Crop profitability. Where should we focus our management efforts? Kansas State U N I V E R S I T Y

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1 Crop profitability Where should we focus our management efforts? Kevin C. Dhuyvetter, PhD Extension Ag Economist University Manhattan, KS

2 A Common Belief? to make 10 more through higher production, you may have to spend 5 to 8. Marketing has little to no cost. Farmer, Top Producer, April/May 2003

3 A Common Belief? Four key areas do affect profitability results. A fifth area is less important but can still add to your bottom line. The last area that separates those who make good returns from others is reducing input costs. It pales in comparison to the opportunity in chasing the top four rabbits, however. First four are marketing, equipment cost management, inventory management, and agronomic management. Farm mgmt consultant, SoybeanDigest.com, Nov 2002

4 A Common Belief? Having a good marketer is better these days than having a good crop consultant. That is critical because the opportunities for a higher price are there. On average, if you took all the ways people could make money last year they could have made $3 a bushel for their corn. Ag lender, High Plains Journal, August 27, 2001

5 A Common Belief? Marketing is as important, or more important, than the (natural) gas price increase. Low crop prices, compounded by poor marketing in some cases, is hurting us. Most growers can raise their crops within five to 10 percent of the yield of anybody else in the county. However, too many of them take 30 percent less than their neighbors because they do not market their crop as well as they should. Crop consultant, Crop Decisions, January 2001

6 Grain marketing Seems like a no-brainer -- do a good job of marketing and you will be successful. Is this really what makes farms successful? What do the data suggest; i.e., is there evidence to support that being successful at marketing is that easy and that important?

7 Persistence -- Something is said to be persistent if it is consistently different (better or worse) than average. Thus, the less persistent something is, the more random it is. What does this mean in terms of where we should spend our management efforts?

8 percent Persistence of management traits Persistence of management traits Pe rs iste nce of m anage me nt traits: percent of farm s sta tistic a lly d iffe re n t f rom a v e ra ge, % 61.6% 39.7% 55.0% 67.7% 81.7% 44.7% 88.2% % 10 0 P ro f it C o s t Y ie ld T e c h R e n t P ric e P la n t G o v t S iz e

9 change in $/acre profit Factors impacting profitability differences Factors impacting profitability differences ( ) diff in pro fit (ov e r a v g f a rm) by be in g in be st 1 $30 $25 $ $20 $15 $10 $ * $ * $ * $ * $ * $5 $ * $0 C o s t Y ie ld P ric e T e c h P la n t R e n t S iz e * statistically different from 0 at 90% confidence

10 DIFFERENCE between the High 1/3 and Low 1/3 farms ranked on return to management Kansas Farm Management Association Enterprise Analysis, State Averages Corn Irr Corn Sorghum Wheat Soybean Alfalfa Number of farms INCOME ($/acre) Yield per acre, bu Price per unit $0.25 $0.28 $0.12 $0.29 $0.40 $13.12 Crop income $97.17 $51.95 $72.78 $45.16 $91.51 $ Government payment Gross income $97.64 $45.16 $68.63 $50.69 $94.12 $ More profitable farms have lower costs than low profit farms in most all categories COSTS ($/acre) 1 Seed More -$3.83 profitable -$27.93 farms get -$2.53 higher yields -$2.14 (and -$2.30 higher prices) $1.42 Fertilizer and have similar to slightly lower government payments Herbicide-insecticide Crop insurance Machinery Other Land Interest Total Cost -$ $ $ $ $ $16.12 Top 1/3 of farms tend to be larger and rent/own land in similar fashion as low profit farms -- most of the differences in returns are due to costs and yield differences Net Return to Management $ $ $ $ $ $ Top 1/3 of farms have considerably higher returns than bottom 1/3 Enterprise acres Operator percentage 4.2% -7.3% -0.6% -1.6% 3.0% 6.5% Yield effect 37.9% 19.9% 48.1% 34.3% 45.7% 49.3% Price effect 18.5% 16.2% 7.5% 9.9% 11.8% 29.0% Operator % effect 13.0% -18.5% -1.4% -3.8% 9.1% 12.9% Cost effect 30.6% 82.4% 45.8% 59.5% 33.3% 8.8% 1 Based on the operator's share of production, and thus includes only production expenses paid by the operator.

