Farm Database Brainstorming, w. Prof. Wahls and Prof. Ciarocca, 2/2/10
GOALS:
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Facilitate collection of organized records for comparison and farm improvement over time
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Collect information in a format useful for future research or academic projects, including GIS
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Provide a practical learning experience for students in the CS database course
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Dining hall o Date, item (crop), description, quantity, price, account code o Template creates invoice to print o Template simultaneously populates overall sales database and dining hall database o Similar template option for other accounts (occasional restaurant sales)
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Farmers’ market o Template creates sales record sheet:
 Crop, quantity, date, price per item
 User updates sales sheet after market to note items sold o Template populates sales databases for market and overall sales
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CSA distribution record o Template populates CSA record database and sales database
 Crop, quantity, date o Template info also “activates” relevant CSA recipe list?
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Donation record to Project SHARE: crop, quantity, date o Template populates donation database and “sales” database
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Could sales databases be aligned to eliminate need for harvest template? -Probably best to keep separate-
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Daily harvest template: o Date, Crop, field & bed info, planting code, variety, quantity, row feet harvested o Populates harvest records database o Allows cumulative “yield per row foot” data over time o Allows comparison of yield data between field & bed, depending on treatments… soil fertility, tillage, variety, planting date, spray record,etc.
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Member name, share size, pickup day, splits share with, contact info o Template above generates CSA membership record, weekly check-in sheets, CSA contact email list o Payment record: amount pledged, payments, dates, check number, balance

all of the following hypothetical tables are related… if all tables could communicate in one global fertility database that would be fantastic
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Soil test info, by field and date, several chemical parameters
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Soil amendments, by field, bed, date, amendment, quantity, method of application
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Compost application, by field, bed, date, compost pile ID, quantity applied o Compost info could be entered as either tons/acre or as raw data… tractor, gear, spreader setting… these variables relate to quantity applied per acre probably best to keep it simple… o Compost info could be correlated to compost test results, grouped by compost pile ID and test results for various parameters… very nifty if use of specific pile ID in “application” input template could populate the soil fertility database with pounds of each nutrient added… o Compost test records, by pile ID, date, various nutrient parameters
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Cover crop info, by field, bed, date o Date seeded, seeding method, seeding rate, method of seed incorporation o Date mowed, date green material incorporated to soil, method of incorporation o Approximate tons per acre fresh matter at incorporation o Approximate nutrient credit for leguminous crops
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Fertigation info o Field, bed, crop, date, material, quantity applied, nutrient content
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Crop tissue analysis info o Field, bed, crop, date, nutrient report parameters
a simple database that is populated by a template with field, bed, date, tillage tool, number of passes, comments
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Spray log database o Date, field, bed, crop, control agent(s), target pathogen, sprayer operator, gallons of water, quantity of control agent, tractor, gear/pto speed, tank pressure, weather data (relative humidity, temp, rain, wind… this could be gleaned from weather station at farm?)
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Pest and disease scouting records: o Date, field, bed, crop, pest/ disease ID, number of crop plants scouted, number of pest individuals sited/ percent infested (disease), growth stage of pest/disease, comments, signs of effective control
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Biocontrol records: o Released biocontrol agents: species, pest targeted, crop, date, field, bed o Sighting of native biocontrol agents: species, date, crop, field, bed

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Overhead irrigation log: o Pump ID, run time, pressure, field, beds, pipe ID, comments. Pipe ID correlates to recorded
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 calibration data for average gallons per minute of flow o Fuel/ oil use record
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Drip irrigation log: o Pump ID, run time, pressure, field, beds, field length (linked to GIS data record table?) number of tapes run o Fuel/ oil use record, same as above
Rainfall log: Date, inches of rainfall from gauge
Soil moisture data?: date, field, bed, crop, mulch type, sample depth, moisture data
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Transplant log o Planting code, crop, variety , seeding date, propagation date, flat size , number of trays planted or number of seeds planted, date transplanted to field, location info: field, bed., spacing, transplanter comments, general comments, row feet per planting…. This log requires further goal setting and thought to get it right o Info from transplant log will prove useful in future seeding calendar planning and adjustments
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Seeding log o Planting code, crop, variety, seeding date, seeder hole size, number of row feet planted, comments, field and bed info
General thoughts and aspirations…
If various databases can be cross referenced using spatial or temporal data common between them, this would make for some nifty comparisons. For example, planting logs create “planting code” which correlates with seeding date. This can be compared with harvest date and yield data. These can further be compared with fertility, pest control, and irrigation data, allowing us to make suppositions regarding what practices work to benefit greater yield….