গাইড লিঙ্ক ক্যুইজ · মাঝারি স্তর
কৃষি কুইজে এ.আই
সময়-সচেতন ইনপুট, ক্ষেত্রের বৈধতা, কর্মের সীমাবদ্ধতা, অনিশ্চয়তা, ডেটা সুরক্ষা এবং মানব তদারকির মাধ্যমে দায়িত্বের সাথে কৃষি AI প্রয়োগ করুন।
প্রশ্ন 1 এর 8
Why define the agricultural outcome and timing before selecting model inputs?
প্রতিটি প্রশ্নের পূর্বরূপ দেখুন8 প্রশ্ন
আপনি কুইজ নেওয়ার সাথে সাথে উত্তর এবং ব্যাখ্যাগুলি উপস্থিত হয়।
- Why define the agricultural outcome and timing before selecting model inputs?
- Different decisions need different evidence, and only inputs available at that time should be used
- Every decision can use future weather
- All crop models share a target
- Timing does not affect evaluation
- A crop-image model works on its training farm. What should be tested before broader use?
- Only the same images again
- Unseen fields, seasons, cultivars, cameras, and weather conditions
- A single accuracy score
- The brand of the tablet
- A disease detector flags a plant. What should be measured before treatment?
- ছবিতে পিক্সেলের সংখ্যা
- Only the model’s speed
- Detection and false alerts in the relevant field conditions
- Whether the plant is near a road
- Why might a model trained on summer images fail in another season?
- The label names are too short
- The crop cannot be photographed in other seasons
- Seasons do not change conditions
- It may rely on a seasonal shortcut such as color or sunlight
- An irrigation model recommends an action. Which constraints should be considered?
- Only the forecast score
- Water availability, soil, crop stage, and operator practice
- The number of model layers
- The farm’s social media reach
- How should a yield estimate be communicated to a buyer?
- Without explaining its timing
- As a guaranteed production amount
- With uncertainty, not as a promise
- As a replacement for a contract
- What should a farm do when an AI model is uncertain or unavailable?
- Maintain a safe manual process and preserve operator authority
- Stop all field decisions
- Allow the model to guess
- Delete sensor history
- Which field conditions should be included in evaluation when costly mistakes matter?
- A single crop at one site
- Only average sunny days
- Only common easy examples
- Rare disease, drought, flooding, and missing-sensor cases