98th ESA Annual Meeting (August 4 -- 9, 2013)

COS 30-4 - Perennial possibilities: a theory for yield differences between annual and perennial grains

Tuesday, August 6, 2013: 9:00 AM
L100J, Minneapolis Convention Center
Richard Barnes, Ecology, Evolution, and Behavior, University of Minnesota, Saint Paul, MN, Clarence Lehman, College of Biological Sciences, University of Minnesota, St. Paul, MN, Michael Kantar, Department of Agronomy and Plant Genetics, University of Minnesota, St. Paul, MN, Lee DeHaan, Land Institute, Salina, KS and Donald Wyse, Department of Agronomy and Plant Genetics, University of Minnesota, Saint Paul, MN
Background/Question/Methods

Agricultural production has increased greatly over the past century, but gains have often come at the cost of long-term sustainability. Crop systems often require fossil fuel-based fertilizers, strain sources of fresh water, contribute to soil loss, and may ultimately reduce arable land. Addressing these shortfalls is essential for future food production, especially in the face of an increasing global population. Perennial crops offer a possible alternative to the annuals upon which current agriculture systems are based. They sequester nutrients and may reduce both soil erosion and the need for tilling. Additionally, because perennial grains have reduced input costs, they may equal the profitability of an annual grain even while producing lower yields.

However, despite their potential, relatively little theoretical research has been done on high-yielding perennial grains. This may be partly because they have not been found in nature. But it may also be a consequence of theories which predict mutually exclusive trade-offs between longevity and seed production. Whatever the case, the controlled conditions of an agriculture system present a novel selective regime which can be studied in its own right and exploited to develop life cycle strategies not possible elsewhere.

Results/Conclusions

Accordingly, we have developed a physiological model of resource allocation within a grain species. The allocation functions themselves are mutable. This permits virtual breeding of modeled grains in order to explore the model's "gene space" and to locate optimal plants for a given set of harvest conditions.

The model is observed to rapidly produce both annual and perennial solutions following a random initialization. Both annuals and perennials may be bred to produce a perennial or annual, respectively. Perennial seed production in the model has been observed to equal or surpass that of annuals under some conditions. Insofar as the model is representative of reality, the implication is that high-yielding perennial grains may be bred in the real world, and that they may offer a competitive alternative to annuals.