Agronomy: AI Agronomy is a cloud-based platform that uses artificial
intelligence to provide farmers with recommendations on crop selection,
fertilizer application, and other agricultural practices. MazaoHub AI
Agronomy is trained on a massive dataset of soil using MazaoHub soil
sensors and crop data, and it generates customized recommendations for
involved in AI Agronomy services offered by MazaoHub:
preparation: The AI Agronomy tool can recommend the best crops to
grow in a particular soil based on the soil reports, the amount of
fertilizer to apply, how to apply and the best time to apply it. The tool
also recommends pest and disease management practices, irrigation
schedules, and harvesting methods.
- Sowing: The
AI Agronomy tool recommends the best sowing method for a particular crop,
the depth to sow the seeds, and the spacing between plants.
application: The AI Agronomy tool recommends the best fertilizer to
apply, the amount of fertilizer to apply, and the best time to apply it.
management: The AI Agronomy tool recommends the best irrigation
schedule for a particular crop connected with sensors, the amount of
water to apply, and the best way to apply it.
and disease management: The AI Agronomy tool recommends the best
pest and disease control methods for a particular crop, the timing of
treatment, and the best way to apply the treatment.
- Harvesting: The
AI Agronomy tool recommends the best harvesting method for a particular
crop, the time to harvest, and the best way to store the harvested crop.
handling: The AI Agronomy tool recommends the best post-harvest
handling practices for a particular crop, such as drying, grading, and
- Storage: The
AI Agronomy tool recommends the best storage conditions for a particular
crop, such as temperature, humidity, and light exposure.
Extension officers from each village collect information and feed MazaoHub
officers from each village collect information from farmers about their
crops, such as the type of crop, the amount of fertilizer applied, the
amount of water used, and the yield of the crop.
extension officers then enter this information into the MazaoHub AI
MazaoHub AI Agronomy platform uses this information to improve its
recommendations to farmers.
AI Agronomy becomes very accurate just like real agronomist giving
extension service to the farmer:
MazaoHub AI Agronomy platform is constantly being trained on new data.
This data comes from farmers, extension officers, and other sources.
the platform is trained on more data, it becomes more accurate in its
the MazaoHub AI Agronomy platform can become as accurate as a real
agronomist giving extension service to the farmer.
Data Collection Process:
Extension officers play a crucial role in
collecting data for MazaoHub's AI Agronomy Module. Here's how the process works:
Extension Officers: Extension officers from
each village are trained to use the MazaoHub platform. They are provided
with smartphones or tablets equipped with the MazaoHub app.
Data Collection: Extension officers visit farms
regularly to collect data. They input information about crop health, soil
conditions, weather observations from Meteo Agency, and any issues
observed during their field visits.
and Sensor Data: They can capture images of
crops, soil samples using MazaoHub Sensors, and use sensors to measure
environmental factors. This data is uploaded to the platform.
Synchronization: The collected data is
synchronized with the central MazaoHub database, where AI algorithms
analyze and process it.
Recommendations: Based on the collected data and
historical trends, the AI generates recommendations for each farmer.
Loop: Extension officers relay these
recommendations to farmers, and their feedback is also recorded. This
feedback loop helps improve the accuracy of AI recommendations over time.
Steps Involved in AI Agronomy Services
The AI Agronomy services offered by MazaoHub
follow the 12 key steps of Good Agricultural Practices (GAP):
Preparation: Soil analysis determines the
need for land preparation, including plowing and leveling.
The platform suggests the optimal planting time and spacing based on
weather and soil conditions.
Selection: AI recommendations include the
choice of crop varieties suitable for the region.
Precise fertilizer recommendations are given based on soil nutrient
Weather forecasts and soil moisture data guide irrigation scheduling.
Management: Recommendations for weed
control, including the use of herbicides or manual weeding.
and Disease Control: AI helps identify and
manage pests and diseases, suggesting suitable treatments.
Monitoring: Continuous monitoring tracks
crop growth and health.
and Thinning: Guidance on crop maintenance
practices like pruning and thinning.
AI determines the optimal time for harvesting based on crop maturity.
Handling: Guidelines for proper
post-harvest handling, including sorting and packaging.
and Marketing: Recommendations for storage
conditions and market access.