The Future of Florida’s Tomato

Industry: Mechanized Harvest

Department of Food and Resource Economics

Ricky Lynch-Curtiss Fry-Lee Bowman-Lott Bullock

Department of Forestry

Emily Witt

Research Question• Will the introduction of mechanical harvesting in

the production of fresh-market Florida tomatoes cause growers to realize increased profitability by cutting harvest costs, allowing them to better compete with Mexican tomato producers?

Background Information

• Today in agriculture producers must not only compete with their neighbor but also on a global scale.

• Because of this it is important that domestic growers have every advantage at hand in order to compete on the World Market.

• Specialty crops and vegetable famers receive very little attention in farm legislation, so the comparative advantage must come from somewhere else.

• Not only do these farmers receive little help from government legislation they must also compete with a Mexican market that not only has lower costs but also benefits from the NAFTA which eliminated tariffs on Mexican imports.

Background Information

• In the late 1940’s California’s processing tomato industry cut costs and increased profitability by introducing a mechanical harvester to eliminate the need for hand harvesting. Significantly reducing their harvest costs.

• 95% of California growers implemented mechanical harvest within 10 years.

• Short Video of California Tomato Harvester

Motivation• Since 1994, Mexico’s comparative advantage in

labor cost has had significant impact on the profitability and market share of Florida Growers.

• It has caused many Florida producers to cut and even stop production.

As Florida’s fresh market continues to be negatively affected by Mexican growers, new technology should be introduced to

level the harvest cost playing field.

Motivation• Agriculture is a leading component of Florida’s

economy and tomatoes are a large part of Florida agriculture production.

• Florida’s fresh tomato production accounts for nearly all of the U.S. fresh tomato production from December-May

• Accounts for nearly half of the domestically produced fresh market tomatoes.

• Accounts for over $400 million in annual revenue

Literature ReviewHarvest mechanization helps agriculture

remain competitive• Article explains how California tomato farmers

have continued to remain competitive due to the implementation of  harvest technology.

• Proved that mechanized harvest reduced labor cost to less than 20% of total cost.

• Proved that the mechanical harvester doesn’t lead to additional unemployment, instead it creates more jobs due to the increase in production (Thompson and Blank, 2000).

Literature Review• Engineering and Horticultural Aspects of Robotic Fruit

Harvesting: Opportunities and Constraints• Over the last few decades, various ideas for how to mechanize

harvesting have been studied, however a feasible solution has not been found yet.

• The technology is available, but the research is not fully completed on how to successfully mechanically harvest tomatoes.

• This article focuses on the technology that is necessary to put this into practice, because it would be much more successful.

• If the technology was there, then mechanized harvesting would be much more profitable.

• This article supports our research on the profitability increase from mechanized harvesting compared to hand harvesting (Burks et. al., 2005).

Objectives & Expectations

• The objective of this research is to determine if the implementation of mechanical harvest will have a significant affect on Florida fresh market tomato producer’s profitability.

• We expect that market price per acre will decrease due to an increase in output, this increase will offset any price decrease.

• Labor costs will decrease due to the elimination of the amount of laborers that are required to hand harvest.

• Fixed costs will increase due to the machine but will only affect profit in the short run.

Hypothesis

represents the parameter estimate of the dummy variable Machine which accounts for the implementation of the machine

Fixed Cost of Harvester

• Commercial harvester is already in use for the production of crush market tomatoes.

• We are using the fixed cost per acre of this machine as our estimate for the cost of the proposed fresh tomato harvester. The cost of the two machines should be relatively close.

• The fixed cost per acre for the harvester comes from published UC Davis information.

Year Cost of Machine

1994 209

1995 160

1996 202

1997 128

1998 185

1999 195

2000 127

2001 114

2002 148

2003 171

2004 177

2005 202

2006 141

2007 129

2008 115

2009 116

Harvest Cost• We will use a combination of

industry contacts as well as published IFAS cost data to determine the cost of hand harvesting per acre.

• We will use UC Davis published cost data to determine the machine harvesting per acre.

• Harvest costs encompass more than just labor.

• Today on average Florida hand harvest labor costs are $2000/acre.

Year Harvest Cost Hand

Harvest cost machine

1994 3570 340

1995 3577 424

1996 3668 494

1997 3672 545

1998 3679 429

1999 3677 400

2000 3694 481

2001 3689 504

2002 3704 760

2003 3726 748

2004 3721 677

2005 3730 576

2006 3728 613

2007 3767 558

2008 3750 616

2009 3900 634

Market Price• Fresh market tomato prices per

acre will be calculated using published USDA data.

