Eric & Joanna Reuter Chert Hollow Farm, LLC January 16, 2012.

Eric & Joanna Reuter

Chert Hollow Farm, LLC

Assessing the Economics of Crop Choices on a Start-up Market Farm

January 16, 2012

Brief farm overview

#$

Chert Hollow Farm, LLC

Columbia Farmers Market

Customer counts up to ~4,000 (Saturday morning)

80+ vendorsFarm also sells to

restaurantsIn 2012 farm converts

to CSA

Farm founded in 2007Certified-organic produce

since 2009

Diversification/on-farm fertility

Intensive vegetable production in permanent, no-till beds, >1 crop/year

Two vegetable growing areas, ~1.5 acres total, space limited

Geologists/natural scientists by trainingThink on long time scalesData orientedFocus on soil health & ecologyRespect for the complexity of the ecosystem

processes that provide the context of our farming

Eric: Full-time farmer since 2007

Joanna: Full-time farmer since 2009Employees: part time, paid in product

Our background & perspective

Crop profitability assessmentAcknowledgment of Wiswall’s approach

An excellent resource with methods to assess crop profitability (& much more):

• Crop enterprise budgets account for cost of:• Labor• Machinery• Input/products• Overhead• & more

An excellent resource with methods to assess crop profitability (& much more):

• However:• Assumes extensive

& detailed records that a new farm may not yet have

• Even an established farm may not have full detail of records desired, especially for time budgets

Crop income comparison modelOur approach

Simplified version of reality

Captures key features, leaves out some details

Useful in planning

What is a model?

Goal: To analyze and explore the economics of crop choices in a relative

context for use as an aid in crop planning

What it will look like: A spreadsheet listing crops with data and calculations that capture the

essence of crop income considerations for a farm

To derive calculations, start simple and add improvements: Estimate gross income potential Account for the fact that not all of the harvested crop is likely to sell Account for expenses of producing specific crops, ignoring overhead Account for growing time (quick vs. long-season crops)

Data sources: For best results, use on-farm data for yield, price, and other factors For new crops, or if records are incomplete, use published data and/or

estimates

Crop income comparison model

Simple crop income assessment:

Yield data sources

Knott’s Handbook for Vegetable Growers (Maynard & Hochmuth, 2007, 5th ed.)

Commercial production data for diverse vegetables

Johnny’s Selected Seeds catalog Commercial/market data for veggies

How to Grow More Vegetables (Jeavons, 2007, 7th ed.)

High-end yields assuming intensive production, lots of compost

Midwest Vegetable Production Guide for Commercial Growers, http://www.btny.purdue.edu/Pubs/ID/ID-56/

Small set of regionally appropriate yields; cringe-inducingly non-organic

Online searches

[units] are in brackets

gross income potential [$] area [area]

marketable yield [weight] area [area]

= price [$]__ yield [weight]

*

Use published data to assess potential new crops

Price data sources

Other vendors at market Don’t forget that these may include sales tax

Grocery store prices Available any time

USDA Agricultural Marketing Service: http://www.marketnews.usda.gov/portal/fv

Wholesale prices, tend to be very low; available past & present

Use published data to assess potential new crops

[units] are in brackets

Simple crop income assessment:




*

Crop type Yield, in pounds per 100 ft2 (Knott’s average)

Price, in $ per pound (~market rate)

Gross income potential, in $ per 100 ft2

Summer squash 37 $2.25 $83

Tomato 66 $2.75 $182

Sweet corn 25 $0.85 $21

Radish 21 $5.50 $116

Pea 9 $7.50 $68

Crop comparison examplegross income potential [$] area [area]



*

Account for the fact that not all of the harvested crop is likely to sell

Of the marketable crop that makes it as far as the packing shed, how much is actually sold?

Define the sales factor as the percentage of marketable crop that is sold

sales factor (%)

marketable yield [wt] area [area]

= price [$]_ yield [wt]

*expected gross income [$] area [area]

*




*

Started with:

Incorporate sales factor:

This number may be hard to pin down for many crops, as it may vary considerably over time, but its presence is a reminder that income projections should not be based on total harvestable yield.

