Biomass data - sorghum.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "from cobra import io\n",
    "from cobra.core import Metabolite\n",
    "from cobra import flux_analysis\n",
    "from Functions import *\n",
    "from IPython import display\n",
    "import logging\n",
    "logging.basicConfig()\n",
    "logger = logging.getLogger('logger')\n",
    "\n",
    "#import sbml file\n",
    "fname = \"/home/sanu/Documents/Scripts/git/plantcoremetabolism-model/PlantCoreMetabolism_v1_3_0.xml\"\n",
    "model = io.sbml.read_sbml_model(fname)\n",
    "display.clear_output()\n",
    "\n",
    "from sweetlovegroup.transform import fixModelCompatibilityIssueCobra015\n",
    "model = fixModelCompatibilityIssueCobra015(model,fname)\n",
    "\n",
    "\n",
    "#change Biomass_tx to Protein_biomass\n",
    "rxn = model.reactions.get_by_id(\"Biomass_tx\")\n",
    "rxn.id = \"Protein_biomass_tx\"\n",
    "for met in [\"K_b\",\"Ca_b\",\"Mg_b\"]:\n",
    "    met  = model.metabolites.get_by_id(met)\n",
    "    coeff = rxn.metabolites.get(met)\n",
    "    rxn.add_metabolites({met:-1*coeff})\n",
    "met = Metabolite(\"Protein_b\",name=\"Protein_biomass\")\n",
    "formula_dict = rxn.check_mass_balance()\n",
    "met.formula = \"\".join([atom+str(formula_dict[atom]*-1) for atom in formula_dict.keys() if atom != \"charge\"])\n",
    "met.charge = formula_dict[\"charge\"]*-1\n",
    "rxn.add_metabolites({met:1})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "biomass = pd.DataFrame(data={\"\":[\"sSUCROSE_b\",\"GLC_c\",\"FRU_c\",\"Starch_b\",\"Cellulose_b\",\"Xylan_b\",\n",
    "                                 \"L_PHOSPHATIDATE_p\",\"PHOSPHATIDYL_CHOLINE_r\",\n",
    "                                 \"L_1_PHOSPHATIDYL_ETHANOLAMINE_r\",\"DIACYLGLYCEROL_p\",\n",
    "                                 \"Galactosyl_galactosyl_diacyl_glycerols_p\",\n",
    "                                 \"D_Galactosyl_12_diacyl_glycerols_p\",\"2_Lysophosphatidylcholines_r\",\n",
    "                                 \"Lysophosphatidylglycerols_r\",\"Triacylglycerols_p\",\n",
    "                                 \"L_1_PHOSPHATIDYL_GLYCEROL_p\",\"L_1_phosphatidyl_inositols_r\",\n",
    "                                 \"SULFOQUINOVOSYLDIACYLGLYCEROL_p\",\"Protein_b\",\n",
    "                                 \"sMAL_b\",\"sCIT_b\",\"sFUM_b\",\"ARG_c\",\"HIS_c\",\"LYS_c\",\"sASP_b\",\n",
    "                                 \"sGLU_b\",\"sSER_b\",\"THR_c\",\"ASN_c\",\"sGLN_b\",\"CYS_c\",\n",
    "                                 \"GLY_c\",\"PRO_c\",\"sALA_b\",\"VAL_c\",\"ILE_c\",\"LEU_c\",\n",
    "                                 \"MET_c\",\"PHE_c\",\"TYR_c\",\"TRP_c\",\"sGABA_b\",\"PALMITATE_p\",\n",
    "                                 \"CPD_9245_p\",\"CPD_17412_p\",\"CPD_17291\",\"STEARIC_ACID_p\",\n",
    "                                 \"OLEATE_CPD_p\",\"Octadecadienoate_p\",\"LINOLENIC_ACID_p\",\n",
    "                                 \"ARACHIDIC_ACID_p\",\"CPD_16709\",\"DOCOSANOATE_p\"],\n",
    "                             \"leaf\":[0.0]*54,\"stem\":[0.0]*54,\"root\":[0.0]*54,\"seed\":[0.0]*54,},dtype=\"float64\")\n",
    "biomass = biomass.set_index(\"\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "cobra/core/metabolite.py:104 \u001b[1;31mUserWarning\u001b[0m: 17.2020450391 is not an integer (in formula C17.2020450391H25.9492553613O5.7497158698N4.9536245179S0.1420323181)\n",
      "cobra/core/metabolite.py:104 \u001b[1;31mUserWarning\u001b[0m: 25.9492553613 is not an integer (in formula C17.2020450391H25.9492553613O5.7497158698N4.9536245179S0.1420323181)\n",
      "cobra/core/metabolite.py:104 \u001b[1;31mUserWarning\u001b[0m: 5.7497158698 is not an integer (in formula C17.2020450391H25.9492553613O5.7497158698N4.9536245179S0.1420323181)\n",
      "cobra/core/metabolite.py:104 \u001b[1;31mUserWarning\u001b[0m: 4.9536245179 is not an integer (in formula C17.2020450391H25.9492553613O5.7497158698N4.9536245179S0.1420323181)\n",
      "cobra/core/metabolite.py:104 \u001b[1;31mUserWarning\u001b[0m: 0.1420323181 is not an integer (in formula C17.2020450391H25.9492553613O5.7497158698N4.9536245179S0.1420323181)\n"
     ]
    }
   ],
   "source": [
    "proteinMW = model.metabolites.get_by_id(\"Protein_b\").formula_weight"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Mature leaves\n",
    "\n",
    "Extract day-time starch:sucrose accumulation rate ratio from Lunn and Hatch 1995, Figure 1\n",
    "\n",
    "<img src=\"references/Screenshot_20190714_104104.png\" height=25% width=25%>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_matureleaf_content_1 = pd.DataFrame(data={\"Time\":[\"Dawn\",\"Dusk\"],\n",
    "                                             \"Hexose (umol hexose/mgChl)\":[24.126984126984112-22.222222222222204,\n",
    "                                                                           121.26984126984127-116.19047619047619],\n",
    "                                             \"Sucrose (umol hexose/mgChl)\":[22.222222222222204-17.142857142857146,\n",
    "                                                                            116.19047619047619-95.87301587301586],\n",
    "                                             \"Starch (umol hexose/mgChl)\":[17.142857142857146,95.87301587301586]})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Hexose (umol hexose/mgChl)</th>\n",
       "      <th>Starch (umol hexose/mgChl)</th>\n",
       "      <th>Sucrose (umol hexose/mgChl)</th>\n",
       "      <th>Time</th>\n",
       "      <th>Starch (dusk-dawn)</th>\n",
       "      <th>Sucrose (dusk-dawn)</th>\n",
       "      <th>Hexose (dusk-dawn)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.904762</td>\n",
       "      <td>17.142857</td>\n",
       "      <td>5.079365</td>\n",
       "      <td>Dawn</td>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5.079365</td>\n",
       "      <td>95.873016</td>\n",
       "      <td>20.317460</td>\n",
       "      <td>Dusk</td>\n",
       "      <td>78.7302</td>\n",
       "      <td>15.2381</td>\n",
       "      <td>3.1746</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Hexose (umol hexose/mgChl)  Starch (umol hexose/mgChl)  \\\n",
       "0                    1.904762                   17.142857   \n",
       "1                    5.079365                   95.873016   \n",
       "\n",
       "   Sucrose (umol hexose/mgChl)  Time Starch (dusk-dawn) Sucrose (dusk-dawn)  \\\n",
       "0                     5.079365  Dawn                  -                   -   \n",
       "1                    20.317460  Dusk            78.7302             15.2381   \n",
       "\n",
       "  Hexose (dusk-dawn)  \n",
       "0                  -  \n",
       "1             3.1746  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Delta_sucrose = float(df_matureleaf_content_1[\"Sucrose (umol hexose/mgChl)\"][df_matureleaf_content_1[\"Time\"]==\"Dusk\"]) - \\\n",
    "float(df_matureleaf_content_1[\"Sucrose (umol hexose/mgChl)\"][df_matureleaf_content_1[\"Time\"]==\"Dawn\"])\n",
    "\n",
    "Delta_hexose =float(df_matureleaf_content_1[\"Hexose (umol hexose/mgChl)\"][df_matureleaf_content_1[\"Time\"]==\"Dusk\"]) - \\\n",
    "float(df_matureleaf_content_1[\"Hexose (umol hexose/mgChl)\"][df_matureleaf_content_1[\"Time\"]==\"Dawn\"])\n",
    "\n",
    "Delta_starch = float(df_matureleaf_content_1[\"Starch (umol hexose/mgChl)\"][df_matureleaf_content_1[\"Time\"]==\"Dusk\"]) - \\\n",
    "float(df_matureleaf_content_1[\"Starch (umol hexose/mgChl)\"][df_matureleaf_content_1[\"Time\"]==\"Dawn\"])\n",
    "\n",
    "df_matureleaf_content_1[\"Starch (dusk-dawn)\"]=[\"-\",Delta_starch]\n",
    "df_matureleaf_content_1[\"Sucrose (dusk-dawn)\"]=[\"-\",Delta_sucrose]\n",
    "df_matureleaf_content_1[\"Hexose (dusk-dawn)\"]=[\"-\",Delta_hexose]\n",
    "df_matureleaf_content_1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Starch sucrose day-time accumulation rate = 10.3333333333\n"
     ]
    }
   ],
   "source": [
    "Sucrose_in_umols = 0.5*(df_matureleaf_content_1.at[1,\"Sucrose (dusk-dawn)\"])\n",
    "Starch_in_umols = (df_matureleaf_content_1.at[1,\"Starch (dusk-dawn)\"])\n",
    "Starch_to_sucrose_ratio = Starch_in_umols/Sucrose_in_umols\n",
    "print (\"Starch sucrose day-time accumulation rate = \"+str(Starch_to_sucrose_ratio))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Leaf"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Extract major sugar and amino acid content (8hr into photoperiod) from Ogbaga et al 2016, Figure 3, 4 and 5\n",
    "\n",
    "<img src=\"references/Screenshot_20190715_102019.png\" height=30% width=30%>\n",
    "\n",
    "<img src=\"references/Screenshot_20190715_101103.png\" height=50% width=50%>\n",
    "\n",
    "<img src=\"references/Screenshot_20190715_102807.png\" height=50% width=50%>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>variery Samsorg 40</th>\n",
       "      <th>variety Samsorg 17</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Metabolite (mg/gDW)</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>sucrose</th>\n",
       "      <td>3.425606</td>\n",
       "      <td>7.439446</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>glucose</th>\n",
       "      <td>38.347107</td>\n",
       "      <td>40.247934</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fructose</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.401372</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ASP</th>\n",
       "      <td>0.055392</td>\n",
       "      <td>0.045588</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SER</th>\n",
       "      <td>0.035772</td>\n",
       "      <td>0.026016</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>THR</th>\n",
       "      <td>0.403252</td>\n",
       "      <td>0.183740</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ASN</th>\n",
       "      <td>1.547059</td>\n",
       "      <td>0.864706</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PRO</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PHE</th>\n",
       "      <td>0.018864</td>\n",
       "      <td>0.009773</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TYR</th>\n",
       "      <td>0.035714</td>\n",
       "      <td>0.032418</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TRP</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     variery Samsorg 40  variety Samsorg 17\n",
       "Metabolite (mg/gDW)                                        \n",
       "sucrose                        3.425606            7.439446\n",
       "glucose                       38.347107           40.247934\n",
       "fructose                       0.000000            0.401372\n",
       "ASP                            0.055392            0.045588\n",
       "SER                            0.035772            0.026016\n",
       "THR                            0.403252            0.183740\n",
       "ASN                            1.547059            0.864706\n",
       "PRO                            0.000000            0.000000\n",
       "PHE                            0.018864            0.009773\n",
       "TYR                            0.035714            0.032418\n",
       "TRP                            0.000000            0.000000"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_leaf_content_1 = pd.DataFrame(data={\"Metabolite (mg/gDW)\":[\"sucrose\",\"glucose\",\"fructose\",\n",
    "                                                              \"ASP\",\"SER\",\n",
    "                                                              \"THR\",\"ASN\",\n",
