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Remote-sensing study of alfalfa aims to predict bloom

Managing bee incubation in step with bloom has been done largely based on growers’ longtime knowledge

By Brad Carlson

Capital Press

Published on October 12, 2018 9:01AM

Last changed on October 12, 2018 1:01PM

Boise State University graduate student Thomas Van Der Weide with remote sensing equipment he designed and built.

Courtesy of Anand Roopsind

Boise State University graduate student Thomas Van Der Weide with remote sensing equipment he designed and built.

Nancy Glenn, Boise State University geosciences professor.

Boise State University

Nancy Glenn, Boise State University geosciences professor.

The best alfalfa seed production occurs when pollinating bees can work on the crop as it approaches, and then reaches, full bloom.

Predicting peak bloom and getting the alfalfa leafcutter bees ready to go at the right time pose problems that producers traditionally solved — successfully, for the most part — with hand-me-down or otherwise shared knowledge.

A field study underway in southwest Idaho aims to take out some of this guesswork by remotely sensing weather and field conditions, and in turn alfalfa plant and seed progress, so peak bloom can be predicted more effectively. Boise State University, the Nampa operations of S&W Seed Co. and research firm Kairosys are participating. Funding includes a $194,000 Idaho Global Entrepreneurial Mission grant through the state Department of Commerce and a $51,000 match from Kairosys.

Best yields occur when bees can pollinate alfalfa flowers when the crop is at peak bloom, Boise State University Geosciences Professor Nancy Glenn said.

“It is challenging to predict when bloom is going to be because of environmental conditions,” she said. Soil and weather variables, and growers’ irrigation decisions can make prediction difficult.

“And growers actually have to cultivate leafcutter bees with the timing of the bloom in mind,” Glenn said. “They want alfalfa to be at peak bloom when the leafcutter bees are mature enough to pollinate.”

Traditionally, growers aimed to release bees when fields were at around 50 percent active bloom, said Brad Chambers, North American production manager with S&W.

“At that point, if you release bees, bloom is progressing every day,” he said. “In the next week or two, they will just continue to bloom. That initial release of bees is important. You want the bees to have food and forage.”

Releasing bees based on the percentage of the field that is in active bloom is a balancing act, he said.

“Any less than the ideal (bloom percentage) and the bees may travel — leave the field,” he said. But if the grower waits until too far into the bloom, “the bees may not catch up, which hurts seed yield on the other end. Plants start dropping flowers, and bees can’t get to them in time.”

Managing bee incubation in step with bloom has been done largely based on growers’ longtime knowledge, and familiarity with the weather calendar, Chambers said.

“The alfalfa industry is successful. Growers do hit that mark,” he said. But growers and seed companies would like to see more consistency in yields, he said.

Tapping technology can help growers replace guesswork with data on temperatures and other environmental conditions, and even the plants’ progress, Chambers said.

In the study, satellites and field-installed sensors collect and track data comprising a fingerprint-like “spectral signature” — which changes over time, and ideally tells observers how plants are progressing and when bloom will gear up, Glenn said.

In a spectral signature, “the alfalfa bloom looks different than the alfalfa green leaves,” she said. “So we can use that difference to find the alfalfa bloom.”

Real-time data can be converted to images showing differences in bloom stage. Remote sensing equipment was placed in two fields this year. Satellites gather images from as many as 30 fields.

Ideally, data and imagery can inform a model that helps predict peak alfalfa bloom and thus help producers cultivate Leafcutter bees to take best advantage, ultimately boosting yield, Glenn said. Remote sensing also may be able to highlight underperforming parts of fields.

A preceding study focused on growing degree-day tracking, with data accessed via smartphone, to help bee producers predict and to an extent control when the insects will hatch — by varying incubation temperature as conditions dictate, or even making up for time lost to bad weather or pesticide application, for example.

Combining the bee-incubation data and application with findings from the current study on remotely sensing alfalfa bloom could help producers release leafcutter bees at a more ideal stage, like when 60 to 80 percent of the crop has bloomed, said Ron Bitner, a Caldwell-based bee scientist who consults for S&W Seed. Choosing the right time to release bees — typically within a two- to three-week period in June, keeping in mind the bees will fly four to six weeks — would be a more data-driven process.

“The premise is that remote-sensing data can be used to track alfalfa bloom progress,” Glenn said. “And from that we can build a model that can predict when bloom will happen.”

Data and images show how green the plants are, and how they progress over time based on conditions and location.

“We think what we are doing here can be transferred to other pollinator crops to improve yield efficiency,” Glenn said.


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