The Importance of Data in Supply Chains

Why is it important to track data in agriculture?

Our planet is predicted to have an approximate population of 9.8 billion by 2050. This indicates an upcoming need to boost our crop production significantly in order to feed the rising population. With the emerging threat of global warming, colonization and climate changes are triggering depression to the farmlands already under cultivation. The US data alone shows a dip of 14 million acres of farmlands between 2014 to 2018.

Unfortunately, traditional agriculture lacks many accuracies including but not limited to, planting and harvesting, water and fertilizer use, and multiple weather episodes. Pests and diseases contribute to intangible losses in production and income of farmers due to their lack of knowledge in knowing how to control them.

In order to address such issues in agriculture, it is paramount to keep records of weather changes, soil conditions, moisture assessments, fertilizer requirements, and the presence of pests and diseases. Tools such as sensors placed in the field can provide data on things such as soil texture and structure, soil pH, nutrients, and moisture levels. With the farm machinery operated and mobilized by GPS and crops monitored and sprayed by agriculture drones, these tools would lead to maximizing the efficiency of farming operations. By utilizing this array of data, farmers can make more precise and smarter decisions that can lead towards sustainability and increased profitability.

How data collection can help improve productivity and yields in coffee?

The data collection can help several ways to improve productivity and yields in coffee. The adoption of one or more technologies can trigger yields along with improving the efficiency of farming operations.

By maintaining cropping calendars:

Based on the previous crop data, the decisions for planting crops that were better adaptable to a particular climatic condition can be made well in advance. This includes the types and varieties of the coffee, sowing & harvesting time, water, and nutrient requirements for the most adaptable and high yielding varieties in any particular area. Combing all sets of data would make a calendar for all agronomic and cultural practices that would be easy to carry out.

Planting layout:

The data also helps in deciding the kind of planting pattern, plant spacing, and the number of plants per hectare would yield. This allows for the utilization of lesser amount of inputs such as fertilizers and other necessary inputs to obtain optimum growth level for maximum productivity.Coffee is pretty sensitive to nutrient dosages and may behave adversely if the standard fertilization is not practiced.

Diseases and Pest Monitoring:

The precise data and images collected using UAVs and sensors can warn about such infestations at a very early stage. By utilizing this method, only affected plants can be spray exclusively using Aerial spraying technique that cuts the application cost of insecticides increasing productivity and profitability of Coffee farmers.

Watering:

The ground sensors connected to the irrigation system collect data on the ground moisture and temperature. Any slight fluctuation in humidity and temperature is noticed in the form of data that sets the system ON or OFF depending on the need of the Coffee crop. Such an application saves time and costs on labor to improve productivity and yield of Coffee.

Harvesting Decisions:

Timely crop harvesting can add 20% or more in the potential of Coffee yield. Farm data advises on the maturity of the Coffee crop through detecting the amount of moisture and color in the clusters of cherries. Timely harvest enhances the quality and quantity of the Coffee cherries to add to the profitability of the growers.

Food Traceability:

Data has the biggest advantages in tracing the origin and the type of Coffee grown, it’s mobility and value addition, and paying the farmers remotely using modern tools of E-Payments in a food supply chain.

What can we learn by collecting data at the farm level?

There are several things to learn from the farm data as it helps us to make precise decisions well in advance to prepare us fully for the next cropping season. The insights on the following features can be learned from the data at the farm level;

The type of variety and the best adaptable location at the farm.
Temperature requirements during different stages of crop growth.
The periods of droughts and precipitation in the cropping season.
The exact amount of fertilizers and insecticide used for maturity.
The type and time of pests and disease infestations.
The climatic conditions and their severity.
The irrigation needs of a particular crop.
Complete records and traceability of the product along with the earning during different cropping seasons.
It also helps to determine the pricing trends in the market.