    "                                                              \"PRO\",\"PHE\",\n",
    "                                                              \"TYR\",\"TRP\"],\n",
    "                                       \"variety Samsorg 17\":[7.43944636678199,40.2479338842975,0.401372212692967,\n",
    "                                                             0.0455882352941172,0.0260162601625953,\n",
    "                                                             0.18373983739837,0.864705882352938,\n",
    "                                                             0,0.00977272727272728,\n",
    "                                                             0.0324175824175804,0],\n",
    "                                       \"variery Samsorg 40\":[3.42560553633216,38.3471074380165,0,\n",
    "                                                             0.0553921568627444,0.0357723577235695,\n",
    "                                                             0.403252032520321,1.54705882352941,\n",
    "                                                             0,0.0188636363636364,\n",
    "                                                             0.0357142857142827,0]})\n",
    "df_leaf_content_1.set_index(\"Metabolite (mg/gDW)\",drop=True,inplace=True)\n",
    "df_leaf_content_1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Gathered soluble sugar, starch, cellulose, hemicellulose and lignin content from Wang et al 2013, Table 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Cellulose (mg/gDW)</th>\n",
       "      <th>Hemicellulose (mg/gDW)</th>\n",
       "      <th>Lignin (mg/gDW)</th>\n",
       "      <th>Soluble sugar (mg/gDW)</th>\n",
       "      <th>Starch (mg/gDW)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>247.6</td>\n",
       "      <td>219.7</td>\n",
       "      <td>13.2</td>\n",
       "      <td>69.3</td>\n",
       "      <td>10.7</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Cellulose (mg/gDW)  Hemicellulose (mg/gDW)  Lignin (mg/gDW)  \\\n",
       "0               247.6                   219.7             13.2   \n",
       "\n",
       "   Soluble sugar (mg/gDW)  Starch (mg/gDW)  \n",
       "0                    69.3             10.7  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_leaf_content_2 = pd.DataFrame(data={\"Soluble sugar (mg/gDW)\":[69.3],\"Starch (mg/gDW)\":[10.7],\n",
    "                                       \"Cellulose (mg/gDW)\":[247.6],\"Hemicellulose (mg/gDW)\":[219.7],\n",
    "                                       \"Lignin (mg/gDW)\":[13.2]})\n",
    "df_leaf_content_2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Extracted phospholipid content from Vanhercke et al 2019 Figure 4\n",
    "\n",
    "<img src=\"references/Screenshot_20190715_130438.png\" height=100% width=100%>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>DAG (mmol/gDW)</th>\n",
       "      <th>DGDG (mmol/gDW)</th>\n",
       "      <th>LPC (mmol/gDW)</th>\n",
       "      <th>MGDG (mmol/gDW)</th>\n",
       "      <th>PC (mmol/gDW)</th>\n",
       "      <th>TAG (mmol/gDW)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>4.71831</td>\n",
       "      <td>14.225352</td>\n",
       "      <td>0.985915</td>\n",
       "      <td>13.873239</td>\n",
       "      <td>4.71831</td>\n",
       "      <td>0.84507</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   DAG (mmol/gDW)  DGDG (mmol/gDW)  LPC (mmol/gDW)  MGDG (mmol/gDW)  \\\n",
       "0         4.71831        14.225352        0.985915        13.873239   \n",
       "\n",
       "   PC (mmol/gDW)  TAG (mmol/gDW)  \n",
       "0        4.71831         0.84507  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_leaf_content_3 = pd.DataFrame(data={\"DAG (mmol/gDW)\":[4.71830985915491],\"DGDG (mmol/gDW)\":[14.2253521126762],\n",
    "                                       \"LPC (mmol/gDW)\":[0.985915492957744],\"MGDG (mmol/gDW)\":[13.8732394366197],\n",
    "                                       \"PC (mmol/gDW)\":[4.71830985915491],\"TAG (mmol/gDW)\":[0.845070422535294]})\n",
    "\n",
    "df_leaf_content_3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>nmol/mgDW</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>C16:0</th>\n",
       "      <td>13.737596</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C16:1</th>\n",
       "      <td>22.844542</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C16:2</th>\n",
       "      <td>0.771775</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C16:3</th>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C18:0</th>\n",
       "      <td>1.190739</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C18:1</th>\n",
       "      <td>26.085998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C18:2</th>\n",
       "      <td>17.816979</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C18:3</th>\n",
       "      <td>0.859978</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C20:0</th>\n",
       "      <td>0.330761</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C20:1</th>\n",
       "      <td>0.705623</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       nmol/mgDW\n",
       "                \n",
       "C16:0  13.737596\n",
       "C16:1  22.844542\n",
       "C16:2   0.771775\n",
       "C16:3   0.000000\n",
       "C18:0   1.190739\n",
       "C18:1  26.085998\n",
       "C18:2  17.816979\n",
       "C18:3   0.859978\n",
       "C20:0   0.330761\n",
       "C20:1   0.705623"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_leaf_content_5_pre = pd.DataFrame(data={\"TAG fatty acid\":[\"C48:0\",\"C48:1\",\"C48:2\",\"C48:3\",\"C50:0\",\n",
    "                                                         \"C50:1\",\"C50:2\",\"C50:3\",\"C52:1\",\"C52:2\",\n",
    "                                                         \"C52:3\",\"C52:4\",\"C52:5\",\"C52:6\",\"C54:1\",\n",
    "                                                         \"C54:2\",\"C54:3\",\"C54:4\",\"C54:5\",\"C54:6\",\n",
    "                                                         \"C54:7\",\"C54:8\",\"C54:9\",\"C56:1\",\"C56:2\",\n",
    "                                                         \"C56:3\",\"C56:4\",\"C56:5\",\"C56:6\"],\n",
    "                                       \"nmol/mgDW\":[0.55126791620728,0.396912899669241,0.066152149944874,\n",
    "                                                       0.022050716648291,0.110253583241457,1.12458654906285,\n",
    "                                                       7.1664829106946,2.80044101433297,0.286659316427784,\n",
    "                                                       1.30099228224917,1.56560088202867,4.27783902976847,\n",
    "                                                       3.63836824696803,0.77177508269019,0.110253583241457,\n",
    "                                                       0.507166482910698,0.242557883131201,0.573318632855572,\n",
    "                                                       0.529217199558989,0.463065049614115,0.374862183020949,\n",
    "                                                       0.15435501653804,0.044101433296583,0.066152149944874,\n",
    "                                                       0.264608599779492,0.15435501653804,0.264608599779497,\n",
    "                                                       0.242557883131205,0.044101433296583],\n",
    "                                       \"C16:0\":[3,2,1,0,2,2,1,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0],\n",
    "                                       \"C16:1\":[0,1,2,3,0,0,1,2,0,0,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0],\n",
    "                                       \"C16:2\":[0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0],\n",
    "                                       \"C16:3\":[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0],\n",
    "                                       \"C18:0\":[0,0,0,0,1,0,0,0,1,0,0,0,0,0,2,1,0,0,0,0,0,0,0,1,0,0,0,0,0],\n",
    "                                       \"C18:1\":[0,0,0,0,0,1,1,1,1,2,2,1,0,0,1,2,3,2,1,0,0,0,0,1,2,2,1,0,0],\n",
    "                                       \"C18:2\":[0,0,0,0,0,0,0,0,0,0,0,1,2,2,0,0,0,1,2,3,2,1,0,0,0,0,1,2,1],\n",
    "                                       \"C18:3\":[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,2,3,0,0,0,0,0,1],\n",
    "                                       \"C20:0\":[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0],\n",
    "                                       \"C20:1\":[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1]})\n",
    "df_leaf_content_5_proc = pd.DataFrame(data={\"\":df_leaf_content_5_pre.columns[0:10]})\n",
    "tempList = list()\n",
    "for cols in df_leaf_content_5_pre.columns[0:10]:\n",
    "    tot = 0\n",
    "    for i in range(0,len(df_leaf_content_5_pre)):\n",
    "        tot = tot + (df_leaf_content_5_pre[cols][i]*df_leaf_content_5_pre[\"nmol/mgDW\"][i])\n",
    "    tempList.append(tot)\n",
    "df_leaf_content_5_proc[\"nmol/mgDW\"]=tempList\n",
    "df_leaf_content_5_proc.set_index(\"\",drop=True,inplace=True)\n",
    "df_leaf_content_5_proc"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Estimate starch content using starch:sucrose ratio at dusk (from Lunn and Hatch 1995) and sucrose content (from Ogbaga et al 2016)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "        vertical-align: middle;\n",
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       "\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Starch from Lunn and Hatch 1995 &amp; Ogbaga et al 2016</th>\n",
       "      <th>Starch from Wang et al 2013 &amp; Ogbaga et al 2016</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>25.634732</td>\n",
       "      <td>6.937357</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Starch from Lunn and Hatch 1995 & Ogbaga et al 2016  \\\n",
       "0                                          25.634732     \n",
       "\n",
       "   Starch from Wang et al 2013 & Ogbaga et al 2016  \n",
       "0                                         6.937357  "
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "starch_mass = df_matureleaf_content_1[\"Starch (umol hexose/mgChl)\"][1]* \\\n",
    "                                                    model.metabolites.get_by_id(\"GLC_c\").formula_weight\n",
    "sucrose_mass = df_matureleaf_content_1[\"Sucrose (umol hexose/mgChl)\"][1]* \\\n",
    "                                                    model.metabolites.get_by_id(\"GLC_c\").formula_weight\n",
    "\n",
    "starch_mass2 = df_leaf_content_2[\"Starch (mg/gDW)\"][0]\n",
    "sucrose_mass2 = df_leaf_content_2[\"Soluble sugar (mg/gDW)\"][0]\n",
    "    \n",
    "\n",
    "df_leaf_content_4 = pd.DataFrame(data={\"Starch from Lunn and Hatch 1995 & Ogbaga et al 2016\":\n",
    "                                       [find_average(df_leaf_content_1.loc[\"sucrose\"])*starch_mass/sucrose_mass],\n",
    "                                       \"Starch from Wang et al 2013 & Ogbaga et al 2016\":\n",
    "                                       [(find_average(df_leaf_content_1.loc[\"sucrose\"])+\n",
    "                                         find_average(df_leaf_content_1.loc[\"glucose\"])+\n",
    "                                         find_average(df_leaf_content_1.loc[\"fructose\"]))*starch_mass2/sucrose_mass2]})\n",
    "df_leaf_content_4"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Summary\n",
    "\n",
    "- Soluble sugar and amino acid data from Ogbaga et al 2016\n",
    "- Phospholipid content was gathered from Vanhercke et al 2019\n",
    "\n",