11 Percent Price effect decreases with additional years 35% 30% 25% Profit Difference Due to PRICE Differences 2009 (1557 farms) (699 farms) (415 farms) (261 farms) 20% 15% 10% 5% 0% Corn Irr Corn Sorghum Wheat Soybean Alfalfa

12 Key drivers of profitability differences among producers Costs Technology adoption Farm size Machinery investment and costs are directly related to these three factors

13 Percent of farms Variability in machinery cost across producers Distribution of Machinery Cost/Acre Mean = $66.07 Median = $ < Cost, $/ac Source: KFMA non-irrigated crop farms having continuous data from (minimum of 160 acres and machinery cost/acre > $10/ac; costs do not include labor total of 614 farms)

14 Machinery costs per acre slightly less persistent Machinery costs per acre are fairly persistent Relative rank in Machinery Cost/Ac Rankings - Non-irrigated Crop Farms (correlation = 0.80) Relative rank in 2009 Source: KFMA non-irrigated crop farms having continuous data from (minimum of 160 acres and machinery cost/acre > $10/ac total of 614 farms)

15 High profit farms have lower machinery costs Kansas Farm Management Association Crop Enterprises Analysis State Averages, Corn Irr Corn Sorghum Wheat Soybean Alfalfa Number of Farms Average Acres Differences in Machinery Costs, $/acre (high profif vs. low profit) Repairs -$4.84 -$9.57 -$4.02 -$7.43 -$7.02 -$7.48 Machine Hire Fuel and Oil Depreciation Labor Total -$ $ $ $ $ $17.79

16 Key drivers of profitability differences among producers Costs Technology adoption Farm size Adopting new machinery technologies is an important way that farm managers lower their machinery costs to distinguish themselves from others for the purpose of increasing profit (but this should only be done if it is profitable) See Machinery Costs The impact of field size, shape, and distance (presentation at 2010 KSU Risk & Profit Conference available at

17 Machinery decision-tools available OwnCombine.xls KSU-GPSguidance.xls OwnBaler.xls OwnSprayer.xls KSU-MachCost.xls OwnTractor.xls 29

19 Precision agriculture means different things to different people Can t make blanket statements that it pays or doesn t pay One aspect of precision agriculture is related to machinery technology Guidance systems Section controllers Issues Machinery overlap Field headlands Large (wide) machinery

20 90-ft sprayer example -- results U N I V based E R S I T on Y machine and input cost savings Impact of Acres Covered on Economics of Guidance System 1 Annual Investment Return on Payback acres supported 2 investment 2,3 years 3 14,000 $32, % ,000 $28, % ,000 $23, % 2.4 8,000 $18, % 3.1 6,000 $14, % 4.3 4,000 $9, % 7.2 2,000 $4, % Machine and input cost savings reducing overlap from 7.0% to 1.75% 2 Based on four-year ammortization 3 Given $15,000 investment Impact of Acres Covered on Economics of Section Control 1 Annual Investment Return on Payback acres supported 2 investment 2,3 years 3 14,000 $52, % ,000 $45, % ,000 $37, % 1.0 8,000 $30, % 1.2 6,000 $22, % 1.6 4,000 $15, % 2.5 2,000 $7, % Automatic control of 5 boom sections, input cost savings (guidance exists) 2 Based on four-year ammortization 3 Given $10,000 investment As with most all technologies, the returns to investing in guidance systems and section controls are not scale neutral Given the assumptions for this example, the returns to investing in section controls are much higher than guidance systems (but you need the guidance system to realize these benefits)

21 90-ft sprayer example -- results U N I V based E R S I T on Y machine and input cost savings Impact of Acres Covered and Input Cost on Guidance System ROI 1 Annual Average cost of input, $/application acre acres $4.00 $8.00 $12.00 $16.00 $ , % 33.9% 54.3% 73.5% 92.0% 12, % 24.8% 43.0% 60.0% 76.3% 10, % 15.2% 31.2% 46.0% 60.1% 8, % 4.9% 18.7% 31.3% 43.3% 6, % -6.5% 5.1% 15.5% 25.3% 4, % -19.6% -10.4% -2.3% 5.3% 2, % -36.7% -30.2% -24.5% -19.4% 1 Machine and input cost savings reducing overlap from 7.0% to 1.75% Based on four-year ammortization Given $15,000 investment Impact of Acres Covered and Input Cost on Section Control ROI 1 Annual Average cost of input, $/application acre acres $4.00 $8.00 $12.00 $16.00 $ , % 99.0% 154.9% 209.2% 262.9% 12, % 82.5% 131.2% 178.3% 224.6% 10, % 65.5% 107.2% 147.1% 186.1% 8, % 47.8% 82.5% 115.3% 147.1% 6, % 28.9% 56.7% 82.5% 107.2% 4, % 8.0% 28.9% 47.8% 65.5% 2, % -17.5% -3.8% 8.0% 18.8% 1 Automatic control of 5 boom sections, input cost savings (guidance exists) Based on four-year ammortization Given $10,000 investment but, as input costs increase, these technologies will pay for smaller operations as well (additionally, investment required likely will fall over time).