Dependent on: Storage characteristics of item

Okra = highly perishable, sell ASAP or lose Garlic = highly storable, sell over period of months

Supply; the quantity ... ...that we offer (more or less predictable/controllable) ...that competitors offer (more of a wildcard) ...that the food system offers (example: hardneck garlic)

How item is displayed/offered for sale Bundles vs. bulk Often hard to sell out 100% because of small-stand syndrome

Demand Customer preferences/whims; food fads Edamame...chef told us he was “moving beyond the Japanese food craze”

Sales factor: % of crop sold

Crop comparison examplesales factor (%)


= price [$]_ yield [wt]

*expected gross income [$] area [area]

*

Crop type Yield, in pounds per 100 ft2 (Knott’s average)



Sales factor(estimate)

Expected gross income, in $ per 100 ft2

Summer squash

37 $2.25 $83 75% $62

Tomato 66 $2.75 $182 75% $136

Sweet corn 25 $0.85 $21 95% $20

Radish 21 $5.50 $116 80% $92

Pea 9 $7.50 $68 95% $64

This is just gross.

What about net?

To make crop choices, do not necessarily need to know true net

Ignore overhead expensesIgnore “base” crop expenses—expenses that are

more or less similar for every crop and thus cancel out when considering relative crop profitability

net income gross income

expenses= -

Farm expenses

Overhead

expenses

Expenses that are necessary to the overall operation of the farm,

but cannot be allocated to a specific crop

Market fees & expenses

Management/accounting

Utilities

Advertising/website

Base crop

expenses

Expenses that benefit several consecutive crops or are necessary for the farm function as a whole

Fertility amendments

Weeding

Expenses that are similar for all crops (& thus

cancel out when considering relative crop

profitability)

Bed preparation

Irrigation infrastructure

Crop-specific expense

s

Expenses that are incurred in association with one specific crop

Transplants (greenhouse

expenses, etc.)Trellising (twine,

labor)

Row cover

Harvest, washing, & packing

Classifying expenses Examples

Only need crop-specific expenses for relative crop income assessment

Classification of crop expenses may vary among farms

Classification of crop-specific expenses may vary among farms Is the cost different enough between different

crops to be worth accounting for in detail?Subdivide labor expenses from other

expenses (products/inputs)Estimate as needed for time budgets

Our independent estimates were very close to each other for the five example crops

Classifying expenses

net income

expected gross income [$] area [area]

sales factor (%)


=

price [$]_ yield [wt]

* * -

relative crop income [$] area [area]

crop-specific expenses [$] area [area]

=relative crop income [$] area [area]

- crop-specific expenses [$] area [area]

An important equation, but not the subject of this presentation:

Instead, use this:

Substitute previously derived equation for expected gross income/area:

Normalize by area:

gross income

expenses= -

relative crop income

gross income

crop-specific expenses= -

Crop comparison example

sales factor (%)


=

price [$]_ yield [wt]

* * -

relative crop income [$] area [area]

crop-specific expenses [$] area [area]

REINSERT TABLE HERECrop type

Yield, in pounds per 100 ft2 (Knott’s average)



Sales factor


Crop-specific expenses, in $ per 100 ft2

Relative crop income, in $ per 100 ft2

Summer squash

37 $2.25 $83 75% $62 $91 ($29)

Tomato 66 $2.75 $182 75% $136 $91 $45

Sweet corn

25 $0.85 $21 95% $20 $18 $2

Radish 21 $5.50 $116 80% $92 $45 $47

Pea 9 $7.50 $68 95% $64 $46 $18

Account for growing timeNumber of days in ground (or allocated to the crop)To estimate, use “days to maturity” data from seed

catalogs (plus a buffer, esp. for crops with long harvest period)

time in ground [time]

sales factor (%)


=

price [$]_yield [wt]

* * -

relative crop income [$]_ area [area] * time [time] crop-specific

expenses [$] area [area]

( )

Crop comparison example


sales factor (%)


=


* * -



( )

Crop type

Yield, in pounds per 100 ft2 (Knott’s average)

Price, in $ per pound


Sales factor


Crop-specific expenses, in $ per 100 ft2


Time in ground, in days

Relative crop income, in $ per 100 ft2 per day

Summer squash

37 $2.25

$83 75%

$62 $91 ($29) 90 ($0.32)

Tomato

66 $2.75

$182 75%

$136 $91 $45 100 $0.45

Sweet corn

25 $0.85

$21 95%

$20 $18 $2 80 $0.02

Radish 21 $5.50

$116 80%

$92 $45 $47 40 $1.19

Pea 9 $7.50

$68 95%

$64 $46 $18 70 $0.26

Other factors that are not quantified by this model: On the spectrum of heavy feeder to nitrogen fixer, where does

crop fall? Do leftovers have value even if they don’t sell?