    "Assumptions\n",
    "\n",
    "- Soluble sucrose content data from Ogbaga et al 2016 and Wang et al 2013 are very different. Values from the latter study was used to scale down, cellulose, hemicellulose and lignin\n",
    "- Starch content predicted from Lunn and Hatch 1995 & Ogbaga et al 2016 is drastically different from that predicted from Starch from Wang et al 2013 & Ogbaga et al 2016. Values from the former was used for biomass."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "biomass.at[\"sSUCROSE_b\",\"leaf\"]=find_average(df_leaf_content_1.loc[\"sucrose\"])/ \\\n",
    "model.metabolites.get_by_id(\"SUCROSE_c\").formula_weight\n",
    "\n",
    "biomass.at[\"Starch_b\",\"leaf\"]=df_leaf_content_4[\"Starch from Lunn and Hatch 1995 & Ogbaga et al 2016\"][0]/ \\\n",
    "                              model.metabolites.get_by_id(\"STARCH_p\").formula_weight\n",
    "\n",
    "biomass.at[\"GLC_c\",\"leaf\"]=find_average(df_leaf_content_1.loc[\"glucose\"])/ \\\n",
    "model.metabolites.get_by_id(\"GLC_c\").formula_weight\n",
    "biomass.at[\"FRU_c\",\"leaf\"]=find_average(df_leaf_content_1.loc[\"fructose\"])/ \\\n",
    "model.metabolites.get_by_id(\"FRU_c\").formula_weight\n",
    "\n",
    "starch_mass2 = df_leaf_content_2[\"Starch (mg/gDW)\"][0]\n",
    "sucrose_mass2 = df_leaf_content_2[\"Soluble sugar (mg/gDW)\"][0]\n",
    "biomass.at[\"Cellulose_b\",\"leaf\"]=df_leaf_content_2[\"Cellulose (mg/gDW)\"]*(starch_mass2/sucrose_mass2)/ \\\n",
    "                                 model.metabolites.get_by_id(\"STARCH_p\").formula_weight\n",
    "\n",
    "biomass.at[\"DIACYLGLYCEROL_r\",\"leaf\"]=df_leaf_content_3[\"DAG (mmol/gDW)\"][0]\n",
    "biomass.at[\"PHOSPHATIDYL_CHOLINE_r\",\"leaf\"]=df_leaf_content_3[\"PC (mmol/gDW)\"][0]\n",
    "biomass.at[\"D_Galactosyl_12_diacyl_glycerols_p\",\"leaf\"]=df_leaf_content_3[\"DGDG (mmol/gDW)\"][0]\n",
    "biomass.at[\"2_Lysophosphatidylcholines_r\",\"leaf\"]=df_leaf_content_3[\"LPC (mmol/gDW)\"][0]\n",
    "biomass.at[\"Galactosyl_galactosyl_diacyl_glycerols_p\",\"leaf\"]=df_leaf_content_3[\"MGDG (mmol/gDW)\"][0]\n",
    "biomass.at[\"Triacylglycerols_p\",\"leaf\"]=df_leaf_content_3[\"TAG (mmol/gDW)\"][0]\n",
    "biomass.at[\"PALMITATE_p\",\"leaf\"]=df_leaf_content_5_proc[\"nmol/mgDW\"][\"C16:0\"]\n",
    "biomass.at[\"CPD_9245_p\",\"leaf\"]=df_leaf_content_5_proc[\"nmol/mgDW\"][\"C16:1\"]\n",
    "biomass.at[\"CPD_17412_p\",\"leaf\"]=df_leaf_content_5_proc[\"nmol/mgDW\"][\"C16:2\"]\n",
    "biomass.at[\"STEARIC_ACID_p\",\"leaf\"]=df_leaf_content_5_proc[\"nmol/mgDW\"][\"C18:0\"]\n",
    "biomass.at[\"OLEATE_CPD_p\",\"leaf\"]=df_leaf_content_5_proc[\"nmol/mgDW\"][\"C18:1\"]\n",
    "biomass.at[\"Octadecadienoate_p\",\"leaf\"]=df_leaf_content_5_proc[\"nmol/mgDW\"][\"C18:2\"]\n",
    "biomass.at[\"LINOLENIC)ACID_p\",\"leaf\"]=df_leaf_content_5_proc[\"nmol/mgDW\"][\"C18:3\"]\n",
    "biomass.at[\"ARACHIDIC_ACID_p\",\"leaf\"]=df_leaf_content_5_proc[\"nmol/mgDW\"][\"C20:0\"]\n",
    "biomass.at[\"CPD_16709_ACID_p\",\"leaf\"]=df_leaf_content_5_proc[\"nmol/mgDW\"][\"C20:1\"]\n",
    "\n",
    "biomass.at[\"sASP_b\",\"leaf\"]=find_average(df_leaf_content_1.loc[\"ASP\"])/ \\\n",
    "model.metabolites.get_by_id(\"L_ASPARTATE_c\").formula_weight\n",
    "biomass.at[\"sSER_b\",\"leaf\"]=find_average(df_leaf_content_1.loc[\"SER\"])/ \\\n",
    "model.metabolites.get_by_id(\"SER_c\").formula_weight\n",
    "biomass.at[\"THR_c\",\"leaf\"]=find_average(df_leaf_content_1.loc[\"THR\"])/ \\\n",
    "model.metabolites.get_by_id(\"THR_c\").formula_weight\n",
    "biomass.at[\"ASN_c\",\"leaf\"]=find_average(df_leaf_content_1.loc[\"ASN\"])/ \\\n",
    "model.metabolites.get_by_id(\"ASN_c\").formula_weight\n",
    "biomass.at[\"PHE_c\",\"leaf\"]=find_average(df_leaf_content_1.loc[\"PHE\"])/ \\\n",
    "model.metabolites.get_by_id(\"PHE_c\").formula_weight\n",
    "biomass.at[\"TYR_c\",\"leaf\"]=find_average(df_leaf_content_1.loc[\"TYR\"])/ \\\n",
    "model.metabolites.get_by_id(\"TYR_c\").formula_weight\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Stem\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Extracted sucrose, glucose and fructose content from Njokweni 2015, Figure 3.1 and Figure 3.2\n",
    "\n",
    "<img src=\"references/Screenshot_20190715_165703.png\" height=50% width=50%>\n",
    "\n",
    "<img src=\"references/Screenshot_20190715_170255.png\" height=50% width=50%>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Fructose (g/L)</th>\n",
       "      <th>Glucose (g/L)</th>\n",
       "      <th>Starch (g/L)</th>\n",
       "      <th>Sucrose (g/L)</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>strain</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>ICSB338</th>\n",
       "      <td>63.220974</td>\n",
       "      <td>8.131868</td>\n",
       "      <td>11.291139</td>\n",
       "      <td>10.673077</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ICSB73</th>\n",
       "      <td>21.647940</td>\n",
       "      <td>2.857143</td>\n",
       "      <td>6.187342</td>\n",
       "      <td>17.788462</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ICSV213</th>\n",
       "      <td>89.063670</td>\n",
       "      <td>12.252747</td>\n",
       "      <td>5.367089</td>\n",
       "      <td>9.182692</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>S35</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.494505</td>\n",
       "      <td>4.911392</td>\n",
       "      <td>0.048077</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Fructose (g/L)  Glucose (g/L)  Starch (g/L)  Sucrose (g/L)\n",
       "strain                                                             \n",
       "ICSB338       63.220974       8.131868     11.291139      10.673077\n",
       "ICSB73        21.647940       2.857143      6.187342      17.788462\n",
       "ICSV213       89.063670      12.252747      5.367089       9.182692\n",
       "S35            0.000000       0.494505      4.911392       0.048077"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_stem_content_1 = pd.DataFrame(data={\"strain\":[\"ICSB338\",\"ICSB73\",\"ICSV213\",\"S35\"],\n",
    "                                       \"Sucrose (g/L)\":[10.6730769230769,17.7884615384615,\n",
    "                                                        9.18269230769231,0.048076923076926],\n",
    "                                       \"Glucose (g/L)\":[8.13186813186791,2.8571428571426,\n",
    "                                                        12.2527472527471,0.494505494505204],\n",
    "                                       \"Fructose (g/L)\":[63.22097378277,21.6479400749044,\n",
    "                                                         89.0636704119839,0],\n",
    "                                       \"Starch (g/L)\":[11.2911392405063,6.1873417721519,\n",
    "                                                       5.36708860759494,4.91139240506329]})\n",
    "df_stem_content_1.set_index(\"strain\",drop=True,inplace=True)\n",
    "df_stem_content_1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Extracted sucrose, starch, glucose, fructose, protein, arabinan, galactan, lignin, xylan and cellulose content of -6 DPA stem from McKinley et al 2016 Figure 3\n",
    "\n",
    "<img src=\"references/Screenshot_20190715_170731.png\" height=75% width=75%>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>-6 DPA (g/100gDW)</th>\n",
       "      <th>-6 DPA (mg/gDW)</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Metabolites</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>sucrose</th>\n",
       "      <td>3.656148</td>\n",
       "      <td>36.561480</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>starch</th>\n",
       "      <td>2.487874</td>\n",
       "      <td>24.878743</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>glucose</th>\n",
       "      <td>8.291621</td>\n",
       "      <td>82.916213</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fructose</th>\n",
       "      <td>6.985854</td>\n",
       "      <td>69.858542</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>protein</th>\n",
       "      <td>1.632209</td>\n",
       "      <td>16.322089</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>arabinan</th>\n",
       "      <td>1.175190</td>\n",
       "      <td>11.751904</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>galactan</th>\n",
       "      <td>0.457018</td>\n",
       "      <td>4.570185</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>lignin</th>\n",
       "      <td>11.882481</td>\n",
       "      <td>118.824810</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>xylan</th>\n",
       "      <td>14.820457</td>\n",
       "      <td>148.204570</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cellulose</th>\n",
       "      <td>28.803047</td>\n",
       "      <td>288.030468</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             -6 DPA (g/100gDW)  -6 DPA (mg/gDW)\n",
       "Metabolites                                    \n",
       "sucrose               3.656148        36.561480\n",
       "starch                2.487874        24.878743\n",
       "glucose               8.291621        82.916213\n",
       "fructose              6.985854        69.858542\n",
       "protein               1.632209        16.322089\n",
       "arabinan              1.175190        11.751904\n",
       "galactan              0.457018         4.570185\n",
       "lignin               11.882481       118.824810\n",
       "xylan                14.820457       148.204570\n",
       "cellulose            28.803047       288.030468"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_stem_content_2 = pd.DataFrame(data={\"Metabolites\":[\"sucrose\",\"starch\",\"glucose\",\"fructose\",\"protein\",\n",
    "                                                      \"arabinan\",\"galactan\",\"lignin\",\"xylan\",\"cellulose\"],\n",
    "                                       \"-6 DPA (g/100gDW)\":[3.65614798694232,2.48787426500548,8.29162132752991,6.98585418933624,\n",
    "                                                 1.63220892274211,1.17519042437434,0.457018498367745,11.8824809575626,\n",
    "                                                 14.8204570184984,28.8030467899891]})\n",
    "df_stem_content_2.set_index(\"Metabolites\",drop=True,inplace=True)\n",
    "df_stem_content_2[\"-6 DPA (mg/gDW)\"]=df_stem_content_2[\"-6 DPA (g/100gDW)\"]*10\n",
    "df_stem_content_2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Retrieved average soluble sugar, starch, hemicellulose, cellulose and lignin content from Arai-Sanoh et al 2011, Table 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>cellulose (mg/gDW)</th>\n",
       "      <th>hemicellulose (mg/gDW)</th>\n",
       "      <th>lignin (mg/gDW)</th>\n",
       "      <th>soluble sugar (mg/gDW)</th>\n",
       "      <th>starch (mg/gDW)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>305</td>\n",
       "      <td>164</td>\n",
       "      <td>128</td>\n",
       "      <td>256</td>\n",
       "      <td>28</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   cellulose (mg/gDW)  hemicellulose (mg/gDW)  lignin (mg/gDW)  \\\n",
       "0                 305                     164              128   \n",
       "\n",
       "   soluble sugar (mg/gDW)  starch (mg/gDW)  \n",
       "0                     256               28  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_stem_content_3 = pd.DataFrame(data={\"soluble sugar (mg/gDW)\":[256],\"starch (mg/gDW)\":[28],\n",
    "                                       \"hemicellulose (mg/gDW)\":[164],\"cellulose (mg/gDW)\":[305],\n",