• The USDA keeps track of annual acres planted, harvested, yield per acre, and market price.

• We will only use data from 1994 onward due to the implementation of NAFTA and the spike in Mexican production which ensued.

Year Market Price

1994 90421995 85561996 10969.511997 124251998 13170.971999 90652000 125202001 10854.362002 122852003 128042004 119162005 191662006 14315.012007 12281.52008 197542009 15482.29

Pre-harvest Cost• Our pre-harvest cost

data comes from published IFAS data.

• It encompasses everything that is needed in order to produce fresh market Florida tomatoes.

• Including fixed land and equipment costs

Year Pre-harvest Cost

1994 55141995 69741996 78041997 79781998 70061999 74592000 76782001 84622002 85442003 85472004 97422005 103132006 110422007 110232008 115852009 12104

VariablesYear Profit Market Price Yield Revenue Harvest Cost Pre-harvest Cost Cost of MachineX1 Y1 X2 X3 X4 X5 X7 X81 -42 9042 330 9042 3570 5514 02 -1995 8556 310 8556 3577 6974 03 109 10970 355 10970 3668 7193 04 1249 12425 350 12425 3672 7504 05 1052 13171 355 13171 3679 8440 06 -3060 9065 350 9065 3677 8448 07 802 12520 400 12520 3694 8024 08 -1297 10854 335 10854 3689 8462 09 -814 12285 325 12285 3704 9395 010 -47 12804 330 12804 3726 9125 011 -1547 11916 360 11916 3721 9742 012 4222 19166 370 19166 3730 11214 013 9 14315 350 14315 3728 10578 014 -2509 12282 385 12282 3767 11023 015 4419 19754 332 19754 3750 11585 016 -522 15482 366 15482 3900 12104 017 8702 9042 330 9042 340 5514 20918 8132 8556 310 8556 424 6974 19719 10476 10970 355 10970 494 7193 19920 11880 12425 350 12425 545 7504 16021 12742 13171 355 13171 429 8440 12922 8665 9065 350 9065 400 8448 16223 12039 12520 400 12520 481 8024 17424 10350 10854 335 10854 504 8462 11425 11525 12285 325 12285 760 9395 14926 12056 12804 330 12804 748 9125 18027 11239 11916 360 11916 677 9742 20228 18590 19166 370 19166 576 11214 15429 13702 14315 350 14315 613 10578 12130 11724 12282 385 12282 558 11023 12931 19138 19754 332 19754 616 11585 11532 14848 15482 366 15482 634 12104 116

ModelThis model estimates profit with mechanical harvesting

Where:

Parameter Estimates

Variable DF

Estimate StandardError

t Value ApproxPr > |t|

Intercept 1 -3303 4613 -0.72 0.4806

X2 1 0.9999 0.0266 37.60 <.0001

X5 1 -1.2230 1.2571 -0.97 0.3399

X7 1 -0.5129 0.1599 -3.21 0.0037

machine 1 8207 4078 2.01 0.0551

year 1 15.4890 80.8053 0.19 0.8495

Interpretation of Model Results

• Profit = -3303 when all other variables are 0

• As market price increases by $1/acre profit increases by $0.999/acre

• As harvest costs increases by $1/acre profit decreases by $1.223/acre

• As pre-harvest costs increases by $1/acre profit decreases by

$0.512/acre

• If the machine is implemented profit increases $8207/acre

• Each additional year results in profit increase of $15.489/acre

Empirical AnalysisMulticollinearity

(Using Variance Inflation Factor)

• Generally VIF should not exceed 10

• Our model did, indicating we have multicollinearity

• This is not an issue because we have a high R2 value and most of our parameter estimates are significant.