22 Historical and forecasted oil and diesel fuel prices

23 Crude oil price, $/barrel Diesel price, $/gallon Monthly Crude Oil and Diesel Prices, Jan Dec 2011 (D e c D e c fore c a ste d / 0 3 / fu ture s pric e s) NYMEX crude oil SW KS diesel Historical relationship suggests that NYMEX crude oil futures market can be used to forecast diesel prices.

24 $/harvested acre SW KS SW fuel KS price, fuel $/gal price, (and $/gal gallons) Impact of fuel prices on costs versus tillage method 24 Comparison of No-Till vs. Tillage -- Fuel and Oil Cost Source: NC FMA, actual, 2010 and 2011 forecasted NT NT (r (r = 0.987) = CT/RT (r (r = 0.979) = Fuel Fuel price Gallons saved F F

25 Fertilizer prices (should you be cutting back on fertilizer rates?)

26 Situation Price volatility of crops and fertilizers have been at unprecedented levels in recent years (similar for irrigation pumping costs) Prices of all fertilizer nutrients increased (and then decreased) significantly in recent years, but the magnitude of changes varied considerably by nutrient and product Increased volatility has led to many questions from producers regarding recommended fertilizer rates (i.e., do optimal levels change?)

27 Price, $/lb Fertilizer prices are on the rise again Weekly Fertilizer Prices -- Western KS Coop NH /10/06 1/8/07 4/8/07 7/7/07 10/5/07 1/3/08 4/2/08 7/1/08 9/29/08 12/28/08 3/28/09 6/26/09 9/24/09 12/23/09 3/23/10 6/21/10 9/19/10 12/18/10

28 Problem Many fertilizer recommendations for a specific nutrient do not explicitly account for prices of the crop or the nutrient Very few (any?) of the fertilizer recommendations for one nutrient (e.g., N) explicitly account for costs of other nutrients/inputs (e.g., P) Subjective understanding of the issue allows recommendations to be modified with regard to direction, but quantifying magnitude is difficult

29 Response to problem Started with KSU fertilizer recommendations for N and P (MF-2586) and developed production functions that could incorporate prices Key assumptions behind analysis KSU recommendations are economic optimal at long run prices ( yr avg prior to publication) Wheat = $3.22/bu; Corn =$2.35/bu; N = $0.2094/lb; P = $0.2445/lb Recommended rates for one nutrient (e.g., N) assume other management factors are non-limiting (implies that yield responds independently to various inputs) Expected P-response can be represented using a quadratic plateau (similar to N-response, which was tested) Initial efforts beginning in late 2005 (Kastens, Dhuyvetter, Schlegel, & Dumler) were based entirely on nitrogen

30 A little background info

31 KSU nitrogen recommendations no prices Corn and grain sorghum N rec = (Yield Goal x 1.6) (%SOM x 20) Profile N Manure N Other N Adjustments + Previous Crop Adjustments Each lb/a of N equates to 0.42 bu/ac Wheat N rec = (Yield Goal x 2.4) (%SOM x 10) Profile N Manure N Other N Adjustments + Previous Crop Adjustments + Tillage Adjustments + Grazing Adjustments Sunflowers N rec = (Yield Goal x 0.075) (%SOM x 20) Profile N Manure N Other N Adjustments + Previous Crop Adjustments

Nitrogen production function In a limiting factor framework, it is generally believed that relationship between N and yield is linear for any given year and location (implies linear plateau

32 Nitrogen production function In a limiting factor framework, it is generally believed that relationship between N and yield is linear for any given year and location (implies linear plateau production function) Linear plateau production function implies that optimal N will either be 0 or level where yield plateaus Average of multiple linear plateau production functions can be non-linear and this represents expectations of future N:yield relationship

33 Yield, bu/acre Functions could and likely should have 0-intercept if response is to total N 90 Lin e a r pla te a u N re spon se for w he a t Yield Goals: 40,50,60,70, Get 0.42 bu. wheat for each lb/a additional N ($1.34 for each $0.21 investment) T U N (f e rt N + S T N * O M ), lb / a c re If wheat = $3.20/bu, N price won t matter until fertn = $1.34/lb, then optimal is 0 lb/acre

34 yield, bu/ac Yield response by year linear plateau fits data quite well Continuous milo response to fertn, , Belleville fertn, lb/ac What would yield be for given fertn next year?