    "                                       \"lignin (mg/gDW)\":[128]})\n",
    "df_stem_content_3"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Gathered soluble sugar, starch, cellulose, hemicellulose and lignin content from Wang et al 2013, Table 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Cellulose (mg/gDW)</th>\n",
       "      <th>Hemicellulose (mg/gDW)</th>\n",
       "      <th>Lignin (mg/gDW)</th>\n",
       "      <th>Soluble sugar (mg/gDW)</th>\n",
       "      <th>Starch (mg/gDW)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>281.8</td>\n",
       "      <td>251.3</td>\n",
       "      <td>32.5</td>\n",
       "      <td>157.0</td>\n",
       "      <td>9.8</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Cellulose (mg/gDW)  Hemicellulose (mg/gDW)  Lignin (mg/gDW)  \\\n",
       "0               281.8                   251.3             32.5   \n",
       "\n",
       "   Soluble sugar (mg/gDW)  Starch (mg/gDW)  \n",
       "0                   157.0              9.8  "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_stem_content_4 = pd.DataFrame(data={\"Soluble sugar (mg/gDW)\":[157.0],\"Starch (mg/gDW)\":[9.8],\n",
    "                                       \"Cellulose (mg/gDW)\":[281.8],\"Hemicellulose (mg/gDW)\":[251.3],\n",
    "                                       \"Lignin (mg/gDW)\":[32.5]})\n",
    "df_stem_content_4"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Gathered sucrose, fructose, glucose, amino acids, organic acids, trehalose, maltose, mannitol, mannose, galactose and raffinose relative abundance from Njokweni 2015 table 2.1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Ala</th>\n",
       "      <th>Asp</th>\n",
       "      <th>Fructose</th>\n",
       "      <th>Galactose</th>\n",
       "      <th>Gln</th>\n",
       "      <th>Glucose</th>\n",
       "      <th>Gly</th>\n",
       "      <th>Leu</th>\n",
       "      <th>Malate</th>\n",
       "      <th>Mannitol</th>\n",
       "      <th>Mannose</th>\n",
       "      <th>Pro</th>\n",
       "      <th>Raffinose</th>\n",
       "      <th>Ser</th>\n",
       "      <th>Sucrose</th>\n",
       "      <th>Trehalose</th>\n",
       "      <th>Val</th>\n",
       "      <th>maltose</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>strain</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>ICSB338</th>\n",
       "      <td>9.02</td>\n",
       "      <td>1.45</td>\n",
       "      <td>1.87</td>\n",
       "      <td>2.16</td>\n",
       "      <td>0.25</td>\n",
       "      <td>2.60</td>\n",
       "      <td>0.61</td>\n",
       "      <td>8.7</td>\n",
       "      <td>7.28</td>\n",
       "      <td>3.12</td>\n",
       "      <td>0.31</td>\n",
       "      <td>0.16</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.46</td>\n",
       "      <td>61.8</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.34</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ICSB73</th>\n",
       "      <td>2.55</td>\n",
       "      <td>0.34</td>\n",
       "      <td>7.49</td>\n",
       "      <td>7.05</td>\n",
       "      <td>0.00</td>\n",
       "      <td>8.63</td>\n",
       "      <td>0.24</td>\n",
       "      <td>4.8</td>\n",
       "      <td>5.22</td>\n",
       "      <td>1.72</td>\n",
       "      <td>4.02</td>\n",
       "      <td>0.14</td>\n",
       "      <td>0.21</td>\n",
       "      <td>0.26</td>\n",
       "      <td>64.5</td>\n",
       "      <td>0.89</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.61</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ICSV213</th>\n",
       "      <td>3.70</td>\n",
       "      <td>1.57</td>\n",
       "      <td>1.18</td>\n",
       "      <td>1.13</td>\n",
       "      <td>0.16</td>\n",
       "      <td>1.35</td>\n",
       "      <td>0.20</td>\n",
       "      <td>49.4</td>\n",
       "      <td>7.28</td>\n",
       "      <td>0.18</td>\n",
       "      <td>0.27</td>\n",
       "      <td>1.01</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.81</td>\n",
       "      <td>94.1</td>\n",
       "      <td>0.82</td>\n",
       "      <td>12.60</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>S35</th>\n",
       "      <td>1.93</td>\n",
       "      <td>1.88</td>\n",
       "      <td>6.70</td>\n",
       "      <td>0.24</td>\n",
       "      <td>0.23</td>\n",
       "      <td>2.17</td>\n",
       "      <td>0.15</td>\n",
       "      <td>25.0</td>\n",
       "      <td>3.78</td>\n",
       "      <td>0.17</td>\n",
       "      <td>1.12</td>\n",
       "      <td>0.70</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.45</td>\n",
       "      <td>39.2</td>\n",
       "      <td>0.41</td>\n",
       "      <td>1.25</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          Ala   Asp  Fructose  Galactose   Gln  Glucose   Gly   Leu  Malate  \\\n",
       "strain                                                                        \n",
       "ICSB338  9.02  1.45      1.87       2.16  0.25     2.60  0.61   8.7    7.28   \n",
       "ICSB73   2.55  0.34      7.49       7.05  0.00     8.63  0.24   4.8    5.22   \n",
       "ICSV213  3.70  1.57      1.18       1.13  0.16     1.35  0.20  49.4    7.28   \n",
       "S35      1.93  1.88      6.70       0.24  0.23     2.17  0.15  25.0    3.78   \n",
       "\n",
       "         Mannitol  Mannose   Pro  Raffinose   Ser  Sucrose  Trehalose    Val  \\\n",
       "strain                                                                         \n",
       "ICSB338      3.12     0.31  0.16       0.00  1.46     61.8       0.00   0.34   \n",
       "ICSB73       1.72     4.02  0.14       0.21  0.26     64.5       0.89   0.00   \n",
       "ICSV213      0.18     0.27  1.01       0.00  1.81     94.1       0.82  12.60   \n",
       "S35          0.17     1.12  0.70       0.00  1.45     39.2       0.41   1.25   \n",
       "\n",
       "         maltose  \n",
       "strain            \n",
       "ICSB338     0.00  \n",
       "ICSB73      0.61  \n",
       "ICSV213     0.00  \n",
       "S35         0.00  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_stem_content_5 = pd.DataFrame(data={\"strain\":[\"ICSB338\",\"ICSB73\",\"ICSV213\",\"S35\"],\n",
    "                                       \"Ala\":[9.02,2.55,3.7,1.93],\n",
    "                                       \"Val\":[0.34,0,12.6,1.25],\n",
    "                                       \"Ser\":[1.46,0.26,1.81,1.45],\n",
    "                                       \"Pro\":[0.16,0.14,1.01,0.7],\n",
    "                                       \"Gln\":[0.25,0,0.16,0.23],\n",
    "                                       \"Leu\":[8.7,4.8,49.4,25],\n",
    "                                       \"Gly\":[0.61,0.24,0.2,0.15],\n",
    "                                       \"Asp\":[1.45,0.34,1.57,1.88],\n",
    "                                       \"Malate\":[7.28,5.22,7.28,3.78],\n",
    "                                       \"Trehalose\":[0,0.89,0.82,0.41],\n",
    "                                       \"maltose\":[0,0.61,0,0],\n",
    "                                       \"Mannitol\":[3.12,1.72,0.18,0.17],\n",
    "                                       \"Mannose\":[0.31,4.02,0.27,1.12],\n",
    "                                       \"Galactose\":[2.16,7.05,1.13,0.24],\n",
    "                                       \"Raffinose\":[0,0.21,0,0],\n",
    "                                       \"Glucose\":[2.6,8.63,1.35,2.17],\n",
    "                                       \"Fructose\":[1.87,7.49,1.18,6.7],\n",
    "                                       \"Sucrose\":[61.8,64.5,94.1,39.2]})\n",
    "df_stem_content_5.set_index(\"strain\",drop=True,inplace=True)\n",
    "df_stem_content_5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "biomass.at[\"sSUCROSE_b\",\"stem\"] =  df_stem_content_2.at[\"sucrose\",\"-6 DPA (mg/gDW)\"]/ \\\n",
    "                                       model.metabolites.get_by_id(\"SUCROSE_c\").formula_weight\n",
    "biomass.at[\"GLC_c\",\"stem\"]=df_stem_content_2.at[\"glucose\",\"-6 DPA (mg/gDW)\"]/ \\\n",
    "                                       model.metabolites.get_by_id(\"GLC_c\").formula_weight\n",
    "biomass.at[\"FRU_c\",\"stem\"]=df_stem_content_2.at[\"fructose\",\"-6 DPA (mg/gDW)\"]/ \\\n",
    "                                       model.metabolites.get_by_id(\"FRU_c\").formula_weight\n",
    "biomass.at[\"Cellulose_b\",\"stem\"]=df_stem_content_2.at[\"cellulose\",\"-6 DPA (mg/gDW)\"]/ \\\n",
    "                                       model.metabolites.get_by_id(\"STARCH_p\").formula_weight\n",
    "\n",
    "#scaling=find_average(df_stem_content_5[\"Malate\"])/find_average(df_stem_content_5[\"Glucose\"])\n",
    "#biomass.at[\"sMAL_b\",\"stem\"] =scaling*df_stem_content_2.at[\"glucose\",\"-6 DPA (mg/gDW)\"]/ \\\n",
    "#                                       model.metabolites.get_by_id(\"MAL_c\").formula_weight\n",
    "#\n",
    "#scaling=find_average(df_stem_content_5[\"Asp\"])/find_average(df_stem_content_5[\"Glucose\"])\n",
    "#biomass.at[\"sASP_b\",\"stem\"]=scaling*df_stem_content_2.at[\"glucose\",\"-6 DPA (mg/gDW)\"]/ \\\n",
    "#                                       model.metabolites.get_by_id(\"L_ASPARTATE_c\").formula_weight\n",
    "#\n",
    "#scaling=find_average(df_stem_content_5[\"Ser\"])/find_average(df_stem_content_5[\"Glucose\"])\n",
    "#biomass.at[\"sSER_b\",\"stem\"]=scaling*df_stem_content_2.at[\"glucose\",\"-6 DPA (mg/gDW)\"]/ \\\n",
    "#                                       model.metabolites.get_by_id(\"SER_c\").formula_weight\n",
    "#\n",
    "#scaling=find_average(df_stem_content_5[\"Gln\"])/find_average(df_stem_content_5[\"Glucose\"])\n",
    "#biomass.at[\"sGLN_b\",\"stem\"]=scaling*df_stem_content_2.at[\"glucose\",\"-6 DPA (mg/gDW)\"]/ \\\n",
    "#                                       model.metabolites.get_by_id(\"GLN_c\").formula_weight\n",
    "#\n",
    "#scaling=find_average(df_stem_content_5[\"Gly\"])/find_average(df_stem_content_5[\"Glucose\"])\n",
    "#biomass.at[\"GLY_c\",\"stem\"]=scaling*df_stem_content_2.at[\"glucose\",\"-6 DPA (mg/gDW)\"]/ \\\n",
    "#                                       model.metabolites.get_by_id(\"PRO_c\").formula_weight\n",
    "#\n",
    "#scaling=find_average(df_stem_content_5[\"Ala\"])/find_average(df_stem_content_5[\"Glucose\"])    \n",
    "#biomass.at[\"sALA_b\",\"stem\"]=scaling*df_stem_content_2.at[\"glucose\",\"-6 DPA (mg/gDW)\"]/ \\\n",
    "#                                       model.metabolites.get_by_id(\"L_ALPHA_ALANINE_c\").formula_weight\n",
    "#\n",
    "#scaling=find_average(df_stem_content_5[\"Val\"])/find_average(df_stem_content_5[\"Glucose\"])    \n",
    "#biomass.at[\"VAL_c\",\"stem\"]=scaling*df_stem_content_2.at[\"glucose\",\"-6 DPA (mg/gDW)\"]/ \\\n",
    "#                                       model.metabolites.get_by_id(\"VAL_c\").formula_weight\n",
    "#\n",
    "#scaling=find_average(df_stem_content_5[\"Leu\"])/find_average(df_stem_content_5[\"Glucose\"])    \n",
    "#biomass.at[\"LEU_c\",\"stem\"]=scaling*df_stem_content_2.at[\"glucose\",\"-6 DPA (mg/gDW)\"]/ \\\n",
    "#                                       model.metabolites.get_by_id(\"LEU_c\").formula_weight"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Summary\n",
    "\n",
    "- sucrose, glucose and fructose content from Njokweni 2015 are in g/L. Conversion to mg/gDW is not available and hence these data points are ignored\n",
    "\n",
    "Assumptions\n",
    "\n",
