Predictive yields for small-scale staple crop production in North Central States using common homestead equipment and minimal inputs.

Commodities

• Agronomic: barley, buckwheat, corn, millet, oats, potatoes, rye, sorghum (milo), soybeans, sunflower, triticale, wheat, amaranth
• Vegetables: beans

Practices

• Natural Resources/Environment: biodiversity

In a time of COVID and escalating social turmoil, strengthening food security at the personal and local level is a priority for many families and communities. This includes growing heritage grains and cereals (barley, wheat, rye, maize) and other previously underrepresented staple crops (amaranth, millet, milo, oats, sunflowers, triticale) on small-scale plots. As a result of our focus, Great Lakes Staple Seeds regularly receives questions regarding the cultivation of these crops. Yield and cultivar questions are frequent - “How much [wheat] will I get if I plant [plot size]?” or similarly, “How much [triticale] do I need to plant to feed my chickens?” "Am I better off planting hulled or hull-less [oats]?" "My summers are getting drier, what should I grow?" To most accurately answer these small-scale producer questions, agronomic data more aligned to the methods and cultivars of pre-1950s industrial cultivation that accounts for modern shifts in weather patterns is essential. Currently most agronomic data available focuses on large-scale, industrialized cultivation that uses predictive growth behavior models reliant on historic weather patterns. This is not easily relevant for or applicable to the manual labor, minimal input cultivation methods employed by an increasing number of North Central small-scale producers.

Solution (500 words): 

Staple crops commonly available to North Central small-scale producers will be field grown, harvested, and processed on my southeast Michigan homestead to generate and analyze relevent agronomic data to better enable growers to more confidently and successfully meet their goal of strengthening their personal or community food security; these crops are: amaranth, barley, beans, buckwheat, maize, millet, milo, oats, potatoes, rye, sunflower, triticale, and wheat. Data collection will consist of samples that span designated staked 10 ft strips within each cultivar's plot. A target of one hundred sample groups per growing season with a minimum of three replications per cultivar will account for differences across crop types and include factors such as grain type, growth habit, and use. Final cultivar selection will consider:

• amaranth: 1 grain cultivar
• barley: hulled vs. hull-less; 2-rowed vs. 6-rowed; spring vs. winter
• beans: common bean for dry use; soybean for oil production; soybean for protein content (tofu)
• buckwheat: 1 grain cultivar
• maize: short season; flint; dent
• millet: 1 grain cultivar
• milo: 1 grain cultivar
• oats: hulled vs. hull-less
• potatoes: 2 cultivars
• rye: 1 cultivar (rye is wind-pollinated and fall-planted so can only grow one cultivar)
• sunflower: 1 oilseed cultivar
• triticale: 2 cultivars
• wheat: spring vs. winter; market class

Much like pre-industrial agricultural times, crops will be grown with sustainable, ecologically responsible cultivation methods. This includes the reliance on manual labor using common equipment (primarily hand tools and occasionally a small-scale tractor) and minimal off-farm inputs (no chemical fertilizers, pesticides, or herbicides.)

Plant metrics will be measured, recorded, and analyzed to inform crop-specific assessments including yields. In addition to crop data, relevant weather information, labor metrics, and cultivation notes will be recorded for agronomic and comparitive analysis. 

Results generated will inform our outreach materials designed to provide cultivation guidance to small-scale growers and to address frequently received relevant questions.

Objectives:

1. During the growing season:
   1. Maintain trial strips within field plots for data collection and for demonstrations and progress updates
   2. Document crop growth (sowing time, maturity progression, harvest) with notes and photos
   3. Document amount, type, and duration of work performed per plot
   4. Document growing conditions (weather, predation events, inputs, and other relevancies)
2. During the duration of the grant:
   1. Share status reports via social media, live in-field webinars, outreach presentations (live, virtual)
   2. Present at a regional conference (2 trips total)
3. Post-harvest:
   1. Processing of grains/seeds and final metric measuring
   2. Aggregation of input/output data into master spreadsheet (plot level and test strip results)
   3. Analysis of data using ANOVA to determine which factors are statistically significant for yield/sq ft and energy/yield
   4. Generate tables, charts and plots to explain the numerical results
   5. Update human calorie model to estimate sq ft of each crop to supply relevant portion of calories
   6. Share findings through social media and conferences
   7. Create and share outreach materials (bulletins, videos, presentations) targeted to small-scale growers, both generalized and crop specific