AI in Vineyards and Winemaking Quiz

Answers and explanations appear as you take the quiz.

1. What does vineyard NDVI primarily estimate from red and near-infrared reflectance?
   • Relative vine vigor as a vegetation-index proxy
   • A direct diagnosis of every disease on each vine
   • The exact water requirement of each individual plant
   • The sensory rating of finished wine without sampling
2. How does AI typically forecast a vineyard's yield months ahead?
   • By guessing from last year only
   • By counting grape clusters with computer vision
   • By weighing the soil
   • By reading the weather forecast alone
3. Which bands does a multispectral camera add for reflectance-based vineyard monitoring?
   • Only ultraviolet wavelengths invisible to all sensors
   • X-ray and gamma-ray wavelengths
   • Near-infrared and other selected spectral bands beyond visible light
   • Audio-frequency bands from hive microphones
4. How can variable-rate irrigation guided by AI be used in a vineyard?
   • Guarantee the exact water need of every vine from one satellite image
   • Apply the same fixed amount to every block regardless of conditions
   • Replace all irrigation checks with a prediction of grape flavor
   • Adjust water by block using weather and soil-moisture estimates, subject to local measurements
5. In the cellar, what are fermentation sensors mainly tracking?
   • Sugar, temperature, and pH
   • Bottle labels
   • Cork quality
   • Lighting levels
6. How can an AI-derived grape-ripeness estimate support harvest planning?
   • Automatically select the harvest date with no grower review
   • Serve as one decision-support input alongside field observations and fruit samples
   • Prove the final wine will receive a particular rating
   • Replace measurement of sugar, acidity, and other fruit traits
7. Which grapevine diseases does the guide name as examples for image-based detection?
   • Sea lice and white spot disease
   • Varroa mites and American foulbrood
   • Downy mildew and powdery mildew
   • Late blight and citrus greening
8. What can multispectral vineyard sensing combined with machine learning help estimate?
   • The exact number of yeast cells in every fermentation tank
   • The chemical composition of any wine without measurements
   • The future market price of a bottle from its label
   • Grape ripening and quality traits