    "- Although r"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Root"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Retrieve sugar, amino acid and organic acid content from Cambria et al 1983, Table 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Amino acids (umoles/gFW)</th>\n",
       "      <th>Sugars (mg/gFW)</th>\n",
       "      <th>organic acids (ueq/gFW)</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Variety</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Al-sensitive</th>\n",
       "      <td>7.4</td>\n",
       "      <td>4.5</td>\n",
       "      <td>16.30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Al-tolerant</th>\n",
       "      <td>7.1</td>\n",
       "      <td>7.5</td>\n",
       "      <td>23.64</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              Amino acids (umoles/gFW)  Sugars (mg/gFW)  \\\n",
       "Variety                                                   \n",
       "Al-sensitive                       7.4              4.5   \n",
       "Al-tolerant                        7.1              7.5   \n",
       "\n",
       "              organic acids (ueq/gFW)  \n",
       "Variety                                \n",
       "Al-sensitive                    16.30  \n",
       "Al-tolerant                     23.64  "
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_root_content_1 = pd.DataFrame(data={\"Variety\":[\"Al-sensitive\",\"Al-tolerant\"],\n",
    "                                       \"Sugars (mg/gFW)\":[4.50,7.50],\n",
    "                                       \"Amino acids (umoles/gFW)\":[7.40,7.10],\n",
    "                                       \"organic acids (ueq/gFW)\":[16.3,23.64]})\n",
    "df_root_content_1.set_index(\"Variety\",drop=True,inplace=True)\n",
    "df_root_content_1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Retrieve organic acid content from Cambria et al 1983, Table 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Citric acid</th>\n",
       "      <th>Fumaric acid</th>\n",
       "      <th>Malic acid</th>\n",
       "      <th>Quinic acid</th>\n",
       "      <th>Succinic acid</th>\n",
       "      <th>Total</th>\n",
       "      <th>t-Aconitic acid</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Variety</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Al-sensitive</th>\n",
       "      <td>0.50</td>\n",
       "      <td>1.44</td>\n",
       "      <td>3.60</td>\n",
       "      <td>0.04</td>\n",
       "      <td>0.24</td>\n",
       "      <td>8.22</td>\n",
       "      <td>2.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Al-tolerant</th>\n",
       "      <td>0.61</td>\n",
       "      <td>1.70</td>\n",
       "      <td>6.53</td>\n",
       "      <td>0.17</td>\n",
       "      <td>0.17</td>\n",
       "      <td>18.68</td>\n",
       "      <td>9.5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              Citric acid  Fumaric acid  Malic acid  Quinic acid  \\\n",
       "Variety                                                            \n",
       "Al-sensitive         0.50          1.44        3.60         0.04   \n",
       "Al-tolerant          0.61          1.70        6.53         0.17   \n",
       "\n",
       "              Succinic acid  Total  t-Aconitic acid  \n",
       "Variety                                              \n",
       "Al-sensitive           0.24   8.22              2.4  \n",
       "Al-tolerant            0.17  18.68              9.5  "
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_root_content_2 = pd.DataFrame(data={\"Variety\":[\"Al-sensitive\",\"Al-tolerant\"],\n",
    "                                       \"Succinic acid\":[0.24,0.17],\n",
    "                                       \"Fumaric acid\":[1.44,1.70],\n",
    "                                       \"Malic acid\":[3.60,6.53],\n",
    "                                       \"t-Aconitic acid\":[2.40,9.50],\n",
    "                                       \"Quinic acid\":[0.04,0.17],\n",
    "                                       \"Citric acid\":[0.50,0.61],\n",
    "                                       \"Total\":[8.22,18.68]})\n",
    "df_root_content_2.set_index(\"Variety\",drop=True,inplace=True)\n",
    "df_root_content_2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Seed\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Retrieve soluble sugar, starch, cellulose, hemicellulose and lignin content from Wang et al 2013 Table 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Cellulose (mg/gDW)</th>\n",
       "      <th>Hemicellulose (mg/gDW)</th>\n",
       "      <th>Lignin (mg/gDW)</th>\n",
       "      <th>Soluble sugar (mg/gDW)</th>\n",
       "      <th>Starch (mg/gDW)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>43.7</td>\n",
       "      <td>147.2</td>\n",
       "      <td>8.1</td>\n",
       "      <td>52.3</td>\n",
       "      <td>395.2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Cellulose (mg/gDW)  Hemicellulose (mg/gDW)  Lignin (mg/gDW)  \\\n",
       "0                43.7                   147.2              8.1   \n",
       "\n",
       "   Soluble sugar (mg/gDW)  Starch (mg/gDW)  \n",
       "0                    52.3            395.2  "
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_seed_content_1 = pd.DataFrame(data={\"Soluble sugar (mg/gDW)\":[52.3],\"Starch (mg/gDW)\":[395.2],\n",
    "                                     \"Cellulose (mg/gDW)\":[43.7],\"Hemicellulose (mg/gDW)\":[147.2],\n",
    "                                     \"Lignin (mg/gDW)\":[8.1]})\n",
    "df_seed_content_1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Estimated FW/DW ratio from Neucere et al 1980, Table I"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1.13726828159\n"
     ]
    }
   ],
   "source": [
    "Moisture = 12.07\n",
    "DW = 100 - Moisture\n",
    "FW_DW_ratio = 100/DW\n",
    "print FW_DW_ratio\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Retrieved fructose, glucose, sucrose, maltose and raffinose content from Neucere et al 1980, Table I and IV"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>fat (mg/gDW)</th>\n",
       "      <th>fructose (mg/gDW)</th>\n",
       "      <th>glucose (mg/gDW)</th>\n",
       "      <th>maltose (mg/gDW)</th>\n",
       "      <th>protein (mg/gDW)</th>\n",
       "      <th>raffinose (mg/gDW)</th>\n",
       "      <th>sucrose (mg/gDW)</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>variety</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>SC301</th>\n",
       "      <td>26.64279</td>\n",
       "      <td>16.7</td>\n",
       "      <td>17.8</td>\n",
       "      <td>3.5</td>\n",
       "      <td>100.94364</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NSA740</th>\n",
       "      <td>30.68757</td>\n",
       "      <td>11.2</td>\n",
       "      <td>6.8</td>\n",
       "      <td>1.6</td>\n",
       "      <td>125.91576</td>\n",
       "      <td>0.3</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CK60</th>\n",
       "      <td>29.10483</td>\n",
       "      <td>23.2</td>\n",
       "      <td>20.0</td>\n",
       "      <td>2.3</td>\n",
       "      <td>87.05070</td>\n",
       "      <td>0.3</td>\n",
       "      <td>5.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TX615</th>\n",
       "      <td>23.38938</td>\n",
       "      <td>18.0</td>\n",
       "      <td>29.4</td>\n",
       "      <td>7.8</td>\n",
       "      <td>104.19705</td>\n",
       "      <td>1.1</td>\n",
       "      <td>3.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GA615</th>\n",
       "      <td>26.37900</td>\n",
       "      <td>10.6</td>\n",
       "      <td>8.7</td>\n",
       "      <td>0.6</td>\n",
       "      <td>85.73175</td>\n",
       "      <td>0.5</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         fat (mg/gDW)  fructose (mg/gDW)  glucose (mg/gDW)  maltose (mg/gDW)  \\\n",
       "variety                                                                        \n",
       "SC301        26.64279               16.7              17.8               3.5   \n",
       "NSA740       30.68757               11.2               6.8               1.6   \n",
       "CK60         29.10483               23.2              20.0               2.3   \n",
       "TX615        23.38938               18.0              29.4               7.8   \n",
       "GA615        26.37900               10.6               8.7               0.6   \n",
       "\n",
       "         protein (mg/gDW)  raffinose (mg/gDW)  sucrose (mg/gDW)  \n",
       "variety                                                          \n",
       "SC301           100.94364                 1.0               5.1  \n",
       "NSA740          125.91576                 0.3               3.0  \n",
       "CK60             87.05070                 0.3               5.8  \n",
       "TX615           104.19705                 1.1               3.8  \n",
       "GA615            85.73175                 0.5               3.0  "
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_seed_content_2 = pd.DataFrame(data={\"variety\":[\"SC301\",\"NSA740\",\"CK60\",\"TX615\",\"GA615\"],\n",
    "                                       \"fructose (g/100gDW)\":[1.67,1.12,2.32,1.80,1.06],\n",
    "                                       \"glucose (g/100gDW)\":[1.78,0.68,2,2.94,0.87],\n",
    "                                       \"sucrose (g/100gDW)\":[0.51,0.30,0.58,0.38,0.30],\n",
    "                                       \"maltose (g/100gDW)\":[0.35,0.16,0.23,0.78,0.06],\n",
    "                                       \"raffinose (g/100gDW)\":[0.1,0.03,0.03,0.11,0.05],\n",
    "                                       \"protein (g/100gFW)\":[11.48,14.32,9.90,11.85,9.75],\n",
    "                                       \"fat (g/100gFW)\":[3.03,3.49,3.31,2.66,3.00]})\n",
    "df_seed_content_2_std = pd.DataFrame(data={\"variety\":[\"SC301\",\"NSA740\",\"CK60\",\"TX615\",\"GA615\"],\n",
    "                                           \"fructose (mg/gDW)\":df_seed_content_2[\"fructose (g/100gDW)\"]*10,\n",
    "                                           \"glucose (mg/gDW)\":df_seed_content_2[\"glucose (g/100gDW)\"]*10,\n",
    "                                           \"sucrose (mg/gDW)\":df_seed_content_2[\"sucrose (g/100gDW)\"]*10,\n",
    "                                           \"maltose (mg/gDW)\":df_seed_content_2[\"maltose (g/100gDW)\"]*10,\n",
    "                                           \"raffinose (mg/gDW)\":df_seed_content_2[\"raffinose (g/100gDW)\"]*10,\n",
    "                                           \"protein (mg/gDW)\":(df_seed_content_2[\"protein (g/100gFW)\"]*FW_DW_ratio)*10,\n",
    "                                           \"fat (mg/gDW)\":(df_seed_content_2[\"fat (g/100gFW)\"]*FW_DW_ratio)*10})\n",
    "\n",
    "df_seed_content_2_std.set_index(\"variety\",drop=True,inplace=True)\n",
    "df_seed_content_2_std"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Gather amino acid composition from Mosse, Huet and Baudet 1988"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Ala (mg/gDW)</th>\n",
       "      <th>Arg (mg/gDW)</th>\n",
       "      <th>Asp (mg/gDW)</th>\n",
       "      <th>Cys (mg/gDW)</th>\n",
       "      <th>Glt (mg/gDW)</th>\n",
       "      <th>Gly (mg/gDW)</th>\n",
       "      <th>His (mg/gDW)</th>\n",
       "      <th>Ile (mg/gDW)</th>\n",
       "      <th>Leu (mg/gDW)</th>\n",
       "      <th>Lys (mg/gDW)</th>\n",
       "      <th>Met (mg/gDW)</th>\n",
       "      <th>Phe (mg/gDW)</th>\n",
       "      <th>Pro (mg/gDW)</th>\n",
       "      <th>Ser (mg/gDW)</th>\n",