35 yield, bu/ac Average of linear plateaus can become non-linear 180 Continuous milo response to fertn, , Belleville Average fertn, lb/ac

36 yield, bu/acre Average of linear plateaus can become non-linear 60 Wheat response to fertn, fall inject, , Tribune fe rtn, lb / a Blue line is NOT based on a mathematical function

37 Functional form Numerous functional forms could be used that would meet objectives. We considered: Linear plateau, along with four different curvilinear forms Based on nitrogen fertilizer research studies from north central and western Kansas on wheat, corn, and milo, quadratic plateau model fit data better than alternatives most often Most non-linear models look very similar, but results (i.e., optimal N versus N price) do vary

38 Nitrogen production function Nice property of non-linear production function is that it implies diminishing marginal returns and thus prices matter Assumed functional form is quadratic plateau which allows diminishing returns consistent with linear plateau in any given year Estimate model parameters such that KSU Nrec is economic optimum at historical average prices Yield plateau is equal to yield goal Intercept goes through origin (i.e., 0 N equates to 0 yield)

39 Yield, bu/acre Defined points that allowed quadratic-plateau function to be defined Wheat yield response function (2) Yield plateaus at yield goal (3) Yield at KSU rec (fertn) is economic optimal (i.e., slope of function = average price ratio) (1) No nitrogen implies zero yield TUN (fertn+stn+10*om, lbs/acre

40 Yield, bu/acre Same optimal N (slope = 0.21/3.22) but yields about 1% lower than plateau W he a t yie ld c o nsiste nt w ith KSU N re c (Y G : 4 0, 5 0,6 0, quadratic pl ateaus; opt TUN: 96,120,144,168, T U N (f e rt N + S T N * O M ), lb / a c re

41 Yield, bu/acre Slope at diamonds is 0.40/3.22 W he a t yie ld c o nsiste nt w ith KSU N re c (Y G : 4 0, 5 0,6 0, opt $0.40 fertn: 87.8,109.8,131.7,153.7, T U N (f e rt N + S T N * O M ), lb / a c re With more expensive N, you make more money by applying less

42 Operationalizing production function We believe we got to the point of if you believe KSU s fertilizer recommendations you have to believe our pricedependent profit-maximizing rates Everything was embedded in an Excel spreadsheet so that users could determine optimal fertilizer N rates based on fertilizer N prices and crop prices We could use the spreadsheet to recommend some typical percentage cutbacks on fertilizer dealers had been requesting such info throughout 2005

43 Late summer early Fall 2008 Very high fertilizer prices and not just N Falling crop prices Producers asking about price-based adjustments again, especially related to high P prices ($1.20/lb P2O5??) And so we adjust the decision spreadsheet again this time incorporating P Use MF-2586 sufficiency P recs

KSU-NPI_CropBudgets.xls available at www.agmanager.

44 KSU-NPI_CropBudgets.xls available at (click on Decision Tools under Projected Budgets )

46 At current fertilizer (NH3 for N) and crop prices, N rates are ~8% lower than official KSU rec and P rates are ~20% lower. TABLE 1. Production Inputs Used for Budgets 5:54 PM 12/07/10 ITEM Wheat Corn Sorghum Soybean Sunflower Price scenarios to consider Use (Y=1, N=0) Low prices $4.50 $3.00 $2.80 $7.50 $ year average prices $6.10 $4.01 $3.76 $9.89 $ bids (Newton -- 12/4/10) $7.13 $4.71 $4.51 $11.27 $ Yield goal (YG), bu/ac Enter 0 for dryland or 1 for irrigated Soil test P (STP), ppm Organic matter (OM), % Soil test nitrogen (STN), lbs/ac Other N adjustments, lbs/ac KSU recommended nitrogen, lbs/ac Econ Optimum fertn, lbs/ac KSU recommended phosphate, lbs/ac Econ Optimum fertp, lbs/ac Econ Optimum Irrigation Amount, in Yield at optimal N, P, and I, bu/ac Change in STP, ppm , User enters yield goal, crop and fertilizer prices, and soil properties optimal N and P rates are calculated. Fertilizer: $/unit Nitrogen (N) $0.400 /lb Phosphate (P) $0.580 /lb "Blue" values represent user-entered user-entered inputs (all other inputs values (all are other calculated) values are calculated).

