Access To Big Data Turns Farm Machine Makers Into Tech Firms
Equipment makers with sufficient sales of machines around the country may in theory actually be able to predict, at least to some small but meaningful extent, the prices of various crops by analyzing the data its machines are sending in — such as “yields” of crops per acre, the amount of fertilizer used, or the average number of seeds of a given crop planted in various regions.
By Scott Carpenter
Forbes
Dec 31, 2020
Excerpt:
The combine harvester, a staple of farmers’ fields since the late 1800s, does much more these days than just vacuum up corn, soybeans and other crops. It also beams back reams of data to its manufacturer.
GPS records the combine’s precise path through the field as it moves. Sensors tally the number of crops gathered per acre and the spacing between them. On a sister machine called a planter, algorithms adjust the distribution of seeds based on which parts of the soil have in past years performed best. Another machine, a sprayer, uses algorithms to scan for weeds and zap them with pesticides. Meanwhile sensors record the wear and tear on the machines, so that when the farmer who operates them heads to the local distributor to look for a replacement part, it has already been ordered and is waiting for them.
Farming may be an earthy industry, but much of it now takes place in the cloud. Leading farm machine makers like Chicago-based John Deere DE +1.1% or Georgia’s AGCO AGCO +0.9% collect data from all around the world thanks to the ability of their bulky machines to extract a huge variety of metrics from farmers’ fields and store it online. The farmers who sit in the driver’s seats of these machines have access to the data that they themselves accumulate, but legal murk obfuscates the question of whether they actually own that data and only the machine manufacturer can see all the data from all the machines leased or sold.