       "      <th>Thr (mg/gDW)</th>\n",
       "      <th>Trp (mg/gDW)</th>\n",
       "      <th>Tyr (mg/gDW)</th>\n",
       "      <th>Val (mg/gDW)</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>variety</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>8.588125</td>\n",
       "      <td>3.869375</td>\n",
       "      <td>67.0</td>\n",
       "      <td>1.014531</td>\n",
       "      <td>203.0</td>\n",
       "      <td>3.208750</td>\n",
       "      <td>2.170625</td>\n",
       "      <td>3.869375</td>\n",
       "      <td>11.985625</td>\n",
       "      <td>2.359375</td>\n",
       "      <td>1.887500</td>\n",
       "      <td>4.907500</td>\n",
       "      <td>7.644375</td>\n",
       "      <td>4.435625</td>\n",
       "      <td>3.161563</td>\n",
       "      <td>1.019250</td>\n",
       "      <td>3.680625</td>\n",
       "      <td>4.907500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>9.602500</td>\n",
       "      <td>4.175000</td>\n",
       "      <td>70.0</td>\n",
       "      <td>0.991562</td>\n",
       "      <td>210.0</td>\n",
       "      <td>3.287812</td>\n",
       "      <td>2.296250</td>\n",
       "      <td>4.488125</td>\n",
       "      <td>14.508125</td>\n",
       "      <td>2.400625</td>\n",
       "      <td>1.722187</td>\n",
       "      <td>5.740625</td>\n",
       "      <td>9.185000</td>\n",
       "      <td>4.801250</td>\n",
       "      <td>3.392188</td>\n",
       "      <td>1.075063</td>\n",
       "      <td>4.383750</td>\n",
       "      <td>5.740625</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>10.005000</td>\n",
       "      <td>4.350000</td>\n",
       "      <td>70.0</td>\n",
       "      <td>0.924375</td>\n",
       "      <td>208.0</td>\n",
       "      <td>3.316875</td>\n",
       "      <td>2.338125</td>\n",
       "      <td>4.567500</td>\n",
       "      <td>14.790000</td>\n",
       "      <td>2.501250</td>\n",
       "      <td>1.685625</td>\n",
       "      <td>5.872500</td>\n",
       "      <td>9.243750</td>\n",
       "      <td>4.893750</td>\n",
       "      <td>3.425625</td>\n",
       "      <td>1.087500</td>\n",
       "      <td>4.458750</td>\n",
       "      <td>5.763750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>10.927500</td>\n",
       "      <td>4.650000</td>\n",
       "      <td>70.0</td>\n",
       "      <td>1.017188</td>\n",
       "      <td>214.0</td>\n",
       "      <td>3.545625</td>\n",
       "      <td>2.615625</td>\n",
       "      <td>4.998750</td>\n",
       "      <td>16.042500</td>\n",
       "      <td>2.673750</td>\n",
       "      <td>1.860000</td>\n",
       "      <td>6.393750</td>\n",
       "      <td>9.997500</td>\n",
       "      <td>5.347500</td>\n",
       "      <td>3.836250</td>\n",
       "      <td>1.174125</td>\n",
       "      <td>4.882500</td>\n",
       "      <td>6.510000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>11.043750</td>\n",
       "      <td>4.766250</td>\n",
       "      <td>69.0</td>\n",
       "      <td>1.104375</td>\n",
       "      <td>217.0</td>\n",
       "      <td>3.603750</td>\n",
       "      <td>2.673750</td>\n",
       "      <td>5.115000</td>\n",
       "      <td>16.507500</td>\n",
       "      <td>2.673750</td>\n",
       "      <td>1.976250</td>\n",
       "      <td>6.393750</td>\n",
       "      <td>10.346250</td>\n",
       "      <td>5.463750</td>\n",
       "      <td>3.836250</td>\n",
       "      <td>1.290375</td>\n",
       "      <td>4.998750</td>\n",
       "      <td>6.510000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>10.692500</td>\n",
       "      <td>4.465000</td>\n",
       "      <td>97.0</td>\n",
       "      <td>1.028125</td>\n",
       "      <td>208.0</td>\n",
       "      <td>3.407500</td>\n",
       "      <td>2.585000</td>\n",
       "      <td>4.817500</td>\n",
       "      <td>15.980000</td>\n",
       "      <td>2.467500</td>\n",
       "      <td>1.586250</td>\n",
       "      <td>6.110000</td>\n",
       "      <td>9.635000</td>\n",
       "      <td>5.287500</td>\n",
       "      <td>3.760000</td>\n",
       "      <td>0.987000</td>\n",
       "      <td>4.582500</td>\n",
       "      <td>6.110000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>12.360000</td>\n",
       "      <td>4.892500</td>\n",
       "      <td>70.0</td>\n",
       "      <td>1.062188</td>\n",
       "      <td>220.0</td>\n",
       "      <td>3.669375</td>\n",
       "      <td>2.768125</td>\n",
       "      <td>5.536250</td>\n",
       "      <td>18.540000</td>\n",
       "      <td>2.768125</td>\n",
       "      <td>1.995625</td>\n",
       "      <td>6.952500</td>\n",
       "      <td>11.458750</td>\n",
       "      <td>5.793750</td>\n",
       "      <td>4.055625</td>\n",
       "      <td>1.287500</td>\n",
       "      <td>5.536250</td>\n",
       "      <td>7.210000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>13.359375</td>\n",
       "      <td>5.203125</td>\n",
       "      <td>77.0</td>\n",
       "      <td>1.300781</td>\n",
       "      <td>224.0</td>\n",
       "      <td>3.937500</td>\n",
       "      <td>3.234375</td>\n",
       "      <td>5.906250</td>\n",
       "      <td>19.406250</td>\n",
       "      <td>2.882812</td>\n",
       "      <td>1.898438</td>\n",
       "      <td>7.734375</td>\n",
       "      <td>11.671875</td>\n",
       "      <td>6.609375</td>\n",
       "      <td>4.500000</td>\n",
       "      <td>1.476563</td>\n",
       "      <td>5.484375</td>\n",
       "      <td>7.453125</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>13.601250</td>\n",
       "      <td>6.142500</td>\n",
       "      <td>73.0</td>\n",
       "      <td>1.389375</td>\n",
       "      <td>212.0</td>\n",
       "      <td>4.387500</td>\n",
       "      <td>3.071250</td>\n",
       "      <td>6.142500</td>\n",
       "      <td>19.451250</td>\n",
       "      <td>3.363750</td>\n",
       "      <td>2.413125</td>\n",
       "      <td>7.751250</td>\n",
       "      <td>11.846250</td>\n",
       "      <td>6.727500</td>\n",
       "      <td>4.680000</td>\n",
       "      <td>1.535625</td>\n",
       "      <td>5.850000</td>\n",
       "      <td>7.751250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>16.292500</td>\n",
       "      <td>6.151250</td>\n",
       "      <td>73.0</td>\n",
       "      <td>1.330000</td>\n",
       "      <td>226.0</td>\n",
       "      <td>4.571875</td>\n",
       "      <td>3.408125</td>\n",
       "      <td>7.315000</td>\n",
       "      <td>23.607500</td>\n",
       "      <td>3.241875</td>\n",
       "      <td>2.660000</td>\n",
       "      <td>9.143750</td>\n",
       "      <td>13.965000</td>\n",
       "      <td>7.813750</td>\n",
       "      <td>5.320000</td>\n",
       "      <td>1.695750</td>\n",
       "      <td>6.650000</td>\n",
       "      <td>8.811250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>17.338750</td>\n",
       "      <td>6.613750</td>\n",
       "      <td>71.0</td>\n",
       "      <td>1.295937</td>\n",
       "      <td>223.0</td>\n",
       "      <td>4.558125</td>\n",
       "      <td>3.575000</td>\n",
       "      <td>7.686250</td>\n",
       "      <td>25.203750</td>\n",
       "      <td>3.485625</td>\n",
       "      <td>2.502500</td>\n",
       "      <td>10.010000</td>\n",
       "      <td>14.836250</td>\n",
       "      <td>8.043750</td>\n",
       "      <td>5.541250</td>\n",
       "      <td>1.787500</td>\n",
       "      <td>7.150000</td>\n",
       "      <td>9.295000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>18.562500</td>\n",
       "      <td>5.754375</td>\n",
       "      <td>67.0</td>\n",
       "      <td>1.392187</td>\n",
       "      <td>229.0</td>\n",
       "      <td>4.640625</td>\n",
       "      <td>3.712500</td>\n",
       "      <td>8.167500</td>\n",
       "      <td>27.286875</td>\n",
       "      <td>3.062813</td>\n",
       "      <td>2.598750</td>\n",
       "      <td>10.580625</td>\n",
       "      <td>15.592500</td>\n",
       "      <td>8.353125</td>\n",
       "      <td>5.568750</td>\n",
       "      <td>1.856250</td>\n",
       "      <td>7.610625</td>\n",
       "      <td>9.466875</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Ala (mg/gDW)  Arg (mg/gDW)  Asp (mg/gDW)  Cys (mg/gDW)  Glt (mg/gDW)  \\\n",
       "variety                                                                         \n",
       "1            8.588125      3.869375          67.0      1.014531         203.0   \n",
       "2            9.602500      4.175000          70.0      0.991562         210.0   \n",
       "3           10.005000      4.350000          70.0      0.924375         208.0   \n",
       "4           10.927500      4.650000          70.0      1.017188         214.0   \n",
       "5           11.043750      4.766250          69.0      1.104375         217.0   \n",
       "6           10.692500      4.465000          97.0      1.028125         208.0   \n",
       "7           12.360000      4.892500          70.0      1.062188         220.0   \n",
       "8           13.359375      5.203125          77.0      1.300781         224.0   \n",
       "9           13.601250      6.142500          73.0      1.389375         212.0   \n",
       "10          16.292500      6.151250          73.0      1.330000         226.0   \n",
       "11          17.338750      6.613750          71.0      1.295937         223.0   \n",
       "12          18.562500      5.754375          67.0      1.392187         229.0   \n",
       "\n",
       "         Gly (mg/gDW)  His (mg/gDW)  Ile (mg/gDW)  Leu (mg/gDW)  Lys (mg/gDW)  \\\n",
       "variety                                                                         \n",
       "1            3.208750      2.170625      3.869375     11.985625      2.359375   \n",
       "2            3.287812      2.296250      4.488125     14.508125      2.400625   \n",
       "3            3.316875      2.338125      4.567500     14.790000      2.501250   \n",
       "4            3.545625      2.615625      4.998750     16.042500      2.673750   \n",
       "5            3.603750      2.673750      5.115000     16.507500      2.673750   \n",
       "6            3.407500      2.585000      4.817500     15.980000      2.467500   \n",
       "7            3.669375      2.768125      5.536250     18.540000      2.768125   \n",
       "8            3.937500      3.234375      5.906250     19.406250      2.882812   \n",
       "9            4.387500      3.071250      6.142500     19.451250      3.363750   \n",
       "10           4.571875      3.408125      7.315000     23.607500      3.241875   \n",
       "11           4.558125      3.575000      7.686250     25.203750      3.485625   \n",
       "12           4.640625      3.712500      8.167500     27.286875      3.062813   \n",
       "\n",
       "         Met (mg/gDW)  Phe (mg/gDW)  Pro (mg/gDW)  Ser (mg/gDW)  Thr (mg/gDW)  \\\n",
       "variety                                                                         \n",
       "1            1.887500      4.907500      7.644375      4.435625      3.161563   \n",
       "2            1.722187      5.740625      9.185000      4.801250      3.392188   \n",
       "3            1.685625      5.872500      9.243750      4.893750      3.425625   \n",
       "4            1.860000      6.393750      9.997500      5.347500      3.836250   \n",
       "5            1.976250      6.393750     10.346250      5.463750      3.836250   \n",
       "6            1.586250      6.110000      9.635000      5.287500      3.760000   \n",