Variable Variance Inflation

Intercept 0.000

X2 2.6725

X5 561.3309

X7 23.2253

Machine 560.1707

Year 20.7818

Empirical AnalysisAutocorrelation

• Using the DW test we found that our model has positive autocorrelation

• Then, using Godfrey’s test we found that the model has a higher order autoregressive error beyond the standard 4 lags

Durbin-Watson Statistics

Order DW Pr < DW Pr > DW

1 0.1677 <.0001 1.0000

Godfrey's Serial Correlation Test

Alternative LM Pr > LM

AR(1) 24.3643 <.0001

AR(2) 24.6416 <.0001

AR(3) 25.0040 <.0001

AR(4) 25.0572 <.0001

Empirical AnalysisAutocorrelation Correction

Durbin-Watson Statistics

Order DW Pr < DW Pr > DW

1 1.4594 0.0473 0.9527

• After positive autocorrelation was detected we ran the model with lagged error (n=1,2,3,4)

• We kept the model at n=1 since there was no difference in the change in the model as the lag time increased

Godfrey’s Serial Correlation Test

Alternative LM Pr>LM

AR(1) 6.8413 0.0089

AR(2) 6.9376 0.0312

AR(3) 9.9031 0.0194

AR(4) 10.2183 0.0369

Results and Interpretations

Based on P-value of parameter estimates • Market price has a significant relationship with profit

because P<0.05• Harvest costs have an insignificant relationship with

profit because P>0.05 (P=0.399)• Pre-harvest costs have a significant relationship with

profit because P<0.05 (P=0.0037)• The implementation of the machine has a slightly

insignificant relationship to profit because P>0.05 (P=0.0551)

• Year has an insignificant relationship with profit because P>0.05 (P=0.8495)

Conclusions• Based on the p-value of the machine we will fail

to reject H0 because 0.0551>0.05.

• We cannot conclude that the machine has a significant relationship with profit.

• Due to how close the p-value is to being significant, we expect that further research on the machine is justifiable, and as more accurate costs are determined the use of mechanical harvest will have a significant effect on profit.

Take Home Message• Our research is limited by the fact that the fresh

tomato harvester is still theoretical, potentially affecting the accuracy of our cost expectations and parameter estimates.

• Over all the take home message is that mechanical harvest of Florida fresh tomatoes is something that needs to be seriously considered.

• It has the potential to result in greater profits for producers allowing them to gain a comparative advantage over Mexican producers.

Questions

Works Cited• Thompson, James F., and Steven C. Blank. "California Agriculture Online." California Agriculture Online.

University of California, May-June 2000. Web. 06 Apr. 2014. <http://californiaagriculture.ucanr.edu/landingpage.cfm?article=ca.v054n03p51&fulltext=yes>.

• Shockwiler, J. S., and John Vansickle. "Impact of Mexican Tomato Imports on the Florida Tomato Market: A Review of Recent Studies." Impact of Mexican Tomato Imports Review. University of Florida, Food and Resource Economics Dept., Nov. 1981. Web. 6 Apr. 2014. <http://www.fred.ifas.ufl.edu/agmarketing/pubs/1980s/Impact%20of%20Mexican%20Tomato%20Imports%20-%20review.pdf>.

• Burks, T., and F. Villegas. "Engineering and Horticultural Aspects of Robotic Fruit Harvesting: Opportunities and Constraints." Engineering and Horticultural Aspects of Robotic Fruit Harvesting: Opportunities and Constraints. American Society for Horticultural Science, Jan.-Feb. 2009. Web. 06 Apr. 2014. <http://horttech.ashspublications.org/content/15/1/79.full.pdf%2Bhtml>.

• Roka, Fritz. "Outlook on Agricultural Labor in Florida, 2012 - 13." Labor_roka.pdf. University of Florida, 2011. Web. 6 Apr. 2014. <http://www.fred.ifas.ufl.edu/pdf/webinar/labor_roka.pdf>.

• "USDA ERS - North American Fresh-Tomato Market." North American Fresh-Tomato Market. USDA, 12 Mar. 2013. Web. 06 Apr. 2014. <http://www.ers.usda.gov/topics/in-the-news/north-american-fresh-tomato-market.aspx#.U0Gr5ld3O2d>.

• "ASABE: UC-Blackwelder Tomato Harvester." UC-Blackwelder Tomato Harvester. American Society of Agricultural and Biological Engineers, 2005. Web. 04 Apr. 2014. <http://www.asabe.org/awards-landmarks/asabe-historic-landmarks/uc-blackwelder-tomato-harvester-45.aspx>.

• "UC-Blackwelder Tomato Harvester ASABE Landmark No 45." YouTube. YouTube, 16 Nov. 2007. Web. 06 Apr. 2014. <https://www.youtube.com/watch?v=Xg1UfcJqTss>.

• "240 Tomato Harvester." Pikrite.com. Pikrite, n.d. Web. 4 Apr. 2014. <http://www.pikrite.com/harvesters/240-tomato-harvester/>.