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PITTSBURG —
It seems like a long time ago, but while I was an undergraduate student at Kansas State University, I worked for the Soybean Breeding Project. At that time, I helped with a graduate student using hydroponics (the process of growing plants without soil, either in sand, gravel, or liquid, along with added nutrients) to screen soybean lines. In what I thought was a very high tech approach, he used the hydroponic system he set up to control the pH and select the soybean lines which were more tolerant to higher pH’s. However, Dr. Bill Schapaugh, Kansas State University Soybean Breeder, and Dr. Kevin Price, Kansas State University Professor in Agronomy and Geography have taken high tech soybean breeding to a whole new level.
Plant breeding is an incredibly long process, often taking eight to ten years to release a variety. In an effort to increase efficiency, Drs. Schapaugh and Price have started using spectral analysis to screen soybean lines with financial support coming from the Kansas Soybean Commission. Spectral analysis is one way to measure the photosynthetic activity of plants by essentially, measuring the amount of chlorophyll in the plant. Their efforts the last few years have been to match the readings that they take from the spectral analysis to actual yield data.
How did they match the data? They developed a training population made up of lines which they knew had a wide range of yield potentials. Of course this gave them a good range of actual yields along with varying readings from their spectral analysis. Brent Christiansen, a graduate student working on this project with them, developed one of the models they are using to test the efficacy of the readings. After plotting these on a line graph, the data showed a remarkable relationship between the spectral readings and the actual yield observed. I should point out that the data was not perfect, but that was not expected in this type of research. It did not predict the yield 100 percent accurately, but it was incredibly close.
So what does this mean? The traditional method would be to plant all of the possible lines in very small plots in research fields and select the higher yielding ones from those plantings. This takes massive amounts of time and space and even funding. With this new technique, they would screen all of the lines with spectral analysis, and only plant those lines which show a potential for high yield in the plots, essentially streamlining the breeding process.
It may not make the script of a sci-fi movie any time soon, but the K-State Soybean Breeding Project is using a pretty advanced technological approach to improving soybean lines. The process has not been limited to just soybeans though. Dr. Jesse Poland, a USDA-ARS wheat geneticist is trying to apply this to wheat research. Hopefully, mid-western farmers will be able to reap the benefits from this novel system.
If you have any questions, please feel free to call me at the office (620) 724-8233 or e-mail me at jcoltrain@ksu.edu.
It seems like a long time ago, but while I was an undergraduate student at Kansas State University, I worked for the Soybean Breeding Project. At that time, I helped with a graduate student using hydroponics (the process of growing plants without soil, either in sand, gravel, or liquid, along with added nutrients) to screen soybean lines. In what I thought was a very high tech approach, he used the hydroponic system he set up to control the pH and select the soybean lines which were more tolerant to higher pH’s. However, Dr. Bill Schapaugh, Kansas State University Soybean Breeder, and Dr. Kevin Price, Kansas State University Professor in Agronomy and Geography have taken high tech soybean breeding to a whole new level.
Plant breeding is an incredibly long process, often taking eight to ten years to release a variety. In an effort to increase efficiency, Drs. Schapaugh and Price have started using spectral analysis to screen soybean lines with financial support coming from the Kansas Soybean Commission. Spectral analysis is one way to measure the photosynthetic activity of plants by essentially, measuring the amount of chlorophyll in the plant. Their efforts the last few years have been to match the readings that they take from the spectral analysis to actual yield data.
How did they match the data? They developed a training population made up of lines which they knew had a wide range of yield potentials. Of course this gave them a good range of actual yields along with varying readings from their spectral analysis. Brent Christiansen, a graduate student working on this project with them, developed one of the models they are using to test the efficacy of the readings. After plotting these on a line graph, the data showed a remarkable relationship between the spectral readings and the actual yield observed. I should point out that the data was not perfect, but that was not expected in this type of research. It did not predict the yield 100 percent accurately, but it was incredibly close.
So what does this mean? The traditional method would be to plant all of the possible lines in very small plots in research fields and select the higher yielding ones from those plantings. This takes massive amounts of time and space and even funding. With this new technique, they would screen all of the lines with spectral analysis, and only plant those lines which show a potential for high yield in the plots, essentially streamlining the breeding process.
It may not make the script of a sci-fi movie any time soon, but the K-State Soybean Breeding Project is using a pretty advanced technological approach to improving soybean lines. The process has not been limited to just soybeans though. Dr. Jesse Poland, a USDA-ARS wheat geneticist is trying to apply this to wheat research. Hopefully, mid-western farmers will be able to reap the benefits from this novel system.
If you have any questions, please feel free to call me at the office (620) 724-8233 or e-mail me at jcoltrain@ksu.edu.
