Cuestionario vinculado a una guía · Medio Nivel

Prueba de IA en agricultura de precisión

Revise cómo las imágenes de cultivos y los datos de campo guían los insumos de dosis variable, el tratamiento de malezas específico y las decisiones locales cuando la conectividad de las granjas es limitada.

Rutas de guía relacionadasIA en agricultura de precisión
Pregunta 1 de 8

Which four spectral bands are typically included in USDA Farm Service Agency four-band imagery?

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  1. Which four spectral bands are typically included in USDA Farm Service Agency four-band imagery?
    • Red, green, blue and near-infrared
    • Ultraviolet, X-ray, thermal and radar
    • Only red and near-infrared
    • Blue, ultraviolet, microwave and lidar
  2. ¿Cómo reduce See & Spray de John Deere el uso de herbicidas?
    • Pulverizando uniformemente todo el campo
    • Mediante el uso de visión por computadora para rociar solo las malezas detectadas
    • Prohibiendo todos los herbicidas
    • Pulverizando sólo por la noche.
  3. ¿Qué es la 'tecnología de tasa variable' en la agricultura de precisión?
    • Cobrar precios diferentes a los agricultores por las semillas
    • Cambiar la velocidad del tractor aleatoriamente.
    • Aplicar diferentes cantidades de insumos a diferentes zonas de campo
    • Un tipo de seguro de cosechas
  4. Which model architecture did the cited 2025 crop-weed paper evaluate for edge weed detection?
    • A speech-recognition Transformer
    • A rule-only spreadsheet parser
    • A large language model trained on contracts
    • A lightweight convolutional neural network
  5. In the USDA ERS 2023 report, variable-rate technology had been adopted on what share of planted acreage for winter wheat, cotton, sorghum and rice?
    • Between 5 and 25 percent
    • Less than 1 percent for every crop
    • Between 50 and 75 percent
    • All planted acreage
  6. What did the cited USDA precision-farming field study report about yield patterns across years?
    • Yield patterns were identical every year
    • Yield patterns changed yearly and had little similarity between years
    • All management zones produced the same yield
    • AI consistently improved yield in every zone
  7. How is NDVI commonly calculated from red and near-infrared reflectance?
    • Red plus blue divided by soil moisture
    • Thermal radiation minus wind speed
    • Near-infrared minus red, divided by their sum
    • Plant height multiplied by fertilizer rate
  8. Why can variable-rate technology use input maps instead of a single field-wide rate?
    • Every part of a field has identical needs
    • Maps eliminate the need for agronomic decisions
    • The system changes crop genetics while spraying
    • Soil and crop conditions can vary across zones within a field