Implementation of the MARYBLYT 

 Model for Fire Blight Control 



Roberta Spitko 



New England Fruit Consultants 



Fire blight, caused by the bacterium Erwinia 

 amylovora, is one of the most destructive and diffi- 

 cult to manage diseases encountered by tree fruit 

 growers throughout the world. Some might argue 

 that apple scab, caused by Venturia inaequalis, 

 deserves this honor but with respect to apple scab, 

 there is always next year and the chance to try again. 

 A severe epidemic of fire blight can damage an 

 orchard of susceptible apple or pear trees so severely 

 that there is no next year; that is, the orchard block 

 must be removed. 



New England Fruit Consultants (NEFCON) 

 has been observing and studying this disease in 

 Massachusetts, Vermont, and New Hampshire for 

 more than a decade. Overall knowledge of this 

 disease has increased significantly since the early 

 1980s, much as a restilt of the excellent work of Dr. 

 Paul Steiner and his colleagues as the University of 

 Maryland. Their development of the MARYBLYT 

 computer model to aid in the control decision making 

 process is enabling us to understand disease devel- 

 opment better and to fine tune our disease control 

 strategies. It is not our intention to describe in detail 

 the epidemiology of fire blight as there are many 

 excellent sources already available (see U.S.D.A. 

 Bulletin No. 631, Fire Blight- Its Nature, Prevention 

 and Control). Our purpose is to describe our suc- 

 cesses and frustrations regarding control, particu- 

 larly with regard to the MARYBLYT model. 



NEFCON has been working with Dr. Steiner 

 and Dr. Daniel Cooley at the University of Massa- 

 chusetts since the mid-1980s as the fire blight model 

 was being developed. We found that it described 

 disease development accurately as we had observed 

 it but we did not attempt to use it as a control 

 strategy at that point. In the past several years as 

 the model has become commercially available, we 

 incorporated it fully into our fire blight management 

 program. In 1992, we implemented the model in 

 multiple sites in Massachusetts, New Hampshire, 

 and Vermont. Our findings are as follows: 



1. The model predicts with extreme accuracy when 

 overwintering canker activity will begin as well as 

 when symptoms of canker blight, blossom blight, 



shoot blight, and trauma bUght will occur. This 

 prediction facilitates detection and removal of 

 blighted tissues if possible (numerous infections are 

 probably best left for winter removal). 



2. If bloom phenology and meteorological data are 

 kept judiciously, and Streptomycin sprays are used 

 when the model predicts the risk for blossom blight 

 is high or blossom infection has occurred, problem 

 sites may be cleaned up, or major outbreaks of 

 blossom blight in new sites may be avoided. 



3. Although keeping track of bloom and weather 

 data may appear simple, it is important that these be 

 extremely accurate as the model's predictions can 

 only be as accurate as the human input allows it to 

 be. In our experience, we found detailing bloom to be 

 difficult. Most orchards have many different culti- 

 vars blooming at different times; an entire bloom 

 period may be several weeks long. Also, many 

 cultivars which are highly susceptible to fire blight 

 produce secondary blossoms (Paula Red, Rome, and 

 Cortland, as well as many kinds of pears). It is 

 possible to have 1/2-inch fruits and open blossoms in 

 the same fruit cluster. It has been our experience 

 that this route is a very common one by which severe 

 epidemics become established. Growers must keep 

 an eye out for these late blossoms in problem areas 

 and be prepared to spray Streptomycin should 

 weather conditions favor infection. 



With respect to weather data, daily maximum 

 and minimum temperatures must be entered. An- 

 other very important input is wettings, however 

 slight they may seem. In several sites in 1992, the 

 model did not predict blossom blight epidemics 

 which occurred. When we revised the data to reflect 

 dews which likely happened due to extreme tem- 

 perature drop at night during bloom, the model 

 accurately predicted that infection of the blossoms 

 had occurred and when symptoms would be visible. 



4. With prolonged bloom periods and weather par- 

 ticularly favorable to fire blight, the model MAY call 

 for more Streptomycin sprays than should be ap- 

 plied considering Streptomycin resistance manage- 



Fruit Notes, Spring, 1993 



15 



