Demo Times
nd
April 22 , 2010
Local Agricultural Supply Chain Improvement
Lindsey Arita, Joseph Lee, Julia Mahon, Jay Raghavan
Advisor: Dr. Eric Bruun
ESE Senior Design 2009-2010
Abstract
9-9:30 AM
9:30-10 AM
10-10:30 AM
1:30-2 PM
Model Description
Successful operation and maintenance of small-scale farms is
becoming increasingly difficult. Escalating farmland prices, price
competition from corporate farms, and increased costs of agricultural
production have forced many farmers to mass-produce for corporations
or sell their farms.
The objective of this project was to design and apply a model that
allows individual farmers in Pennsylvania to identify factors that help
increase profitability. The key steps in the construction of this model
included determining the most significant contributors to a farm’s profit
through stepwise regressions on extensive census data and understanding
how these profit indicators could be realistically improved. This system
helps farmers understand specific opportunities for improvement by
comparing their unique data to optimal performance levels across
statistically significant factors. The final product is a self-assessment
model and an information hub for local farmers, which includes a website
that offers a downloadable copy of the model and analysis of extensive
research on the agricultural dynamics in Pennsylvania.
The individual utilization of this model and increased accessibility to
regional agricultural data ultimately contributes to the long-term viability
of local agriculture. This allows farmers to avoid resorting to growing
crops strictly for corporations, which tends to reduce the farmers’
margins and decreases product quality for the end-consumer. Local
consumers further benefit from this supply chain improvement by gaining
more access to locally grown, higher quality agricultural goods.
The model is a self assessment and predictive tool that farmers run within Excel:
• The farmer inputs his or her input variables and the model calculates how the farmer is doing relative to all the
other farmers in Pennsylvania.
• The model calculates the farmer’s predicted net income using the linear regression obtained from the stepwise
algorithm.
• Each variable has a detailed definition of what goes into calculating the variable and also tailored responses to
how well the farmer is performing in that particular variable.
• Since not all farmers are familiar with statistical analysis, text explanations and analysis are offered for each
variable as well.
• The model aims to help farmers by allowing them to evaluate themselves in comparison to their competitors.
While much of the data is publicly available, the data analysis and results have been refined to provide the
maximum utility to farmers.
User Portal (Website) Description
The website is designed as a portal for local farmers to gain access to
valuable research on the agricultural dynamics in Pennsylvania. On the website,
farmers can:
·
Download a copy of the model for personal use and verification;
·
Access detailed maps of Pennsylvania by county displaying:
·
Market Value (Total Sales) per Farm by County,
·
Profit per Farm vs. Concentration of Farms,
·
Government Subsidies vs. Type AND Volume of Sales;
·
Access a map of all Farmers’ Markets in Pennsylvania, including hours of
operation and contact information;
·
Access to links and resources for further assistance and information.
User Flow Chart
Results
Farm Profitability vs. Concentration of Farms
Nine variables were found to be statistically significant variables in farm profit:
Certain kinds of products contribute more to profit than others;
• Sale of livestock (i.e. milk products), for example, tends to contribute more to
profit than vegetables and potatoes;
Some variables have significant correlation but not cause;
• More acres of woodland may mean larger farms with higher margins, but no
farm can instantaneously acquire more acres of woodland;
• The negative correlation with the number of farmers’ markets is likely because
counties with greater opportunity for improvement attract the formation of
more farmers’ markets, not that farmers’ markets are detrimental to profit.
In Pennsylvania , by County
Validation
•
Average Market Value (Total Sales) Per Farm
In Pennsylvania, by County
Output Report
•
• Explanation of
location’s most
significant contributors
to farm profit
• Comparison of farm
performance relative to
others in PA region
• Customized
recommendations for
improved profitability
•
Organizations like the Food Trust and Delaware Valley Regional Planning
Committee (DVRPC) have offered support of the project's endeavors and
have provided references of farmers to work with on improving the model;
9 out of 14 farmers expressed interest in such a system after trying the
model;
Feedback from regional planners and farmers have been incorporated to
make the model easier to understand, more user-friendly, and more
applicable.
Recommended Next Steps
•
•
•
Example Statistics from Model Interface
Increased farmer interaction to institute continuous improvement of model
and a feedback loop
Initialize a rigorous data gathering process to include individual farm data
Develop network of farmers to facilitate development and distribution of
model