EC 50.00 0.007 0.001 0.023 LC/EC 85.00 0.270 0.074 3.014 LC/EC 90.00 0.646 0.152 12.555 LC/EC 95.00 2.357 0.420 110.918 LC/EC 99.00 26.701 2.545 7277.590 103 University of Ghana http://ugspace.ug.edu.gh Site: Opeibea Chi - Square for Heterogeneity (calculated) = 6.074 Parameter Estimate Std. Err. 95% Confidence Limits --------------------------------------------------------------------- Intercept 5.652140 0.175470 ( 5.308219, 5.996061) Slope 0.793648 0.137271 ( 0.524596, 1.062700) Spontaneous 0.209912 0.061656 ( 0.089067, 0.330758) Response Rate Estimated LC/EC Values and Confidence Limits Exposure 95% Confidence Limits Point Conc. Lower Upper LC/EC 1.00 0.000 0.000 0.002 LC/EC 5.00 0.001 0.000 0.008 LC/EC 10.00 0.004 0.000 0.018 LC/EC 15.00 0.007 0.001 0.031 LC/EC 50.00 0.151 0.038 0.375 LC/EC 85.00 3.049 1.289 9.772 LC/EC 90.00 6.210 2.487 25.274 LC/EC 95.00 17.819 6.148 110.671 LC/EC 99.00 128.662 30.139 1966.573 104 University of Ghana http://ugspace.ug.edu.gh Site: Sinna’s garden Chi - Square for Heterogeneity (calculated) = 1.944 Parameter Estimate Std. Err. 95% Confidence Limits --------------------------------------------------------------------- Intercept 5.698296 0.170873 ( 5.363385, 6.033206) Slope 0.680458 0.118010 ( 0.449158, 0.911757) Spontaneous 0.125569 0.056790 ( 0.014260, 0.236878) Response Rate Estimated LC/EC Values and Confidence Limits Exposure 95% Confidence Limits Point Conc. Lower Upper LC/EC 1.00 0.000 0.000 0.000 LC/EC 5.00 0.000 0.000 0.003 LC/EC 10.00 0.001 0.000 0.007 LC/EC 15.00 0.003 0.000 0.013 LC/EC 50.00 0.094 0.025 0.242 LC/EC 85.00 3.140 1.172 14.182 LC/EC 90.00 7.198 2.408 45.079 LC/EC 95.00 24.611 6.622 264.169 LC/EC 99.00 246.896 40.640 7913.326 105 University of Ghana http://ugspace.ug.edu.gh Site: Ashaiman Chi - Square for Heterogeneity (calculated) = 1.332 Parameter Estimate Std. Err. 95% Confidence Limits --------------------------------------------------------------------- Intercept 5.651617 0.150488 ( 5.356661, 5.946572) Slope 0.761406 0.131055 ( 0.504538, 1.018275) Spontaneous 0.125415 0.053377 ( 0.020797, 0.230033) Response Rate Estimated LC/EC Values and Confidence Limits Exposure 95% Confidence Limits Point Conc. Lower Upper LC/EC 1.00 0.000 0.000 0.001 LC/EC 5.00 0.001 0.000 0.006 LC/EC 10.00 0.003 0.000 0.014 LC/EC 15.00 0.006 0.000 0.026 LC/EC 50.00 0.139 0.036 0.333 LC/EC 85.00 3.202 1.403 10.205 LC/EC 90.00 6.720 2.741 27.845 LC/EC 95.00 20.162 6.920 131.631 106 University of Ghana http://ugspace.ug.edu.gh LC/EC 99.00 158.293 35.647 2674.040 Site: school farm Chi - Square for Heterogeneity (calculated) = 6.023 Parameter Estimate Std. Err. 95% Confidence Limits --------------------------------------------------------------------- Intercept 5.851677 0.176211 ( 5.506304, 6.197051) Slope 0.790156 0.119765 ( 0.555416, 1.024896) Spontaneous 0.122805 0.044258 ( 0.036061, 0.209550) Response Rate Estimated LC/EC Values and Confidence Limits Exposure 95% Confidence Limits Point Conc. Lower Upper LC/EC 1.00 0.000 0.000 0.001 LC/EC 5.00 0.001 0.000 0.003 LC/EC 10.00 0.002 0.000 0.007 LC/EC 15.00 0.004 0.001 0.012 LC/EC 50.00 0.084 0.034 0.175 LC/EC 85.00 1.713 0.748 5.914 LC/EC 90.00 3.500 1.384 15.319 LC/EC 95.00 10.090 3.336 64.826 LC/EC 99.00 73.492 16.479 1022.642 107 University of Ghana http://ugspace.ug.edu.gh Appendix 1.4: susceptibility of T.urticae to levo Site: Susceptible Chi - Square for Heterogeneity (calculated) = 5.992 Parameter Estimate Std. Err. 95% Confidence Limits --------------------------------------------------------------------- Intercept 6.867028 0.370392 ( 6.141059, 7.592998) Slope 0.748621 0.147076 ( 0.460351, 1.036890) Spontaneous 0.125521 0.045703 ( 0.035943, 0.215099) Response Rate Estimated LC/EC Values and Confidence Limits Exposure 95% Confidence Limits Point Conc. Lower Upper LC/EC 1.00 0.000 0.000 0.000 LC/EC 5.00 0.000 0.000 0.000 LC/EC 10.00 0.000 0.000 0.000 LC/EC 15.00 0.000 0.000 0.001 LC/EC 50.00 0.003 0.001 0.009 LC/EC 85.00 0.078 0.027 0.431 LC/EC 90.00 0.165 0.052 1.321 LC/EC 95.00 0.505 0.129 7.355 LC/EC 99.00 4.107 0.650 200.843 108 University of Ghana http://ugspace.ug.edu.gh Site: Opeibea Chi - Square for Heterogeneity (calculated) = 2.969 Parameter Estimate Std. Err. 95% Confidence Limits --------------------------------------------------------------------- Intercept 7.143714 0.474318 ( 6.214052, 8.073378) Slope 1.115353 0.262105 ( 0.601626, 1.629079) Spontaneous 0.211683 0.052309 ( 0.109157, 0.314209) Response Rate Estimated LC/EC Values and Confidence Limits Exposure 95% Confidence Limits Point Conc. Lower Upper LC/EC 1.00 0.000 0.000 0.001 LC/EC 5.00 0.000 0.000 0.002 LC/EC 10.00 0.001 0.000 0.003 LC/EC 15.00 0.001 0.000 0.005 LC/EC 50.00 0.012 0.003 0.028 LC/EC 85.00 0.102 0.043 0.424 LC/EC 90.00 0.169 0.068 0.969 LC/EC 95.00 0.357 0.127 3.499 LC/EC 99.00 1.458 0.368 42.779 109 University of Ghana http://ugspace.ug.edu.gh Site: Sinna’s garden Chi - Square for Heterogeneity (calculated) = 2.373 Parameter Estimate Std. Err. 95% Confidence Limits --------------------------------------------------------------------- Intercept 6.380169 0.282147 ( 5.827161, 6.933177) Slope 0.648092 0.127173 ( 0.398832, 0.897351) Spontaneous 0.128032 0.057445 ( 0.015440, 0.240624) Response Rate Estimated LC/EC Values and Confidence Limits Exposure 95% Confidence Limits Point Conc. Lower Upper LC/EC 1.00 0.000 0.000 0.000 LC/EC 5.00 0.000 0.000 0.000 LC/EC 10.00 0.000 0.000 0.001 LC/EC 15.00 0.000 0.000 0.001 LC/EC 50.00 0.007 0.002 0.021 LC/EC 85.00 0.295 0.096 1.957 LC/EC 90.00 0.705 0.200 7.233 LC/EC 95.00 2.561 0.563 53.286 