Your crop visibility is insufficient
Your customers trust you to source grain that complies with stringent requirements like Non-GMO, hard endosperm, high amylose, high purity, and color. So your research team develops genetics that grant you a thin margin above the local basis.
The challenge (and opportunity) is that the production cycle is out of your hands, which means your monitoring capability is limited to what your staff observes as they drive from field to field.
The best you can do is develop a test for measuring the parameter(s) your customers prefer, and take and analyze samples before harvest to estimate the state of the crop, so that if you miss your targets you can at least buy the shortfall from a competitor and satisfy your customers.
Know your crop
Farming is becoming more efficient and data-driven, and growers need a place where they can push information you can use to make more informed management decisions throughout the growing season.
Using MyFarms, growers can report the location of every field along with planting details such as seed choice, planting date and planting population. Combining this data with hourly weather data, we calculate the growth stage of each field. Then, based on your workforce and footprint, we build a Key Fields algorithm to your specification to automatically identify the best fields for your limited work force to scout. As they enter kernel counts (for example) for each key field, your yield picture for each hybrid takes shape through a convenient web interface.
Go the extra mile by delivering sustainability
Are your customers asking for sustainability? The only way to deliver on this request is to log what happens at the field level. With MyFarms you can go well beyond the planting operation to record nitrogen, fertilizer and spraying applications. If the grower has precision technology capable of recording what is planted or applied on each acre, those maps can be brought into MyFarms as well.
Maybe your research team wants to look for a correlation between a desirable grain characteristic and a certain management practice such as planting date, population or nitrogen application timing. With field specific data, that analysis becomes possible.
Tie quality back to the field
Once every field is uniquely identified, you can track every load at the grain dump back to the field, along with the quality data you recorded in the lab. By associating this data back to the field on a large scale, you can use it to conduct correlation studies between management practices and the quality characteristics that matter most. Then, as correlations are identified, you can incentivize growers to use the practices that lead to the best result.