diff --git a/food_energy.pdf b/food_energy.pdf index 3e075c2..783362c 100644 Binary files a/food_energy.pdf and b/food_energy.pdf differ diff --git a/food_energy.synctex.gz b/food_energy.synctex.gz index ab57df6..cd9ba9c 100644 Binary files a/food_energy.synctex.gz and b/food_energy.synctex.gz differ diff --git a/food_energy.tex b/food_energy.tex index 30f0005..99ce06c 100644 --- a/food_energy.tex +++ b/food_energy.tex @@ -103,7 +103,8 @@ As figure \ref{ag_yields} shows, the epoch of ``Better Living Through Chemistry' USDA yields over time The data plotted comes from the USDA \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} \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 %numbered equations, figures or tables the command \appendix should precede it and %\setcounter{section}{1} must follow it -%\appendix -\%section{Introductory Food Energy Questions} +\clearpage +\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}