LC/EC 99.00 28.832 3.568 2466.939 110 University of Ghana http://ugspace.ug.edu.gh Site: Ashaiman Chi - Square for Heterogeneity (calculated) = 3.578 Parameter Estimate Std. Err. 95% Confidence Limits --------------------------------------------------------------------- Intercept 6.714321 0.281170 ( 6.163228, 7.265414) Slope 0.762458 0.118133 ( 0.530917, 0.993999) Spontaneous 0.120696 0.051213 ( 0.020319, 0.221073) Response Rate Estimated LC/EC Values and Confidence Limits Exposure 95% Confidence Limits Point Conc. Lower Upper LC/EC 1.00 0.000 0.000 0.000 LC/EC 5.00 0.000 0.000 0.000 LC/EC 10.00 0.000 0.000 0.000 LC/EC 15.00 0.000 0.000 0.001 LC/EC 50.00 0.006 0.002 0.013 LC/EC 85.00 0.129 0.057 0.405 LC/EC 90.00 0.271 0.110 1.066 LC/EC 95.00 0.811 0.280 4.706 111 University of Ghana http://ugspace.ug.edu.gh LC/EC 99.00 6.348 1.484 82.627 Site: school farm Chi - Square for Heterogeneity (calculated) = 3.964 Parameter Estimate Std. Err. 95% Confidence Limits --------------------------------------------------------------------- Intercept 6.748228 0.264652 ( 6.229510, 7.266946) Slope 0.658302 0.105055 ( 0.452394, 0.864210) Spontaneous 0.117230 0.045666 ( 0.027725, 0.206736) Response Rate Estimated LC/EC Values and Confidence Limits Exposure 95% Confidence Limits Point Conc. Lower Upper LC/EC 1.00 0.000 0.000 0.000 LC/EC 5.00 0.000 0.000 0.000 LC/EC 10.00 0.000 0.000 0.000 LC/EC 15.00 0.000 0.000 0.000 LC/EC 50.00 0.002 0.001 0.005 LC/EC 85.00 0.083 0.032 0.338 LC/EC 90.00 0.196 0.068 1.071 LC/EC 95.00 0.697 0.195 6.217 LC/EC 99.00 7.553 1.307 182.316 112 University of Ghana http://ugspace.ug.edu.gh Appendix 1.5: susceptibility of T.urticae to sulphur Site: Susceptible Chi - Square for Heterogeneity (calculated) = 0.022 Parameter Estimate Std. Err. 95% Confidence Limits --------------------------------------------------------------------- Intercept 6.586844 0.369914 ( 5.861812, 7.311876) Slope 0.633816 0.141558 ( 0.356363, 0.911269) Spontaneous 0.163533 0.063803 ( 0.038479, 0.288587) Response Rate Estimated LC/EC Values and Confidence Limits Exposure 95% Confidence Limits Point Conc. Lower Upper LC/EC 1.00 0.000 0.000 0.000 LC/EC 5.00 0.000 0.000 0.000 LC/EC 10.00 0.000 0.000 0.000 LC/EC 15.00 0.000 0.000 0.000 LC/EC 50.00 0.003 0.000 0.011 LC/EC 85.00 0.135 0.036 1.509 LC/EC 90.00 0.330 0.076 6.444 LC/EC 95.00 1.235 0.216 59.546 LC/EC 99.00 14.678 1.366 4303.211 113 University of Ghana http://ugspace.ug.edu.gh Site: Opeibea Chi - Square for Heterogeneity (calculated) = 3.374 Parameter Estimate Std. Err. 95% Confidence Limits --------------------------------------------------------------------- Intercept 5.986101 0.259809 ( 5.476875, 6.495327) Slope 0.799625 0.181846 ( 0.443208, 1.156043) Spontaneous 0.199044 0.063504 ( 0.074577, 0.323511) Response Rate