ISSS608 Group07 Proposal

Corn: The A-maize-ing Crop.

Overview

Proposal

Poster

Application

Report

Overview
Corn or Maize (as called in some countries) was first grown in ancient Central America. Corn has become a staple in many parts of the world, providing not only substances that we fill our belly with, but also act as the raw ingredient for corn ethanol, animal feed etc. The United States accounts for about 40% of production of corn in the world¹, which makes it the largest corn producer. The major portion of production is found in the Midwestern states, such as Illinois, Iowa, Nebraska and Minnesota – these states were grouped and eventually became known as the ‘Corn Belt’. The Corn Belt has about 96,000,000 acres of land just for corn production. The states that make up the Corn Belt were selected due to leveled land, fertile and highly organic soils².

Objective and Scope

Scope

The scope of the project is limited to the corn produced in USA. We will use all the years provided in the dataset, but with a focus on only the months that fall within the growing season of that particular hybrid. We will also limit the environmental factors to be the following:

1. Precipitation
   
2. Exposure length to sun
   
3. Average Temperature
   
4. Location of where the hybrid is planted
   
5. Which year the hybrid was planted
   
   

Objective

The first objective of this project is to visualise our dataset:

1. Weather Data: Precipitation, Average Temperature,Length of (sun) Radiation over the years
   
2. Performance Data: Average Yield by State, by Plantation and finally by Hybrid. However after skimming through our data, about 45% of our hybrids are only planted once. Hence we do not have enough data for us to do a time-series analysis. Instead, we will be doing cross-sectional analysis, where we will analyse and visualise our data year by year.
   
   

The second objective is to predict the yield of a particular drought-resistant corn hybrid, given the soil conditions and topography of the plantation. The model that we are going to implement is Geo-weighted Regression (GWR) Model. However to make this prediction, we first need to classify the hybrids to whether a particular corn hybrid is drought resistant or not. This is will be further elaborated on in the Methodology section.To determine whether a hybrid is drought resistant or not, we compare the individual average precipitation of each hybrid with the global average precipitation of all hybrids.

Data Source

This data from the 'Syngenta Crop Challenge 2019'.

Data Source

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Reference

The image for the banner was taken from https://iegvu.agribusinessintelligence.informa.com/CO215920/South-Africa-corn-planting-plummets.

[1] Olson, R. A., & Sander, D. H. (1988). Corn production. Corn and corn improvement, (cornandcornimpr), 639-686.
[2] Smith, C. W. (2004). Corn: origin, history, technology, and production (Vol. 4). John Wiley & Sons.