       "7            1.995625      6.952500     11.458750      5.793750      4.055625   \n",
       "8            1.898438      7.734375     11.671875      6.609375      4.500000   \n",
       "9            2.413125      7.751250     11.846250      6.727500      4.680000   \n",
       "10           2.660000      9.143750     13.965000      7.813750      5.320000   \n",
       "11           2.502500     10.010000     14.836250      8.043750      5.541250   \n",
       "12           2.598750     10.580625     15.592500      8.353125      5.568750   \n",
       "\n",
       "         Trp (mg/gDW)  Tyr (mg/gDW)  Val (mg/gDW)  \n",
       "variety                                            \n",
       "1            1.019250      3.680625      4.907500  \n",
       "2            1.075063      4.383750      5.740625  \n",
       "3            1.087500      4.458750      5.763750  \n",
       "4            1.174125      4.882500      6.510000  \n",
       "5            1.290375      4.998750      6.510000  \n",
       "6            0.987000      4.582500      6.110000  \n",
       "7            1.287500      5.536250      7.210000  \n",
       "8            1.476563      5.484375      7.453125  \n",
       "9            1.535625      5.850000      7.751250  \n",
       "10           1.695750      6.650000      8.811250  \n",
       "11           1.787500      7.150000      9.295000  \n",
       "12           1.856250      7.610625      9.466875  "
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_seed_content_3 = pd.DataFrame(data={\"variety\":range(1,13),\n",
    "                                       \"N content (g/100gDW)\":[1.51,1.67,1.74,1.86,1.86,1.88,\n",
    "                                                               2.06,2.25,2.34,2.66,2.86,2.97],\n",
    "                                       \"Gly (g/16g N)\":[3.4,3.15,3.05,3.05,3.1,2.9,2.85,2.8,3,2.75,2.55,2.5],\n",
    "                                       \"Ala (g/16g N)\":[9.1,9.2,9.2,9.4,9.5,9.1,9.6,9.5,9.3,9.8,9.7,10],\n",
    "                                       \"Val (g/16g N)\":[5.2,5.5,5.3,5.6,5.6,5.2,5.6,5.3,5.3,5.3,5.2,5.1],\n",
    "                                       \"Leu (g/16g N)\":[12.7,13.9,13.6,13.8,14.2,13.6,\n",
    "                                                        14.4,13.8,13.3,14.2,14.1,14.7],\n",
    "                                       \"Ile (g/16g N)\":[4.1,4.3,4.2,4.3,4.4,4.1,4.3,4.2,4.2,4.4,4.3,4.4],\n",
    "                                       \"Ser (g/16g N)\":[4.7,4.6,4.5,4.6,4.7,4.5,4.5,4.7,4.6,4.7,4.5,4.5],\n",
    "                                       \"Thr (g/16g N)\":[3.35,3.25,3.15,3.3,3.3,3.2,3.15,3.2,3.2,3.2,3.1,3],\n",
    "                                       \"Tyr (g/16g N)\":[3.9,4.2,4.1,4.2,4.3,3.9,4.3,3.9,4,4,4,4.1],\n",
    "                                       \"Phe (g/16g N)\":[5.2,5.5,5.4,5.5,5.5,5.2,5.4,5.5,5.3,5.5,5.6,5.7],\n",
    "                                       \"Trp (g/16g N)\":[1.08,1.03,1,1.01,1.11,0.84,1,1.05,1.05,1.02,1,1],\n",
    "                                       \"Pro (g/16g N)\":[8.1,8.8,8.5,8.6,8.9,8.2,8.9,8.3,8.1,8.4,8.3,8.4],\n",
    "                                       \"Met (g/16g N)\":[2,1.65,1.55,1.6,1.7,1.35,1.55,1.35,1.65,1.6,1.4,1.4],\n",
    "                                       \"Half Cys (g/16g N)\":[2.15,1.9,1.7,1.75,1.9,1.75,\n",
    "                                                             1.65,1.85,1.9,1.6,1.45,1.5],\n",
    "                                       \"Lys (g/16g N)\":[2.5,2.3,2.3,2.3,2.3,2.1,2.15,2.05,2.3,1.95,1.95,1.65],\n",
    "                                       \"His (g/16g N)\":[2.3,2.2,2.15,2.25,2.3,2.2,2.15,2.3,2.1,2.05,2,2],\n",
    "                                       \"Arg (g/16g N)\":[4.1,4,4,4,4.1,3.8,3.8,3.7,4.2,3.7,3.7,3.1],\n",
    "                                       \"Asp (g/100gDW)\":[6.7,7,7,7,6.9,9.7,7,7.7,7.3,7.3,7.1,6.7],\n",
    "                                       \"Glt (g/100gDW)\":[20.3,21,20.8,21.4,21.7,20.8,\n",
    "                                                         22,22.4,21.2,22.6,22.3,22.9]})\n",
    "df_seed_content_3_std = pd.DataFrame(data={\"variety\":range(1,13),\n",
    "                                       \"Gly (mg/gDW)\":(df_seed_content_3[\"Gly (g/16g N)\"]/16)* \\\n",
    "                                                            df_seed_content_3[\"N content (g/100gDW)\"]*10,\n",
    "                                       \"Ala (mg/gDW)\":(df_seed_content_3[\"Ala (g/16g N)\"]/16)* \\\n",
    "                                                            df_seed_content_3[\"N content (g/100gDW)\"]*10,\n",
    "                                       \"Val (mg/gDW)\":(df_seed_content_3[\"Val (g/16g N)\"]/16)* \\\n",
    "                                                            df_seed_content_3[\"N content (g/100gDW)\"]*10,\n",
    "                                       \"Leu (mg/gDW)\":(df_seed_content_3[\"Leu (g/16g N)\"]/16)* \\\n",
    "                                                            df_seed_content_3[\"N content (g/100gDW)\"]*10,\n",
    "                                       \"Ile (mg/gDW)\":(df_seed_content_3[\"Ile (g/16g N)\"]/16)* \\\n",
    "                                                            df_seed_content_3[\"N content (g/100gDW)\"]*10,\n",
    "                                       \"Ser (mg/gDW)\":(df_seed_content_3[\"Ser (g/16g N)\"]/16)* \\\n",
    "                                                            df_seed_content_3[\"N content (g/100gDW)\"]*10,\n",
    "                                       \"Thr (mg/gDW)\":(df_seed_content_3[\"Thr (g/16g N)\"]/16)* \\\n",
    "                                                            df_seed_content_3[\"N content (g/100gDW)\"]*10,\n",
    "                                       \"Tyr (mg/gDW)\":(df_seed_content_3[\"Tyr (g/16g N)\"]/16)* \\\n",
    "                                                            df_seed_content_3[\"N content (g/100gDW)\"]*10,\n",
    "                                       \"Phe (mg/gDW)\":(df_seed_content_3[\"Phe (g/16g N)\"]/16)* \\\n",
    "                                                            df_seed_content_3[\"N content (g/100gDW)\"]*10,\n",
    "                                       \"Trp (mg/gDW)\":(df_seed_content_3[\"Trp (g/16g N)\"]/16)* \\\n",
    "                                                            df_seed_content_3[\"N content (g/100gDW)\"]*10,\n",
    "                                       \"Pro (mg/gDW)\":(df_seed_content_3[\"Pro (g/16g N)\"]/16)* \\\n",
    "                                                            df_seed_content_3[\"N content (g/100gDW)\"]*10,\n",
    "                                       \"Met (mg/gDW)\":(df_seed_content_3[\"Met (g/16g N)\"]/16)* \\\n",
    "                                                            df_seed_content_3[\"N content (g/100gDW)\"]*10,\n",
    "                                       \"Cys (mg/gDW)\":0.5*(df_seed_content_3[\"Half Cys (g/16g N)\"]/16)* \\\n",
    "                                                            df_seed_content_3[\"N content (g/100gDW)\"]*10,\n",
    "                                       \"Lys (mg/gDW)\":(df_seed_content_3[\"Lys (g/16g N)\"]/16)* \\\n",
    "                                                            df_seed_content_3[\"N content (g/100gDW)\"]*10,\n",
    "                                       \"His (mg/gDW)\":(df_seed_content_3[\"His (g/16g N)\"]/16)* \\\n",
    "                                                            df_seed_content_3[\"N content (g/100gDW)\"]*10,\n",
    "                                       \"Arg (mg/gDW)\":(df_seed_content_3[\"Arg (g/16g N)\"]/16)* \\\n",
    "                                                            df_seed_content_3[\"N content (g/100gDW)\"]*10,\n",
    "                                       \"Asp (mg/gDW)\":df_seed_content_3[\"Asp (g/100gDW)\"]*10,\n",
    "                                       \"Glt (mg/gDW)\":df_seed_content_3[\"Glt (g/100gDW)\"]*10})\n",
    "df_seed_content_3_std.set_index(\"variety\",drop=True,inplace=True)\n",
    "df_seed_content_3_std"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "biomass.at[\"sSUCROSE_b\",\"seed\"] = find_average(df_seed_content_2_std[\"sucrose (mg/gDW)\"])/ \\\n",
    "                                            model.metabolites.get_by_id(\"SUCROSE_c\").formula_weight\n",
    "biomass.at[\"GLC_c\",\"seed\"]=find_average(df_seed_content_2_std[\"glucose (mg/gDW)\"])/ \\\n",
    "                                            model.metabolites.get_by_id(\"GLC_c\").formula_weight\n",
    "biomass.at[\"FRU_c\",\"seed\"]=find_average(df_seed_content_2_std[\"fructose (mg/gDW)\"])/ \\\n",
    "                                            model.metabolites.get_by_id(\"FRU_c\").formula_weight\n",
    "biomass.at[\"L_PHOSPHATIDATE_p\",\"leaf\"]=14.2253521126762/model.metabolites.get_by_id(\"L_PHOSPHATIDATE_p\").formula_weight\n",
    "biomass.at[\"Protein_b\",\"leaf\"]=8.339/proteinMW\n",
    "\n",
    "biomass.at[\"ARG_c\",\"seed\"] = find_average(df_seed_content_3_std[\"Arg (mg/gDW)\"])/ \\\n",
    "                                            model.metabolites.get_by_id(\"ARG_c\").formula_weight\n",
    "biomass.at[\"HIS_c\",\"seed\"] = find_average(df_seed_content_3_std[\"His (mg/gDW)\"])/ \\\n",
    "                                            model.metabolites.get_by_id(\"HIS_c\").formula_weight\n",
    "biomass.at[\"LYS_c\",\"seed\"] = find_average(df_seed_content_3_std[\"Lys (mg/gDW)\"])/ \\\n",
    "                                            model.metabolites.get_by_id(\"LYS_c\").formula_weight\n",
    "biomass.at[\"sASP_b\",\"seed\"] = find_average(df_seed_content_3_std[\"Asp (mg/gDW)\"])/ \\\n",
    "                                            model.metabolites.get_by_id(\"L_ASPARTATE_c\").formula_weight\n",
    "biomass.at[\"sGLU_b\",\"seed\"] = find_average(df_seed_content_3_std[\"Glt (mg/gDW)\"])/ \\\n",
    "                                            model.metabolites.get_by_id(\"sGLU_b\").formula_weight\n",
    "biomass.at[\"sSER_b\",\"seed\"] = find_average(df_seed_content_3_std[\"Ser (mg/gDW)\"])/ \\\n",
    "                                            model.metabolites.get_by_id(\"sSER_b\").formula_weight\n",
    "biomass.at[\"THR_c\",\"seed\"] = find_average(df_seed_content_3_std[\"Thr (mg/gDW)\"])/ \\\n",
    "                                            model.metabolites.get_by_id(\"THR_c\").formula_weight\n",
    "biomass.at[\"CYS_c\",\"seed\"] = find_average(df_seed_content_3_std[\"Cys (mg/gDW)\"])/ \\\n",
    "                                            model.metabolites.get_by_id(\"CYS_c\").formula_weight\n",
    "biomass.at[\"GLY_c\",\"seed\"] = find_average(df_seed_content_3_std[\"Gly (mg/gDW)\"])/ \\\n",
    "                                            model.metabolites.get_by_id(\"GLY_c\").formula_weight\n",
    "biomass.at[\"PRO_c\",\"seed\"] = find_average(df_seed_content_3_std[\"Pro (mg/gDW)\"])/ \\\n",
    "                                            model.metabolites.get_by_id(\"PRO_c\").formula_weight\n",
    "biomass.at[\"sALA_b\",\"seed\"] = find_average(df_seed_content_3_std[\"Ala (mg/gDW)\"])/ \\\n",
    "                                            model.metabolites.get_by_id(\"L_ALPHA_ALANINE_c\").formula_weight\n",
    "biomass.at[\"VAL_c\",\"seed\"] = find_average(df_seed_content_3_std[\"Val (mg/gDW)\"])/ \\\n",
    "                                            model.metabolites.get_by_id(\"VAL_c\").formula_weight\n",