Estimated LC/EC Values and Confidence Limits Exposure 95% Confidence Limits Point Conc. Lower Upper LC/EC 1.00 0.000 0.000 0.001 LC/EC 5.00 0.001 0.000 0.004 LC/EC 10.00 0.001 0.000 0.009 LC/EC 15.00 0.003 0.000 0.016 LC/EC 50.00 0.058 0.009 0.176 LC/EC 85.00 1.156 0.386 7.103 LC/EC 90.00 2.342 0.726 21.988 LC/EC 95.00 6.666 1.709 127.103 LC/EC 99.00 47.428 7.551 3852.981 114 University of Ghana http://ugspace.ug.edu.gh Site: Sinna’s garden Chi - Square for Heterogeneity (calculated) = 2.583 Parameter Estimate Std. Err. 95% Confidence Limits --------------------------------------------------------------------- Intercept 6.032766 0.184980 ( 5.670206, 6.395327) Slope 0.584879 0.097980 ( 0.392839, 0.776919) Spontaneous 0.128849 0.060056 ( 0.011139, 0.246559) Response Rate Estimated LC/EC Values and Confidence Limits Exposure 95% Confidence Limits Point Conc. Lower Upper LC/EC 1.00 0.000 0.000 0.000 LC/EC 5.00 0.000 0.000 0.000 LC/EC 10.00 0.000 0.000 0.001 LC/EC 15.00 0.000 0.000 0.002 LC/EC 50.00 0.017 0.004 0.050 LC/EC 85.00 1.014 0.342 5.101 LC/EC 90.00 2.663 0.796 19.076 LC/EC 95.00 11.133 2.607 143.737 LC/EC 99.00 162.790 21.872 7004.759 115 University of Ghana http://ugspace.ug.edu.gh Site: Ashaiman Chi - Square for Heterogeneity (calculated) = 3.174 Parameter Estimate Std. Err. 95% Confidence Limits --------------------------------------------------------------------- Intercept 6.729144 0.238588 ( 6.261510, 7.196777) Slope 0.911365 0.128806 ( 0.658905, 1.163825) Spontaneous 0.113277 0.052972 ( 0.009452, 0.217103) Response Rate Estimated LC/EC Values and Confidence Limits Exposure 95% Confidence Limits Point Conc. Lower Upper LC/EC 1.00 0.000 0.000 0.000 LC/EC 5.00 0.000 0.000 0.001 LC/EC 10.00 0.000 0.000 0.002 LC/EC 15.00 0.001 0.000 0.003 LC/EC 50.00 0.013 0.005 0.025 LC/EC 85.00 0.174 0.091 0.389 LC/EC 90.00 0.323 0.162 0.833 LC/EC 95.00 0.808 0.365 2.707 116 University of Ghana http://ugspace.ug.edu.gh LC/EC 99.00 4.521 1.537 26.775 Site: school farm Chi - Square for Heterogeneity (calculated) = 4.825 Parameter Estimate Std. Err. 95% Confidence Limits --------------------------------------------------------------------- Intercept 6.100797 0.184864 ( 5.738464, 6.463130) Slope 0.644929 0.108194 ( 0.432869, 0.856989) Spontaneous 0.121176 0.046339 ( 0.030351, 0.212001) Response Rate Estimated LC/EC Values and Confidence Limits Exposure 95% Confidence Limits Point Conc. Lower Upper LC/EC 1.00 0.000 0.000 0.000 LC/EC 5.00 0.000 0.000 0.000 LC/EC 10.00 0.000 0.000 0.001 LC/EC 15.00 0.000 0.000 0.002 LC/EC 50.00 0.020 0.006 0.047 LC/EC 85.00 0.795 0.307 3.532 LC/EC 90.00 1.907 0.646 11.942 LC/EC 95.00 6.977 1.856 76.182 LC/EC 99.00 79.472 12.518 2643.617 117 University of Ghana http://ugspace.ug.edu.gh 118 University of Ghana http://ugspace.ug.edu.gh 119