✍️Answer the questions below in your own words and compare your answers with the model answers. If you are not sure, look for information in the study text, recommended literature or on the Internet.
The model answer shows what a correct and complete answer might sound like.
1. Why is it important to store agricultural data in both local and cloud systems?
2. What are the benefits of sorting and organizing your farm data (e.g. naming files, creating folders)?
3. What does an NDVI map show, and how can a farmer use it?
4. Name one digital tool mentioned in the text and describe how it helps with data interpretation.
5. How can data-driven farming contribute to environmental sustainability?
💡MODEL ANSWER TO THE QUESTION: Why is it important to store agricultural data in both local and cloud systems?
Combining local and cloud storage ensures both safety and accessibility. Local storage offers offline access, while cloud storage enables remote access, synchronization, and backups in case of data loss.
2. MODEL ANSWER TO THE QUESTION: What are the benefits of sorting and organizing your farm data (e.g. naming files, creating folders)?
Organizing data helps track field history, compare yields over time, and identify patterns. It also supports better decision-making and makes it easier to share records with advisors or institutions.
3. MODEL ANSWER TO THE QUESTION: What does an NDVI map show, and how can a farmer use it?
An NDVI map displays plant vitality based on satellite or drone imagery. Green indicates healthy vegetation, yellow signals average growth, and red points to stress or poor conditions. It helps farmers target interventions like irrigation or fertilization more precisely.
4. MODEL ANSWER TO THE QUESTION: Name one digital tool mentioned in the text and describe how it helps with data interpretation.
CleverFarm is a mobile app that helps visualize soil moisture, temperature, and other sensor data. It provides alerts and maps that support better decisions, such as when and where to irrigate.
5. MODEL ANSWER TO THE QUESTION: How can data-driven farming contribute to environmental sustainability?
Data helps avoid unnecessary use of water, fertilizers, and chemicals by targeting interventions. This reduces waste, lowers pollution, and protects soil and water resources, supporting long-term sustainability.