    "biomass.at[\"ILE_c\",\"seed\"] = find_average(df_seed_content_3_std[\"Ile (mg/gDW)\"])/ \\\n",
    "                                            model.metabolites.get_by_id(\"ILE_c\").formula_weight\n",
    "biomass.at[\"LEU_c\",\"seed\"] = find_average(df_seed_content_3_std[\"Leu (mg/gDW)\"])/ \\\n",
    "                                            model.metabolites.get_by_id(\"LEU_c\").formula_weight\n",
    "biomass.at[\"MET_c\",\"seed\"] = find_average(df_seed_content_3_std[\"Met (mg/gDW)\"])/ \\\n",
    "                                            model.metabolites.get_by_id(\"MET_c\").formula_weight\n",
    "biomass.at[\"PHE_c\",\"seed\"] = find_average(df_seed_content_3_std[\"Phe (mg/gDW)\"])/ \\\n",
    "                                            model.metabolites.get_by_id(\"PHE_c\").formula_weight\n",
    "biomass.at[\"TYR_c\",\"seed\"] = find_average(df_seed_content_3_std[\"Tyr (mg/gDW)\"])/ \\\n",
    "                                            model.metabolites.get_by_id(\"TYR_c\").formula_weight\n",
    "biomass.at[\"TRP_c\",\"seed\"] = find_average(df_seed_content_3_std[\"Trp (mg/gDW)\"])/ \\\n",
    "                                            model.metabolites.get_by_id(\"TRP_c\").formula_weight\n",
    "biomass.to_csv(\"/home/sanu/biomass_sorghum.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>leaf</th>\n",
       "      <th>stem</th>\n",
       "      <th>root</th>\n",
       "      <th>seed</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>sSUCROSE_b</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GLC_c</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FRU_c</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Starch_b</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cellulose_b</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Xylan_b</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>L_PHOSPHATIDATE_p</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PHOSPHATIDYL_CHOLINE_r</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>L_1_PHOSPHATIDYL_ETHANOLAMINE_r</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DIACYLGLYCEROL_p</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Galactosyl_galactosyl_diacyl_glycerols_p</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>D_Galactosyl_12_diacyl_glycerols_p</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2_Lysophosphatidylcholines_r</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lysophosphatidylglycerols_r</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Triacylglycerols_p</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>L_1_PHOSPHATIDYL_GLYCEROL_p</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>L_1_phosphatidyl_inositols_r</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SULFOQUINOVOSYLDIACYLGLYCEROL_p</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Protein_b</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sMAL_b</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sCIT_b</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sFUM_b</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ARG_c</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HIS_c</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LYS_c</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sASP_b</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sGLU_b</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sSER_b</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>THR_c</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ASN_c</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sGLN_b</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CYS_c</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GLY_c</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PRO_c</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sALA_b</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>VAL_c</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ILE_c</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LEU_c</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MET_c</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PHE_c</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TYR_c</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TRP_c</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sGABA_b</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PALMITATE_p</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CPD_9245_p</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CPD_17412_p</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CPD_17291</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>STEARIC_ACID_p</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OLEATE_CPD_p</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Octadecadienoate_p</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LINOLENIC_ACID_p</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ARACHIDIC_ACID_p</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CPD_16709</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DOCOSANOATE_p</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                          leaf  stem  root  seed\n",
       "                                                                \n",
       "sSUCROSE_b                                 0.0   0.0   0.0   0.0\n",
       "GLC_c                                      0.0   0.0   0.0   0.0\n",
       "FRU_c                                      0.0   0.0   0.0   0.0\n",
       "Starch_b                                   0.0   0.0   0.0   0.0\n",
       "Cellulose_b                                0.0   0.0   0.0   0.0\n",
       "Xylan_b                                    0.0   0.0   0.0   0.0\n",
       "L_PHOSPHATIDATE_p                          0.0   0.0   0.0   0.0\n",
       "PHOSPHATIDYL_CHOLINE_r                     0.0   0.0   0.0   0.0\n",
       "L_1_PHOSPHATIDYL_ETHANOLAMINE_r            0.0   0.0   0.0   0.0\n",
       "DIACYLGLYCEROL_p                           0.0   0.0   0.0   0.0\n",
       "Galactosyl_galactosyl_diacyl_glycerols_p   0.0   0.0   0.0   0.0\n",
       "D_Galactosyl_12_diacyl_glycerols_p         0.0   0.0   0.0   0.0\n",
       "2_Lysophosphatidylcholines_r               0.0   0.0   0.0   0.0\n",
       "Lysophosphatidylglycerols_r                0.0   0.0   0.0   0.0\n",
       "Triacylglycerols_p                         0.0   0.0   0.0   0.0\n",
       "L_1_PHOSPHATIDYL_GLYCEROL_p                0.0   0.0   0.0   0.0\n",
       "L_1_phosphatidyl_inositols_r               0.0   0.0   0.0   0.0\n",
       "SULFOQUINOVOSYLDIACYLGLYCEROL_p            0.0   0.0   0.0   0.0\n",
       "Protein_b                                  0.0   0.0   0.0   0.0\n",
       "sMAL_b                                     0.0   0.0   0.0   0.0\n",
       "sCIT_b                                     0.0   0.0   0.0   0.0\n",
       "sFUM_b                                     0.0   0.0   0.0   0.0\n",
       "ARG_c                                      0.0   0.0   0.0   0.0\n",
       "HIS_c                                      0.0   0.0   0.0   0.0\n",
       "LYS_c                                      0.0   0.0   0.0   0.0\n",
       "sASP_b                                     0.0   0.0   0.0   0.0\n",
       "sGLU_b                                     0.0   0.0   0.0   0.0\n",
       "sSER_b                                     0.0   0.0   0.0   0.0\n",
       "THR_c                                      0.0   0.0   0.0   0.0\n",
       "ASN_c                                      0.0   0.0   0.0   0.0\n",
       "sGLN_b                                     0.0   0.0   0.0   0.0\n",
       "CYS_c                                      0.0   0.0   0.0   0.0\n",
       "GLY_c                                      0.0   0.0   0.0   0.0\n",
       "PRO_c                                      0.0   0.0   0.0   0.0\n",
       "sALA_b                                     0.0   0.0   0.0   0.0\n",
       "VAL_c                                      0.0   0.0   0.0   0.0\n",
       "ILE_c                                      0.0   0.0   0.0   0.0\n",
       "LEU_c                                      0.0   0.0   0.0   0.0\n",
       "MET_c                                      0.0   0.0   0.0   0.0\n",
       "PHE_c                                      0.0   0.0   0.0   0.0\n",
       "TYR_c                                      0.0   0.0   0.0   0.0\n",
       "TRP_c                                      0.0   0.0   0.0   0.0\n",
       "sGABA_b                                    0.0   0.0   0.0   0.0\n",
       "PALMITATE_p                                0.0   0.0   0.0   0.0\n",
       "CPD_9245_p                                 0.0   0.0   0.0   0.0\n",
       "CPD_17412_p                                0.0   0.0   0.0   0.0\n",
       "CPD_17291                                  0.0   0.0   0.0   0.0\n",
       "STEARIC_ACID_p                             0.0   0.0   0.0   0.0\n",
       "OLEATE_CPD_p                               0.0   0.0   0.0   0.0\n",
       "Octadecadienoate_p                         0.0   0.0   0.0   0.0\n",
       "LINOLENIC_ACID_p                           0.0   0.0   0.0   0.0\n",
       "ARACHIDIC_ACID_p                           0.0   0.0   0.0   0.0\n",
       "CPD_16709                                  0.0   0.0   0.0   0.0\n",
       "DOCOSANOATE_p                              0.0   0.0   0.0   0.0"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "biomass"
   ]
  },
  {
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   "metadata": {},
   "source": [
    "### References\n",
    "\n",
    "- Wang, J.S., Wang, M.L., Spiertz, J.H.J., Liu, Z.X., Han, L.P. and Xie, G.H. (2013) Genetic variation in yield and chemical composition of wide range of sorghum accessions grown in north-west China. Res. Crop., 14, 95–105.\n",
    "- Ogbaga, C.C., Stepien, P., Dyson, B.C., Rattray, N.J.W., Ellis, D.I., Goodacre, R. and Johnson, G.N. (2016) Biochemical analyses of sorghum varieties reveal differential responses to drought J.-S. Zhang, ed. PLoS One, 11, e0154423. https://doi.org/10.1371/journal.pone.0154423.\n",
    "- Vanhercke, T., Belide, S., Taylor, M.C., et al. (2019) Up-regulation of lipid biosynthesis increases the oil content in leaves of Sorghum bicolor. Plant Biotechnol. J., 17, 220–232. Available at: http://doi.wiley.com/10.1111/pbi.12959.\n",
    "- Lunn, J.E. and Hatch, M.D. (1995) Primary partitioning and storage of photosynthate in sucrose and starch in leaves of C4 plants. Planta, 197, 5000. https://doi.org/10.1007/BF00202661.\n",
    "- Njokweni, A.P. (University of the W.C. (2015) COMPARATIVE ANALYSIS OF SUGAR-BIOSYNTHESIS PROTEINS OF SORGHUM STEMS AND THE INVESTIGATION OF THEIR ROLE IN HYPEROSMOTIC STRESS TOLERANCE. University of the Western Cape. \n",
    "https://pdfs.semanticscholar.org/cb3f/6b1c4f9b2acae9fe0afba1c3603c32fdb2c7.pdf.\n",
    "- Arai-Sanoh, Y., Ida, M., Zhao, R., et al. (2011) Genotypic variations in non-structural carbohydrate and cell-wall components of the stem in rice, sorghum, and sugar vane. Biosci. Biotechnol. Biochem., 75, 1104–12. Available at: http://www.tandfonline.com/doi/full/10.1271/bbb.110009.\n",
    "- Cambria, J., Galvani, F.R., Estevao, M.M. and Sant’Anna, R. (1983) Effects of Aluminum on Organic Acid,’ Sugar and Amino Acid Composition of the Root System of Sorghum (Sorghum Bicolor L. Moench). J. Plant Nutr., 6, 313–322. https://doi.org/10.1080/01904168309363092.\n",
    "- Neucere, N.J. and Sumrell, G. (1980) Chemical composition of different varieties of grain sorghum. J. Agric. Food Chem., 28, 19–21. http://doi.org/10.1021/jf60227a022."
   ]
  },
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