For our pantry, employee pay, food bank, pig/goats/chicken, or the compost pile?

What additional expenses might be incurred as a result of growing decisions (& are these costs worth it if they might be avoided with other crop combinations?): Will extra cooler space or a new trailer be needed because of too

much bulk at a given time? Do specific crops or combination of crops increase the farm’s

resilience to extreme weather? How is work load distributed in crop production?

Heavy up front (work happens even if crop fails) Heavy at harvest (work only happens if crop is successful)

Additional considerations for crop choice

Data sourcesOur farm’s yield data vs. generic yield dataSame prices, sales factors, and crop-specific expenses,

used in both calculationsCrop type Knott’s average yields Chert Hollow Farm, LLC

yields (2010)

Yield, in pounds per 100 ft2


Yield, in pounds per 100 ft2


Summer squash

37 ($29) 65 (includes some seconds)

$18

Tomato 66 $45 45 (very approx.,

included some dud varieties)

$2

Sweet corn 25 $2 Did not grow n/a

Radish 21 $47 ~21 (with greens)

$47

Pea 9 $18 21 (snow peas) $104

Once data are in a spreadsheet, there are many opportunities for data exploration

Ask the question: What can be done to make a crop more profitable? Would we be better off raising the price & selling

less?Would reducing picking frequency and accepting

more overgrowns improve profitability through lower labor requirements?

Would reducing production to ensure regular sell-outs improve profitability?

Is trellising worth the hassle? (Compare yields & time budgets for bush & pole beans or peas)

Data exploration

Record-keeping suggestions

Using on-farm data

Data needs:YieldArea plantedPriceSales factorTime a crop is in

groundCrop-specific

expenses:Products/inputsLabor

Why collect your own data?Results are as good as

the data you put inBetter understanding

of strengths & limitations of the numbers

Way to assess year-to-year variation


sales factor (%)


=


* * -



( )

Area planted: Planting plan &/or seeding/transplant record sheets

Yield data: Harvest record sheet

Developing an effective record sheet is an iterative process If it is not being used or if it does not have the

information needed, it is not effective; change itPitfall: inconsistent units

Try to use consistent units (weight, volume, or count) on harvest and sales records

Label containers with tare weightAlso record conversion factors between weight & volume

(for example, 1 pint edamame = 0.5 lbs) or weight & count (x peppers = y pounds) so can convert if needed

Time in ground

End date: Look for date of last

harvest

Start date

Price data: Market records & invoices

market prices(include sales

tax)

restaurant prices

Sales factor: Market record sheets&/or compilation of harvest & sales records

Compiled from various sources:Receipts, bank records (need these for the IRS

anyway)Records of materials used (twine, irrigation,

etc.)Labor expenses:

Employee time sheetsTask logs, crop journal

Crop-specific expenses

Plan record keeping to fulfill your data needs (not just what the certifiers or bureaucrats require)

Harness the records that you haveAnalyze data even if on-farm records aren’t

perfect; fill in with estimates or use off-farm data as needed

Improve record-keeping methods each year

Record-keeping summary

Reasons to diversifyRisk management (Grohsgal,

Growing for Market, Oct. & Nov. 2006)

Work load distribution over time

Rotational considerations (nutrient use, disease)

Enjoyment of growing, experimenting with, & eating diverse plants

Not enough market to make a full living off of very few crops

Efficiency in:PlanningRecord keepingPlantingHarvestCrop profitability

analysis Customers often can’t

absorb full diversity of complex stand in a busy market

How many types of crops?

Reasons to simplify

This method is:Flexible enough to be tailored to farm-specific methods

& conditionsUseful for assessing crops even if they have not been

grown on a farmBest with good on-farm records, but still useful even if

farm records are incomplete or imperfectUseful for considering ways to improve profitability of a

given crop

Crop income comparison model


sales factor (%)


=


* * -



( )

Questions?

[email protected]

Eric & Joanna Reuter Chert Hollow Farm, LLC January 16, 2012.

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Transcript of Eric & Joanna Reuter Chert Hollow Farm, LLC January 16, 2012.