47 At current fertilizer (UAN for N) and crop prices, N rates are ~14% lower than official KSU rec and P rates are ~30% lower. TABLE 1. Production Inputs Used for Budgets 5:55 PM 12/07/10 ITEM Wheat Corn Sorghum Soybean Sunflower Price scenarios to consider Use (Y=1, N=0) Low prices $4.50 $3.00 $2.80 $7.50 $ year average prices $6.10 $4.01 $3.76 $9.89 $ bids (Newton -- 12/4/10) $7.13 $4.71 $4.51 $11.27 $ Yield goal (YG), bu/ac Enter 0 for dryland or 1 for irrigated Soil test P (STP), ppm Organic matter (OM), % Soil test nitrogen (STN), lbs/ac Other N adjustments, lbs/ac KSU recommended nitrogen, lbs/ac Econ Optimum fertn, lbs/ac KSU recommended phosphate, lbs/ac Econ Optimum fertp, lbs/ac Econ Optimum Irrigation Amount, in Yield at optimal N, P, and I, bu/ac Change in STP, ppm , User enters yield goal, crop and fertilizer prices, and soil properties optimal N and P rates are calculated. Fertilizer: $/unit Nitrogen (N) $0.550 /lb Phosphate (P) $0.580 /lb "Blue" values represent user-entered user-entered inputs (all other inputs values (all are other calculated) values are calculated).

48 At current fertilizer (UAN for N) and low crop prices, N rates are ~30% lower than official KSU rec and P rates are ~50% lower. TABLE 1. Production Inputs Used for Budgets 5:56 PM 12/07/10 ITEM Wheat Corn Sorghum Soybean Sunflower Price scenarios to consider Use (Y=1, N=0) Low prices $4.50 $3.00 $2.80 $7.50 $ year average prices $6.10 $4.01 $3.76 $9.89 $ bids (Newton -- 12/4/10) $7.13 $4.71 $4.51 $11.27 $ Yield goal (YG), bu/ac Enter 0 for dryland or 1 for irrigated Soil test P (STP), ppm Organic matter (OM), % Soil test nitrogen (STN), lbs/ac Other N adjustments, lbs/ac KSU recommended nitrogen, lbs/ac Econ Optimum fertn, lbs/ac KSU recommended phosphate, lbs/ac Econ Optimum fertp, lbs/ac Econ Optimum Irrigation Amount, in Yield at optimal N, P, and I, bu/ac Change in STP, ppm , User enters yield goal, crop and fertilizer prices, and soil properties optimal N and P rates are calculated. Fertilizer: $/unit Nitrogen (N) $0.550 /lb Phosphate (P) $0.580 /lb "Blue" values represent user-entered user-entered inputs (all other inputs values (all are other calculated) values are calculated).

49 Summary of fertilizer economics In order to determine how to adjust fertilizer rates in response to prices, a mathematical relationship between nutrient and yield is needed A quadratic-plateau function can be backed out of KSU N and P recs Quadratic-plateau function allows diminishing returns, but is also consistent with linear plateau within any site-year If multiple inputs are considered simultaneously, economic optimal rates are lower than when other inputs are ignored (or have zero cost)

50 So, what should one do? Use the spreadsheet! If your intuition causes you to question the results: Average the results with some other method Use the adjustment factors in the spreadsheet Question your intuition Likely, no one would ignore prices forever, i.e., regardless of their levels

51 Summary Tremendous variability in profitability across producers Prices impacts returns, but we have little evidence indicating they can be managed consistently Over time, differences in profitability are driven principally by cost and yield differences High profit farms are low-cost operators, but they do not cut costs at the expense of yields Machinery is a major determinant of cost differences, hence profit differences, and current technologies offer tremendous opportunity to lower costs

52 For more information and decision tools related to crop and machinery economics go to Kevin Dhuyvetter

Crop Production Management

Crop Production Management in Volatile Times Terry L. Kastens -- tkastens@ksu.edu -- 785-626-9000 Kevin C. Dhuyvetter -- kcd@ksu.edu -- 785-532-3527 Department of Agricultural Economics Kansas State University