Vince Jones at Washington State University is testing the new Z-Trap, which zaps insects and records when they were trapped. It might be possible to remotely identify the type of insect, also.

Vince Jones at Washington State University is testing the new Z-Trap, which zaps insects and records when they were trapped. It might be possible to remotely identify the type of insect, also.

The key to integrated pest management is monitoring—knowing what is going on in your orchard.

“Monitoring is very, very expensive. It takes time and manpower, and it has to be accurate,” says Dr. Larry Hull, Penn State University entomologist.

He explained that he and a team of seven collaborators from across the United States are working on a ­project to make monitoring more efficient and less costly.

Imagine a sex pheromone-baited monitoring trap that would detect the first codling moth of the season—not by catching it in a sticky trap but by detecting it electronically and then sending the information directly to your computer.

Hull, speaking at the Mid-Atlantic Fruit and Vegetable Convention in Hershey, Pennsylvania, described his team’s efforts over the last three years to perfect just such a device, not just for codling moth but also for oriental fruit moth and various species of leafrollers.

Currently, he said, growers need to check pheromone traps every day early in the season to detect first moth flight and establish the biofix, which sets the start of the whole weather-based schedule of insect development (initiating and calculating the cumulative number of insect degree-days). Then they need to check traps at least weekly to confirm that insect populations are being suppressed by the tools they use for control.


The team developed its first prototypes late in 2008 and tested them in orchards in 2009. One prototype was based on an array of infrared sensors in a basic plastic bucket trap baited with a sex pheromone lure. The magnitude of the signal detected by the infrared sensors is correlated with the size of the insect entering the trap, providing evidence to help identify the species of insect.  Another prototype tested in 2010 was a “zapper trap,” called the “Z-Trap,” which is baited with pheromone and equipped with a metallic coil that not only detects when an insect enters, but also stuns the moth with an electric charge and captures the stunned moth at the base of the trap. Using its real-time clock chip, the Z-Trap not only detects the event, but records the time of the event as well.  Also, the amount of electric current discharged by the Z-Trap when a moth touches the coil may help ­identify the species of insect.

In an amusing talk, Hull described some of the joys and frustrations of conducting this research. The Z-Trap, cranked up to 2,000 volts, makes quite an explosive show when a moth hits it. It is used at about 700 volts to stun rather than incinerate the insect. The initial prototype worked well—but required 15 changes of AA batteries over the season. “There was not much time savings there,” he said. The improved prototype in 2010 used six D batteries and lasted for 140 days when operated for the five to six hours per day that the moths are active.

Hull hopes growers will have such detectors available within the next two years. His team’s work plans for 2011 include redesigning the Z-Trap and ­modifying the infrared traps to increase capture rates, possibly incorporating the two systems into a single trap. The researchers want to further analyze the electronic signals ­generated by the Z-Trap, which may help  them identify ­target and nontarget species.

In addition, they want to develop a user interface that works with wireless communication and automatically displays trap location, insect detection frequency by trap, and makes graphs showing the rate of cumulative insect detections.


In a separate monitoring project, Hull and other researchers at Penn State, Purdue University, and Carnegie Mellon University are developing camera technology that can be mounted on an Automated Prime Mover—a robotic vehicle that can autonomously drive in fruit orchards—to detect fruit injury caused by internal ­feeding insects.

The idea is for this unmanned vehicle to travel the orchard, photographing apples and detecting those that are damaged. The researchers collected 2,800 apple images in 2009 and 6,000 in 2010 and created a database of what healthy and injured apples look like.

“We can detect the damage caused by codling moth and oriental fruit moth,” Hull said. “It goes relatively fast, and right now we are getting about 5 percent false positives. We want to reduce that further with additional research.”

Collaborators on the project are Dr. Johnny Park, German Holguin, and Guiqin Li at Purdue University; Dr. Henry Mederios, Spensa Technologies; Dr. Vince Jones and  Teah Smith, Washington State University; and Dr. Hull and Brian Lehman at Penn State University.

The large CASC (Comprehensive Automation for Specialty Crops) Project is funded by the USDA Specialty Crops Research Initiative program. The institutions conducting research under the project include Carnegie Mellon University, Penn State University, Purdue University, Oregon State University, Washington State University, and USDA. The Washington Tree Fruit Research Commission also provided funding for the development of the Z-Trap.