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Nathan Moore 2023-01-12 22:27:05 -06:00
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3 changed files with 43 additions and 3 deletions

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@ -103,7 +103,8 @@ As figure \ref{ag_yields} shows, the epoch of ``Better Living Through Chemistry'
USDA yields over time USDA yields over time
The data plotted comes from the USDA The data plotted comes from the USDA
\url{https://www.nass.usda.gov/Statistics_by_Subject/index.php} \url{https://www.nass.usda.gov/Statistics_by_Subject/index.php}
The idea for this plot came from an online blog, \cite{math_encounters} The idea for this plot came from an online blog, \cite{math_encounters}.
Details for recreating this plot are given in \ref{how_yield_plot_is_made}.
} }
\label{ag_yields} \label{ag_yields}
\end{figure} \end{figure}
@ -150,8 +151,47 @@ The work was prompted in part by discussions with John Deming, Carl Ferkinhoff,
%a simple heading of Appendix use the code \section*{Appendix}. If it contains %a simple heading of Appendix use the code \section*{Appendix}. If it contains
%numbered equations, figures or tables the command \appendix should precede it and %numbered equations, figures or tables the command \appendix should precede it and
%\setcounter{section}{1} must follow it %\setcounter{section}{1} must follow it
%\appendix \clearpage
\%section{Introductory Food Energy Questions} \appendix
\section{Creating the historical kcal/acre figure from USDA data}
\label{how_yield_plot_is_made}
The United States Department of Agriculture (USDA) provides historical crop information via the National Agricultureal Statistics Service, \url{https://www.nass.usda.gov/Statistics_by_Subject/index.php?sector=CROPS}. Data was downloaded in spreadsheet csv format and then combined and plotted via a Python Jupyter notebook.
Each crop has its own bespoke units, for example potatoes are sold by hundredweight (CWT) but sugar beets are measured by the ton.
Every imaginable agricultural product seems to be tracked in the NASS site, for example Maple Syrup production is tracked and given in gallons of syrup per (tree) tap!
Conversion factors used are summarized in Table \ref{conversions}.
Calorie (kcal) density for each crop was taken from \url{https://fdc.nal.usda.gov/fdc-app.html}. Within this database, foods are identified by an FDC ID.
An example calculation (implemented in the Jupyter notebook) follows for Corn.
In 2022 the USDA reported an average production of 172.3 bushels of corn per acre of farmland.
\be
172.3\frac{bu}{acre}\cdot\frac{56lbs~corn}{bu}\cdot\frac{453.592~grams}{lbs}\cdot\frac{365~kcal}{100~grams} = 15,974,657 \frac{kcal}{acre}
\ee
Obviously the result is only reasonable to two signifigant figures!
%grams_per_lbs=453.592
%corn_lbs_per_bu=(56.0/1.0)
%corn_kcal_per_gram=(365/100)
%corn_kcal_per_acre = corn_bu_per_acre*corn_lbs_per_bu*grams_per_lbs*corn_kcal_per_gram
\begin{table}
\caption{\label{label}
A summary of units and conversions used to create figure \ref{ag_yields} from USDA NASS data. $1cwt$ is a hundred pounds of potatoes. A bushel, $1bu$, is a volume unit of about 35liters and corresponds to about 60lbs of grain. Calorie content per 100 gram mass of food is taken from the USDA's ``Food Data Central'' database. It isn't clear from any of these resources if lb is pound-force (lbf) or pound-mass (lbm) and so I am ignorantly treating them as ``grocery store units'' where $1 lbs = 453.592 grams$.
}
\begin{indented}
\item[]\begin{tabular}{@{}lllll}
\br
Crop&per acre unit&production unit&kcals per 100gram & FDC ID\\
\mr
Corn & bu/acre & $1bu=56lbs$ & 365 &170288 \\
Potatoes & cwt/acre & $1CWT=100lbs$ & 77 & 170026 \\
Soybeans & bu/acre & $1bu=60lbs$ & 446 & 174270 \\
Sunflowers & lbs/acre & & 584 & 170562 \\
Wheat & bu/acre & $1bu=60lbs$ & 327 & 168890 \\
\br
\end{tabular}
\end{indented}
\label{conversions}
\end{table}