Incidence, Distribution and Characteristics of Major Tomato Leaf ...
Incidence, Distribution and Characteristics of Major Tomato Leaf ... Incidence, Distribution and Characteristics of Major Tomato Leaf ...
Incidence, distribution and characteristics of major tomato leaf curl and mosaic virus diseases 1991; Bautista et al., 1995; Van de Watering et al., 1996). Major vectors of tomato viruses in East Africa are whiteflies, aphids and thrips (Nono-Womdim et al., 1996). Aphids and whiteflies are the major vectors reported in Uganda (Baliddawa, 1990). Of the two vectors, only whiteflies transmit tomato viruses in a persistent manner (Green, 1991), and as such they transmit geminiviruses efficiently from one host to another, tomato included. It is known that vectors spread viruses from one infected host to another especially due to their transient feeding behaviour. Movement of vectors depends on host range and presence, as well as vector host preference and life history. Doncaster (1943) observed that vectors actively fly from one plant to another in still air, and are less active over long distances when blown by wind, but could still be active without wind, provided wings continue to beat (Thresh, personal communication). Changes in cropping systems and weeding patterns affect vector populations and virus transmission, as has been the case for Tomato spotted wilt virus (TSWV) in Hawaii (Gonslaves and Providenti, 1989). According to Raccah (1986), presence of inoculum is an essential factor in virus transmission. Therefore, field environmental factors and insect pest population dynamics should be studied if one is to understand the relationship between transmitted virus and vector. Raccah (1986) monitored spread of viral infection in space and time by measuring the distance between old and new infections in relation to time interval between detection of first symptom and subsequent symptoms. At each stage of disease spread, the number of plants infected was recorded to develop temporal and spatial patterns of disease-spread curves. Disease spread in space was calculated using an equation developed by Allen (Plumb and Thresh, 1983), in which the probability of a new infection to occur at a distance x from the source was deduced by: Px = 1-exp (-x/x¹) (1), 32
Incidence, distribution and characteristics of major tomato leaf curl and mosaic virus diseases whereby x is distance from source of infection; P is the probability, and exp is the exponential factor. Earlier Vanderplank (1963), determined virus spread with time by: dN/dt = KN (Nmax – N) (2), whereby N is number of plants infected; t is the time; dN is the difference between number of plants infected at a particular time and another; dt is the difference in time; K is a constant factor; and Nmax is the maximum number of plants infected. Plumb and Thresh (1983) and Raccah (1986) also studied virus spread in time and space in relation to prevailing weather conditions. They found that there was direct influence of weather conditions on the rate at which viruses spread. According to http://www.apsnet.org (2003), if disease progress is a monocyclic epidemic, and is linear, the slope of the disease progress curve is constant. Furthermore, disease progress in a monocyclic epidemic is proportional to the amount of initial inoculum. We can calculate the slope of the disease progress curve, and describe a monocyclic epidemic with linear disease progress curves using the differential equation: dx/dt = QR (3), whereby dx is an infinitesimally small increment in disease severity; dt is an infinitesimally small time step; Q is the amount of initial inoculum; and R is a proportionality constant that represents the rate of disease progress per unit of inoculum. Since Q and R are both constant during the course of an epidemic, the slope, dx/dt, is constant, and disease progress is linear. R has a value that represents the "average" for the whole epidemic, a value that depends on many factors such as aggressiveness of pathogen, host susceptibility, environmental conditions, etc. 33
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<strong>Incidence</strong>, distribution <strong>and</strong> characteristics <strong>of</strong> major tomato leaf curl <strong>and</strong> mosaic virus diseases<br />
whereby x is distance from source <strong>of</strong> infection; P is the probability, <strong>and</strong> exp is the<br />
exponential factor. Earlier V<strong>and</strong>erplank (1963), determined virus spread with time by:<br />
dN/dt = KN (Nmax – N) (2),<br />
whereby N is number <strong>of</strong> plants infected; t is the time; dN is the difference between<br />
number <strong>of</strong> plants infected at a particular time <strong>and</strong> another; dt is the difference in time; K<br />
is a constant factor; <strong>and</strong> Nmax is the maximum number <strong>of</strong> plants infected.<br />
Plumb <strong>and</strong> Thresh (1983) <strong>and</strong> Raccah (1986) also studied virus spread in time <strong>and</strong> space<br />
in relation to prevailing weather conditions. They found that there was direct influence<br />
<strong>of</strong> weather conditions on the rate at which viruses spread.<br />
According to http://www.apsnet.org (2003), if disease progress is a monocyclic epidemic,<br />
<strong>and</strong> is linear, the slope <strong>of</strong> the disease progress curve is constant. Furthermore, disease<br />
progress in a monocyclic epidemic is proportional to the amount <strong>of</strong> initial inoculum. We<br />
can calculate the slope <strong>of</strong> the disease progress curve, <strong>and</strong> describe a monocyclic epidemic<br />
with linear disease progress curves using the differential equation:<br />
dx/dt = QR (3),<br />
whereby dx is an infinitesimally small increment in disease severity; dt is an<br />
infinitesimally small time step; Q is the amount <strong>of</strong> initial inoculum; <strong>and</strong> R is a<br />
proportionality constant that represents the rate <strong>of</strong> disease progress per unit <strong>of</strong> inoculum.<br />
Since Q <strong>and</strong> R are both constant during the course <strong>of</strong> an epidemic, the slope, dx/dt, is<br />
constant, <strong>and</strong> disease progress is linear. R has a value that represents the "average" for the<br />
whole epidemic, a value that depends on many factors such as aggressiveness <strong>of</strong><br />
pathogen, host susceptibility, environmental conditions, etc.<br />
33