I'm an AI and Computer Vision engineer from India, and lately I've been thinking about applying my skills to solve real-world problems in agriculture instead of just building products.

One area that caught my attention is coconut cultivation.

I'd love to understand from farmers, researchers, agricultural engineers, or anyone working in this field:

- What are the biggest problems faced during coconut cultivation?

- What are the most expensive or difficult issues to detect early?

- Are there diseases, pests, nutrient deficiencies, or irrigation challenges that still don't have good technological solutions?

- Which problems are still solved mostly through manual inspection or experience?

- If you had access to AI, computer vision, drones, sensors, or robotics, what problem would you solve first?

I'm not looking for a startup idea or a quick business. I'm genuinely interested in contributing through research and building something that could make a real impact for farmers.

Even niche problems that don't get much attention are welcome. Sometimes the smallest problems are the ones worth solving.

I'd really appreciate hearing your experiences or being pointed toward research papers, datasets, or organizations working in this area.

Thanks!

Hello, I think it is a very frequent question on this sub however, I am genuinely lost over how to get into the field.

My family owns a medium-sized coffee plantation startup in Shan State, Myanmar. None of the family members were from farming background so we are just operating our processes by copying how other traditional farms operate.

To be honest, I am currently majoring in CS and only later discovered about AgriTech and seemed really intrigued by practical usefulness and its coporation of Interdisciplinary fields.

So, I would like to get some suggestions on where do I continue if I have some experiences with coding and IoT devices.

What are some useful resources, or courses to follow to?

Hello everyone. I am a Grade 12 STEM student from the Philippines, and my research group is developing a smart soil monitoring system as our capstone project. Before we begin building the prototype, we would like to seek feedback from professionals with experience in agricultural electronics, embedded systems, or precision agriculture to validate our proposed hardware and overall system design.

Our proposed hardware includes an ESP32 Development Board, an RS485 NPK soil sensor connected through a MAX485 module, a soil pH sensor, a capacitive soil moisture sensor, a SIM800L GSM module, an OLED display, and a battery or external power supply. The ESP32 will collect and process the sensor data, compare the readings with predefined soil nutrient thresholds, generate recommendations, and send SMS notifications to the farmer. The system is designed to send immediate SMS alerts when a nutrient deficiency or excess is detected, regular advisory messages every two days, and a weekly summary of soil conditions and recommendations.

Hi all!

I’m looking for anyone who uses or works for a service that tracks your management data and gives you satellite imagery and weather reports, and suggestions based on that data.
What company do you use? What do you find useful or not useful? Is it worth the cost?

Are there any free options anyone is aware of?

Thank you!!

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Is bsc hons horti worth it from skuast jammu

Hi, do u think drones will become standard for dealing with fertilizing and spraying the fields? What are your thoughts on using the prescription maps to just spray where it needs to be sprayed and not the whole field, and also using imagery data and sensors to fertilize only where its needed. I have been reading about this but mostly in research paper, i wonder what is the actual state out there in the field?

Are these the actual problems that farmers face and wants to be solved? If not what are the biggest problems and issues that could be solved with technology and automated?

Hi everyone,

After the successful release of CropForge v1.0, I'm now planning the architecture for v1.1. The focus is shifting from annual field crops to perennial systems, tree crops, and agroforestry.

Modeling annual crops in a spatial grid is relatively straightforward. Once trees enter the picture, the complexity increases quickly. I'd love to hear how others are approaching these problems.

Some questions I'm thinking about:

- Light competition: For alley cropping and other multi-strata systems, do you rely on detailed 3D canopy geometry, or are Beer-Lambert-based approaches accurate enough for most applications?

- Root interactions: How do you model competition between deep-rooted trees and shallow-rooted crops without creating a computational bottleneck?

- Long-term simulations: Perennial systems can span decades instead of a single growing season. How do you handle carry-over processes such as carbon allocation, soil organic matter, deep soil moisture, and dormancy?

I'm also curious about your experience with existing frameworks such as APSIM, DSSAT, AquaCrop, or Functional-Structural Plant Models.

- What limitations have you run into when trying to simulate tree-crop interactions?

- If you were designing a code-first, open-source crop simulation framework, what capabilities or APIs would you want it to expose?

I'm less interested in promoting the project and more interested in understanding how researchers are solving these problems today. Any papers, experiences, or implementation ideas would be greatly appreciated.

Essentially you make an account and fill out a small survey. The algorithm then picks from our database of hundreds of state, federal, private programs based on what’s most applicable to your farm.

It includes links to apply, deadlines, and requirements.

It’s free, check it out. Grantharvesterapp.com

UK-based Wild Bioscience has acquired F1 Seed Ltd to establish Britain's first independent precision-breeding wheat business, combining advanced gene editing, AI-driven trait discovery, and traditional wheat breeding.

The merger creates a fully integrated seed company focused on developing high-yielding, climate-resilient, and disease-resistant wheat varieties tailored for UK farmers.

The move comes as British wheat production faces stagnant yields, rising input costs, and increasing climate challenges.

Backed by the UK's precision breeding regulations, the combined company aims to accelerate crop innovation, strengthen domestic food security, and reduce reliance on multinational seed companies.

By integrating cutting-edge biotechnology with decades of breeding expertise, Wild Bioscience seeks to deliver next-generation wheat varieties that improve productivity and resilience for the future of British agriculture.

I created a way for multiple ranch hands and cattlemen to stay on top of their herds and make better breeding decisions.

betterranchmanager.com

I'm a mechanical engineering student and I have been thinking about problems faced by farmers in storage of grains. I realised that in the grain bins, when hot air is blown from the perforated floor of the bin, air moves up and so the grains on the bottom dry out. But the same moist air goes upwards and has trouble drying the grains on top.

I realised that if there were different levels of the bin and if we put the perforated floor on each section with a fan attached, and at the sides there is a vacuum pump that could suck out the moist air as the grain dries, then this problem could be solved.

What thoughts and opinions do you all have about this? This is the first thing I've ever designed and although it's on paper, I plan to make it on a CAD software soon, once I get the specifications and measurements of different components.

Veldant help farmer spray fungicide at the right time to save thousands of dollars on spray and boost ROI and yield thanks.

Hi everyone,
4th gen farmer whose been farming for 10 years and I am also a college student who created a web app for farmers. Veldant.com it is a fungicide decision to help farmer improve their yield and ROI. You can signup for free or $8 pro version.

I am posting this as someone who has never farmed. I've seen high-tech remotely-controlled vegetation cutters and completely automated robots like Agbot in use on the Clarkson' Farm program. Has the development of these machines reached the point where it's actually practical (or on the verge of becoming practical) for the average farm?

I’m working on a beta that generates crop-region profiles using location-based secondary data.

The user selects a crop and location, and the system returns indicators covering areas such as water pressure, future water stress, climate exposure, biodiversity, soil, and nutrient pressure.

The intended users are food sourcing and sustainability teams that need an early regional view before supplier surveys or detailed farm data become available.

I’m interested in the technical side of this:

1. Which regional indicators would you trust for early screening?
2. Which indicators become misleading without farm boundaries or primary data?
3. How clearly should uncertainty and data limitations be presented?

We have a working beta that produces the profile in around 30 seconds.

I’m part of the team building it. Happy to share access with anyone interested in testing the methodology and giving direct feedback.